This paper discusses domestic problem of waiting hot water for the shower use till it reaches satisfactory temperature, which result a lot of wastage in fresh water. The outcome from research survey shows that there is no satisfactory solution till now as all solutions were either expensive or with no effective results. Local small inline electric heater equipped with fuzzy logic controller is proposed in this paper to be installed just before the showerhead to measure the water temperature and flow before the showerhead, as control input-variables, and decide the operating voltage of the heater, as control output-variable (MISO). MATLAB Simulink is used to model the proposed system. Different test cases are simulated to prove the performance and the safe operation of the system. Techno-economic study is carried out to determine the “Direct Benefits” and “Indirect Benefits” that can be achieved if such system is implemented in wide range. Azerbaijan data is taken as an example to calculate the economic benefits. The results show important benefits not only for economy but also for climate and the reduction of CO₂ gas emission. Different economic indices are provided to be an easy reference for decision makers and project managers.

Mitochondria is a cellular source of energy, playing an essential role in cellular stress induced by environmental stimuli. The genetic diversity of mitochondrial genes involved in oxidative phosphorylation affects the production of cellular energy and regional adaptation to various ecological (climatic) pressures influencing amino acid sequences (variants of protein). However, a little is known about the combined effect of protein changes on cell-level metabolic alterations in simultaneous exposure to various environmental conditions, including mitochondrial dysfunction and oxidative stress induction. Present study was designed to address this issue by analyzing the mitochondrial proteins in Fasciola species including Cytochrome C oxidase (COX1, COX2, COX3 and CYTB) and NADH dehydrogenase (ND1, ND2, ND3, ND4, ND5 and ND6). Mitochondrial proteins were used for a detailed computational investigation using available standard bioinformatics tools to explore structural and functional relationships. Our analysis shows that the mitochondrial protein family of Fasciola species are extensively diversified in all species studied, showing an extending role in various biological processes The results showed that the protein of COX1 of F. hepatica, F. gigantica and F. jacksoni consist of 510, 513 and 517 amino acids respectively. The alignment of proteins showed that these proteins are conserved in the same regions at ten positions in COX and CYTB proteins while at twelve locations in NADH. Three dimensional structure of COX, CYTB and NADH proteins were compared and the differences in additional conserved and binding sites in COX and CYTB proteins as compared to NADH were found in three Fasciola species. These results, based on the amino acid diversity pattern, were used to identify sites in the enzyme and the variations in mitochondrial proteins among Fasciola species. This study provides valuable information for future experimental studies including identification of therapeutics, diagnostics and immunoprophylactic interests with novel mitochondrial proteins.

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.

With the every passing day, the demand for data traffic is increasing and this demand forces the research community not only to look for alternating spectrum for communication but also urges the radio frequency planners to use the existing spectrum smartly. Cell size is shrinking with the every upcoming communication generation which makes the base station placement planning complex and cumbersome. In order to make the next-generation cost-effective, it is important to design the network in such a way which utilizes minimum number of base stations while ensure coverage and quality of service. This paper aims at develop a new approach using hybrid metaheuristic and metamodel applied in multi-transmitter placement planning (MTPP) problem. We apply radial basis function (RBF) metamodel to assist particle swarm optimizer (PSO) in a constrained simulation-optimization (SO) of MTPP to mitigate the associated computational burden of optimization procedure. We evaluate the effectiveness and applicability of proposed algorithm in a case study by simulating MTPP model with two, three, four and five transmitters.

Beaked whales (Ziphiidae) are rarely reported in the Arabian Sea. Four new cases (five individuals) were documented in deep waters offshore Pakistan through a pilot programme in 2015-2018 where trained fishers video-recorded net entanglements in the pelagic tuna drift gillnet fishery. Videos were analysed frame-by-frame. The large body size (est. 5-6m) of one specimen, its moderately bulbous melon, long tubular rostrum and a large falcate dolphin-like dorsal fin, indicated Longman’s beaked whale Indopacetus pacificus. It represents the first record for Pakistan (EEZ), and with a stranding at Gujarat, India, a second for the northern Arabian Sea. The other 4 ziphiids were significantly smaller (est. 3– 4.5m), with a decidedly non-bulbous melon, variable short to moderately short rostra, falcate to subtriangular dorsal fin and a nondescript greyish colouration, identified as Mesoplodon spp. Video quality was poor but none of the specimens showed tusks, arched mandible lines or noticeable linear tooth rakes, practically excluding adult males. The successful release of all net-entangled beaked whales is unprecedented. The simultaneous bycatch of two mesoplodonts in the same net set is equally exceptional. This citizen science strategy adds to our understanding of the distribution of I. pacificus and mesoplodonts, which may be more common in the Arabian Sea than the scarce literature suggests. If significant bycatch of beaked whales is confirmed, the massive tuna gillnet fishing effort in the Arabian Sea could have negative implications for their conservation status.

Introduction Color vision deficiency (CVD) constitutes one of the frequently observed eye disorders in all human populations. Color is a prominent sign utilized in the medical profession to study and identify histopathological specimens, lab instruments, and patient examination. Color deficiency affects the medical skills of students resulting in poor clinical examination and color appreciation. There is no effective screening of CVD at any level of the medical profession. Hence, this study was aimed to determine the prevalence of CVD among medical students. Materials and methods This was a cross-sectional study conducted from September 2019 to February 2020 over a period of six months in Karachi, Pakistan. All medical students aged 18-21 years of either gender enrolled in the first and second years of medical college were included in this study. The examination was performed during daylight. Ishihara plates were placed at a distance of 75 cm from the subject and tilted so that the plane of the paper lies perpendicular to the line of vision. Students were given five seconds to read the plate and one examiner was instructed to mark the checklist. A score of less than 12 out of 14 red/green test plates (not including the demonstration plate) was considered as a CVD. All statistical analysis was performed using Statistical Package for Social Sciences version 20.0 (Armonk, NY: IBM Corp). Results The mean age of the medical students was 19.61± 1.22 years. There were (n=123) 53.0% females and (n=111) 47.0% males. Most of the medical students (n=131, 56.0%) belonged to the upper-middle-class socioeconomic group. CVD was observed in (n=13) 6.0%of medical students. Age (p=0.001) and socioeconomic status (p=0.001) were the only demographic factors significantly associated with color deficiency. Conclusions Color deficiency, although an unnoticed concern, is fairly common among medical students. Medical students must be screened for CVD as this will enable them to be aware of their limitations in their future observational skills as a doctor and devise ways of overcoming them in clinical practice.

The microgrid is a small-scale, autonomous decentralized power plant with its own distributed generation, storage capacity and multiple loads, with the capacity to function in grid interconnected and an island mode. The decentralized control of microgrids with parallel operated voltage source converters (VSCs) is proposed in this paper to improve power quality using a machine learning approach. The DNN based MPPT controller is proposed and its best performance is presented. The SRF-PLL is utilized for AC side synchronization in VSC control. The proposed microgrid involves two PV arrays fed to two voltage source converters along with their independent controls, connected in parallel through LC filters and line coupling transformers and serves the loads at PCC. The proposed model is simulated using MATLAB/Simulink. The dq-framed inner loop control is employed to individually regulate the real and reactive power at the point of common coupling. Furthermore, the proposed model is analyzed and compared by employing a mathematical model of AC system dynamics, inner loop control, output voltage quality, AC harmonic spectrum analysis, and total harmonic distortion (THD) in both grid interconnected and island mode. In island mode, AC harmonic spectrum and THD are accomplished within the permissible range.

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.

Yeast extract is widely used in different food industries as a flavoring agent or vitamin supplement. In this study, a process was optimized for the production of yeast extract from Baker’s yeast (Saccharomyces cerevisiae). A glass vessel stirred fermenter was used for the cultivation of yeast biomass. The effect of various physical and chemical factors was evaluated on the production of yeast cells and optimum conditions for the production of maximum yeast biomass were determined. The optimum growth was obtained at 30ºC with pH 4.5 using molasses as a substrate supplemented with urea at 150rpm. Yeast cells were then separated by centrifugation and ruptured and autolysis was observed to be the most feasible method. Among various method employed to dry the yeast extract, spray dryer appeared as most efficient one. Yeast extract obtained after drying was subjected to different analyses and compared with commercial yeast extract. The produced yeast extract was applied in media preparation to grow different microorganisms including yeast, bacteria and fungi and considerable growth was observed. These results indicated that the developed process is a cost effective alternate approach for the production of yeast extract.

Previously the nanoparticles were synthesized by chemical methods which were costly and toxic to bio-systems. Plant extracts provides simpler, eco-friendly and cost efficient method for synthesizing nanoparticles. Lemon peel extract (LPE) was used to synthesize silver nanoparticles (AgNPs) which were evaluated for their antimicrobial effects after optimizing the pH of extract and concentration of both extract and synthesized AgNPs. The characterization of synthesized AgNPs was carried out using Ultraviolet-Visible (UV-Vis) Spectrophotometer, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Well diffusion method was used to determine the antimicrobial activities of synthesized AgNPs. The presence of phenols and proteins was assumed to reduce the Ag⁺ ion into silver nanoparticles. The characteristic surface plasmon resonance frequency was observed at 405–425 nm for all varying condition of silver nanoparticles synthesis. Furthermore, results revealed that the synthesized AgNPs remains stable upto 75 days. The average particle size was 2–5 nm, calculated with the help of scherrer’s equation by using XRD data. LPE mediated AgNPs (200 µg/mL) showed significant antimicrobial activity, compared to commercially available nanoparticles while LPE (50 mg/ml) showed no effect. LPE mediated AgNPs might get attention of pharmacists in order to design medicines against different diseases including the infections of bacteria.

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the world health organization declared it pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. In this urgency situation, development of SARS-CoV-2 based vaccines is immediately required. Immunoinformatic and molecular modelling are generally used time-efficient methods to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines is proved to be a promising immunization strategy against viruses and pathogens, which induce more comprehensive protective immunity. The current study demonstrated a comprehensive in-silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in-silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in E. Coli. Despite this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can present to be a better prophylactic solution against COVID-19.

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) linked with coronavirus disease 2019 (COVID-19) poses a serious threat to public health worldwide. Firstly, the SARS-CoV-2 was reported in Wuhan, Hubei Province, China in December 2019. Initially, the major proportion of virus-infected cases (i.e. about 99%) was reported in China and now it is being reported in other counties as well. Humans begin to be infected within their communities and transmittance of the viral epidemic increased rapidly due to lack of understanding of its transmission routes and precautionary measures. The existence of SARS-CoV-2 in China threatened the population greatly due to the high incidence of fatal respiratory infections. Current investigations speculated that this virus transferred into a human from viral-infected bats. However, the process of interspecies viral transmission is an important scientific question to be addressed. Due to the continuous increase in the patients infected with COVID-19 associated pneumonia, the World Health Organization (WHO) has included this viral epidemic to the priority list of diseases. Therefore, accelerated research developments are required to control the spread of this outbreak, as it is declared as a public health emergency by WHO especially in the absence of efficacious drugs and vaccines. Our review encompasses the recent status of disease severity in China, a particular replication mechanism of SARS-CoV-2 and potential risks and precautionary measures required to avoid contact with this fatal viral infection.

