Agroforestry practices evolve with the development of basic and advanced facilities, changes in natural and artificial factors of land use change. The study aims to examine the socioeconomic characteristics and compare satisfaction levels across forest products and vegetable farming of the agroforestry community in Khost Province. Data were collected from 662 farmers and was analyzed using univariate Analysis of Variances (ANOVA) and Multivariate Analysis of Variances (MANOVA). The results found that forest and vegetable products, including fruits, berries, herbs, mushrooms, wild animals, oils, wood, honey, okra, eggplant, carrot, cucumber, pine nuts, pepper, and timber has different impact in terms of satisfaction with basic and advanced facilities, knowledge about land use and impacts, natural and artificial factors of land use change, and positive and negative impact of land use change. The limitation of the study included an absence of exogenous factors in the model such as climate change, financial conditions, market fluctuations, regulatory system, an area in which the study is selected, research design, and current condition of endogenous factors. Overall, agroforestry practices can improve the socioeconomic development of agroforestry-dependent communities in Khost Province, Afghanistan. This study provided useful insights for policymakers and development practitioners to promote agroforestry practice adoption and improve the socioeconomic development of agroforestry-dependent communities. Future works could explore the implications of agroforestry practices on the socioeconomic development of other dependent communities in Afghanistan.

The Imbalance Cost Pass-Through (ICPT) is a flexible component of the Incentive Regulation (IBR) that empowers power producers to adjust tariffs in response to variable fuel prices, thereby enhancing the economic resilience of electricity generation. However, the cost of electricity generation is significantly influenced by the volatility of commodity prices, including coal, gas and LNG. In Malaysia, the Energy Commission has conducted biannual reviews of fuel and other generation costs. Any cost savings or increases identified during these reviews will be passed on to customers in the form of rebates or surcharges. Due to that reason, this study proposes ICPT price forecasting for the electricity market in Peninsular Malaysia. The study aims to construct an ICPT-related baseline model for the peninsular generation data by employing three forecasting methods. The forecasting performance is analysed by a Mean Absolute Percentage Error (MAPE). In findings, the ARIMA method is one of the most accurate forecasting methods for fuel prices compared to the Moving Average (MA) and LSSVM methods. The observed price differences between the ARIMA and LSSVM models for ICPT are minimal. The ICPT price for July-December 2022 and January-June 2023 is MYR 0.21/ kWh for ARIMA and MYR 0.18/kWh for LSSVM, which are close to the actual TNB’s ICPT tariff. As for the forecasting, the ICPT price is expected to drop for the next announcement. The findings of this study may contribute to a positive impact on the sustainability of the energy sector in Malaysia.

Modular steel buildings (MSBs) interlocking inter-module connections (IMCs) have piqued researchers’ interest. However, the existing literature has not yet studied the optimisation of its plate thicknesses. This paper, therefore, focuses on optimising interlocking (IMCs) plate thickness in (MSBs), leveraging previous experimental and numerical simulation methodologies. Various numerical models for four MSBs interlocking (IMCs) with plate thicknesses (4 mm, 6 mm, 10 mm, and 12 mm) were developed under compression loading conditions. The study’s novelty lay in its comprehensive parametric analysis, which evaluated the slip phenomenon in (MSBs) connections and introduced a slip prediction model validated against empirical data. Further innovative machine learning approach was utilised to predict slip values based on applied force through a random forest regression model trained using the 'Treebagger' function. Sensitivity analysis and comparisons with alternative methods were utilised to underscore the reliability and applicability of the findings. The results showed that 11.03 mm was the optimal plate thickness for interlocking (IMCs) in modular steel buildings, with up to 8.08% reduced material costs. Increasing plate thickness boosts its deformation resistance by up to 50.75%. ‘TreeBagger’ random forest for anomaly detection and machine learning improves slip prediction up to 7% at higher force levels.

Ming-style round-backed armchairs as a classic Chinese chair design are renowned for the blend of ergonomics, practicality, and elegance. Although the Chinese armchair furniture industry has made strides in sustainability, there is still a need for further improvements in material selection, manufacturing processes, and supply chain management to fully support the development of sustainable furniture. Laminated bamboo lumber as new sustainable materials are becoming a popular option for furniture designers in the era of "sustainable design". This research aims to investigate the feasibility and application of laminated bamboo lumber in the design of Chinese armchair furniture and proposes innovative ideas for optimizing the armchair's design. First, an empirical study was conducted to comprehensively understand the classification of Ming-style round-backed armchairs’ structure to develop a 3D model. Secondly, an experimental research method was then employed to explore the parameters of laminated bamboo lumber for future studies. Additionally, a validation experiment was conducted to compare real-world scenarios with simulations using finite element analysis in Ansys. Finally, finite element analysis was used to test the feasibility and application of laminated bamboo lumber in furniture design, focusing on the material’s mechanical properties. Results indicated that laminated bamboo lumber has excellent mechanical properties as furniture design materials, subsequently, using the optimized results, the use of 0.6319 kg of steel was successfully reduced by 23.68% to ensure the armchair’s stability. This provides a reference for the future compter-assist and standardized innovative design of Chinese armchair. By incorporating compter-assist design and lightweight optimization, it is possible to save materials and make more efficient use of resources, thereby contributing to sustainable development goals in the field of furniture design.

: Leveraging the sustainability of the power system market, researchers have developed various ML models for forecasting electricity demand. The LSSVM is well suited to handle complex non-linear power load series. However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a hybrid model based on the LSSVM optimized by the IBFOA for forecasting the daily electricity load in Peninsular Malaysia. The IBFOA for parameter optimization of LSSVM is introduced. The IBFOA based on the sine cosine equation is proposed to adjust the constant step size in the BFOA, which creates an imbalance between the exploration and exploitation during optimization. Finally, the load forecasting model based on LSSVM-IBFOA is constructed using MAPE as the objective function. Comparative analysis demonstrates the model, achieving the highest R2 (0.9880) and significantly reducing error metrics (MAPE, MAE, RMSE, MSE, NRMSE) compared to the baseline LSSVM (average reduction of 27.72% to 47.72%). Additionally, IBFOA exhibits faster convergence and higher accuracy compared to BFOA, highlighting the accuracy of LSSVM-IBFOA for short-term load forecasting.

Intellecta dataset emerges as an innovative synthetic dataset, engineered to enhance the cognitive processing capabilities of contemporary language models. With a composition of 11.53 billion tokens, integrating 8.01 billion tokens of synthetic data with 3.52 billion tokens of rich textbook data, Intellecta is crafted to foster advanced reasoning and comprehensive educational narrative generation. Leveraging the Mixtral-8x7B-Instruct-v0.1 model, the dataset facilitates the generation of complex thought processes and detailed, textbook-style explanations, thus enabling language models to engage in both critical thinking and profound educational discourse. This hybrid dataset stands as a testament to the potential of synthetic data in pushing the boundaries of AI, offering a repository that is not only vast and varied but also refined to align with ethical standards and intellectual rigor.

Promoting organic foods production and consumption contributes to accomplishing United Nations sustainable development goals. Social commerce provides a promising opportunity to develop the organic food industry. However, there is limited knowledge regarding customer behaviors in relation to purchasing organic foods via social commerce platforms. Therefore, this study expanded upon the unified theory of acceptance and use of technology (UTAUT-2) to develop a comprehensive model that explains how customers' social commerce trust and behavioral intentions to purchase organic foods using Instagram social commerce affect their purchasing behaviors. The research model was analyzed by employing partial least squares structural equation modeling (PLS-SEM) for the data collected from a quantitative survey of 410 customers who used Instagram to purchase organic foods in Iran. The results revealed that facilitated purchasing conditions, hedonic motivations, social influence, rating and reviews, and influencers’ endorsements increase customers' purchase intentions. Moreover, Instagram’s recommendations and referrals, influencers’ endorsements, as well as social influence boost customers' trust in the social commerce platform. Eventually, it was determined that influencers’ endorsements, social commerce trust, and purchase intention determine a customer’s organic foods purchasing behaviors. This research provides valuable insights for organic food marketers to optimize their social commerce strategies.

The growing global population and limitations in fish catch production have led to a surge in the demand for aquaculture. Contaminants of emerging concern (CEC) are frequently being detected at low levels in surface water. These CECs, which include previously unidentified or unregulated pollutants, pose potential risks to health and the environment, though their impacts are not yet fully understood. Extensive research studies have been proposed and undertaken to address the issue of aquaculture wastewater, aiming to minimize its impact and implement effective treatment methods. This review provides an analysis of various technologies used for treating aquaculture wastewater using advanced oxidation processes (AOPs) focusing on photocatalysis and ozonation. It examines their advantages and disadvantages, as well as their respective treatment efficacies and discusses their potential applications in sustainable aquaculture practices complying with the Sustainable Development Goals of 1,2 and 6 and the Environmental Social and Governance (ESG) framework.

The sustainability of ecotourism is the backbone of tourism development of a country. Ecotourism can contribute to both conservation and development in which involves dynamic relationship between tourism, biodiversity and communities, facilitate by great management. The purpose of this study is to analyze the dimensions of the socio-economic and environmental impacts of ecotourism in communities surrounding the Tasik Kenyir in Terengganu, Malaysia. This study provides a framework for the development and evaluation of ecotourism. The framework will determine if the relationships between indicators are positively correlated which will result in positive contribution to the other by using System Dynamic. Socio-cultural and economic data will be collected through interviews and group discussions in selected communities in Tasik Kenyir. Data on wildlife will be extracted from secondary data from Kenyir Research Institute, Universiti Malaysia Terengganu. The data analysis will explore the socio-cultural and economic differences between and within different communities due to ecotourism development, the contribution of ecotourism to conservation activities, local support for conservation and ecotourism as well as the influence of tourist activities on the distribution of wildlife species in Tasik Kenyir. This study aims to contribute toward understanding the natural resource community-ecotourism inter-relationship and help to bridge the knowledge gap that hinders biodiversity conservation initiatives. The findings will be used as a base for further development of ecotourism and will recommend alternative management options where necessary for the study area.

Residents’ perceptions on ecosystem services (ESs) provided by urban green spaces (UGSs) are vital for developing sustainable cities. However, there has been limited research on this issue in Malaysia. The aim of this paper is to assess Malaysians’ perceptions on ESs provided UGSs and how their perceptions are influenced by different socio-demographic factors. We used a structured online questionnaire and obtained 645 responses on 16 ESs from regulatory, cultural, and supporting ES categories. Descriptive statistics and binary logistic regressions were used for data analysis. In general, city dwellers have high positive perceptions on ESs provided by UGSs. Their perceptions for global climate regulation, noise buffering, pest regulation, spiritual, and research and education services would likely to significantly increase as they grow older. Households with moderate income have significantly greater perceptions of microclimate regulation, air filtration and aesthetic services. Having non-tertiary level education would significantly lower their perceptions of global climate and microclimate regulation, spiritual, aesthetics, and recreational services. Tertiary educated residents with non-environmental degrees also showed similar associations. Infrequent visits to UGSs would likely to significantly reduce the perception of global climate regulation, noise buffering, runoff reduction, erosion control, spiritual, and aesthetics services. People living far (>5km) from the UGSs also have significantly lower perceptions of microclimate regulation, air filtration services. Suggestions are made to incorporate ESs related content in pre-university curriculum and establishing small parks in neighborhoods to improve knowledge and uses of UGSs. These findings would assist urban planners designing environmentally sound urban policies and thereby improving human wellbeing in the cities.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

The COVID-19 pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has exposed the vulnerabilities and unpreparedness of the global healthcare system in dealing with emerging zoonoses. In the past two decades, coronaviruses (CoV) have been responsible for three major viral outbreaks, and the likelihood of future outbreaks caused by these viruses is high and nearly inevitable. Therefore, effective prophylactic universal vaccines targeting multiple circulating and emerging coronavirus strains are warranted. This study utilized an immunoinformatic approach to identify evolutionarily conserved CD4+ (HTL) and CD8+ (CTL) T cells, and B-cell epitopes in the coronaviral spike (S) glycoprotein. A total of 132 epitopes were identified, with the majority of them found conserved in the bat CoV, pangolins CoV, endemic coronaviruses, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). Their peptide sequences were then aligned and assembled to identify the overlapping regions. Eventually, two major peptide assemblies were derived based on their promising immune-stimulating properties. In this light, they can serve as lead candidates for universal coronavirus vaccine development, particularly in the search for pan-coronavirus multi-epitope universal vaccines that can confer protection against current and novel coronaviruses.

