This panel study investigates the relationship between green logistics indices, economic, environmental, and social factors in the perspective of Asian emerging economies. This study adopted FMOLS and DOLS methods to test research hypothesis, catering the problem of endogenity and serial correlation. The results suggest that logistics operations, particularly LPI2 (efficiency of customs clearance processes), LPI4 (quality of logistics services) and LPI5 (trade and transport-related infrastructure), are positively and significantly correlated with per capita income, manufacturing value added and trade openness. While, greater logistics operations are negatively associated with social and environmental problems including, climate change, global warming, carbon emissions, and poisoning atmosphere. In addition, human health is badly affected by heavy smog, acid rainfall, and water pollution. The findings further extend and reveal that political instability, natural disaster and terrorism are also a primary cause of poor economic growth and environmental sustainability with poor trade and logistics infrastructure. Further, the application of renewable energy resources and green practices can mitigate negative effects on social and environmental sustainability without compromising the performance of economic growth. There is very limited empirical work presented in literature using renewable energy and green ideology to solve macro-level social and environmental problems, while this study will assist the policymakers and researchers to understand the importance of green concept in improving countries’ social, economic and environmental performance.

We do this research to investigate the relationship between renewable energy, public health expenditure, logistics performance indices, and economic and environmental sustainability in the ASEAN member states, through the analysis of a panel data from 2007 to 2017. The study used secondary data, which is downloaded from the World Bank Website and employs SEM (Structural Equation Modelling) model for testing hypothesis. The results show that the usage of renewable energy in logistical operations would enhance the environmental and economic performance in terms of mitigating carbon emissions and greenhouse gas emissions. While, public health expenditure and environmental performance is negatively correlated, which confirms that greater environmental sustainability with lower carbon emissions and greenhouse gases will improve human health and economic growth. Moreover, greater public health expenditure and poor environmental performance has negative effect on economic growth, inefficiency and low productivity of labor slowdown to the economic activities. For another side, the usage of renewable energy and the adoption of green practices in international logistics will develop the environmental sustainability, establish better image of a country and attract foreign direct investment inflows, and also minimize carbon emissions and public health expenditure, spurring sustainable economic growth with better export opportunities in pro-environmental countries.

Coronavirus disease is a newly identified infectious disease that began in Wuhan, China in 2019 and is recognized as COVID-19. This virus has a serious impact on the planet that causes the deaths of millions of people; it produces unemployment and poverty. However, it has constructive environmental effects that reduce the amount of pollution in the atmosphere. Pakistan is also a developing economy caused by this deadly virus. Before 03 April 2021, the percentage of reported cases ranges from 682,888, with about 14,697 casualties and a total of 609,691 cases retrieved. Pakistan’s war against coronavirus can differ from advanced technical countries due to lack of resources. In this article, we will address the relation between COVID-19 and the environment in the particular case of Pakistan. There is evidence that this pandemic has lowered concentrations of greenhouse gases, including CO2 and NO2, as a consequence of global lock-down strategies.

The major aim of this study was to investigate and explores the linkage between economic growth, electricity access, energy use and population growth in Pakistan. To check the variables stationarity, Augmented Dickey-Fuller (ADF) and Phillips-Perron unit root test was applied and an Autoregressive Distributed Lag (ARDL) bounds testing approach to co-integration was applied to investigate the dynamic causality link among the study variables. These tests shed light on the long-run connection among the variables; further, the results revealed that electricity access to population, electricity access to urban population, energy usage, population growth, and urban population growth had a significant impact on economic growth, while the electricity access to rural population and rural population growth has a negative impact on the economic growth in Pakistan. According to these findings, study commends that government of Pakistan pay further attention to increase its electricity production from different sources including, hydroelectric, solar, oil and gas and nuclear in order to fulfill the country’s demands. By using ARDL bounds testing approach, this study filled the literature gap regarding economic growth, electricity access, energy use and population growth in Pakistan.

This paper investigates and explores the minor crops production in Pakistan and its association with the agricultural gross domestic product. The agriculture sector of Pakistan has a rich contribution to the economic growth and development. Like major crops; minor crops also have a vital role to boost up the agriculture sector. Time span data was used in this study and it was collected from the Economy Survey of Pakistan annual reports. Augmented Dickey-Fuller (ADF) unit root test and Ordinary Least Square (OLS) method was used to analyze the data and results were interpreted by employing the Johansen co-integration test. Study results reveal that bajra, barely and jowar has a significant impact on the agricultural gross domestic product, while the total cropped area has a negative impact on AGDP. On the basis of the study results, we recommend the policy implications.

Hepatitis B and C are major health issues in developing countries such as Pakistan and Afghan-istan. The aim of this study was to determine the prevalence and effectiveness of a screening program for hepatitis B and C in a region with no existing programs, and to estimate their prev-alence in the general population in Khyber Pakhtunkhwa Province, Pakistan, as well as in Afghan refugees or migrants. A prospective cohort study was done in the general population of Peshawar and its adjacent districts, as well as migrants from neighboring provinces of Afghani-stan, who presented to our tertiary-care health facility. A Microsoft Excel registry was created for data collection, which were analyzed using IBM SPSS via descriptive analysis, normal distribution curve histograms, and chi-squared tests. A total of 9563 individuals were screened for hepatitis (5894 males and 3669 females), including Afghan migrants in Peshawar and surrounding districts. 876 individuals tested positive for hepatitis, with 538 positive for hepatitis B (383 males and 155 females) and 330 positive for hepatitis C (198 males and 134 females). Eight individuals had a hepatitis B and C co-infection. Among the study population, the prevalence rates were 2.2% for hepatitis B and 2.3% for hepatitis C, of which the Afghan migrants accounted for 2.7% and 0.5%, respectively. According to the gender-based distribution, hepatitis B was more prevalent in males, whereas there was no significant gender-based difference for hepatitis C. Our results highlight the need for a comprehensive approach to control hepatitis B and C in Pakistan and Afghanistan. Increased awareness, improved healthcare, and preventive measures such as screening and elimination programs to prevent severe liver diseases and eradicate hepatitis are necessary.

For disciplines like biological science, security, and the medical field, link prediction is a popular research area. To demonstrate the link prediction many methods have been proposed. Some of them that have been demonstrated through this review paper are TransE, Complex, DistMult, and DensE models. Each model defines link prediction with different perceptions. We argue that the practical performance potential of these methods, having similar parameter values, using the fine-tuning technique to evaluate their reliability and reproducibility of results. We describe those methods and experiments; provide theoretical proofs and experimental examples, demonstrating how current link prediction methods work in such settings. We use the standard evaluation metrics for testing the model's ability.

Rockburst is a hazardous phenomenon in deep tunnels influenced by geological structural planes like faults, joints, and shear planes. Small-scale shear-plane-like structures have damaging impact on the boundaries of the tunnel, which accumulate high stresses. Such a shear plane was exposed in the side wall of the right headrace tunnel in the Neelum-Jehlum Hydropower Project. This project is constructed in the tectonically active Himalayas with high stress conditions. A shear plane combined with high stress conditions is very dangerous in deep excavations. The influence of a shear zone on rockburst occurrence near a tunnel is studied. The FLAC3D explicit code simulated the shear zone in the right tunnel, revealing that the stresses are concentrated near the shear zone, with no stress concentration in the left tunnel, which has neither shear zone nor rockburst. Rock mass was displaced near this shear zone even before excavation. Modeling results confirm that the side wall shear zone of the tunnel has a major influence on rockburst occurrence. A shear slip along this plane released huge amounts of energy, causing human fatalities and property damage. A numerical simulation validates the actual conditions and helps us understand the phenomenon of stress concentration near the shear zone and its impact during deep tunneling.

Globally, rice is utilized as staple food, belongs to the family Poaceae. From the past few decades under variable climate conditions, it greatly affected by the bacterial leaf blight (BLB) disease caused by a bacterium Xanthomonas oryzae pv. oryzae (Xoo). Scientists studied causes of the disease and found more than 61 isolates of Xoo. About 39 Xa genes were noted that cause race specifically resistance either individually or in pairs against Xoo. The canvas on the characterization of these genes is still unrevealed. In this study, amino acid sequences of Xa15, Xa19, Xa20 and Xa21 were mined and used for motif-domain identification, characterization, and comparative analysis. It includes screening of physical and chemical characteristics, sequence comparison to find sequence similarity between them and their phylogenetic comparison with other Xa genes and other species based upon LRR and S_TKc domains to find evolutionary relationship among them. The comparison-based modeling was performed and assessed by different tools to gain better understanding and structural evaluation. The results showed identified domains are specific in function, each domain involved in resistance against biotic and abiotic stresses through regulating different cellular processes. This study also revealed high similarity (>98% sequence identity) between these genes and encode a similar leucine-rich repeat receptor kinase like protein. It will optimize the breeding programs as it will be useful for the selection of effective genes to produce resistance in rice varieties against the specific strains of Xoo that will be more effective against BLB than the other Xa genes.

The Chiltan Formation is a potential hydrocarbon-producing reservoir in the Indus Basin, Pakistan. However, its diagenetic alterations and heterogeneous behavior lead to significant challenges in accurately characterizing the reservoir and production performance. This manuscript aims to utilize Chiltan Limestone core samples to conduct a detailed analysis of the diagenetic impacts on reservoir quality. The formation evaluation was carried out through thin section analysis, SEM-EDS and FTIR investigation, as well as plug porosity and permeability measurements under different stress conditions. In results, Petrography revealed three microfacies with distinct diagenetic features and micro-nano fossil assemblages, including intraclasts, pelloids, bioclasts, and stylolites. Diagenesis has a significant impact on petrophysical properties, leading to increased reservoir heterogeneity. The specified depositional environment exposed the alteration of the Chiltan formation during distinct diagenetic phases in marine, meteoric, and burial settings. Pore morphology and mineralogy reveals complex micro-pore structure with various carbonate mineral phases and cement types in the formation samples. The average porosity and permeability of the core samples were found to be 3.4% and 0.449 mD respectively, indicating poor reservoir quality. Stress sensitivity was determined using Klinkenberg corrected permeability, which indicated a reduction in measured and absolute permeability due to increasing confining stress, further reducing the pore throat structure of the formation. In conclusion, the Chiltan formation possesses intricate reservoir heterogeneity and varied micro-pore structure caused by diagenesis and depositional settings. The formation is classified as a low-quality reservoir due to its non-uniform pore geometry, which exhibits low petrophysical properties resulting from overburden stress. The results of this study provide solid foundation in reservoir characterization and quality assessment which has implications for exploring and exploitation of indigenous resources.

The demand of high data rate and ubiquitous coverage in heterogeneous cellular (HetNets) is increasing progressively. In order to meet this demand, sophisticated model having applied interference reduction scheme and cell association technique is needed. The small base station (sBS)are deployed inside the broadcasting area of macro base station (mBS), in heterogeneous cellular networks (HetNets). Since mBS has high transmission power therefore a large number of users get connected with mBS. This causes disproportion of load distribution across the HetNets. For load balancing users from high power mBS are migrated to low power sBS to increase network capacity and to decrease the load from mBS. This results in interference in the communication signal because of strong mBS Interference. Hence, we need interference management technique to mitigate interference and user association and to efficiently use sBSs’ resources. Inter-cell interference (ICI) limit the HetNets’ performance. Additionally, there exist deliberate jamming interference which depends on jammers transmission power and its proximity with the target, which notably degrades the network performance. In this paper, we employ reverse frequency allocation scheme (RFA) to reduce inter cell interference, deliberate jamming interference and to accomplish load balancing. The proposed setup is analyzed inquisitively and with the help of simulations. The result shows reduction in interferences as well as balance of load distribution in the network achieved by employing RFA scheme together with cell association.

