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Albania is now implementing a range of steps as part of its journey towards European Union integration, based on agreements that have been achieved. Key to these initiatives is the extensive adoption of circular economy concepts through comprehensive waste management systems. This collaboration is based on systematically implementing measures that align with the fundamental principles of the waste management hierarchy. Albania wants to lead in waste-to-energy conversion exploration by focusing on trash minimization, reuse, recycling, and energy generation from residual waste. Although there has been notable advancement, especially in aligning laws with EU requirements, there are practical obstacles, especially in the execution of waste-to-energy projects. The challenges involve the need for effective waste segregation, higher recycling rates, and the use of advanced waste-to-energy technologies. The essay utilizes meticulously selected data on Albania’s waste generation from reputable organizations and the legal framework regulating waste management to assess the current situation and predict future possibilities, which may be advantageous for government ministries and agency platforms.

The McMaster nuclear reactor (MNR) is an important research facility that not only provides researchers with neutrons for fundamental science, but also supplies the medical industry with isotopes used for cancer treatment. To ensure the safety and performance of the MNR, modeling of the thermal hydraulics during nominal and accidental conditions is required. For such a task, system codes are customarily used. While system codes can assess the safety aspects of complex thermal–hydraulic systems, the question arises whether such systems can be modeled appropriately in a three-dimensional manner, such as computation fluid dynamics (CFD), while capturing the thermal mixing of the coolant. Modeling the thermal hydraulics of nuclear research reactors using CFD is relatively new. Therefore, validating such methods against experimental data is of utmost importance. The validation of CFD is the main focus of this work. More specifically, the influence of the loss of heat sink on the pool temperature is assessed using the CFD code Ansys CFX. The validation basis was provided by an experiment performed at the MNR in March 2023. In this experiment, the secondary heat removal system was intentionally shut down, and the pool temperature was measured in a few positions. The results obtained by modeling the loss of heat sink in the MNR using Ansys CFX agree well with the experiment.

This work embarks on an exploration of piezoelectric energy harvesting (PEH), seeking to unravel its potential and practicality. PEH has emerged as a promising technology in the field of civil engineering, offering a sustainable approach to generating energy from ambient mechanical vibrations. We will explore the applications and advancements of PEH within the realm of civil engineering, focusing on publications, especially from the years 2020 to 2024. The purpose of this study is to thoroughly examine the potential and practicality of PEH in civil engineering applications. It delves into the fundamental principles of energy conversion and explores its use in various areas, such as roadways, railways, bridges, buildings, ocean wave-based energy harvesting, structural health monitoring, and even extraterrestrial settings. Despite the potential benefits of PEH in these domains, there are significant challenges that need to be addressed. These challenges include inefficient energy conversion, limitations in scalability, concerns regarding durability, and issues with integration. This review article aims to address these existing challenges and the research gap in the piezoelectric field.

The incentives and subsidies needed to stimulate growth, resilience, and success in agri-preneurial businesses will only be realized through numerous interventions as agri-preneurship contributes significantly to sustainable agricultural development in South Africa. This study provided a novel insight into agri-preneurial resilience and success and evidenced the hypothesis that there is no significant positive correlation between agri-preneurial resilience, farm success, and selected demographic characteristics of smallholders. We surveyed a total of 200 agri-preneurs who were willing and able to participate in this study. This study used a structured questionnaire that was divided into the following sections: (i) demographic information; (ii) agri-preneurial resilience; and (iii) agri-preneurial success. Descriptive statistics and a regression analysis were employed to articulate responses. Four distinct models were employed to ascertain the goodness of fitness and the hypothesis, and assess the relationship between success, resilience, and selected demographic characteristics of agri-preneurs. To determine resilience, the Connor–Davidson Resilience Scale (CD-RISC) with 10 items was used because the CD-RISC justifies the best psychometric characteristics that portrays the levels of resilience amongst agri-preneurs. In measuring success, the scale items were graduated and ranked on a 5-point scale from 1 to 5. The reliability of the scale was also tested, and α = 0.93 was obtained. This study obtained a Cronbach alpha value of 0.96, indicating optimum reliability. Additionally, we ran a factor analysis to certify the reliability of the variable, which gave one factor from the four items. Significant positive correlations were found between gender, age, education, income, household size, diversification, and agri-preneurial resilience and success. This study concluded that most of the selected demographic characteristics were predictors of agri-preneurial resilience and success. However, demographic variables may be influenced by numerous factors given the heterogeneity of agri-preneurs in the study area.

Student enrollment is a vital aspect of educational institutions, encompassing active, registered and graduate students. All the same, some students fail to engage with their studies after admission and drop out along the line; this is known as attrition. The student attrition rate is acknowledged as the most complicated and significant problem facing educational systems and is caused by institutional and non-institutional challenges. In this study, the researchers utilized a dataset obtained from the National Open University of Nigeria (NOUN) from 2012 to 2022, which included comprehensive information about students enrolled in various programs at the university who were inactive and had dropped out. The researchers used deep learning techniques, such as the Long Short-Term Memory (LSTM) model and compared their performance with the One-Dimensional Convolutional Neural Network (1DCNN) model. The results of this study revealed that the LSTM model achieved overall accuracy of 57.29% on the training data, while the 1DCNN model exhibited lower accuracy of 49.91% on the training data. The LSTM indicated a superior correct classification rate compared to the 1DCNN model.

A building’s level of seismic performance remains the greatest concern for engineers and researchers in seismic-event-prone countries [...]

Masonry towers are peculiar structures with complex structural behavior despite biased conclusions deriving from their geometrical regularity and simplicity. Their geometrical features and the epistemic uncertainty that masonry material bears strongly influence their static and seismic behavior. This paper investigates a remarkable and representative case study. The bell tower of Portogruaro (Italy) is a 57 m high tall construction, built in the XII-th century, and has a notable inclination. The Italian Guideline for the safety assessment of masonry towers is a key focus in this paper, highlighting the pros and cons of different suggested approaches. Some relevant proposals are presented in this paper in order to address the seismic safety assessment of masonry bell towers. The findings show that very slender structures do not meet the guidelines recommendations due to limitations in their current stress state. In addition, in similar cases, the recommended values for the mechanical properties of masonry material led to predicting non-withstanding structural behavior, questioning the correct choice of the adapted material properties. Advanced pushover analysis has been conducted in order to investigate the results of the simplified approach in terms of failure patterns and seismic safety estimation. The simulations are implemented for four different hypothetical scenarios of the existing masonry mechanical properties. The results obtained for the case study tower reflect a different perspective in the seismic assessment of masonry towers when specific approaches are defined. The preliminary results on the safety of Portogruaro Tower show a significant variability of seismic safety based on the adopted scenario, highlighting the necessity to pay attention to the preservation state of the present case and of similar ones.