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence and are insensitive to wind direction which has a huge impact on the cost since the yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a results tremendous efforts are exerted to improve its efficiency which mainly focus on two methods regardless of whether the study is a CFD simulation or a field test or lab test experiment. An active approach which involves the modification of the rotor itself such as the blade design, angle, trailing and leading edges, inner blades, chord thickness, contra-rotating rotor, etc. While the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting a guiding vane such as a diffuser or other shapes at the upwind position of the rotor. Among all techniques undertaken, the CRWT rotor technique seems to be the most effective with an output even comparable to that of Horizontal Axis Wind Turbines (HAWT), while the Savonius rotor received more attention compared to other designs of VAWTs. Apart from technological issues, it was also suggested that geographical issues such as proper site siting of the wind turbine rotor at a particular location where a uniform flow could be guaranteed is of paramount importance to ensure an effective conversion capacity of wind turbines.

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Large language models (LLMs) are known for their exceptional performance across a range of natural language processing tasks, but their deployment comes at a high computational and financial cost. On the other hand, smaller language models (SLMs), which can be deployed on lower-cost edge devices, struggle to match the performance of their larger counterparts. This paper presents a novel hybrid inference approach that leverages the strengths of both model types while minimizing reliance on costly cloud-based LLMs. Unlike existing methods that route entire queries to either an SLM or a cloud LLM, our approach introduces a reward-based mechanism to dynamically determine the involvement of the cloud LLM during token generation. Specifically, each token predicted by the SLM is evaluated against a reward score, and only when this score falls below a certain threshold is the cloud LLM consulted for assistance in the next token prediction. This method not only reduces the traffic to the cloud LLM, thereby lowering costs, but also allows for flexible control over response quality depending on the reward score threshold. Experimental results demonstrate that our approach significantly reduces cloud LLM usage with minimal impact on overall response quality, offering a cost-effective solution for deploying high-performance language models.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

Long COVID, also referred to as post-COVID-19 condition, describes the lingering after-effects of COVID-19 infection. This complex syndrome encompasses a range of symptoms affecting physical well-being, cognitive function, and mental health. The widespread impact of long COVID extends beyond individual sufferers, placing significant strain on healthcare systems and causing far-reaching socioeconomic consequences. The scale of this multifaceted health crisis is unparalleled in recent history, affecting millions globally and challenging our understanding of post-viral conditions. This study aimed to explore the possibility of targeting G protein-coupled receptors (GPCRs) signaling pathway-related genes as therapeutics for long COVID using computational analysis. Targeting GPCRs and their signaling pathways holds significant promise for long COVID therapeutics, as these receptors are involved in crucial physiological processes including immune regulation, inflammation control, and neurotransmission. All of these are implicated in the diverse and persistent symptoms of long COVID, potentially offering a versatile approach to addressing multiple aspects of the condition simultaneously. This study identified 21 genes associated with GPCRs for further exploration as potential targets. Notably, GPCR genes such as HRAS, KRAS, GNAQ, and GNA11 were determined to be possible therapeutic targets for the pathophysiological mechanisms of long COVID. FDA-approved drugs targeting these genes were identified, including Binimetinib, Cabozantinib, Selumetinib, Panitumumab, Cetuximab, Adagrasib, Tipifarnib, and Sotorasib. Additionally, Naltrexone and Tipifarnib have emerged as potential new treatment options for long COVID. SARS-CoV-2 may hijack GPCR signaling pathways to dysregulate lung ion and fluid transport, contributing to the pathophysiology of pulmonary edema in patients with COVID-19. Further research is required to translate the findings into the development of therapeutics and to investigate the relationship between viral infection and GPCR signalling.

This cross-sectional study evaluated the validity of three alternative methods compared to the gold standard 24-h urine collection for estimating dietary sodium intake, a modifiable risk factor for hypertension, among middle-aged and older adults with elevated blood pressure. These included spot urine collection (using Kawasaki, Tanaka, and INTERSALT equations), 24-h dietary recall, and food frequency questionnaire responses, compared against 24-h urine collection in a subset of 65 participants (aged 50–75 years, 58.5 % women, 61.6 % hypertensive) from the DePEC-Nutrition trial. The validity of the methods was assessed using bias, Spearman correlation coefficient (SCC), intraclass correlation coefficient (ICC), and Bland-Altman analysis. Among the alternative methods, spot urine collection using the Kawasaki equation showed the strongest correlation (SCC 0.238; ICC 0.119, 95 % CI -0.079 to 0.323) but it exhibited a significant bias (1414 mg/day, p-value < 0.001) relative to 24-h urine collection. Conversely, dietary surveys had a smaller bias but wider limits of agreement. These findings underscore the complexities of accurately estimating dietary sodium intake using spot urine collection or dietary surveys in this specific population, suggesting that a combination or refinement of existing methodologies might improve accuracy. Further research with larger samples is necessary to develop more reliable methods for assessing sodium intake in this high-risk group.

Comprehending the replication kinetics of SARS-CoV-2 variants helps explain why certain var-iants spread more easily and are more contagious, and pose significant health menaces to the global populations. The replication kinetics of Malaysian isolates of the Alpha, Beta, Delta, and Omicron variants were studied in the Vero E6 cell line. Their replication kinetics were deter-mined using the plaque assay, quantitative real-time PCR (qRT-PCR), and viral growth curve. The Beta variant exhibited the highest replication rate at 24 hours post-infection (h.p.i), as evi-denced by the highest viral titers and lowest viral RNA multiplication threshold. The plaque phenotypes also varied among the variants, in which the Beta and Omicron variants formed the largest and smallest plaques, respectively. All studied variants showed strong cytopathic effects after 48 h.p.i. The whole-genome sequencing highlighted cell-culture adaptation, where the Beta, Delta and Omicron variants acquired mutations at the multibasic cleavage site after three cycles of passaging. The findings suggest a strong link between the replication rates and their respec-tive transmissibility and pathogenicity. This is essential in predicting the impacts of the upcom-ing variants on the local and global populations and is useful in designing preventive measures to curb the virus outbreaks.

Differences in metabolic regulation among obesity phenotypes, specifically metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) women, may lead to varied responses to interventions, which could be elucidated through metabolomics. Therefore, this study aims to investigate the differences in metabolite profiles between MHO and MUO women and the changes following a lifestyle intervention. Serum from 36 MHO and 34 MUO women, who participated in a lifestyle intervention for weight loss were analyzed using an untargeted proton nuclear magnetic resonance spectroscopy (1H NMR) at baseline and 6 months post-intervention. Anthropometric, clinical and dietary intake parameters were assessed at both time points. Both groups showed differential metabolites profile at baseline and sixth month. Seven metabolites including trimethylamine-N-oxide (TMAO), arginine, ribose, aspartate, carnitine, choline and tyrosine significantly changed between group post-intervention, in which all showed a decreasing pattern in MHO. Significant reduction in body weight and BMI in the MUO correlated with changes in carnitine and tyrosine levels. In conclusion, metabolite profiles differed significantly between MHO and MUO women before and after a lifestyle intervention. Changes in carnitine and tyrosine levels in MUO correlated with weight loss, suggesting potential targets for therapeutic intervention.

In recent years, large language models have demonstrated remarkable performance across various natural language processing (NLP) tasks. However, deploying these models for real-world applications often requires efficient inference solutions to handle the computational demands. In this paper, we explore the utilization of CPUs for accelerating the inference of large language models. Specifically, we introduce a parallelized approach to enhance throughput by 1) Exploiting the parallel processing capabilities of modern CPU architectures, 2) Batching the inference request. Our evaluation shows the accelerated inference engine gives an 18-22x improvement in the generated token per sec. The improvement is more with longer sequence and larger models. In addition to this, we can also run multiple workers in the same machine with NUMA node isolation to further improvement in tokens/s. Table 2, we have received 4x additional improvement with 4 workers. This would also make Gen-AI based products and companies’ environment friendly, our estimates shows that CPU usage for Inference could reduce the power consumption of LLMs by 48.9% (1252 W for A100 with AMD EPYC 7V13 vs 613 W for Intel® Xeon® Gold 6538N) while providing production ready throughput & latency.

Phenolic compounds, present in plants, provide substantial health advantages, such as antioxidant and anti-inflammatory properties, which enhance cardiovascular and cognitive well-being. Australia is enriched with a wide range of plants with phytopharmacological potential, which needs to be fully elucidated. In this context, we analyzed leaves of aniseed myrtle (Syzygium anisatum), lemon myrtle (Backhousia citriodora), and cinnamon myrtle (Backhousia myrtifolia) for their complex phytochemical profile and antioxidant potential. LC-ESI-QTOF-MS/MS was applied for screening and characterizing these Australian myrtles’ phenolic compounds and the structure-function relation of phenolic compounds. This study identified 145 and quantified/semi-quantified 27 phenolic compounds in these Australian myrtles. Furthermore, phenolic contents (total phenolic content (TPC), total condensed tannins (TCT), and total flavonoids (TFC)) and antioxidant potential of phenolic extracts from the leaves of Australian myrtles were quantified. Aniseed myrtle was quantified with the highest TPC (52.49 ± 3.55 mg GAE/g) and total antioxidant potential than other selected myrtles. Catechin, epicatechin, isovitexin, cinnamic acid, and quercetin were quantified as Australian myrtles' most abundant phenolic compounds. Moreover, chemometric analysis further validated the results. This study provides a new insight into the novel potent bioactive phenolic compounds from Australian myrtles that could be potentially useful for functional, nutraceutical, and therapeutic applications.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

Herbal Coffee is getting more popular due to its unique flavor and higher concentration of bioactive compounds, mainly polyphenols. Rosemary is a unique herb with potent antioxidant properties. A green technique called ultrasound aids in releasing bioactive substances from the plant cell wall. In this context, ultrasound-assisted herbal coffee prepared and their anti-diabetic, anti-Alzheimer, and antioxidant activities were measured while the LC/MS was used to determine the bioactive components from the herbal coffee infusion. A total of 95 secondary metabolites were putatively reported, including alkaloids, phenolic acids, and flavonoids, which we identified in the herbal coffee infusion. The total phenolic content (61.5 ± 5.1 mg GAE/g), total flavonoid content (19.3 ± 0.9 mg QE/g), and total condensed tannin (7.6 ± 0.7 mg CE/g) of herbal coffee infusion were observed to be highest of the two remaining samples. The herbal coffee extracts were used to determine all samples' antioxidant, anti-diabetic, and anti-Alzheimer activities. Using LC-MS/MS, we semi-quantified 19 phenolic metabolites. The results show numerous bioactive components in herbal coffee infusion with more potent antioxidant, antidiabetic, and anti-Alzheimer potential. Moreover, more studies must be conducted to confirm how the metabolomic profile of herbal coffee affects its flavor profile.

The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-to-everything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such sort of attacks, if and when materializes, jeopardizes the entire IoV network, thereby putting the human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves 9 salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward / punishment, and context, which play a considerable role for ascertaining the trust of a vehicle within an IoV network.

Childhood nutrition is a cornerstone of long-term health, yet many children exhibit reluctance to consume healthy foods such as vegetables. This aversion can be influenced by various factors, including food neophobia and the sensory and visual appeal of the foods presented. Understanding how visual cues affect children's willingness behaviors can provide insights into effective strategies to enhance their dietary habits. This study aims to investigate the liking and emotional responses on the relationships between intrinsic and extrinsic cues and children's willingness to eat and to ask parents to buy. To understand how these factors influence children with food neophobia food-related behaviors and to identify effective strategies to promote healthier eating habits. A sample size consisting of 420 children recruited was needed in this cross-sectional study. A validated and reliable self-administered questionnaire was employed. Independent t-test and ANOVA were used to test the differences between gender and food neophobia means. Spearman correlations were used for correlation analysis. Hierarchical regression analyses were conducted to explore the relationships among intrinsic cues, extrinsic cues, and the mediating effect of liking and emotional responses. Attributes such as plate color and shape significantly influence children's food-related behaviors and their emotions. Liking and emotional responses significantly mediates the relationship between intrinsic/extrinsic cues and willingness. Positive visual cues experiences are crucial for increasing children's inclination to purchase and consume. Positive emotional responses enhance acceptance and purchase. There are significant differences between boys and girls. Boys prefer blue and triangular plates, while girls prefer pink plates and generate more positive emotions. Children with food neophobia will initially experience a disorder, but its negative effects can be mitigated by increasing sensory appeal and emotional engagement. By employing strategies designed to enhance visual cues and liking and emotions, children’s willingness to choose healthy eating habits can be effectively increased.