The cutting-edge photovoltaic cells are an indispensable part of the ongoing progress of earth-friendly plans for daily life energy consumption. However, the continuous electrical demand that extends to the night time requires a prior deployment of efficient real-time storage systems. In this regard, metal-air batteries have presented themselves as the most suitable candidates for solar energy storage, combining extra lightweight with higher power outputs and promises of longer life cycles. Scientific research over non-precious functional catalysts has always been the milestone and still contributing significantly to exploring new advanced materials and moderating the cost of both complementary technologies. Metal-organic frameworks (MOFs) derived functional materials have found their way to the application as storage and conversion materials, owing to their structural variety, porous advantages, as well as the tunability and high reactivity. In this review, we provide a detailed overview of the latest progress of MOF-based materials operating in metal-air batteries and photovoltaic cells.

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble methods, to enhance credit card fraud detection. Through an extensive review of existing literature, we identified limitations in current fraud detection technologies, including issues like data imbalance, concept drift, false positives/negatives, limited generalisability, and challenges in real-time processing. To address some of these shortcomings, we propose a novel ensemble model that integrates a Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), Bagging, and Boosting classifiers. This ensemble model tackles the dataset imbalance problem associated with most credit card datasets by implementing under-sampling and the Synthetic Over-sampling Technique (SMOTE) on some machine learning algorithms. The evaluation of the model utilises a dataset comprising transaction records from European credit card holders, providing a realistic scenario for assessment. The methodology of the proposed model encompasses data pre-processing, feature engineering, model selection, and evaluation, with Google Colab computational capabilities facilitating efficient model training and testing. Comparative analysis between the proposed ensemble model, traditional machine learning methods, and individual classifiers reveals the superior performance of the ensemble in mitigating challenges associated with credit card fraud detection. Across accuracy, precision, recall, and F1-score metrics, the ensemble outperforms existing models. This paper underscores the efficacy of ensemble methods as a valuable tool in the battle against fraudulent transactions. The findings presented lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, crucial as credit card fraud techniques continue to evolve.

The makeup of human microbiota has been linked to a number of autoimmune disorders. Recent developments in whole metagenome sequencing and 16S rRNA sequencing technology have considerably aided research into the microbiome and its relationship to disease. Due to the inherent high dimensionality and complexity of data generated by high-throughput platforms, conventional bioinformatics techniques could only provide an inadequate explanation for the most relevant changes and seldom provide correct predictions. Machine learning, on the other hand, is a subset of artificial intelligence applications that enable the untangling of high-dimensional systems and intricate knots in correlation by learning complex patterns and improving automatically from training data without being explicitly programmed. Machine learning is increasingly being utilized to research the influence of microbes on the onset of illness and other clinical features since computer power has increased dramatically in the last few decades. In this review paper, we focused on emerging methodological approaches of supervised machine learning algorithms for identification of autoimmune disorders utilizing metagenomics data, as well as the potential benefits and limitations of machine learning models in clinical applications.

Biomedical implants are the need of this era due to the increase in number of accidents and follow-up surgeries. Different types of bone diseases such as osteoarthritis, osteomalacia, bone cancer, etc. are increasing globally. Mesoporous bioactive glass nanoparticles (MBGNs) are used in biomedical devices due to their osteointegration and bioactive properties. In this study, silver (Ag) and strontium (Sr) doped mesoporous bioactive glass nanoparticles (Ag-Sr MBGNs) were prepared by a modified Stöber process. In this method, Ag+ & Sr2+ were co-substituted in pure MBGNs to harvest the antibacterial properties of Ag ions, as well as pro-osteogenic potential of Sr2 ions. The effect of the two ion concentration on morphology, surface charge, composition, antibacterial ability, and in-vitro bioactivity was studied. Scanning electron microscopy (SEM), X-Ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) confirmed the doping of Sr and Ag in MBGNs. SEM and EDX analysis confirmed the spherical morphology and typical composition of MBGNs, respectively. The Ag-Sr MBGNs showed a strong antibacterial effect against Staphylococcus carnosus and Escherichia coli bacteria determined via turbidity and disc diffusion method. Moreover, the synthesized Ag-Sr MBGNs develop apatite-like crystals upon immersion in simulated body fluid (SBF), which suggested that the addition of Sr improved in-vitro bioactivity. The Ag-Sr MBGNs synthesize in this study can be used for the preparation of scaffolds or as a filler material in the composite coatings for bone tissue engineering.

This review focuses on the therapeutic effects of metallic ions when released in physiological environments. Recent studies have shown that metallic ions like Ag+, Sr2+, Mg2+, Mn2+, Cu2+, Ca2+, P+5, etc., have shown promising results in drug delivery systems and regenerative medicine. These metallic ions can be loaded in nanoparticles, mesoporous bioactive glass nanoparticles (MBGNs), hydroxyapatite (HA), calcium phosphates, polymeric coatings, and salt solutions. The metallic ions can exhibit different functions in the physiological environment such as antibacterial, antiviral, anti-cancer, bioactive, biocompatible, and angiogenic effect. Furthermore, the metallic ions can be loaded in scaffolds to improve osteoblast proliferation, differentiation, bone development, fibroblast growth, and improved wound healing efficacy. Moreover, different metallic ions possess different therapeutic limits. Therefore, further mechanisms need to be developed for the highly controlled and sustained release of these ions. This review paper summarizes the recent progress in the use of metallic ions in regenerative medicine and encourages further study of metallic ions as a solution to cure diseases.

Poliomyelitis, commonly known as “polio” is a paralytic and perilous disease caused by the poliovirus. Due to its highly contagious nature, the virus was a challenge to the world in the late 1980s. . Since 1988 the collective work of the Global Polio Eradication Initiative (GPEI), Centre for Disease Control and Prevention (CDC), and World Health Organization (WHO) through immunizations, communication awareness, and monitoring have helped the world exonerate polio. The mission of polio-free Pakistan was herculean and had confronted enormous challenges in different ways but came out with positive results. In 2019, with only two remaining polio-endemic countries, Pakistan and Afghanistan, GPEI launched an “Endgame strategy 2019-2023” which aims to eradicate polio globally, with a targeted focus, especially on polio-endemic countries, the plan emphasizes the early detection of polio cases for complete eradication and to restrict the spread of polio. Pakistan has achieved a milestone in combating polio despite having a web of factors that have thwarted Pakistan’s polio eradication efforts, but this is not the end, the struggle continues until we really get an internationally verified certification of Polio free nation, for this WHO has designed a multidisciplinary strategy 2022-2026 to really end this polio for once and for all.

This paper presents a theoretical analysis of an International conflict, i.e. East Pakistan Crisis, 1971, and reveals that unequal development creates conflict in society. Natural resource scarcity and environmental degradation can also become a source of conflict, so marginalised and excluded people fight for their rights through non-peaceful means. This essay supports the theoretical approaches of poverty, environment, and conflict nexus and reveals that unequal development and resource scarcity deepens the poverty and creates conflicts in the society, causing harm to the environment. The degraded environment increases the poverty as environment and poverty are interlinked, and the poor have limited choices other than to degrade the environment for their survival. This vicious downward spiral link between poverty and degradation of the environment requires working extensively for poverty alleviation to reverse the environmental decline.

The four solvent extractives obtained from aerial parts of Leucophyllum frutescens were evaluated for their Total Antioxidant Activity (TAA) by ammonium molybdate method, scavenging potential by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Trolox-Equivalent Antioxidant Capacity (TEAC) assays, metal-reducing potential by Cupric Reducing Antioxidant Capacity (CUPRAC) and Ferric Reducing Antioxidant Power (FRAP) assays, Total Phenolic Content (TPC), Total Flavonoid Content (TFC) and their biological activities. The study concluded that BULE exhibited total antioxidant activity (226.235±1.222 mg AA.Eq.gm-1 DE±S.D) by molybdate method, CHLE exhibited more scavenging potential (DPPH 209.589±8.500 mg trolox Eq.gm-1 DE±S.D and TEAC 210.166±7.954 mg trolox Eq.gm-1 DE±S.D) and reducing potential (CUPRAC 646.889±16.889 mg trolox Eq.gm-1 DE±S.D & FRAP 472.981±15.625 mg trolox Eq.gm-1 DE±S.D). Phytochemical quantification concluded high TPC by BULE (189.369±1.393 mg GA.Eq.gm-1 DE±S.D) and high TFC by CHLE (232.458±1.589 mg Qu.Eq.gm-1 DE±S.D). Strong inhibition of α-glucosidase and urease enzymes was observed by HELE (IC50 0.3321±0.007 mg.ml-1±SD) and BULE (IC50 4.09±0.357 mg.ml-1±SD) extractives, respectively. The hemolytic effect shown by hexane extract (HELE) was higher with HA50 25.545±0.927 ug.ml-1±SD whereas methanol (MELE), chloroform (CHLE), and butanol (BULE) exhibited hemolytic effects at higher concentration with HA50 400.067±1.364, 321.394±1.332, and 332.957±0.465 µg.ml-1±SD, respectively. GC-MS profiling of HELE of L. frutescens was performed for qualitative analysis. The principal phytochemicals tentatively identified by GC-MS analysis of HELE accounts for fatty acids (60.221%), lignans (17.687%), ketones (3.358%), phenols (2.584%), sesquiterpenes (1.265%), and aldehydes (0.345%).

Wheat has a large and diverse repertoire of NLRs involved in disease resistance, with over 1,500 NLRs detected in some studies. These NLR genes occur as singletons or clusters containing copies of NLRs from different phylogenetic clades. The number of NLRs and cluster size can differ drastically among ecotypes and cultivars. Primarily, duplication has led to the evolution and diversification of NLR genes. Among the various mechanisms, whole genome duplication (WGD) is the most intense and leading cause, contributing to the complex evolutionary history and abundant gene set of hexaploid wheat. Tandem duplication or recombination is another major mechanism of NLR gene expansion in wheat. The diversity and divergence of duplicate NLR genes are responsible for the broad-spectrum resistance of most plant species with limited R genes. Understanding the mechanisms underlying the rapid evolution and diversification of wheat NLR genes will help improve disease resistance in crops. The present review focuses on the diversity and divergence of duplicate NLR genes and their contribution to wheat disease resistance. Moreover, we provide an overview of disease resistance-associated gene duplication and the underlying strategies in wheat.

The purpose of this article is to address two questions that will aid researchers in understanding FinTech’s inception, development, and potential impact on the stability of the financial system. First, it explains why financial technology is a current phenomenon. While many of the underlying technology for FinTech breakthroughs have been around for some time, it is only recently that financial institutions and entrepreneurs have begun to apply them to financial goods and services. Supply and demand factors in "conventional" financial innovation have been studied, and they have been found to converge, leading to a high rate of innovation. And second, this article explains why FinTech is being covered in greater depth than other types of innovation. This study introduces the concept of "depth" of innovation as a means of answering this question. The more fundamental the innovation, the more it will affect the financial sector. In this paper, we demonstrate that many recent developments in the field of financial technology (FinTech) are truly revolutionary advances, with far-reaching implications for the financial services industry. In addition to the benefits of more adaptability, higher transformational potential might bring increased risk to economic security.