Monoterpene and 5-methylcoumarin- or 5-methylchromone-coupled meroterpenoids occurring mainly in the Asteraceae species proved to have high potency against protozoans, worms, and various tumor cells, which make them interesting targets for searching for new bioactive compounds. The African plant Centrapalus pauciflorus was applied in traditional medicine for healing chest pain and stomach aches. Three new meroterpenoids named centrapalus coumarin N (2), pauciflorins P (3), and Q (4), and the already known cyclohoehnelia coumarin (1), were isolated from the chloroform extract of C. pauciflorus, together with centrapalus coumarin O (5), which was obtained for the first time from a natural source. The structures were established from HRESIMS, 1D (1H NMR, 13C NMR JMOD) and 2D NMR (HSQC, HMBC, 1H-1H COSY, NOESY) spectroscopies, and the absolute stereochemistry of 5 was determined by single-crystal X-ray diffraction. Compounds 1, 2, and 5 are hybrid molecules of 5-methylcoumarin–monoterpene origin. Centrapalus coumarin N is the first example of meroterpenoids, where a monoterpene is fused with a coumarin and an acetophenone unit. Pauciflorins P and Q are dimeric meroterpenoid isomers. Centrapalus coumarins N and O were tested for antiproliferative activity against human adherent breast (MCF-7, MDA-MB-231), cervical (HeLa, SiHa), and ovarian (A2780) cancer cell lines, and were additionally included to obtain data concerning cancer selectivity. Both compounds exhibited moderate (IC50 > 10 µM) but selective activity against A2780 cells.

This paper discusses the groundwater vulnerability to pollution assessment for the Tirana–Ishmi alluvium aquifer, Albania. Economic activities, municipal wastewater discharged into rivers and groundwater overexploitation threaten to pollute the groundwater. Based on the aquifer characteristics and the available data, SINTACS was selected as the most realistic assessment model. The SINTACS parameters’ rates assigned to the aquifer’s characteristics (water table depth, infiltration, unsaturated zone, soil media, aquifer media, hydraulic conductivity, topography) were adapted to the local features, followed by GIS vulnerability mapping. Statistical analysis indicates that the unsaturated zone, hydraulic conductivity and aquifer media have the highest influence on groundwater vulnerability, whereas topography has the lowest influence. Validation through sensitivity analysis and nitrates content confirms the rational selection of the SINTACS model and the reliability of the study’s outputs. The most vulnerable areas to pollution are the recharge zones, followed by the highly urbanized Tirana City area, characterized by high levels of groundwater extraction rate and wastewater discharged into the rivers. The paper, being the first completed groundwater vulnerability assessment of the study area, could serve as a basis for a scientific–based groundwater management that should be considered in local territory planning.

This study explores the resilience and resemblance among children of parents with alcohol-related problems in Botswana. Alcohol misuse affects both users and their families, particularly children. Although children raised in an alcoholic environment often face long-term adversities, some become resilient adults while others present behaviours resembling those of their parents. This study used socio-ecological resilience theory to explore the perceptions and experiences of adult children of parents and carers with alcohol-related problems, as well as the pathways they use to navigate risks. We collected data from seven adult children in a village in Botswana using in-depth, unstructured interviews. The study revealed two global themes: familial practices and protective factors. The vulnerability, resemblance, and resilience experienced by adult children of parents with alcohol-related problems are discussed. This study helps us to understand the adult children of parents and carers with alcohol-related problems in a rural cultural context. Their lived experiences demonstrate that resilience and resemblance coexist and are not mutually exclusive.

Anthropogenic activities lead to the spread of chemicals and biological materials, including plastic waste, toxic metals, and pharmaceuticals, of which the impact on the Mediterranean Sea is of high concern. In this context, the EU Interreg Italy-Albania-Montenegro Project “ADRINET (Adriatic Network for Marine Ecosystem) _244” (2018–2020) arises. It aims to carry out biomonitoring campaigns in the main commercial interest of fish and cephalopod species, such as Sparus aurata, Dicentrarchus labrax, Sepia spp., and Loligo spp. sampled in three different subregions of the Mediterranean Sea. The presence of the main environmental contaminants, such as cadmium, microplastics, and antibiotics was investigated in these seafood samples. Contamination by cadmium and antibiotics in the seafood investigated in our study was negligible. However, a high value of microplastics was detected in the stomach and gut of Sparus aurata and Dicentrarchus labrax. Overall, even though the presence of microplastics needs to be investigated by further studies, the results confirmed that the environmental conditions of the three bays investigated by the ADRINET project partners (Italy, Albania, Montenegro) are positive and not affected by intensive anthropogenic activity.

Incidence data from 17-year veterinary neoplasm surveillance and registration were reviewed. Most of the neoplastic cases diagnosed in Nigerian veterinary teaching hospitals (VTHs) were in the avian (49%) and canine species (44%). Fewer cases were recorded in the equine (3.2%), bovine (2.4%), ovine (1.5%), caprine (0.3%) and porcine (0.15%) species. Marek’s disease was the most prevalently diagnosed neoplastic disease of domestic animals in Nigerian VTHs from 2000–2017. Also, the Nigerian local breed had a higher mean distribution than any other dog breed and this was statistically significant (p < 0.05). Nearly all of the neoplastic cases diagnosed, were found in females (60.4%) and so the mean distribution of sex was statistically significant (p < 0.05). The digestive system, with 296 (46.25%) cases, was the anatomic location where the majority of the neoplastic cases were found. However, the mean distribution of different neoplastic anatomic sites was not statistically significant (p > 0.05). In conclusion, little emphasis is given to the appropriate diagnosis and recording of neoplastic cases that are diagnosed. The study provides information regarding the prevalence and distribution of tumours in different animal species consulted in Nigeria veterinary teaching hospitals. To illustrate all of this, ArcGIS software was used. Veterinary clinicians, pathologists and epidemiologists from Nigeria may benefit from the results of this study by freely accessing some specific data regarding the breed, the age group or the gender of some animal species diagnosed with different tumours.