The detection of Fasciola eggs in ruminant fecal samples typically occurs around 15 weeks post-infection during patent infections. The recent introduction of coproantigen ELISA (cELISA) diagnostics, which capture antigenic enzymes in fecal material, holds promise for monitoring Fasciola fecal egg count (FFEC) to implement control programs, particularly targeted treatments. This study compared two study groups, those with positive FFEC (FFEC+ve) and negative FFEC (FFEC-ve), to assess the sensitivity of Flukefinder sedimentation and a cELISA kit. This study reports that the coproantigen ELISA detection limit was 4.5 eggs per gram (epg) for a 100% positivity rate. Additionally, a moderate, statistically significant positive correlation (r²=0.716, p-value < 0.01) and an odds ratio of 1.96 (p-value < 0.01) were observed between FFEC and Fasciola coproantigen from cELISA. This implies that for every single unit increase in FFEC, there is a 96% likelihood of obtaining a higher optical density (OD) reading from the cELISA test. The results suggest that cELISA can complement fecal sedimentation tests, serving as a valuable tool for detecting cattle with high FFEC. This capability facilitates targeted treatment strategies, thereby aiding in the control and prevention of the spread of fasciolosis within the studied area.

Abstract: Objective: The aim of the study was to identify dietary patterns and its association with socio-economic, dietary and lifestyle practices among adolescents in Malaysia. Methods: A validated food frequency questionnaire was used to assess dietary patterns. Results: Multivariate analyses show that age and physical activity (PA) levels were emerged as positive determinants of healthy-based food pattern in Malay (All, p<0.001), whereas higher consumption of eating-out from home (EatOut) and fast food (All, p<0.05) were negative determinants. High weekly breakfast skipping (p<0.001) and EatOut (p<0.01) were positively associated with a western-based pattern, whereas age (p<0.001) and household income (p<0.05) were negative determinants. Higher frequency of daily snacking (p<0.05) was emerged as positive determinant of local-based food pattern. For Chinese adolescents, age (p<0.001), PA levels (p<0.001) and maternal education level (p<0.05) emerged as positive determinants for the healthy-based pattern, whereas high EatOut and fast food intakes (All, p<0.01) were negative determinants. Higher weekly consumption of EatOut (p<0.01), fast food (p<0.05) and carbonated beverages (p<0.05), and daily snacking practice (p<0.01) were positively associated with higher western-based food pattern, whereas age (p<0.01) was inversely associated. Conclusion: These findings suggest that unhealthy dietary and lifestyle practices could increase the risk of adherence to unhealthy western-based food pattern that is high in fat, sugar and salt contents, and consequently increase the risk of developing obesity and metabolic-related disorders during these critical years of growth.

Long COVID, characterized by persistent symptoms lasting from weeks to several months following initial infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), significantly impacts individuals' quality of life and poses a potential long-term burden on global healthcare systems. Clinical manifestations of Long COVID are diverse, affecting multiple systems including respiratory, cardiovascular, neurological, and gastrointestinal. While the precise mechanisms underlying Long COVID remain unclear, emerging evidence suggests involvement of various bodily pathways. This study employs bioinformatics tools to investigate the mechanisms of Long COVID and identify potential drug targets associated with key pathways, including inflammation, cytokines, immune response, coagulation, mitochondrial function, oxidative stress, and autonomic dysfunction. Tools such as the National Center for Biotechnology Information (NCBI) database, PubChem, UniProt, and iGEMDOCK were utilized for pathway analysis and molecular docking. The analysis aimed to identify drug molecules that may interact with target proteins to regulate or inhibit pathway activity, yielding several potential drug candidates for further investigation.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

In today's interconnected global business landscape, companies face numerous risks, particularly from their supply chains. Supplier disruptions can cause financial damages, inefficiencies, and reduced competitive edge, highlighting the need for robust supplier risk management. This paper scrutinizes recent studies on supplier risk management spanning 2020 to 2023. This review examines supplier risk management, focusing on supplier evaluation, payment terms, contract duration, and buyer-supplier collaboration as critical factors influencing risk mitigation and control in the procurement of goods and services. Through a systematic literature review, the study identifies the multifaceted nature of supplier risks, including production delays, quality issues, and financial challenges. It underscores the importance of proactive risk identification, comprehensive supplier evaluation, strategic payment terms, appropriate contract durations, and robust buyer-supplier collaboration. Despite the benefits, challenges remain, such as understanding regulatory impacts and ensuring methodological consistency. This review contributes to the discourse on supplier risk management, offering insights for future research and practical applications to enhance resilience and operational efficiency in global supply chains. Based on the findings, future studies should concentrate on formulating holistic supplier risks management approaches that nurture buyer-supplier collaboration and harness innovative technologies to enhance risk management practices.

Understory plants are important components of forest ecosystem productivity and diversity. Compared to biomass models of overstory canopy trees, few are available for understory saplings and shrubs and therefore their roles in estimation of forest carbon pools are often ignored. In this study, we harvested 24 understory species including 4 saplings, 9 tree-like shrubs and 11 typical shrubs in coniferous and broadleaved mixed forest in northeastern China and developed the best fit allometric equations of above- and below-ground and total biomass by species-specific or multispecies using morphological measurements of basal diameter, height and crown area as independent variables. The result showed that single basal diameter, height or crown area had good explanatory power for both species-specific and multispecies (p<0.001). The best-fit models included only basal diameter in sapling and tree-like shrubs, and combinations of crown area, height, and basal diameter in typical shrubs. The logarithmic model was most desired among the 4 model forms of linear, quadratic, multiple linear and logarithmic, for species-specific and multispecies. The models we developed should help the estimation of forest ecosystem carbon stocks, especially for belowground component, and provide tools for quantification of individual species biomass of understory plants.

This study assessed the performance of low-dose CT lung scans across various acquisition parameters and examined the impact of iterative reconstruction (IR) algorithms on image quality for lung cancer screening. The performance of multi-slice CT scanners was assessed by using a Catphan 600 phantom, specifically within the CTP404 test module that contains materials like Teflon, Delrin, Acrylic, Polystyrene, LDPE, PMP, Air, and water. Three protocols were selected and categorized into standard, low dose, and ultra-low dose. The standard protocol featured a tube voltage of 100 kVp for single-detector CT, a pitch of 0.75, detector collimation of 0.60 mm, and a gantry rotation time of 0.33 seconds, with 5 mm slice thickness. Images were reconstructed using standard kernels like B80f and 170f, combined with either FBP or various IR algorithms. Findings indicated that the noise power spectrum (NPS) peak value (HU2mm2) increased with higher IR levels, with FBP showing the highest peak. Additionally, NPS spatial frequency diminished as IR levels rose. Optimizing contrast and spatial resolution for both background and regions of interest involved adjusting the target transfer function (TTF) and contrast-to-noise ratio (CNR), crucial for protocol optimization. Proper adjustment of IR levels is vital, as higher levels can alter image texture and affect NPS spatial frequency. The results of this study showed that the use of IR algorithms in low-dose CT lung scans significantly improved image quality, particularly in terms of noise reduction and spatial resolution. However, the choice of acquisition parameters also played a crucial

Porphyromonas gingivalis is the major pathogenic bacteria found in the subgingival plaque of patients with periodontitis, leading to neuroinflammation. The bacteria destroy periodontal tissue through its virulence factors which are retained in the bacteria’s outer membrane vesicles (OMV). The purpose of this study was to determine the real time effect of intraperitoneal in-jection of P. gingivalis OMV on the production and expression of inflammatory markers as well as histopathological changes in the central nervous system (CNS) of adult zebrafish. Fol-lowing the LD50 (21 µg of OMV), the zebrafish were injected intraperitoneally with 18 µg of OMV and control group with normal saline at 7 different time points. Brains of experimental zebrafish were dissected at desired time points for colorimetric assays, ELISA and histology. This study discovered that nitric oxide and PGE2 were significantly increased at 45 minutes while IL-1β and IL-6 were expressed at subsequent 12- and 24-hours. respectively. Histopatho-logical changes such as blood coagulation, astrocytosis, oedema, spongiosis, and necrosis were also observed between 6- and 24-hours. The two apoptotic enzymes, caspases 3 and 9 were not expressed at any time point. In summary, the OMV induced neuroinflammatory responses and histopathological changes in adult zebrafish were time point dependent

This study aims to unravel the paradox of perceptions and knowledge of the flood victims towards the causes of the disaster in both internal and external context. Internal context comprises of a comparison of perceptions and knowledge based on individual characteristics (age, gender, education and income). Whereas, the external context includes the factors of the awareness of the victims towards the amount of rainfall, the impact of land use changes as well as the negligence of the responsible parties. The main objective of this study is to determine the differences of perception and knowledge of December 2014 flood victims in Kelantan towards the factors that lead to the flood. This disaster had resulted in huge amount of money loss as well as traumatize the victims in which can be felt to this day. Since that incident, there were various points of view and different perceptions in finding the cause of the disaster occurred. Besides that, the study found that the level of perception and knowledge as to the cause of the disaster is different in the internal context (individual characteristics). This difference has a significant influence on the awareness of the causes of the floods that occurred in the external context. Significant relationships at the level of p <0.05 has existed between perception and knowledge of the causes of the disaster victims affected by environmental changes in the last 10 years. This indicates that although the victim is aware of the physical environment changes happening around them, but all that is seen as not a major contributing factor to the cause of the floods in Kelantan in 2014.

Esophageal cancer (EC) is one of the most common malignant tumors worldwide, and its two major types, esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) present a severe global public health problem with an increasing incidence and mortality. Established risk factors include smoking, alcohol consumption, and dietary habits, but recent research highlights the substantial role of oral microbiota in EC pathogenesis. This review explores the intricate relationship between microbiome and esophageal carcinogenesis, focusing on eight significant mechanisms: chronic inflammation, microbial dysbiosis, production of carcinogenic metabolites, direct interaction with epithelial cells, epigenetic modifications, interaction with gastroesophageal reflux disease (GERD), metabolic changes, and angiogenesis. Certain harmful bacteria, such as Porphyromonas gingivalis and Fusobacterium nucleatum, are specifically implicated in sustaining irritation and tumor progression through pathways including NF-κB and NLRP3 inflammasome. Additionally, the review explores how microbial byproducts, including short-chain fatty acids (SCFAs) and reactive oxygen species (ROS), contribute to DNA harm and disease advancement. Furthermore, the impact of reflux on microbiota composition and its role in esophageal carcinogenesis is evaluated. By combining epidemiological data with mechanistic understanding, this review underscores the potential to target microbiota-immune system interplay for novel therapeutic and diagnostic strategies to prevent and treat esophageal cancer.

Rhodotorula mucilaginosa fungaemia is rare and highly resistance to antifungal therapy. We herein report a case involving a 31-year-old male admitted after a high-velocity road traffic accident. He sustained a grade IV liver injury with right hepatic vein thrombosis, necessitated an urgent laparotomy. Post-operatively, repeated imaging of the abdomen revealed presence of biloma. Percutaneous subdiaphragmatic drainage was done but appeared ineffective, prompting second surgery for a urgent hemi-hepatectomy. Patient then was nursed in the intensive care unit (ICU) however during his stay in the ICU he became more sepsis evident by worsening ventilatory support and rise in septic parameters from the biochemistry parameters. Despite on intravenous piperacillin-tazobactam and fluconazole, his septic parameters did not improve and a full septic workup was done and was found to be positive for Rhodotorula mucilaginosa from the blood cultures. After discussion with the infectious disease physicians and clinical microbiologist, it was decided to initiate a course of intravenous meropenem and amphotericin B based on minimum inhibitory concentration (MIC) values, considering the patient's extended ICU stay and catheter use. Eventually, successful weaning off mechanical ventilation was discharge from ICU care. This case underscores the necessity of individualized approaches, combining timely imaging, appropriate drainage techniques, and tailored treatments to optimize outcomes for such intricate post-traumatic complications.

Oedaleus decorus asiaticus, Calliptamus abbreviatus, Angaracris rhodopa, and Myrmeleotettix palpalis are the main grasshoppers that harm the natural grassland in the Hexi Corridor. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers habitats and to assess their distribution under current and future climate change conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, 61 occurrences of O. decorus asiaticus, 68 occurrences of A. rhodopa, 58 occurrences of C. abbreviatus, and 92 occurrences of M. palpalis were recorded by GPS, and the distribution of suitable habitats for O. decorus asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis were predicted under current and future climatic scenarios using a MaxEnt model. The average AUC and TSS values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a potential distribution area of 1.44×104, 1.43×104, 1.29×104, and 2.12×104 km2, accounting for 15.3, 15.2, 13.7, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the east-central part of Zhangye City, the western part of Wuwei City, and the western and southern part of Jinchang City, with areas of 0.35×104, 0.29×104, and 0.20×104 km2, accounting for 3.7, 3, and 2.2% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32×104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of O. asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis was predicted to decrease.