The demand for high-energy-density batteries necessitates novel anode materials. Transition metal oxides (TMOs) show promise due to their high capacity, sustainability, and cost-effectiveness. However, TMO-based anodes face challenges related to expansion and conductivity. This study presents a two-step dilution crystallization method to fabricate porous ZnO nanoflowers at a moderate temperature. In-situ integration with carbon nanotube dispersants enhances conductivity and reduces agglomeration. The resulting composite anode exhibits impressive initial discharge capacity (2314.2 mAh g-1) and cycling stability (580.5 mAh g-1 over 50 cycles). This study provides a facile approach for next-generation anode materials.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Cadmium Sulfide nanoparticle (CdS-LA hybrid nanoparticles) was synthesized here by a green approach using the precursor cadmium acetate and sodium sulphide along with the extract of a plant Lathyrus aphaca L. containing the phytochemicals which were responsible for surface modification of nanoparticles. The nanoparticle was used to evaluate their inhibition potential against species of bacteria and fungi. The nanoparticles were characterized by XRD which demonstrates the hexagonal crystal structure. SEM confirms the homogenous surface appearance of the CdS-LA hybrid crystalline structure. EDX analysis confirms surface modification of nanoparticles by phytochemicals. FTIR confirmed the Cd-S linkage laterally with the related functional groups and the presence of metabolites on the surface of nanoparticles. The UV-visible spectroscopy confirmed the peak at the characteristic wavelength range but a slight shift occurred in the peak of the CdS nanoparticles due to the presence of the phytochemicals. This study particularly provides an environment-friendly strategy to synthesize the CdS nanoparticles capped by Lathyrus Aphaca L. extract that are biologically active due to the mediation of the plant extract. CdS-LA hybrid nanoparticles have shown inhibition potential against various species of bacteria and fungi and realize the biological importance of the green synthesis of nanoparticles especially mediated with the plant extract.

Atherosclerotic cardiovascular disease, a leading cause of morbidity and mortality worldwide, is a chronic inflammatory disease, linked to a state oxidative stress, with several well-identified culprits, of which low-density-lipoprotein cholesterol (LDL-C) and lipoprotein(a). No specific treatment is currently available to lower lipoprotein(a). It is, therefore, of paramount importance to identify nutritional factors that could lower lipoprotein(a). Growing evidence shows that although reducing saturated fatty acid (SFA) intake decreases LDL-C, it could increase lipoprotein(a). Optimal dietary recommendations may therefore differ depending on an in-dividual’s baseline lipoprotein(a) and LDL-C levels. Assessing the diet-induced true LDL-C response and net balance of these two atherogenic entities is difficult because LDL-C measurement is confounded by lipoprotein(a) cholesterol content. We have estimated, for the first time, the net atherogenic result of diet-induced variations of both LDL-C and lipoprotein(a), thanks to our new concept of LDLapoB risk equivalent=apoB+lp(a)x5 (in nmol/L). This is illustrated, via the rare case of a physician with very high lipoprotein(a) and hypobetalipoproteinemia. She experiences twice a considerable lipoprotein(a) increase (+32%, + 28mg/dL, + 67nmol/L) and higher LDLapoB risk equivalent (138mg/dL versus 123mg/dL) on a mediterranean diet, low in SFA. A reasonable SFA intake, despite causing marginal LDL-C increase, may be advisable in patients with high lipoprotein(a) who need personalized dietary recommendations.

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

Nowadays, more than 180 million people believe that the Holy Qur'an was sent by the Almighty Allah through Prophet Muhammad in 610-632 A.D in Mecca and Medina. However, the word Mecca (Q: 48:24) is mentioned only once in the entire Holy Qur'an, which is not related to the birth of the Prophet or any worship. Conventional Islam is mostly based on the hearsay of some Islamic narrators published in the eighth and ninth centuries. To think deeply and conduct research on the verses of the Holy Quran has been mentioned (special urge) directly and indirectly by this Holy Scripture itself many times but it would not be wrong to say that there is no scholarship on the verses of the Quran based on the research method described in the Holy Quran until the present century. Therefore, this paper has been dared to carry out by combining the methods of research followed in the Holy Quran and the academically accepted research methodology. The analysis shows that the results of almost fourteen hundred years of mythological history of conventional Islamic narrators are opposites. First of all, the proper name of the Prophet revealed by the Holy Quran is Ahmed, but Muhammad is an adjective and there are many such names. Secondly, this prophet was not born in Mecca, KSA, nor in 570/571 A.D, but in the Beqaa Valley of Lebanon, between the third and fourth centuries. Thirdly, the Muslim Hajj (pilgrimage) of Mecca is celebrated entirely according to the Lahwal Hadith (idle tales) (Q: 31:6) in the language of the Holy Quran. Originally the place designated for pilgrimage was in the Beqaa Valley, Lebanon. This article will have a double influence on the Muslim world, that is, Islamic scholars will think again deeply and research new ways of scholarship of the Holy Quran, instead of based on the hearsay of idle tales (Lahwal Hadith). On the contrary, those who are stubborn Islamic narrators, since they have already rejected the Holy Quran, will not hesitate to violently attack the researchers and they will not be positively motivated by this paper. This article specifically urges Islamic scholars to conduct in-depth studies on the most important issues of Islam using the Holy Quranic research method.

Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. This study investigated the molecular evaluation of a new mango cultivar ‘Azeem Chaunsa’ using a set of the most effective 50 hyper-variable polymorphic SSR markers. Highly specific DNA fingerprints were identified in the genome of this mango cultivar, ‘Azeem Chaunsa’ compared with three standard cultivars such as Sindhri, Samar Bahisht (S.B) Chaunsa and Sufaid Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. An agglomerative hierarchical clustering method was used to construct dendrogram based on the ‘Unweighted Pair- Group Method with Arithmetic Mean’ (UPGMA). The genetic similarity coefficients were recorded between the mangos cultivars ranged from 0.49 to 0.67. Cultivar identification (CID) evaluates association among standard cultivars and Azeem Chaunsa and further concludes significant variations. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future mango breeding programmes in the context of climate change.

Liability to prevent consequences of an unhealthy situation due to accumulating toxic and hazardous emissions caused by open dumping of municipal solid waste with increasing urbanization has necessitated a renewed thinking on waste disposal. Grate fired incineration systems were adopted by urban managements in past and present but with criticisms due to formation of air borne emissions. Improved combustion methods like fluidized bed are now propagated because of current requirements like efficient energy recovery potential, stricter emission norms, adaptability with urban growth, adaptability to co-firing with other waste like biomass, edible oil wastes or industrial effluent and integration with conventional energy generation. Such a comprehensive and futuristic approach is more sustainable for the community. Multi-criteria decision-making tool is used to identify the best technology option among grate combustion and fluidized bed combustion for disposing and energy recovery from waste. Ten different collection and disposal options involving two combustion methods, namely, grate combustion and fluidized bed method are considered. Utilization of the energy is done for three end uses, namely, power generation, water distillation and district cooling. Two different regions in Saudi Arabia are considered for this study under two types of scenario, namely with recycling and without recycling. The different options are prioritized based on their overall ranking using five major performance factors.

Aim: Shockwaves have been felt all over the world as a result of war, inflation, food shortages, and the COVID-19 pandemic's long tail. The aim of the study is to correlate present global conflicts, pandemic and socio-economic crises with present healthcare sustainability, identifying possible threats and visualize future global health crises if all these catastrophes persist for long. Materials and Methods: PubMed, ALTAVISTA, Embase, Scopus, Web of Science, and the Cochrane Central Registers were prioritized to collect public health issues. Results: The global economic slowdown, sharp decline in financial asset values, decline in imports and exports, contraction of industrial production, rise in inflation, decrease in wages, rise in unemployment, damage to the social security caused by numerous natural calamities, human displacement due to pandemic and ongoing conflicts tear down not only the economic sector but also the health sector. It is already late for taking corrective measure by the participation every country, community or intelligence. Only healthcare issues, highlighted in this study, if focused in the highest platforms, could compel global leaders to forego conflicts and work together. Conclusion: The global health sector will be collapsed soon, if proper initiatives are not taken right now, which has already been grossly mistreated by the pandemic.

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

This study aims to focus on using the Volterra series and machine learning for forecasting random and chaotic wind speed regimes, since the calm weather is mostly noticed at the local site, making the dataset selection difficult. A novel method is proposed to predict Volterra kernels up to the third order, using a forward-back propagation neural network with 12-month measurements at Fujairah site (UAE). Both daily and monthly wind speed data sets are investigated for forecasting. The three dominant hourly and daily kernels are extracted for each day and each month. Predicted future Volterra kernels are estimated from past values using both statistical analysis and individual neuro networks for each of the Volterra kernel coefficients. Due to the random nature of wind speed at the local site, a two-layer with 4 neurons per layer neuro network is used to locate the most variable and intense speed during 8-hours in the day. Forecasted wind speed is determined with errors arising from different sources such as the utilization of only 3rd-order Volterra kernels and the difficulty of machine training of the employed shallow network. Nevertheless, this work depicts a useful algorithm to forecast chaotic and random wind speed regimes. Computational time is a trade of the complexity of Volterra mathematical analysis.

Blockchain innovation stands out enough to be noticed and adopted in various countries and organizations around the world. Many businesses, including finance, medical services, inventory networks, security, libraries, and the internet of things, are currently under attack. For the benefit of the blockchain, many businesses incorporate blockchain technology into their frameworks. Despite its solidarity, blockchain faces a few challenges in security, protection, adaptability, and other areas. This paper examines the forward leap in blockchain innovation, as well as its applications and challenges. While many blockchain papers focus on digital currencies, IoT, and security, this paper focuses on the overall best in a class of blockchain innovation, its new twists and turns, and choices, particularly in areas other than cryptographic forms of money. The investigators' goal is to provide a thorough audit of the cryptography underlying blockchain to better understand the innovation. The examiners also conduct general research on people and venture blockchains, as well as future exploration opportunities and their implications for blockchain innovation.

Hydrogels can provide instant relief to pain and facilitate the fast recovery of wounds. Currently the incorporation of medicinal herbs/plants in polymer matrix is being investigated due to their anti-bacterial and wound healing properties. Herein, we investigated the novel combination of chitosan (CS), chondroitin sulfate (CHI) and garlic (Gar) to synthesize hydrogels through freeze gelation process for faster wound healing and resistance to microbial growth at the wound surface. The synthesized hydrogels were characterized via Fourier transform infrared spectroscopy (FTIR), which confirmed the presence of relevant functional groups. The scanning electron microscopy (SEM) images exhibited the porous structure of the hydrogels, which is useful for the sustained release of Gar from the hydrogels. The synthesized hydrogels showed significant inhibition zones against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Furthermore, cell culture studies confirmed the cyto-compatibility of the synthesized hydrogels. Thus, the novel hydrogels presented in this study can offer antibacterial effect during wound healing and promote tissue regeneration.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.

The study is an attempt to enquire into the preference of undergraduate students, after a considerable and over a year-long experience with Online Teaching and Learning (OTL), under the emergency preventive measure of switching from the traditional face-to-face classes to online. The study followed an exploratory approach, with a quantitative survey followed by a qualitative one, and a convenient sampling method to collect responses from a substantial sample size. The study is positioned after more than a year of remote classes by the undergraduate student, and hence represents highly experienced reflections and preferences from these students, as compared to other studies conducted last year. The study has profound implications in considering, and questioning, the importance of on-campus classes, and significance of the physical presence of a tutor in the class, and its effect on the learning experience of undergraduate students.

This study was designed to assess variation of possible phytochemical compounds in the ethanolic extracts of Gigantochloa scortechinii rhizome. Destructive sampling was done by using selective random sampling method on four consecutive rhizomes from healthy clumps and was conducted at two natural forests and one secondary forest (planted). Homogenized sample were extracted using solvent extraction (70% ethanol) method. Ethanolic extracts of G. scortechinii rhizome were qualitatively analyzed using GC/MS GC2010 Plus, Shimadzu to determine the composition of phytochemical compounds and identified using FFNSC 1.3, NIST11, PMW_tox2, and Wiley229 spectral library. A qualitative variation was observed with a total of 56 compounds were identified and differentiated between study site and rhizome age. Results revealed that G. scortechinii rhizome contains various phytochemical compounds with potential as a plant of phytopharmaceutical importance. This is the first finding on the spatial and age-related effects of phytochemical compounds in a consecutive rhizome and of G. scortechinii rhizome specifically.

