The bioactive compound, thymoquinone (TQ), found in Nigella sativa seeds is known for its various therapeutic properties. Thymoquinone (TQ), a bioactive compound found in Nigella sativa seeds, is known for its various therapeutic properties. However, TQ as a compound is challenging for a pharmaceutical formulator due to its hydrophobic nature and chemical instability, limiting its skin penetration. Transethosomes, as a formulation, provide an environment that enhances the solubility of TQ, stability, as well as skin permeation. To optimize TQ transethosomal formulations, we introduced a combination of surfactants namely nonionic Tween 20 and ionic sodium lauryl sulfate (SLS) or sodium lauroyl glutamate (SLG). These surfactants stabilize the formulation, reduce aggregation, and improve biocompatibility, as well as minimizing potential toxicity. Using the Langmuir monolayer technique, we fine-tuned the formulation composition and gained insights into its interfacial behavior. We conducted skin penetration studies using Rhodamine B as a model lipophilic compound to understand the skin penetration mechanisms. Our findings revealed that the transethosomes formulation, a combination of ionic and nonionic surfactants in the F2 formulation, resulted in the smallest particle sizes (115.4 nm) and demonstrated the highest skin permeation after 24 hours (267.13 μg/cm²), surpassing the control and ethosomal formulations. Additionally, this transethosomal formulation exhibited antimicrobial activity against S. aureus, with a zone of inhibition of 26.4 ± 0.3 mm. Importantly, we assessed the cytotoxicity of both ethosomes and transethosomes at concentrations ranging from 3.5 μM to 50 μM on HaCaT cell lines and found no cytotoxic effects in comparison to TQ solution controls. These results suggest the potential safety and efficacy of these TQ formulations and their further development in skin delivery.

Mental healthcare conditions in India are severely deficient, particularly concerning the living conditions of patients. Post-treatment, numerous individuals with mental illness are abandoned by their families, who may lack the willingness or financial means to care for them. These recovered patients often experience setbacks due to the absence of facilities aimed at developing the skills necessary for reintegrating into society. The lack of separate accommodations for recovered individuals forces them to reside with other patients, worsening their condition. The government is struggling to accommodate and finance the care of recovered patients, affecting those in need of treatment as hospital bed space becomes overwhelmed by the increasing number of cured individuals. Therefore, there is an urgent need for halfway homes. These facilities offer a range of services, including social, medical, psychological, and educational support, alongside housing. The term "halfway houses" reflects their position between fully independent living and highly regulated in-patient or correctional facilities. Following treatment, many patients experience abandonment by their families or encounter difficulties returning home due to memory loss. Recovered patients often live in confined spaces, lacking essential social skills. Therefore, establishing a workspace focused on teaching social and other necessary skills before reintegrating them into society would be a beneficial approach. This would provide a structured environment for individuals who have spent significant time in seclusion, assisting them in developing the skills needed to navigate societal challenges effectively. Recent reports indicate that over 2,000 cured patients are still housed in mental hospitals across the country, according to the NHRC. The NHRC has raised concerns about the situation, noting that all 46 Government Mental Healthcare Institutions in India display very poor and inhumane treatment of patients, leading to the issuance of notices. NHRC visits have revealed deplorable conditions in all 46 mental institutes across the country.

The term dehumanisation refers to the ways in which a person is perceived to be less than human or treated as if they are less than human. It involves treating a person as if they are a child or infant, like an animal or non-living object, or as if they are dead, or any other way in which someone fails to be treated like a human being with an adult identity. Dehumanisation is widespread in dementia care; it is a major obstacle to person-centred care and has poor outcomes for people with dementia. This article proposes a new model of dehumanisation. The New Model presents a new way of describing dehumanisation that has been synthesised from current understanding about the phenomenon and reflects what is presently known about the subject. The model aims to summarise existing theories and models of dehumanisation and make dehumanisation theory accessible to students and trainees in healthcare. This article describes the new model, discusses existing models and theories in the literature, and explores the potential role of the new model in solutions for reducing dehumanisation in dementia care.

The implementation of management systems has become a strategic advantage in achieving business goals, especially in industrial organizations, but the implementation of social responsibility requirements is especially ethical. Large multinational companies have long been developing and, in particular, implementing their own codes of conduct, which include their suppliers, to demonstrate their commitment to Corporate Social Responsibility (CSR). The compliance with CSR requirements from stakeholders is thus extended or intertwined with requirements in established management systems (MSs). The objectives of the study were to (1) analyze the different approaches to CSR in internationally recognized cross-industry and industry-specific standards and codes in different industries; (2) select the most appropriate framework for assessing the degree of applicability of CSR in the selected management systems and develop a methodology for its assessment; (3) apply the proposed methodology (referred to as SRIMS) in the selected areas: automotive industry, research organization, and metallurgical industry; (4) through ANOVA, validate its use for assessing the overall level of CSR applicability in an organization's established management systems. The application of the Bonferroni method confirmed the hypotheses that the developed SRIMS model is a sufficiently appropriate tool for assessing the overall level of applicability of CSR requirements to established MSs.

Agriculture is the mainstay of the Ethiopian and a key sector of its economy. However, Lack of productive and environmentally friendly technology is not widely applicable elsewhere. Likewise, the vermicomposting technology is a recently emerging science which not effectively transferred to the users across the country. Thus, this review is aimed to shine the importance, unexploited opportunities and the challenges hindered for further expansions in Ethiopian context. Vermicompost is among the powerful organic fertilizers which enhance soil Fertility and productivity. As agrarian society; there are plenty of raw byproducts and weed species which are not center of focus (i.e cattle waste, crop residues and invasive weeds like P.Juliflora, P.hysterophorus and E.crassipes respectively). However, there are many constraints there like policy issue, handling problems and sensitivity of the worms for different environmental factors which hindered to invest on a wide range. Generally, the number and weight of vermiculture as well as amount of produced casts are promised and every possible ways were recommended to entertain on the large scale.

Mechanochemical production of copper (II) isonicotinate Metal-Organic Framework ([Cu (INA)2]-MOF) and its modified magnetic iron composite ([Cu (INA)2]-MOF@Fe3O4]) allowed for the adsorptive removal of Terbutaline from water. A variety of characterization techniques, including Fourier, transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and scanning electron microscopy (SEM), were used to elucidate the distinct chemical and morphological features of the two advanced materials. The optimal adsorption conditions were determined by investigating a wide range of adsorption-related variables, including contact time, initial Terbutaline concentration, adsorbent dosages pH, and temperature. The chemistry involved in the adsorption process between the adsorbents and the adsorbate molecules was evaluated using the best-fitting models, such as kinetics, isotherms, and thermodynamics, and the regeneration study was performed to evaluate the adsorbents' reusability. Incredibly maximum adsorption capacities (Qmax) of 1667 and 2500 mg L-1 were attained within 40 minutes under alkaline pH 11 by the [Cu (INA)2]-MOF and the [Cu (INA)2]-MOF@Fe3O4, respectively. The adsorbents have been proven to be good for the adsorption of Terbutaline as a priority pollutant in an aqueous solution, with pseudo-first order and Langmuir as the best-fitting models for the kinetic and isotherm models respectively.

This study investigates the prevalence, causes, and spatial distribution of Abandoned, Lost, or Discarded Fishing Gears (ALDFGs) in the Gulf of Gabès, a critical fishing area in Tunisia. Five main fishing gear types—benthic trawls, encircling nets, longlines, gillnets, and trammel nets were analyzed for their loss rates and contributing factors. The study involved extensive surveys among local fishermen using geographic information system (GIS) tools for spatial mapping. The findings reveal varying loss rates among different gear types, with longlines experiencing the highest losses (59%), followed by trammel nets (45%), gillnets (40%), trawls (38%), and encircling nets (36%). Causes of gear loss include entanglement on obstructions, conflicts with other fishing gears, entanglement with marine animals, adverse weather conditions, and intentional dumping at sea. The study highlights the challenges posed by the consistent increase in regional fishing efforts. Spatial distribution mapping indicates two significant concentrations of ALDFGs, correlating with specific fishing activities and depths. The study emphasizes the importance of addressing gear losses as a threat to marine biodiversity and ecosystem health. Recommendations for mitigation include improving boat equipment, raising awareness among fishermen, implementing effective waste management, and exploring economic incentives for ALDFG recovery. This research contributes essential insights for fisheries management, environmental conservation, and sustainable practices in the Gulf of Gabès. Collaborative efforts are crucial to developing and implementing strategies that minimize the impact of ALDFGs on the marine environment while supporting the socio-economic interests of fishermen.

Coating of suitable materials having thickness of few atoms to several microns on a substrate is of great interest to the scientific community. Hard coatings develop under the significant composition of suitable-natured atoms where their force-energy behaviors when in certain transition state favour binding. In the binding mechanism of suitable atoms, electron belonging to outer ring filled state of gas-atom undertakes another clamp of energy knot belonging to outer ring unfilled state of solid-atom. Set process conditions develop the binding of different-natured atoms when processing their suitable composition in a system. Atoms of different nature develop structure in the form of hard coating by locating their ground points between the original ones. Here, gas-natured atoms increase the potential energy under decreasing levitational force of electrons, whereas, solid-natured atoms decrease the potential energy under decreasing gravitational force of electrons. In TiN coating, Ti–Ti atoms bind under the difference of expansion of their lattices, called nets of energy knots, where one atom just lands on the already landed atom. An adhered N-atom to a Ti-atom forms its position among four Ti-atoms where N-atom occupies the interstitial site of Ti-atoms. Two oppositely working force-energy behavior atoms deposit in the form of coating at substrate surface as per set conditions of the process. The rate of ejecting (or dissociating) solid-natured atoms depend on the nature of their source (target), process parameters and processing technique. In random arc-based vapor deposition system, depositing differently natured atoms at substrate surface depends on the input power. In addition to intrinsic nature of atoms, different properties and characteristics of coatings emerge as per engaged forces under their involved energy. The present study sets new trends in the field of coatings involving the diversified class of materials and their counterparts.