Laser Powder Bed Fusion (L-PBF)-based manufacturing is a growing area of research, with a particular focus on evaluating constraints in printed products. This research emphasises the importance of considering various factors—including mechanical properties and support structures—that influence the final product during the design phase. Specifically, the design of microchannel heat exchangers is highlighted, where all constraints are critical. This article will present a method for analysing channel pressure limitations and report findings about mechanical properties loss from examining tube porosity. This includes a summary of results and the establishment of an experimental device system.

This review paper aims to understand the current processing plant maintenance systems and further identify on-stream phased array corrosion mapping (PACM) to reduce turnaround maintenance (TAM) activity during plant operations. Reducing the TAM duration and extending the TAM interval are common goals of most researchers. Thus, a detailed review was performed to understand the maintenance systems and the problems faced. Furthermore, a review of the current PACM application and the possibility of applying it during on-stream inspection was also per-formed. PACM has better detectability for localized corrosion, and the results can be obtained for a range of thicknesses, which is the main advantage of this method. The challenge is to apply it to a surface with high temperatures, owing to the greater probe contact and the limitation of ultrasonic properties. This literature review provides a more precise direction for future research to evaluate PACM on piping that can be utilized in inspection during plant operation at elevated temperatures. Detecting and monitoring corrosion growth without shutdown.

To meet the dual-carbon objective, China's economy needs to move from a carbon-intensive to a green economy. Green technology innovation and renewable energy development are key to promoting green economic growth. The study uses 2010–2022 provincial panel data from 30 Chinese provinces. The super-efficient SBM model measures the province's green economic growth index. A panel fixed-effects model is used to experimentally evaluate how green technology innovation and renewable energy development affect green economic growth. Green financing moderates and a panel threshold model tests the threshold effect of renewable energy development on green economic growth. The results demonstrate that (1) China's green economic growth is rising and has a "U" shape. (2) all selected variables significantly impact green economic growth. However, population density, government intervention, and industrial structure are inversely associated with GEG. Green economic growth is significantly boosted by the moderate role of green finance in the development of renewable energy and green technological innovation. (3) Renewable energy development has a single threshold non-linear effect on green economic growth, depending on its development level and green technological innovation. Considering China's current condition and research findings, this study examines the green energy transition to promote green economic growth and high-quality economic development. Meanwhile, puts forward some important policy recommendations.

We monitored the water quality and hydrological conditions of a horizontal subsurface constructed wetland (HSSF-CW) in Beijing, China, for 2 years. We simulated the area rate constant and the temperature coefficient with the first-order kinetic model. We examined the relationships between the nitrogen (N) removal rate, N load, seasonal variations in the N removal rate, and environmental factors, such as the area rate constant, temperature, and dissolved oxygen (DO). The effluent ammonia (NH₄⁺-N) and nitrate (NO₃⁻-N) concentrations were significantly lower than the influent concentrations (p<0.01, n=38). The NO₃⁻-N load was significantly correlated with the removal rate (R²=0.9566, p<0.01), but the NH^₄+-N load was not correlated with the removal rate (R²=0.0187, p>0.01). The area rate constants of NO₃⁻-N and NH₄⁺-N at 20 °C were 27.01±26.49 and 16.63±10.58 m∙yr⁻¹, respectively. The temperature coefficients for NO₃⁻-N and NH₄⁺-N were estimated at 1.0042 and 0.9604, respectively. The area rate constants for NO₃⁻-N and NH₄⁺-N were not correlated with temperature (p>0.01). The NO₃⁻-N area rate constant was correlated with the corresponding load (R²=0.9625, p<0.01). The NH₄⁺-N area rate was correlated with DO (R²=0.6922, p<0.01), suggesting that the factors that influenced the N removal rate in this wetland met Liebig's law of the minimum.

Excess nitrogen in agricultural drainage poses a serious threat to the water quality safety of the Yellow River basin. Utilizing aquatic plants to modify the rhizosphere microbial community structure and facilitate nitrogen transformation is a crucial strategy for mitigating regional water eutrophication. Our results revealed that the denitrification rate (DR), dissimilatory nitrate reduction to ammonium rate (DNRAR) and nitrogen fixation rate (NFR) of rhizosphere sediments exhibited a significant increase in artificially cultivated ditch. Compared with those in natural ditches, the richness of the bacterial community and the relative abundances of Bacteroidota, Verrucomicrobiota, Firmicutes, Anaeromyxobacter and Geobacter, which are involved mainly in the nitrogen cycle, in the rhizosphere sediments of artificially cultivated ditch were significantly greater due to improvements in environmental conditions. In artificially cultivated ditch, the dominant functional genes affecting DRNARs in the rhizosphere sediments of P. australis were nrfC and nrfA, while DRs were driven mainly by norB and napA, which were influenced by the nitrogen and carbon levels; and the dominant functional genes affecting NFRs in the rhizosphere sediments of T. orientalis were nifD, nifK and nifH. Our results provide a scientific basis for the use of aquatic plants for mitigating excess nitrogen levels in agricultural drainage.

As computer networks develop in size and complexity, the need for equipment that can characterize, inspect, monitor, and summarize the features of a transmission in real time grows. Many transmission and packet inspection theories are required to examine network traffic. Unfortunately, loss the track or traceability of one traffic scenarios against others over real-time network. Deep packet inspection (DPI) approaches can be used to alleviate the problem but still face flexibility constraints in the sense that it will be difficult to keep track of prior occurrences. There have been significant theoretical improvements in packet inspection, but the problem of event tracking flexibility remains unsolved. A novel approach for “integrating blockchain with DPI” in summarizing computer network traffic flow events has emerged as a result of this research: This technique captured traffic flows in the network, DPI report, and the entire transmission session header and load them into a smart-contract based- Blockchain. Two experimental scenarios are used to test the validity of the system. The first scenarios involve analysis of DPI transmission without integrating blockchain, follow by the captured of transmission session involving DPI with blockchain. The finding indicates that DPI transmission with blockchain is more secured against "Tampering Incidents", "Unauthorized Access Attempts", “Auditability” and many other security concern. Whereas, the performance overhead introduced by blockchain-based DPI indicate an increase in "DPI Processing Time from 68ms to 150ms, a "CPU Usage increment by 20%, Network Latency increment of 15ms from 20ms to 35ms, and almost all other computational resources increase. Therefore, the finding can be summarized that the performance overhead introduced by integrating blockchain with DPI increases, but it provides a secure DPI reports for decision making.

Due to the host immunological disease brought on by infection is sepsis, multiple organ dysfunction syndrome (MODS), which has a high morbidity and mortality rate, could be the result. With advances in pathogen detection technologies, breakthroughs in anti-infection drugs, and the creation of organ function support, the clinical diagnosis and treatment of sepsis have advanced significantly. Pathogen-induced abnormal immunological responses, which can range from excessive inflammation to immunosuppression, are recognized to play a significant role in the high death rate. Unfortunately, no medications that are specifically intended to treat sepsis have been licensed. In order to offer a theoretical foundation for the management of sepsis, we will now discuss current advancements in research on immunological responses in sepsis. The prognosis of sepsis patients may be improved by developing and optimizing a dynamic immune system treatment plan based on anti-infection therapy, fluid replacement, support for organ function, and timely application of immunomodulatory therapies

Exploring new approaches to innovating higher vocational education is a worldwide pursuit driven by the increasing demand for graduates equipped with competencies. This study investigated how Outcomes-Based Education (OBE) influences the attainment of graduate competence (AGC) in China’s higher vocational education, using the theory of Constructive Alignment (CA) as its foundation. The OBE framework incorporates intended learning outcomes (ILOs), project-based learning (PjBL), assessment strategies (ASs), and AGC. The study tested the model by assessing the impact of ILOs, PjBL, and ASs on AGC, respectively and sequentially. Surveys were administered to 320 CBEC learners in April 2024, resulting in 301 usable responses. Data were analyzed using structural equation modeling (SEM) with SPSS 23.0 and AMOS 24.0. Results indicated that PjBL and ASs were directly and positively related to graduate competency attainment, while ILOs were indirectly associated with graduate competence through the mediating roles of PjBL and ASs. The most substantial mediating effect between ILOs and graduate competence was ASs, followed by PjBL, and then, the chain mediating effect of PjBL and ASs. These findings enhance the theoretical understanding of OBE and provide detailed procedures for tracking and enhancing sustainability in higher vocational education. Beneficiaries include educators, policymakers, and accreditation bodies.

Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (R_h) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting Ecosystem Respiration (R_eco) to Gross Primary Productivity (GPP). To do so, we developed a simplification of the Soil Carbon dynamics routine proposed in DNDC [1]. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameters distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

This paper aims to provide an evaluation of how Value Added Tax (VAT) policy alterations influence market liquidity, trading volume, and stock performance. To fill the existing literature gap on the direct effect of (VAT) adjustments on stock market dynamic, particulate within the banking industry. The study employs an event study methodology to analyse the immediate and medium-term effects on bank stocks listed in markets subject to a (VAT) adjustments. The core of the study analysis is anchored around two pivotal events, the initial application of (VAT) on 1st January 2018, and the subsequent (VAT) increase to 15% on 1st July 2020 using MATLAB R2022b. The study analysis encompasses the period immediately before and after the introduction and subsequent increase (VAT) in kingdom Saudi Ariba (KSA) employing an eleven sample comprises the (KSA) largest banks with a ±7 days window period from the event. The analysis revels that the imposition of 5% (VAT) lead a substation downturn in trading volume and stock returns of 9.5%, and 39.5%, subsequently. While when the (VAT) was increased by 15% the market exhibited a mixed but ultimately positive response of 3.3% trading volumes increases and 128.7% average stock return recovery.

The understanding of the natural water cycle, also known as the hydrological cycle, has evolved significantly from early philosophical contemplations to the contemporary scientific models employed today. Ancient Greek philosophers initiated this development, and further progression occurred during the Renaissance and Enlightenment periods through empirical research. The 19th and 20th centuries witnessed transformative impacts with technological advancements. Notably, the Quran contains descriptions of the water cycle that align with contemporary scientific knowledge. This study underscores the timeless accuracy of the Quranic verses, which remain unaffected by the era in which they were revealed and align with the latest scientific discoveries.

Every finite simple group P can be generated by two of its elements. Pairs of generators forP are available in the Atlas of finite group representations as (not necessarily minimal) permutation representations P . It is unusual but significant to recognize that a P is a Grothendieck’s dessin d’enfant D and that a wealth of standard graphs and finite geometries G - such as near polygons and their generalizations - are stabilized by a D. In our paper, tripods P − D − G of rank larger than two,corresponding to simple groups, are organized into classes, e.g. symplectic, unitary, sporadic, etc (as in the Atlas). An exhaustive search and characterization of non-trivial point-line configurationsdefined from small index representations of simple groups is performed, with the goal to recognize their quantum physical significance. All the defined geometries G's have a contextuality parameterclose to its maximal value 1.

RNA extraction from human cumulus cells (CCs) is considered challenging due to low cell’s pop-ulation and small cell. The successful gene expression analysis from cumulus cells ultimately de-pends on an excellent concentration of Ribonucleic acid (RNA) yield by an appropriate technique. Our study aims to consolidate appropriate cumulus cell collection method, preparation and ex-traction techniques to ensure a good yield of RNA for better gene expression analysis. From the results obtained, the optimal strategy found involved mechanical denudation without an enzy-matic process, followed by the use of RNA stabilizer prior to RNA extraction. Subsequently, uti-lizing a smaller homogenizer, preferably manual pressure control with filter (Bio-Masher III®) is paramount for a pure and homogenize sample. Subsequently, during RNA extraction, the use of RNeasy micro kit and RNA carriers is recommended. These sample collection, preparation, and extraction techniques yielded an excellent-quality RNA concentration and successful gene expres-sion analysis. We also conducted a systematic review to consolidate our findings with current evidence of RNA extraction technique. Our results added a value as a current strategy for opti-mizing RNA extraction in CCs for experimental studies. Thus, our findings can contribute to for-mulating a better strategy for optimizing the RNA extraction in CCs for transcriptomic studies.

The escalating global population and subsequent demand for agricultural products have led to a surge in agricultural waste generation, posing significant disposal challenges. Conventional disposal methods such as burning and dumping not only harm the environment but also jeopardize human health and safety. Recognizing the urgent need for sustainable waste management, researchers have increasingly focused on repurposing agricultural plant waste as a valuable resource. This paper presents a comprehensive review of the potential of agricultural plant waste in wealth creation and sustainable development. It highlights the detrimental impacts of current disposal methods and emphasizes the necessity for alternative approaches. By analyzing the physical, mechanical, and chemical properties of plant fibers, particularly cellulose, hemicellulose, and lignin, this review underscores their suitability for diverse applications. Moreover, it explores the emerging trend of utilizing pineapple leaf fiber, a sustainable and lightweight material, in structural applications such as UAV construction. With its exceptional mechanical properties and biodegradability, pineapple leaf fiber holds promise as a viable alternative to traditional materials, contributing to a more sustainable future. In conclusion, this review advocates for a paradigm shift towards embracing agricultural plant waste as a valuable asset for economic prosperity and environmental sustainability. It underscores the importance of continued research and technological advancements to unlock the full potential of agricultural waste in fostering a circular economy and driving sustainable development globally.