Antibiotic resistance has emerged as one of the major concerns to public human health due to issues in treatment and control of major infectious diseases. From discovery of penicillin in 1940, the antibiotic resistance originated and now developed the microorganisms as resistive strains to the major available antibiotics. Furthermore, studies on this captivating activity of the microbes provide insight into the complexities of microbial physiology and may offer some guidance in preventing the onset and consequent development of antibiotic resistance. Despite of initiatives taken in last few decades to overcome the issues, the trends of antibiotic resistance gained much peak. Antibiotic resistance appears to have emerged as a result of various factors including antibiotics being misused and overused in both the medical field and the agricultural sector. Important factors in the development of antibiotic resistance also include bacterial mutation, unplanned evolution, and horizontal gene transfers. In addition, antibiotics resistance imposed the financial consequences to public health and drug development research. Future advancements related to innovative antibiotics and molecular drug designing become challenge for researchers due to intensive multiple antibiotics resistance among human population. Many researches have been conducted on origin, evolutionary aspect of antibiotic resistance and mechanisms of antibiotics resistance, but its effect on future drug development is little understood. Therefore, the recent review will highlight the role of antibiotic resistance in drug designing and impacts of antibiotic resistance on drug development in future.

The chlorophyll is one of the most important natural pigments used extensively in the food industry. Two important factors for the production of chlorophyll are the use of plants rich in chlorophyll and efficiency of extraction method. Present investigation was performed to compare the extraction of photosynthetic pigments by using solvents of different chemical nature. The purslane plants with different growth behavior viz. Scrollable and standing were grown under shade and sunshine stress condition. Different solvents including diethyl ether, 5% ethanol, pure acetone, 20% acetone, pure methanol and 10% methanol were used to extract chlorophyll and carotenoids from the purslane plant. The results indicated that stress, growth type and different solvents had a significant effect on the extraction of chlorophyll and carotenoids. Different trend was observed in extraction rate for chlorophylls and carotenoids. Among the solvents, pure methanol was the best for extraction of chl a. Methanol and acetone were appropriate solvents to achieve the highest amount of chlorophyll from plant tissues. Among different solvents, pure methanol for chl a, pure acetone and methanol for carotenoids were best solvent for purslane plant with a growing type scrollable of under shade.

Australia is a unique continent surrounded by the ocean and the majority of catchments flow to the coast. Some of these catchments are gauged and others are ungauged. There are 405 gauged catchments covering 2,549,000 km2 across the coastal regions of 12 drainage divisions in Australia. Whereas there are 771 catchments conceptualised as ungauged covering additional 835,000 km2. The mean annual rainfall and PET and its spatial and temporal distribution vary significantly from one drainage division to another. We developed a continuous daily streamflow time series of all gauged and ungauged catchments from 1993 onwards. We applied the GR4J lumped conceptual model to these catchments. The performance of gauged catchments was analysed through (i) visual inspection of daily hydrographs, flow duration curves and daily scatter plots, and (ii) performance metrics including NSE and PBias. Based on the NSE and PBias, performance ratings of 80% and 96% of the models respectively were found 'good'. There was no relationship found between the catchment area and model performance. The ungauged catchments were divided into four categories based on distance from potential donor catchments where observed data are available for GR4J model calibration, and Köppen climate zone. The total ungauged catchments represent 24.7% of the total drainage division areas. The streamflow from ungauged catchments was estimated using GR4J model based on the parameters of their donor catchments. Overall, runoff ratios from ungauged catchments were found to be higher compared to their donor gauged catchments, likely driven by their higher rainfall and less PET. This tendency was particularly evident in two drainage divisions – the Carpentaria Coast (CC) and Tanami-Timor Sea Coast (TTS) where ungauged areas comprised 51% and 43% respectively. The mean gauged annual streamflow varied significantly across drainage divisions – 230 GL from South Australian Gulf (SAG) to 146,150 GL in TTS. The streamflow from all ungauged catchments was estimated at 232,200 GL per year. Overall, the average streamflow from all drainage divisions, including gauged and ungauged areas, across the coastal regions of Australia was estimated at 419,950 GL per year. This nationwide estimate of streamflow dataset could potentially enhance our understanding of coastal processes and improvements of marine modelling systems and tools.

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.

In this paper, a seamless connection between sensor technology and machine learning (ML) has been presented which has wide applicability in rehabilitation and physical medicine. The intent is to identify an ML algorithm which has a better performance, easy to deploy, and has less training time and consumes less computational resources. In short, we propose an algorithm which maximizes the synergy between a sensor and ML by maximizing classification performance and easy to do implementation, which is robust in computational power and lower in resource consumption. The premise of the work is to show the important considerations for evaluating ML algorithms for Upper-limb activity recognition for Physical medicine and rehabilitation field.

As we are aware Information Technology had its cutting-edge lifestyle from the overdue sixties of the remaining century whilst the Arpanet become introduced, funded with the aid of using the branch of protection of the USA. After that, the IT enterprise has come a protracted manner to its cutting-edge form in which its miles gambling a dominant function in each sphere of life. It has made innovative modifications in facts amassing and dissemination and worldwide communication. It is growing into a surely paperless painting environment. Also, we can now ship a message very without difficulty to everywhere withinside the international in seconds. From a schooling factor of view, we can have a digital elegance in which the teacher ought to take a seat down in any part of the arena and his college students scattered in all exceptional elements of the arena via video convention with the presentation of look at substances in addition to query and solution sessions. A health practitioner now sitting in any part of the arena ought to carry out a surgical procedure in which the affected person is mendacity in some other part of the arena. These work examples display where we stand these days compared to what has become 1/2 of a century back. But as we recognize, nothing on this international is only correct as the whole thing has a darkish side. In this paper, we might speak about the deserves and demerits of enforcing IT globally and in which we are heading withinside the future.

The laser differential equations are used to transform them into identical coupled maps. Valuable results are deduced during analytical and numerical studies on cavity loss. Phase and spatiotemporal synchronized attractors are observed via quasi-chaos under a certain range of controlling parameters, and symmetry breaking of chaotic attractors due to collision with their basin boundaries, and transpire differently from the previous attractors. During the numerical simulation, it is found that the sequence of repeated strange attractors if the coupling strength further increases, which are orthogonal mirror images (the dynamics of the system is the same at different values of controlling parameters). Moreover, it can help us to predict future problems and their solutions based on current issues, if we develop this model in more general.

People must have particular personality traits and social resources, also known as health literacy, in order to access, comprehend, and use information to make decisions about their health. Patients' ability to engage in complex disease management and self-care is strongly related to their level of health literacy. It can help us stay healthy by preventing illness and effectively managing existing illnesses. People with low health literacy (LHL) may find it difficult to manage their condition and prevent illness, which may lead to increased use of healthcare services. Furthermore, LHL is associated with increased hospitalizations, increased use of emergency care, decreased use of preventative services, and a worsened ability to understand labels and health messages, a worsened state of health, higher mortality, and more expensive medical care.

COVID-19 has affected 210 countries around the world, killed more than 240,000 and infected more than 3.4 million. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of noncommunicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes degree based topological indices of Bismuth Tri-Iodide chains and sheets with the help of M-polynomial.

The present work deals with the development of finite element methodology for obtaining the stress distributions in thick cylindrical HK40 stainless steel pipe that carry high temperature fluids. The material properties and loading are assumed to be random variables. Thermal stresses that are generated along radial, axial and tangential directions are computed generally using analytical expressions which are very complex. To circumvent such an issue, the probability theory and mathematical statistics have been applied to many engineering problems which allows to determine the safety both quantitatively and objectively based on the concepts of reliability. Monte Carlo simulation methodology is used to study the probabilistic characteristics of thermal stresses which is used for estimating the probabilistic distributions of stresses against the variations arising due to material properties and load. A 2-D Probabilistic finite element code is developed in MATLAB and the deterministic solution is compared with ABAQUS solutions. The values of stresses that are obtained from the variation of elastic modulus are found to be low as compared to the case where the load alone is varying. The probability of failure of the pipe structure is predicted against the variations in internal pressure and thermal gradient. These finite element framework developments are useful for the life estimation of piping structures in high temperature applications and subsequently quantifying the uncertainties in loading and material properties.

In recent years, natural polymers have replaced synthetic polymers for antibacterial orthopedic applications owing to their excellent biocompatibility and biodegradability. Zein is a biopolymer found in corn. The lacking mechanical stability of zein is overcome by incorporating bioceramics e.g. mesoporous bioactive glass nanoparticles (MBGNs). In present study, pure zein and zein/Zn-Mn MBGNs composite coatings were deposited via electrophoretic deposition (EPD) on 316L stainless steel (SS). Zn and Mn were co-doped in MBGNs in order to make use of their antibacterial and osteogenic potential, respectively. A Taguchi design of experiment (DoE) study was established to evaluate the effect of various working parameters on the morphology of the coatings. It was observed that coatings deposited at 20 V for 5 min with 4 g/L concentration (conc.) of Zn-Mn MBGNs showed highest deposition yield. Uniform coatings with highly dispersed MBGNs were obtained adopting these optimized parameters. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-Ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR) were employed to investigate the morphology and elemental composition of zein/Zn-Mn MBGNs composite coating. Surface properties i.e. coating roughness and wettability analysis concluded that composite coatings were appropriate for cell attachment and proliferation. For adhesion strength various techniques including tape test, bend test, pencil hardness test, and tensile test were performed. Wear and corrosion analysis highlighted the mechanical and chemical stability of coatings. Colony forming unit (CFU) test showed that zein/Zn-Mn MBGNs composite coating was highly effective against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) due to the presence of Zn. The formation of hydroxyapatite (HA) like structure upon immersion in simulated body fluid (SBF) validated the in vitro bioactivity of the coating. It was concluded that zein/Zn-Mn MBGNs coating synthesized in this work can be used for bioactive and antibacterial orthopedic applications.

Globally, large numbers of adults remain unbanked and most of them live in rural areas of the Third World. The recent outbreak of the COVID-19 pandemic has shown us how inequalities in accessing financial services continue to affect us. However, financial inclusion has emerged as an effective tool to tackle socioeconomic ills and drive economic development. In fact, due to these modern technological developments, the number of studies in this area is very limited, especially in the context of developing economies. This study examines the impacts of migrant remittances on digital financial inclusion within households using the Migration and Remittance Household Survey in Bangladesh. To meet the research objectives of this study, a household survey was conducted and interviewed 2,165 households in 2022-2023 in Bangladesh. This study finds that the coefficient of remittance has a positive relationship with the probability of using mobile banking for a household's financial transactions. However, the use of ATM cards by households for financial transactions has not been significantly affected. The article concludes that remittance flows may enhance access to and use of digital financial inclusion by reducing some of the barriers and costs in Bangladesh, which can greatly contribute to the country's economic growth by creating and increasing a strong fund for investment.

When discussing the Diophantine quintic equation $p(a^5 + b^5) = q(c^5 + d^5)$ where p is a prime and q is an integer, there is a clear gap between the mathematical literature and online forums. Because of the intrinsic complexity of parameterizing fifth-degree equations, this equation re- mains largely unexplored. In this work, we approach this quintic problem through algebraic methods with the goal of providing numerical solutions that illuminate its properties and behaviors.Our research uncovers in- triguing patterns and connections that shed light on the enigmatic nature of Diophantine quintic equations in this particular form.