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell Acute Lymphoblastic Leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

In its 8th Malaysia Plan (MP*), the Malaysian government has given nanotechnology development a high priority and has been made a Strategic Research (SR) programme. Consequently, an exhaustive and long-term approach is essential. Additionally, specific laws are required to provide an optimal health and safety environment for workers. Consequently, the current study intends to assist Malaysian policymakers in promoting improved safety, risk assessment, and management for nanotechnology workplaces, as well as drafting a comprehensive policy for the recently released DOSH guideline in 2018. Utilizing a unique methodology, this study evaluated the assessment and management of nanotechnology health and safety risks in Malaysia using the international risk governance council (IRGC) framework. In addition to document analysis, n = 20 semi-structured interviews were conducted with representatives of several nanotechnology platforms to collect data that was then analyzed thematically. The research evaluated current workplace safety regulations and laws. Consequently, we propose a future dynamic strategy for Malaysian nanotechnology with more favourable upgrades supported by increased concentrations in the following areas: I policy creation, ii) comprehensive management system, iii) knowledge transfer, and iv) infrastructure management. In addition, the findings highlight the need of cross-sectional communication in bridging existing gaps. This study laid the groundwork for a more systematic and comprehensive health and safety strategy.

With global climate change and resource constraints looming large, sustainable design has become a focus of attention for all industries. The purpose of this study was to investigate the attitudes and behavioural intentions of undergraduate fashion design students towards sustainable fashion practices. Undergraduate fashion design students (n = 441) from three universities in Guangdong Province, China, participated in this survey. By constructing different scales of environmental knowledge, attitude towards sustainable fashion practice and behavioural intention towards sustainable fashion practice, and by using structural equation modelling to analyse the relationship between environmental knowledge and sustainable fashion practice, the following conclusions were drawn: (1) environmental knowledge has a positive effect on attitude towards sustainable fashion practice (p＜0.05); (2) environmental knowledge has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05); (3) Subjective norms has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05). (4) Attitudes towards sustainable fashion practice play a mediating role in the relationship between environmental knowledge and intentions towards sustainable fashion practice behaviour (p＜0.05). The findings of this study have implications for environmental education for undergraduate fashion design students and for sustainable production in companies.

Joining of aluminium alloys to steels has been extensively studied, especially in the automotive sector. However, aluminium alloys are known to be difficult to join with steels when methods involving fusion welding are used because of hot cracking problem. Hence, a high strength joint between these dissimilar metals would be of benefit especially in reducing the weight of products. In this work the torch brazing method was applied to join AR500 steel with AA7075 aluminium alloy using Al-Si-Zn base filler metal at various flame times. The effect of the brazing work on the intermetallic phase formation and the mechanical strength of the joints were investigated. In this work, the maximum shear load obtained was 6460 N and the presence of the intermetallic phases had reduced the shear strength of the brazed joints. However, the torch brazing process using Al-Si-Zn filler metal had successfully facilitated the joining of these dissimilar metals.

Election Algorithm (EA) is a powerful metaheuristics model motivated by phenomena of the socio-political mechanism of the presidential election conducted in many countries. EA is selected as a topic of discussion due to its capability and robustness to carry out complex problems in the random-2SAT logic program. This paper utilizes a hybridized EA assimilated with the Hopfield neural network (HNN) in carrying out random logic program (HNN-R2SATEA). The efficiency of the proposed method was compared with the existing traditional exhaustive search (HNN-R2SATES) model and the recently introduced HNN-R2SATICA model. From the result obtained, clearly proven that based on our proposed hybrid model outperformed other existing model based on the Global Minima Ratio (ZM), Mean Absolute Error (MAE), Bayesian Information Criterion (BIC) and Execution Time (ET). The expected outcome portrays that the EA algorithm outperformed the other two algorithms in doing random-kSAT logic program. The results proved the robustness, effectiveness, and compatibility of the HNN-R2SATEA model.

Bioconvective flows have attracted attention in recent years due to actual and potential applications. In this paper, we consider a steady and laminar convective MHD flow of a nanofluid with heat, mass and microorganism transfer with a heat source/sink present. In addition, we assume there exists a first order chemical reaction. The governing partial differential equations (PDEs) are reduced to ordinary differential equations (ODEs) using the scaling group transformation and the associated boundary value problem is then solved. The influences of selected governing parameters on the dimensionless velocity, temperature, nanoparticle concentration, density of motile microorganisms, skin friction, heat transfer, mass transfer, and motile microorganism density rates are computed and discussed

Purpose: For businesses of all sizes, turnover is a significant issue that has a detrimental impact on organizational performance. This study investigates the variables influencing SME workers' intentions to leave their current employers. This study also examines the moderating effect of organizational commitment on the relationships between attitude, subjective norms, perceived behavioral control, and turnover intentions. Methodology: Six hypotheses were proposed regarding the connections between the initial TPB components and organizational commitment. Results: The PLS-SEM structural path analysis findings revealed that the three fundamental predictors of TPB significantly influence turnover intention, with perceived behavioral control most strongly influencing intention. Furthermore, the results revealed that organizational commitment moderated the relationship between TPB constructs and turnover intention. Practical Implications and Originality: This study used an extended TPB model to introduce fresh perspectives into the literature on SME workers' organizational commitment.

Differentiated instruction has been implemented in classrooms where students who come from various backgrounds require appropriate lessons that are tailored to their varied learning preferences. As the spread of coronavirus 19 (Covid-19) is becoming more rampant, online learning has been lifted up as the main platform of teaching and learning, forcing the need to shift from the conventional face-to-face classroom to online, or virtual, mode of knowledge transfer. Having such global phenomenon affecting education, how does it affect the implementation of differentiated instruction that has been practised regularly by teachers before the wake of Covid-19? Previous studies have shown how it is done in the normal classroom setting, and that the practice of differentiated instruction contributes to students’ motivation as well as academic performance. However, there is a need to explore how do teachers go about with online differentiated instruction and how does it affect the students, since online learning poses various threads to both teachers and students; and thus, one might argue the effectiveness of not only the teaching approach but also the overall teaching and learning outcomes. Borg’s framework of teacher cognition, which has been extensively used in exploring how teachers teach, can be utilized to document the practice of online differentiated instruction. This study aimed to explore the practice of online differentiated instruction by teachers and examined its impact on students’ motivation and academic performance during the Covid-19 outbreak. The participants of this study consists of 247 gifted students from a public school in Malaysia. To meet these aims, this study employed a mixed method research design, utilizing the framework of teacher cognition to explore the teachers’ practice of online differentiated through interviews; and, utilizing a survey design using a questionnaire to determine the impact of online differentiated instruction towards students’ motivation and academic performance. The findings revealed that although online differentiated instruction is feasible, however, appropriate combination of differentiation constructs need to be applied in order to achieve higher motivation and better academic performance among the students.

Nanofibres have gained increasing attention due to their advantages of having a high porous structure, narrow pore size and distribution, and a high specific surface area. One of the most efficient techniques for producing nanofibres is via electrospinning. Nanofibres are currently being used in various fields, including water filtration. Although nanofibres possess the ability to filter various components, the fibres generally have a low mechanical strength that can mitigate the performance over time. Therefore, in overcoming this issue, several studies have focused on improving the strength of the nanofibre membranes for a water filtration application. This review discusses the advantages and challenges of nanofibres for water filtration membranes and summarises the methods to increase the strength of the membranes, including solvent vapour, thermal treatment, and chemical crosslinking.

Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

The aim of this study was to assess the effects of organic fertilisers (cow manure + dung water; cattle slurry) applied in different annual doses of nitrogen (54 kg ha-1; 84 kg ha-1; 120 kg ha-1) according to 3 different intensities of grassland utilisation (extensive – 2 cuts per year, medium intensive – 3 cuts per year, intensive – 4 cuts per year) on percentage of plant functional groups (grasses, legumes, forbs), dry matter yield, and forage quality. The study was performed as a small-plot trial over 7 years on moderately moist grassland in the Czech Republic. The proportion of legumes was significantly higher in the fertilisation treatments with cow manure + dung-water combined with medium intensive utilisation and intensive utilisation (10.2% and 10.3%, respectively). Fertilisation significantly increased dry matter yields by 51.9 % (cow manure + dung water) and 56% (cattle slurry) compared to unfertilised controls (4.81 t ha-1). Grasslands fertilised with cattle slurry showed significantly higher concentration of crude protein (142.9 g kg-1) than unfertilised (126.4 g kg-1). Extensive grassland utilisation significantly increased crude fibre concentration (up to 282.1 g kg-1), and decreased the energy value (up to 4.68 MJ kg-1 of NEL). Organic matter digestibility was negatively influenced by extensive grassland utilisation (61.0%, 65.42 % and 67.44% for the extensive, medium intensive and intensive utilisation, respectively). Our findings suggest that medium intensive and intensive grassland utilisation using organic fertilisation which correspond to annual doses of nitrogen of 84 kg ha-1 and 120 kg ha-1, are the most suitable for animal nutrition.

A biofilm is any syntrophic consortium of microorganisms in which cells adhere to one another and, in some cases, to a surface. These adherent cells become encased in a slimy extracellular matrix made up of extracellular polymeric substances (EPSs). Until now, the use of commercial disinfectants remains the main strategy to control biofilm-mediated problems. This mini review summarizes common antibiofilm mode of actions taken by disinfectants and how water channels in microbial biofilms contribute to disinfectant resistance.

The Kuwaiti dialect is a particular dialect of Arabic spoken in Kuwait; it differs significantly from standard Arabic and the dialects of neighboring countries in the same region. Few research papers with a focus on the Kuwaiti dialect have been published in the field of NLP. In this study, we created Kuwaiti dialect language resources using Q8VaxStance, a vaccine stance labeling system for a large dataset of tweets. This dataset will fill this gap and provide a valuable resource for researchers studying vaccine hesitancy in Kuwait. Furthermore, it will contribute to the Arabic natural language processing field by providing a dataset for developing and evaluating machine learning models for stance detection in the Kuwaiti dialect. The proposed vaccine stance labeling system combines the benefits of weak supervised learning and zero-shot learning; for this purpose, we implemented 52 experiments on 42815 unlabeled tweets extracted between December 2020 and July 2022. The results of the experiments show that using keyword detection in conjunction with zero-shot model labeling functions is significantly better than using only keyword detection labeling functions or just zero-shot model labeling functions. Furthermore, using the Arabic language in both the labels and prompt or a mix of Arabic labels and an English prompt is statistically significant compared to using English in both the labels and prompt for the total number of generated labels evaluation metric. Finally, the best accuracy for Macro-F1 values were found in the experiments KHZSLF-EE4 and KHZSLF-EA1, with values of 0.83 and 0.83, respectively. And, for the total automatically labeled data evaluation metric, experiment KHZSLF-EE4 labeled 42,270 tweets, while experiment KHZSLF-EA1 was able to generate 42,764 labels.