Stem cell-derived therapies have shown substantial promise in regenerative medicine for the treatment of degenerative diseases and injuries. Mesenchymal Stem Cells (MSCs) exhibit a remarkable capacity to differentiate into diverse cell types, modulate immune responses, and facilitate tissue repair. Nevertheless, concerns regarding their potential to induce tumors arise from their intrinsic properties, environmental factors, and genetic mutations that occur during handling. This review explores the intricate challenges associated with the tumorigenic potential of stem cell-derived therapeutic products and examines the underlying mechanisms contributing to this risk, such as oncogene activation, suppression of tumor suppressor genes, and the influence of the microenvironment on stem cell behavior. Furthermore, it delves into the role of epigenetic modifications and chromosomal aberrations in cell culture and expansion. This article provides an overview of strategies to mitigate tumorigenic risks, encompassing rigorous quality control measures, refined differentiation protocols, and advanced screening techniques. It also highlights innovative approaches, such as gene editing technologies and small-molecule modulation of stem cell behavior, as promising avenues to enhance safety. Despite these challenges, ongoing research and technological advancements are actively addressing these concerns to ensure safer and more effective utilization of stem cell-based therapies in clinical settings.

Access to medical care is a global issue. Technology-aided approaches have been applied in addressing this. Interventions have however not focused on medical diagnosis as a fully automated procedure and available applications employ mainly text-based inputs rather than conversation in natural language. We explored the utility of ontology-based chatbot technology for the design of intelligent agents for medical diagnosis through a systematic review of the most recent related literature. English articles published in 2011-2016 returned 233 hits which yielded 11 relevant articles after a 3-stage screening. Findings showed that the creation of expert systems had been the focus of many the studies which utilize the physician-system-patient framework with system training based mostly on expert knowledge for designing web- or mobile phone-based applications that serve assistive purposes. Findings further indicated gaps in the design and evaluation of more effective systems deployable as standalone applications, for example, on an embodied robotic system. The need for technology supporting the physical examination part of diagnosis, connection to data sources on patients’ vitals and medical history are also indicated in addition to the need for more qualitative work on natural language-based interaction. The system should be one that is continuously learning. Future works should also be directed towards the building of more robust knowledge base as well as evaluation of theory-based diagnostic methodological options

Mesenchymal Stem Cells (MSCs) secretions, usually containing growth factors, cytokines, and chemokines, have improved wound healing via a paracrine mechanism. This makes them particularly valuable as potential cell therapeutics. Similarly, wound healing is mainly regulated via paracrine signaling of growth factors, cytokines, and chemokines. Chronic wound healing has prolonged inflammatory, proliferative, or remodeling phases, resulting in tissue fibrosis and non-healing ulcers. The growth factors, cytokines, and chemokines secreted by MSCs can be applied to wounds by transplanting cells or using the secretome/conditioned medium (CM) of MSCs, which contains these secreted bioactive molecules. For their success in increasing the wound healing rate, MSCs offer a promising option for treating chronic wounds. This review provides a concise summary of current knowledge of the biological properties of MSCs and describes the use of MSCs for wound healing. In particular, the scope of this review focuses on the role of MSCs in wound healing by increasing wound healing rate with the secretion of growth factors, cytokines, and chemokines. In addition, the function and type of MSCs also have been discussed.

Continuum robots play the role of end-effector in various surgical robots and endoscopic devices. The robots may be categorized as rigid or soft continuum robots (SCRs). While the SCRs have proven advantages such as safety and compliance, more research and development are required to enhance their capability for specific medical scenarios. This research aims at designing a soft robot considering concepts of geometric and kinematic similarities. The chosen application is a semi-invasive medical application known as Transesophageal Echocardiography (TEE), but the methodology can be implemented in other similar applications. Since established rigid carrier construction make use of principles we find as well embodied in vertebral spines, the paragon for soft robot solution can be the phylogenetic precursor of the spine, the Chorda dorsalis. The feasibility of fabrication of a soft endoscopic device derived from that paragon within a robotics laboratory was shown empirically by producing a three-segment pneumatic SCR. The kinematic model was proposed based on the method of transformation matrices, and an algorithm based on a self-organizing map (SOM) was proposed and applied to realize kinematic similarity. The simulation results indicate that the algorithm acting as an open-loop controller forces the soft robot tip to follow the desired path which in this case is the path of the rigid probe. It is concluded that the solution provides a soft robot that can surrogate and succeed the traditional rigid counterpart owing to size, workspace, and kinematics.

Future healthcare professionals can play a significant role in managing those with thoughts of suicide. This scoping review aims to determine healthcare students’ knowledge and attitude towards suicide. A systematic search was conducted across five databases: PubMed, CINAHL, EMBASE, PsycINFO, Cochrane, and DARE. Only primary studies written in English, from database inception until 31st December 2023 were included. A total of 44 studies were included. Overall, healthcare students demonstrated low to moderate confidence in managing patients with thoughts of suicide and low levels of relevant education despite acknowledging their importance in preventing suicide. Increased personal exposure to suicide was associated with increased suicide literacy, confidence in managing patients with thoughts of suicide, and reduced stigma. Demographics and culture were shown to affect knowledge and attitude as well. Further research is needed to better understand various contributing factors to healthcare students’ knowledge and attitude regarding suicide. Evaluating healthcare curricula should be considered to implement effective suicide training program.

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050 , sustainability emerges as a crucial focus area and paradigm shift to enhance environmental friendliness, improved quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The growing use of sustainable construction practices is growing in the U.A.E., where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current as well as future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a Triple -Bottom Line approach. Through an exploration of the significance of sustainable construction materials, this researcher underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance, and project management practices. The construction sector's role in economic development and its substantial environmental impact are discussed in, alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability; and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally;, the incorporation of recycled content;, considerations for indoor air quality, energy, and water efficiency parameters;, and how these properties relate to project scope, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects.

External audit reliance issues on the internal audit function (IAF) are increasingly important in financial auditing, yet its application in audit engagements lags behind other applications. Despite the belief that audit reliance will shape auditing in the future, limited and intervalley publications explore this transformative potential. This paper investigates the increasing importance of external audit reliance issues in financial auditing. It investigates the use of the IAF in external audit reliance decisions and its potential to enhance audit quality, process transparency, and stakeholders' credibility. Through a systematic literature review of 68 scientific articles from 1984 to 2022, factors influencing external auditors' dependence on the IAF are analyzed, including IAF work quality, assistance type, organizational factors, customer pressure, and business risk. The review highlights the IAF's crucial role in improving financial reporting integrity and external audit effectiveness. However, the challenges that allowed external auditors to decide whether to rely on the works of IAF like limited disclosures and accessible data hinder assessing IAF reliance effects, leading to information asymmetry that may impact stakeholder confidence. The paper discusses implications, limitations, and future research directions to explore technology adoption and optimize audit practices, promoting transparency in the audit process.

Cervical cancer remains a significant global health challenge, ranking as the fourth most common cancer among women. The primary causative agents, Human papillomavirus (HPV) strains 16 and 18, are well-known for their role in cervical carcinogenesis, primarily through the actions of the E6 and E7 oncoproteins. This study aimed to identify a natural compound capable of inhibiting both E6 and E7 oncoprotein activities, thereby offering a potential therapeutic approach using a single agent. This study also comprises an extensive in silico analysis with molecular docking studies by AutoDock Vina and Schrodinger Maestro to analyse the binding affinity, hydrogen bonds interactions of selected compounds against HPV 16 E6 &E7 proteins. GROMACS package and iMODS server was used to perform molecular dynamics simulations of protein-ligand complexes to elucidate stability of the ligands around the receptor at different time points. SwissADME was utilized for the prediction of pharmacokinetic properties while PROTOX-II helped in predicting toxicological data Capsaicin emerged as the most promising candidate, exhibiting binding energies of -7.3 kcal/mol and -5.6 kcal/mol against the HPV 16 E6 and E7 proteins, respectively. Notably, Capsaicin formed a single hydrogen bond with each oncoprotein, indicating a strong and specific interaction. The compound also demonstrated a favourable pharmacokinetic profile, with no violations of drug-likeness rules, and was classified as Toxicity Class 4, suggesting a moderate safety profile. These results, thus branding Capsaicin as a promising lead compound for further investigations in cervical cancer therapy that deserves documentation through well-equipped wet lab experiments followed by clinical studies.

The Industrial Revolution 4.0 (IR4.0) is transforming the global economy, necessitating mall and medium-sized enterprises (SMEs) to adopt new technologies like artificial intelligence (AI), the Internet of Things (IoT), blockchain, and cloud computing. Therefore, SMEs need to assess their readiness to identify capabilities and areas for improvement to remain competitive. However, existing IR4.0 readiness assessment such as the Industry4WRD Readiness Assessment and Industry 4.0-Readiness by IMPULS German are time-consuming and restrict the participation of various sectors. Using the understanding of theories such as Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Readiness Index (TRI), and Diffusion Of Innovation (DOI), this study developed an initial research model that identifies the dimensions of IR4.0 readiness; (i) organization, (ii) data, (iii) infrastructure, (iv) analytics, and (v) IT, development and operations. This study carried out qualitative methods through four different phases. The first phase is a systematic literature review, and data collection through participant observation (PO) in IR4.0 skills training programs, seminars, and workshops. The second phase is the development of an initial research model to identify the dimensions of IR4.0 readiness that will be used in the next phase. The third phase is a survey on SME’s IR4.0 readiness via the IR4.0 e-Readiness Checker (IR4.0 eRC) readiness assessment system, which produces the final research model, IR4.0 SME Readiness Model. In the fourth phase, the IR4.0 Readiness Model is confirmed for use by SMEs in Malaysia through interviews with three industry experts in Malaysia. Based on the 50 responses in the IR4.0 eRC evaluation, the average IR4.0 readiness of SMEs is 66%, and only 10 SMEs with less than 50%, showing room and improvement opportunities for the continuous research and development of IR4.0 transformation. This study developed IR4.0 readiness model for SMEs to assess readiness for IR4.0 transformation, support investments in IoT projects and employee upskilling programs.

The integration of artificial intelligence (AI) into academic settings in Sabah, Malaysia, is transforming education and research landscapes. While AI technologies promise to enhance teaching, learning, and scholarly activities, they also pose challenges such as ethical concerns and skill gaps among academic staff. This study addresses the multifaceted impacts of AI adoption on academicians in Sabah, focusing on two key research questions: the impact of AI-based intelligent tutoring systems on student engagement, learning outcomes, and educational equity, and the challenges and opportunities in building academicians' capacity to integrate AI technologies effectively. Through a multidisciplinary approach, incorporating insights from education, computer science, social sciences, and ethics, this research aims to evaluate the effectiveness of AI tools in educational settings and identify strategies for skill development and infrastructure support. The study recommends empirical assessments within Sabah's educational institutions, considering contextual factors and fostering collaborative partnerships with local communities. Professional development programs, collaboration with industry partners, and improved access to AI infrastructure are proposed strategies. Longitudinal studies and interdisciplinary research initiatives are suggested for future research, along with qualitative methods to capture diverse perspectives. Ultimately, by embracing a collaborative and multidisciplinary approach, Sabah's academic community can harness the transformative potential of AI to advance education, research, and scholarship while promoting ethical and inclusive practices.

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. Globally the atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, the total increasing temperature globally averaged combined land and surface between the average of the 1850-1900 period and the 2003 to 2012 period is 0.78 °C (0.72 to 0.85). But should we prepare for such the relatively small change? The importance is not the mean of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the difference in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays to train services. During the period of flood, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration, high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion on to the infrastructure as well as additional quasi-static burden exerted. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore.

The objective of this study was to compare the effectiveness of a professional-oriented education approach to traditional teaching methods among high school secondary students in Kazakhstan in aligning students to their suitable career education track. The study utilised a mechanics physics course to assess both approaches and involved two groups of students over 26 months - a control group (n=58) and an experimental group (n=57). Quantitative data was collected through a Mechanics Physics Test administered before and after the teaching and learning class. In Kazakhstan, students will be aligned directly with either secondary vocational education, the initial vocational education track, or the general education track, which relies on the final performance of their secondary school. The findings indicated that both teaching methods improved the student's performance, but the experimental group exhibited a significantly higher level of improvement than the control group. This study shows that a professional-oriented education approach can clearly align students with their interests and strengths and help them pursue their desired careers confidently. This approach enables students to make informed decisions about their future studies and career paths, reducing costs and saving time for schools and governments—implications and, to a further extent, the study is also discussed.