Trypanosomes are the extracellular protozoan parasites that cause human African trypanosomiasis disease in humans and nagana disease in animals. The disease is endemic in African countries where tsetse flies which act as a vector for the transmission of disease are present. The animals infected by these parasites become useless or workless and disease can become fatal if not treated. Old drugs used for treatment have many side effects and some are responsible for death in 5% of the patients. The parasite possesses a major surface protein known as variant surface glycoprotein. The immune system of the host develops antibodies against this antigen but due to antigenic variation, parasites evade the immune response. Currently, no vaccine is available that provides complete protection. Only partial protection using certain antigens in murine models was investigated. The tools of molecular biology and immunology have enabled a novel approach to the development of vaccines against trypanosomes. Immunization is the sole method for the control of disease because the eradication of the vector from endemic areas is an impossible task. Genetic vaccines can carry multiple genes encoding different antigens of the same parasite or different parasites. DNA immunization induces the activation of both cellular immune response and humoral immune response along with the generation of memory. This review highlights the importance of DNA vaccines and advances in the development of DNA vaccines against T. brucei.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

For bounded unit interval, we propose a new Kumaraswamy generalized (G) family of distributions from a new generator which could be an alternate to the Kumaraswamy-G family proposed earlier by Cordeiro and de-Castro in 2011. This new generator can also be used to develop alternate G-classes such as beta-G, McDonald-G, Topp-Leone-G, Marshall-Olkin-G and Transmuted-G for bounded unit interval. Some mathematical properties of this new family are obtained and maximum likelihood method is used for estimating the family parameters. We investigate the properties of one special model called a new Kumaraswamy-Weibull (NKwW) distribution. Parameter estimation is dealt and maximum likelihood estimators are assessed through simulation study. Two real life data sets are analyzed to illustrate the importance and flexibility of this distribution. In fact, this model outperforms some generalized Weibull models such as the Kumaraswamy-Weibull, McDonald-Weibull, beta-Weibull, exponentiated-generalized Weibull, gamma-Weibull, odd log-logistic-Weibull, Marshall-Olkin-Weibull, transmuted-Weibull, exponentiated-Weibull and Weibull distributions when applied to these data sets. The bivariate extension of the family is proposed and the estimation of parameters is given. The usefulness of the bivariate NKwW model is illustrated empirically by means of a real-life data set.

In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

Two-dimensional (2D) semiconductors like Transitional Metal Dichalcogenides (TMDCs) have attracted strong research interest in the last decade. Unlike the more celebrated 2D material graphene, TMDCs like molybdenum disulfide(MoS₂) possess bandgap. The number of layers critically depends on the band structure of MoS₂. For example, it is indirect for bulk MoS₂. However, it becomes direct bandgap material for a monolayer MoS₂. Monolayer MoS₂, therefore, becomes an important material for photoelectronic devices. An essential aspect of such devices is the metal-semiconductor junction. Metal-TMDC junction is, therefore, a well-studied interface due to its importance for 2D materials-based photoelectronic devices. Most importantly, it can be flexible, stretchable to it’s length, and bent to a large angle. We used metals like Au and Al to interface with TMDs like MoS₂. We used silicon and PDMS as substrates. So, we have to focus on investigating the relative properties of various TMDCs. We see change in band energy and vibrational modes via Photoluminiscence and Raman spectroscopy as shown in the article. However, certain aspects are yet to be explored, for example, how this interface behaves in the presence of strain.

The feasibility of using zeolites, synthesized from components found in municipal solid waste fly ash (MSW-FA), as sorbents for the recovery of nutrients (nitrate and phosphate) and heavy metals is critically assessed in this review. The inherent drawbacks of utilising a highly contaminated, variable, and relatively Al- and Si-dilute source such as MSW-FA to synthesize zeolites are discussed, and different methods to extract and decontaminate zeolite precursor materials from MSW-FA are considered. Ways to synthesize tailored zeolites and how their properties as well as the operational conditions impact the adsorption of cations such as ammonium and heavy metals are summarized. The use of surface-modified zeolites to adsorb nitrate and phosphate is also reviewed. And subsequently, approaches to utilise directly or recover for reuse the adsorbed compounds are considered, discussing potential challenges and mitigating measures related to leaching of unwanted compounds from the zeolites. Moreover, the possibility to regenerate the adsorption capacity of the zeolites for multiple adsorption cycles is considered. In the final chapter of the review a more general discussion of the main challenges and existing research gaps is provided, giving directions for recommended studies.

Owing to the upsurge in the number of endangered species and understanding animal patterns in general as well as population demographics; the monitoring of wildlife species is an essential for the conservation and safety of animals. In order to organize and manage the reserves, the nature bequeaths to us, we need to have hands-on information of their population and food trends, conditions where they survive and other species in the ecosystem. The paper presents a vision-based approach to monitor wildlife using an aerial platform. A quad-rotor based aerial platform is used for the very first time for this purpose. Field imaging is done using a digital cellphone camera mounted on the platform to acquire video of horses in the field. Two techniques, Lucas-Kanade and Horn-Schunck methods are applied on the acquired set of images and the results are compared. Noise due to fluctuations and light conditions are minimized using Gaussian and HSV filters. Experiments show results with an absolute mean difference of 2.84 pixels and 8.50 pixels for changes in X and Y directions respectively for the two approaches.

For autonomous driving, perception is a primary and essential element that fundamentally deals with the insight into the ego vehicle’s environment through sensors. Perception is a challenging task suffering from dynamic objects and continuous environmental changes. The issue gets worse due to interrupting the quality of perception by adverse weather like snow, rain, fog, night light, sand storm, strong daylight, etc. In this work, we have tried to improve camera-based perception accuracy, such as autonomous driving-related object detection in adverse weather. We proposed the improvement of YOLOv8-based object detection in adverse weather through transfer learning using merged data from various harsh weather datasets. Two prosperous open-source datasets (ACDC and DAWN) and their merged dataset were used to detect primary objects on the road in harsh weather. A set of training weights were collected from training on the individual datasets, their merged version, and several subsets of those datasets according to their characteristics. A comparison between the training weights also occurred by evaluating the detection performance on the above-mentioned datasets and their subsets. The evaluation revealed that using custom datasets for training significantly improves the detection performance compared to the YOLOv8 base weights. And using more images through the feature-related data merging technique steadily increases the object detection performance.

Rat is one of the most commonly used model animals for biological research. The organs and systems of human being are somewhat similar to that of rat in structure as well as functions, making it a valuable choice for research experimentation in biological sciences. A number of studies have been conducted to evaluate the potential risks and toxicity of different elements on the physiology and histology of rats. There is need to address certain environmental factors affecting rats condition during experimentation. Reproduction along with its pathologies is under investigation on larger scale throughout the world, being central for the existence of a species. These studies focus on the major factors that influence reproductive function. Review of literature clearly indicated the unwanted consequences of over nutrition, malnutrition, high or low temperature, non-enriched housing, improper handling, intense or poor light exposure and environmental pollution on histology and hormonal profile of reproductive system of rats.

Obesity is characterized by surplus buildup of body lipids primarily in adipose tissue. Prevalence and incidence of obesity are ascending persistently at an alarming rate. Unusual eating behaviors like compulsion to eat (food addiction) and excessive consumption are the premier contributors to obesity. Both are under influence of a variety of stimuli, mainly being stress, emotions, dietary restrictions, sweetness, hyperpalatability, neural pathways, hormonal imbalance and genetics. This review summarizes the potential driving factors behind overeating and food addiction for understanding and exploring obesity linked novel agents and processes as an endeavor to advance treatment approaches. Obesity has been studied extensively throughout the world due to high incidence and association with several metabolic disorders including cardiovascular disorders. The food addition has considered one of potential key factor of obesity and excessive weight gain. Sedentary life style and availability of food also induce obesity.

Purpose –The basic purpose of this paper is to find out the librarians perceptions, skills, most effective and constrains to use social media for the marketing purposes in the University libraries and to examine how these libraries perceive the importance of social media marketing. Design/methodology/approach –A nation-wide online survey on University libraries in the Pakistan was conducted to flourish this study, and a total number of 161 responses were used to analyze collected data. Findings –This study revealed the application of social media in university Libraries is very high .The results also disclosed that University libraries observe social media as a substantial tool to increase marketing of library sources and services anticipate to increase their use. Practical implications –The findings of this study can help as a parameter for University libraries when engaging social media for marketing purposes in their libraries. Originality/value –This study calculated the present situation of social media use for marketing in the University Libraries environment, a background that has been under-study in the literature, from these perspectives: perceptions, Skills, effectiveness, practices and constrains

The present study explained factors influencing citizen satisfaction service in the Investment and One-Stop Service Agency of Tanah Bumbu Regency. In particular, this research analyses the level of citizen satisfaction and the extent to which Awareness, Rules, Organizational, Income, Skill-Ability, and Service Facility Factor influence Citizen Satisfaction. This study uses a mixed methodology with a sequential explanatory strategy. Using the incidental sampling with Slovin's Formula to calculate the number of samples is 93 respondents. The quantitative data were analyzed by the SmartPLS 3.0 program. The findings showed that the level of citizen satisfaction is included in the category "Satisfied". Furthermore, the variable of Citizen Satisfaction is influenced by variables of Awareness, Rules, Organizational, Income, Skill-Ability dan Service Facility Factor for 70,5%. Whereas Awareness, Rules, Organizational, and Skill-Ability Factor has a significant influence on Citizen Satisfaction. Besides, Income and Service Facility Factor do not have a significant influence on Citizen Satisfaction.

The purpose of this study was to recommend to the government about the appropriate land use based on geoelectric and hydrochemical works. The results were supposed to be used as models for effective land use. During the study, a groundwater survey using a geoelectrical method was conducted and was used to map an aquifer flow. In general, Solok groundwater mapping was meant to provide information necessary to optimize follow-up activities for the use of clean water. It was also intended to minimize the negative impacts of exploitation and utilization of groundwater. This research aimed to provide information on groundwater conditions in Solok. It focused on the survey of groundwater sources, the inversion of measurement data on Sclumberger electrode configuration geoelectric in thirteen districts, and chemical analysis of pH, Fe, Nitrite, and DHL. The results show there was a great potential for groundwater-unconfined aquifers.

Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local Binary Pattern (CLBP). We first divide the image into blocks and then re-divide the blocks into cells. For each cell, we compute CLBP and then concatenate them to describe the texture of the corresponding block. We then train a multi-class Support Vector Machine (SVM) classifier, which classifies each block of image into one of four categories, i.e. Very Low, Low, Medium, and High. We evaluate our technique on the PETS 2009 dataset, and from the experiments, we show to achieve 95% accuracy for the proposed descriptor. We also compare other state-of-the-art texture descriptors and from the experimental results, we show that our proposed method outperforms other state-of-the-art methods.

We proposed a deep learning based chemometric data analysis technique. We trained L2 regularized sparse autoencoder end-to-end for reducing the size of the feature vector to handle the classic problem of curse of dimensionality in chemometric data analysis. We introduce a novel technique of automatic selection of nodes inside hidden layer of an autoencoder through pareto optimization. Moreover, linear regression, ϵ-SVR , and Gaussian process regressor are applied on the reduced size feature vector for the regression. We evaluated our technique on orange juice and wine dataset and results are compared against state-of-the-art methods. Quantitative results are shown on Normalized Mean Square Error (NMSE) and the results show considerable improvement in the state-of- the-art.

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

Quinine and its less toxic derivatives have served humanity for decades as potent antimalarial drugs. Emergence of drug resistance has narrowed the usage of these drugs in malaria prevention and treatment. Fortunately, these drugs have roles in the treatment of other diseases as well including rheumatic disorders and viral infections. Quinine derivatives have proven antiviral effects, especially against human immunodeficiency virus (HIV), Zika virus (ZiKV), herpes simplex virus (HSV), Ebola virus and dengue virus (DENV). The prophylactic and therapeutic role of Chloroquine/hydroxychroquine has become a topic of interest after the recent outbreak of novel Corona virus-19 (nCoV-19). This virus is also named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and WHO has officially named this disease as Corona virus disease 2019 (COVID-19). This lethal virus has affected almost 186 countries of the world till to date just in a period of four months of its outbreak. No approved antiviral drug is existed for the treatment of COVID-19. Therefore, this review is focused on potential prophylactic and therapeutic role of chloroquine/hydroxychlroquine for COVID-19.

