With rising rates of human obesity, the study aimed to determine the relationship between maternal diet-induced obesity and offspring morphometrics and behaviour in mice. Pregnant and lactating female mice fed a diet high in fat and sugar (HFHS) commonly consumed by human populations showed decreased food, calorie, and protein intake but increased adiposity at the expense of lean mass. The pre-weaning body weight of HFHS offspring was reduced for the first postnatal week but not thereafter with HFHS female offspring having higher body weights by weaning, due to continuing higher fractional growth rates. Post-weaning, there were minor differences in offspring food and protein intake. Maternal diet, however, affected fractional growth rate and total body fat content of male but not female HFHS offspring. Maternal diet did not affect offspring locomotor activity or social behaviour in either sex. Both male and female HFHS offspring displayed reduced anxiety-related behaviours with sex differences in particular aspects of the elevated plus maze task. In the novel object recognition task, performance was impaired in male but not female HFHS offspring. Collectively, the findings demonstrate that maternal obesity alters the growth, adiposity, and behaviour of male and female offspring, with sex-specific differences.

Nowadays, the demand of agricultural production increase, Moreover, the rapid increase of the population in Egypt led to an increase in the demand for food, prompting the government to reclaim more desert lands. Such a study contributes to providing information that contributes to the promising optimization of land resources. This study carried out in an area south Egypt covering 386,171.04 hectares (ha). Remote sensed data were manipulated for defining the land cover/use features. Setting up DEM configures the network of natural drainage flows via the descending slopes. It was a guide for allocating micro dams as water harvesting sites as well as minimizing the runoff hazards and managing the priority of land use suitability versus flood hazards. Land cover/use units were defined as terrestrial irrigated areas of sequentially herbacous crops and permanent trees covering 1387.83 ha in levees; 1608.82 ha in point bar; 718.89 ha in bow bar and 23938.29 ha in alluvial plain. Terrestrial natural vegetation is dominated by xerophytes herbaceous in wadis (123533.56 ha). Terrestrial non-vegetated areas includes bare areas of rock land (98102.59 ha) and 67201.57 in bajada. Artificial non linear surfaces include buildings (5403.59 ha) and linear features include roads and railways (875.78 ha). Aquatic areas include artificial irrigation and drainage canals (1062.15 ha) and natural water body of River Nile course (2785.92 ha). Current land suitability for specific Land Utilization Types (LUTs) was assessed by matching soil attributes with the growth requirement of each LUT. Current land suitability can be improved by decreasing of salinity and framing practices. Accordingly, the land units can be potentially more profitable for increasing the ability of extra crops to be more productive. Old cultivated areas are the most profitable land cover/use units highly suitable (S1) for all LUTs comparing with other land cover categories.

Remote sensing (RS) as a landscape planning and management tool for socio-cultural diversity and inclusiveness in protected(reserved) areas through monitoring of the land-use changes, settlement/living patterns, predominant trades/socio-economic activities in the urban-rural locations, and the demography in Sub-Saharan Africa (SSA). The eighteen federal governments recognized nature reserves in Nigeria being the giant of Africa because of their green landscapes, rich biodiversity, and human resources. This study aimed to explore the application of remote sensing to assess the extent of land degradation and encroachment in the 18 recognized national parks in Nigeria. A review of the protection of national parks using remote sensing and monitoring the trend of national park invasions which could either be natural or man-made. The study is in line with the United Nations SDG Goal 15: Life on Land- “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss”. Located in the West Africa subregion lying on Latitude: 9° 04' 39.90" N (9.077899) and Longitude: 8° 40' 38.84" E (8.677599), with an estimated population of over 220,000,000 people. This study through an intensive review of various literature adopted a mixed approach for the analysis and assessment of the geospatial data, the updated aerial photographs obtained through the Landsat imageries (Google Earth Pro, 2023), and the use of GIS for Geospatial analysis which enables the collection and analysis of spatial and geographic data gathering land use/land covers (LULC) maps, soil type, and elevation maps. While exploring the geophysical ecology and biodiversity conservation of some selected national parks in Nigeria, while also providing cost-effective alternatives for biodiversity monitoring and conservation strategy development. A review of national implementation strategies on biodiversity conservation with the deployment of remote sensing technologies, it is now feasible to obtain large details of the surface of the planet without conducting arduous field activities with the assistance of the availability of multi-date, multi-resolution, multi-sensor aerial information to help prevent for encroachment, loss, and degradation of the natural landscapes.

The current global financial sector is dedicated to providing customers with more advanced and strategic services. With channels like internet banking, mobile phone banking, and telephone banking, the industry delivers multi-channel banking services to satisfy its clients. The COVID-19 pandemic has directly impacted the global economy, as well as the financial sector, with the banking sector facing lockdown initiatives to curb the virus's spread. As a result, mobile payment methods have been favored by people over physical money for transactions. This study analyzes the factors that influenced mobile banking usage during the pandemic in Sri Lanka.. Convenience sampling was used, comprising of 200 online questionnaires conducted among customers in Sri Lanka. The collected data was analyzed using descriptive analysis, exploratory factor analysis, and multiple linear regression through IBM SPSS 25. Research findings revealed that trust and risk were significant factors affecting mobile banking usage in Sri Lanka. Trust had a positive effect while Risk negatively effects to the mobile banking usage. Ease of use and Usefulness were irrelevant factors during the COVID-19 pandemic in Sri Lanka.

Radio astronomical observations at millimeter and submillimeter wavelengths are a very important tool of astrophysical research. However, there is a huge area in the northern Eurasia, including the whole Russian territory, which lacks sufficiently large radio telescopes effectively operating at these wavelengths. In this review we describe our long-term efforts to find suitable sites for such radio telescopes in this area, that is, sites with good atmospheric transparency at millimeter and submillimeter waves. We describe methods and instruments used for measurements and evaluations of the atmospheric opacity. They include special radiometric systems, which are used for estimations of the atmospheric opacity from the sky brightness measurements. Evaluation of the precipitable water vapor from such measurements by the artificial neural network is discussed. Alternative approaches use global atmospheric models and signals of the Global Navigation Satellite Systems. To date, a long-term radiometric monitoring has been performed at several candidate sites and atmospheric conditions for many sites have been evaluated using global atmospheric models. Several sites with the best atmospheric transparency at millimeter and submillimeter wavelengths have been selected. They can be effectively used for astronomical observations at least in the major atmospheric transparency windows at 1.3 mm and 0.85 mm. These results can be also used for space communications and radar systems.

This study assesses the impact of incorporating an adaptive learning mechanism into an agent-based model (ABMS) simulating behavior on a university campus during the course of a pandemic outbreak, with a particular case on the COVID-19 pandemic. The aim is to reduce overcrowding and infections on campus through the use of Reinforcement Learning (RL). Our findings indicate that RL is a viable approach for effectively representing agents’ behavior within this context. The results reveal specific temporal patterns of overcrowding violations. While our study successfully mitigated campus crowding, it had limited influence on altering the course of the epidemic. This highlights the necessity for comprehensive epidemic control strategies that consider the role of individual decision-making influenced by adaptive learning, along with the implementation of targeted interventions. This research significantly contributes to our understanding of adaptive learning within complex systems and offers valuable insights for shaping future public health policies in similar community settings. Future research directions encompass exploring various parameter settings and updating representations of the disease’s natural history.

Taxanes, particularly docetaxel (DTX), has been widely used for combination therapy of head and neck squamous cell carcinoma (HNSCC). For locally advanced unresectable HNSCC, DTX combined with cisplatin and 5-fluorouracil as a revolutionary treatment revealed an advantage in improvement of patient outcome. In addition. DTX plus immune check inhibitors (ICIs) showed low toxicity and increased response of patients with recurrent or metastatic HNSCC (R/M HNSCC). Accumulating data indicate that taxanes not only function as antimitotics but also impair diverse oncogenic signalings including angiogenesis, inflammatory response, ROS production, and apoptosis induction. However, despite an initial response, development of resistance remains a major obstacle to treatment response. Taxane resistance could result from intrinsic mechanisms such as enhanced DNA/RNA damage repair, increased drug efflux, and apoptosis inhibition, and extrinsic effects such as angiogenesis and interactions between tumor cells and immune cells. This review provides an overview of taxanes therapy applied in different stages of HNSCC and describe the mechanisms of taxane resistance in HNSCC. Through a detailed understanding the mechanisms of resistance may help developing the potential therapeutic methods and the effective combination strategies to overcome drug resistance.

Deforestation brings vast and detrimental impact on the environment, economy, and social aspects of community. Thus, it is important to assess and analyze deforestation to inform the decision maker that oversees issued policy and development strategies. The present study aims to characterize deforestation in Central Kalimantan between 2006 - 2020. Utilized land cover map issued by Indonesian Ministry of Environment and Forestry, we analyzed the change in natural forest cover using Remote Sensing and Geographical Information System (GIS) to find the rate the trend, location, and land cover replacement of deforestation in Central Kalimantan Province, Indonesia. The research found that during the period Central Kalimantan lost 1.5 million ha of natural forest with the rate of deforestation 117,000 ha/year. In general, the deforestation shown decrease trend and fluctuated during the period. Deforestation majority takes place at secondary swamp and dry forest that are located at south part of the island. Most of deforestation resulted shrubs, plantations, and agriculture land. The finding of this research could be used as a base to determine the target location for rehabilitation strategy and approach to prevent further deforestation.

Pharmaceutical poisoning is a significant global public health concern, causing approximately 190,000 deaths yearly. This scoping review aims to comprehensively map the available literature on pharmaceutical poisoning and compare patterns between high-income countries (HICs) and low-middle-income countries (LMICs). A systematic search was performed across the following databases: Embase, PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and CINAHL. Studies included were from 1st January 2011 to 31st December 2020, in English, with full text available. Seventy-nine articles were included in the study; 21 were from LMICs and 58 were from HICs. The toxic exposure was largely intentional (77%) in LMICs and accidental (68%) in HICs. Drugs acting on the nervous system were responsible for 95% of toxicities worldwide with analgesics accounting for the largest subtherapeutic group in both LMICs (40%) and HICs (58%). Notable statistics were that HICs accounted for 99% of opioid overdoses, and LMICs accounted for 19% of anti-epileptic-induced toxicities. Overall, the medical outcomes of poisonings were generally worse in LMICs. The review provides possible interventions to target specific geographic locations, based on the trends identified, to reduce the burden worldwide. Many gaps within the literature were recognised, calling for more robust analytical research.

The growing population with changing consumption patterns in developing countries is causing significant challenges with regards to solid waste management. Plastic wastes are particularly problematic, with single-use plastics leaking into the environment, including the marine environment, at an unprecedented rate. Approximately 80 percent of ocean plastics come from land-based sources or about 8 million tons are dumped into the ocean every year. Thailand was identified as one of the top 10 countries ranked by mass of mismanaged plastic wastes, with more than 60,000 tons per year entering the ocean through multiple outlets, including rivers. In the environment, plastic wastes can be degraded into small sizes (less than 5 mm), called microplastics (MPs), which could contaminate the ecosystems and the food chain, including foodstuffs and water supply. Tap water samples collected from a water supply treatment plant and Academic Institutions 1 and 2 in central Thailand were found to contain MPs about 304 ±90, 270 ±109 and 386 ±102 particles/L, respectively. In addition, MPs concentrations of 211 ±70 and 122 ±60 particles/L were also found in drinking water samples collected from commercial bottled water and membrane filtration water, respectively. The MPs sizes of 0-50 µm were most abundant in both the tap and drinking water samples whose shapes were mainly fragments and fiber. These data indicated potential health risks to the people who consume these water sources, and recommendations for health impacts minimization were proposed.

Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide long-range wireless sensor connectivity. In this article, we examine the reliability of the wireless-powered communication network by maximizing the net bit rate. To accomplish our goal, we focus on enhancing the performance of hybrid access points and information sources by optimizing their transmit power. Additionally, we aim to maximize the use of harvested energy by energy-harvesting relays for both information transmission and energy relaying. However, this optimization problem is complex as it involves non-convex variables and requires combinatorial relay selection indicators optimization for decode and forward (DF) relaying. To simplify this problem, we utilize the Markov decision process and deep reinforcement learning framework based on the deep deterministic policy gradient algorithm. This approach enables us to tackle this non-tractable problem, which conventional convex optimisation techniques would be difficult to solve in complex problem environments. The proposed algorithm significantly improves the end-to-end net bit rate of the smart energy borrowing and relaying EH system by 13.22%,27.57%, and 14.12% compared to the benchmark algorithm based on borrowing energy with an adaptive reward for Quadrature Phase Shift Keying, 8-PSK, and 16-Quadrature amplitude modulation schemes, respectively.

Rice canopy height and density are directly usable crop phenotypic traits for the direct estimation of crop biomass. Therefore, it is crucial to rapidly and accurately estimate rice canopy phenotypic parameters. To achieve non-destructive detection and estimation of essential phenotypic parameters in rice, a platform based on LiDAR point cloud data for rice phenotypic parameter detection was established. Data collection of rice canopy layers was performed across multiple plots. The LiDAR-detected canopy top point clouds were selected using a method based on the highest percentile, and the rice canopy surface model was calculated. Canopy height estimation was the difference between ground elevation and percentile value. To determine the optimal percentile defining the rice canopy top, testing was conducted incrementally from 0.8 to 1 with an increment of 0.005. The optimal percentile value was found to be 0.975. The root mean square error (RMSE) between LiDAR-detected canopy height and manually measured canopy height was calculated. The prediction model based on canopy height (R2=0.941, RMSE=0.019) exhibited a strong correlation with actual canopy height. Linear regression analysis was conducted between gap fraction of different plots and manually detected average Leaf Area Index (LAI) of rice canopy. Prediction models for canopy LAI based on ground return counts (R2=0.24, RMSE=0.1) and ground return intensity (R2=0.28, RMSE=0.09) showed strong correlations but had lower correlation with rice canopy LAI. Regression analysis was performed between LiDAR-detected canopy height and manually measured rice canopy LAI. The results indicated that the prediction model based on canopy height (R2=0.77, RMSE=0.03) was more accurate.

Obstetric Violence refers to dehumanized or derogative treatment of women in their pregnancy, childbirth or postpartum periods and may be manifested through the attitudes of health professionals or the performance of unjustified or outdated practices without maternal consent. Currently, there is no tool validated in Spain to measure women’s perception of obstetric violence. The objective of this study was to carry out the cultural adaption and validation of an existing 14-item Obstetric Violence Scale to the Spanish context, and to evaluate its psychometric properties. The research was conducted in two phases: first, a methodological study designed to evaluate content validity, through assessments by 8 experts (calculating the Aiken V coefficient) and face validity in a sample of 20 women; second, a cross-sectional study to evaluate construct validity (through confirmatory factor analysis and Rasch analysis), divergent validity against a scale of birth satisfaction, known groups validity and reliability. In Phase 1, Aiken V values higher than 0.71 were obtained for all items. Phase 2 was conducted on a sample of 256 women and the fit values for the unidimensional model were RMSEA: 0.070 [95%CI: 0.059-0.105] and GFI: 0.982 [95%CI: 0.823-0.990]. The Rasch analysis indicated poor performance of item 2, which was removed. The Omega and Cronbach's Alpha coefficients were 0.863 and 0.860, respectively. A final 13-item version of the Obstetric Violence scale was produced, with total score ranging from 0 (no obstetric violence perception) to 52 (maximum obstetric violence perception). The Obstetric Violence Scale is a reliable and useful tool to measure women's perception of obstetric violence.

Head and neck squamous cell carcinoma (HNSCC) takes the sixth place among the most common cancers in the world. Abnormal methylation can be one of the reasons for this cancer. The aim of this study was to investigate the DNA promotor methylation status of cancer-associated genes (ATM, APC, CDO1, RB1, TP53, WIF1) in patients with HNSCC. Bisulfite Conversion and Methylation-Sensitive High-Resolution Melting was used for analysis of the DNA methylation level of normal and tumor tissues in 44 patients. There were significant differences in DNA methylation level between patient’s tumor and normal tissues for CDO1 and WIF1 genes in all subjects and subgroups (p<0.05). In T3 subgroup there was significant correlation between CDO1 gene methylation and age in the normal tissue. The same correlation was detected also for the WIF1 gene methylation in tumor tissue samples in the subgroup with T3 and in normal tissue samples in the subgroup with T4 (p<0,05). In all genes no significant differences were found between the subgroups (T2, T3, T4 stage, primary/recurrent lesion, non-keratinizing/keratinizing SCC, age before/ after 50, smokers/non-smokers) of the patients. Thus, changes in the expression of the CDO1 and WIF1 genes can affect mechanisms of the occurrence and development of HNSCC.

Amidst the dynamic landscape of education, this paper embarks on a transformative journey that explores the integration of Artificial Intelligence (AI) in literature and language education. Through a qualitative exploratory approach, purposeful and maximum variation sampling method, the researcher delves into the experiences of educators and learners, unraveling the multifaceted dimensions of AI-driven pedagogy in SMC. Drawing upon a theoretical framework encompassing Constructivism, Connectivism, and Socio-Cultural Theory, the study examines AI's role in reshaping pedagogical landscapes, fostering critical thinking, and expanding access to education. The results resonate with participants' narratives, unveiling AI's potential in fostering personalized learning pathways, enhancing collaborative engagement, and bridging digital divides. Ethical considerations in AI education are explored, leading to the proposition of responsible guidelines. These findings underline the transformative power of AI in education, aligned with the institution's commitment to quality education and innovation. Overall, the study calls for ongoing exploration, emphasizing the qualitative research method's depth and richness, as well as the theoretical framework's guidance in realizing the study's objectives. As AI continues to shape education's frontiers, this research underscores the significance of adaptability, ethical awareness, and holistic engagement for school administrators, educators, learners, and researchers alike.

The discovery of interesting inter-relationships between the different malaria epidemiological parameters is essential towards the disease control. However, existing associative rule-based machine learning algorithms for pattern discovery are slow while working on high-dimensional Malaria Indicator Survey (MIS) data, with the further challenge of data under fitting and inadequate result visualization. Hence, this work proposed a novel and efficient associative rule-based machine-learning algorithm with enhanced graphical visualization capacity for rigorous and confident biological result interpretation for malaria control. Through empirical and asymptotic comparative time-complexity performance evaluations, the proposed algorithm scaled better than other existing associative rule-based machine learning algorithms while maintaining its accuracy. The algorithm was applied to two real MIS data sets obtained from the Demographic and Health Survey repository and other supplementary literature source using Nigeria as a case study. The resulting interesting malaria epidemiological discovered novel trends were: a) the malaria disease might not be associated with the anemia symptom; b) there was no significant association between the anemia symptom and the wealth indices of individuals; c) there were other parameters associated with the insecticide resistance capacity of the malaria vector asides the knock down resistance alleles; d) the population dynamics of the malaria vector was not associated with the malaria disease endemicity. In conclusion, this work developed a computationally efficient and user-friendly associative rule-based machine-learning algorithm called E_Apriori for the control of the malaria disease.

Despite the Australian Government’s attempts to reduce domestic violence (DV) incidences, impediments that exist within the social and health systems and interventions designed to identify DV victims may contribute to female victims’ reluctance to disclose DV experiences to their primary healthcare providers. This scoping review aimed to provide the state of evidence about reasons for such reluctance to reveal DV, symptoms and comorbidities patients present to healthcare providers, detection and interventions in the clinical setting, and recommendations to generate more effective responses to DV. Female victims are reluctant to reveal DV because they do not trust or believe that general practitioners can help them to solve the issue, they do not acknowledge they are in an abusive relationship or are unaware that they are, or had been, victims of DV. The most common symptoms and comorbidities victims present with are sleep difficulties and fear. DV screening programs are the most prominent intervention type within Australian primary health services. This scoping review provides formative evidence that further research and interventions are required to increase professional skills, knowledge, sensitivity and referral processes among primary healthcare professionals treating patients experiencing DV in Australia.

This study describes the AMD impacted environments and critically discusses the effects of AMD, current prediction and prevention methods and treatment technologies. The study further, crit-ically analyses the case studies, gaps in AMD research and the challenges and opportunities of-fered by AMD. The study outlined future technological intervention aiming at a paradigm shift towards reducing the volume of sludge generated as well as the operating cost and improving AMD treatment efficiency. The integrated AMD treatment technologies that result in a holistic approach toward sustainable AMD treatment are a current need. As a result, a sustainable AMD treatment strategy has been made possible due to water reuse and rich resource recoveries such sulphuric acid, rare earth elements, and metals. The cost of AMD treatment can be decreased with the use of recovered water and resources, which is essential for developing a sustainable AMD treatment process.

Coptisine (Cop) exerts a neuroprotective effect in central nervous system disease, particularly ischemic stroke. However, its protective mechanism is still unclear. This study aimed to investigate the protective effect of Cop on cerebral ischemia-reperfusion (IR) rats with a middle cerebral artery occlusion model by integrating a gas chromatography-mass spectrometry (GC-MS) based metabolomics approach with biochemical assessment. Our results showed that Cop could improve neurobehavioral function and decrease the ischemia size in IR rats. In addition, Cop was found to decrease inflammatory mediators (e.g., prostaglandin D2 (PGD2) and tumor necrosis factor-α (TNF-α) and attenuate oxidative stress response (e.g., increase the superoxide dismutase (SOD) expression and decrease 8-iso-PGF2α level). Furthermore, GC-MS based cerebrospinal fluid (CSF) metabolomics analysis indicated that Cop influenced the level of glycine, 2,3,4-trihydroxybutyric acid, oleic acid, glycerol, and ribose during IR injury. Cop exhibited a good neuroprotective effect against cerebral IR injury and metabolic alterations which might be mediated through its antioxidant and anti-inflammatory property.

Organophilic nano clay is the composition of mostly clay and organic molecules designed to improve various materials' physical and chemical properties. Permanent deformation in asphalt pavements is primarily the result of inadequate compaction, excessive loading, and high temperatures. Rutting can result in aquaplaning, leading to accidents and costly maintenance and rehabilitation works that drain the economy. Such behavior of asphalt pavements may be attributable to poor selection of aggregate, asphalt binder, or substandard asphalt binders. This study used different percentages of organophilic nano clay ranging from 3.0% - 5.0% with two penetration grade bitumen, i.e., N.R.L 60-70 &amp; N.R.L 80-100. Adding organophilic nano clay to asphalt binder significantly reduced the rutting potential under cyclic loading at high temperatures (55 °C). Ten modified formulations and two virgin bitumen specimens were prepared. The modified binders' viscosity and rutting were tested using the Rotational Viscometer and Wheel Tracker Test (W.T.T.), respectively. The results were analyzed using software for Statistical Analysis. It was recorded that organophilic nano clay-modified bitumen significantly affected rutting to interpret the results. The results indicated that rutting decreased and viscosity increased in all nano clay-modified bitumen samples, with a 4.5% O.N.C modified binder showing the most significant improvement.