Urbanization-induced land use transition results in a decline in ecosystem services, which has implications for regional ecological security. In order to explore the relationship between ecosystem services and land use transition, this paper utilizes the InVEST model, geographically weighted regression model to examine the impact of land use transition on ecosystem services in the Dongting Lake area (DLA). The results showed that (1) During the period 2000-2020, the intensity and motivation of land-use transition showed obvious spatial and temporal heterogeneity with the variation of urbanization development. (2) Habitat quality and Carbon sequestrations showed a downward trend. In contrast, food supply followed an upward trend; soil conservation and water yield services initially increased and dropped later. The overall spatial changes in habitat quality and Carbon sequestration appear to be insignificant. Food supply shows significant differences in the plains compared to other areas; while soil conservation and water yield service shows significant changes in places other than the DLA. (3) From 2000 to 2020, land use transition dynamics, population density, GDP density, night lighting and transition intensity had mainly negative effects on ecosystem services. Only the Normalized Vegetation Index (NDVI) showed a positive effect on ecosystem services. The results of the research will provide valuable references for the development and implementation of spatial ecological restoration planning and land use policies in the national territory.

The present investigation highlights the synthesis of polyaniline (PANI) coated graphene oxide doped with SrTiO3 nanocube nanocomposites through facile in-situ oxidative polymerization method for the efficient removal of carcinogenic dyes, namely, the cationic dye methylene blue (MB) and the anionic dye methyl orange (MO). The synthesised nanocomposites were characterised by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The adsorption efficiencies of graphene oxide (GO), PANI homopolymer and SrTiO3 nanocubes-doped nanocomposites were assessed by monitoring the adsorption of methylene blue and methyl orange dyes from aqueous solution. The adsorption efficiency of nanocomposites doped with SrTiO3 nanocubes were found to be of higher magnitude as compared with undoped nanocomposite. Moreover, the nanocomposite with 2 wt% SrTiO3 with respect to graphene oxide demonstrated excellent adsorption behaviour with 99% and 91% removal of MB and MO respectively, in a very short duration of time.

Despite their prevalence in almost all publicly orientated conservation settings, sign design receives limited attention in the research literature. We used a remote eye-tracking device to test how visitors read educational signs, maps, and species signage. Three designs, plus a plain-text control sign, were tested for each sign type. Sign content was based on Brackenhurst Botanic Garden, Kenya and included four different information texts (156-256 words long) and a species information text (64 words long). Four presentations of extinction threat-status were also tested as were depictions of trail routes on maps. Data were collected from 51 participants at six cultural venues across Nottingham, UK. Signs positioned centre-left of an exhibit were read first. Information on the left-hand side of signs was read first and dwelled upon the longest. Signs with a single large image and a single block of text were generally preferred, and images were most frequently recalled. Extinction threat-status was most frequently viewed and best recalled from green-red thermometer diagrams and least from the IUCN red-list diagram. Map routes were clearest when presented as coloured solid lines. This study indicates the potential benefit of eye-tracking research for measuring sign use and assisting in sign design.

Orchids totalling close to 4000 species in Malaysia are one of the most diverse and most widespread family here had gained momentum in recognition among policy makers and guardians of the forest as one of the profiles that fit and can benefit plant conservation on a broad scale in recent years. Listed not only as conservation indicator but also as priority germplasm for sustainable floriculture industry in the country, a milestone that could safeguard wild orchids from verge of extinction in the natural habitat. Through our 30 years of studying orchids in the wild, we understand more about the distribution, rarity, threats and extinction of orchids than ever before, and we have the scientific tools to address many of the problems, yet many species face daily threats including habitat loss and unsustainable exploitation mainly via Internet trade. Prior to executing workable conservation plan, various research institutions working closely with Forestry Departments in Malaysia to first inventory and document the orchid species richness in the country. Selangor, Sarawak and Perlis Forestry Departments in collaboration with UPM have published seven orchid books that cover various habitat types. Selangor Forestry Department is leading on publishing biodiversity data in form of books for its various ecotourism’s sites and State Parks, and had published two books on orchids. Sarawak state has published one on the limestone orchids, and Perlis is the first to embark on the feat published one in 2010 and currently preparing a new book that includes other flagship wild flowers. Realizing the importance of documenting its biodiversity wealth, Malaysia has developed an information system that would be a one-stop retrieval point or repository for biodiversity facts and as a part of the commitments to CBD to facilitate reporting and the transfer of biological diversity and conservation-related information both nationally and internationally.

Urban lakes, especially those of natural origin, provide ecosystem services, recreation being one of the most important and highly valued by the city dwellers. Fulfilling the needs of city residents to relax and have contact with nature has become a priority in urbanized areas and has been proved to positively affect people’s health and well-being. The recreational potential of water bodies was identified to be most important aspect of ecosystem services to the residents of the neighboring areas. An assessment of recreational ecosystem services (RES) provisioning to society based on the real time spent by the citizens and housing values in the rural-urban gradient revealed that the economic benefits of lakes differ in urbanized, suburban and rural landscapes. The growth of cities has led to an increased population density in the surroundings of ecologically valuable areas, resulting in higher pressure from visitors seeking recreational areas. Along with urbanization, the impoverishment of ecosystem functions takes place, limiting their capability to provide ecosystem services. In this work provisioning of recreational ecosystem services of 28 floodplain lakes located along the urban-rural gradient of the Warsaw agglomeration was assessed. The relationship between the ecological value of the water bodies, measured using naturalness indices, and the recreational ecosystem services they can provide was assessed. The results showed that the floodplain lakes located along the urban-rural gradient are of a great importance to the citizens due to their recreational potential. The provisioning of recreational ecosystem services is poorly connected with the ecological characteristics of the floodplain lakes. Only hemeroby, was significantly correlated with provisioning, and there was no relationship with factors such as naturalness of vegetation or water quality, demonstrating that public preference was not generally influenced by high ecological quality. These data should be available to potential buyers and be integrated in spatial planning management plans in order to shape future housing policy.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

Brand visual identity is a critical component of brand image and impacts consumers' brand perception and attitude. Although scholars and practitioners have increasingly researched brand visual identity, most focus on brand communication and corporate management perspectives, necessitating a systematic review of consumer attitudes based on brand visual identity elements. This study aims to review the impact of brand visual identity on consumer attitudes and provide directions for future research. We conducted a systematic search using PRISMA guidelines, reviewed relevant articles published in four databases (Web of Sciences, ProQuest, Scopus, and Elsevier) in the past two decades (2004-2024), and obtained 559 articles in April 2024. We conducted a thorough peer-review of both theoretical and empirical journal articles, followed by a scoping review. Thirty-four studies were eligible, analysing consumers' perceptions of various core elements of brand visual identity (BVI) (such as brand logo, colour, name, typography, and font), as well as the impact of brand visual identity on consumer attitudes and the practical implications of brand management. The results show that the consumption of visual identification elements affects consumers' perceived brand quality, brand personality, brand satisfaction, loyalty, favourability, and so on., as well as purchase intentions and social attitudes. In summary, the findings indicate that brand visual identity elements impact consumer perceptions and attitudes. However, despite some progress, further research is necessary to arrive at more definitive and robust conclusions.

Surface–subsurface soil-rock modeling is crucial for infrastructure design and groundwater yield optimization, especially in the complex crystalline basement terrains of Penang Island, Malaysia. This study conducted large-scale characterization of soil-rock profiles using ERT, SRT, rock quality designation, and soil penetration test (SPT N-values) data, optimized through regression modeling. The approach effectively identified soil-rock structures and their suitability to prevent structural failures and enhance groundwater productivity. Correlations between borehole lithologic logs and velocity–resistivity models revealed distinct soil compositions across the study area. The results highlighted thick, saturated, and loose silty to sandy bodies in the eastern to northern sections, contrasting with sandy compositions and penetrative fractures in the southern part. The study also found good correlations between rock mass quality and N-values for different soil types. Depths of intra-bedrock weathered/fractured units varied between 12 and >35 m. This has significant implications for determining optimal foundation depths in the study area. Groundwater productivity was associated with intra-bedrock planes of weakness at depths exceeding 40 m. Overall, this study developed empirical relations between geophysical and geotechnical parameters for wet tropical granitic terrains, filling critical gaps in understanding subsurface characteristics.

The research improves the strength of plastic using avocado seed starch and PLA. The effect of blending avocado seed starch and PLA was optimized using the RSM approach by using two variables: water absorption and biodegradability. Mixing them using RSM gave the best result: 1.8 g of starch and 3 g of PLA. Degradable plastic has a (tensile strength of 10.1 MPa; elongation at break of 85.8%; young modulus of 190 MPa). Infrared spectroscopy showed that the plastic had a -OH bond at 3273.20 cm-1, 3502.73 cm-1, 3647.39 cm-1, a CH2 bond at 2953.52 cm-1, 2945.30 cm-1, 2902.87 cm-1, a C=C bond at 1631.78 cm-1, and a C-O bond at 1741.72 cm-1. The plastic decomposed in soil. It was organic and hydrophilic. Thermal tests, the plastic can withstand heat well, losing weight at 356.86°C to 413.64°C, forming crystals and plastic melts at 159.10°C—the same as PLA. Melt flow test, sample melts before measurement, therefore not measurable—process conditions that affect. Water absorption of 5.763% and biodegradation rate of 37.988% decomposed for 12 days. In morphology analysis, the starch and PLA fused to form a smooth surface. RSM found value was close to 1. RSM gave the best process parameters.

In this work, zinc oxide (ZnO)/ granular activated carbon (GAC) composites at different ZnO concentration (0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC) were prepared by an in-situ hydrothermal method and demonstrated synergistic photocatalytic degradation and ad-sorption of Rhodamine B (RhB). The thermal stability, morphological structure, elemental com-position, crystallographic structure, and textural properties of developed catalysts were charac-terized by thermal gravimetric analysis (TGA/DTG), scanning electron microscopy equipped with energy dispersive-x-ray (SEM-EDS), x-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis. Successful loading of ZnO onto GAC was confirmed by SEM-EDS and XRD analysis. The BET surface areas of GAC, 0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC were 474 m2/g, 450 m2/g, 453 m2/g, and 421 m2/g, respectively. The decrease in GAC could be attributed to the successful loading of ZnO on the GAC surface. Notably, 0.5M-ZnO@GAC exhibited the best photocatalytic degradation efficiency of 82% and 97% under UV-A and UV-C light over 120 min, attributed to improved crystallinity and visible light absorption. The photocatalytic degradation parameters revealed that lowering the RhB concentration, raising the catalyst dosage and pH be-yond the point of zero charge (PZC) would favor the RhB degradation. Photocatalytic reusability was demonstrated over 5 cycles. Scavenger tests revealed that the hydroxyl radicals (•OH), su-peroxide radicals (O2−•), and photoinduced hole (h+) radicals play a major role during the RhB degradation process. Based on the TOC results, the RhB mineralization efficiency of 79.1% was achieved by 0.5M-ZnO@GAC. Additionally, GAC exhibited a strong adsorptive performance towards RhB with adsorption capacity and RhB removal of 487.1 mg/g and 99.5% achieved within 90 min equilibrium time. The adsorption characteristics were best described by pseu-do-second-order kinetics, suggesting chemical adsorption. This research offers a new strategy for the development of effective photocatalyst materials with potential for wider wastewater treat-ment applications.

This paper presents a Cartesian model of sustainability by a novel integration of Circular Economy principles and ESG (Environmental, Social, and Governance) criteria to explicitly establish a clear path for closing the loops of negative social and environmental externalities. As global sustainability transformations accelerate, they bring both opportunities and inherent financial risks and social uncertainties. Historically, economic development has often been achieved at the expense of environmental balance. The contemporary challenge is to attain a dynamic equilibrium between natural and socio-economic systems. We introduce an integrated, multidisciplinary, and dynamic framework for studying and managing sustainability transitions. Our innovative 4-quadrant framework utilizes a Cartesian coordinate system to map the impacts of various business models on natural and socio-economic systems, spanning from linear open-loop to circular closed-loop ESG models. The framework is data-driven, employing normalized coordinates (-1 to 1) to facilitate empirical analysis and the establishment of temporal Key Performance Indicators. By integrating the Human Development Index within ecological limits, our model targets regenerative development that harmonizes human progress with planetary boundaries. This versatile and robust framework serves as a practical tool for businesses, households, organizations, and policymakers to navigate the complexities of sustainable development, promoting innovation and fostering a just transition towards regenerative practices. Our approach provides a comprehensive roadmap for achieving high human development within the planet's ecological limits, contributing significantly to the broader discourse on sustainability science and management.