Implants are used to replace damaged biological structures in human body. Although stain-less-steel (SS) is a well-known implant material, corrosion of SS implants led to the release toxic metallic ions which produce harmful effects in human body. To prevent material degradation and its harmful repercussions, these implanted materials are subjected to biocompatible coatings. Polymeric coatings play a vital role in enhancing the mechanical and biological integrity of the implanted devices. Zein is a natural protein extracted from corn and is known to have good bio-compatibility and biodegradability. In this study, Zein/Ag-Sr doped mesoporous bioactive glass nanoparticles (Ag-Sr MBGNs) were deposited on SS substrates via electrophoretic deposition (EPD) at different parameters. Ag and Sr ions were added to impart antibacterial and osteogenic properties to the coatings, respectively. In order to examine the surface morphology of coatings, optical microscopy and scanning electron microscopy (SEM) were performed. To analyze me-chanical strength, pencil scratch test, bend test, corrosion and wear tests were conducted on ze-in/Ag-Sr doped MBGNs coatings. The results show good adhesion strength, wettability, corro-sion, and wear resistance for zein/Ag-Sr doped MBGNs coatings as compared to bare SS sub-strate. Thus, good mechanical and biological properties were observed for zein/Ag-Sr doped MBGNs coatings. Results suggested these zein/Ag-Sr MBGNs coatings have great potential in bone regeneration applications.

Sustainable Humanitarian logistics is gaining attention due to increased disasters. It involves various operations to support people's survival efforts. Key characteristics include unpredictable demand, sudden large demand volumes, high stakes in delivery timeliness, and limited resources. However, the complexity and unpredictability of disaster scenarios necessitate robust and adaptable performance measurement models to evaluate the effectiveness of sustainable humanitarian relief logistics (SHRL). This study proposes a novel performance measurement model for sustainable humanitarian logistics and supply chains that integrates the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) method. In this research, using 115 articles focused on sustainable humanitarian logistics and supply chains, crisis management, and humanitarian aid, this research identified 25 key performance indicators (KPIs) in the initial phase. Following the implementation of FDM, 19 KPIs were identified as crucial for further analysis. These KPIs were then divided into four distinct categories: "Quality," "Accountability," "Operational Excellence," and "Sustainability". Initially, FDM is utilized to reach a consensus among experts concerning KPIs for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. The study concludes with the development of a comprehensive performance measurement model that facilitates the strategic planning and operational assessment of humanitarian organization operations. The integration of FDM and fuzzy DEMATEL methods offers multiple perspectives for decision-making and helps stakeholders identify critical areas for improvement. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and main cause in the cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas.

Wheat pollen, characterized by its short lifespan, exhibits rapid germination after anthesis. The preservation of wheat pollen is contingent upon environmental factors, including temperature, relative humidity, light, and wind. The objective is to develop a method for preserving wheat pollen effectively, specifically for the purpose of breeding. The short longevity of wheat pollen grains renders it impractical to conduct tests for pollen viability and in vitro germination on a large scale. Herein, the impact of storage temperatures and duration was assessed on pollen viability and in vitro germination to optimize storage conditions for preserving pollen viability. Pollen grains from 50 diverse spring wheat genotypes, each with three replicates, were harvested and stored at temperatures of 22°C, -20°C, and 4°C. Subsequently, pollen viability and in vitro germination rates were determined after storage of 1, 3, and 6 days. The results revealed that storage temperatures, durations, genotypes, and their interactions had a statistically significant impact on both pollen viability and in vitro germination. Notably, when pollen was kept at 22°C, almost all genotypes exhibited a loss of pollen viability and in vitro germination after 1, 3, and 6 days of storage. Likewise, storage at -20°C failed to extend pollen germination. However, at a storage temperature of 4°C, the pollen of 36 wheat genotypes exhibited a range of 6-14% in vitro pollen germination and remained viable even for 6 days. Simple linear regression analysis further revealed a significant negative correlation between pollen viability, in vitro germination, and storage time and temperature. In conclusion, our findings underscore 4°C as the optimal temperature for preserving pollen viability and in vitro pollen germination in spring wheat for up to 6 days. The results of the present study suggests that pollen viability of wheat is genotype de-pendent, storage temperature and storage duration. Thus, the 36 wheat genotypes identified during the present work could be efficiently maintained at 4◦C for short-term storage (6 days) and could be further used for genetics and breeding purposes.

Variations in groundwater levels that are noticed in different parts of the world are typically the primary focus of research carried out in hydrology. The fluctuating levels of groundwater can be ascribed to several different factors, some of which include an increase in the demand for water, inappropriate irrigation practices, improper management of soil, and unregulated extraction from aquifers. It is necessary to effectively manage groundwater resources to have a trustworthy method of measuring and forecasting groundwater levels. The dynamics of groundwater are inherently uneven and difficult to understand. As a result, applying methods driven by data could potentially yield significant gains in hydrology. In this study, two data-driven models were utilized to estimate groundwater levels at a total of 4 monitoring wells located in Colorado state, USA. These models included ARIMA and ANN. The comparative analysis of the algorithms made use of a data set that had one month's worth of information from each of the years 1980 to 2019. The models were put through their paces, and the results of those tests were statistically and visually assessed. To evaluate the relative accuracy and precision of the models, the mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE) were used. When compared to ARIMA, the analysis demonstrates that ANN can produce the most accurate forecasts of groundwater levels in Colorado state USA.

The emergence of digital twins (DTs) represents a recent advancement in technological processes that support the planning, construction, and oversight of constructed assets. A DT is essentially a digital model that facilitates simulations and two-way information exchange with its real-world counterpart (a physical twin), creating opportunities for data-driven decision-making. Despite the promising prospects of DTs, both the technology and the methodologies for developing them, as well as their potential applications, remain not fully understood in both academic and industrial contexts. This research explores the applications of DTs for the management of existing assets within the AEC/FM industry. The study presents the results of a comprehensive literature review that explores existing knowledge in this domain. The findings reveal that procedures for creating DTs are still in their early stages, emphasizing potential applications in asset management throughout their lifespan, facilitating sustainability upgrades, and supporting the maintenance and restoration of heritage assets. The review concludes by providing recommendations for future research in this evolving field.

Within the past few decades, thousands of experiments have been performed to characterize waste and biomass to estimate the bioenergy potential and product identification. There is a need to develop an integrated process model based on experimental literature, and simulation to obtain suitable products. In this study municipal solid waste (MSW) characterization and integrated process model have been developed to optimize final products in a reactor system. The process model has two modes R&D and reactor control (RC) to obtain suitable products including bio-oil, char, and gases. A database was integrated based on thermokinetics, machine learning and simulation models to optimize product efficiency. The experimental data includes thermogravimetric analysis, Fourier transform Infrared Spectroscopy, Gas chromatography, and Mass spectrometry, which are linked with pyrolysis experimental setup. Feedstock-product mapping models were incorporated into the database along with the temperature, heating rates, elemental analysis, and final product concentration, which are utilized for pyrolysis reactor setup. Product feasibility is conducted based on lifecycle cost, affordability, and product efficiency. The present work will bridge the gap between experimental study and decision making based on obtained products at several experimental conditions around the world.

This study investigates how a range of economic, environmental, and social indicators have influenced the concept of inclusive growth in 19 member countries of the Asian Cooperation Dialogue over the period spanning from 1995 to 2021. To analyze these relationships, the research employs the Driscoll Kraay's Standard Errors regression technique, designed to account for factors such as cross-sectional dependence, hetero-scedasticity, and autocorrelation within the data. Furthermore, various preliminary tests were conducted to assess the data for cross-sectional dependence, slope heterogeneity, heteroscedasticity, and autocorrelation. Additionally, the Westerlund cointegration test was employed to evaluate the potential long-term equilibrium relationships among the variables. The findings reveal that the influence of independent variables on the dependent variable, which in this case is the level of inclusive growth (ING), differs significantly among three distinct income categories: lower-middle-income countries (LMYCs), upper-middle-income countries (UMYCs), and high-income countries (HYCs). Notably, the results underscore the overall statistical significance and robust fit of the regression model for all three income groups. One of the primary contribu-tions of this research is the provision of empirical evidence concerning the role played by fishery and aquaculture production in fostering inclu-sive growth in the Asian context. This research also highlights the trade-offs between economic development and environmental sustainability in terms of trade openness, agriculture, forestry and fishing, ecological footprint, and renewable energy utilization. Enhancing inclusive growth in Asia requires improving fishery and aquaculture management, diversifying economic activities, reducing ecological footprint, and increasing renewable energy utilization. The paper suggests some future work directions for extending the analysis to other regions and indicators, as well as incorporating dynamic panel data models and causality tests. The paper also suggests some policy implications for fostering inclusive growth in Asia through regional cooperation, capacity building, technology transfer and green financing.

Asphaltene precipitation and deposition pose significant operational challenges in both reservoirs and surface facilities by inducing formation damage. To understand the kinetics involved in asphaltene particle nucleation, growth, and aggregation, this study employed confocal microscopy and centrifuge-based methods under a unified set of experimental parameters. The acquired time-resolved particle size images were analyzed using MIPAR image processing software, while asphaltene mass yield was quantitatively evaluated through centrifugation. Experimental conditions were varied to study the effects of heptane concentration, asphaltene concentration, and shear rate. Notably, this investigation introduces, for the first time, the parameter of particle count as an additional variable influencing asphaltene mass production. This study aims to discern how particle count correlates with asphaltene mass yield over time. Results indicate that the minimum mean particle diameter was observed to be 2 microns, which progressively grew up to 80 microns. The mean particle diameter exhibited a positive correlation with both asphaltene concentration and shear rate, whereas an inverse correlation was seen with heptane concentration. Furthermore, the asphaltene mass yield was found to increase with greater asphaltene and heptane concentrations, as well as with higher shear rates. The relationship between mean particle diameter and mass yield was found to be nonlinear. In the early stages, a higher prevalence of small particles contributed to a greater total particle count, while at later stages, particle aggregation led to the formation of larger particles that influenced the overall asphaltene mass. The insights gained from understanding the relationship between particle diameter, count, and mass yield are crucial for advancing the fundamental science of asphaltene precipitation and deposition. These findings may also guide future research that relies solely on particle counts for assessing asphaltene deposition.

Background: This study examines the relationship between energy usage, health issues, and pro-environmental behavior (PEB) in Kyrgyzstan, amidst the country's commitment to transition from coal-based energy to renewable sources in line with the Paris Agreement. The purpose is to investigate citizens' attitudes towards PEB and their intentions to engage in environmentally friendly actions, focusing on gas, electricity, and coal. Methods: Drawing upon the Theory of Planned Behavior (TPB) framework, a survey was conducted among 1,455 respondents to explore attitudes towards PEB and energy sources' impact on health issues. Results: Decarbonization efforts in Kyrgyzstan and Central Asia are in their early stages, with coal remaining a primary energy source. The study emphasizes the importance of governmental policies and citizen action in achieving decarbonization goals. Rising electricity costs outweigh the increase in indirect energy costs for food, posing challenges for households in adapting to changing energy dynamics. Conclusions: Targeted interventions and communication strategies are crucial to promote pro-environmental behavior and facilitate the transition to sustainable energy sources. Understanding the relationships between health concerns, air pollution awareness, PEB, and energy source choices can inform policymakers and organizations in their efforts to ensure a sustainable and healthy future for Kyrgyzstan and other Central Asian countries.

Durability of concrete requires a dense microstructure which can be achieved by using self-compacting concrete (SCC). Both calcined clay (CC) and rice husk ash (RHA) are promising supplementary cementitious materials (SCMs) that can partially replace cement, but their use in SCC is critical due to their higher water demand and specific surface area (SSA) compared to cement. Empirical method of SCC design was adopted considering the physical properties of both CC and RHA. The influence of partially substituting cement at 20 vol-% with binary and ternary blends of CC and RHA were investigated. The fresh properties of SCC were investigated using a variety of tests. The time dependent workability was monitored by plunger method and flow resistance determined based on the rheological measurements of SCC. The evolution of the hydrate phases of the binder in SCC was determined by thermogravimetric analysis, while the durability was evaluated by rapid chloride migration test. Cement partial replacement with 20 vol-% CC has no significant effect on SCC fresh, time dependent, compressive strength and durability properties. 20 vol-% RHA on the other hand requires higher dosage of SP to achieve self-compactability and increased the viscosity of SCC. Its workability retention is only up to 30 min after mixing and exhibited higher flow resistance. It consumes more CH and improves compressive strength and chloride resistance of SCC. The ternary blending with CC and RHA yielded better fresh SCC properties compared to the binary blend with RHA, while an improved chloride penetration resistance could be achieved compared to binary CC blend.