Copernicus is Europe's space-based Earth monitoring asset, which consists of a complex set of systems that collect data from different sources: remote sensing satellites (RS) and in-situ sensors such as ground stations, airborne and marine sensors. This study was originally prepared for the needs of the Czech agricultural community, where we provided an in-depth analysis of articles related to Earth observation in precision agriculture. At a later stage, we extended this study by comparing the recommendations of the European EO4Agri project and scientific articles published in MDPI. We had two important objectives, one was to validate the results of the EO4Agri project and the other was to look for gaps in current research and community needs. To recognize the importance of using Sentinel 1 data, we also added a specific analysis of methods for data fusion of Sentinel 1 and Sentinel 2 data.

The parameters of logistic regression models are usually obtained by the method of maximum likelihood (ML). However, in analyses of small data sets or data sets with unbalanced outcomes or exposures, ML parameter estimates may not exist. This situation has been termed “separation” as the two outcome groups are separated by the values of a covariate or a linear combination of covariates. To overcome the problem of non-existing ML parameter estimates, applying Firth’s correction (FC) was proposed. In practice, however, a principal investigator might be advised to “bring more data” in order to solve a separation issue. We illustrate the problem by means of an examples from colorectal cancer screening and ornithology. It is unclear if such an increasing sample size (ISS) strategy that keeps sampling new observations until separation is removed improves estimation compared to applying FC to the original data set. We performed an extensive simulation study where the main focus was to estimate the cost-adjusted relative efficiency of ML combined with ISS compared to FC. FC yielded reasonably small root mean squared errors and proved to be the more efficient estimator. Given our findings, we propose not to adapt the sample size when separation is encountered but to use FC as the default method of analysis whenever the number of observations or outcome events is critically low.

The modern diet, which consists of food produced with high level of industrial processing, is associated with an increased risk of the development of lifestyle diseases. Current nutritional science is, however, focused on chemical composition of food, and not on the type and degree of processing used during the food production. Here, we take a fresh perspective on the relationship between the extent and type of food processing, and evaluate its impact on consumer health. We argue that the preference for consumption of minimally processed foods, and restriction of ultra-processed foods should be an essential part of a healthy lifestyle, disease prevention, and even treatment. We also present a simple, user-friendly consumer guide, which is intended to be used as a practical, ready-to-go identifier of ultra-processed foods.

A sustainable, scalable source of energy‐dense chemical fuel is urgently needed to ensure the security of our energy supply for future generations. Solar energy is the only renewable energy source of sufficient scale to replace fossil fuels and meet rising environmental demand. Hydrogen is expected to play a key role as an energy carrier in future energy systems of the world. As fossil fuel supplies become scarcer and environmental concerns increase, hydrogen is likely to become an increasingly important chemical energy carrier and eventually may become the principal chemical energy carrier. When most of the world’s energy sources become non-fossil based, hydrogen and electricity are expected to be the two dominant energy carriers for the provision of end-use services. Photocatalytic hydrogen evolution from water by solar energy over semiconductors offers a promising way for clean and renewable production of hydrogen. The TiO2-based materials have received considerable attention in recent years due to their extensive application in photocatalysis for hydrogen evolution. Though TiO2 is the most widely investigated photocatalyst for hydrogen evolution, it still provides low photocatalytic activity due to the wide bandgap that results in photocatalytic activity only under ultraviolet (UV) irradiation. Modification of TiO2 photocatalysts with several transition metals has been extensively studied to extend the absorbance capacity of TiO2 into the visible range. The effect of different photocatalytic deposition and reaction parameters also play major roles in enhancing the photostability of photoanode and increasing the hydrogen gas output, respectively.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Moringa oleifera is a miracle plant with many nutritional and medicinal properties. Chemopreventive value of the combined mixture of moringa leaves and seed residues (MOLSr) at different ratios (M1S9, M1S1 and M9S1) were investigated. MOLSr extracts were subjected to phytochemical screening, antioxidant assays, metabolite profiling and cytotoxic activity on various human cancer cell lines including primary mammary epithelial cells (PMEC). The MOLSr ratio with the most potent antiproliferative activities were used in xenograft mice injected with MDA-MB-231 cell lines for in vivo tumourigenicity study as well as protein and gene expression studies. M1S9, specifically comprised of saponin and amino acid, retained the lowest antioxidant activity and highest glucosinolates content as compared to other ratios. Cell viability decreased significantly in MCF-7 breast cancer cells and PMEC after treatment with M1S9. Solid tumour from MDA-MB-231 xenograft mice was inhibited up to 64.5% at third week after treatment with high-dose M1S9. High-dose M1S9 significantly decreased the expression of calcineurin (CaN) and vascular endothelial cell growth factor (VEGF) proteins as well as the secreted frizzled-related protein 1 (SFRP1) and solute carrier family 39 member 6 (SLC39A6) genes. This study provides new scientific evidence for the chemoprevention properties of MOLSr in breast cancer model.

Low Back Pain (LBP) is one of the most common problems among adults. The usual physiotherapy treatment is to perform physical exercises. However, some LBP patients have false beliefs regarding their pain and they tend to avoid physical movements which might increase their pain and disability. Virtual Reality (VR) has shown to be an effective intervention in improving motor functions and reducing pain perception. Existing VR interventions for LBP rehabilitation were based on a non-immersive VR, whereas to effectively reduce the pain intensity, we need an immersive VR. In this paper, we introduce the development and evaluation of a serious game called RabbitRun with an immersive experience to engage the patients in a virtual environment and distract them from the pain while performing LBP exercises. The initial usability evaluation results suggest that RabbitRun game is enjoyable and acceptable. The game is easy to play and learn and most of the participants are willing to play the game at home. This solution will enhance the rehabilitation outcome since the patients who are suffering from LBP can use the system at their home and train more for long period of time using a smartphone and low-cost virtual reality device such as Google Cardboard.

Patients in intensive care unit often lose a considerable fraction of their gut microbiome due to exposure of broad-spectrum antibiotics and other reasons. Dysbiosis often results in prolonged diarrhea and increase occurrence of multi-drug resistant pathogens in the colon with clinical consequences not yet well understood. Restoring the microbioma by faecal microbial transplantation (FMT) is a plausible therapeutic possibility, so far only documented in case reports and case series using very heterogeneous methodologies. Before FMT in critically ill can be tested in randomised controlled trials, there is a burning need to describe a standardized operating procedure (SOP) of the whole process, respecting the specifics of critically ill population, such as the risk of disrubted intestinal barrier and time critical nature of the procedure. We describe the SOP that has been developed for experimental use in critically ill patients by a multidisciplinary team of intensivists, gastroenterologist and microbiologist based on feedback from regulatory authority (State Institue of Drug Control of the Czech Republic). The hallmarks of these SOPs are multi-donor freshly frozen transplantate quaranteeded for 3 months consisting of 7 aliqutes from 7 unrelated healthy donors, and administered by rectal tube. In this paper we discuss the rationale for this SOP and the process of its development in details and release the full proposed SOP is in the form of online appendix.

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 Ranau Earthquake that struck on 5, June 2015 and follow by February 2018 and April 2021, were a new disaster in Sabah and caused many Sabahan to panic. The unpredicted disaster also caused a serious impact on all aspects of life in Sabah. The earthquake has caused severe damage to eight primary schools in the vicinity of the epicenter; although no casualties were reported. However, the disaster has passing deep psychological effects among students. In this study, we examine how the primary school teachers enabled the student to be resilient during and after the disaster. Based on the interviews of 16 primary school students it was revealed that most of the teachers used WhatsApp to support resilience during and after the earthquake. Interviews with 16 primary school teachers revealed there were two main reasons for them to communicate with students namely, delivering emotional aid and monitoring their stress. Based on student interviews, five content categories of emotional support were identified: caring, reassuring, emotion sharing, belonging, and distracting. The main contribution of this study is social media can be used as a spontaneously and proactive tool to support student's resilience during and after the earthquake trauma.

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R² = 87.4% and R²=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

Global waste generation keeps increasing over the year and requires innovative solutions to minimize their impacts on environmental quality and public health. Predicted 2.2 billion tonnes per year of global municipal waste generation in the year 2025 which 1.6 fold is higher than in 2012. Hence, a strategic plan must be ascertained to overcome the future challenges of MSW locally and globally. Universiti Putra Malaysia (UPM) coined an initiative to demonstrate a showcase pilot plant for green energy production from MSW. Therefore, the data was obtained from the survey and actual sampling within the UPM compound to estimate the MSW generated and it's potentially used for green energy production. It is estimated that 5.0 – 7.0 tonne per day of MSW generated which about 30 - 35% is an organic fraction. Upon separation, the organic fractions were digested into biogas through anaerobic. At the maximum conversion of organic fraction, about 775 kWh of electricity may able to generate from the waste. In this study, the complete biorefinery setup and utilize organic components from the MSW generated in UPM was proposed that the biogas subsequently will be used to produce green energy in the form of electricity or cooking fuel.

Populaces are prominent indicators of livability in creating ‘street life’ for cities and public spaces. Evaluating people’s experiences is significant in creating a city liveliness and urban heritage trail. The exploration of design strategies that could allow them to integrated and connected with other spaces in the context of city and heritage as well as creating a social life among them. The measuring variables are people’s experience on the spaces; thus, create the pattern of behavior, which cause spaces liveliness, using Kuala Lumpur Heritage Trail as an example of pedestrian priority streets, city environment and heritage value. The aim of this research is to evaluate people’s experiences and analyze their behavior towards the urban street design within cities environment and Malaysia heritage values. The analyzed review comprising on the livability of the street in the context of interrelation between behavioral patter of people and the preferences of urban heritage. Hence, this paper will give an understanding of how people experiences the presence of urban streets and heritage values, thus, bringing liveliness to the streets.

Electron Channeling Contrast Imaging (ECCI) is becoming a powerful tool in Materials Science for characterizing deformation defects. Dislocations observed by ECCI in Scanning Electron Microscope, exhibit several features depending on the crystal orientation relative to the incident beam (white/black line on a dark/bright background). In order to bring new insights concerning these contrasts, we report an original theoretical approach based on the dynamical diffraction theory. Our calculations led, for the first time, to an explicit formulation of the backscattered intensity as a function of various physical and practical parameters governing the experiment. Intensity profiles are modeled for dislocations parallel to the sample surface for different channeling conditions. All theoretical predictions are consistent with experimental results.