There is an urgent need to address the global mortality of the COVID-19 pandemic, as it reached 6.3 million as of July 2022. As such, the experts recommended the mass diagnosis of SARS-CoV-2 infection at an early stage using nanotechnology-based sensitive diagnostic approaches. The development of nanobiosensors for Point-of-Care (POC) sampling of COVID-19 could ensure mass detection without the need for sophisticated laboratories or expert personnel. The use of Artificial Intelligence (AI) techniques for POC detection was also proposed. In addition, the utilization of various antiviral nanomaterials such as Silver Nanoparticles (AgNPs) for the development of masks for personal protection mitigates viral transmission. Nowadays, nano-assisted vaccines have been approved for emergency use, but their safety and effectiveness in the mutant strain of the SARS-CoV-2 virus remain challenging. Methodology: Updated literature was sourced from various research indexing databases such as PubMed, SCOPUS, Science Direct, Research Gate and Google Scholars. Result: We presented the concept of novel nanotechnology researched discovery, including nano-devices, electrochemical biosensing, nano-assisted vaccine, and nanomedicines, for use in recent times, which could be a formidable step for future management of COVID-19.

Lassa virus (LASV) is a zoonotic pathogen endemic throughout western Africa and is responsible for a human disease known as Lassa fever (LF). Historically, LASV has been emphasized as one of the greatest public health threats in West Africa, with up to 300,000 cases and 5000 associated deaths per year. This, and the fact that the disease has been reported in travelers, has driven a rapid production of various vaccine candidates. Several of these vaccines are currently in clinical development, despite limitations in understanding the immune response to infection. Alarmingly, the host immune response has been implicated in the induction of sensorineural hearing loss in LF survivors, legitimately raising safety questions about any future vaccines as well as efficacy in preventing potential hearing loss. The objective of this article is to revisit the importance and prevalence of LF in West Africa, with focus on Nigeria, and discuss current therapeutic approaches and ongoing vaccine development. In addition, we aim to emphasize the need for more scientific studies relating to LF-associated hearing loss, and to promote critical discussion about potential risks and benefits of vaccinating the population in endemic regions of West Africa.

Polycystic ovary syndrome (PCOS) manifests a multifactorial pathology characterized by polycystic ovaries, menstrual cycle disorders, varying degrees of hyperandrogenism, and an ad-verse metabolic risk profile. The position of hyperandrogenism in this syndrome has been extensively studied. A multitude of mechanisms place it in the position of cause but also of consequence; therefore, ongoing research efforts are focused on identifying medications that can effectively reduce levels of androgens in women with PCOS. Moreover, lipid abnormalities are common in this population, with up to 70% of patients having dyslipidemia. Statins may have potential therapeutic benefits for women with PCOS, as they have been shown to improve insulin resistance and reduce the risk of cardiovascular disease. In addition, their role in accelerated steroidogenesis by limiting one source of cholesterol, influencing enzymatic activity, and providing several other beneficial mechanisms is widely investigated. This review aimed to provide a comprehensive overview of the pathogenesis of androgen excess and dyslipidemia in PCOS, as well as the therapeutic potential of statins.

Vjosa is the main river of South Albania. Currently, the confined Quaternary gravelly aquifer in its lower course supplies drinking water for roughly 300,000 local residents. In the past years, extracted groundwater quantity has increased, whereas the groundwater quality has been affected by seawater intrusion. This paper aims to assess the groundwater quality and to discuss the dominant hydrochemical processes in the aquifer. To fulfil this goal, the study discusses the groundwater quality’s spatial and temporal variations on the basis of the hydrochemical parameters and ratios for 2010–2021 period, during which data are collected from three monitoring wells, located 6, 14 and 17 km, from the sea. While for 1961–2009 period, hydro-chemical water types and TDS maps are prepared using roughly 100 chemical analyses. The hydro-chemical parameters are discussed related to the factors controlling the groundwater’s chemical constituents and the groundwater extraction. Heavy metals and nitrates’ contents indicate that the aquifer is not affected by anthropogenic pollution. The main conclusion is that the groundwater quality is affected by seawater intrusion due to overexploitation. The study reveals its gaps, mentions its possible usefulness, and underlines the discrepancy between the policy makers and the hydrogeologists approaches concerning groundwater extraction.

A WUSCHEL-related homeobox (WOX) gene family has been implicated in promoting vegetative organs to embryonic transition and maintaining plant embryonic stem cell identity. Using genome-wide analysis, we identified 17 candidates, WOX genes in ramie (Boehmeria nivea). The genes (BnWOX) showed highly conserved homeodomain regions typical of WOX. Based on phylogenetic analysis, they were classified into three distinct groups: modern, intermediate, and ancient clades. The genes displayed 65% and 35% collinearities with their Arabidopsis thaliana and Oryza sativa ortholog, respectively, and exhibited similar motifs, suggesting similar functions. Furthermore, four segmental duplications (BnWOX10/14, BnWOX13A/13B, BnWOX9A/9B, and BnWOX6A/Maker00021031) and a tandem-duplicated pair (BnWOX5/7) among the putative ramie WOX genes were obtained, suggesting that whole-genome duplication (WGD) played a role in WOX gene expansion. Expression profiling analysis of the genes in the bud, leaf, stem, and root of the stem cuttings revealed higher expression levels of BnWOX10 and BnWOX14 in the stem and root and lower in the leaf consistent with the qRT-PCR analysis, suggesting their direct roles in ramie root formation. Analysis of the rooting characteristics and expression in the stem cuttings of sixty-seven different ramie genetic resources showed a possible involvement of BnWOX14 in the adventitious rooting of ramie. Thus, this study provides valuable information on ramie WOX genes and lays the foundation for further research.