Measuring pulmonary nodules accurately can help with early diagnosis of lung cancer, which can improve a patient’s chances of survival. Many methods for segmenting nodules have been developed, but they all rely on input from radiologists in the form of a 3D volume of interest (VOI) or use a constant region of interest (ROI) and only consider the presence of nodule within the given VOI. These approaches limit the networks’ ability to detect nodules outside the given VOI and can also include unnecessary structures in the VOI, leading to potentially inaccurate segmentation. In this work, we propose a novel approach for 3D lung nodule segmentation by using 2D region of interest (ROI) inputted from radiologist or computer-aided detection (CADe) system. Particularly, we design a dual-encoder-based hard attention network (DEHA-Net) which incorporates the full slice of thoracic computed tomography scan along with the ROI mask to produce an accurate segmentation mask of lung nodule in the given slice. The proposed architecture exploits the adaptive region of interest (A-ROI) algorithm to automatically investigates the penetration of lung nodule into surrounding slices while eliminating the need to drawing separate ROIs in each slice. Further, the framework performs the multi-view analysis, i.e., in sagittal and coronal views, to improve the segmentation performance. The proposed scheme has been rigorously evaluated on the lung image database consortium and image database resource initiative (LIDC/IDRI) dataset and an extensive analysis of results have been performed. The quantitative analysis shows that the proposed method not only improves the existing state-of-the-art in term of dice score but also, significantly robust against the different types, shape and dimensions of lung nodules.

Migrant population have always been vulnerable for high burden of social exclusion, mental disorders, physical illness and economic crisis. The current COVID-19 pandemic has further created the frantic plight among them, particularly for the undocumented migrant workers in global south. We have conducted a mixed method study among the undocumented Myanmar migrant workers (UMMWs) in Thailand to explore how the COVID-19 disruption has impacted on their mental health and what are the coping strategies adopted by them. Following the onset of COVID-19 and the recent coup d'etat in Myanmar, our current study is the first attempt to understand the mental health status and predicament of this neglected migrant group. A total of 398 UMMWs were included in the online survey among whom 23 participated in qualitative interviews. The major mental health issues reported by the study participants were depression, generalised anxiety disorder, frustration, stress and panic disorder while loss of employment, worries about the pandemic, social stigma, refused access to healthcare, lockdown and fear of detention were the predominant contributing factors. In response, we identified two key coping mechanisms- coping at personal layer (listening to music, playing online game, praying, self-motivation) and social layer (chatting with family and friends, visiting religious institutions). These findings point to the importance of policy and intervention programs aimed to uphold mental health at such humanitarian conditions. Sustainable institutional mental health care support and social integration for the migrant workers irrespective of their legal status should be ensured.

A total $m$-labelling $\alpha$ on graph $\Gamma$ is called an edge irregular total $m$-labelling if for any two different edges of $\Gamma$, their weights respect to $\alpha$ are distinct, where the weight of any edge is defined as the sum of its label and the labels of its end vertices. We determine the minimum $m$ such that $\Gamma$ can be labelled by an edge irregular total $m$-labelling whenever $\Gamma$ is an odd staircase graph or an even staircase graph.

We investigate the behavior of thermal quantum coherence in the Heisenberg XXX model for a two-qubit system placed in independently controllable Inhomogeneous magnetic fields applied to two qubits respectively. We discuss the behavior of quantum coherence by systematically varying the coupling parameter, magnetic field, and temperature for both ferromagnetic and antiferromagnetic cases. The results show the interesting behavior of quantum coherence in a certain range of parameters. Generally, it is observed that quantum correlations decay with temperature, but in the ferromagnetic case with uniform magnetic interaction, it rises with temperature up to a certain threshold value and ultimately it decreases its value to zero. Moreover, it is observed that preserving the quantum coherence for small temperatures is very hard with the increasing magnetic field because, at small temperatures, quantum coherence decays sharply with the increase in magnetic field whereas at larger temperatures it decays completely at fairly large values of the magnetic field. The variation of quantum coherence with uniform magnetic field in the antiferromagnetic case is observed to be Gaussian for larger temperature but at zero or nearly zero temperature, it behaves as a constant function for uniform magnetic field up to a threshold value and then decays to zero with an infinite slope. This shows the signature of quantum phase transition from quantum nature to classicality.

Presently, nano-crystallization is widely accepted for increasing the solubility and biological barrier permeability of poorly soluble drugs. It improves the bioavailability of therapeutic agents, increasing the effectiveness for treating diseased conditions, and could be safely administered by oral, parenteral, or transdermal routes. Drug nanocrystals are drug particles coated with a thin polymer layer to enhance their stability and could be decorated with ligands for active targeting. In addition, nanocrystals, due to their morphological properties, improve cell internalization. Therefore, passive targeting by high cellular uptake and retention in the mononuclear phagocyte system (MPS) may be expected. Drug nanocrystals are formulated by either top-down or bottom-up methods and could be scaled up for industrial manufacturing. In the past few decades, nanocrystal formulation has been increasingly studied to overcome the limitations of BCS Class II and IV chemotherapeutic agents. The study of cytotoxic effects of drug formulation on cell lines gives an insight for estimating its in-vivo biodistribution. This review highlights the role of morphology, stabilizer, and ligand conjugation on drug targeting and cellular uptake in cancer cells, as well as a brief discussion on nanocrystal production.

Transverse momentum spectra of +, p, Λ, Ξ or ¯Ξ+, Ω or ¯Ω+ and deuteron (d) in different centrality intervals in Gold-Gold (Au-Au) and Lead-Lead (Pb-Pb) collisions at 62.4 GeV and 2.76 TeV respectively, are analyzed by the blast wave model with Boltzmann Gibbs statistics. We extracted Kinetic freeze out temperature,transverse flow velocity and kinetic freezeout volume from the transverse momentum spectra of the particles. It is observed that the non-strange and strange (multi-strange) particles freezeout separately due to different reaction cross-sections. While the freezeout volume and transverse flow velocity are mass dependent which decrease with the rest mass of the particles. The present work reveals the scenario of double kinetic freezeout in collisions at STAR and ALICE Collaborations. Furthermore, the kinetic freezeout temperature and freezeout volume are larger in central collisions than the peripheral collisions and they decrease from central to periphery. However the transverse flow velocity remains almost unchanged from central to peripheral collisions.

Classification of human actions from uni-modal and multi-modal datasets is an ongoing research problem in computer vision. This review is aimed to scope current literature on data-fusion and action-recognition techniques and to identify gaps and future research direction. Success in producing cost-effective and portable vision-based sensors has dramatically increased the number and size of datasets. The rise in number of action recognition datasets intersects with advances in deep-learning architectures and computational support, both of which offer significant research opportunities. Naturally, each action-data modality - such as RGB, depth, skeleton, and infrared - has distinct characteristics; therefore, it is important to exploit the value of each modality for better action recognition. In this article we will focus solely on areas such as data fusion and recognition techniques in the context of vision with a uni-modal and multi-modal perspective. We conclude by discussing research challenges, emerging trends, and possible future research directions.

Emerging and reemerging pathogens is a global challenge for public health. Recently, a novel coronavirus disease emerged in Wuhan, Hubei province of China, in December 2019. It is named COVID-19 by World Health Organization (WHO). It is known to be caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that affects the lower respiratory tract and manifests as pneumonia in humans. Coronaviruses (CoVs) are structurally more complicated as compared to other RNA viruses. This viral epidemic has led to the deaths of many, including the elderly or those with chronic disease or compromised immunity. Viruses cause infection and diseases in humans of varying degrees, upper respiratory tract infections (URTIs) cause common cold while lower respiratory tract infections induce pneumonia, bronchitis, and even severe acute respiratory syndrome (SARS). The costs of COVID-19 are not limited. It equally affects all the medical, sociological, psychological, and economic aspects globally. This is regarded as the third deadly outbreak in the last two decades after Severe Acute Respiratory Syndrome SARS (2002–2003) and Middle East Respiratory Syndrome MERS (2012). Based on the sequence homology of SARS-CoV-2, different animal sources including bats, snakes, and pangolins have been reported as potential carriers of this viral strain. Real-time RT-PCR represents the primary method for the diagnosis of new emerging viral strain SARS-CoV-2. The transmission dynamics suggest that SARS-CoV-2 is transmitted from person-to-person through direct contact or coughing, sneezing, and by respiratory droplets. Several anti-viral treatments including lopinavir/ritonavir, remdesivir, chloroquine phosphate, and abidor are also suggested with different recommendations and prescriptions. Protective and preventive strategies as suggested by various health organization i.e. WHO and US Center for Disease Control and Prevention (CDC) must be adopted by everyone. This review covers the important aspects of novel COVID-19 including characteristics, virology, symptoms, diagnostics, clinical aspects, transmission dynamics, and protective measures of COVID-19.

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear and has threatened global health security. Although phenomenal efforts are in progress to effectively combat this COVID-19 outbreak. Still, no licensed antiviral drugs or vaccines are available, and treatment is limited to supportive care and few repurposed drugs. In this urgency situation, computational drug discovery methods provide both an alternative and a supplement to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has shown the most successful strategy in antiviral drug discovery. The present study deals with the identification of potential compounds that specifically interact with SARS-CoV-2 vital proteins, including main protease (Mpro), Nsp12 RNA-dependent-RNA-polymerase (RdRp) and Nsp13 helicase. A constructive and integrated virtual screening efforts together with molecular dynamics simulations identified potential binding modes and favourable molecular interaction profile of corresponding compounds. Moreover, structurally important binding site residues in conserved motifs located inside the active site are elucidated, which displayed relative importance in ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural information obtained from this computational study paved the way to identify and design specific targeted inhibitors to combat COVID-19 outbreak.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

In this paper, a technique of image watermarking using multiple images as watermarks is presented. The technique is based on transform domain functions including discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) with an image as the host signal i.e. the watermarks will be used as proofs of the authenticity of the host image. The technique is executed by performing multilevel DWT followed by applying DCT and SVD to both the host and watermark. Multiple watermarks are used for the insurance of better security level. The scheme is immune to common image processing operations & some attacks and exhibits PSNR of 108.3781dB, normalized cross correlation (NCC) over 0.99 and normalized correlation (NC) over 0.99.

Agricultural intensification has been adopted as a viable option for Poverty eradication and hunger, attainment of food security, socio-economic wellbeing as well as sustainable livelihood across the West Africa sub-humid and semi-arid zones. Thus, there is need to identify and address the challenges of sustainable livelihoods in the agriculture-intensive semi-arid and dry sub-humid zones of West Africa. This was addressed through review of relevant literature and analysis of environmental parameters from recent research by the authors to unveil the environmental uncertainties that threaten the sustainability of agriculture and human livelihoods across the ecologically fragile regions of West Africa, using pointers from Nigeria. The research identified the fundamental challenges, adaptation and mitigation approaches to environmental constraints, and requirements for reducing risk, enhance agricultural resilience as well as livelihoods in the zones. This was based on the premise that primarily, the use of adequate and accurately derived environmental information is crucial for increased agricultural productivity, sustainability of economic diversification and human livelihoods and by implication, enhanced regional and national security.

The aim of this article is introduced the concept of double framed T-soft fuzzy set (DFT-soft fuzzy set) which is the combination of soft set and fuzzy set. We also defined the notions and apply this concept in BCK/BCI-algebras. By using example, we also discussed the concept of double framed T-soft fuzzy algebra (DFT-soft fuzzy algebra) and double framed B-soft fuzzy algebra (DFB-soft fuzzy algebra) and also investigated their properties. Each double framed T-soft fuzzy algebra is double framed B-soft fuzzy algebra but by using example, we proved that converse may or may not be possible.

In advanced world stroke is one of the disabling cause of death that can be managed with thrombolysis if presents early despite further risk of intracerebral haemorrhage. Secondary prevention is an important objective in ischaemic stroke where recurrence is very high with subsequent stroke. Carotid End Arterectomy impact a definitive and effective role for both symptomatic and asymptomatic carotid stenosis for secondary stroke prevention in selective cases. Thrombolysis is a potential primary management for certain group whereas carotid surgery employs secondary preventative measure in a specified ischaemic stroke group.