Extensive research has been conducted on printable antenna technologies, believed to be fast-growing due to their significant impact on wireless devices. It is necessary to study the progress of printable antenna technology as they are core devices for wireless technology today. This review work offers a comprehensive account of the previous and recent research achievements based on the principle of printable antenna, and parametric studies of several key design parameters, for future wireless network applications. The systems considered for evaluation include broadband techniques, large Bandwidth, high gain, dual/multi-band, or reconfigurable structure, low-profile, size-reduction, compact, linear, or circular polarization applications. It also highlights the fabrication procedures, and the numerous material characteristics affecting the antenna performance for various wireless applications with design considerations. Fully printed antennas on different substrates and conductive ink were investigated, including polyethylene terephthalate (PET), synthetic paper (Teslin), resin-coated photo paper, and Kapton polyimide substrates, among many others. The findings show that the fully inkjet-printed antenna made fabrication easy, improving the accuracy and conductivity of the printed patterns by concentrating on the inherently difficult problems and opportunities. Inkjet-printed antennas are believed to be the futuristic demand for sustainability and wireless solution in several ways.

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.

Abstract: Heavy metals (HMs) contamination is one of the main among abiotic factors affecting crop productivity and also threatens human health via consuming metal contaminated crops as a food source. Over the past few years, HMs have drawn a lot of attention due to their increased use for commercial purposes and their harmful effects on plants and other life forms, thus threatening human survival. However, in recent years, several methods have been adopted to combat the harsh effects of HMs. After phytohormones, use of mineral nutrients such as selenium (Se) in the prevention of HM stress has been explored by the researchers more recently. Selenium is an important micronutrient widely known for its antioxidant properties in both plants and animals. Exogenous Se inhibits metal uptake and its translocation and also improves the antioxidant system, thus imparts resistance to HM toxicity in plants. Moreover, Se also regulates the production of various osmolytes in cells that helps in developing cell osmolarity. Selenium also induces the production of different types of secondary metabolites (SMs) that are also involved in plant's secondary defense mechanisms to different stresses. Uptake of mineral nutrients is a vital process for plant growth and development, which is also positively correlated with Se under metalloid toxicity. However, in order to understand the exact mechanism of Se in HM tolerance, different metabolic processes stimulated by Se and their pathways need to be explored. Hence, this review focuses on the role of Se on nutritional status, antioxidants metabolism, interaction with phytohormones and its role in the regulation of various genes involved in Se induced HM tolerance. Thus, this study will help researchers in the future for the improvement of HM tolerance via Se application in plants.

Abstract: The effect of some weather parameters (rainfall and temperature) on the production of oil palm in Peninsular Malaysia was investigated. Data were analysed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, time series analysis, and multiple linear regression (MLR) carried out. SPSS and Microsoft Excel 2010 were used to analyse the results. The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature and rainfall (independent variables). The regression output returned three components; regression coefficients, regression statistics and ANOVA. The findings of the study revealed medium to high rainfall variability at the rate of 0.0008. This implies that rainfall is increasing over time with variations in its amount and intensity. As rainfall increases oil palm FFB production is predicted to increase at a slow rate of 0.0009. The estimation of average annual temperature indicated an increase of 5.6℃ at the rate of 0.0357℃ per year with a temperature maximum of 32.01℃ and minimum of 25.45℃. The result also revealed an increase in oil palm yield at the rate of 0.2581 per year with a mean value of 176247.6. Overall, there is a significant difference in the impact of rainfall and temperature on oil palm yield. This signifies that rainfall has a significant impact on oil palm yield (FFB) compared to temperature.

In this study, the effects of music therapy on anxiety for patients undergoing regional anaesthesia in an operating room was succinctly investigated. This investigation was largely based on the adapted Hospital Anxiety and Depression Score (HADS) and Spielberger State-Trait Anxiety Inventory (STAI-S), of patients undergoing regional anaesthesia in an operating room. A randomized control trial was performed on 90 patients due for surgery. The selected patients for regional anaesthesia were allocated to either the music therapy group who listened to music using headphones for the entire surgery or the no-treatment control group. Based on the findings, it has been conclusively demonstrated that music can decrease the patient's anxiety level. According to the socio-demographic evaluation, elderly patients have the highest stress hormones levels when compared to young patients. Although elderly patients are more likely to choose religious songs to help them relax, cortisol analysis revealed an increase in cortisol levels among the elderly compared with younger patients. As a result, music is especially important to be delivered to elderly patients. Nonetheless, there is no restriction against administering music to elderly patients because evidence from the Hospital Anxiety and Depression Score (HADS) and State-Trait Anxiety Inventory (STAI-S) has shown that music helps to shift their attention away from pain and complications and makes them feel tranquil. Similarly, the HADS and modified Spielberger STAI (STAI-S) analyses demonstrate a substantial outcome for both groups, with respondents responding positively. The study found that listening to music during regional anaesthesia might help people feel less worried.

LCK, a member of the Scr kinase family, is a non-receptor tyrosine kinase involved in immune cell activation, antigen recognition, tumor growth, and cytotoxic response. The enzyme has usually been linked to T lymphocyte activation upon antigen recognition. Lck activation is central to CD4, CD8, and NK activation. However, recently, it has become clearer that activating the enzyme in CD8 cells can be independent of antigen presentation and enhance cytotoxic response. The role of Lck in NK cytotoxic function has been controversial in a similar fashion as the role of the enzyme in CAR T cells. Inhibition of Lck has been mainly to treat hematologic malignancies with a high rate of success. They may be useful in treating other tumor types, and they may be useful to prevent cell exhaustion. New, more selective inhibitors have been documented, and they have shown inter-esting activities not only in tumor growth but in the treatment of autoimmune diseases, asthma, and graft vs host disease. Drug repurposing and bioinformatics can aid in solving several unsolved is-sues on the role of Lck in cancer. In summary, the role of Lck in immune response and tumor growth is not a simple event and requires more research.

Heavy metals pollution in the Straits of Malacca warrants the development of rapid, simple and sensitive assays. Enzyme-based assays are excellent preliminary screening tool with near real-time potential. The heavy-metal assay based on the protease ficin was optimized for mercury detection using Response Surface Methodology. The inhibitive assay is based on ficin action on the substrate casein and residual casein is determined using the Coomassie dye-binding assay. Heavy metals strongly inhibit the hydrolysis. A Central Composite Design (CCD) was utilized to optimize detection. The results show a marked improvement for the concentration causing 50% inhibition (IC50) for mercury, silver and copper. Compared to One-factor-at-a-time (OFAT) optimization, RSM gave an improvement of IC50 from 0.060 (95% CI, 0.0300.080) to 0.017 (95% CI, 0.0160.019), from 0.098 (95% CI, 0.0770.127) to 0.028 (95% CI, 0.0220.037) and from 0.040 (95% CI, 0.035.045) to 0.023 (95% CI, 0.0200.027), for mercury, silver and copper, respectively. A near real-time monitoring of mercury concentration in the Straits of Malacca at one location in Port Klang was carried out over a 4-h interval for a total of 24 h and validated by instrumental analysis with the result revealing an absence of mercury pollution in the sampling site.

As people grow a custom to effortless outdoor navigation there is a rising demand for similar possibility indoors as well. Unfortunately, indoor localization, being one of the necessary requirements for navigation, continues to be problem without a clear solution. In this article we are proposing a method for an indoor positioning system using a single image. This is made possible using small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with SIFT algorithm we can look through the database and find image which is the most similar to the image taken by user. Pair of images is then used to find coordinates of database image using PnP problem. Furthermore, projection and essential matrices are determined allowing for the user image localization ~ determining the position of the user in indoor environment. Benefits of this approach lies in the single image being the only input from user and no requirements for new onsite infrastructure and thus enables a simpler realization for the building management.

(1) Background: Newer generation ophthalmologists practicing in the developed world are not very familiar with some tropical ocular diseases due to the absence of reports in the ophthalmic literature over the past thirty years. Because of world globalization or due to influx of immigrants from Sub Saharan Africa, exotic retinal diseases are being encountered more often in ophthalmology clinics; (2) Methods: Case series of chorioretinitis or optic neuritis with obscure etiology; (3) Results: 4 cases qualified with the diagnosis of ocular onchocerciasis based on their residence near fast rivers in endemic areas, multimodal imaging, long term follow-up showing progressive disease and negative workup for other diseases. Characteristic findings include peripapillary choroiditis with optic neuritis or atrophy, subretinal tracts of the microfilaria, progressive RPE atrophy around heavily pigmented multifocal chorioretinal lesions of varying shapes and subretinal white or crystalline dots. Typical skin findings are often absent in eyes with chorioretinitis rendering the diagnosis more challenging; (4) Conclusions: Familiarity with the myriad ocular findings of onchocerciasis, and a high degree of suspicion in subjects residing in endemic areas can help in the correct diagnosis and implementation of appropriate chemotherapy. Onchocercid chorioretinitis is a slow insiduous progressive and prolonged polymorphous disease.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, characterized by fluid-filled sacs in the ovaries and various symptoms including high androgen levels, endometrial irregularities, and cysts. While the cause of PCOS is unknown, it has been linked to genetic, endocrine, and metabolic factors, and there are several treatment options, including lifestyle modifications, medications, and surgery. Natural products, such as medicinal plants and fruits, are being explored as potential treatments for PCOS due to their bioactive compounds with pharmacological effects related to antioxidant, antimicrobial, anticancer, and antidiabetic properties. Some of these compounds improve insulin sensitivity, reduce inflammation, and enhance glucose metabolism, which is beneficial for women with PCOS. This review examined the effects of natural products on PCOS, including their effects on ovarian histological changes, blood glucose, sex hormones, and lipid profile, based on animal and human studies. This study suggests that the use of natural products as complementary medicine can be a promising resource for the development of effective therapeutics for PCOS, but that further research is needed to fully understand their benefits

Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for augmenting farmers the concentration and composition prediction-based crop nutrient recovery. This captures the holistic representation of crop characteristics, considering the intricate relationships between environmental factors, nutrient concentrations, and crop compositions. However, the complexity arising from diverse soil and environmental conditions makes nutrient content analysis expensive and time-consuming. This paper presents the result of a predictive digital twin case study that employs six regression algorithms namely Elastic Net, Polynomial, Stepwise, Ridge, Lasso, and Linear Regression to predict rice nutrient content efficiently, particularly considering the coexistence and composition of multiple nutrients. Our research findings highlight the superiority of the Polynomial Regression model in predicting nutrient content, with a specific focus on accurate nitrogen percentage prediction. This insight can be used for nutrient recovery intervention by knowing the precise amount of nutrient to be added into the crop medium. The adoption of the Polynomial Regression model offers a valuable tool for nutrient management practices in the crop digital twin, potentially resulting in higher-quality rice production and a reduced environmental impact. The proposed method can be replicable in other low-resourced crop digital twin system.