Fe- and Al-rich metapelite from the Transangarian segment of the Yenisey Ridge (East Siberia, Russia) is a potential new source of high-alumina refractories. The rocks have relatively high average contents of Al2O3 (20 wt.%) and Fe2O3 (7.91 wt%), moderate K2O (3.44 wt%), and low CaO (0.74 wt%). Their dominant mineral assemblages are andalusite + muscovite + margarite + chlorite + biotite + quartz or staurolite + kyanite or/and andalusite + chlorite + muscovite + biotite + quartz with ±garnet and ±plagioclase. Al2SiO5 polymorphs occur as up to 1.5 cm andalusite porphyroblasts and partial or complete pseudomorphs after andalusite (kyanite and staurolite). Accessories include abundant Fe-Ti oxides and sporadic REE-, Y-, Ca-phosphates; sulfides are negligible. The composition of Al2SiO5 concentrates obtained in laboratory by heavy-media and magnetic separation from ≥0.06 mm fractions meet all requirements for raw material of this type: &gt;56 wt% Al2O3, &lt;42 wt% SiO2, &lt;1 wt% Fe2O3, &lt;1.2 wt% TiO2, and &lt;0.2 wt% (CaO+MgO). The andalusite, kyanite, and mixed ores yield 0.7-4.1 wt%, 0.7-2.2 wt%, and 1.9-6.0 wt% of concentrate, respectively. The best-quality ores rich in Al2SiO5 polymorphs reside in zones of contact and/or dynamic metamorphism superimposed over regional metamorphism of Al-rich rocks.

BMAP-18, derived from the N-terminal region of bovine myeloid antimicrobial peptide BMAP-27, demonstrated potent antimicrobial activity without cytotoxicity. This study aimed to compare the antibacterial, antibiofilm, and anti-inflammatory properties of BMAP-18, rich in aromatic phenylalanine residues, with its aliphatic analogue, BMAP-18-FL. Both aromatic BMAP-18 and aliphatic BMAP-18-FL exhibited equally potent antimicrobial activities against Gram-positive and Gram-negative bacteria, particularly methicillin-resistant Staphylococcus aureus (MRSA) and multidrug-resistant Pseudomonas aeruginosa (MDRPA). Mechanistic investigations employing SYTOX green uptake, DNA binding, and FACScan analysis revealed that both peptides acted by inducing membrane permeabilization and subsequent intracellular targeting. Moreover, both BMAP-18 and BMAP-18-FL effectively prevented biofilm formation and eradicated existing biofilms of MRSA and MDRPA. Notably, BMAP-18-FL displayed superior anti-inflammatory activity compared to BMAP-18, significantly reducing the expression levels of pro-inflammatory cytokines in lipopolysaccharide-stimulated macrophages. This study emphasizes the similarities and differences in the antimicrobial, antibiofilm, and anti-inflammatory properties between aromatic BMAP-18 and aliphatic BMAP-18-FL, providing valuable insights for the development of multifunctional antimicrobial peptides against drug-resistant bacteria.

This paper intends to delve deeply into the current understanding of the ways in which the transition from a central-based economy to an economy relying on free competition, has led to changes in the big urban centres, bringing about a change in the relationships with the suburban areas. The authors take into account the high population density, the lack of space and the elevated price of terrains inside the big cities, hence urban functions migrate beyond the administrative boundaries, thus favouring the process of suburbanization. Within this context, commercial forces are shifted, migrating from the centre to the urban peripheries, or even outside them. This research is based on a comprehensive process of participative investigation (2012-2022) in Bucharest, Ro-mania’s capital city. The research relies on field investigation, statistical and quantitative analyses and bibliographical sources. The conclusions rely primarily on the idea that political changes cannot be separated from economic, cultural and environmental ones, highlighting globalizing flows and the development of big cities. Industrial activities, strongly developed within a central-based economy, have significantly declined, partly compensated for by the development of the tertiary sector and of commercial services, in particular, leading to a functional reconversion of the urban peripheries and of suburban areas. The conclusions suggest that it is very important to be highly careful towards the dilemmas and provocations ensuing from uncontrolled urban growth, therefore several measures of urban planning should be taken with a view to achieving a better co-operation between urban stakeholders and those from the metropolitan areas so as to attain some common objectives in infrastructure in order to reach an integrated regional development.

This paper presents a numerical method for solving a two-dimensional subdiffusion equation with a Caputo fractional derivative. The problem considered assumes symmetry in both the equation’s solution domain and the boundary conditions, allowing for a reduction of the two-dimensional equation to a one-dimensional one. The proposed method is an extension of the fractional Crank-Nicolson method, based on the discretization of the equivalent integral-differential equation. To validate the method, the obtained results were compared with a solution obtained through Laplace transform. The analytical solution in the image of the Laplace transform was inverted using the Gaver-Wynn-Rho algorithm implemented in the specialized mathematical computing environment, Wolfram Mathematica. The results clearly show the mutual convergence of the solutions obtained by the two methods.

This study proposes an image recognition method to assist swine farm managers in collecting health data related to pig feeding and excretion. Analyzing the correlation between sow health data and indoor air quality in the pigsties revealed significant influences of air quality indicators on sow health. Increased levels of TVOC, CO2, and temperature were found to negatively affect feeding health, while increased temperature, humidity, and PM10 were found to negatively impact excretion health. These findings provide a basis for evaluating variables when constructing future sow disease prediction models. Analyzing the correlation between pig health status and air quality can help swine farm managers improve sow production environments, reduce disease risks, enhance production efficiency, and provide valuable insights for future research on disease prediction models.

Non-alcoholic fatty liver disease (NAFLD) has gained attention in the last few years due to its increasing prevalence worldwide becoming a global epidemic. This review aims to discuss the latest recommendations regarding diagnosis and treatment of NAFLD-associated HCC and the remaining challenges. Thus, there is a high amount of data derived from basic and clinical studies that revealed the molecular pathways which drive NAFLD-associated hepatocellular carcinoma (HCC). Based on these findings, new prevention, surveillance and treatment strategies are emerging. However, current data on treatment modalities in NAFLD-associated HCC are still scarce, but based on subgroup analysis results from non-NAFLD HCC studies are promising and could provide a basis for future research agenda to address NAFLD/NASH patients. Conclusion: Due to the pandemic proportions that NAFLD gained in the last few years, there is a high amount of data derived from basic and clinical studies that revealed the molecular path-ways which drive NAFLD-associated HCC. Based on these findings, new prevention, surveillance and treatment strategies could be developed at an individual level.

This paper describes the indoor air pollution in urban (Lahore, Faisalabad, Gujranwala, Rawalpindi and Karachi) Pakistani regions while considering the outdoor air and the health and wellbeing of the occupants present indoors. It also aims to assess previous methodological approaches Such as Air Conditioning Systems, used by developed countries to improve air quality to demonstrate the improvements that can be made in air quality in Pakistani urban areas. This research also investigates the causes, concentration and effects of poor air quality in Pakistani urban areas such as particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulphur oxides (SOx) and volatile organic compounds (VOC’s). The average concentration of these pollutants in Pakistan’s indoor air is, particulate matter (PM): [100 – 250 µg/m3 for PM2.5, 200 – 600 µg/m3 for PM10] 1 – 20 ppm for carbon monoxide (CO), nitrogen oxides (NOx): [50 – 100 µg/m3 for NO2, 20 – 40 µg/m3 for NO], 20 – 50 µg/m3 for sulfur dioxide (SO2), volatile organic compounds (VOCs): 0.1 – 0.5 ppm for formaldehyde, 5 – 10 µg/m3 for benzene and 20 – 30 µg/m3 for toluene. It should be noted that these concentrations can differ depending on the origin of pollution, location, and time of day. The literature review is made up of a combination of descriptive research methods that are used to inform the research background of ambient and indoor air quality, thus the literature review provides a theoretical and methodological background about the air pollution and its improvement in different parts of the world. According to the World Air Quality Index, Pakistan is the third most polluted country in terms of average PM2.5 concentration which is 14.2 times the WHO annual air quality guideline value. As a result, it is suggested that a PM2.5 concentration reduction program be implemented in urban Pakistani regions' indoor air.

Brassica napus is an important vegetable and oil crop worldwide. The research is meaningful for yield and plant architecture in B. napus. In this study, one natural mutant (MT) line with determinate and capitulum-like inflorescence was chosen for further study. The paraffin sectioning detected that the inflorescence apex began to split and developed into one terminal flower, starting from five-leaf stage. Genetic analysis indicated that the segregation patterns of inflorescences in the F2 populations supported a digenic inheritance model, which was further approved by BSA-Seq technique. The BSA-Seq method detected two QTL region on C02 (14.27-18.41 Mb) and C06 (32.98-33.68 Mb) for the genetic control of determinate inflorescences in MT plants. In addition, the expression profile in MT compared with WT was analysized, and a total of 133 candidate genes for regulating the flower development (75 genes, 56.4%), shoot meristem development (29 genes, 21.8%) and inflorescence meristem development (13 genes, 9.8%) were identified. Then one joint analysis combing BSA-Seq and RNA-Seq identified two candidate gene of BncTFL1 and BncAP1 for regulating the MT phenotype. Besides, the potential utilization of the MT plants was also discussed.

Survivors of sexual and gender-based violence (SGBV) are often hindered in their quest to access quality healthcare. This could complicate the achievement of the laudable SDG Target 3.7. The study used an ethnographic approach to solicit information from health providers, adolescents, and young women (AYW) in 10 communities from Lagos and Ibadan; two major cities in Nigeria. Findings indicated that the structural system of services provided in the health services at the primary healthcare level was limited, which posed a great challenge in AYW’s utilization of services for sexual and gender-based violence (SGBV). Some of the challenges identified by health providers included non-existing counseling services, rehabilitation centers, referral problems, and a lack of training for health providers in handling victims of SGBV. The study provided the context of the health providers’ inadequacy and structural problem of health services in providing comprehensive support services to victims of SGBV like adolescents and young women in the slum setting. This poses a barrier to the utilization of services by the survivors. Necessary inclusive services that will meet the need of the victims of SGBV should be in place at primary healthcare centers close to the people in the community for accessibility.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

This qualitative study conducted at St. Michael's College explores the integration of philosophical dimensions in arts and sciences education and its implications for pedagogy and student learning. Drawing on three theoretical framework informed by Piaget, Sartre, and Vigotsky, the study examines the perspectives of 30 participants, including teachers and students, through semi-structured interviews. The findings reveal diverse viewpoints, with some participants emphasizing disciplinary specialization for focused skill development, while others advocate for integrating philosophical dimensions to enhance critical thinking, interdisciplinary connections, and ethical awareness. The implications highlight the importance of balancing disciplinary depth with interdisciplinary exploration in arts and sciences education. Educators are encouraged to recognize the value of disciplinary specialization while integrating philosophical dimensions to foster critical thinking skills, interdisciplinary connections, and ethical awareness among students. Recommendations include providing professional development opportunities for educators, incorporating philosophical perspectives in curriculum frameworks, and exploring the long-term impact of integrating philosophical dimensions on student learning outcomes. Future research should investigate specific pedagogical approaches, consider cultural and contextual factors, and further explore the impact of integrating philosophical horizons to advance educational practices. By embracing the integration of philosophical dimensions, educators can create meaningful learning experiences that promote critical thinking, interdisciplinary connections, and ethical awareness in arts and sciences education.