Amyotrophic Lateral Sclerosis (ALS) is a prototypical neurodegenerative disease characterized by progressive degeneration of motor neurons to severely effect the functionality to control voluntary muscle movement. Most of the non additive genetic aberrations responsible for ALS make its molecular classification very challenging along with limited sample size, curse of dimensionality, class imbalance and noise in the data. Deep learning methods have been successful in many other related areas but have low minority class accuracy and suffer from the lack of explainailbilty when used directly with RNA expression features for ALS molecular classification. In this paper we propose a deep learning based molecular ALS classification and interpretation framework. Our framework is based on training a convolution neural network (CNN) on images obtained from converting RNA expression values into pixels based on DeepInsight similarity technique. Then we employed Shapley Additive Explanations (SHAP) to extract pixels with higher relevance to ALS classifications. These pixels were mapped back to the genes which made them up. This enabled us to classify ALS samples with high accuracy for a minority class along with identifying genes that might be playing an important role in ALS molecular classifications. Taken together with RNA expression images classified with CNN, our preliminary analysis of the genes identified by SHAP interpretation demonstrate the value of utilising Machine Learning to perform molecular classification of ALS and uncover disease-associated genes.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes Zagreb polynomials and redefined first, second and third Zagrebindices of Bismuth Tri-Iodide chains and sheets.

In this article we compute many topological indices for the family of Möbius ladder. At first we give general closed form of M-polynomial of this family and recover many degree based topological indices out of it. We also compute Zagreb indices and Zagreb polynomials of this family.

Aiming at the limitations of single-functionality, limited applicability, and complex designs prevalent in current metasurfaces, we propose a terahertz multifunctional and multiband tunable metasurface utilizing a VO2-metal hybrid structure. This metasurface structure comprises a top VO2-metal resonance layer, a middle polyimide dielectric layer, and a gold film reflective layer at the bottom. This metasurface exhibits multifunctionality, operating independently of polarization and incident angle. The varying conductivity states of the VO2 layers, enable the metasurface to achieve various terahertz functionalities, including single-band absorption, broadband THz absorption, and multiband perfect polarization conversion for linear (LP) and circularly polarized (CP) incident waves. Finally, we believe that the functional adaptability of the proposed metasurface expands the repertoire of options available for future terahertz device designs.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. Closed forms of multiplicative degree-based topological indices which are numerical parameters of the structure and determine physico-chemical properties of the concerned molecular compound. In this article, we compute and analyze many multiplicative degree-based topological indices of silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q].

The partial discharge (PD) event in high voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well-established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of acoustic pulse and the acoustic reflections pose fundamental challenges to the Acoustic Emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse's shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

An efficient design of conservation tillage trencher (CTT) saves time, natural resources, and conserves soil health by avoiding vigorous soil disturbance of tillage operations. A two-wheel tractor operated CTT has constructed with modified rotary shafts, toolbar frames, depth control bars, bed shapers and chisel ploughs for conservation tillage operation of sugarcane plantation. The performance evaluation of developed CTT was tested for comparing the suitability with small-scale farmer’s practice (SFP) and large farm practice (LFP). Finally, the CTT is applied for preparing sugarcane farmland in different conservation tillage methods of i) bed cum trenching (BT), ii) zero-tillage trenching (ZT) and iii) strip-tillage (ST). The performance of effective field capacities of CTT were 0.14 ha h-1, 0.12 ha h-1 and 0.14 ha h-1 for BT, ZT and ST, respectively. Developed CTT saved time 80% and 26-37% over SFP and LFP, and required 96% and 26-36% less labour than SFP and LFP, respectively. Conservation tillage required 7-10 l ha-1diesel whereas SFP and LFP required 25 l ha-1and 65 l ha-1, which reduced CO2 emission by 60-72% and 85-89% compared to SFP and LFP, respectively. Ultimately, newly developed CTT saved sugarcane land preparation costs by 86% to 90% compared to conventional tillage systems.

Currently, various issues on environment have been discussed, whether the importance, destruction or ways to prevent the destruction of the environment. This paper will explore the issue from the conventional viewpoint as well as from the Islamic perspective. Destruction of the environment in recent times has worsened due to the uncontrolled exploitation of natural resources by human beings in order to generate profits. In view of the increasing technological development in Malaysia presently, this matter should not have occurred because the citizens intellectual abilities can be considered advanced. In other words, these people should be able to weigh between positive and negative consequences of voraciously exploiting natural resources. However, the greed that engulfs some of these people has obscured their view from grasping the future consequences of their acts. Based on the Islamic perspective in which the Quran is the ultimate reference, destruction of the environment can actually be prevented if every individual is aware of his or her trustworthiness or responsibility as His caliphate in this universe. Nevertheless, is there any specific verse in the Quran which explains about preservation of the environment? Can lessons from the Quran provide solutions to the environmental crises in Malaysia? This study provides explanations to the questions based on literature surveys and content analyses. By interpreting some selected verses that relate to preservation of the environment, findings from the discussions have identified that the Quranic verses are valuable resources for the sustainability of the environment.

There is clinical concern about the combined use of alcohol and opiates. Several lines of evidence support an interaction between alcohol and the endogenous opioid system. Thus, we hypothesized that ethanol by causing the release of opioid peptides may sensitize the system to the action of exogenous opioids such as morphine. In this study, using the place conditioning paradigm as an animal model of reward, we determined whether a morphine challenge would alter the pre-established preference induced by ethanol conditioning in mice, and whether this response was mediated by the mu opioid receptor (MOP). Given that ethanol exposure stimulates the release of opioid peptides, we also assessed the role of beta-endorphin (β-END) and enkephalins (ENKs) in this response. Mice lacking MOP, β-END and/ or ENKs as well as their respective wild-type controls were tested for baseline place preference on day 1, conditioned with ethanol (2 g/kg) versus saline on days 2 to 4 and then tested under a drug-free state for postconditioning place preference on day 5. On day 8, mice received a single injection of morphine (5 mg/kg) and were tested for place preference. On each test day, mice were placed in the central neutral chamber and allowed to freely explore the conditioning chambers. The amount of time that mice spent in each chamber was recorded. We found that a challenge dose of morphine given on day 8 enhanced the CPP response in mice previously conditioned with ethanol. This response was abolished in MOP null mice, confirming the role of MOP in this response. Although this enhanced response was not altered in mice lacking either β-end or ENKs compared to their wild-type littermates/controls, it was completely blunted in mice lacking both β-end and enkephalins. Together, these results suggest that these opioid peptides jointly mediate the crosstalk between the rewarding actions of morphine and ethanol.

Our daily activities hinge on the flexibility of our fingers, and a fractured finger can significantly disrupt these routines. The finger bones enable us to bend and fold the fingers and thumb to pick up or grasp objects and do all of our daily activities. A broken finger can cause adverse effects on our daily life activities. It is important to treat broken finger as soon as possible. Swift and precise treatment begins with capturing multiple X-rays, followed by the critical step of fracture detection in these images. Relying on the naked eye for this task carries the risk of overlooking small fractures. To address this issue an automated diagnoses of fractured fingers from images is required for which the current research employs advanced deep learning models—ResNet34, ResNet50, ResNet101, ResNet152, VGG-16, and VGG-19—to classify finger images from the Musculoskeletal Radiographs (MURA) dataset as either fractured or non-fractured. The results emphasize the consistently strong performance of ResNet models, attaining an impressive accuracy of 81.9%. This surpasses VGG models by 3.4% and establishes ResNet as the new benchmark for state-of-the-art accuracy.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. In this report, we study the silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q]. We compute several Zagreb polynomials and Redefined Zagreb indices of these silicon-carbons.

Family Phyllanthaceae is one of the largest segregates of the eudicot order Malpighiales and its species are herb, shrub, and tree, which are mostly distributed in tropical regions. Certain taxonomic discrepancies exist at genus and family level. Here, we report chloroplast genomes of three Phyllanthaceae species—Phyllanthus emblica, Flueggea virosa, and Leptopus cordifolius— and compare them with six others previously reported Phyllanthaceae chloroplast genomes. The species of Phyllanthaceae displayed quadripartite structure, comprising inverted repeat regions (IRa and IRb) that separate large single copy (LSC) and small single copy (SSC) regions. The length of complete chloroplast genome ranged from 154,707 bp to 161,093 bp; LSC from 83,627 bp to 89,932 bp; IRs from 23,921 bp to 27,128 bp; and SSC from 17,424 bp to 19,441 bp. Chloroplast genomes contained 111 to 112 unique genes, including 77 to 78 protein-coding, 30 transfer RNA (tRNA), and 4 ribosomal RNA (rRNA) that showed similarities in arrangement. The number of protein-coding genes varied due to deletion/pseudogenization of rps16 genes in Baccaurea ramiflora and Leptopus cordifolius. High variability was seen in number of oligonucleotide repeats while analysis of guanine-cytosine (GC) content, codon usage, amino acid frequency, simple sequence repeats analysis, synonymous and non-synonymous substitutions, and transition and transversion substitutions showed similarities in all Phyllanthaceae species. We detected a higher number of transition substitutions in the coding sequences than non-coding sequences. Moreover, the high number of transition substitutions was determined among the distantly related species in comparison to closely related species. Phylogenetic analysis shows the polyphyletic nature of the genus Phyllanthus which requires further verification. We also determined suitable polymorphic coding genes, including rpl22, ycf1, matK, ndhF, and rps15 which may be helpful for the reconstruction of the high-resolution phylogenetic tree of the family Phyllanthaceae using a large number of species in the future. Overall, the current study provides insight into chloroplast genome evolution in Phyllanthaceae.

In this article, our main purpose is to establish a new extension of Mittag-Leffler function by using the known extended beta function $\mathbf{B}_{\omega}(a,b;p)$ introduced in [1]. It led to a novel extension of the applicability of Mittag-Leffler function that introduced them as distributions defined for a specific set of functions. We also, investigate some of its important properties, namely recursion relation, Mellin transform and differential formulas.

The processing of fossil fuels is the major environmental issue today which should be lessen. Biomass is gaining much interest these days as an alternate to energy generation. Lignocellulosic biomass (cellulose, hemicellulose and lignin) is abundant and has been used for a variety of purposes. Among them, the lignin polymer having phenyl-propanoid subunits linked together through C-C bonds or ether linkages, can produce numerous chemicals. It can be depolymerized by microbial activity together with certain enzymes (laccases and peroxidases). Both acetic acid and formic acid production by certain fungi contribute significantly to lignin depolymerization. Natural organic acids production by fungi has many key roles in nature that are strictly dependent upon organic acid producing fungus type. Fungal enzymatic conversion of lignocellulosic is beneficial over other physiochemical processes. Laccases, the copper containing proteins oxidize a broad spectrum of inorganic as well as organic compounds but most specifically phenolic compounds by radical catalyzed mechanism. Similarly, lignin peroxidases (LiP), the heme containing proteins perform a vital part in oxidizing a wide variety of aromatic compounds with H₂O_2. Lignin depolymerization yields value-added compounds, the important ones are BTX (Benzene, Xylene and Toluene) and phenols as well as certain polymers like polyurethane and carbon fibers. Thus, this review will provide a concept that biological modifications of lignin using acidophilic microbes can generate certain value added and environment friendly chemicals.