Salmonella enterica serovar Typhi, is one of the major infection spreading from consuming contaminated food and water. The poor sanitation is one the major cause for successful infection. S. typhi is responsible for causing typhoid fever, which is a growing public health concern in developing countries. This bacterium has acquired antimicrobial resistance to many promising which is a growing health concern for community. This study is aim to elucidate the molecular complexity of flouroquinolone resistance in S. Typhi isolates (n=286). Genomic data was downloaded from NCBI and analysis was done by Resfinder, MLST, and Pointfinder. Genomic analysis unveils a complex resistance profile, featuring antimicrobial resistance genes (ARG) including blaCTXM-15, blaTEM-1D, catA1, dfrA7, qnrS1, sul1, sul2, and tetA(B). The investigation focuses on mutations in DNA gyrA, parC, and qnrS1 genes which plays an important role in quinolone resistance. Mutation analysis reveals mutations such as DNA gyrA_S83F, DNA gyrA_D87N, DNA gyrA_S83Y, DNA gyrB_S464F, parC_S80I, and parE_L416F with the presence of qnrS1 gene produces resistance against quinolones. The Docking studies was conducted by “Autodock vina” and visualize by “Discovery studio” which demonstrate that these mutations leads to ciprofloxacin resistance, indicating reduced binding affinity, and altered solvent accessibility which indicates the structural changes at mutation sites. This study provides crucial insights into the molecular mechanisms driving flouroquinolone resistance in S. typhi, guiding future strategies to combat antibiotic resistance. Further validation through experimental mutagenesis is recommended, for targeted therapeutic interventions against the mounting threat of antibiotic-resistant S. typhi.

Herein, we have fabricated graphitic carbon nitride (g-C3N4) nanosheets with embedded ZnCdS nanoparticles to form a type II heterojunction using a facile synthesis approach and used for photocatalytic H2 production. The morphologies, chemical structure and optical properties of the obtained g-C3N4‒ZnCdS samples were characterized by a battery of techniques such as, TEM, XRD, XPS and UV-Vis DRS. The as-synthesized g-C3N4‒ZnCdS, photocatalyst exhibits the highest hydrogen production rate of 108.9 μmol·g-1·h-1 compared to individual components (g-C3N4: 13.5 μmol·g-1·h-1, ZnCdS: 45.3 μmol·g-1·h-1). The improvement of its photocatalytic activity is mainly attributed to the heterojunction formation and resulting synergistic effect, which provide more channels for charge carrier migration and reduce the recombination of photogenerated electrons and holes. Meanwhile, the g-C3N4‒ZnCdS heterojunction catalyst also showed higher stability over a number of repeated cycles. Our work sheds insight of using g-C3N4 and metal sulfide combination to develop low-cost, efficient, visible-light active hydrogen production photocatalysts.

This research aims to investigate the carbon fiber reinforced polymer (CFRP) when subjected to tensile, bending, and compression. Half of the specimens are also subjected to water to find out how water influences. The CFRP is created using a combination of carbon fiber layers and epoxy resin Bisphenol A Epichlorohydrin with hardener and is formed using the vacuum infusion method. From the water absorption test, it was found that the average weight gain of the specimens was 2.9% and the lowest value was at 0.6%, it was concluded that the increase in wet specimen weight was not too significant and water absorption tended to be slow. Mechanical testing ob-tained the highest average tensile stress, bending stress, compressive stress, and modulus of elasticity of 195 MPa, 295 MPa, 96 MPa, and 8914 MPa were from dry specimens while the lowest average values were 146 MPa, 286 MPa, 81 MPa, and 6160 MPa from wet specimens. The results of micro-photo observations on the tensile test fracture show that the specimen has a XGM fracture character with delamination and splitting fractures happening in multiple areas. In the bending test, the specimens experienced buckling fracture due to the fiber breaking and the inability of the matrix to withstand the additional stress. Shear fracture happened during the compressive test. In conclusion, water absorption has a bad impact towards the composite strength.

Recent progress in deep learning has led to accurate and efficient generic object detection networks. Training of highly reliable models depends on large datasets with highly textured and rich images. However, in real-world scenarios, the performance of the generic object detection system decreases when (i) occlusions hide the objects, (ii) objects are present in low-light images, or (iii) they are merged with background information. In this paper, we refer to all these situations as challenging environments. With the recent rapid development in generic object detection algorithms, notable progress has been observed in the field of object detection in challenging environments. However, there is no consolidated reference to cover state-of-the-art in this domain. To the best of our knowledge, this paper presents the first comprehensive overview, covering recent approaches that have tackled the problem of object detection in challenging environments. Furthermore, we present the quantitative and qualitative performance analysis of these approaches and discuss the currently available challenging datasets. Moreover, this paper investigates the performance of current state-of-the-art generic object detection algorithms by benchmarking results on the three well-known challenging datasets. Finally, we highlight several current shortcomings and outline future directions.

The construction industries face several challenges related to productivity. Productivity mainly depends upon labour effort and performance. The poor productivity of labour is one of the major reasons of time over-runs and increasing cost in construction projects. Our study aims to build a comprehensive assessment on the relationship between various factors that affect labour productivity in the construction of prestressed concrete Buildings in Ghana. A sample of 200 re-spondents collected from workers of Construction Company in Ghana. The questionnaire was designed which comprises two parts; the first part contains background information of the staff of construction company while second section explores the opinion of the staff regarding factors af-fecting labour productivity. The Smart-PLS was utilized to analyze and estimate the relationship among construct variables. By utilizing relative importance index and multiple linear regressions, it is identified that the management factor such as inadequate incentives; material factor such as poor quality of material; labour factors such as poor quality and training of labors; supervision factor such as incompetence of site supervisor; equipment factor such as frequent damage of equipment have a negative and significant relationship with labour productivity in the construc-tion of prestressed concrete buildings in Ghana. The findings of this study recommend that in order to improve labour productivity, the construction industries must conduct labour productivity measurements by adopting schedule for procurement of materials, safety programs, motivational system, and frequent meeting with project professionals.

In this study, silver-strontium doped hydroxyapatite (AgSr-HA)/chitosan composite coatings were deposited on stainless steel (SS) substrate via electrophoretic deposition (EPD) technique. The EPD parameters such as the concentration of Ag Sr-HA particles in the suspension, applied voltage and deposition time were optimized on by the Taguchi Design of Experiment (DoE) approach. DOE approach elucidated that the “best” coating was obtained at; the deposition voltage of 20V, deposition time of 7 minutes, and at 5 g/L of Ag Sr-HA particles in the suspension. The optimum coatings were characterized by using scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy. SEM images confirmed the deposition of chitosan/Ag Sr-HA on the SS substrate. The wettability studies indicated the hydrophilic nature of the chitosan/Ag Sr-HA coatings, which confirmed the suitability of the developed coatings for orthopedic applications. The average surface roughness of the chitosan/Ag Sr-HA coatings was in a suitable range for the attachment of bone marrow stromal cells. Chitosan/Ag Sr-HA coatings showed a potent antibacterial effect against the Gram-Positive and Gram-negative bacteria.

Optimizing the nitrogen (N) timings and rate can improve nutrient uptake, and nutrient-efficiencies, especially of N in wheat under the changing climate scenario. Climatic stress in the form of high temperature and drought resulted in the decreased crop physiology and, ultimately, grain yield. Taking the example of rainfed wheat, we quantified the impact of N application rates as full and split-dose at three variable sites of rainfed Pothwar, Pakistan by conducting field experiments for two years (2013-14 and 201-15). Treatments include, T₁ = Control (No fertilizer applied), full dose of N applied at the time of crop sowing, i.e. T₂ = 50 kg N ha^-1, T₃ = 100 kg N ha^-1 and T₄ = 150 kg N ha^-1 and split application of N at different timings during different stages of the crop called as split application of N, i.e. T₅: Application of 50 kg N ha^-1 (15 kg N ha^-1 (Sowing) : 20 kg N ha^-1 (Tillering) :15 kg N ha^-1 (Anthesis), T₆: Application of 100 kg N ha^-1 (30 kg N ha^-1 (Sowing): 40 kg N ha^-1 (Tillering) : 30 kg N ha^-1 (Anthesis) and T₇: Application of 150 kg N ha^-1(45 kg N ha^-1 (Sowing) : 60 kg N ha^-1 (Tillering) : 45 kg N ha^-1 (Anthesis). Three study sites include viz. Islamabad (High rainfall with optimum temperature), University Research Farm (URF)-Koont (Medium rainfall with moderate temperature), and Talagang (low rainfall with high temperature). Results showed that the highest stomatal conductance (0.80 mole m^-2 sec^-1), net photosynthetic rate (20.07 μmole m^-2s^-1), transpiration rate (9.58 mmole m^-2s^-1), intercellular CO₂ concentration (329.25 μmole CO₂ mol^-1 air), SPAD values (58.86 %) and proline contents (35.42 μg g^-1) were obtained for split application of N (T₆ = Split N₁₀₀) compared to control and full dose of N treatments. Among sites, these physiological traits remained highest at Islamabad and lowest at Talagang, while among years, maximum values of the measured parameters were obtained in 2013-14. A similar trend was observed for crop total N, N efficiencies, and agronomic traits of the crop. Our results suggest that optimum N application rate and its suitable timings can help to harvest real benefits of N as in our findings, split dose resulted in the maximum performance of the crop from physiological parameters to the agronomic traits of the rainfed wheat crop.

This paper reports the design, development, and testing of a novel, yet simple and low-cost portable device for the rapid detection of SARS-CoV-2. The device performs loop mediated isothermal amplification (LAMP) and provides visually distinguishable images of the fluorescence emitted from the samples. The device utilises an aluminium block embedded with a cartridge heater for isothermal heating of the sample and a single-board computer and camera for fluorescence detection. The device demonstrates promising results within 20 minutes using clinically relevant starting concentrations of the synthetic template. Time-to-signal data for this device are considerably lower compared to standard qPCR machine (~10-20 minutes vs >38 minutes) for 1×105 starting template copy number. The device in its fully optimized and characterized state can potentially be used as simple to operate, rapid, sensitive, and inexpensive platform for population screening as well as point-of-need SARS-CoV-2 detection and patient management.

The versatile one-pot green synthesis of a highly concentrated and stable colloidal dispersion of AgNPs was carried out using the self-assembled tannic acid without using any other hazardous chemicals. Tannic acid (Plant-based polyphenol) was used as a reducing and stabilizing agent for silver nitrate in a mild alkaline condition. The synthesized AgNPs were characterized for their concentration, capping, size distribution, and shape. The experimental results confirmed the successful synthesis of nearly spherical and highly concentrated (2281 ppm) AgNPs, capped with poly-tannic acid (AgNPs-PTA). The average particle size of AgNPs-PTA was found 9.90 ± 1.60 nm. The colloidal dispersion of synthesized nanoparticles was observed stable for more than 15 months in the ambient environment (25 oC, 65 % relative humidity). The synthesized AgNPs-PTA showed an effective antimicrobial activity against Staphylococcus Aureus Escherichia coli. Ag-PTA also exhibited enhanced catalytic properties. It reduces 4-nitrophenol into 4-aminophenol in the presence of NaBH4 with a normalized rate constant (Knor = K/m) of 615.04 mL·s-1·mg-1. Furthermore, AgNPs-PTA were stable for more than 15 months under ambient conditions. The unique core-shell structure and ease of synthesis render the synthesized nanoparticles superior to others, with potential for large-scale applications, especially in the field of catalysis and biomedical.

The contemporary landscape of eHealth is characterized by major concerns related to electronic medical records (EMRs). In an EMR, critical patient health information gets its own repository, which is the core of the eHealth system. Notably, the EMR not only retrieves health information generated in ambulatory clinical settings but also includes court-generated records. These overlapping records assume the role of a foundational data source for a comprehensive electronic health record (EHR). This scholarly review sheds light on recent trends in medical records and associated challenges, while at the same time providing insights into Saudi Arabia’s targeted approaches to healthcare delivery. Additionally, the talk expands to include a description of blockchain technology and its underlying conceptual framework. This demonstration positions blockchain technology as a promising approach that requires consideration for future use in the healthcare system.