As the demand for aromatic and medicinal herbs increases, so does the pressure to intensify production, increasing the risk of overexploitation of these natural resources. Sustainability corresponds to the preservation of something that exists in the present and must be maintained in the future, implying accountability and obligation. However, in order to maintain the conditions and essential goods for the survival of future generations, consumers and businesses must commit to sustainable practices. The circular economy is considered one of the solutions to promote a sustainable system and can be defined as a transition from a linear model, where resources are transformed, used and discarded, to a circular (regenerative) model, where materials are reused whenever possible. An ecologically correct approach to waste reuse avoids the negative impacts associated with improper disposal of agro-industrial wastes, such as mass proliferation of microorganisms, production of greenhouse gases, loss of energy potential, and other negative impacts on the environment or human health. The objective of this study is to provide a compilation of good agricultural practices that promote sustainability in the production of medicinal and aromatic herbs, particularly in the areas of cultivation, harvesting, drying, extraction, and packaging, and to highlight the potential for evaluating processing residues in medicinal and aromatic herbs.

Introduction: The identification of some prognostic markers in head and neck cancers (HNC) is necessary for the stratification of the therapeutic approach with benefits in increasing treatment response rates and limiting the toxic side effects of treatments. Neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and pallets-to-lymphocyte ratio (PLR) are currently validated as cheap and accessible biomarkers in different types of solid tumors. The purpose of the study was to evaluate the possible biomarker value of NLR, PLR and MLR recorded pre-treatment (radiotherapy/chemotherapy) for prognostic purposes in HNC. Materials and methods: The study included 190 patients with HNC included in the oncology record in the oncology outpatient clinic of the Craiova County Emergency Hospital starting from January 2002 and deceased until December 2022. Among them, 40 patients treated multimodally in the Clinic were included in the study of Oncology of the Craiova County Emergency Hospital for which the pre-treatment value (chemotherapy/radiotherapy) of NLR, PLR and MLR could be calculated. Overall survival (OS) values were correlated with NLR, PLR and MLR. Results: Median values for NLR, PLR and MLR were 6.15 (1.24-69), 200.79 (61.3- 1775.0) and 0.53 (0.12-5.5) respectively. In the study, the mean values for NLR, PLR and MLR of 2.88, 142.97 and 0.36 respectively were obtained. Median OS in the study group was 11 months (1-120). Although a negative Pearson`s correlation, the relationship between your variables was only weak, values R =.07, p=.67; R=.02, p=.31 and R=07, p=.62 being related with NLR, PLR and MLR respectively correlation with overall survival (OS). The median values of NLR, PLR and MLR were calculated (1.53, 90.32 and 0.18 respectively) for HNC cases with pre-treatment values of NLR <2 and for HNC cases with NLR values ≥6 (23.5, 232.78 and 0.79 respectively). Median OS for cases with NLR<2 and NLR≥6 were 17.4 and 13 months, respectively. Conclusions: The negative correlations of NLR, PLR and MLR with OS reported in the study are in accordance with the data reported in the literature for locally advanced recurrent and metastatic HNSCC cases. The comparative analysis of the data in the group with NLR<2 and NLR≥6 highlights an advantage of 4.4 months in median OS in favor of the group with low values of NLR. Being cheap and accessible, these markers could change the therapeutic approach even in centers with limited resources. The role of borderline NLR values as a prognostic factor in HNSCC must also be defined. PLR and MLR are less evaluated as biomarkers but the study demonstrates their potential to be used as prognostic biomarkers, it remains to be clarified if their inclusion in multivariable models along with NLR would bring a benefit

Violence against paramedics has been described as a ‘serious public health problem’ but one that remains ‘vastly underreported’, owing to an organizational culture that stigmatizes reporting – hindering efforts at risk mitigation in addition to creating a gap in research. Leveraging a novel reporting process developed after extensive stakeholder consultation and embedded within the electronic patient care record, our objective was to provide a descriptive profile of violence against paramedics in a single paramedic service in Ontario, Canada. Between February 1, 2021, through January 31, 2023, a total of 374 paramedics in Peel Region (48% of the workforce) generated 941 violence reports, of which 40% documented physical (n=364) or sexual (n=19) assault. The violence was typically perpetrated by patients (78%) and primarily took place at the scene of the 9-1-1 call (47%); however, violent behavior frequently persisted or recurred while in transit to hospital and after arrival. Collectively, mental health, alcohol, or drug use were listed as contributing circumstances in 83% of violence reports. In all, 81 paramedics were physically harmed because of an assault. On average, our data correspond to a paramedic filing a violence report every 18 hours, being physically assaulted every 46 hours, and injured every 9 days.

Pesticides are chemical products are used to protect crops to prevent or eliminate undesirable organisms. Pesticides can contaminate continental waters, air, soil and food products. The presence of pesticide residues must therefore be monitored in water and food using sensitive, reliable and broad-spectrum analytical methods, as there is a huge variety of pesticides. Biosensors are one of the screening methods with great potential for detecting residues below the maximum residue limits. The different sensing principles of enzymatic biosensors for pesticide analysis will be described. This review highlights the great potential of colorimetric, enzymatic biosensors for detecting pesticide residues in water and food. Moreover the development of dual colorimetric and fluorimetric sensors during the past years is presented. These methods are most often based on the enzyme acetylcholinesterase, whose activity is inhibited by pesticides. The different approaches used in the development of these biosensors will be detailed, based on different chemical substrates, fluorophores and nanomaterials. The advantages and disadvantages of each approach will be discussed. Finally, the development prospects for improving these biosensors will be presented.

Globally, gastric cancer is a major cause of cancer mortality, with a 5-year survival rate of 32% for locally advanced and metastatic gastric cancer. This systematic literature review summarized the clinical, safety, and humanistic outcomes associated with systemic regimens given as first line therapy for locally advanced and metastatic gastric cancer. The search included articles published in English in PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, and the American Society of Clinical Oncology meeting library, from inception to April 2022. Phase II and III randomized controlled trials conducted among western populations diagnosed with stage III and IV locally advanced and metastatic gastric cancer were included. Two investigators independently reviewed the studies, conducted data extraction, and assessed risk of bias in accordance with PRISMA guidelines. Twenty-four randomized controlled trials totaling 8,705 patients were included. Median overall survival ranged from 5.0-13.1 months, median progression-free survival ranged from 2.0-7.7 months, and objective response ranged from 13.0-64.1%. Two studies reported higher quality of life outcomes. Grade 3 and 4 adverse events were reported in most studies. Improvement in clinical outcomes can be seen in recently published randomized controlled trials for locally advanced and metastatic gastric cancer.

Many buildings built before the energy performance regulations are in a situation of thermal discomfort and energy inefficiency. The creation of intelligent environments advances towards new opportunities, based on real-time monitoring and on the development of sensors and technologies. Furthermore, the standards for building automation and electronic systems enable interoperability and interconnection between control devices and systems. The application of soft computing has significantly improved the energy efficiency, however, requires prior assessment to design the automation functions. Temperature, humidity, air quality, occupancy and energy consumption are the most common measured parameters, but the relationship with other operational variables such as occupancy or some building states remains as a research challenge. This article presents a methodology to develop the automatization of an existing large public building. The methodology consists of three stages: 1. Assessment and diagnosis to set appropriate actions using EN ISO 52120-1. 2. EN 50090 for open communication networks, and EN ISO 52120-1 to assign the technical building management. 3. System control deploying of low-cost and low-consumption input and output devices. It has been proved that it is possible to effectively automate an obsolete building with a low cost, open source system that can be easily applied in other buildings.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

The global malaria community has picked up the theme of malaria elimination in greater than 90 % of the world’s population in the next decade. The recent reports of P. vivax in all sub-Saharan Africa, including Duffy negative individuals, threaten the efforts to achieve elimination. This is not only in view of strategies that are tailored only to P. falciparum elimination, but also due to currently revealed biological characteristics of P. vivax concerning the relapse patterns of hypnozoites and conservation of a large biomass at cryptic sites in the bone marrow and spleen. A typical scenario has been observed in Botswana from the period between 2008 to 2018, which palpably projects how P. vivax could endanger efforts at malaria elimination where the two parasites co-exist. The need for the global malaria community, NMPs, funding agencies and relevant stakeholders to engage in a forum to discuss and recommend clear pathways for sub-Saharan Africa regarding malaria elimination including P. vivax, is warranted.

To realize the energy recovery of wheat straw, the pyrolysis behavior of wheat straw was studied at three heating rates (10, 20, and 30 K/min) based on thermogravimetric analysis (TG–DTG). Kinetics and thermodynamics were analyzed using Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) model-free methods, and reaction mechanism was determined using Coats–Redfern (CR) model-fitting method. The results show that there are three weightlessness stages in the pyrolysis process, of which the second stage was the main weightlessness stage and two distinct peaks of weightlessness were observed in this stage. With increasing heating rate, the main pyrolytic weightlessness peaks of DTG curve shifts to higher temperature. The pyrolysis activation energy calculated by FWO and KAS methods are 165.17–440.02 kJ/mol and 163.72–452.07 kJ/mol, and the pre-exponential factor vary in the range of 2.58×1012–7.45×1036 s-1 and 1.91×1012–8.66×1037 s-1, respectively. The thermodynamic parameters indicates that wheat straw has the favorable conditions for product formation and containes potential energy to be utilized for bioenergy production, its pyrolysis reaction was non-spontaneous and the energy output is stable. CR method analysis shows that the A1/3 random nucleation model is the most suitable mechanism to characterize the pyrolysis process, and random nucleation may be in charge of the main pyrolysis stage. This study can provide a theoretical basis for the thermochemical conversion and utilization of wheat straw.

This article explores the behavioral geography of the Hajj pilgrimage, focusing on the impact of the physical environment on pilgrims' behavior. Using qualitative research and analyzing religious literature and online publications, the study reveals significant findings. The spatial arrangement of the Grand Mosque, including the central courtyard and pillars, influences pilgrims' behavior during the Tawaf ritual. Environmental factors such as crowds and noise affect pilgrims' experiences, evoking anxiety while enhancing the ceremony's spiritual significance. Cultural and religious beliefs also shape pilgrims' behavior during the circumambulation. This study provides valuable insights into the multifaceted factors shaping pilgrims' behavior during the Hajj, including spatial organization, cultural influences, and social interactions. The findings can inform improvements in infrastructure, crowd management, and services to enhance the overall pilgrimage experience.

The automobile industry is often believed to be moving towards electric vehicles. Hybrid electric vehicles (HEVs) and electric vehicles (EVs) are anticipated to dominate the automotive industry. Regenerative braking is one of the modern approaches that recharge the battery by extracting the kinetic energy from the braking thus improving the vehicle range. However, the rate of current supplied by regenerative braking to the battery is a major concern as lithium-ion (Li-ion) is susceptible to failure due to the intensity of the charging-discharging rate, and operating temperature. So, this review article focuses on the effect of regenerative braking on the life of the battery and measures being taken to protect the battery from higher charging during regenerative braking. Various research articles are considered for observing the effect of regenerative braking on battery life. It is found that longer duration charging current obtained from regenerative braking that is irrespective of current intensity is the prominent factor of battery deterioration. If the SOC and the temperature are not in the optimal range, the Lithium plating rate increases. However, a higher level of regenerative braking increases the battery life even at high SOC and temperature by reducing the Depth of Discharge (DOD) and by using shorter recharging periods.