The laser sintering process and modification of electrophoretic deposition (EPD) YSZ coatings on YSZ air plasma sprayed thermal barrier coatings (TBCs) were investigated. Ni-based superalloy was plasma sprayed using yttria-stabilized zirconia (YSZ) to perform thermal barrier coating with 400 μm thickness. The electrophoretic deposition (EPD) technique was used for depositing nanopowder of YSZ on the surface of YSZ TBCs. In this study, a technology of direct sintering the green EPD layer by laser beam was carried out. The best conditions of deposition YSZ overlay coating using DC current were obtained with applied voltage 40 V, deposition time 5 min, and suspension concentration 10 g/l. Iodine was added to the solutions as the stabilizing agent. To overcome the disadvantages of high sintering temperatures, laser sintering was taken as a new approach. Microstructures for all specimens were studied using Field Emission Scanning Electron Microscopy (FESEM) with EDS analysis. Surface roughness was investigated using AFM analysis and central line average (CLA). The results indicated that the morphology after the direct laser sintering of the EPD layer has a fine and controllable grain size, high hardness, and low roughness. Which is better than the direct laser on plasma-sprayed coatings.

This study aimed to assess knowledge and practice of caregivers and its relationship to the disease and nutritional status of children under five years of age in rural areas of Sylhet, Bangladesh. A total of 110 households having 6 to 59 months aged children was selected by simple random method from ten rural communities of three Upazila of Sylhet during September 2019 to February 2020. Descriptive statistics were used to assess the WASH knowledge & practice and multivariate chi-square analyses were performed to assess associations among diseases & nutritional status with WASH following a structured questionnaire. The study found a significant association of WASH with childhood disease and nutritional status, and 65% of children were found to be in a diseased state and 35% of children were found to be in a disease-free state within the last six months. The findings sketched that mother with poor wash knowledge and practice was at greater risk for disease outbreaks, disease frequency and duration. The highest incidence of diarrhea was 17% in children aged 12 to 23 months. Significant effect of WASH was also found in children nutrition status, that was reflected in the ratio of stunted, underweight and wasted children. Integrated convergent work focusing on the provision of clean water within the household, stop open defecation, promotion of hand washing, behavior change and poverty alleviation is needed to improve the situation. Health, nutrition and livelihood programs should be uninterrupted, and mothers or caregivers should be encouraged to participate in these programs.

Arsenic (As) is the most poisonous metalloid with negative effects on the plant and ecosystem. In the current study, observed that iron oxide nanoparticles (NPs) affected the molecular features of rice under arsenic (As) stress. The result showed that 1-D electrophoresis (SDS-PAGE) demonstrated variable expression of protein profiles. The polypeptide pattern was altered in the SDS-PAGE under arsenic stress. The findings also showed that low molecular weight polypeptides (MTs) expression was maximum under arsenic stress, while iron oxide NPs decreased the expression of these polypeptides and reduced the arsenic stress. RT-PCR was used to analyse the expression of the MYB transcriptional factor, WRKY, and OsGF14 genes in the rice plant. The results showed that these genes were up-regulated in response to arsenic stress, iron oxide NPs reduced arsenic stress, and Myeloblastosis (MYB), WRKY, and OsGF14 genes had very low expression levels. Our work showed that iron oxide nanoparticles (NPs) not only reduced the effects of arsenic stress but also decreased the expression of stress-related genes and metallothioneins (MTs).

Background and objectives: The appropriate use of antibiotics is the main strategy of Antimicrobial stewardship program. This study was planned to evaluate the quality of antibiotic prescriptions, its adherence with standard guidelines and surgeons’ perception regarding antibiotic use in surgeries. Methods: A prospective cross-sectional observational and survey-based study comprised of two sections: Phase 1; to investigate the antibiotic utilization in three most common abdominal surgical procedures during 9 months (January 2017 to September 2017). The appropriateness of antibiotics was compared with evidence-based guidelines. Phase 2; the surgeon’s perspectives were evaluated through a self-administered questionnaire (13 items) during the next three months (October 2017 to December 2017). Descriptive statistics, chi-square and Fisher’s exact tests analysis were used through SPSS Statistical Package 21.0. Results: A total of 866 eligible surgical cases out of 1015 were investigated. An acute appendectomy (n= 418; 48.2%) was most common surgical intervention followed by laparoscopic cholecystectomy (n= 278; 32.1%) and inguinal hernia (n= 170; 19.7%). About 97.5% of patients received antibiotics. Among these, 9.5% adhered according to guidelines with respect to correct choice, 40% for timing, 100% for dose and route (optimal value 100%). The ceftriaxone (J01XD04; n= 503; 59.5%) was most frequently prescribed antibiotic. A 200 participants (response rate 70.6%) filled out a validated questionnaire (internal consistency; α ≥ 0.7). One hundred and thirty-eight (69%) reported the overuse of antibiotics and most of them (97%) preferred broad-spectrum antibiotics instead of narrow-spectrum. The participants reported that non-availability hospital-based guidelines (n=193; 96.5%), prescribing of antibiotics without guidelines (n=186; 93%), underestimation of infection (n=177; 88.5%), lack of consensus (n=135; 67.5%) and poor awareness about guidelines (n=122; 61%) were the main determinants in their health care settings. Conclusions: The compliance of Surgical antibiotic was far below the recommendations of guidelines. The urgent needs of awareness among surgeons and implementation of antimicrobial stewardship program were important recommended interventions for appropriate use antibiotics.

The novel coronavirus disease (COVID-19) pandemic has resulted in over 720 million confirmed cases and 7 million deaths worldwide, with insufficient treatment options. Innumerable efforts are being made around the world for faster identification of therapeutic agents to treat the deadly disease. Postacute sequelae of SARS-CoV-2 infection or COVID-19 (PASC), also called Long COVID, is still being understood and lacks treatment options as well. A growing list of drugs are being suggested by various in silico, in vitro and ex vivo models, however currently only two treatment options are widely used: the RNA-dependent RNA polymerase (RdRp) inhibitor remdesivir, and the main protease inhibitor nirmatrelvir in combination with ritonavir. Computational drug development tools and in silico studies involving molecular docking, molecular dynamics, entropy calculations and pharmacokinetics can be useful to identify new targets to treat COVID-19 and PASC, as shown in this work and our recent paper that identified alendronate as a promising candidate. We have now investigated all bisphosphonates which can bind competitively to nidovirus RdRp-associated nucleotidyl (NiRAN) transferase domain, and systematically down selected seven candidates (CHEMBL608526, CHEMBL196676, CHEMBL164344, CHEMBL4291724, CHEMBL4569308, CHEMBL387132, CHEMBL98211), two of which closely resemble the approved drugs minodronate and zoledronate. This work and our recent paper together provide an in silico mechanistic explanation for alendronate and zoledronate users having dramatically reduced odds of SARS-CoV-2 testing, COVID-19 diagnosis, and COVID-19-related hospitalizations, and indicate that similar observational studies with minodronate could be valuable.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

The regulation of apoptosis depends upon the Bcl-2 protein family. The process of cell death and survival is highly complicated and regulated by various types of extrinsic as well as intrinsic network of biological system. Several enzymes and regulators play crucial role in cell death and survival cycle not only in healthy but also in pathological state particularly in cancer. In cancerous cells, various proto-oncogenes and anti-apoptotic proteins are activated and responsible for the cell survival and longevity. The mechanism of activation and inactivation of various proteins in cell survival is regulated by the process of phosphorylation (kinases) and dephosphorylation (phosphatases). The current review will summarize the dynamics of Bcl-2 phosphorylation and its role in apoptosis and cell survival.

Chronic fatigue and fibromyalgia symptoms frequently occur in major depressive disorder (MDD). The pathophysiology of these symptoms may in part, be ascribed to activated immune pathways, although it is unclear whether muscular factors play a role in their onset. The aim of the present study is to examine the role of muscle proteins in major depression in association with symptoms of chronic fatigue and fibromyalgia. We measured serum levels of agrin, talin-2, titin, and creatine phosphokinase (CPK) as well as the FibroFatigue (FF), the Hamilton Depression Rating Scale (HAM-D) and the Beck Depression Inventory (BDI-II) in 60 MDD patients and 30 healthy controls. The results show a significant increase in agrin and talin-2 in MDD patients as compared with controls. There were highly significant correlations between agrin and HAM-D, BDI-II and FF scores. Agrin, but not talin or titin, was significantly and positively associated with all 12 items of the FF scale. We found that a large part of the variance in HAM-D (47.4%), BDI-II (43.4%) and FF (43.5%) scores was explained by the regression on agrin, smoking, female sex (positively associated) and education (inversely associated). CPK was significantly and inversely associated with the total FF score and with muscle and gastro-intestinal symptoms, fatigue, a flu-like malaise, headache and memory, autonomic and sleep disturbances. These results suggest that aberrations in neuromuscular (NMJs) and myotendinous junctions may play a role in MDD and that the aberrations in NMJs coupled with lowered CPK may play a role in symptoms of chronic fatigue and fibromyalgia in MDD. Moreover, the increase of agrin in MDD probably functions as part of the compensatory immune-regulatory system (CIRS).

Over the last three decades, special economic zones (SEZs) have given new impetus to the ever-growing export-oriented industrialization in developing countries. Where various economies have benefited from SEZs, many zones have ended up becoming enclaves with trifling advantage. The SEZs in Pakistan have experienced the same fate and failed to contribute to exports, employment and creating linkages with the domestic economy. Recently under China Pakistan Economic Corridor (CPEC), SEZs are proposed to be set up in Pakistan; with a hope to fuel the stuttering economy. However, it is pertinent to first understand the local context and device policies considering stakeholders' perspectives. This study aims to identify the factors for the successful implementation of SEZs derived from the regional context of Pakistan. In-depth interviews are conducted from most relevant stakeholders, who have been involved in the development of SEZs. The results pointed towards the removal of political influence over zones and government taking the lead role in deciding the types of industry to be invited in these zones. Each zone should have a clear vision of development based on its regional advantage. The zone promotions should be based on competitiveness rather than fiscal incentives. Joint ventures and PPP to be encouraged inside the zones for sustainable operations.

Ghana Tamale's current waste management system is overwhelmed by the growing waste crisis, necessitating the exploration of Waste-to-Energy technologies as an innovative solution. This study explores challenges and opportunities for integrating Waste-to-Energy (WtE) technologies into Tamale's existing waste management system. Qualitative research identified policy hurdles, financial constraints, social concerns, and institutional weaknesses as key barriers. Conversely, stakeholder collaboration, public education, and capacity building emerged as some success fac-tors. A proposed implementation plan emphasizes feasibility studies, public engagement, pub-lic-private partnerships (PPPs), and technology selection based on waste composition. Addition-ally, a novel framework for WtE integration within a broader Integrated Solid Waste Manage-ment (ISWM) system is presented. This framework incorporates waste sorting, recycling, WtE alternatives, and responsible management of residuals. Validation by key stakeholders con-firmed the framework's potential to improve waste management in Tamale. By overcoming identified challenges and implementing the proposed framework, Tamale can achieve environ-mental sustainability, energy generation, and progress towards UN SDGs 7, 11, and 12. This re-search offers valuable insights for policymakers and paves the way for a cleaner and more sus-tainable future for Tamale, potentially serving as a model for other developing cities.

Ganoderma boninense is the major causal agent for the basal stem rot (BSR) disease in oil palm, causing the progressive rot of the basal part of the stem. Despite its prominence, key pathogenicity determinants for the aggressive nature of hemibiotrophic infection remain unknown. In this study, genome sequencing and annotation of G. boninense T10 were carried out using the Illumina sequencing platform and comparative genome analysis was performed with previously reported G. boninense strains (NJ3 and G3). The pan-secretome of G. boninense was constructed and comprised of 937 core orthogroups, 243 accessory orthogroups, and 84 strain-specific orthogroups. A set of core candidate effector proteins (CEPs) were found to be enriched with catalytic protein classified as the carbohydrate-active enzymes, hydrolases as well as non-catalytic proteins. Differential expression analysis revealed an upregulation of CEP genes which was linked to the suppression of PTI signaling cascade while the downregulation of CEP genes was linked to the inhibition of PTI by preventing host defense elicitation. Genome architecture analysis revealed the one-speed architecture of the G. boninense genome and the lack of preferential association of CEP genes to the transposable elements. The findings obtained from this study would aid in the characterization of pathogenicity determinants and molecular biomarkers of BSR disease.