In this study organic bulk heterojunction (BHJ) solar cell along with the spiro OMeTAD as a hole transport layer (HTL) and the PDINO as an electron transport layer (ETL) was simulated through the Solar Capacitance Simulator, one dimensional (SCAPS-1D) software to examine the performance of this type of polymer thin film organic solar cells. As an active layer the blend of polymer donor PBDB-T and non-fullerene acceptor ITIC-OE was used. Numerical simulation was performed by varying the thickness of HTL and active layer. Firstly, the HTL layer thickness was optimized to 50 nm, after that the active layer thickness varied up to 80 nm. These results of simulation demonstrated that the HTL thickness has rather little impact on efficiency while in the case of active layer thickness improves efficiency significantly. The temperature effect on the performance of solar cells was considered, by the simulation performed for temperature from 300 K up to 400 K and the efficiency of solar cell decreases with increasing temperature. Generally, polymer films usually are full of traps and defects, the density of defects (Nt) value was also introduced to the simulation, and it was confirmed that with the increasing of defect density (Nt), the efficiency of solar cell decreases. After thickness, temperature and defect density optimization, the reflection coating was also applied on it. It turned out that by introducing the reflection coating on the back side of solar cell, the efficiency increases by 2.5 %. Additionally, the positive effect of HTL and ETL doping on efficiency of this type of solar cells was demonstrated.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

Power and energy efficiency are among the most crucial requirements in high-performance and other computing platforms. This work examines through extensive experimentation methods and procedures suitable for assessing the power and energy efficiency of fundamental hardware building blocks inside a typical high-performance CPU, focusing on the dynamic branch predictor (DBP). The investigation relies on the Running Average Power Limit (RAPL) interface from Intel, a software tool for credibly reporting the power and energy based on instrumentation inside the CPU. We use well-known microbenchmarks under various run conditions to explore potential pitfalls and to develop precautions to raise the precision of the measurements obtained from RAPL for more reliable power estimation. The authors discuss the factors that affect measurements and share the difficulties encountered and the lessons learned.

The elegance of mathematical models in quantum mechanics has often been seen with awe, and especially frustration. Nonetheless, the mathematical physics of quantum mechanics is fascinating beyond measure. And fortunately, there are quite baffling things about quantum mechanics that showed us what we never thought could be seen, making it simpler to figure out the behavior of physical systems without having to delve into the subtleties of the subject. In this paper, we present a review on the density of quantum states in an intuitive fashion that is easily comprehensible to undergraduate students with an elementary background in physics.

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.

Recently there is a growing concern regarding potential health hazards linked with 5G deployment and radio frequency emitted by these stations. It becomes fundamentally important to scientifically address these concerns. In this paper, the health risks incorporated with 5G are discussed critically in the light of scientific work and debunk these tittle-tattles where required. We confute scientifically the “5G appeal”, discuss effects of 5G on health, its implications on privacy, pandemics, ecosystem and role of world health organization in fighting these narratives. Finally, we provide future direction to negate these false claims linked with 5G.

Hydrothermal /super critical processes are important process to synthesize materials which are otherwise difficult to form under normal conditions. A mathematical model is developed using standard transport equations to calculate the time for heating of hydrothermal reactor and computer simulation of the model was carried out in SOLIDWORKS® to validate it. The materials used to form reactor vessel were stainless steel (outer body) and TEFLON (PFA) (inner vessel). It was shown that composite wall, its geometry, construction & properties greatly affect the time and pattern of heat transfer. The time calculated and pattern generated were found to be in good agreement with experimental values.

The purpose of this paper is to develop WebSecuDMiner algorithm to discover unusual web access patterns based on analysing the potential rules hidden in web server log and user navigation history. Design/methodology/approach: WebSecuDMiner uses equivalence class transformation (ECLAT) algorithm to extract user access patterns from the web log data, which will be used to identify the user access behaviours pattern and detect unusual one. Data extracted from the web serve log and user browsing behaviour is exploited to retrieve the web access pattern that is produced by the same user. Findings: WebSecuDMiner is used to detect whether any unauthorized access have been posed and take appropriate decisions regarding the review of the original rights of suspicious user. Research limitations/implications: The present work uses the database which is extracted from web serve log file and user browsing behaviour. Although the page is viewed by the user, the visit is not recorded in the server log file, since it can be access from the browser's cache.

Along with the advantages associated with access to information and fast communication, screen time from increased digital media consumption has recently been associated with adverse effects on youth well-being. To get a clearer picture of its value for global youth based sustainability initiatives, this study investigates the effects of increased digital media consumption on youth's interests in ecosystem services, sustainability and science as a means for disease prevention. We achieve this, using data on 187821 adolescent students from 50 countries worldwide. Methodologically, we rely on a mixed bivariate ordered probit representation of youth's joint interest in the biosphere (ecosystem services and sustainability) and science as a means for disease prevention, which we then estimate using Markov Chain Monte Carlo (MCMC) Methods. We found that each level increase in adolescent students' reported frequency of news blogs visits and web browsing on broad science adversely affect their interests in ecosystem services, sustainability and science as a means for disease prevention. Although each level increase in youth's frequency of ecological website visits also reduces by 20% (with 95% CI [-0.36; -0.32]) their interests in the biosphere, it is found to increase however by 3% (with 95% CI [0.02; 0.05]) their interest science as a means for disease prevention. Overall, our results highlight heterogeneous effects of digital media consumption on adolescents' well-being in terms of their interests in ecosystem services, sustainability, and science as a means for disease prevention.

Background: Since the advent of virtual reality (VR), it has been used in medical education for surgical training and anatomy teaching. Recently, other modalities of extended reality (XR) such as augmented reality (AR) and mixed reality (MR) has also made its way into medical education. Although there has been research validating XR’s use in medical education, there have been few studies on the research trends of the different XR modalities. The paper aims to compare the research trends of the XR modalities in general and in terms of the medical fields studied and outcomes measured. Methods: Web of Science was searched, and preliminary data was extracted to analyze the general trend. Inclusion and exclusion criteria were then applied, and finalized articles were analyzed and grouped based on the medical field studied and outcomes measured. Results: 31 articles on VR, eight on AR and one on MR were included in the final analysis. We found that there is increasing research in VR since 1990 and AR since 2008. The research in MR is constant. Most of the papers on VR studied endoscopic surgery and anatomy whereas AR studied mostly anatomy and endovascular procedures. Using Miller’s prism of clinical competence, the competency measured most for VR and AR is “show”. Discussion and conclusion: Advancement in computing, communication and display technologies since 1990 may contribute to the increase in research on VR whereas the ubiquity of smartphone since 2008 may explain the increase in research on AR. Although both VR and AR are used in surgical training and anatomy teaching, we found possible strengths of VR in counseling and AR in practical skills. The competency "show" was measured most as most of the papers were on surgery, and the XR simulators used can capture surgical parameters

Endocannbinoids system (ECS) engrossed a considerable interest as potential therapeutic targets in various carcinomas and cancer related conditions alongside with neurodegenerative diseases. Cannabinoids are implemented in several physiological processes such as appetite stimulation, energy balance, pain modulation and the control of chemotherapy induced nausea and vomiting (CINV). However, pharmacokinetics and pharmacodynamics interactions could be perceived in drug combinations, so in this short review we tried to shed the light over the potential drug interactions of medicinal cannabis. Hitherto, few data have been provided to the healthcare practitioners about the drug-drug interactions of cannabinoids with other prescription medications. In general, cannabinoids are usually well tolerated, but the bidirectional effects may be expected with concomitant administered agents via affected membrane transporters (glycoprotein p, breast cancer resistance proteins) and metabolizing enzymes (Cytochrome P450 and UDP- glucuronosyltransferases). The caveats should be undertaken to closely monitor the responses of cannabis users with certain drugs to guard their safety, especially for the elderly and people with chronic diseases or kidney and liver conditions.

The Aminofunctional starch/Carboxylated nitrile butadiene rubber (ANS/XNBR) latex films were prepared with control (0), 5, 10, 15, and 20 phr of ANS loadings. The films were subjected to soil burial test for 8 weeks, which recovered every two weeks to quantify the degraded properties. The control (week 0) and biodegraded films were subjected to physical tests (crosslink density, tensile, and tear strength tests) and biodegradation quantification (mass loss retention, and water vapor transmission rates). The optimum physical properties of ANS/XNBR films were subjected to further assessment of its degradation properties which include morphological (optical and scanning electron microscopes (SEM)), Fourier transform infrared (FTIR) analysis, and thermogravimetric analysis (TGA) respectively. Overall, mechanical properties of biodegraded ANS/XNBR latex films decreased as biodegradation period elapses. The biodegradation assessment via water vapor transmission rates and mass loss analyses indicates the high degree of biodegradation rates were observed with higher loading of ANS/XNBR latex films. Morphological analyses via optical microscope shows the transformation of the films surface opacity during biodegradation test. SEM images depicted the microorganism remains on the film surfaces. For FTIR analysis, the most significant changes in the spectras of the films appeared in the region of 790–3000 cm⁻¹. TGA thermograph shows the thermal retention of the materials decreased, as the biodegradation period elapses for optimum ANS/XNBR latex films. From the results obtained, ANS/XNBR latex films shows optimum degradation and mechanical properties at 10 phr filler loading.

The rise in IoT (Internet of Things) devices poses a significant security challenge. Maintaining privacy and ensuring anonymity within the system is a sought-after feature with inevitable trade-offs, such as scalability and increased complexity, making it incredibly challenging to handle. To tackle this, we introduce our proposed work for managing IoT devices using Hyperledger fabric. We integrated our system on the blockchain with a closed-circuit television (CCTV) security camera fixed at a rental property. The CCTV security camera redirects its feed whenever a new renter walks in. We have introduced the web token for authentication from the renter to the owner. Our contributions include the proposition of efficient framework architecture, a novel chain code algorithm, and stealth addresses with modified ring signatures. We performed different analyses to show the system's throughput and latency through stress testing. We have shown the advantages of the proposed architectures by comparing similar existing schemes. Our proposed scheme enhances the security of blockchain-enabled IoT devices and mitigates the single point of failure issue. Our future work includes scaling it up to cater to the needs of the healthcare system.

This study aims at the sustainable valorization of eggshells (ES) from different countries of origin in cement concrete as a cement replacement for Hong Kong. For this purpose, sixteen different eggs from different regions across the world were selected from the local market. Firstly, the extent of uniformity in the weight and mineral content of sampled eggshells were assessed by a specific gravity test and thermogravimetric analysis (TGA), respectively. It was found that specific gravity varies between 2.02 and 2.39, with an average value of 2.20 ± 0.01, whereas CaCO₃ varies between 94.65% and 97.23%, with an average value of 96.33%. These values were a bit lower than those of extra-pure limestone (LS) because of the organic part and the porous structure of eggshells. Secondly, three different eggshells were selected for cement replacement in cement concrete, both in the uncalcined and calcined states, based on having the highest, medium, and lowest CaCO₃ content, respectively. To get the calcined eggshells, the eggshells were calcined at 800^oC for three hours. It was found that the strength of eggshells varies with CaCO₃, but the variation was acceptable. The calcined eggshells showed comparatively more compressive strength and were close to the LS because of the free CaO and the absence of an organic part. In general, the variation in the basic properties of eggshells from different regions across the world is negligible and suitable to use as a cement replacement with acceptable variation in strength in Hong Kong.