Road intersections are made of asphalt pavement, a popular road surface material used worldwide. The pavement may suffer deformities and deterioration, resulting in higher maintenance expenses and an elevated likelihood of road accidents, due to factors such as heavy vehicles and environmental variables like temperature and rainfall. To tackle these obstacles, researchers have devised several machine-learning algorithms and optimization techniques. These tools aim to forecast and scrutinize pavement deformation, with the goal of refining pavement design and maintenance approaches, as well as obtaining a more comprehensive comprehension of the factors that impact pavement effectiveness. This paper shows that heavy vehicles contribute significantly more to road erosion, and the retention and braking of vehicles greatly impact roadways. We also emphasize the statistical errors computed on the actual data range and demonstrate the results of the multilayer perceptron (MLP) model. The MLP model used the lath erosion standard to simulate future impact. Even though the model given is based on a small sample of data from one intersection, its estimates for road erosion in a year were found to be accurate when contrasted to real data. Controlling traffic flow can significantly improve road conditions, reducing erosion decay by reducing the time spent at intersections and other parameters. We conclude that machine learning can help control traffic flow, which can significantly improve road conditions, reducing vehicle time stretches at intersections.

.Purpose: This paper presents a comparative analysis of state-of-the-art DIR algorithms in the context of head and neck squamous cell carcinoma (HNSCC) radiation therapy. Materials and Methods: We used a dataset of head and neck cancer patients within the Cancer Image Archive, which includes 31 patients with 3D CT image data from pre-treatment, mid-treatment, and post-treatment stages of radiotherapy. We applied DIR algorithms to two datasets, one for pre-treatment to mid-treatment registration and another for mid-treatment to post-treatment registration, by aligning one CT image to another CT image. To quantitatively analyze the patient data, we focused on the spinal cord, optic nerve, brain stem, cochlea, and PTV as the OAR datasets. To verify the DIR algorithm, we used two non-learning-based methods, SyN and NiftyReg, as well as three deep learning-based methods, Voxelmorph, Cyclemorph, and Transmorph. We trained a deep learning model by adjusting the ratio of the training dataset, validation dataset, and test dataset to 7:1:2. Results: The average DSCs of SyN and NiftyReg, the non-learning-based methods, were 0.74±0.06 and 0.70±0.12, respectively. The deep learning-based methods, Voxelmorph, Cyclemorph, and Transmorph, had average DSCs of 0.72±0.08, 0.68±0.11, and 0.69±0.13, respectively. The deep learning DIR algorithm produced transformed outputs of OAR/PTV in a shorter time than other models, including commercial and conventional mathematical algorithms (At Inference(sec/images), Voxelmorph: 0.36, Cyclemorph: 0.3, Transmorph: 5.1, SyN: 140, NiftyReg: 40.2). Conclusions: In conclusion, our study provides a comprehensive comparison of commercial DIR algorithms with traditional and deep learning-based DIR methods. Our results demonstrate that commercial DIR algorithms outperform traditional DIR methods in terms of accuracy and efficiency. However, we also show that deep learning-based DIR methods have the potential to achieve similar performance to commercial algorithms with proper training and optimization. Our findings suggest that both commercial and deep learning-based DIR methods have their respective advantages and limitations, and the choice of method should depend on the specific requirements of the clinical application. Overall, our study contributes to ongoing efforts to improve the accuracy and efficiency of DIR methods for better patient outcomes.

Cooking is a very decentralized and private way of energy consumption in human activities. The existing investigation and statistical analysis can’t effectively calculate the proportion of population relying on clean cooking fuel and utilization technology in the region. Therefore, based on the big data of the earth, this paper adopts the combination of spatial analysis and statistical analysis to determine the survey sample area, and according to the economic conditions, topographic characteristics, national policies for new energy construction and living habits of the provinces and cities under investigation, the questionnaire survey is conducted for the research area to calculate the proportion of the regional population relying on clean cooking fuels and utilization technologies. Taking the south of the Yangtze River in China as an example, the paper effectively calculates that 88.25% of the population depends on clean cooking fuel and technology in this region, of which 89.81% are in urban areas and 79.87% are in rural areas. Analysis of the survey data shows that the proportion of the population using clean cooking fuels and technologies is related to factors such as economic development, income and resource endowment. There is a large urban–rural gap in terms of energy consumption tendency and structure in the south of the Yangtze River in China and cooking energy consumption in rural households also varies from region to region. The technical ideas and conclusions of the paper have high reference application value, which can help promote the upgrading of clean energy utilization and provide data basis for relevant decision and policy making.

Habitat loss and fragmentation are of concern to conservation biologists worldwide. However, not all organisms are affected equally by these processes, thus it is important to study the effects of living in fragmented habitats on species that differ in lifestyle and habitat requirements. In this study we examined dispersal and connectivity patterns of rodents, one endemic (Eliurus myoxinus) and one invasive (Rattus rattus), in two landscapes containing forest fragments and adjacent continuous forest patches in northwestern Madagascar. We generated genomic (RADseq) data for 66 E. myoxinus and 81 R. rattus individuals to evaluate differences in genetic diversity as well as inbreeding and connectivity in two landscapes. We found higher levels of inbreeding and lower levels of genetic diversity in E. myoxinus compared with R. rattus. We observed related dyads both within and between habitat patches and positive spatial autocorrelation at lower distance classes for both species, with a stronger pattern of spatial autocorrelation in R. rattus. Across each site we identified contrasting migration rates for each species, but these did not correspond to habitat-matrix dichotomies. The relatively low genetic diversity in the endemic E. myoxinus suggests ecological constraints that require further investigation.

When the minimal length approach emerging from noncommutative Heisenberg algebra, generalized uncertainty principle (GUP), and thereby integrating gravitational fields to this fundamental theory of quantum mechanics (QM) is thoughtfully extended to Einstein field equations, the possible deformation of the metric tensor could be suggested. This is a complementary term combining the effects of QM and general relativity (GR) and comprising noncommutative algebra together with maximal spacelike four–acceleration. This deformation compiles with GR as curvature in relativistic eight–dimensional spacetime tangent bundle, generalization of Riemannian spacetime, is the recipe applied to derive the deformed metric tensor. This dictates how the affine connection on Riemannian manifold is straightforwardly deformed. We have discussed the symmetric property of deformed metric tensor and affine connection. Also, we have evaluated the dependence of a parallel transported tangent vector on the spacelike four–acceleration given in units of L, where L = rℏcG3 is a universal constant, c is speed of light, and ℏ is Planck constant, and G is Newton’s gravitational constant.

The risks for complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection are higher in obese individuals. Obesity is a state of chronic low-grade inflammation, with high leptin levels due to leptin resistance, high basal levels of other pro-inflammatory cytokines such as TNF-alpha, MCP-I and IL-6, and low adiponectin levels, thus contributing to a state of defective innate immunity as well as impaired B and T cell responses. Obesity is a risk factor for metabolic syndrome, diabetes, cardiovascular disease and hypertension. It has been observed that pre-existence of these diseases confers a higher risk of severe SARS CoV2 infection as well as the need for intensive care; even below the age of 60 years if their body mass index (BMI) is greater than 30 kg/m2, and even more so if it is > 35 kg/m2. The metabolic factors contributing to the changes in altering the immune mechanisms in obese individuals and how this enhances the susceptibility to infection and development of serious SARS-CoV2 infection have been the subject of many debates. Future development of targeted therapy and guidelines will be benefited by greater understanding into these metabolic pathways.

E-commerce has gained increased popularity over the last decade. To date, there is an open debate as to whether e-commerce or brick-and-mortar shopping is environmentally less sustainable, especially due to the growing mobility resources needed for e-commerce distribution. The analysis at hand compares the CO2-equivalent emissions of e-commerce and brick-and-mortar shopping of pharmaceutical products considering spatial aspects and the typical transport modal mix of consumers when doing online and offline shopping. The object of analysis is a retailer of pharmaceutical products, more precisely medicines, which offers, both, brick-and-mortar shop and online shopping possibilities. The results show that spatial aspects concerning the residential location of consumers, the vehicles used for shopping trips, the shopping basked size, and trip-chaining effects have a crucial impact on the mobility demand and CO2-equivalent emissions of the two commerce forms. In general, for rural and sub-urban areas, e-commerce results in lower CO2-equivalent emissions, while in urban areas, brick-and-mortar shopping is the favourable solution, if the consumers walk or cycle to the next pharmacy.

Background: Human Papillomavirus causes various types of cancer in both men and women. Woman with HPV infection has a risk of developing invasive cervical cancer. Globally, HPV 16 and 18 were predominant. This study aims to find the distribution of various HPV types in South Andaman. Methods: A cross sectional study conducted among woman in South Andaman where cervical scrapes were collected after the collecting the written informed consent. Detection of HPV genotypes was carried out by using PCR assay. Further, sequencing analysis was performed using MEGA11 to identify various genotypes in this territory. Result: Of these 1000 samples, 32 were positive for HR-HPV16 and 4 were positive for HR-HPV18. Fifteen HPV genotypes were detected using molecular evolutionary analysis. Six cases were identified with multiple genotypes. Most prevalent genotype is HPV16 which belonged to Lineage-A and sub-lineage A2. HPV18 identified in South Andaman belonged to the lineage A1 to A5. Discussion: Various HPV types were identified among women in South Andaman. Global burden of cervical cancer associated with various HPV sub-lineages. HPV-16 A1 sub-lineage was globally widespread whereas sub-lineages A1, A2 and D1 was prevailing in South Andaman. Conclusion: High risk HPV identified in this study enlightening the importance of HPV vaccination among the woman in remote places. These findings will help to strengthen public health awareness programs and prevention strategies for the women in remote areas.

In order to formulate a reasonable water input model for cotton fields in southern Xinjiang, scientific and rational fertilization, reduce soil carbon leaching, and improve soil carbon sequestration capacity, the undisturbed soil column leaching test was used to simulate the current field management method in the study area. Two methods of drip irrigation and flood irrigation were set up, and three irrigation and three nitrogen fertilizer levels were used to carry out the undisturbed soil column leaching test. The results showed that the amount and mode of water and nitrogen input affected the distribution and leaching loss of organic carbon and inorganic carbon in soil. When the nitrogen application rate increased from 270 kg·hm-2 to 450 kg·hm-2, the leaching loss of soluble organic carbon and soluble inorganic carbon increased significantly. When the water input increased from 6000 m3·hm-2 to 9000 m3·hm-2, the leaching loss of DOC and DIC increased significantly. The carbon leaching loss under drip irrigation was higher than that under flood irrigation. The leaching rates of DOC and DIC were the fastest under the conditions of high water ( 9000 m3·hm-2 ) and high fertilizer ( 450 kg·hm-2 ). It shows that water and nitrogen input and irrigation methods are important factors affecting soil carbon leaching. In the case of excessive water input, long-term high-frequency irrigation is the main factor affecting carbon leaching.

This article provides a comprehensive analysis of the global gas and liquefied natural gas (LNG) markets. The article begins by discussing the increasing demand for gas and LNG, particularly in Asia, as countries aim to transition to cleaner sources of energy. It explores how market volatility has led to energy security interventions and lasting economic and emissions impacts. It then explores the global supply and demand dynamics, highlighting the structural change expected in the market and the competition between Europe and Asia for limited new LNG supply. The article also focuses on Europe's increased flexibility and dependence on LNG imports, which have risen by 60% to 121 million tonnes, offsetting lower Russian pipeline imports. Furthermore, the article delves into global supply and demand dynamics, how the market is expected to remain tight, and how record gas and LNG prices have led to demand reductions. Additionally, it analyzes the future outlook and investment needs, highlighting the continued uptake of gas in heavy-duty transport and the need for further investment to avoid a supply-demand gap. The article concludes with an analysis of the implications for the future of the global gas and LNG markets.