Societal changes have had effects on deaths from all causes in Russia. Up until now, deaths from all causes have been well researched, although several inconsistencies persist on the contributions of researchers. This study assessed research output, trends and topics that shaped deaths from all causes studies in Russia. Using bibliometric and topic modelling approaches, deaths from all causes in Russia published from 1914 to date was analysed using data on publications, citations, journals, keywords co-occurrence, year of publication, institutional affiliations, and country of origin from Scopus. Overall results indicate a steady growth of publications in Russia was documented after 1985. The h-index of some top 10 authors did not surpass single digits. A network visualisation map showed that ‘Russia’, ‘male’, ‘mortality’ and ‘human’ were the most commonly encountered vital terms. Of the ten most prolific authors, McKee M, Shkolnikov VM, Bobak M, Samorodskaya IV and Andreev E were the first five. Although the top 10 journals researching on death causes in Russia were Russian, these journals were not included in the most cited journals. The most prolific institutions studying deaths in Russia included; Tehran University of Medical Sciences, London School of Hygiene and Tropical Medicine, University College London, Max Planck Institute for Demographic Research and National Research University-Higher School of Economics. Findings suggest that deaths from all causes research attention in Russia increased in recent years, but the number of publications and research related engagements (e.g., networking and/ collaboration) does not match-up to other countries (e.g., UK, US, Germany). This research lag calls for more collaborative research between public health disciplines and networking among researchers (i.e., both national and international).

Robot Operating System 2 (ROS 2) is a robotic software that uses a set of Quality of Service (QoS) policies to manage the quality of robot data transmissions in a network, such as the RELIABLE and KEEP_LAST options. In ROS 2 node communication, the RELIABLE connection guarantees that all message data can be properly sent from the publisher to the subscriber. However, strict reliability is not guaranteed if the RELIABLE connection uses the KEEP_LAST option to transmit the robot data in the publish-subscribe communication. This study aims to analyze the efficiency of local cache, cache control, and QoS balancing optimization to improve ROS 2 node communication when using the RELIABLE and KEEP_LAST options to transmit multi-robot data in Aggregated Robot Processing (ARP) architecture. Our idea in local cache and cache control is to streamline the sensor data output before processing it when the sensor device produces the data with the same value in a row. Furthermore, QoS balancing optimization aims to balance the DEPTH and DEADLINE QoS configuration to determine the rates and buffer size in ROS 2 node communication. This study shows that combining local cache and QoS balancing optimization improves multi-robot data transmission and cooperation in ARP architecture.

Aim: aim of this study is to evaluate the clinical and radiographic healing after repairing mechanical furcal perforations that occurred in primary molars by using MTA (Mineral Trioxide Aggregate) and search in some factors that may affect the prognosis of the treatment. Materials & Methods: we had 34 primary molars in 32 children aged 5–10 years, were treated by using MTA material after the occurrence of furcal perforation during pulpotomy procedure. Cases had been followed clinically and radiographically within 12 months. Statistical analyses were performed at p-value = 0.05. Results: All teeth were asymptomatic at the first week. Overall success rate was 79.3%. There was no significant statistically differences between overall-success rates according to the perforation size and continues bleeding in the furcation area (p-value > 0.05). Conclusions: Iatrogenic furcal perforations that may occur during pulpotomy in primary molars can be treated successfully by using MTA, and small sized-perforations may have more favorable prognosis than the large ones. Iatrogenic furcal perforations that may occur during pulpotomy in primary molars can be treated successfully by using MTA, and small sized- perforations may have more favorable prognosis than the large ones.

The most important plastic resins used for wire coating are Polyvinyl Chloride (PVC), Nylon, Polysulfone and Low-high density polyethylene (LDPE / HDPE). In this article,the coating process is performed using elastic-viscous fluid as a coating material for wire coating in a pressure type coating die. The elastic-viscous fluid is electrically conducted in the presence of an applied magnetic field. The governing non-linear equations are modeled and then solved analytically by utilizing an Adomian decomposition method (ADM). The convergence of the series solution is established. The results are also verified by Optimal Homotopy Asymptotic Method (OHAM). The effect of different emerging parameters such as non-Newtonian parameters α and β, magnetic parameter M and the Brinkman number Br on solutions (velocity and temperature profiles) are discussed through several graphs. Additionally, the current result also compares with the published work already available in the literature.

Bile acids (BA) are classically known as an agent important in lipid absorption and cholesterol metabolism. Nowadays, BAs have been found to be involved in various cellular signaling pathways such as protein kinase cascades, cyclic AMP (cAMP) synthesis and calcium mobilization. In addition, they have also been shown to regulate glucose and energy homeostasis. Bile acids are ligands for several nuclear hormone receptors, including FXR. Recently, muscarinic receptor and TGR5, G-protein-coupled receptor (GPCR), have been suggested to play a role in bile acid activity which is independent of nuclear hormone receptors. Moreover, BAs have also been studied in other GPCR associated pathways, namely sphingosine-1-posphate and glucagon receptor. Hydrophobic bile acids have been proven to affect heart rate and its contraction. Elevated bile acids are associated with arrhythmias in adults and fetal heart. Altered ratios of primary and secondary bile acid are reported in chronic heart failure patients. Meanwhile in patients with liver cirrhosis, cardiac dysfunction has been strongly linked to the increase of serum bile acid concentrations. In contrast, the most hydrophilic BA known as ursodeoxycholic acid has been found beneficial in improving peripheral blood flow in chronic heart failure patients and protecting heart against reperfusion injury.

The fidelity of the decadal experiment in Coupled Model Intercomparison Project Phase-5 (CMIP5) has been examined, over different climate variables for different temporal and spatial scales, in many previous studies. However, most of the studies were for the temperature and temperature-based climate indices. A quite limited study was conducted on precipitation of decadal experiment and no attention was paid to a catchment level. This study evaluates the performances of eight GCMs (MIROC4h, EC-EARTH, MRI-CGCM3, MPI-ESM-MR, MPI-ESM-LR, MIROC5, CMCC-CM, and CanCM4) for the monthly hindcast precipitation of decadal experiment over the Brisbane River catchment in Queensland, Australia. First, the GCMs datasets were spatially interpolated onto a spatial resolution of 0.050×0.050 (5 km× 5 km) matching with the grids of observed data and then were cut for the catchment. Next, model outputs are evaluated for temporal skills, dry and wet periods, and total precipitation (over time and space) based on the observed values. Skill test results reveal that model performances varied over the initialization years and showed comparatively higher scores from the initialization year 1990 and onward. Models with finer spatial resolutions show comparatively better performances as opposed to the models of coarse spatial resolutions where MIROC4h outperformed followed by EC-EARTH and MRI-CGCM3. Comparing the skills, models are divided into three categories (Category-I: MIROC4h, EC-EARTH, and MRI-CGCM3; Category-II: MPI-ESM-LR and MPI-ESM-MR; and Category-III: MIROC5, CanCM4, and CMCC-CM). Three multimodel ensembles’ mean (MMEMs) are formed using the arithmetic mean of Category-I (MMEM1), Category-I and II (MMEM2), and all eight models (MMEM3). The performances of MMEMs are also assessed using the same skill tests and MMEM2 performed best which suggests evaluating the models before the formation of MMEM.

Being a great source of protein, B-vitamins and minerals, meat and fish are staple foods in many cultures. However, cooking at high temperatures can produce chemicals associated with an increased risk of developing cancer. This review investigates the possible carcinogenic activity of chemicals formed during the cooking of meat and fish including heterocyclic amines (HCAs), polycyclic aromatic hydrocarbons (PAHs), and advanced glycation end products (AGEs). High-temperature cooking methods for meat, including grilling or frying, result in the formation of HCAs. Meat that has been smoked, grilled, or cooked over an open flame produces PAHs whereas, dry heat methods including roasting, grilling, and frying results in formation of AGEs. In vitro studies have shown that these compounds can damage DNA, cause mutations, and promote the growth of cancer cells. Research shows that thoroughly cooked meat increases the risk of cancer, particularly colorectal, pancreatic, and prostate cancer. Alternative cooking techniques, marinades, and incorporating fruits and vegetables can help to mitigate this risk. For determining the efficacy of these measures, additional studies are required. For the purpose of lowering the potential carcinogenic activity of chemicals formed during the cooking of meat and fish, mitigation techniques must be understood and put into practice. Cancer can be avoided by informing people about the dangers of eating meat and fish that have been cooked at high temperatures and by encouraging better diets and cooking styles. In order to lessen the possible health concerns related to the eating of meat and fish, further studies are required.

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

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.

Oil spillage over a sea or ocean’s surface is a threat to marine and coastal ecosystems. Spaceborne synthetic aperture radar (SAR) data has been used efficiently for the detection of oil spills due to its operational capability in all-day all-weather conditions. The problem is often modeled as a semantic segmentation task. The images need to be segmented into multiple regions of interest such as sea surface, oil spill, look-alikes, ships and land. Training of a classifier for this task is particularly challenging since there is an inherent class imbalance. In this work, we train a convolutional neural network (CNN) with multiple feature extractors for pixel-wise classification; and introduce to use a new loss function, namely ‘gradient profile’ (GP) loss, which is in fact the constituent of the more generic Spatial Profile loss proposed for image translation problems. For the purpose of training, testing and performance evaluation, we use a publicly available dataset with selected oil spill events verified by the European Maritime Safety Agency (EMSA). The results obtained show that the proposed CNN trained with a combination of GP, Jaccard and focal loss functions can detect oil spills with an intersection over union (IoU) value of 63.95%. The IoU value for sea surface, look-alikes, ships and land class is 96.00%, 60.87%, 74.61% and 96.80%, respectively. The mean intersection over union (mIoU) value for all the classes is 78.45%, which accounts for a 13% improvement over the state of the art for this dataset. Moreover, we provide extensive ablation on different Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) based hybrid models to demonstrate the effectiveness of adding GP loss as an additional loss function for training. Results show that GP loss significantly improves the mIoU and F1 scores for CNNs as well as ViTs based hybrid models. GP loss turns out to be a promising loss function in the context of deep learning with SAR images.

In the radar system, detection represents a basic and important stage in the receiver side. The detection process is based on the thresholding criteria; two philosophies of this criteria, constant and adaptive threshold. The constant threshold is simple in design, but it has a mis-detection and does not control the false alarm rate. As for the adaptive threshold, it is powerful in target detection, and better control of the false alarm rate, where it is called Constant False Alarm Rate (CFAR). Lots of research in the CFAR design, but the gap in the previous works is that there is no CFAR algorithm can be working with all or most environmental fields and all or most target situations.In this paper, The CFAR, which can work with the most environment and most of the target situations, has been presented. The producing the design and implementation of the new practical CFAR processor is presented. Where, the new CFAR is a combination of the properties of three different CFAR algorithm (CA, OSGO, and OSSO), and from two different families; averaging and statistical. Where it has overperformed of it's is 97.25% for simulation and 96.25% for the implementable version for different target situations. The simulation analysis is made by using Matlab 2015, while the implementation is done by using Xilinx Spartan 700 3a.