The rural road landscape is crucial in forming rural areas' landscape character (LC). As a platform for portraying the rural landscape, the rural roads demonstrate the area's unique natural and cultural characteristics to the visitors. However, with the continuous development of rural areas, the rural LC has been severely impacted, thus impacting visitors' visual experience. In order to preserve and protect the rural landscape, this study aims to assess the visual quality of rural road landscapes based on public preference and heatmap analysis. The results indicated that most of the participants had a higher level of preference for rural landscapes with open horizontal views represented by agricultural areas such as paddy fields. It was also found that different paddy field characters based on their planting stages can also positively affect the visual quality of rural road landscapes. The study also revealed that rural LCs with roadside settlements, commercial structures, mixed agricultural crops, and vegetation received low preference ratings. These characters negatively impact the visual quality of the rural road landscape. These findings provide significant insight for planners and decision-makers regarding protecting and preserving the essential rural road landscapes for the rural tourism experience.

Ag/TiO₂ thin films were prepared using the sol-gel spin coating method. The microstructural growth behaviors of the prepared Ag/TiO2 thin films were elucidated using real-time synchrotron radiation imaging, its structure determined using grazing incidence X-ray diffraction (GIXRD), its morphology imaged using the field emission scanning electron microscopy (FESEM), and its surface topography examined using the atomic force microscope (AFM) in contact mode. Cubical white spots were detected, identified as Ag, while the TiO₂ thin film resembles a porous ring-like structure with each ring coalescing and forming channels. Junction growth is directly proportional with time under continuous heating conditions (annealing), and its growth orientations and patterns were seemingly random.

The new emergence and re-emergence of arbovirus infections vectored by Aedes mosquitoes have been spread across Southeast Asia, Central Africa, United States, tropical Oceania and become a major of public health concerns. These arbovirus diseases found to have a similar vector, symptoms of the diseases and environments. The situation has become complicated without any specific vaccine or treatment for the diseases. As far as we concern, vector control is the best defense with many challenges, a scattered breeding site and biological behavioral sometimes, more difficult to control. Herein, we present a review of studies on current techniques proposed to combat arbovirus infections vectored by Aedes mosquitoes. A crucial gap in a vector control program is the inability to eliminate and destroy the cryptic breeding site by using conventional control methods. The idea and proper concept of using mosquitoes to bring insecticide to their oviposition site had been getting more interest in people to explore. Autodissemination is a self-delivery technique by manipulating the behavior of mosquitoes, carrying the insecticide and disseminate to cryptic breeding sites. This technique has shown a promising result in some countries and can be considered as additional tools in a vector control program

Gender recognition is trivial for physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during the stepping exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SMO). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Nazarloo's work (90.34%) and other classifiers.

Claudins are a family of 27 proteins that have an important role in the formation of tight junc-tions. They also have an important function in ions exchange, cell mobility, and in in the epitheli-al-to-mesenchymal transition, the latter being very important in cancer invasion and metastasis. Therapeutic targeting of claudins has been investigated to improve cancer outcomes. Recent evi-dence shows improved outcomes when combining monoclonal antibodies against Claudin 18.2 with chemotherapy for patients with gastroesophageal junction cancer. Currently Chimeric anti-gen receptor T-cells targeting Claudin 18 are under investigation.

This study aimed to characterize the antioxidant, mechanical and physical properties of chicken skin gelatin/CMC/Centella asiatica blended film. The influence of Centella asiatica at 0.3% and 0.7% on antioxidant activities; mechanical properties and physical properties of chicken skin gelatin/CMC/Centella asiatica film were investigated. Characterization of the blended films with 0.7% Centella asiatica extract shows higher antioxidant activities with a total phenolic content of 0.36 mg/g of GAE, DPPH of 89.26%, and reducing power of 0.80 nm compared to 0.3% Centella asiatica extract. The addition of 0.3% of Centella extract provide higher value in tensile strength (5.0 × 10⁻² MPa), elongation at break (281%), melting point (131.31 °C), transparency (0.86) but lower UV-light penetration. While the addition of 0.7% Centella extract contribute to higher value in WVP (1.13 × 10⁻⁴ g m⁻¹s⁻¹Pa⁻¹) and puncture test (0.06 N). There are no significant differences between functional groups obtained from this blended film as evaluated by FTIR analysis (p > 0.05). Furthermore, XRD analysis showed the addition of extract decrease the crystallinity of film. In conclusion, the incorporation of Centella asiatica extracts on film greatly increased antioxidant levels and improved some of the mechanical and physical properties of the film blends.

Phage, which is often used therapeutically, has begun to receive interest as an alternative to antibiotic growth promoters (AGPs) to enhance chicken growth. Another option that has been extensively studied as a growth promoter in chicken is probiotics. However, there are no studies using phages and probiotics as prospective feed additives for broiler chickens. Therefore, this study demonstrated the effects of phage cocktail, probiotics and their combinations on growth performance and gut microbiota of broiler chickens. A total of 288 one-day-old male Cobb 500 broilers were randomly allotted to 1 of 6 treatments in a completely randomised design. The treatments were: (i) C (basal diet (BD) only), (ii) 1ɸ (BD + 0.1% phage cocktail), (iii) 2ɸ (BD + 0.2% phage cocktail), (iv) P (BD + 0.1% probiotic), (v) 1ɸP (BD + 0.1% phage cocktail + 0.1% probiotic), (vi) 2ɸP (BD + 0.2% phage cocktail + 0.1% probiotic). The 1ɸP treatment had significantly (P < 0.05) better BW (35 d), BWG (22 – 35 d, 1 – 35d), and FCR (1-21 d. 22-35 d, 1-35 d) compared to C. Unique gut microbiota diversity was also found between the ɸP (1ɸP and 2ɸP) and non-ɸP groups (C, 1ɸ, 2ɸ and P) in ilea, particularly in the 35 d chickens. Microorganisms associated with short-chain fatty acid (SCFA) producers were significantly (P <0.05) present in the ɸP group than in the non- ɸP group. The carbohydrate and amino acid metabolism predicted genes were significantly upregulated in ɸP groups compared to non- ɸP groups. These genes were involved in the digestion and absorption of nutrients as well as the production of energy. Our findings showed that 1ɸP treatment could be a potential alternative to AGPs for poultry where growth performance was enhanced, and gut microbiota was positively modulated.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

The neurovascular niche is crucial for constant blood supply and blood-brain barrier (BBB) function and is altered in a number of different neurological conditions, making this an intensely active field of research. Brain vasculature is unique for its tight association of endothelial cells with astrocytic endfeet processes. Separation of the vascular compartment by centrifugation-based methods confirmed enrichment of astrocytic endfeet processes, making it possible to study the entire vascular niche with such methods. Several centrifugation-based separation protocols are found in the literature; however, with some constraints which limit their applicability and the scope of the studies. Here, we describe and validate a protocol for physically separating the neurovascular niche from the parenchyma, which is optimized for smaller tissue quantities. Using endothelial, neuronal and astrocyte markers, we show that quantitative Western blot-based target detection can be performed of both the vascular and parenchymal fractions using as little as a single mouse brain hemisphere. Validation of our protocol in rodent stroke models by detecting changes in serum albumin signals and astrocyte activation, i.e. increased glial fibrillary acidic protein expression, between the ipsilateral and the lesion-free contralateral hemisphere demonstrates this protocol as a new way of detecting BBB breakdown and astrogliosis, respectively.

Genetic disorders are preeminent determinants of infant mortality. The inherited pediatric-onset genetic disorders have consequential stress on child growth and development: several congenital, complex and rare disorders with indistinguishable clinical symptoms where diagnosis always remains a challenging task. Traditional diagnosis methods include biochemical tests followed by chromosomal microarray and sequencing of a single gene or panel of genes. These methods had several limitations, but with the advent of whole-exome sequencing (WES), genetic testing has become cost-effective and transformative. Exome sequencing has been known for its effectiveness, which appropriately elucidates and distinguishes the heterogeneous disorders to avoid misdiagnosis and decode the underlying genetic alterations. WES has led to discovering genes and genomic variants in a broad spectrum of diseases, including autism, epilepsy, congenital heart diseases, neurodevelopmental diseases, cancer, nephrotic disorders, neural tube defects and fetal structural anomalies. WES is significant in producing immense genomic biomarkers that can be made as appropriate pharmacogenomic targets for drug therapy. In this article, we analyze the recent exploration of WES technology to revolutionize not only the process of genetic variation and disease detection but also the convention of preventative and targeted drug discovery.

Microalgae are known as a rich source of bioactive compounds which exhibit different biological activities. Increased demand for sustainable biomass for production of important bioactive components with various potential especially therapeutic applications has resulted in noticeable interest in algae. Utilization of microalgae in multiple scopes has been growing in various industries ranging from harnessing renewable energy to exploitation of high-value products. The focuses of this review are on the isolation of bioactive compounds from microalgae regarding different metabolites which are currently used and new possible applications of the compounds in industries and future prospects. Moreover, this work discusses the advantage, potential new beneficial strains, applications, limitations, research gaps and future prospect of microalgae in industry.

A Zn(II) perchlorate complex has been prepared and characterized by single X-ray crystallography, nuclear magnetic resonance spectroscopy, thermogravimetric analysis, infrared spectroscopy, elemental analysis, and UV-vis spectroscopy. The complex crystallizes in the monoclinic space group P21/c (Z = 4) with a pentacoordinated zinc center. Interestingly, the Zn complex was found be to a potential fluorophore that could sense acetone and other ketones with high selectivity and sensitivity.

While there has been a tremendous decline in malaria disease burden in the remote parts of the Malaysia, little is known about malaria incidence in its urban localities. This study aimed to analyse trends of malaria cases in urban Kuala Lumpur, Malaysia. All suspected cases presented to a university hospital in Kuala Lumpur from January 2005 to December 2020 were examined by microscopy. Infection status was analysed using descriptive statistics and curve estimation analysis. Of 3105 blood films examined, 92 (3%) were microscopically confirmed malaria cases. Plasmodium vivax infections accounted for the majority (36.9%) of all malaria cases. Nearly half (47.8%) of cases were found among foreign cases (P&lt;0.001). The majority of foreign cases were males (86.4%) and came from Southeast Asian countries (65.9%). Curve estimation analysis showed significant decreases of malaria cases due to P. vivax (R2 = 0.598; P&lt;0.001) and Plasmodium falciparum (R2 = 0.0259, P = 0.029), but increase for Plasmodium knowlesi (R2 = 0.325, P = 0.021) during the 16 years. This study revealed that malaria incidence in urban Kuala Lumpur is low and has remained stable since 2005. However, P. knowlesi played a significant role in the increase of overall malaria in the area, highlighting the importance of continued vigilance and improved surveillance.