Fruit softening is an important characteristic of peach fruit ripening. The auxin receptor TIR1 (Transport Inhibitor Response 1) plays an important role in plant growth and fruit maturation, but little research has been conducted on the relation of TIR1 to the softening of peach fruits. In this study, the hardness of isolated peach fruits was reduced under exogenous NAA treatment of low concentration, at the same time, the low concentration of NAA treatment reduced the transcription level of PpPG and Ppβ-GAL genes related to cell wall softening, and PpACS1 genes related to ethylene synthesis. The transient over-expression of the PpTIR1 gene in peach fruit blocks caused significant down-regulation of the expression of early auxin-responsive genes, ethylene synthesis and cell wall metabolic genes related to fruit firmness. Through yeast two-hybrid technology, bimolecular fluorescence complementary technology, and firefly luciferase complementation imaging assay, an interaction between PpTIR1 and PpIAA1/3/5/9/27 proteins was revealed, and the interaction depended on auxin and its type and concentration. These results show that PpTIR1-Aux/IAA module has a possible regulatory effect on fruit ripening and softening.

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

3D point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we design an augmented sampling and grouping (ASG) module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to mine point cloud’s local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first try to use a linearly-normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module is adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that our method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which was 0.5% higher than PCT. Our network also archived 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

Accelerating the construction of livestock powerhouses is of great significance to better enhance the ability to guarantee the supply of livestock products and improve the quality, efficiency and competitiveness of the livestock industry. This study constructed an evaluation index system to assess the level of China’s livestock powerhouse and then performed an in-depth analysis of the issues and challenges facing the construction of livestock powerhouses. The research results showed that the level of China’s livestock powerhouse ranked 5th in the world, and the livestock industry was transitioning from being a large livestock country to a powerhouse, while there was still a large gap in terms of reaching the goal of constructing livestock powerhouses. There were significant differences in the level of livestock powerhouses across different livestock industries; the layer industry was the world leader in China, whereas the pig, sheep and goat, and broiler industries were stronger, while the beef cattle and dairy industries were weaker. There are still many challenges to accelerating the construction of livestock powerhouses in terms of supply security, scientific and technological support, operation systems, industry and supply chain resilience, international trade, policy support, etc. It is recommended to improve the institutional mechanism for the construction of livestock powerhouses, promote a high level of self-reliance and self-improvement in livestock science and technology, build a modern livestock operation system, enhance the resilience and security level of the industrial and supply chain, and consolidate and expand international trade and cooperation.

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid.

Bionic robotic hand can perform many movements similar to human hand. But there is still a significant gap in manipulation between robot and human hand. It is necessary to understand the finger kinematics and motion patterns of human hand to improve the performance of robotic hand. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hand of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a largest dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Besides, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by PIP joint. Regarding the finger sequence, the thumb started to move before four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided kinematic reference for the design of robotic hand and thus contribute to its development.

Quantile regression model is widely used in variable relationship research of general size data, due to strong robustness and more comprehensive description of the response variables' characteristics. With the increase of data size and data dimension, there have been some studies on high-dimensional quantile regression under the classical statistical framework, including higher-efficient frequency perspective, which is however at cost of randomness quantification, or lower-efficient Bayesian method based on MCMC sampling. To overcome these problems, we propose the high-dimensional quantile regression with Spike-and-Slab Lasso penalty based on variational Bayesian (VBSSLQR), which can not only improve the computational efficiency but also measure the randomness via variational distributions. The simulation studies and real data analysis illustrate that the proposed VBSSLQR method is superior to or equivalent to other quantile and non-quantile regression methods (including Bayesian and non-Bayesian methods), and its efficiency is higher than any other method.

The formation and localization of sporadic E(Es) layers predicted by the ions vertical drift velocity and its vertical change in the lower thermosphere during nighttime are shown analytically and by numerical simulations. The consideration of existence of a minimum negative value of the vertical change of the ions vertical drift velocity as a necessary condition of formation of Es layer and determining ions convergence rate into this layer, is extended in case of the presence of vertical wind. Upward vertical wind can shift the convergence regions upward, while downward vertical wind shift them downward, unlike the cases of presence of only meridional and zonal winds. It also changes the ion convergence rate compared to the one with just a horizontal wind. It is shown for the first time that the upward constant wind also causes the convergence of ions with maximum rate in the region where the ion-neutral collision frequency is equal to their cyclotron frequency. While demonstrating the presented theory by numerical simulations, HWM14 data is used for the meridional and zonal wind velocity profiles and the presence of its vertical component is assumed. In this case, in addition to the estimated ion drift velocity and its vertical changes, their initial distribution and ambipolar diffusion also determine the development of ion convergence/divergence processes. For small magnitude of vertical wind velocity, its significant influence on the ions/electrons behavior is demonstrated, which shows the importance of both tidal wind and wind changes caused by the propagation of atmospheric gravity waves on the formation of the Es layer. In this theoretical research it is shown that the realistic profile of the wind velocity, which takes into account the vertical component along with its zonal and meridional ones, is important for prediction of the Es layers formation, as well as regions of ion depletion.

CD39 is involved in adenosine metabolism through conversion of extracellular ATP to adenosine. Because extracellular adenosine plays a critical role in the immune suppression of tumor microenvironment, the inhibition of CD39 activity by monoclonal antibodies (mAbs) is one of the important strategies for tumor therapy. In this study, we developed specific and sensitive mAbs for mouse CD39 (mCD39) using the Cell-Based Immunization and Screening (CBIS) method. The established anti-mCD39 mAbs, which were established by the CBIS method including C₃₉Mab-1 (rat IgG_2a, kappa) and C₃₉Mab-2 (rat IgG_2a, lambda), reacted with not only mCD39-overexpressed Chinese hamster ovary-K1 (CHO/mCD39) but also endogenously mCD39-expressed cell lines, such as L1210 (mouse lymphocytic leukemia) and J774-1 (mouse macrophage-like) cell lines through flow cytometry. Kinetic analyses using flow cytometry indicated that the dissociation constant (K_D) of C₃₉Mab-1 and C₃₉Mab-2 for CHO/mCD39 was 7.3 × 10⁻⁹ M and 5.5 × 10⁻⁹ M, respectively. K_D of C₃₉Mab-1 and C₃₉Mab-2 for L1210 was 3.3 × 10⁻⁹ M and 3.6 × 10⁻¹⁰ M, respectively. Furthermore, C₃₉Mab-1 could detect the lysate of CHO/mCD39 by western blot analysis. These results indicate that C₃₉Mab-1 and C₃₉Mab-2 are useful for the detection of mCD39 in many functional studies.

Benchmarks for general language understanding have been rapidly developing in recent years of NLP research, particularly because of their utility in choosing strong-performing models for practical downstream applications. While benchmarks have been proposed in the legal language domain, virtually no such benchmarks exist for privacy policies despite their increasing importance in modern digital life. This could be explained by privacy policies falling under the legal language domain, but we find evidence to the contrary that motivates a separate benchmark for privacy policies. Consequently, we propose PrivacyGLUE as the first comprehensive benchmark of relevant and high-quality privacy tasks for measuring general language understanding in the privacy language domain. Furthermore, we release performances from multiple transformer language models and perform model-pair agreement analysis to detect tasks where models benefited from domain specialization. Our findings show the importance of in-domain pretraining for privacy policies. We believe PrivacyGLUE can accelerate NLP research and improve general language understanding for humans and AI algorithms in the privacy language domain, thus supporting the adoption and acceptance rates of solutions based on it.

(1) Background: The CEECCA questionnaire assesses the ability to communicate among individuals with aphasia. It was designed using the NANDA-I and NOC standardised nursing languages (SNLs), reaching high content validity index and representativeness index values. The questionnaire was pilot-tested, demonstrating its feasibility for use by nurses in any healthcare setting. This study aims to identify the psychometric properties of this instrument. (2) Methods: 47 individuals with aphasia recruited from primary and specialist care facilities. The instrument was tested for construct validity and criterion validity, reliability, internal consistency, and responsiveness. The NANDA-I and NOC SNLs and the Boston test were used for criterion validity testing. (3) Results: 5 language dimensions explain 78.6% of the total variance. Convergent criterion validity tests showed concordances of up to 94% (Cohen’s κ: 0.9; p&lt;0.001) using the Boston test, concordances of up to 81% using DCs of NANDA-I diagnoses (Cohen’s κ: 0.6; p&lt;0.001), and concordances of up to 96% (Cohen’s κ: 0.9; p&lt;0.001) using NOC indicators. Internal consistency (Cronbach’s alpha) was 0.98. Reliability tests revealed test-retest concordances of 76%-100% (p&lt;0,001). (4) Conclusions: The CEECCA is an easy-to-use, valid, reliable instrument to assess the ability to communicate among individuals with aphasia.

Design for Manufacture and Assembly (DfMA) in architectural, engineering, and construction (AEC) industry is attracting the attention of designers, practitioners, and construction project stakeholders. Digital fabrication (Dfab) and design for additive manufacturing (DfAM) practices are found in current needs for further research and development. The DfMA's conceptual function is to maximize the process efficiency of Dfab and AM building projects. This work reviewed 171 relevant research articles over the past few decades. The concept of DfMA and the fundamentals of DfMA in building and construction were explored. In addition, DfMA procedures associated with Dfab and DfAM, as well as its AM assembly process, were discussed. Lastly, the current machine learning research on DfMA in construction was also highlighted. Large research gaps in the DfMA for Dfab and DfAM can be filled to increase operational efficiency and sustainable practices.

this article presents the results of implementing existing software tools in the accounting field. The teaching processes regarding the use of Learning and Knowledge Technologies (TAC) in the university environment, and very specifically, in what has to do with the pedagogical integration of the same in the curriculum is deficient and disjointed with the current technological development. Thus, in the different curricula of professional programs of Public Accounting and related, the courses related to computer automation processes are oriented only towards the management of computer science and accounting software and the great diversity of existing applications that would undoubtedly directly benefit the student to know the potential of these in their future accounting practice is not taken into account. Strengthen the various skills of a Public Accountant in training through Learning and Knowledge Technologies (TAC), under the hypothesis of developing skills in the accounting field through TACs. The research was developed using a quantitative approach, an empirical-analytical method, with a type of descriptive research under an experimental design based on G1 x O1 and G2–O2, three phases were defined. In the first phase, the characterization of the existing software tools in the accounting field was carried out. In the second phase, their relevance was determined. In the third phase, performance was evaluated and then classified in a repository. The data obtained were analyzed with parametric analysis techniques through which it was found that the difference in quantitative results in the academic process between the experimental and control groups was statistically significant, which concluded the success of the experimental treatment. The use of CT scans in the classroom by the experimental group resulted in an improvement in their academic performance compared to the control group, strengthening their self-learning processes and facilitating the development of cognitive functions and skills necessary in the exercise of their accounting profession. This research supports and strengthens the work skills developed in the classroom for public accounting students. The tools TAC is developed from the request made by the radiometry laboratory as a first phase and a second phase is necessary for validation with experts.