This study evaluated the influence of asphalt binder and biochar-based geopolymer composites on the permanent deformation resistance (PDR) of asphalt concrete. The influence of three design variations, asphalt binder, biochar, and geopolymer content, was evaluated by employing the response surface method (RSM) based on the Box Behnken approach. The asphalt binder content ranged between 4 and 6%, whereas the biochar and geopolymer content ranged between 0 and 4%. The average rut depth of Bio-Geopolymer Asphalt concrete (BGAC) was employed as the response variable. The synergetic influence of the design variable was examined using the RSM approach, and a model was developed to determine optimum contents for improving PDR. The model has very high R2 values and adequate precision, showing that there is a significant relationship between the experimental and predicted values. The study ANOVA revealed that the asphalt binder and a biochar-based geopolymer composite modifier showed a significant effect in enhancing the PDR of BGAC. Furthermore, the optimization shows that the optimal content for biochar, geopolymer, and asphalt binder are 3.22%, 1.81%, and 5.4%, respectively. The generated model’s percentage error was found to be 5%, showing a significant correlation between the actual and predicted data. The results of this study show that using RSM to predict and optimize the PDR of BGAC is a very efficient and effective technique.

In today’s intricate and dynamic world, Supply Chain Management (SCM) is encountering escalating difficulties in relation to aspects such as disruptions, globalisation and complexity, and demand volatility. Consequently, companies are turning to data-driven technologies such as machine learning to overcome these challenges. Traditional approaches to SCM lack the ability to predict risks accurately due to their computational complexity. In the present research, a hybrid Bayesian-optimized Light Gradient-Boosting Machine (LightGBM) model, which accurately forecasts backorder risk within SCM, has been developed. The methodology employed encompasses the creation of a mathematical classification model and utilises diverse machine learning algorithms to predict the risks associated with backorders in a supply chain. The proposed LightGBM model outperforms other methods and offers computational efficiency, making it a valuable tool for risk prediction in supply chain management.

The municipal water supply, related mainly to the cities of Albania, began to develop in the second half of the 19th century and very intensively after 1945. Today, the reported mean water production for the cities, on average, is about 300 l/capita/d, including drinking and industrial water supplies. The territory of Albania has an uneven distribution of very heterogeneous aquifers conditioning often the difficulty of municipal water supply solutions. In this article, are analyzed and classified the hydrogeological aspects of the water supply sources of the settlements, which are summarized in five groups: (a) wells in alluvial intergranular aquifers; (b) karst springs; (c) wells in karst aquifers; (d) springs in fissured rocks; and (e) mixed water sources. For each group of the water supply sources, the main concerns regarding the quantity and quality problems are analyzed, facilitated by the description of a variety of representative examples of different situations. Based on the gained experience, important recommendations are given for the better understanding of hydrogeological aspects of water supply systems, related to the river water recharge areas, the seawater intrusion in coastal aquifers, and the high vulnerability of karst aquifers, as well as transboundary aquifers. However, the main problem of public water supply of Albania remains the poor management of water supply systems, which is reflected in the significant water losses, as well as the low public awareness of requests for sustainable use.

The best possible use of natural resources and the large amounts of trash produced by industrial and human activity is necessary for sustainable development. Due to the threat of global climate change and other environmental challenges, waste management systems are changing, leading to more instances of water resource management. The waste generated must be controlled from a sustainability point of view. Typically, the conventional disposal of Agricultural Wastewater (AW) and biomass can be achieved by recycling, reusing, and converting them into a variety of green products. To improve the AW quality for the purposes of environmental sustainability, Sustainable Development Goals (SDGs) 6 and 14, dealing with clean water, sanitation, and life below water, are very important goals. Therefore, the present investigation evaluates the effectiveness of a Bench-scale Activated Sludge Reactor (BASR) system for AW treatment. The BASR was designed to focus on getting the maximum possible utilization out of a biosorbent derived from oil palm waste activated hydrochar (OPAH). This is in accordance with SDG 9, which targets inorganic and organic waste utilization for added value. An experiment was developed using the Response Surface Methodology (RSM). A Hydraulic Retention Time (HRT) of 1–3 days was used in the bioreactor’s setup and operation, and Mixed Liquor Suspended Solids (MLSS) concentrations of 4000–6000 mg/L were used. BASR was fed with AW with initial mean concentrations of 4486 ± 5.63 mg/L and 6649 ± 3.48 for the five-day Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) experiments, respectively. The results obtained showed that maximum reductions of 84.66% and 72.07% were recorded for BOD5 and COD, respectively. Through RSM optimization, the greatest reductions in the amounts of organic materials were achieved with a 2-day HRT and an MLSS dosage of 5000 mg/L. Substrate elimination thresholds were assessed using the first-order, the Grau second-order, and the modified Stover–Kincannon models. The reported observations were found to be perfectly fit by the modified Stover–Kincannon model, with high R2 values of 0.9908 and 0.9931 for BOD5 and COD, respectively. As a result, the model may be used to design the BASR system and forecast how the reactor would behave. The findings from this study suggest that the developed OPAH has promising potential to be applied as eco-friendly material for the removal of BOD5 and COD from AW. Consequently, the study findings additionally possess the ability to address SDGs 6, 9, and 14, in order to fulfil the United Nations (UN) goals through 2030.

Two earthquakes struck the NW region of Albanian territory on 21 September 2019 (Mw = 5.6) and on 26 November 2019 (Mw = 6.4). The epicenters of the seismic activity were located offshore NW Durrës, one of Albania’s most populated cities, located 30 km from the capital Tirana. Various aftershocks followed subsequently. While there were no reported injuries, a number of buildings sustained significant damage near the epicenter following the initial event. Subsequently, during the second event, there was loss of life and extensive damage to civilian structures, resulting in multiple collapses. This study focuses on the earthquake damages observed in residential and public buildings in the earthquake-affected region. The earthquakes predominantly affected low-rise masonry buildings, while the newly constructed RC structures built according to the latest seismic rules were almost unaffected. The commonly encountered building typologies in the region, together with photos showing the amount of destruction are presented here. As observed by the authors during the reconnaissance visit to the stricken area, examples of various damage patterns are presented, along with a technically substantiated description of the reasons for those damages. Although modern buildings during recent earthquakes in the region show acceptable performance, the detailed surveys from the Durrës Earthquakes showed that there is still an important level of deficiency in current masonry buildings built by conventional methods and materials. This problem may reoccur in future earthquakes that may hit other rural regions of Albania, which must be focused on systematically in the near future.