Assessment of stigma among cancer patients is of utmost importance as stigma may lead to various psychological sequelae and lower quality of life. This study aimed to translate the English version of the Shame and Stigma Scale (SSS) into Malay and validate the Malay version of the SSS (SSS-M) among cancer patients in Malaysia. Initially, concurrent translation and back translation of the SSS-M was performed, and face and content validity were assessed. Then, the SSS-M was administered to a total of 234 patients of mixed types of cancer to assess its reliability (internal consistency and test-retest reliability), construct validity (convergent and discriminant validity), exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The SSS-M total score registered good internal consistency (Cronbach’s α of 0.886) and test-retest reliability (intraclass correlation coefficient of 0.846, p < 0.001). EFA and CFA confirmed that the SSS-M consisted of 20 items in 5 domains. Its convergent and discriminant validity were achieved. Hence, the SSS-M demonstrated good psychometric properties and is available for use to assess stigma among cancer patients in Malaysia.

Biogenic emission can have significant impact on atmospheric chemistry. Isoprene (C5H8) is known as the most predominant volatile organic compound and its emission is highly dependent on temperature and light (solar radiation). This study aims to investigate future changes of isoprene emission under climate change scenario. The Southeast Asia (SEA) region is home to 15% of the world’s tropical forest, and the biogenic emission from this region can have significant effect on the global climate chemistry. Three climate change scenarios (RCP4.5, RCP6.0 and RCP8.5) were used to drive climate change simulation in 2013 (baseline), 2030 (near-future), 2050 (mid-century), 2070 (post-mid) and 2100 (end of century) using the Weather Research Forecasting (WRF v3.9.1) model. The Model Emission of Gases and Aerosol from Nature (MEGAN v2.1) was then used to simulate isoprene fluxes using climate output datasets from the WRF model. This study highlights that the projected mean surface temperature and PAR (photosynthetic active radiation) were higher in July than in January. Towards the end of the century, the overall surface temperature and PAR over the SEA region is expected to increase by 0.9℃ - 2.1℃, and 7.6 W m-2 – 12 W m-2 under all RCPs. The all-time high isoprene emitters are Borneo and Papua Island. Meanwhile, the projected increment of isoprene emission over this region is between 10 – 14%, 15-30% and 29 – 53% for RCP4.5, RCP6.0 and RCP8.5, respectively. Our result concludes that the total isoprene emission was higher during July, consistent with the high surface temperature and PAR. The results also agreed with the hypothesis of high isoprene emission over the region that has oil palm plantation. Thus, challenges in dealing with future emissions of isoprene in SEA are closely tied to future climate policies to limit the warming of the atmosphere over this region and the land-use conversion of palm oil plantations.

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.

Biofilm-associated proteins (BAPs) are important in the development and resilience of biofilms, which are intricate populations of microbes protected by extracellular matrix. All members of the BAP family are known to possess common characteristics such as high molecular weight and a signal sequence for extracellular secretion. It has been shown that BAPs are directly linked to the pathogenicity of many bacteria. This mini review highlights several potential strategies to target BAPs for drug development.

This chapter is written for the welfare of the society, questioning and enlightening the effects of the increment or decrement in the percentage of quality of air causing pollution due to the rise in the traffic post-lockdown due to COVID-19 in metro cities, specifically in Delhi. In this chapter, we address the question about people's preference in moving in the shared taxis to their workplaces or their reluctance and denial of the idea of moving in the shared vehicle because of the fear of getting infected. The sensitivity of the situation will compel the people to move in a single occupied vehicle (SOV). The rise in the number of vehicles on the roads will result in traffic jams and different kinds of pollution where people battling with the pandemic will inevitably get exposed to other health-related issues. We use a BPR (Bureau of Public Roads) model to combat this issue endangering the environment and public health. We exploit the BPR function to relate average travel time to the estimated number of commuters travelling by car. We collect mode share data from the NITI Ayog, the State Resource Centre and other authentic sources, which gives unique figures of the impact of shared mobility in India and how, in its absence, various sectors will get affected. Using the given data and the BPR, we evaluate increased vehicle volumes on the road if different portions of transit and carpool users switch to single-occupancy vehicles and its effect on multiple other factors. Based on the study of densely populated city, Delhi, we predict that cities with significant transit ridership are at risk for extreme traffic and pollution unless transit systems can resume safe with effective protocols.

The recent happenings in the world such as flood and wild forest fire were as a result of climate effect as being envisaged by scientists. It is urgent now to adopt a source of energy that will eliminate this effect on our universe. Solar energy is the major energy means that is abundant which could be utilized. In this review, the prospects of solar energy exploration were studied in Nigeria which include assessments, economic viability and hybrid systems. Findings show higher potential in the North as compared to the Southern region. Additionally, potential of offshore solar energy system was simulated by considering 2002, 2003 and 2004 data sets from Era5-land base. Their monthly mean, seasonal changes and annual mean value were estimated. The algebraic annual solar radiance for 2002, 2003 and 2004 were 34,914.732 kWh/m2, 33,898.316 kWh/m2 and 34,338.324 kWh/m2. Suggestions were made due to the present status of solar energy utilization that will enhance its maximum usage and development. One of these is the establishment of a functioning financial scheme and the database for all renewable energy systems. When all these are put in place, the energy supply will increase, climate effect will be reduced, and the economy will be boosted.

Increase demand for palm oil production has indirectly increased waste and pollution. Empty fruit bunch (EFB), which is the major solid waste from this industry, has the potential to be further treated into valuable product. In this study, cellulose will be extracted from EFB through alkali treatment and acid hydrolysis treatment with a different approach and further modified via acetylation and silylation technique. The modified samples are to be utilized to reduce pollution due to palm oil mill effluent (POME) and carbon dioxide (CO2) emission from the industry. The characterization of the extracted and modified cellulose was carried out using attenuated total reflectance-Fourier transform infrared (ATR-FTIR), thermogravimetric analysis (TGA) and scanning electron microscope (SEM). ATR-FTIR analysis revealed that the cellulose was successfully extracted from raw EFB and the cellulose-acetyl, nanocrystalline cellulose (NCC) and cellulose-2 has been successfully modified from the cellulose. TGA analysis shows that both modified cellulose have higher thermal stability compared to raw EFB and extracted cellulose. SEM morphology of the modified cellulose shows a higher surface area due to the wrinkled formation while the wax layer and cuticle pore has been diminished clearly. The modified sample gave a significant performance where cellulose-acetyl absorbed 98.5% of oil compared to unmodified cellulose-1 sample that only absorbed 5% of oil from POME. NCC-AEAPDMS adsorbed physically and chemically 3.5 cm3/g CO2 gas compared to NCC sample, which undergoes only physical adsorption with maximum capacity up to 2.4 cm3/g. Thus, modification can enhanced the performance of cellulose for industrial applications.

The effect of SARS-CoV-2 pandemic has been subsided significantly following the rapid development of vaccine. However, patients with cancer and immunosuppressed state, who are more prone to mortality and morbidity due to this infection, were excluded from majority of the vaccine trials. Moreover, suggested dose modification for cancer and immunosuppressed patients are often not followed because of lack of awareness or unavailability of vaccination schedule. This review will try to bridge this knowledge gap by summarizing the current suggestions of dose modification of COVID-19 vaccine for patients with cancer and immunosuppression.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densi- ties and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on dierent set of true values. Some real data sets were employed to show the usefulness and exibility of the model which serves as generalization to many sub-models in the elds of engineering, medical, survival and reliability analysis.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densities and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on different set of true values. Some real data sets were employed to show the usefulness and flexibility of the model which serves as generalization to many sub-models in the field of engineering, medical, survival and reliability analysis.

Remanufacturing is a way for product recovery initiative and maintaining sufficient production flow to satisfy customer demand through circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chain vulnerable to disruptions. Among the disruptions that usually occur is the shortage in spare parts supply, which causes unexpected delay in production and possible loss of sales. In the face of potential disruption, it is essential for remanufacturing facilities to manage their supply chains in an optimum manner as to decrease the adverse impact of disruptions to their business. In this study, a two-stage production-inventory system is analysed by developing a cost-minimisation model focusing on the recovery schedule after a disruption occurrence in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch and bound algorithm. Through numerical experiments, the results indicate that the optimal recovery schedule and the number of recovery cycles are significantly dependant on disruption time, lost sales and backorder costs. Moreover, a sensitivity analysis shows that the lost sales option seems to be more effective than the backorder option in optimising the system’s overall cost. The proposed model could assist managers in deciding the optimal production strategy while providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

Customer satisfaction is the process of reaching a customer's expectations to generate delightful experiences with a product or a brand. Delight involves delivering an unforgettable experience to users by focusing on their requirements, desires, and interests. Delighting Customers is crucial for organizations’ economic growth worldwide, especially in the airline industry. This study aims to determine if safety measures, ticketing policies, and the cost of air travel impact among the airline passengers’ satisfaction post-COVID-19 in Malaysia. A research framework is designed to present an in-depth understanding of the mentioned variables. In this study, a comprehensive survey using online questionnaire was used and 388 valid responses were obtained from airline passengers in Malaysia. Data were analyzed by employing data reduction technique and multivariate data analysis. The results revealed that safety appears to be the most essential aspect of airline customer satisfaction among Malaysians, while cost is perceived as a significant factor. Moreover, as the cost of living rose because of the pandemic, many of the income earners in the lower category are less inclined to take vacations. In a nutshell, the study recommends that airlines implement a conscious practice that contributes to the happiness of passengers, which in turn increases profitability and ensures sustainable growth of the airlines.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Even though the rules for free movement of machinery within the European Union market have existed for more than 30 years, accidents related to their activities have constantly been achieving significant value. When designing the machine, a designer must stem from risk assessment, whereas all stages of its life cycle and ways of its use must be taken into consideration. In industrial operations, there is old machinery, which, although fulfilling its function reliably, the safety level is not in accordance with the developing requirements for their safe operation. The proposed methodology of assessment of the machinery safety condition comes out from the presupposition of the right application of steps of risk assessment and their reduction mainly by means of implementation of both effective and efficient preventive measures. The aim of the research applied in 3 operations, was to verify the method of machinery safety management. The created methodology based on 19 requirements for safety evaluates the level of the actual measures by means of the so-called criterion of current status and total efficiency of measures. Its output is the assessment of the efficiency level of implemented safety of each machine as well as of the whole operation.