The tumor necrosis factor receptor associated factor 1 (TRAF1) plays a key role in promoting lymphocyte survival, proliferation, and cytokine production. Recent evidence showed that TRAF1 plays opposing roles in monocytes and macrophages where it controls NF-B activation and limits pro-inflammatory cytokine production as well as inflammasome-dependent IL-1 secretion. Importantly, TRAF1 polymorphisms have been strongly linked to an increased risk of rheumatoid arthritis (RA). However, whether and how TRAF1 contributes to RA pathogenesis is not fully understood. Moreover, investigating the role of TRAF1 in driving RA pathogenesis is complicated by its multifaceted and opposing roles in various immune cells. In this study, we show that intraarticular injection of TRAF1 deficient macrophages into knee joints of wildtype (WT) mice subjected to the collagen antibody induced arthritis (CAIA) model of RA significantly exacerbated joint inflammation, immune cell infiltration and tissue damage compared to mice injected with WT macrophages. This study may lay the groundwork for novel therapies for RA that target TRAF1 in macrophages.

We investigate new graph characteristics namely total (vertex, edge) face irregularity strength of gen- eralized plane grid graphs Gmn under k-labeling Phi of type (Alpha, Beta, Gamma). The minimum integer k for which a vertex-edge labelled graph has distinct face weights is called the total face irregularity strength of the graph and is denoted by tfs(Gmn). In this article, the graphs G = (V;E; F) under consideration are simple, fi nite, undirected and planar. We will estimate the exact tight lower bounds for the total face irregularity strength of some families of generalized plane grid graphs.

Purpose: A novel coronavirus, SARS-CoV-2 was identified as the cause of COVID-19 eventually led to the declaration of Public health emergency of international concern and a pandemic by WHO due to its exponential global spread. Present study was conducted to investigate the impact of second wave of pandemic on mental wellbeing and social behaviors among university students of Pakistan during this crucial period of COVID-19 infection. Methods: A cross-sectional analytical study was designed to evaluate the psychosocial impact during the current COVID-19 outbreak among the students of The Islamia University of Bahawalpur, Pakistan. Snowball sampling or chain referral sampling procedure was adopted to recruit the participants in the study. Verbal informed consent was taken from all participants before recruitment in the study irrespective of their gender, age and socioeconomic status. Results: Mental health of university students during COVID-19 epidemic was affected to a varying degree revealing that 26.66% were recorded to have mild, 27.15% moderate and 17.04% suffering from severe anxiety out of total 1029 students. Students who were residing in urban areas with parents and having a steady family income were negatively associated and found protective factors against anxiety. However, having a relative or an acquaintance infected with COVID-19 was an independent risk factor for experienced anxiety. Positively associated factors with the level of anxiety symptoms included economic stressors, effects on daily-life, and academic delays whereas social support was negatively correlated with anxiety in COVID-19 related stressors. Conclusion: Public health emergencies and such pandemic are exerting serious psychological impacts on university students. It is recommended that the higher authorities should plan better policies to reduce this impact for the provision of high quality and timely crisis-oriented psychological services to university students.

Greenwater (splashing of water on the deck) loading is a classical problem faced by the designer of ship-shaped vessels, which becomes even worst when the vessel operates at harsh weather conditions for an extended period. Installation of breakwaters on the deck can play a crucial role in minimizing this impact. However, research on the design and optimization of the breakwater is still at its infancy, and this study aims at shedding further light on this area by proposing and analyzing the effectiveness of three breakwater designs on a fixed box-shaped vessel. Commercial CFD software is used for this investigation. However, the design model (without breakwater) was validated at first against experimental results of green water splashing, before performing the actual simulations with proposed breakwater design. A vertical plate is used as the deck structure, and greenwater pressure at several locations on that plate is measured to compare the effectiveness of various breakwater designs. Overall, breakwaters with openings (perforations, grillages etc.) found to be more effective in minimizing the pressure generated by the greenwater. Nevertheless, there are significant rooms for improvement on breakwater designs, and some topics for further research are also suggested in this regard.

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

Due to the prospective local and international markets, the neon tetra fish breeding industry has its own allure for fish lovers and as a side business. The goal of the study was to analyze the opportunities and difficulties associated with neon tetra fish farming in order to build a "Blue Economy" policy. The Depok City Food Security and Fisheries Service (DKP3) program was implemented with the help of key informants who were chosen based on the following criteria: 1) DKP3 Officials, such as the Board of Trustees of the Fish Farming Group (POKDAKAN), 2) Researchers from the BRBIH (Ornamental Fish Farming Research Center), 3) Practitioners/Extension Workers, and 4) POKDAKAN.The study's conclusions state that the relevant Dinas must support local policies based on natural identification that are strengthened at the national level, that routine human resource training needs to be improved, that technology needs to be taken into account in collaboration with the private sector, and that post-harvest and market access are essential for industry. The SWOT analysis's findings, which are in quadrant 1, show that the firm is in a position for rather aggressive expansion.

UPF3B is a constituent of the classical nonsense-mediated mRNA decay (NMD) pathway that degrades both the aberrant transcripts and a set of physiological transcripts. In higher eukaryotes, UPF3B have significant biochemical functions in diverse cellular processes including NMD and translation. UPF3B plays a crucial role in neuronal development and differentiation. Next-generation sequencing technologies identified several loss-of-function mutations in the UPF3B gene that results in neuro-developmental disorders in humans. To uncover the mechanistic role of UPF3B in neuronal functions, we have generated the UPF3B-knockout mammalian cell line model system using CRISPR-Cas9 gene editing method. RNA-Sequencing Analysis of cellular transcriptome from UPF3B-KO cells identified specific genes involved in cell growth and neuronal functions. Altered expression of genes related to the axon guidance pathway delineated the UPF3B function to regulate the neuron-specific genes. Functional enrichment analysis identified the genes involved in the disorders related to mental health and intellectual disability. Our study has the potential to identify the direct players of intellectual disability and will have broader implications.

Due to Motor Neurone Diseases, a large population remains disabled worldwide, negatively impacting their independence and quality of life. This typically involves a weakness in the hand and forearm muscles, making it difficult to perform fine motor tasks such as writing, buttoning a shirt, or gripping objects. This project presents a vision-enabled rehabilitation hand exoskeleton to assist disabled persons in their hand movements. The design goal was to create an accessible tool to help with a simple interface requiring no training. This prototype is built on a commercially available glove where a camera and embedded processor were integrated to help open and close the hand, using air pressure, thus grabbing an object. An accelerometer is also implemented to detect the characteristic hand gesture to release the object when desired. This passive vision-based control differs from active EMG-based designs as it does not require individualized training. Continuing the research will reduce the cost, weight, and power consumption to facilitate mass implementation.

N-Acyl-homoserine lactones, the Quorum sensing signaling molecules predominantly found in gram-negative bacteria, which regulate several bacterial genes including virulence and antibiotic resistant genes. The study was aimed to identify and characterize QS and QQ bacteria from different samples. 5 samples with different ecological background were collected from soil and 10 samples from hospital setup. 31 different bacteria were isolated with either QS or QQ activities all together. CV026 and A136 biosensor strains were used for the detection of QS and QQ positive strains. QS activity was observed by cross streaking test of bacteria against CV026, it was affirmed that 13 isolates from the soil and 5 from hospital equipment’s showed positive QS activity. QQ activity of each isolate was tested by well diffusion assay, C6-HSL and C12-HSL were our candidate AHL molecules. The AHL molecule degradation was detected in 4 isolates of soil and none from the samples obtained from hospital setup. The total of 6 strongly positive QS and QQ isolates were identified and selected for 16S rRNA gene sequencing. The phylogenetic analysis revealed that these isolates were closely related to Pseudomonas, Bacillus and Exiguobacterium genera. In contrast, 1 Gram positive bacterial isolate was also purified with QS potential.

Background: Asthma is a widespread chronic respiratory disease that poses a significant public health challenge. The current study investigated the associations between air pollution and asthma severity among individuals residing near the Sohar industrial port (SIP) in Oman. Despite the presence of multiple major industrial complexes in Oman, limited knowledge regarding their impact on respiratory health is accredited. Hence, the primary objective of this study is to offer valuable insights into the respiratory health consequences of industrial air pollution in Al Batinah North. Methods: The state health clinics' records for patient visits related to asthma were collected for the timeframe spanning 2014 to 2022. Exposure was defined as the distance from SIP, Majan Industerial Area (MIA) and Sohar Industerial Zone (SIZ) to determine high, intermediate, and low exposure zones (12 km, respectively). Exposure effect modifications by age, gender, and smoking status were also examined. Results: The conducted cross-sectional study of 410 patients (46.1% males and 53.9% females) living in over 17 areas around SIP revealed that 73.2% of asthmatics were under 50 years old, with severity significantly associated with closeness to the port. Risk ratios were estimated to be (RR:2.42; CI95%: 1.01–5.78), (RR:1.91; CI95%: 1.01–3.6), and (RR:1.68; CI95%: 0.92–3.09) for SIP, MIP and SIZ areas, respectively, compared to the control area. Falaj Al Qabail (6.4 km) and Majees (6 km) had the highest number of asthma patients (N. 69 and N. 72), and highest percentages of severe asthma cases among these patients (28% and 24%) with significant risk ratios (RR:2.97; CI95%: 1.19–7.45 and RR:2.55; CI95%: 1.00–6.48), correspondingly. Moreover, severe asthma prevalence peaked in the 25-50 age group (RR:2.05; CI95%: 1.26–3.33), and this linkage between asthma and age was much more pronounced in males than females. Smoking and exposure to certain contaminant (dust and smoke) increased also the risk of severe asthma symptoms, but their effects were less important in the high risk zone, suggesting much more important risk factor. A neural network model accurately predicted asthma risk (94.8% accuracy), with proximity to Sohar Industrial Port as the most influential predictor. Conclusion: The study highlights the High asthma burden near Sohar Industrial Port, linked to port proximity and smoking and wind direction as major risk factors. These findings inform vital public health policies to reduce air pollution and improve respiratory health in the region, prompting national policy review.

1) Background: A significant proportion of child laborers are compelled to work in exploitative environments, experience both deteriorating health and financial loss. The present study sought to determine the factors affecting child labour and the characteristics of their working environment. 2) Methods: A questionnaire survey was conducted with 80 child labourers aged 5 to 17 years. Alongside descriptive statistics, a newly devised technique known as Influencing Causes Index (ICI) was administered and tested. 3) Results: The startling demographic findings reveal that peak share of child labourers are young children (12-14 years) and 32.5% child laborers had never attended school. The thorough assessment of determinants reflects that not only poverty, but schooling expenses and lack of access opportunity to primary schools are also the top-ranked push factors to trigger children towards labour. Around 72.5% of children work for over 8 hours a day. A significant proportion of participants received no leave, training, or access to hygiene facilities. The existing pattern of employment and working conditions resulted in musculoskeletal pain and dermatological infections among child labourers (p<0.05). 4) Conclusion: This research suggests that income measures for households, and an education programme for both children and parents would expedite the abolition of child labour.

This paper presents the development and implementation of a Pan-Tilt-Zoom (PTZ) camera interfaced with a Jetson processor hosting Artificial Intelligence (AI) algorithms, designed to address the challenges of traditional biometric capture for first-time passport photos of young children. The system enhances the accuracy, efficiency, and adaptability of facial biometric capture by recognizing and accommodating the dynamic and diverse behaviors of children. Utilizing AI, the system detects faces and analyzes facial features using 68 landmark points, ensuring high-quality images that meet ISO standards. These technical specifications, implementation process, and performance evaluations of the developed system are provided in this paper, demonstrating the potential of the proposed AI Face-Capture to advance biometric identification and verification for young children.