Due to rapid urbanization, solid waste management (SWM) is a major challenge in Malaysia, hence the need to sustainably manage it. Compared with other states, Selangor produces the highest volume of domestic waste. Most of the state’s waste is generated in Shah Alam City. This condition is expected to worsen because the population of Shah Alam is projected to rise by 2.5% from 2018 to 2035. This situation will increase the demand for resources, production, and consumption, increasing the volume of waste generated in Shah Alam. Hence, the pressing necessity to advance from the current traditional waste management practices to a more sustainable SWM system has been identified as a key target in Shah Alam’s 2025–2030 plans. The Smart Waste Management System (SWMS) has been identified as a novel approach to dealing with the absence of route optimization, real-time information exchange, and the consequent increase in waste management costs. All of these elements have characterized the current traditional households’ SWM. However, because this method is novel, there is a dearth of knowledge on the appropriate measurement model for evaluating the dimension of households’ intention to recycle waste through source separation as well as measuring the determinants of such a pro-environmental intention under the new SWMS. Thus, confirmatory factor analysis (CFA) was carried out to verify the factorial structure of the variables, relying on the Theory of Planned Behavior (TPB) based on the structural dimensions identified in prior exploratory factor analysis (EFA). The study found support for the use of TPB as a relevant framework for modeling the intention for source separation and its determinants under SWMS.

Effective control of diseases transmitted by Aedes aegypti is primarily achieved through vector control by chemical insecticides. However, the emergence of insecticide resistance in A. aegypti undermines current control efforts. Arachnid venoms are rich in toxins with activity against dipteran insects and we therefore employed a panel of 41 spider and 9 scorpion venoms to screen for mosquitocidal toxins. Using an assay-guided fractionation approach, we isolated two peptides from the venom of the tarantula Lasiodora klugi with activity against adult A. aegypti. The isolated peptides were named U-TRTX-Lk1a and U-TRTX-Lk2a and comprised 41 and 49 residues with monoisotopic masses of 4687.02 Da and 5718.88 Da, respectively. U-TRTX-Lk1a exhibited an LD50 of 38.3 pmol/g when injected into A. aegypti and its modeled structure conformed to the inhibitor cystine knot motif. U-TRTX-Lk2a has an LD50 of 45.4 pmol/g against adult A. aegypti and its predicted structure conforms to the disulfide-directed β-hairpin motif. These spider-venom peptides represent potential leads for the development of novel control agents for A. aegypti.

The aim of this paper is to introduce new forms of quasi-contractions in metric-like spaces and initiate more general conditions for the existence of invariant points for such operators. The proposed notions are then applied to study novel existence criteria for the existence of solutions to two-point boundary value problems in the domains of integer and fractional orders. To attract further research in this direction, important consequences are deduced and discussed to indicate the novelty and generality of our proposed concepts.

In this paper, the notion of generalized quasi-weakly contractive operators in metric-like spaces is introduced, and new conditions for the existence of fixed points for such mappings are investigated. A non-trivial example which highlights the novelty of our principal idea is constructed. It is observed comparatively that the proposed concepts herein subsume some important results in the corresponding literature. As an application, one of our obtained findings is utilized to setup novel criteria for the existence of solutions to two-point boundary value problems of a second order differential equation. To attract new researchers in the directions examined in this article, a significant number of corollaries are pointed out and discussed.

Collecting time-series receive signal strength (RSS) observations and averaging them is a common method for dealing with RSS fluctuation. However, outliers in the time-series observations affect the averaging process, making this method less efficient. The Z-score method based on the median absolute deviation (MAD) scale estimator has been used to detect outliers, but it is only efficient with symmetrically distributed observations. Experimental analysis has shown that time-series RSS observations can have a symmetric or asymmetric distribution depending on the nature of the environment in which the measurement was taken. Hence, the use of the Z-score method with the MAD scale estimator will not be efficient. In this paper, the Sn scale estimator is proposed as an alternative to MAD to be used with the Z-score method in detecting outliers in time-series RSS observations. Performance comparison using an online RSS dataset shows that the Z-score with MAD and Sn as scale estimators falsely detected about 50% and 13%, respectively, of the RSS observations as outliers. Furthermore, the average absolute RSS median deviations between raw and outlier-free observations are 3 dB and 0.25 dB, respectively, for the MAD and Sn scale estimators, corresponding to a range error of about 2 m and 0.5 m.

A lot of work has been completed in efforts to extend the notions of soft set and fuzzy soft set and their applications to other domains. However, neither of the two concepts has been examined in the study of functional equations in b-metric spaces. Given this background information, this paper proposes the idea of b-hybrid fuzzy soft contraction in b-metric space and investigates new criteria for the existence of fixed points for such mappings. The significance of the obtained principal result lies in the fact that the contractive inequalities can be specialized in various ways, depending on the choice of the parameters, thereby making it possible to unify, deduce, and refine several corresponding results. To motivate further studies in the directions studied herein, two applications regarding decision-making problems and an existence theorem of integral inclusion are considered, using fuzzy soft set-valued maps.

A receive signal strength (RSS) fingerprinting-based indoor wireless localization system (I-WLS) uses a localization machine learning (ML) algorithm to estimate the location of an indoor user using RSS measurements as the position-dependent signal parameter (PDSP). There are two stages in the system’s localization process: the offline phase and the online phase. The offline phase starts with the collection and generation of RSS measurement vectors from radio frequency (RF) signals received at fixed reference locations, followed by the construction of an RSS radio map. In the online phase, the instantaneous location of an indoor user is found by searching the RSS-based radio map for a reference location whose RSS measurement vector corresponds to the user’s instantaneously acquired RSS measurements. The performance of the system depends on a number of factors that are present in both the online and offline stages of the localization process. This survey identifies these factors and examines how they impact the overall performance of the 2-dimensional (2-D) RSS fingerprinting-based I-WLS. The effects of these factors are discussed, as well as previous researchers’ suggestions for minimizing or mitigating them and future research trends in RSS fingerprinting-based I-WLS.