Regarding landscape preferences for highways, there is a dynamic interaction between users and the variety of natural and cultural landscape elements along the roadside, reflecting a balance between the highway and the natural environment. However, the rapid pace of urbanization has accelerated the development of highways, leading to the neglect or destruction of valuable landscapes. This highlights the need for visual preference assessments to protect aesthetic and environmental values. Currently, there is a lack of comprehensive criteria for assessing the visual preference of highway landscapes. Therefore, this study aims to review existing literature and establish complete assessment criteria. This study conducted a systematic literature review by searching for keywords in three databases: Web of Science, Scopus, and Google Scholar. The review included 22 papers published between 2013 and 2023 that met the criteria. An additional four relevant papers were included through a “snowballing” approach to supplement the research and results. The results of the study focused on the relationships between highway landscapes and users, user preferences, preference methods, and related variables. These inter-established relationships were used to complete an assessment framework, which establishes a basic reference standard for professionals.

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

Virtual Histology- Intravascular Ultrasound (VH-IVUS) image is an available method for visualizing plaque component to detect thin cap fibroatheroma. Nevertheless, this imaging modality has considerable limitations to extract the plaque component features and identifying the TCFA plaque. The aim of this paper is to improve the identification of TCFA using fusion of IVUS and VH-IVUS images. In order to generate the automatic technique for reducing the human interaction, a new method namely Active Contour based Plaque Border Detection (ACPB) is proposed. In order to perform the pixel wise classification, hybrid of K-means algorithm with Particle Swarm Optimization and Plaque based Minimum Euclidean Distance (KMPSO-PMED) method is presented to classify the plaque region as well. Moreover, to obtain more significant information of imaging modalities, fusion of two different images consisting of VH-IVUS and IVUS is performed. Therefore, geometric features are extracted from the plaque region and combine with IVUS features. Furthermore, different group of plaque features are divided by means of the histopathological studies. SVM classifiers is applied to detect the TCFA and non-TCFA plaques. The proposed method is applied on 566 in-vivo IVUS and their matching VH-IVUS images obtained from 9 patients. The best result of SVM illustrates the accuracy rates of 99.41% for classification of TCFA plaque. The results prove that the highest accuracy is achieved by integrated features of IVUS and VH-IVUS images.

The most modern technique utilized to create intricate and complexly manufactured parts for a variety of applications is called additive manufacturing (AM). Fused deposition modeling (FDM) has received the greatest attention in the development and manufacturing sectors. The main objective of this study was to investigate how printing factors affected the mechanical characteristics of printed samples. Samples were produced using an FDM 3D printer in compliance with ASTM D638 using a variety of input settings, including orientation, layer thickness, speed, and infill pattern. On the printed samples, tensile tests and morphological analysis using a scanning electron microscope (SEM) were done. The findings of this study demonstrate that factors including layer thickness, printing speed, and orientation significantly affect the tensile strength of ABS printed samples. Discovering the process settings that could lead to superior mechanical and physical characteristics would undoubtedly assist designers and manufacturers worldwide as the FDM 3D printer becomes more and more crucial in manufacturing engineering parts.

The global spread of multidrug-resistant (MDR) microbial infections is currently one of the most severe risks to global public health, with 10 million fatalities expected by 2050 unless action is taken. Nanotechnology has revolutionized science and medicine. The reliance on nanotechnology is growing. Nanoparticles have distinct properties that improve biological, chemical, and physical properties studied for various uses. A significant area of attention in the synthesis of nanoscale modulators is the utilization of crude formulations, retro-synthesized, and pure chemicals, mainly from herbal sources, with fewer adverse effects. Green chemistry has devised a tangential technique for synthesizing metals and metal oxides to produce nanoparticles. Plant extracts (leaves, stems, and shoots) and microorganisms (bacteria, fungus, and yeast) are used as reducing intermediates to make nanoparticles. Studies in microbiology have shown that nanoparticles kill bacteria, fungi, viruses, and protozoa. These green nanoparticles contain antibacterial, antifungal, and anti-inflammatory effects. Most nanoparticles have high antibacterial properties, indicating they may be used to combat diseases and biological contaminants. These nanoparticles have antibacterial action against pathogenic microorganisms that cause serious illnesses, including multidrug-resistant pathogens. The current research will pave the way for future applications and improved methods for producing nanoparticles, paving the way for an innovative route in nano-life sciences with widespread recognition.

Computer vision is a rapidly developing field that focuses on highly sophisticated picture analysis, manipulation, and comprehension. Its objective is to analyze what is happening in front of a camera and utilize that understanding to control a computer or robotic system or to present users with fresh visuals that are more enlightening or appealing than the original camera images. Computer vision technologies make it feasible for new user interfaces, augmented reality gaming, biometrics, automobile, photography, movie creation, Web search, and many more applications. This essay seeks to explain how computer vision can be utilized to play blackjack successfully.

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.

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.

Background: This study aimed to develop and evaluate a dietary self-care promotion program for hemodialysis patients based on Hurley's self-efficacy model. Methods: The needs of hemodialysis patients were identified, and an online community-based dietary self-care promotion program was developed with expert evaluations. 44 hemodialysis patients were randomly assigned to an experimental group (n=22) and a control group (n=22). The program was applied to the experimental group for four weeks. Before and after the intervention, as well as four weeks after the intervention, dietary self-efficacy, dietary self-care behavior, interdialytic weight gain, serum phosphorus, and serum potassium were assessed in both groups. Results: Significant differences over time and between groups were observed in dietary self-efficacy, interdialytic weight gain, serum phosphorus, and serum potassium. The interaction between time and group was also significant. While no significant differences were found over time in dietary self-care behavior, significant group differences and interaction effects between time and group were identified. Conclusions: The results indicate that the dietary self-care promotion program using an online community for hemodialysis patients is more effective in enhancing dietary self-efficacy and dietary self-care behavior compared to conventional treatment. This suggests the clinical applicability of the proposed dietary self-care promotion program.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

Stingless bee beekeeping provides new opportunities to improve the incomes of many households in Malaysia through the sale of honey and other bee products. While Heterotrigona itama is one of the most commonly cultured species of stingless bees, its behavior is not very well understood. Hence, we conducted this study to investigate the behavior of H. itama in exploiting food sources by ascertaining the nectar sugar concentration preferred by the bee. We also aimed to determine the preferred distance of food source from the bee hive. Our results suggest that H. itama prefers high sugar concentrations of 35% and above, and they would fly up to 7 m from the hive to collect food. We discuss how nectar concentration and food distance influence the number of bees exploiting food sources and the overall foraging pattern of H. itama.

A study on the selection of hyperelastic constitutive model for polymeric materials is performed using a hybrid experimental-computational approach. Bis-GMA polymer is used as a case study of hyperelastic material to describe the polymer characteristics by determining its Poisson’s ratio and its valid range of the hyperelastic stress-strain curves. These two parameters are then used to determine the hyperelastic constitutive model by using the hybrid approach. Several uniaxial compression tests along with their finite element simulations are implemented in a systematic way, to identify the polymer behavior under the compressive loading conditions. Nano-indentation experiments are conducted to verify the hyperelastic behavior of the polymer. The experimental and computational evidences confirm that the Poisson’s ratio of Bis-GMA is 0.40 and the appropriate hyperelastic constitutive model for this polymer is of a second order polynomial. It is shown that, the results can be used to determine the true stress-strain curve of hyperelastic materials.

REV-ERBα and its paralog, REV-ERBβ encoded by NR1D1 and NR1D2 genes, are key nuclear receptors that link the circadian timing system and metabolic homeostasis. Since heme is an endogenous ligand, REV-ERBs have been considered key components of the circadian molecular clock that can be pharmacologically targeted to treat various circadian rhythm-related diseases, such as cardiometabolic, inflammatory, and neuropsychiatric diseases, as well as cancer. REV-ERBs are believed to be functionally redundant and compensatory, although they often affect the expression of gene subsets in an isoform-specific manner. Therefore, this study aimed to identify the redundant and distinct roles of each isoform in controlling its target genes by comparing the transcriptome profiles of a panel of mutant U2OS human osteosarcoma cells in which either NR1D1 or NR1D2 was ablated. Indeed, our transcriptomic analyses revealed that most REV-ERB-regulated genes were controlled by redundant or even additive actions. However, the RNA expression profiles of each single mutant cell line also provided strong evidence for isoform-dependent actions. For example, REV-ERBα were more responsible for regulating the NF-κΒ signaling pathway, whereas a group of extracellular matrix components required REV-ERBβ to maintain their expression. We found that REV-ERBs have isoform-selective functions in the regulation of certain circadian output pathways, despite their overlapping roles in the circadian molecular clock. Thus, the development of isoform-selective REV-ERB modulators may help treat metabolic disturbances and certain types of cancer.

.Most of the accident cases at work are caused by unsafe behaviour. Scholars have thus extensively researched factors of safe behavior.Safety leadership is stated as the most effective factor in safety behaviour. Besides, safety knowledge and safety attitudes are also found to influence safety behaviour. The purpose of this paper is to investigate the nature of the relationship between safety leadership, safety knowledge, safety attitude, and safety behavior, which has been found to be limited or rare in previous research.A self-administered questionnaire was applied and was distributed randomly to 140 SME manufacturing workers and they were analysed using the structural equation modelling partial least squares (PLS-SEM). The results prove that safety leadership has a significant effect on safety knowledge, safety attitude, and safety behaviour, with safety knowledge and safety attitude mediating the safety leadership-safety behaviour relationship. Consequently, the results provide a more in-depth view of the relationship between safety leadership and safety knowledge-attitude-behaviour via adapting social-cognitive theory and social learning theory in solving safety issues in SME. This study also provides a starting point for researchers to better understand how effective safety leadership is provided by supervisors in terms of improving worker safety and safety knowledge-attitude-behaviour.

Satellite Crop Detection technologies are focused on detection of different types of crops on the field in the early stage before harvesting. Crop detection is usually done on a time series of satellite data by classification of the desired fields. Currently, data obtained from Remote Sensing (RS) are used to solve tasks related to the identification of the type of agricultural crops, also modern technologies using AI methods are desired in the postprocessing part. In this challenge Sentinel-1 and Sentinel-2 time series data were used due to their periodic availability. Our focus was to develop methodology for classification of time series of Sentinel 2 and Sentinel 1 data and compare how accuracy of classification can be increased, but also how to guarantee availability of data. We analyse phenology of single crops and on the basis of this analysis we started to provide crop classification. Original crop classifications were made from Enhanced Vegetation Index (EVI) layers made from Sentinel-2 time-series data and then we added also . To increase accuracy we also integrate into the process parcel borders and provide classification of fields..