Glacial meltwater has been lifeline of agriculture in Gilgit-Baltistan for centuries which is being effected by the climatic changes and associated challenges. The government line institutions and development agencies have been investing to sustain and further extend the cultivated areas by leveraging the available glacial meltwater source. However, approximately 13% arable land, laying mainly along river banks, has limited access to glacial meltwater. Moreover, already cultivated areas also need alternate and sustainable irrigation water supplies to insurefood security. Hence, there is need to explore more potential options to address these challenges and bringing arable land under irrigation for regional prosperity and environmental gains. The International Centre for Integrated Mountain Development (ICIMOD) and its partners piloted solutions for aforementioned issues in Gojal, District Hunza. These solutions included river water lifting through solar and Hydraulic Ram Pumps, uphill water storages and application through drip irrigation systems. In order to assess the technical and economical viabilities of these piloted systems, a semi-structured questionnaire survey, field observation visits to collect data and economic assessment studies were carried out in Morkhun and Khyber. Both piloted systems have been proven as climate resilient, adaptable, environment friendly and economically viable. The cost to benefit ratio for solar powered drip irrigation and Hydraulic Ram Pump drip irrigation systems are 2.96 and 4.21 respectively, with payback period of 9.21 and 8.25 years respectively. The drip irrigation systems at Khyber and Morkhun sites have exhibited excellent hydraulic performance with Coefficient of Uniformity 92.61 and 93 % respectively. However, the field application efficiency of drip irrigation systems estimated for Khyber and Morkhun sites are 85.24 and 88.88% which are lower than the optimal value mainly due to lesser water holding capacity. The Hydraulic Ram Pump can lift four times more water to greater height, while comparing to solar pump of approximately similar capacity and higher capital costs. Both water lifting systems have some limitations and requires local customization for sustainable use.

Geopolymer is an emerging material alternative to Portland cement and has potential as a refractory material. Adding filler in geopolymer material is a strategy to increase the advantages of its physical and mechanical properties. It has been previously reported that adding nanoparticles can increase the compressive strength value, but there is no reported interaction between nanoparticles and geopolymer during the geopolymerization process. This study aims to study the effect of adding nano-zirconia fillers on the physical and mechanical changes of metakaolin-based geopolymers with nano-zirconia fillers. The geopolymer samples were made with 100 g of metakaolin as the base material and nano-zirconia in amounts of 2 gr, 5 gr, 10 gr, and 15 gr. Further characterization was carried out by XRD, FTIR, and SEM-EDX. This study showed that the compressive strength of the MZr05 sample increased significantly by 58.7% compared to the control sample. The test results of the structure and functional groups did not lead to any new compounds formed in the geopolymerization reaction. Therefore, the interaction of metakaolin geopolymer with nano-zirconia only creates an interfacial bonding.

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.

We report on an immunofluorescent paper-based assay for the detection of severe acute respiratory symptom coronavirus 2 (SARS-CoV-2) humanized antibody. The paper-based device was fabricated by using lamination technique for easy and optimized handling. Our approach utilises a two-step strategy that involves (i) initial coating of the paper-electrode with recombinant SARS-CoV-2 nucleocapsid antigen to capture the target SARS-CoV-2 specific antibodies, and (ii) subsequent detection of SARS-CoV-2 antibodies using fluorophore-conjugated IgG antibody. The fluorescence readout was observed with fluorescence microscopy. The images were processed and quantified using a MATLAB program. The assay can selectively detect SARS-CoV-2 humanized antibodies spiked in PBS and healthy human serum samples with the relative standard deviation of approximately 6.4% (for n = 3). It has broad dynamic ranges (1 ng to 50 ng/µL in PBS and 5 to 100 ng/µL in human serum samples) for SARS-CoV-2 humanized antibodies with the detection limits of 2 ng/µL (0.025 IU/mL) and 10 ng/µL (0.125 IU/mL) in PBS and human serum samples, respectively. We believe that our assay has the potential to be used as a simple, rapid, and inexpensive paper-based diagnostic device with a portable fluorescent reader to provide point-of-care diagnosis. This assay can be used for rapid examination of a large batch of samples toward clinical screening of SARS-CoV-2 specific antibodies as a confirmed infected active case or to evaluate the immune response to a SARS-CoV-2 vaccine.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

Poliovirus 2A protease (PV2Apro) plays a vital role in viral replication and down-regulation of host cell protein synthesis. In order to understand more concerning PV2Apro, the protein was over-expressed in bacteria following amplification using sense and antisense primers and cloning in pET15b. Several expression hosts were tested and BL21 (DE3) pLysS cells gave the best expression of PV2Apro with minimal unwanted protein expression following IPTG induction. The 2Apro protein was purified to homogeneity using column chromatography, its solubility determined and its molecular weight and composition determined by MALDI-TOF mass spectrometry. The protease was found in the insoluble fraction and the purified protein had a slightly lower molecular weight than predicted. Moreover, three dimensional structure was modelled using template 1z8r with 58% identity and validated using ramachandran plot. Results revealed that most of the residues lie in favoured and allowed regions. These findings could help in a better understanding of PV2Apro structure and inhibition thus, highlighting potential targets for antiviral drug development.

Haemonchus contortus (H. contortus) is a gastrointestinal parasite affecting small ruminants, leading to a significant decline in animal productivity. In this study, we developed a nanovaccine by encapsulating the recombinant protein rHcES-15, derived from the excretory/secretory products of H. contortus, within biodegradable poly (D, L-lactide-co-glycolide) (PLGA) nanoparticles (NPs). To construct the nanovaccine, PLGA NPs were prepared using a modified double emulsion solvent evaporation technique. Scanning electron microscopy (SEM) illustrated successful encapsulation of rHcES-15 within PLGA NPs, with a size ranging between 350-400 nm. The encapsulation efficiency (EE) of the antigen in the nanovaccine was determined to be 72%. A total of forty experimental mice were divided into five groups, receiving the nanovaccine on day 0 and being humanely sacrificed at the end of the 14-day trial. The stimulation index (SI) from mice vaccinated with the nanovaccine indicated an amplified lymphocyte proliferation and a significant increase in anti-inflammatory cytokines (IL-4, IL-10, and IL-17). Furthermore, the percentages of T-cells (CD4+, CD8+) and dendritic cell phenotypes (CD83+, CD86+) were substantially upregulated in mice immunized with the nanovaccine compared to control groups and the rHcES-15 group. Similarly, higher levels of antigen-specific serum immunoglobulins (IgG1, IgG2a, IgM) were observed in response to the nanovaccine compared to both the antigenic (rHcES-15) and control groups. In conclusion, the data strongly supports the notion that encapsulation of rHcES-15 within PLGA NPs effectively stimulates immune cells in vivo, ultimately augmenting antigen-specific adaptive immune responses against H. contortus. This discovery highlights the promising potential of the nanovaccine, justifying additional investigations to ascertain its efficacy finally.

Conventional plant breeding methods exploit already existing genomic variation in plants to develop a variety in 8 to 10 years, which can decrease the genetic variability of the plant’s genome. The ever-increasing food demand for cereals crops cannot be met by traditional breeding methods. In order to increase food production in less time, there is a dire need to improve breeding methods. Several conventional and molecular breeding methods are being used to improve the crops traits. Molecular researchers have developed new genome editing tools like CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dcas9 epigenetic modification, and several other transgene-free genomes editing approaches. These genome editing tools can improve the desired traits precisely and efficiently. Moreover, a newly developed breeding method “Speed Breeding” has revolutionized the agriculture by shortening the crop cycle. It can produce 5-6 generations of cereals in a year. In this review, we have summarized all these conventional and molecular breeding approaches to improve cereal crops.

Patients satisfaction with fast and high-quality services is the most important in the healthcare settings and specially in outpatient departments and private clinics. High quality services on health sector are indicated by continuous quality improvement (CQI). CQI is a progressive incremental process focused on safety of all participants, outcomes, systematic process, regulated and improved working environment at the later than earlier stages. Among the various suggested strategies, we adopted the patents feedback to improve the quality of services our clinic. All of the patient visited hospital were sent a massage on mobile and requested to provide their feedback on our services. Roughly around 5% of all visitors responded and filled up questionnaire. Majority of them were satisfied with the services in various department. However, they provided us some suggestions to identify the further gaps and improve the services in improving patients experience at our clinic. We considered their feedback, identified problems, redesigned the policies and implemented. After implementation of new strategies, we preliminary again evaluated the patients’ feedback on our services. Patients feedback explores that optimized methods of services for the has considerably increased the patients’ satisfaction. Taken together, our this shows that patients’ feedback is very important factor to improve patients’ experience at outpatient clinics using continuous quality improvement tools. For that reason, this study would serve as reference for public health stack holders, administrators and researchers.

This study evaluated the using of machine vision in combination with deep learning to identify weeds in real-time for wheat production system. PMAS-Arid Agriculture university research farm were selected for collection of images (6000 total images) of weeds and wheat crops under different weather condition. During growing season, the database was constructed to identify the weeds. For this study two framework were used TensorFlow and PyTorch under CNNs and Deep learning. Deep learning perfromed better with in PyTourch value as compared to another model in Tensorflow. comparing with other networks such as YOLOv4, we concluded that our network reaches a better result between speed and accuracy. Specifically, the maximum precision of weed and wheat plants were 0.89 and 0.91 respectively with 9.43 ms and 12.38 ms inference time per image (640 × 640) NVIDIA RTX2070 GPU.

In this paper, we employ fuzzy Sumudu transform for solving system of linear fuzzy differential equations with fuzzy constant coefficients. The system with fuzzy constant coefficients is interpreted under strongly generalized differentiability. For this purpose, new procedures for solving the system are proposed. A numerical example is carried out for solving system adapted from fuzzy radioactive decay model. Conclusion is drawn in the last section and some potential research directions are given.

Purpose: The aim of this research was to prepare adhesive nanoparticles for the topical application of Minoxidil (MXD). Methods: Thiolated β-CDs were prepared via conjugation of cysteamine with oxidized CDs. MXD was encapsulated within thiolated and unmodified β-CDs. Nanoparticles (Thio-NP and blank NP) were prepared by ionic gelation of CDs with chitosan. Particle size and zeta potential were measured. FTIR analyses were performed for characterization of inclusion complex. Drug dissolution studies were carried out. An in vitro adhesion study over human hair was performed. An in vivo skin irritation study was performed. Ex vivo drug uptake was evaluated by using a Franz diffusion cell. Results: Thiolated β-CDs presented 1804.68 ± 25 μmol/g thiol groups and 902.34 ± 25 μmol/g disulfide bonds. Nanoparticles displayed particle sizes within a range of 231 nm to 319 nm. The zeta potential was in the range of ̶ 8.1 to + 12.0. FTIR analyses confirmed no interaction between the excipients and drug. Delayed drug release was observed from Thio-NP. Thio-NP retained over hair surfaces for a significantly longer time. Similarly, drug retention was significantly improved. Thio-NP displayed no irritation over rabbit skin. Conclusion: Owing to the above results, nanoparticles developed with MXD-loaded thiolated β-CDs might be a potential drug delivery system for topical scalp diseases.

Rice wheat cropping system prevailed in more than fifty percent areas of rice belt of central and upper Punjab. In this area yield of wheat is curtailed every year due to late harvesting of rice crop. In addition to this, lack of machinery for direct sowing of wheat into combine harvested rice is a major limitation for timely wheat sowing due to presence of heavy straw load dropped by the combine harvester. A field experiment was planned and executed during two consecutive years 2017-18 and 2018-19 at Agronomic Research Station Farooqabad to evaluate the various stubble management techniques for the sowing of wheat in a rice-wheat cropping system. The Experiment consist of four treatments Happy seeder (Zero tillage), conventional sowing without burning of rice stubble, Rotavator two times, and Conventional sowing with the burning of rice stubble. The trail was arranged as a Randomized Complete Block Design with four replications having a net plot size of 8 m x 20 m. The Treatments have significant effects on Plant height, Number of productive tillers, 1000- grain weight, and grain yield. Maximum plant height (94.74 and 94.25 cm), numbers of productive tillers/m2 (324.00 and 322.25), 1000-grain weight (36.35 and 36.20 g), grain yield (3780 and 3613 kg/ha), and benefit-cost ratio (2.54 and 2.43) were recorded from the treatment happy seeder (Zero tillage) during both years respectively. It is concluded that the sowing of wheat with a happy seeder (Zero tillage) is an appropriate technique in the rice-wheat cropping system by protecting the environment and soil health from the burning of rice stubbles.