Resveratrol is a polyphenol compound beneficial to human health, and its main source is grapes. In the present study, the molecular regulation of resveratrol biosynthesis in developing grape berries was investigated using weighted gene co-expression network analysis (WGCNA). At the same time, the reason for the resveratrol content difference between grape exocarp (skin) and mesocarp (flesh) was explored. Hub genes (CHS, STS, F3’5’H, PAL, HCT) related to resveratrol biosynthesis were screened with Cytoscape software. The expression level of hub genes in the exocarp was significantly higher than that in the mesocarp, and the expressions of the hub genes and the content of resveratrol in exocarp peaked at the maturity stage. While the expression levels of PAL, CHS and STS in the mesocarp, reached the maximum at the maturity stage, and F3′5′H and HCT decreased. These hub genes likely play a key role in resveratrol biosynthesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis further indicated that resveratrol biosynthesis was related to flavonoid biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis, and stilbene biosynthesis pathways. This study has theoretical significance for exploring genes related to resveratrol biosynthesis in the exocarp and mesocarp of grapes, and provides a theoretical basis for the subsequent function and regulatory mechanism of hub genes.

Consumption of white rice (WR) has been shown to predispose individuals to metabolic disorders. However, brown rice (BR), which is relatively richer in bioactive compounds, possesses anti-glycaemic and antioxidant effects. In this study, fifteen cultivars of paddy rice that are predominantly consumed in North West Nigeria were analysed for their nutritional composition, bioactive contents and effects on metabolic outcomes in a fruit fly model. Gene expression analyses were conducted on the whole fly, targeting dPEPCK, dIRS, and dACC. The protein, carbohydrate, and fibre contents and bioactives of all BR cultivars were significantly different (p < 0.05) from the WR cultivars. Moreover, it was demonstrated that the glucose and trehalose levels were significantly higher (p < 0.05), while glycogen was significantly lower (p < 0.05) in the WR groups compared to the BR groups. Similarly, the expression of dACC and dPEPCK was upregulated, while that of dIRS was downregulated in the WR groups compared to the BR groups. Sex differences (p < 0.05) were observed in the WR groups in relation to the nutrigenomic effects. Our findings confirm metabolic perturbations in fruit flies following consumption of WR via distortion of insulin signalling and activation of glycogenolysis and gluconeogenesis. BR prevented these metabolic changes possibly due to its richer nutritional composition.

This work successfully created a polypyrrole-polyethyleneimine (PPy-PEI) nano adsorbent for the elimination of the lead ion Pb2+ from an aqueous solution. An efficient conducting polymer-based adsorbent called as was created using ammonium persulfate (NH4)2S2O8 as an oxidant (PPy-PEI). The PEI hyper-branched polymer with terminal amino groups was added to the PPy adsorbent to offer heavy metals more effective chelating sites. Pb2+ removal from aqueous solution using polyethyleneimine micro adsorbent was successfully accomplished using a batch equilibrium technique (PPy-PEI). The generated water-insoluble polymer nanoadsorbent had enough nitrogen atoms; therefore, an effort was made to link PEI, a water-soluble PPy, with PPy, a conjugated polymer, for lead ion adsorption from an aqueous solution. The generated PPy-PEI nanoadsorbents were discovered to have average particle sizes of 18–34 nm and a Brunauer-Emmet-Teller surface area of 17 m2/g, respectively. The thermal behavior of the composites was investigated using thermo gravimetric and differential scanning calorimetric methods. The lead ion adsorption efficacy of pure polypyrrole was found to be 38%; however, a batch equilibrium technique employing nanoadsorbent revealed with the maximum adsorption capacity of 75.60 mg g−1. At pH 10 and 30 min of contact time at 50 °C, 0.2 g of adsorption was shown to be the ideal dosage. X-ray diffraction analysis, energy-dispersive ray spectroscopy, and Fourier transform infrared ray spectrum support the lead ion adsorption by PPy-PEI nanoadsorbents. The cauli-like structure was visible using field emission scanning electron microscopy. Studying the thermodynamic showed that the adsorption was endothermic as illustrated from the positive value of value of ΔH° is 1.439 kJ/mol which indicates that the uptake of Pb2+ onto nanoadsorbent PPy-PEI could be attributed to a physical adsorption process. According to the values of ΔG°, the adsorption process was spontaneous at all selected temperatures. The positive value of ΔS° value (43.52 j/mol) suggested an increase in the randomness at the solid/solution interface during the adsorption process. The adsorption data meet the pseudo-second-order kinetic model and suited the Langumuir isothermal model effectively.

Protein Language Models (PLMs) are shown to be capable of learning sequence representations useful for various prediction tasks, from subcellular localization, evolutionary relationships, family membership, and more. They have yet to be demonstrated useful for protein function prediction. In particular, the problem of automatic annotation of proteins under the Gene Ontology (GO) framework remains open. This paper makes two key contributions. It debuts a novel method that leverages the transformer architecture in two ways. A sequence transformer encodes protein sequences in a task-agnostic feature space. A graph transformer learns a representation of GO terms while respecting their hierarchical relationships. The learned sequence and GO terms representations are combined and utilized for multi-label classification, with the labels corresponding to GO terms. The method is shown superior over recent representative GO prediction methods. The second major contribution in this paper is a deep investigation of different ways of constructing training and testing datasets. The paper shows that existing approaches under- or over-estimate the generalization power of a model. A novel approach is proposed to address these issues, resulting in a new benchmark dataset to rigorously evaluate and compare methods and advance the state-of-the-art.

The essential role of the frequent coexistence of mental disorders and polycystic ovary syndrome (PCOS) is being increasingly recognized in the management of PCOS patients since it influences the success of weight loss interventions. Patients frequently experience disrupted eating behaviors, evidenced by the high prevalence of eating disorders in this population. Therefore, assessment and potential modification of eating disorders and eating-related behavior might be especially relevant to improve obesity treatment outcomes in this population, which remains the most efficient causal treatment in PCOS patients with high metabolic risk. Following a literature overview on common eating disorders and eating behaviors in PCOS, the aim of this review was to explore the prevalence and underlying mechanisms behind those occurrences. Understanding the clinical relevance of those associations and the addition of the assessments of eating disorders as well as eating phenotypes, eating chronotypes, and eating content as essential determinants of eating behavior could aid in the successful management of women with PCOS. In addition, the review also covers the potential of using eating disorders and eating behavior as a tool for the personalization of obesity treatment in PCOS.