Nature-Based Solutions (NBSs) can help to achieve multiple Water-Ecosystem-Food Nexus Do-main Objectives & Nexus Resilience Qualities, facilitating the transition to more resilient agrifood systems and providing an evidence base for a broader Nexus policy dialogue. This paper de-scribes the stepwise methodology developed in the EU-funded LENSES project to carry out a comprehensive analysis of NBSs in 6 pilot areas in 5 Mediterranean countries, and presents the results of NBSs implementation in 4 pilot areas, highlighting obstacles and opportunities. The methodology includes the development of an analytical evaluation framework and of a com-prehensive catalogue of Nexus-related NBSs, whose suitability needs to be assessed at the local level to achieve better use of protected/natural ecosystems, increase the sustainability and mul-tifunctionality of managed ecosystems and design and manage novel ecosystems. Subsequently, in a collective learning process which supported the operationalisation of the WEF Nexus, NBSs were identified that address specific contextual vulnerabilities, improve water distribution and enhance food security, while preserving ecosystems and supporting adaptation to climate change. The added value of the proposed methodology lies in the multi-stakeholder participatory approach to gain in-depth knowledge of local agri-food systems, including their main WEF-related challenges, and to facilitate overcoming barriers to NBS implementation.

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is a fundamental work in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a "two-step refinement zoning method" to address this gap, first using the self-organizing feature mapping method to delineate EFZs based on ESs at a township scale, and then applying hotspot overlay analysis to identify hotspots of dominant ESs within EFZs at a village scale. By overlaying the outcomes of these two steps, EFZs can be further graded by designating villages with hotspots of dominant ESs as level I and those without as level II. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ESs combinations and land use compositions. Furthermore, 5.23% of villages were identified as Level I of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.

Because the integrity, availability, and confidentiality of digital assets are so important, cybersecurity is key to both the education sector and the critical infrastructure sector. This article investigates the state of cybersecurity in education, emphasizing strategies for securing the classroom against cyberattacks. We go over important subtopics including risk assessment, putting security measures in place, and incident response preparation. Furthermore, we examine how industry-academia partnerships might improve cybersecurity resilience. We also explore cybersecurity for critical infrastructure, stressing the need for risk assessment, security control implementation, and incident reaction and recovery planning. We introduce subtopics such as public-private partnerships in critical infrastructure protection and continuous monitoring and threat detection systems. By use of an extensive examination, this article seeks to provide perspectives on efficacious cybersecurity tactics for preserving education and vital infrastructure, guaranteeing the sustained steadiness and adaptability of the community against constantly changing cyber threats.

The objective of this study was to determine how application with dolomitic limestone and grazing type (continuous or deferred) affect sheep grazing location and feed preference when the pasture growth rate is maximum. A 4ha field was divided into 4 plots: P1 and P2- without application of dolomitic limestone, continuous (CG) and deferred grazing (DG), respectively; P3 and P4- with application of dolomitic limestone, DG (1AUE), and CG (2.4 AUE), respectively. In DG, animals were placed and removed from the plots depending on the height of the pasture. In each plot, 12 georeferenced sampling points were identified. Throughout the pasture's vegetative cycle (autumn, winter, spring, and early summer) several measurements of pasture height and cut were carried out. From the beginning of March to the beginning of June, animal behavior was observed, by trained observers, through binoculars on six dates. Animals' activity grazing and location was recorded. The results show that: (i) the application of dolomitic limestone combined with CG provided higher values of pasture height; (ii) there were no significant differences in pasture quality between treatments; (iii) Deferred grazing led to 50% more sheep grazing days than continuous grazing; (iv) there were no significant differences in soil compaction between CG and DG; (v) the type of grazing and the treatment with dolomitic limestone did not seem to change the grazing pattern between treatments. This work contributes to understanding the relationships between different types of grazing in dryland pastures, with and without application of dolomitic limestone, and preferred grazing locations for sheep. This work could help agricultural managers make more informed decisions with the aim of promoting the sustainable intensification of livestock production in the Montado ecosystem.

A single mode waveguide grating coupler based on multiple Si-SiO₂ pairs onto Si substrate has been designed. Numerical analysis has been carried out to calculate optimum thickness of the layers of Si-SiO₂ that ensures the constructive interference between reflected waves and actual guided wave for high coupling efficiency. Based on the results, an optimal design is developed and modeled by using a 2-D finite difference time domain (2-D FDTD) simulator that dictates a coupling efficiency of as much as 78% (-1.07 dB) at the wavelength of 1550 nm, and a 1-dB bandwidth of 77 nm. The numerical method will be useful to calculate the optimum thicknesses of the layers for any reflector based grating coupler of different materials.

Reductions in water availability and increasing rainfall variability are generating a narrative of growing competition for water in the Mediterranean basin. In this article, we explore the distribution and importance of water resources in the Muga River Basin (Catalonia, Spain) based on key stakeholders’ perceptions. We performed a sociocultural evaluation of the main water ecosystem services in the region through stakeholder interviews and participatory mapping. The basin was generally perceived as a hotspot of ecosystem services, but we detected varying opinions and considerable differences in the perceptions of importance and spatial distribution of water ecosystem services. These discrepancies were linked to the varying levels of stakeholders’ dependence on water. Our findings are important for contributing to correct water planning and management in the river basin, which is a complex water social system marked by conflicts between different stakeholder groups vying for the same resource. This complex situation requires bottom-up strategies to create transparent, participatory decision-making models.

IL1RA intron 2 86-bp repeat and IL4 intron 3 70-bp repeat are VNTRs that have been associated with various diseases, but their role in obesity is elusive. The objective of this study was to investigate the association of IL1RA and IL4 VNTRs with obesity and adiposity in 315 Malaysian subjects (128 M/187 F; 23 Malays/251 ethnic Chinese/41 ethnic Indians). The allelic distributions of IL1RA and IL4 were significantly different among ethnicities, and the alleles were associated with total body fat (TBF) classes. Individuals with IL1RA I/II genotype or allele II had greater risk of having higher adiposity - even after controlling for ethnicity [Odds Ratio (OR) of I/II genotype = 12.21 (CI = 2.54, 58.79; p = 0.002); II allele = 5.78 (CI = 1.73, 19.29; p = 0.004)]. However, IL4 VNTR B2 allele was only significantly associated with overall adiposity status before adjusting for ethnicity [OR = 1.53 (CI = 1.04, 2.23; p = 0.03)]. TBF was also significantly higher in those with IL1RA II allele compared with I allele (31.79 ± 2.52 vs. 23.51 ± 0.40; p = 0.005). Taken together, IL1RA intron 3 VNTR seems to be a genetic marker for overall adiposity status in Malaysian subjects.

Diabetic peripheral neuropathy (DPN) is a prevalent complication of type 2 diabetes that affects a significant proportion of diabetic patients worldwide. Although the pathogenesis of DPN involves axonal atrophy and demyelination, the exact mechanisms remain elusive. Current research has predominantly focused on neuronal damage, overlooking the potential contributions of Schwann cells, which are the predominant glial cells in the peripheral nervous system. Schwann cells play a critical role in neurodevelopment, neurophysiology, and nerve regeneration. This review highlights the emerging understanding of the involvement of Schwann cells in DPN pathogenesis. This review explores the potential role of Schwann cell plasticity as an underlying cellular and molecular mechanism in the development of DPN. Understanding the interplay between Schwann cell plasticity and diabetes could reveal novel strategies for the treatment and management of DPN.

Food allergy has been recognised by the World Health Organisation as a chronic disease that could lead to fatality. The symptoms can mediate from mild to severe consequences. Some cases have reported that food allergy sufferers are bullied and are discriminated at workplace, thus increasing their stress level, apart from facing difficulty in consuming certain food due to allergy. This has an adverse effect on the quality of life amongst food allergy sufferers. Medical bills are increased when food allergy sufferers become unknowingly exposed to food allergen. Hence, this study investigated food allergens among food allergy sufferers in order to make their lives better. A total of 250 respondents participated in an online survey. Surprisingly, apart from chicken, soybean and other food allergens that have been listed under the Big Eight Allergens, the respondents mentioned some fruits that could trigger allergic reactions, such as rambutans and watermelons. Food allergy sufferers can be allergic to seafood and seafood products as well, such as shrimp paste or locally known as belacan, which refers to fermented shrimp paste cured under the sun. It is a common food ingredient used among Malaysians. The study findings offer practical insights, such as avoidance of food allergens amidst food allergy sufferers and help the government to carefully manage for menu planning. The knowledge contribution of this study reveals several specific food and fruits, as aforementioned, which appear to be common and nutritious food, yet harmful to food allergy sufferers.

Several studies in recent years have shown that the use of non-Saccharomyces yeasts, used both in single and in mixed fermentations with Saccharomyces cerevisiae can help produce craft beers with distinctive compositional characteristics. The aim of this study was to evaluate the suitability of three Metschnikowia pulcherrima strains, isolated from Albanian vineyards, to be used as starters in the brewing process. Due to its specific enzymatic activities (protease, β-glucosidase and β-lyase) and its low production of hydrogen sulfide, M. pulcherrima 62 was selected as a starter culture for the production of craft beer. Specifically, the aptitude of this yeast to be used in sequential inoculation with S. cerevisiae S04 for the production of an American IPA-style beer and the main volatile compounds produced during fermentation were evaluated. Results showed significant differences in glycerol, isoamyl alcohol and isoamyl acetate content in beer obtained with sequential inoculum of M. pulcherrima 62 with S. cerevisiae S04 compared to beer obtained using S. cerevisiae S04 as a single starter. Therefore, these preliminary data support a candidacy of M. pulcherrima 62 as a new starter in the brewing process.

Several degraded ecosystems worldwide need to attain a stable vegetal cover after mandatory active restoration; thus, plants soil, and soil biodiverse microbes can be taken into consideration for a successful mission. Among environmental and biological variables, interactions with soil and its microorganisms are critical for permanent plant establishment. Thus, advances in the use of microbial management such as inoculation of mycorrhizas and bacteria become a modern aspect of active restoration programs. New strengths have increased worldwide since most plant species, including grasses, associate to mycorrhizae, Thus, a high percent of restored areas, which were degraded due to the increasing mining or conventional agriculture, rest to be monitored. This study shows current reports on active restoration of degraded landscapes as well as the methodology required for a successful ecosystem restoration. Active restoration has been recognized as the best method to restore tropical forests; however, the higher cost of active restoration, which requires planting seedlings, direct seeding, root inoculation of microorganisms or mitigation of disturbances, which aid the recovery process despite monitoring. On the other hand, the spontaneous recovery of trees that colonize and establish in abandoned fields or natural disturbances, named natural regeneration, is less targeted and can require more time to achieve results. We conducted a web of science search of recent published articles on restoration and analyzed them. We confirmed the important role of AMF on root colonization and soil AMF spores as drivers of restoration of main ecosystems according to previous results from restored sites in Brazil. In the restored sites AMF (more than 8 species) was generally found, while in preserved sites dominated Gigaspora, Scutellospora and Acaulospora, restored sites presented relevant AMF richness as well as the preserved sites. Root colonization by AMF in experimental mined sites was high. Vesicles were frequent in restored sites.; however, colonization intensity was generally the same despite treatments. In general, in the control treatments, values of root colonization remain high.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Reducing fertilizer-N rate, applying nitrification inhibitor (NI), and incorporating straw are widely recommended to improve N use efficiency of crops and decrease N losses. However, how these practices affect crop N uptake by regulating the fertilizer-N fate during the growing season is not well understood. We conducted a field 15N tracer study to explore the effectiveness of reduced N application, NI, and straw incorporation on fertilizer-N fates for maize cultivation in Northeast China. The following six treatments were used: 1) no N fertilization (control); 2) 200 kg urea-N ha−1 (100%N); 3) 200 kg urea-N ha−1 and 2400 kg dry-straw ha−1 (100%N+S); 4) 160 kg urea-N ha−1 (80%N, i.e., 20% reduction of N fertilization); 5) 160 kg urea-N ha−1 and nitrification inhibitor (Nitrapyrin) (80%N+NI); 6) 160 kg urea-N ha−1, nitrification inhibitor and 2400 kg dry-straw ha−1 (80%N+NI+S). Our results showed that the five N fertilization treatments yielded 16%–25% more grain and 39%–60% more crop N uptake than the control receiving no N fertilizer, but the differences among the five treatments were not statistically significant. In contrast to plant growth, changes in fertilizer-N fates in soil and plant pools were more pronounced. Compared with the 100%N treatment, 20% fertilizer-N reduction (80%N) decreased 15N concentration in topsoil and plant pools but increased the proportion of plant 15N recovery at harvesting (N use efficiency, NUE15N, 60% vs. 50%) (P &lt; 0.05). Nitrapyrin co-application (80%N+NI) delayed soil nitrification and increased soil 15N retention at harvesting (52% vs. 36%), thereby decreasing NUE15N significantly (P &lt; 0.05). Straw incorporation (100%N+S) decreased fertilizer-N retention compared with NI co-application because it promoted NUE15N significantly (P &lt; 0.05). The combined application of NI and straw (80%N+NI+S) was more conducive to fertilizer-N retention in soil. Our findings demonstrate that NI and straw additions are efficient strategies for stabilizing fertilizer-N in soils and potentially minimizing N loss; however, their effects on NUE15N vary and the related mechanism must be further clarified in long-term trials.