Objective: The private healthcare providers (PHCP) are believed to improve access to healthcare services in Public-Private Mix (PPM) projects, as they are considered first point of contact for healthcare. The purpose of this study was to know the satisfaction level of TB patients. Design: A questionnaire-based, cross-sectional study was carried out during November and December 2017 for 572 under-treatment patients registered with PHCPs in the PPM project. Lot quality assurance sampling technique was used to randomly select 19 districts from sample frame of 75 districts. In each selected district, data collector retrieved TB register of 8 months (Jan – Aug 2017) and systematically selected patients by fixed periodic interval. SPSS (version 24.0) was used to analyze the data. Results: Study included 53% (n=301) of males and 47% (n=271) of females, with mean age of 38 years (SD, ±18). Almost half of the participants were illiterate (51%, n=289) and 64% (n=365) were non-earning members of the family. In practice, most of the participants visit private providers (71%, n=407), including private hospital/clinic (44%) and traditional practitioners (27%; n=153). 55% of participants visited the current doctor because of clinic’s proximity to residence. 82% of the participants (n=469) were satisfied with the TB care services and 85% (n=488) said that they would recommend this clinic to others. Conclusion: PHCPs are preferred providers for individuals, which is consistent with findings of other studies. Though they are satisfied with TB care and services, interventions should be introduced to reduce the financial burden on the patient. Partnering PHCP is a way forward to ensure universal health coverage, health system strengthening and better health outcomes of the population.

Because of the covid-19 pandemic, world development has de-escalated, and some have come to a halt because there are many new problems that this era never faced before. Especially in Indonesia's education, every student in this millennial era who is already used to face-to-face lectures and teachers and professors are going through massive changes where every task will be done virtually. These actions are being done to prevent the spread of Covid-19. With online meetings, there will be many changes in the curriculum to find an effective way of studying, and the former curriculum will not fit because it was made for the offline lecture. Also adapting to it will take time. This article will bring up Indonesia’s education progress in this era while Covid-19 pandemic is happening and give an insight on how to anticipate this problem. Questions that arise from this topic are the effect of government effort on holding the pandemic, is it safe if school will be opened soon, and how education after this pandemic is. This research uses literature review methods where it’s done by search, gather, compile and interpret data that is being used. The data are from the latest research, namely from 2019 to 2021 published through Google Scholar, totaling 11 articles, and few online news to keep relevancy of the topic. The results of this study indicate that Covid-19 produces a change that is worse than the good. Even so, the government has allowed face-to-face and online learning according to the consent of students and parents. Thus, the community, especially students, teachers, and others, are expected to uphold education even though it is required to adapt according to existing protocols. From the research, literature review methods proved to be effective to study this topic while Covid-19 is happening to keep safety measures, but it does not give many details and specific information well. This method is recommended to researchers who don’t want to risk their life by being exposed to the pandemic.

Polymorphism in cytochrome P450 (CYP) 2C9 enzyme is known to cause significant inter-individual differences in drug response and occurrence of adverse drug reactions. Different alleles of the CYP2C9 gene have been identified but the notable alleles responsible for reduced enzyme activity are CYP2C9*2 and CYP2C9*3. No pharmacogenetic data is available on CYP2C9*2 and CYP2C9*3 alleles in Pakistani population. In Pakistan pharmacogenetics which examines the relationship between genetic factors and drug response, are in the early stages of development. We for the first time investigated the association between the CYP2C9 variant alleles CYP2C9*2 and CYP2C9*3 and the incidence of hypoglycemia in diabetic patients who were receiving the sulfonylurea medications. A total of n=400 individuals of Pashtun ethnicity were recruited from ten different districts of Khyber Pakhtunkhwa, Pakistan to participate in the study. The study participants were divided into two distinct groups: the case group (n=200) and the control group (n=200). The case group consisted of individuals with Type 2 Diabetes Mellitus (T2DM) who were receiving sulfonylurea medications and experience hypoglycaemia with it whereas the control group included individuals with T2DM who were receiving sulfonylurea medication but did not experience sulfonylurea-induced hypoglycaemia (SIH). Blood samples were obtained from study participants following informed consent. DNA was isolated from whole blood samples using Wiz-Prep DNA extraction kit. Following DNA isolation, CYP2C9 alleles were genotyped using MassARRAY sequencing platform at centre of genomics Rehman Medical Institute (RMI). The frequency of CYP2C9*2 (low activity allele) was more frequent in the diabetic patients with sulphonylurea-induced hypoglycaemia (SIH) compared to the control group (17.5% vs. 6.0%, p=0.021). The frequency of its corresponding genotype CYP2C9*1/*2 was higher in cases compared to control group (10% vs. 6% with P=0.036), same was true for genotype CYP2C9*2/*2 (7% vs. 3.5 % with P=0.028). Logistic regression analysis evident potential association of CYP2C9*2 allele and its genotypes with SIH. When adjusted for confounding factors such age, weight, sex, daily dose of sulphonylurea and triglyceride level the association between the CYP2C9*2 allele and hypoglycemia remains consistent. Confounding factors played no role in SIH because both groups (cases and controls) were closely matched in term of age, weight, sex, mean daily dose of sulphonylurea and trigyleride levels. Our study suggests that genetic information about a patient's CYP2C9 gene/enzyme can potentially assist physicians in prescribing the most suitable and safest drug based on their genetic make-up.

Present study reports the green synthesis of pectin fabricated silver-based nanocomposite (Pectin-AgNPs) with Carpesiumnepalense leaves extract and evaluated their bactericidal kinetics, in-vivo hepatoprotective and cytotoxic potentials with their possible mechanisms. GC/MS and LC/MS analysis indicated the presence of different new phytochemicals constituents in the plant extract. The physicochemical characterization of Pectin-AgNPs by UV/Vis, SEM, DLS, FTIR and EDX techniques showed the spherical and uniform size range synthesis of nanocomposite i.e. 50-110 nm. The highly significant (P<0.005) antibacterial activity was found against all tested four bacterial strains with the ZIs of 24.8 to 27.2 mm. Significant damage in bacterial cell membrane was also observed in AFM study after treated with Pectin-AgNPs. At the doses of 0.05 mg/kg, nanocomposite showed highly significant (P<0.005)hepatoprotective activity in biochemical and histopathology analysis as compared to CCL4 administered control group. The ameliorative effects of Pectin-AgNPs were observed in PCR analysis on both GAPDH and PPARs genes expression and its potential to restore gene alterations caused by CCl4 intoxication.Pectin-AgNPs produced cytotoxic activity against HeLa cell lines at higher doses with the LC50 of 223.7 µg/mL. The current findings demonstrate positive attributes of pectin fabricated AgNPs as a promising antibacterial, hepatoprotective and cytotoxic agent.

A highly sensitive strain sensor based on tunable cascaded Fabry-Perot interferometers (FPIs) is proposed and experimentally demonstrated. Cascaded FPIs consist of a sensing FPI and a reference FPI which effectively generate the Vernier Effect (VE). The sensing FPI comprises a hollow core fiber (HCF) segment sandwiched between single-mode fibers (SMFs), and the reference FPI consists of a tunable air reflector, which is constituted by a computer programable fiber holding block to adjust the desired cavity length. Simulation results predict the dispersion characteristics of modes carried by HCF. The sensor’s parameters are designed corresponding to a narrow bandwidth range, i.e., 1530 nm to 1610 nm. Experimental results demonstrate that the proposed sensor exhibits optimum strain sensitivity of 23.9 pm/με in the range of 0 to 3000 με which is 13.73 times higher than the single sensing FPI strain sensitivity of 1.74 pm/με. The strain sensitivity of the sensor can be further enhanced by extending the source bandwidth. The proposed sensor exhibits ultra-low temperature sensitivity of 0.49 pm/°C in the wider temperature range of 25 °C to 135 °C, providing good isolation for eliminating cross-talk between strain and temperature. The sensor is very robust, cost-effective, easy to manufacture, repeatable, and shows a highly linear and stable response in the wider range of axial strain. Based on the sensor’s performance, it may suit plenty of practical applications in the real sensing world

Depth maps produced by LiDAR based approaches are sparse. Even high-end LiDAR sensors produce highly sparse depth maps, which are also noisy around the object boundaries. Depth completion is the task of generating a dense depth map from a sparse depth map. While the traditional approaches focus on directly completing this sparsity from the sparse depth maps, modern techniques use RGB images as a guidance tool to resolve this problem. Whilst many others rely on affinity matrices for depth completion. Based on these approaches, we have sub-divided the literature into two major categories; traditional approaches and backbone-based approaches. The latter is further sub-divided into two-branch, and spatial propagation approaches. The two-branch approaches still have a sub-category named guided-kernel approaches. In this paper, for the first time ever we present a comprehensive survey of depth completion methods. We present a novel taxonomy of depth completion approaches, review and detail different state-of-the art techniques within each category for depth completion of LiDAR data, and provide quantitative results for the approaches on KITTI and NYUv2 depth completion benchmark datasets.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

A new series of 1,3,4-oxadiazoles derivatives was synthesized, characterized and evaluated for their in vitro and in vivo anti-thrombotic activity. Compounds (3a-3i) exhibited significant clot lysis with respect to negative control and reference drug streptokinase (30,000 IU) while enhanced clotting time (CT) values were observed (130-342 sec) for these tested compounds than the standard drug heparin (110 sec.). High affinity towards 1NFY with greater docking score was observed for the compounds (3a, 3i, 3e, 3d and 3h) than the control ligand RPR200095. In addition, very good inhibitory potential against factor Xa (F-Xa) was observed with higher docking scores (5612-6270) with ACE values (–189.68 to –352.28 kcal/mol) than the control ligand RPR200095 (Docking score 5192; ACE –197.81 kcal/mol. In vitro, in vivo and in silico results proposed that these newly synthesized compounds can be used as anti-coagulant agents.

Optical switching is an essential part of photonic integrated circuits and the focus of research at the moment. In this research, an optical switch design working on the phenomenon of the guided-mode resonances in 3D photonic crystals-based structure is reported. The optical-switching mechanism is studied in a dielectric slab-waveguide-based structure operating in the near-infrared range in a telecom window of 1.55 µm. The mechanism is investigated by interference of two signals, i.e., the data signal and the control signal. The data signal is coupled into the optical structure and filtered utilizing guided-mode resonance, whereas, the control signal is index guided in the optical structure. The amplification or de-amplification of the data signal is controlled by tuning the spectral properties of the optical sources and structural parameters of the device. The parameters are optimized first using a single-cell model with periodic boundary conditions and later in a finite 3D-FDTD model of the device. The numerical design is computed in an open-source Finite Difference Time Domain simulation platform. Optical amplification in the range of 13.75 % is achieved in the data signal with a decrease in the linewidth up to 0.0079 µm and a quality factor of 114.58. The proposed device presents great potential in the field of photonic integrated circuits, biomedical technology, and programmable photonics.

The purpose of current research work was to formulate and typify gelatin and poly(vinyl) alcohol (Gel/PVA) hydrogel which would be highly pH-responsive and can able to accomplish targeted delivery of methotrexate in order to treat the colo-rectal pathologies. The primed gel/pva hydrogel discs were subjected to various physicochemical techniques i.e. swelling, diffusion co-efficient, sol-gel analysis and porosity using three altered sorts of pH (1.2, 6.8 & 7.4) phosphate buffer solutions for assessment/evaluation, and their characterization was done through Fourier transform infrared spectroscopy (FTIR) and thermal gravimetric analysis (TGA). Shape alteration and controlled methotrexate of release of Gel/PVA hydrogel have been done using three type of pH (1.2, 6.8 & 7.4) phosphate buffer mediums. Methotrexate was loaded through in-situ drug loading method due to hydrophobicity. Different kinetic models (first order & zero order kinetic), Higuchi model and Krosmere peppas model/Power law were applied to manipulate the drug release data. Physicochemical evaluation tests and drug release profile results were found insignificant (p< 0.05) in various pH mediums and dependent upon polymers concentration pH of medium and cross-linker amount. Kinetic model disclosed that release of methotrexate from Gel/PVA hydrogel follow non-Fickian diffusion method. It became concluded from this research work that release of methotrexate Gel/PVA hydrogel in targeted colon area can be achieved for treating colo-rectal disorders.