Given the increasing risks that antibiotic abuse poses to microecology and human health, it is imperative to develop incredibly powerful adsorbents. This study investigated the use of environmentally sustainable polymeric nanocomposite based on gum arabic (GA) and magnetic nanoparticles (MNPs) synthesized via co-precipitation method to form gum arabic magnetitic nanoparticles (GA-MNPs) as an efficient adsorbent for ciprofloxacin (CIP) removal from aqueous solution. The physicochemical properties and morphology of the synthesized GA-MNPs were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and Energy Dispersive X-Ray Analysis (EDX). The experiment was designed by response surface methodology (RSM) and the Central Composite Design (CCD) was utilized to optimize the operating variables: contact time (0–120 min), pH (3–10), adsorbent dosage (0.10–0.40 g/L), and concentration of adsorbate (5–100 mg/L). Results showed that 96.30% was the maximum percentage of CIP removed. The adsorption effect of the CIP molecule on the surface of the GA-MNPs was investigated using regression analysis and analysis of variance. Furthermore, Freundlich Isotherm and Pseudo Second order kinetic equations have the highest consistency with experimental investigations suggesting double-layer adsorption. This implies that chemisorption was the mechanism involved. In addition, the calculated thermodynamic parameters were postulating an exothermic and spontaneous method in nature. Owing to its adsorption selectivity and recyclability, GA-MNPs could be classified as an environmentally friendly, less expensive, and highly efficient promising adsorbent for remediation of CIP from aqueous solution.

The focus of this paper is to establish a new concept of b-hybrid fuzzy contraction regarding the study of fuzzy fixed-point theorems in the setting of b-metric spaces. This idea harmonizes and refines several well-known results in the direction of point-valued, multivalued, and fuzzy-set-valued maps in the comparable literature. To attract new researchers to this field, some important results are shown to be corollaries. Moreover, a result is presented to establish sufficient conditions for the existence of solutions of integral inclusion of Fredholm type. Lastly, illustrations are presented to validate the suppositions of the given theorems.

In the current study, the total content from two Apocynum species leaves (Apocynum venetum and Apocynum hendersonii) collected from the Ili River Valley Region were extracted, and their bioactivities were investigated. The results showed a significant variation in the total flavonoid contents in the leaf samples collected at different periods (June, July, August, and September), with the highest content in August (60.11 ± 0.38 mg RE/g DW for A. venetum and 56.56 ± 0.24 mg RE/g DW for A. hendersonii), and the lowest in June (22.36 ± 0.05 mg RE/g DW for A. venetum and 20.79 ± 0.02 mg RE/g DW for A. hendersonii). The total flavonoid content was comparably higher in A. venetum than in A. hendersonii. Leaves extracts from the two species demonstrated strong bioactivity, which positively correlated with the total flavonoid contents. The anti-oxidative activity of A. venetum was higher than that of A. hendersonii in tandem with its higher flavonoid contents; the antibacterial activity, however, was conversely opposite. Furthermore, a total of 83 flavonoid metabolites were identified in the two species based on UPLC-ESI-MS/MS, out of which 24 metabolites were differentially accumulated. The variability in these metabolites might be the reason for the different bioactivities displayed by the two species. The present study provides insight into the optimal harvest time for Apocynum species planted in the major distribution area of the Ili River Valley and the specific utilization of A. venetum and A. hendersonii.

Agro-waste management processes are evolving through the development of novel experimental approaches to understand the mechanisms in reducing their pollution levels efficiently and economically from industrial effluents. Agro-industrial effluent (AIE) from biorefineries that contain high concentrations of COD and color are discharged into the ecosystem. Thus, the AIE from these biorefineries requires treatment prior to discharge. Therefore, the effectiveness of a continuous flow bioreactor system (CFBS) in the treatment of AIE using hybrid waste sludge biochar (HWSB) was investigated. The use of a bioreactor with hydraulic retention time (HRT) of 1–3 days and AIE concentrations of 10–50% was used in experiments based on a statistical design. AIE concentration and HRT were optimized using response surface methodology (RSM) as the process variables. The performance of CFBS was analyzed in terms of COD and color removal. Findings indicated 76.52% and 66.97% reduction in COD and color, respectively. During biokinetic studies, the modified Stover models were found to be perfectly suited for the observed measurements with R2 values 0.9741 attained for COD. Maximum contaminants elimination was attained at 30% AIE and 2-day HRT. Thus, this study proves that the HWSB made from biomass waste can potentially help preserve nonrenewable resources and promote zero-waste attainment and principles of circular economy.

Over the past decade, Markov State Models (MSM) have emerged as powerful methodologies to build discrete models of dynamics over structures obtained from Molecular Dynamics trajectories. The identification of macrostates for the MSM is a central decision that impacts the quality of the MSM but depends on both the selected representation of a structure and the clustering algorithm utilized over the featurized structures. Motivated by a large molecular system in its free and bound state, this paper investigates two directions of research, further reducing the representation dimensionality in a non-parametric, data-driven manner and including more structures in the computation. Rigorous evaluation of the quality of obtained MSMs via various statistical tests in a comparative setting firmly shows that fewer dimensions and more structures result in a better MSM. Many interesting findings emerge from the best MSM, advancing our understanding of the relationship between antibody dynamics and antibody–antigen recognition.

Concrete is one of the construction industry’s most essential and commonly used materials [...]