The study investigated determinants of open defecation among rural women in Ghana. The study extracted data from the female’s file of the 2003, 2008 and 2014 Ghana Demographic and Health Survey (GDHS). A total of 4,284 pooled sample size of rural women aged 15-49 with complete information about the variables analyzed in the study. The outcome variable was “open defecation” (i.e., defecating in an open space rather than a toilet facility) whilst fourteen (14) key explanatory variables were used. Two regression models were built, and output reported in odds ratio. Descriptively, 42 in every 100 women aged 15-49 practised open defecation (n=1811, 95’CI=49-52). Open defecation significantly correlated with educational attainment, wealth status, religion, access to mass media, partner's education, and zone of residence. The likelihood to practice open defecation reduced among those with formal education [aOR=0.69, CI=0.56-0.85], those whose partners had formal education [aOR=0.64, CI=0.52-0.80], women in the rich wealth quintile [aOR=0.12, CI=0.07-0.20], the traditionalist [aOR=0.33, CI=0.19-0.57], and those who had access to mass media [aOR=0.70, CI=0.57-0.85]. Residents in the Savannah zone were over 21-fold higher to defecate openly [aOR=21.06, CI=15.97-27.77]. The prevalence of open defecation is disproportionately pro-poor indicating that impoverished rural women are more likely to perform it.

To examine the association of sleep quality and work from home with physical inactivity (PI) in leisure time during Covid-19 pandemic. A population-based household survey was conducted in two Bra-zilian municipalities from October to December 2020. Leisure-time physical activity (PA) was self-reported, and individuals who practiced less than 150 minutes of moderate PA or 75 minutes of vigorous PA weekly were classified as PI. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). WFH was assessed by: "Currently, how is your work routine regarding location? Associations were investigated using logistic regression and directed acyclic graphs (DAG) for the multivariate models. A total of 1,750 adults were interviewed, 69.1% were PI and 51.9% had poor sleep quality. Furthermore, 79.8% were not in WFH. In multivariate analysis, leisure PI was associated with poor sleep quality (OR:1.59: 95% CI: 1.02-2.48), and not being in WFH (OR:1.62: 95% CI: 1.05-2.50). When performing the combined analysis between these two factors, and who were not in WFH were four times more likely to be PI at leisure (OR=4.22;95%CI:2.05-8.65). The results indicate a high prevalence of PI, with poor quality sleep and non-WFH associated with leisure PI. These combined factors exacer-bated the occurrence of PI.

This study demonstrates the possibility of growing green walls in normal commercial building environments with lighting designed primarily for aesthetic reasons, rather than the promotion of plant growth. Lighting is a key resource required for the growth and maintenance of robust green walls within interior environments. The study evaluated the appearance and growth of green walls with electric lighting used primarily for aesthetic reasons. Three identical green walls with six different plants were illuminated using three different white LED light sources for a period of five months. Plant health was monitored and documented in terms of growth patterns. One hundred and six subjects appraised the appearance of the walls using questionnaires. Findings of this study indicate that it is indeed possible to grow and maintain green walls in normal commercial building environments with lighting designed for aesthetic reasons. Further, it was observed that the selection of the correct plant species for the green walls is important to ensure plant health.

The density functional theory was used to explore the structural, electronic, dynamical, and thermoelectric properties of a VIrSi Half-Heulser (HH) alloy. The minimum lattice constant of 5.69 ( ̊A) was obtained for VIrSi alloy. Besides, the band structure and the projected density of states for this HH alloy were calculated, and the gap between the valence and conduction bands was noted to be 0.2 eV. Also, the quasi-harmonic approximation was used to predict the dynamical stability of the VIrSi HH alloy. At 300 K, the Seebeck Coefficient of 370 and -270 μV.K−1., respectively, was achieved for the p and n-type doping. From the power factor result, the highest peak of 18 X 1011W/cm.K2 is obtained in the n-type doping. The Figure of Merit (ZT) result revealed that VIrSi alloy possesses a high ZT at room temperature, which would make VIrSi alloy applicable for thermoelectric performance.

Background: The uptake of COVID-19 booster vaccines has been significantly low. Therefore, it is questionable whether combining the COVID-19 booster vaccines with Influenza vaccines can increase the population's interest in taking such vaccines and manage the health pandemic effectively. Methodology: In this systematic review and meta-analysis, a synthesis of the findings and summary of a total of 30 research articles based on the topic, ‘combining influenza and COVID-19 booster vaccination strategy’ was undertaken. The research articles were identified from three databases, namely, PubMed, Cochran Library, and Google Scholar using specific keywords and inclusion criteria. However, research articles that were not peer-reviewed and not published in English were excluded from the systematic review and meta-analysis. The average risk ratio of the included articles was 0.78% based on a 95% CI. On the other hand, the heterogeneity between such studies was I² = 35%, while the statistical significance of their findings occurred at p < 0.05. The average p-value of the included research studies was p = 0.62, implying that the null hypothesis was not rejected in almost all the studies. Results: A synthesis of the chosen research articles revealed that when influenza and COVID-19 booster vaccines are combined, there is potential for an increase in the uptake of the latter, mainly because many populations have already been accustomed to taking influenza vaccines on an annual basis. Conclusions: In this way, through such findings, medical health experts can make informed decisions to increase the population's willingness to receive the COVID-19 booster vaccines.

Intensive care nurses are highly prone to occupational stress and burnout, affecting their physical and mental health. The occurrence of the pandemic and related events increased nurses’ workload and exacerbated stress and burnout. We conducted a prospective longitudinal mixed-methods study with a cohort of nurses working in a medical ICU (COVID unit; n = 14) and cardiovascular ICU (non-COVID unit; n = 5). Each participant was followed for six 12-hour shifts. Validated questionnaires measured occupational stress and burnout prevalence. Wrist-worn wearable technologies recorded physiological indices of stress. Participants elaborated on the contributors to stress via post-study questionnaire. Data were analyzed using statistical and qualitative methods. Participants who cared for COVID patients at the COVID unit were 3.71 times more likely to experience stress (p &lt; .001) in comparison to non-COVID unit participants. No differences in stress levels were found when the same participants worked with COVID and non-COVID patients at different shifts at the COVID unit. The cohorts expressed similar contributors to stress including communication tasks, patient acuity, clinical procedures, admission processes, proning, labs, and assisting coworkers. Nurses in COVID units, irrespective of whether they care for a COVID patient, may experience high occupational stress and burnout.

Global warming has been increasing heat stress threat in animals which can be monitored by Temperature Humidity Index (THI). The present study describes the relationship of THI, calculated using 35 years period weather station data, and production performances of dairy cattle in a se-lected area of Bangladesh. The month January and June were identified as the coolest and hottest, respectively. Based on this outcome, every year in the month of January and June production performances of 10 crossbred cows with homogenous characteristics were monitored for a period of 5 years. The average THIMEAN value was found 17% higher in June as compared to January, and with this increment of THIMEAN average milk production was decreased 24.4% (p<0.05). The milk fat and protein content were also reduced (p<0.05) by 14.5 and 15.2%, respectively suggesting negative correlation as like as milk production. However, ash content was increased 15.3% that indicates a positive correlation. In addition, multiple regression analysis revealed each point increase in THIMEAN and rectal temperature, there was a decrease in milk yield 0.04 and 1.17 kg ECM, respectively. In contrary, each point increase in THIMEAN resulted 0.059 C increase of rectal temperature. Taken together, THIMEAN value calculated using metrological station data has distinct relationship with the production performances of lactating crossbred dairy cows.

Objective: The aim of the study was to characterize varieties of Moringa alfileria honey (unfloral and polyfloral) from Saudi Arabia based on antibacterial, antioxidant activities, physicochemical, melissopalynological analysis, total phenolic and flavonoid contents. Material and Methods: The fresh 376 honey samples (3 kg of each) were kindly provided by Alnahal aljwal Company, 2021 flowering season. The honey samples collected in sterile universal glass containers and kept at 2– 8°C until tested. Antibacterial, antioxidant activities and physiochemical analysis were done. Determination of sediment content, total grains, moisture content, water-soluble solids, acidity, electrical conductivity, total sugars content, inverted sugars, glucose (g/100 g), fructose (g/100 g), total glucose + fructose, fructose/ glucose ratio, sucrose (g/100 g), diastase enzyme activity and HMF were calculated. As well as total phenolic and flavonoid contents Results: Antibacterial activity and physiochemical analysis of honey samples w varied. All parameters studied were significantly different (P < 0.05) among all honey varieties. The results of the physiochemical analysis were compared with Saudi National Standard, Codex standard, as well as published data in the literature. Conclusion: It was obvious that the honey quality was varied based on the botanical origins

Hyperaccumulator plant species growing on metal-rich soils can accumulate high quantity of metals and metalloids in aerial tissues and several proteomic studies on the molecular mechanisms at the basis of metals resistance and hyperaccumulation have been published. Hyperaccumulator are also at the basis of phytoremediation strategy to remove more efficiently metals from polluted soils or water. Arabidopsis halleri and Noccea caerulescens are both hyperaccumulators of metals and nano-metals. In this study it was assessed the change in some proteins in A. halleri and N. caer-ulescens after the growth in soil with cadmium and zinc, provided as sulphate salts (CdSO4 and ZnSO4) or sulfide quantum dots (CdS QDs and ZnS QDs). The protein extracts obtained from plants after 30 days of growth were analyzed by 2D-gel electrophoresis (2D SDS-PAGE) and identified by MALDI-TOF/TOF mass spectrometry. A bioinformatics analysis was carried out on quantitative protein differences between control and treated plants. In total, 43 proteins resulted significatively modulated in A. halleri, while 61 resulted modulated in N. caerulescens. Though these two plants are hyperaccumulator of both metals and nano-metals, at protein levels the mechanisms involved do not proceed in the same way but at the end bring to a similar physiological result.

Field observations of external wounds associated with two common tree injection methods compared open (plug-less) and sealed (plug) systems in green ash (Fraxinus pennsylvanica Marshall) trees . A wound from any cause within 1.37 meters above the ground was common with 28.8% of all trees. The open system had statistically fewer (p&lt;0.001) trees with at least one wound (11.6% of trees) than the sealed system (47.4% of trees). The open system had fewer (P&lt;0.001) wounds (0.17, 0.04 SE) per tree and a smaller (P&lt;0.001) total wound area (25.5 cm2, 8.7 SE) per tree, compared to the sealed system wounds (1.14, 0.13 SE) per tree and the total wound area (99.7 cm2, 16.2 SE) per tree. The incidence of a tree with a wound(s) within 1.37 m above the ground was 7.2 times more likely with trees treated though the sealed system. Wounds in the sealed system were observed to appear to have a high rate of improper application of plugs, which was associated in 77% of the cases to explain the wounds. Implications of study results are further provided to best protect ash trees, while at the same time reducing the incidence external wounding on ash trees.

It is well established the complex exponential and logarithm are multivalued functions, both failing to maintain most identities originally valid over the positive integers domain. Moreover the general case of complex logarithm, with a complex base, is hardly mentionned in mathematic litterature. We study the exponentiation and logarithm as binary operations where all operands are complex. In a redefined complex number system using an extension of the C field, hereafter named E, we prove both operations always produce single value results and maintain the validity of identities such as log_u (w v) = log_u (w) + log_u (v) where u, v, w in E. There is a cost as some algebraic properties of the addition and subtraction will be diminished, though remaining valid to a certain extent. In order to handle formulas in a C and E dual number system, we introduce the notion of set precision and set truncation. We show complex numbers as defined in C are insufficiently precise to grasp all subtleties of some complex operations, as a result multivaluation, identity failures and, in specific cases, wrong results are obtained when computing exclusively in C. A geometric representation of the new complex number system is proposed, in which the complex plane appears as an orthogonal projection, and where the complex logarithm and exponentiation can be simply represented. Finally we attempt an algebraic formalization of E.