As a result of increased energy consumption, global trade has surged, and serious environmental problems have arisen. The problem is made more complicated by the fact that either environmental damage or economic advancement cannot be compromised. The elements contributing to environmental contamination must be identified and dealt with accordingly if we are to have a healthier future. In this study, what causes CO₂ emissions in Malaysia are examined using the Autoregressive distributed lag (ARDL) model using time series data from 1995 to 2020. The paper also examines the impact of energy use and economic complexity on CO2 emissions. Firstly, it is noted that the Environmental Kuznets Curve (EKC) theory holds in Malaysia. Furthermore, energy consumption has a detrimental impact on reducing CO2 emissions. Furthermore, it has been noted that a greater degree of economic complexity leads to an elevated amount of CO2 emissions over an extended period. The findings suggest significant environmental policy implications for reducing CO2 emissions in Malaysia.

Enhancing the management and monitoring of oil and gas processes demands developing precise predictive analytics techniques. Over the past two years, oil and its prediction have advanced significantly using conventional and modern Machine Learning techniques. Several review articles detail the developments in predictive maintenance and technical and non-technical aspects of influencing the uptake of big data. The absence of references for machine learning techniques impacts the effective optimization of predictive analytics in the oil and gas sector. This review paper offers readers thorough information on the latest machine learning methods utilized in this industry's predictive analytical modelling. The review covers forms of Machine Learning techniques used in predictive analytic modelling from 2021 to 2023 (91 articles). It provides an overview of the details of the papers that were reviewed, comprising of the model’s categories, the data's temporality, field, and name, the dataset's type, predictive analytics (classification or clustering or prediction), the models' input and output parameters, performance metrics, optimal model, and benefits and its drawbacks. Additionally, suggestions for future research directions are provided to raise the potential of the associated knowledge and increase the accuracy of oil and gas predictive analytics models.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

Only languages with abundant resources are given the opportunity to build speech recognition systems, whereas low resource languages are disregarded. This project attempts to create a system that can normally convert speech to text in the Myanmar (Burmese) language, a language part of low resource languages. The Burmese language is extremely intricate and is made up of vowels, consonants, tones, and stress. There are 10 numbers, 12 vowels, and 33 letters in the Myanmar alphabet. Deep learning allows for the evolution of numerous algorithms while eradicating ignorance and even low-resource languages may be turned into speech-to-text systems with a small quantity of data. The procedures required to construct a successful speech recognition system that can assist both the corporate sector and society will be covered in this project, including data collecting, preprocessing, modeling, prototyping, assessment, and ultimately deployment.

Rapid urbanization has profoundly impacted regional ecosystem services. However, few studies have comprehensively examined the spatiotemporal relationship between multi-dimensional urbanization processes and ecosystem services. This study investigated the spatiotemporal dynamics of urbanization and ecosystem services value (ESV) in the Yangtze River Delta (YRD) region, China, from 2010 to 2020. We measured urbanization levels from two dimensions: Urbanization I (demographic, economic, and land urbanization) and Urbanization II (social and cultural urbanization). The ESV was quantified using the equivalent factor method. The results showed that: (1) The level of Urbanization I increased steadily, while Urbanization II, despite a lower level, exhibited a faster growth rate, especially after 2017; (2) The total ESV declined, with regulating services decreasing the most. The spatial distribution of ESV showed significant heterogeneity; (3) Urbanization had a significant negative correlation with ESV, with Urbanization I exerting a greater negative impact than Urbanization II; (4) The eastern region was dominated by high urbanization-low ESV clusters, while the western region was characterized by low urbanization-high ESV clusters. The findings provide important implications for regional sustainable development and can serve as a reference for related studies in other rapidly urbanizing areas around the world.

Background: Tourism is one of the prominent industry that has a capability to generate handsome income for developed as well as developing countries. However, the study to investigate specifically the perception of local residents towards tourism is still lacking. The perception of the locals is important since it could determine the extent of their support for tourism development. Plus, previous research found that male residents are more support better towards the tourism development. Thus, this factor is adapted as well in this study to examine whether this gender may influence to the tourism industry. 2) Methods: This study used Structural Equation Modeling (SEM) technique for determining the structural estimates between constructs. 3) Results: The respondents agree that positive perception, negative perception and tourism impact has a significant impact on support for tourism development in which has been recognized as Social Exchange Theory model. Moreover, the finding also revealed that gender has a potential to moderates the causal effect of tourism impact on tourism development. 4) Conclusion: The resident understand the tourism sector could strengthen economic nation but they also want the natural resources should be protected.

As an emerging discipline, Design Morphology, with the advantage of "Form Study", has been integrated with many disciplines, and gradually formed its collaborative innovation paradigm. The inclusion of "Ecology" into Design Morphology is expected to promote the research of Design Morphology with the help of the systematic thinking and methods of ecology. The ecosystem of Design Morphology includes the natural ecosystem and the quasi-ecosystem closely related to human beings, and also put forward the concept of "Form Community" for the first time in the design field. In fact, this is exactly the research scope of Design Morphology. Advocating the ecological view of Design Morphology, can not only help to design researchers improve their values and world view, with new thinking and method to engage in "Form Study", but also contribute to the theoretical construction and thinking expansion of Design Morphology, and play a positive role in promoting interdisciplinary collaborative innovation led by Design Morphology. In addition, it can be used to evaluate the overall research and future development trend of Design Morphology, and provide the new research ideas and approaches for the development of design.

Background: Despite the tremendous effort in hamstring injury prevention, injury rates in soccer remain elevated. Hypothesis: Hamstring and hip/pelvic isometric strength imbalances may increase the likelihood of hamstring strain injury (HSI) occurrence amongst soccer players.Study design: Case-control study.Methods: In 120 male soccer players (mean age: 20.0 +/- 6.96 years) pre-season maximum isometric strength of the hip adductors, abductors, flexors, and knee flexors were measured, and strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. A multivariate and Machine learning-based Logistic Regression model was employed to estimate the likelihood of players sustaining a hamstring injury.Results: 21 players sustained 32 hamstring injuries. Players with higher abduction strength in the dominant leg had an 18.5% lower risk of sustaining a hamstring injury (OR = 0.818, CI 95% = [(0.695-0.964]). No other significant contributor variables were found to be significant predictors of hamstring injury in the player group (p> 0.05).Conclusion: Isometric strength of the abductor muscles in the dominant limb had a significant association with hamstring injury.Clinical relevance: Our findings indicate the utilization of hip strength measurements as an integral component of the pre-season screening assessment, thereby affirming prior research on the correlation between lumbo-pelvic stability and incidence of hamstring injuries. Consequently, clinicians should contemplate incorporating hip strengthening exercises into regular training sessions, rehabilitation programs, and injury prevention protocols especially indicated when lower hip strength levels are observed.

As the primary secondary tree species in Northeast China, Quercus mongolica possesses significant ecological and economic value. This study employed the Biomod2 platform in conjunction with ArcGIS spatial analysis to assess the potential suitable habitat distribution area of Q. mongolica under current climatic conditions. Furthermore, it forecasted the distribution range and niche changes of potentially suitable habitats for Q. mongolica from 2022 to 2090, and pinpointed the key environmental factors influencing its distribution. The findings reveal that the total potential suitable area for Q. mongolica covers 74,994.792 km², predominantly spread across Inner Mongolia, Heilongjiang, Jilin, and other regions. The primary determinants of suitable area distribution were peak temperature of hottest month, lowest temperature of coldest month and altitude. Under future climate scenarios, the potentially suitable habitats of Q. mongolica are anticipated to diminish to varying extents, with the distribution center exhibiting a tendency towards northward migration. Concurrently, the overlap among different climate scenarios is predicted to expand over time. This investigation facilitates a comprehensive understanding of Q. mongolica's adaptation to climate change, enabling informed adjustments and serving as a valuable reference for the preservation and sustainable management of Q. mongolica populations.

In the era of mounting water scarcity, particularly in arid regions, the agricultural sector is striving to optimize the water resource management practices. Treated wastewater (TWW) has emerged as a viable alternative to freshwater for irrigation, offering a sustainable solution to water conservation. However, ensuring the safety and quality of TWW is paramount to safeguard for both crop health and environmental integrity. Electrical conductivity (EC), a critical factor in assessing TWW suitability for irrigation, can significantly impact crop yields and soil health since it is directly linked to the concentration of dissolved salts and ions. Therefore, this study delves into the development of advanced predictive models for EC assessment by employing supervised machine learning (ML) techniques like the Support Vector Regression (SVR), Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR). The TWW samples collected from Al-Qatif area, Saudi Arabia were assessed in the lab through a sensor-based real-time monitoring system integrated with Internet of Things (IoT) network and a multiprobe device. The key water quality parameters assessed involved, temperature (T), pH, Oxidation Reduction Potential (ORP), Resistivity (RES), Total Dissolved Solids (TDS), Salinity and Turbidity which served as the foundation for these models, given their profound influence on and their anticipated impact on EC levels. Following feature selection, two distinct model combinations were identified for the SVR, ANFIS and MLR models. Furthermore, to evaluate prediction performance, four statistical criteria, including coefficient of determination (R²), correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE), were employed. Overall, the comparative performance results proved that ANFIS-M2 indicated the strongest predictive capability with the R² value of 0.99572 and 0.75145 and the RMSE values of 0.00965 and 0.01134, respectively in both calibration and verification stages.

The ecosystem plays a crucial role in mitigating climate change and protecting the environment. This study employs GIS technology to conduct an in-depth analysis of the current status of Queensland's ecosystem and develops a Climate Change Vulnerability Index (CCVI) model based on six sub-factors. These sub-factors include the Exposure Index (Mean surface temperature and precipitation), the Sensitivity Index (Population density, Building density, and Proximity to forests and nature reserves), and the Adaptive Capacity Index (Nighttime light radiation). The findings indicate that the CCVI value is lowest in the southeastern coastal region of Queensland, suggesting that this area is less vulnerable to climate change. However, other coastal areas and the far western inland regions exhibit higher CCVI values, indicating greater climate vulnerability. These areas require attention and the implementation of appropriate measures. By deepening our understanding of exposure, sensitivity, and adaptive capacity, we can formulate effective policies and measures to promote sustainable development and mitigate the negative impacts of climate change on the region. This study holds significant practical implications for guiding ecological planning and management decisions in the area.

Conventional fertilization practices can lead to many ecological problems, such as nutrient imbalance, soil acidity, and reduced soil fertility in natural rubber plantations. To address these challenges, a field investigation was strategically carried out to substitute inorganic fertilizer with organic fertilizers consisted of six treatments, i.e., no fertilization (CK), inorganic fertilizer (NPK), 25 % replacement of inorganic through organic (25%M), 50 % replacement of inorganic through organic (50%M), 75 % replacement of inorganic through organic (75%M), and 100% organic fertilizer (100%M). The soil physicochemical properties (SOC, TN, AN, C:N, pH, NH4+-N, and NO3--N) and carbon and nitrogen converting enzymes (BG, NAG, and LAP) were all determined. The partial substitution of inorganic fertilizers with organic fertilizers (i.e., 75%M at surface soil layer) showed higher SOC (14.52 g.kg-1), TN (1.06 g.kg-1), AN (20.07 mg.kg-1), C:N (14.63), NH4+-N (10.63 mgkg-1), and NO3--N(11.06 mg.kg-1) than NPK and CK. Such increase in physicochemical properties in partial replacement of inorganic with organic fertilizers plots resulted from higher carbon and nitrogen enzymes activities (BG (143.17 nmol.g-1.h-1), NAG (153.96 nmol.g-1.h-1), and LAP (153.48 nmol.g-1.h-1)) compared to NPK and CK, and further the person correlation and RDA analysis confirmed a significant positive correlation between SOC, AN, and soil enzymes. This study presents a new strategy for assessing the impact of partially replacing inorganic fertilizers with organic fertilizers in rubber plantations, mainly by modifying the soil nutrient composition in tropical regions.