Apocynum hendersonii is a traditional medicinal plant used primarily as tea. It has a potential health benefit from its rich bioactive substances. This study investigated the reactivity of solvents of different polarities (ethanol, ethyl acetate, n-hexane, methanol, and water) extracts of the A. hendersonii leaf. The phytochemical composition of the extracts was evaluated using a Fourier Transform Infrared spectrophotometer (FT-IR), Gas Chromatography-Mass Spectrometry (GC-MS), UHPLC-MS, and Higher Performance Liquid Chromatography (HPLC). The result revealed the presence of medicinally important bioactive constituents, including phenols, flavonoids, and polysaccharides. Methanol extracts exhibited the highest flavonoid contents (20.11 ± 0.85 mg QE/g DW) and the second-highest in terms of phenolic (9.25 ± 0.03 mg GAE/g DW) and polysaccharide (119.66 ± 2.65 mg GE/g DW). It also had the highest antioxidant capacity with 60.30 ± 0.52% and 4.60 ± 0.02 µmol Fe2+ per g DW based on a 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and ferric reducing antioxidant power (FRAP), respectively. Ethanol extract displayed the maximum antibacterial action against Gram-negative and Gram-positive bacteria and the highest inhibition activity against the enzymes tyrosinase and acetylcholinesterase, followed by methanol extract. The principal component analysis revealed a positive correlation between the constituents, bioactivities, and extracts. The overall result showed A. hendersonii as a rich natural source of antimicrobial and antioxidant bioactive compounds and may be used for future applications in pharmaceuticals and food industries.

With the debut of AlphaFold2, we now can get a highly-accurate view of a reasonable equilibrium tertiary structure of a protein molecule. Yet, a single-structure view is insufficient and does not account for the high structural plasticity of protein molecules. Obtaining a multi-structure view of a protein molecule continues to be an outstanding challenge in computational structural biology. In tandem with methods formulated under the umbrella of stochastic optimization, we are now seeing rapid advances in the capabilities of methods based on deep learning. In recent work, we advance the capability of these models to learn from experimentally-available tertiary structures of protein molecules of varying lengths. In this work, we elucidate the important role of the composition of the training dataset on the neural network’s ability to learn key local and distal patterns in tertiary structures. To make such patterns visible to the network, we utilize a contact map-based representation of protein tertiary structure. We show interesting relationships between data size, quality, and composition on the ability of latent variable models to learn key patterns of tertiary structure. In addition, we present a disentangled latent variable model which improves upon the state-of-the-art variable autoencoder-based model in key, physically-realistic structural patterns. We believe this work opens up further avenues of research on deep learning-based models for computing multi-structure views of protein molecules.

This paper investigates the Bregman version of the Takahashi-type generic 2-generalized nonspreading mapping which includes the generic 2-generalized Bregman nonspreading mapping as a special case. Relative to the attractive points of nonlinear mapping, the Baillon-type nonlinear mean convergence theorem for finite commutative generic 2-generalized Bregman nonspreading mappings without the convexity assumption is proved in the setting of reflexive Banach spaces. Using this result, some new and well-known nonlinear mean convergence theorems for the finite generic generalized Bregman nonspreading mapping, the 2-generalized Bregman nonspreading mapping and the normally 2-generalized hybrid mapping, among others, are established. Our results extend and generalize many corresponding ones announced in the literature.

The COVID-19 pandemic has resulted in millions of human deaths, prompting the rapid development and regulatory approval of several vaccines. Although Nigeria implemented a COVID-19 vaccination program on 15 March 2021, low vaccine acceptance remains a major challenge. To provide insight on factors associated with COVID-19 vaccine hesitancy (VH), we conducted a national survey among healthcare workers, academics, and tertiary students, between 1 September 2021 and 31 December 2021. We fitted a logistic regression model to the data and examined factors associated with VH to support targeted health awareness campaigns to address public concerns and improve vaccination rates on par with global efforts. A total of 1525 respondents took part in the survey, composed of healthcare-workers (24.5%, 373/1525), academics (26.9%, 410/1525), and students (48.7%, 742/1525). Only 29% (446/1525) of the respondents were vaccinated at the time of this study. Of the 446 vaccinated respondents, 35.7% (159/446), 61.4% (274/446) and 2.9% (13/446) had one, two and three or more doses, respectively. Reasons for VH included: difficulty in the vaccination request/registration protocols (21.3%, 633/1079); bad feelings towards the vaccines due to negative social media reports/rumours (21.3%, 633/1079); personal ideology/religious beliefs against vaccination (16.7%, 495/1079); and poor confidence that preventive measures were enough to protect against COVID-19 (11%, 323/1079). Some health concerns that deterred unvaccinated respondents were: innate immunity issues (27.7%, 345/1079); allergic reaction concerns (24.6%, 307/1079); and blood clot problems in women (21.4%, 266/1079). In the multivariable model, location of respondents/geopolitical zones, level of education, testing for COVID-19, occupation/job description and religion were significantly associated with VH. Findings from this study underscore the need for targeted awareness creation to increase COVID-19 vaccination coverage in Nigeria and elsewhere. Besides professionals, similar studies are recommended in the general population to develop appropriate public health interventions to improve COVID-19 vaccine uptake.

One of the major impediments to the commercialization of biodegradable plastic is the high cost of substrate. Consequently, there is a continuous search for effective microorganisms and cheaper carbon substrates to reduce the high production cost. In this study, waste transformer oil-degrading bacteria were isolated from soil, wastewater, and sediment samples, using a mineral salt medium (MSM) supplemented with 1% waste transformer oil as the sole carbon source. The isolates were screened for polyhydroxyalkanoates (PHA) production using Nile red staining and fluorescence microscopy. PHA granules accumulation was confirmed using transmission electron microscopy. Oil degradation analysis was accomplished using solvent extraction and gravimetric methods whereas, the bacteria were identified using 16S DNA sequence homology. A total of 62 transformer oil-degrading bacteria were isolated, out of which 16 (26%) showed positive results for Nile red fluorescence microscopy. The identified organisms belong to four different taxonomic genera of Acinetobacter, Bacillus, Proteus, and Serratia. The percentage of oil degradation observed among the different isolates ranged between 19.58% and 57.51%. Analysis of the PHA extracted from the selected isolate revealed the presence of medium chain length polyhydroxyalkanoates (mcl-PHA). The findings of this work have further highlighted the diversity of the bacteria capable of utilizing waste streams such as waste transformer oil. Consequently, the isolates can be explored as agents of converting waste transformer oil into bioplastics.