There is a growing recognition of the need to incorporate sustainability considerations early-on in the product development (PD) process (PDP). As part of a case study at an engineering consultancy firm, this paper identifies considerations that influence the integration of sustainable design practices into real-world PD practices. This is informed by the first author getting embedded in the firm as an intern, and closely observing the PD workflow across various projects, conducting interviews and group discussions with a wide range of practitioners, and iteratively designing and testing various potential interventions. From literature and observation, we find that designers and engineers often struggle to identify and apply the right sustainable design methods and tools (SDMTs) to tackle the environmental impacts associated with their products. Through a human-centered design process, we co-created a reusable, modular framework of practices that aids the selection of relevant strategies, based on the environmental hotspots, stage of the PD process, and the client’s sustainability priorities. The paper further presents insights related to the framework’s real-world application and impacts in the firm, based on results of longitudinal engagement with the firm.

In this work, plastic deformation was locally introduced at room temperature by nanoindentation on a γ-TiAl based alloy. Comprehensive analyzes of microstructures were performed before and after deformation. In particular, the Burgers vectors, the line directions and the mechanical twinning systems were studied via accurate electron channeling contrast imaging. Accommodation of the deformation are reported and a scenario is proposed. All features help to explain the poor ductility of the TiAl based alloys at room temperature.

Immunomodulation as means of immunotherapy has been studied in major research and clinical laboratories for many years. T-Regulatory (Treg) cell therapy is one of the modulator used in immunotherapy approaches. Similarly, nuclear receptor peroxisome proliferator activated receptor gamma (PPARγ) has extensively been shown to play a role as an immuno-modulator during inflammation. Given their mutual roles in downregulating the immune response, current study examined the influence of PPARγ ligands i.e thiazolidinedione (TZD) class of drugs on Foxp3 expression and possible crosstalk between PPARγ and nTreg cells of NOD and NOR mice. Results showed that TZD drug, ciglitazone and natural ligand of PPARγ 15d-prostaglandin downregulated Foxp3 expression in activated nTreg cells from both NOD and NOR mice. Interestingly, addition of the PPARγ inhibitor, GW9662 further downregulated Foxp3 expression in these cells from both mice. We also found that PPARγ ligands negatively regulate Foxp3 expression in activated nTreg cells via PPARγ-independant mechanism(s). These results demonstrate that both natural and synthetic PPARγ ligands capable of suppressing Foxp3 expression in activated nTreg cells of NOD and NOR mice. This may suggest that the effect of PPARγ ligands in modulating Foxp3 expression in activated nTreg cells is different from their reported effects on effector T cells. Given the capability to suppress foxp3 gene, it is possible to be tested as immunomodulators in cancer-related studies.

Nodes in wireless sensor networks (WSN) are characterized particularly by their limited power and memory capabilities. Limited memory is an important parameter as it defines the size of the operating system and the processing code. As established previously, energy and memory efficiency is the most important evaluation factors of WSNs as they are directly related to data loss and network lifetime. However, based on our simulation results, memory efficiency determines the selection or abandon of nodes by the botmaster for the propagation of bots in an IoT infrastructure. Consequently, the node’s memory efficiency determined the spread of bots in the network and provides defense actors with an insight of the botmaster behavior for mitigation of the attack. Conventional botnet propagation and mitigation models did not consider the impact of node’s memory efficiency in the IoT platform. To address this gap, we build IoT-SIEF, a novel propagation model with forensic capability that will analyze command and control propagation behavior based on the perspective of the node’s memory efficiency. IoT-SIEF model used to explore the dynamics of propagation using numerical simulation with more than 50% outperform other models in mitigating the number of secondary bots. Consequently, it can serve as a basis for assisting the planning, design, and defense of such networks from the investigator's point of view.

Background Globally the average age of the worlds’ population of older persons continues to upsurge and social support becomes increasingly relevant. Overall, in Malaysia, social support and networking prevalence was found to be lower among older persons at 30.76%. In view of the scarce data on social support and its association with smoking status and its associated factors among the older Malaysian population this study was conducted. Methods Data from the National Health and Morbidity (NHMS) 2018 survey on health of older Malaysian adults was analyzed. This was a cross sectional population-based study using a two-stage stratified random sampling design. Elderly population aged 60 years and above was selected. Data were collected were sociodemographic characteristics, smoking status, and social support. A validated Malay language, interviewer-administered questionnaire of 11-item Duke Social Support Index was applied for assessing social support among the elderly. A complex sampling design analysis was used for the descriptive statistics. The associated risk factors for social support were identified using Multiple Logistic Regression analysis. Results A total of 3923 elderly respondents participated in the study. The prevalence of good social support was significantly higher among the 60-69 years old respondents compared to the > 80 years old (73.1%, 95% CI :69.3% -76.5% vs 50.1 %, 95% CI:41.7 %- 58.6%).Multivariate logistic regression analysis showed that the odds of poor social support were 1.7 times (aOR: 1.72 % ,95%CI: 1.19 -2.48) higher for the respondents aged > 80 years old, than those aged 60-69 years. Respondents with no formal education were 1.93 higher odds of poor social support than the respondents with tertiary education (aOR: 1.93%, 95%CI: 1.13,3.30). Respondents with income < RM 1000 were 1.94 times more likely to have poor social support compared to respondents with income > RM 3000 (aOR: 1.94, 95% CI : 1.21 -3.13). Former smokers have good social support compared to current smokers (73.6% ,95% CI: 67.7-78.7 vs 65.1 %, 95%CI:58.4 -71.2). For current smokers, the odds of poor social support were 42.0% higher than for non-smokers (aOR: 1.42, 95% CI: 1.05 -1.91. Conclusion There is poor social support among the older persons who are current smokers, advancing age, no formal education and low income However, further longitudinal studies are needed to determine the exact effects of the studied variables. These findings could assist the policymakers to develop strategies at the national level to enhance social support among the older smokers to ensure cessation of smoking.

Background: This study aimed to describe the frequency and duration of sedentary bouts and assess the bidirectional cross-sectional associations between these characteristics and adiposity in elderly women. Methods: Data from 314 elderly community-dwelling women (mean age 66.6±6.5 years) from Czech Republic, Poland, and Slovakia were analyzed. Measures were collected in 2008–2017. Fat mass percentage (FM%) was used as an indicator of adiposity. The patterns of sedentary behaviour were monitored using an accelerometer, and ≥5, ≥10, ≥20, ≥30, ≥40, and ≥60 minute bouts were analyzed. The exponent alpha was also calculated to express the accumulation of sedentary time in bouts. We performed a multiple linear regression analysis to assess the bidirectional causal association between variables. Results: There was a significant association of FM% with time spent in bouts with a duration ≥5, ≥10, ≥20min (β ranging 0.11–0.28, p≤0.01) and the frequency of bouts with a length ≥5, ≥10, ≥20, and ≥30min (β ranging 0.03–0.74, p≤0.05) in fully-adjusted models. In contrast, a strong negative association was observed between FM% and alpha (bout distribution) in both directions (p≤0.001). Conclusions: Our results suggest that the sedentary characteristics such as bout duration, bout frequency, and distribution (alpha) are bidirectionally associated with adiposity and they should be considered in further research in older adults.

The present study examined the volatile composition and antimicrobial and gastrointestinal activity of the essential oils of Elettaria cardamomum (L.) Maton harvested in India (EC-I) and Guatemala (EC-G). Monoterpene were present in higher concentration in EC-I (83.24%) than in EC-G (73.03%), whereas sesquiterpenes were present in higher concentration in EC-G (18.35%) than in EC-I (9.27%). Minimum inhibitory concentrations (MICs) of 0.5 and 0.1 mg/mL were demonstrated against Pseudomonas aeruginosa in EC-I and EC-G, respectively, whereas MICs of 0.125 and 1 mg/mL were demonstrated against Escherichia coli in EC-I and EC-G, respectively. The treatment with control had the highest kill-time potential, whereas the treatment with oils had shorter kill-time. EC-I was found to be more potent in the castor oil-induced diarrhoea model than EC-G. At 100 and 200 mg/kg, EC-I exhibited 40% and 80% protection, respectively, and EC-G exhibited 20% and 60% protection, respectively, in mice, whereas loperamide (positive control) exhibited 100% protection. In the in vitro experiments, EC-I inhibited both carbachol (CCh, 1 µM) and high K+ (80 mM)-induced contractions at significantly lower concentrations than EC-G. Thus, EC-I significantly inhibited P. aeruginosa and E. coli and exhibited more potent antidiarrheal and antispasmodic effects than EC-G.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

This qualitative study aims at identifying the essence of personal experiences of accounting partners in Saudi Arabia. For this phenomenology approach employs to understand the lived experience of accounting partners and how would such experience affect their career. It mainly aims to explore the different experiences of fifteen (15) Saudi partners working in various accounting companies in Saudi Arabia. The interviews conducted to explore the most important challenges and difficulties for accountants to become a partner, and the most important job skills that the partners must have. This study found that there is urgent need for a number of things, including the required number of years of experience to become a partner, and to make sure that the partners are having the right education and professionally qualified. In addition, other different skills that the partner must have include responsible leadership, professional communication, good marketing skills and excellent command of English. Moreover, this research is vital for the concerned parties to identify the current challenges in the accounting profession in Kingdom of Saudi Arabia.

Taking care of stroke survivors can be taxing, however, it was understudied in Malaysia. This study aims to describe the burden of informal stroke caregivers within three months after hospital discharge. A longitudinal study design was conducted. Acute stroke survivors and their informal caregivers were recruited prior to hospital discharge, and the caregivers were interviewed by phone. Self-reported caregiver burdens were measured with Zarit Caregiver Burden Interview – Malay version (MZBI) and Caregiver Assessment of Function and Upset – Malay version (Malay-CAFU). The MZBI and Malay-CAFU scores were collected four times within three months. A total of 85 stroke survivors and 155 informal caregivers were recruited, with 58.1% of the caregivers were female. The stroke survivors had two caregivers on average. The mean (SD) scores for the three scales show a reduction, from 27.42 (12.73) in the first week to 17.77 (11.20) in the third month for MZBI, from 1.14 (0.94) to 0.62 (0.64) for instrumental activities of daily livings (IADL) of Malay-CAFU upset scale and 1.36 (1.00) to 0.78 (0.65) for activities of daily living (ADL) of Malay-CAFU upset scale in the same period. Stroke survivors may have several caregivers, usually their spouses or children. Within a short period, the caregiver’s burden was reduced. Early psychosocial support to alleviate the caregiver burden may be necessary.

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.