Spatial approach based on the deformation measurement of volcanic dome and crater rim is key to evaluate the activity of a volcano, such as Merapi volcano where associated disaster risk is regularly taking lives. Within this framework, this study aime to detect localized deformation and change in the summit area that has occurred concomitantly with the dome growth and explosion reported. The methodology was focused on two sets of data, one LiDAR-based dataset of 2012 and one UAV-dataset of 2014. The results show that during the period 2012-2014, the crater walls are 100 m to 120 m high above the crater floor at its maximum (North to East-South-East sector), while the West and North sector presents a topographic range of 40 to 80 m. During the period 2012 – 2014, the evolution of the crater rim around the dome is generally stable (no large collapse). The opening of a new vent on the surface of the dome has displaced an equivalent volume of 2.04 E+04 m3 corresponding to a maximum -9 m (+/- 0.9 m) vertically. This concludes that during the period 2012 – 2014 when the dome of Merapi experienced phreatic or phreatomagmatic explosions, the topography around the dome rose. This rise does not seem to be related to large wall collapses, and it is likely that modification in the subsurface have triggered those changes.

In northern Thailand, the problem of small particulate matter happens every year, with the pri-mary source being agricultural weed burning and wildfire. The tourism industry is strongly impacted and has been the spotlight for the past few years. Thus, the study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data was collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data was analyzed using data mining and association rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially the number of customers has decreased. Operational factors and prod-uct/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

Research background – Learning and growth is one of the essential tools that companies ought to use in today's market economy in order to ensure their sustainable development in the long-term and, consequently, to achieve their maximum market value.Purpose – This article is predominantly of theoretical nature and considers the possibility of using the applied strategic analysis technique that was developed by the author to analyze learning and growth in the course of a study of strategic aspects of learning growth. The technique is based on the balanced scorecard system of the same name. Design/methodology/approach – Methodologically, the study is based on Kaplan and Norton's balanced scorecard concept and the author's concept of applied strategic analysis. Findings – It is shown that applied strategic analysis of learning and growth envisages comparative evaluation, diagnostics of deviations and predictions of the values of the balanced scorecard metrics of learning and growth in the dimension of strategic objectives. It includes analysis of the level of motivation in employees, the volume of authroity delegation and whether their personal goals match company goals; analysis of the expansion capacity of information systems, and analysis of the quality of retraining and the creativity level of employees. The applied strategic analysis of learning and growth with comparative evaluation of the metrics of the level of motivation in employees, the volume of delegation to them and of the match between their personal and corporate goals, and concludes with a prediction of the values of factor measures of the quality of retraining and creativity development in employees.Originality/value – The author comes to a conclusion that applied strategic analysis of learning and growth is a new and sufficiently effective instrucment for studying the strategic aspects of companies' performance that is associated with the training and development of their personnel. The instrument provides analytical support to strategic management as regards personnel training and development in today's conditions. Its results might be useful when working out managerial decisions for the company's short-term, medium-term and long-term plans in the area of learning and growth.

The full impact of COVID-19 on policing, crime and disorder is slowly being fully unraveled. However, there remains a number of areas of policing that are yet to be examined in detail. Two of these areas include the impact on the intrinsically linked, volume of police recorded intelligence reports, and the use of stop and search. In this study we examine them symbiotically and frame them in the context of the intelligence led policing model, in particular in an effort to understand how national lockdowns in the United Kingdom affected both proactive policing approaches and the underpinning intelligence cycle. To achieve this, we use data from freedom of information requests regarding the annual levels of recorded police intelligence over a 10-year period for 20 police services. To supplement this, we examine overall national monthly volumes of stop and search activity over a 5-year period. Finally, we then use a case study approach of 3 police services to further explore changes in the conduct of stop and search such as the officer defined ethnicity, grounds for search and disposal outcomes. The findings indicate that both recorded intelligence reports and stop and search increased dramatically during periods of lockdown, despite widespread decreases in crime and social mobility. Changes in proportional impact are identified for White and Black citizens, searches for controlled drugs and the no further action disposal, but these are not consistent across police services. Potential causes and implications are then discussed and again, framed within the context of the impact on the intelligence led policing model and wider policing environment.

Raman Spectroscopy has long been anticipated to augment clinical decision making, such as classifying oncological samples. Unfortunately, the complexity of Raman data has thus far inhibited its routine use in clinical settings. Traditional machine learning models have been used to help exploit this information, but recent advances in deep learning have the potential to improve the field. However, there are a number of potential pitfalls with both traditional and deep learning models. We conduct a literature review to ascertain the recent machine learning methods used to classify cancers using Raman spectral data. We find that while deep learning models are popular, and ostensibly outperform traditional learning models, there are many methodological considerations which may be leading to an over-estimation of performance: primarily, small sample sizes which compound upon sub-optimal choices regarding sampling and validation strategies. Amongst several recommendations is a call to collate large benchmark Raman datasets, similar to those that have helped transform digital pathology, which researchers can use to develop and refine deep learning models.

The supramolecular aggregation processes occurring on metallic (aluminum and gold) surfaces in aqueous solutions of bovine serum albumin (BSA) during drying were studied using advanced scanning electron microscopy (SEM). The possible mechanism for the formation of amazing intricate fractal structures on metallic surfaces was proposed based on the analysis of SEM images, size distribution diagrams and EDX-scanning elements distribution maps.

Stage of cancer is a discrete ordinal response that indicates aggressiveness of disease and is often used by physicians to determine the type and intensity of treatment to be administered. For example, the FIGO stage in cervical cancer is based on the size and depth of the tumor as well as the level of spread. It may be of clinical relevance to identify molecular features from high-throughput genomic assays that are associated with stage of cervical cancer, to elucidate pathways related to tumor aggressiveness, identify improved molecular features that may be useful for staging, and identify therapeutic targets. High-throughput RNA-Seq data and corresponding clinical data (including stage) for cervical cancer patients has been made available through The Cancer Genome Atlas Project (TCGA). We recently described penalized Bayesian ordinal response models that can be used for variable selection for over-parameterized datasets such as the TCGA-CESC dataset. Herein, we describe our ordinalbayes R package, available from the Comprehensive R Archive Network (CRAN), which is capable of fitting cumulative logit models when the outcome is ordinal and the number of predictors exceeds the sample size, P>N, such as for TCGA data. We demonstrate use of this package through application to TCGA cervical cancer dataset. Our ordinalbayes package can be used to fit models to high-dimensional dataset and effectively performs variable selection.

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

Cholera is a severe diarrheal disease caused by Vibrio cholerae, a natural inhabitant of brackish water. Effective control of cholera outbreaks depends on prompt detection of the pathogen from clinical specimens and tracking its source in the environment. Although the epidemiology of chol-era is well studied, rapid detection of V. cholerae remains a challenge, and data on its abundance in environmental sources are limited. Here, we describe a sensitive molecular quantification as-say by qPCR, which can be used on-site in low resource settings directly on water without the need for DNA extraction. This newly optimized method exhibited 100% specificity for total V. cholerae as well as V. cholerae O1 and allowed detection of as few as three target genome copies per reaction. The limit of detection is as low as 5 × 10E3 genome copies/L of water after concentrat-ing biomass from the sample. The ability to perform qPCR directly on water samples, portable features of the equipment, stability of the reagents at 4°C and user-friendly online software facili-tate fast quantitative analysis of V. cholerae. These characteristics make this assay extremely use-ful for field research in resource-poor settings and could support continuous monitoring in cholera endemic areas.

A very strong earthquake of magnitude Mw8.2 struck the coastal zone of Alaska (USA), on July 29, 2021. This earthquake was felt around the Gulf of Alaska, on a wide offshore area belonging to USA and Canada. In order to identify an anomalous geomagnetic signal before the onset of this earthquake, we retrospectively analyzed the data collected on the interval June 17 - July 31, 2021, via internet (www.intermagnet.org), at the two geomagnetic observatories, College (CMO) - Alaska and Newport (NEW)-USA, by using the polarization parameter (BPOL) and the strain effect–related to geomagnetic signal identification. Thus, for the both observation sites (CMO and NEW), the daily mean distribution of the BPOL and its standard deviation (STDEV) are carried out using an FFT band-pass filtering in the ULF range (0.001-0.0083Hz). Further on, a statistical analysis based on a standardized random variable equation was applied to emphasize the following: a) the anomalous signature related to Mw8.2 earthquake on the both time series BPOL*(CMO) and BPOL*(NEW); b) the differentiation of the transient local anomalies associated with Mw8.2 earthquake from the internal and external parts of the geomagnetic field, taking the NEW observatory as reference. Finally, on the BPOL*(NEW-CMO) time series, carried out on the interval 07-31 July, 2021, a very clear anomaly of maximum, greater than 1.2 STDEV, was detected on July 22, with 7 days before the onset of Mw8.2 earthquake

I wish to suggest a physiological function for alpha-synuclein (a-syn) that has the potential to explain its role in pathology. Intraneuronal proteinaceous Lewy Bodies (LBs), the pathological hallmark of Parkinson’s disease and other synucleinopathies, consist majorly of a-syn. Ample evidence suggests that LBs are not the result of simple amyloidosis of cytosolic a-syn. Benign soluble unstructured a-syn gets converted into toxic species which preferentially accumulates in LBs. But how these aberrant a-syn molecules are produced in the cytosol, is still not clear. The present hypothesis is an effort to relate a metabolic reaction specific to neuronal function, that is, phase transition, with the pathobiology of a-syn. During high frequency stimulation, which entails rapid phase transition reactions at the presynaptic compartment, aberrant interaction of a-syn with the membrane occasionally generates toxic a-syn molecules. My conjecture is that the physiological function of a-syn is to modulate membrane fluidity by a process wherein it goes through a conformation cycle driven by a flux of energy from mitochondria. It is the range of toxic a-syn produced during aberrant phase transition reaction that is responsible for pathology, not the normal a-syn that reenters the conformation cycle, thereby, resolving the paradox of the Janus-face of a-syn.

The tryptophan catabolite (TRYCAT) pathway is implicated in the pathophysiology of schizophrenia (SCZ) since the rate-limiting enzyme indoleamine-dioxygenase (IDO) may be induced by inflammatory and oxidative stress mediators. This systematic review searched PubMed, Web of Science, and Google Scholar for papers published from inception until August 2021 and meta-analyzed the association between SCZ and TRYCATs in the central nervous system (CNS) and peripheral blood. We included 61 studies comprising 2813 patients and 2948 healthy controls. In the CNS we found a significant (p<0.001) increase in the kynurenine/tryptophan (KYN/TRP) (standardized mean difference, SMD=0.769, 95% confidence interval, CI: 0.456; 1.082) and kynurenic acid (KA)/KYN+TRP (SMD=0.697, CI:0.478-0.917) ratios, KA (SMD=0.646, CI: 0.422; 0.909) and KYN (SMD=1.238; CI: 0.590; 1.886), while the 3OH-kynurenine (3HK) + KYN-3-monooxygenase (KMO)/KYN ratio was significantly reduced (SMD=-1.089, CI: -1.682; -0.496). There were significant differences between KYN/TRP, (KYN+KA)/TRP, (3HK+KMO)/KYN, KA, and KYN levels among the CNS and peripheral blood, and among serum and plasma KYN. The only useful peripheral marker of CNS TRYCATs findings was the increased KYN/TRP ratio in serum (SMD=0.211, CI: 0.056; 0.366, p=0.007), but not in plasma. There was no significant increase in a neurotoxic composite score based on KYN, 3HK, and picolinic, xanthurenic, and quinolinic acid. SCZ is accompanied by increased IDO activity in the CNS and serum, and reduced KMO activity and a shift towards KA production in the CNS. This CNS TRYCATs profile indicates neuroprotective, negative immunoregulatory and anti-inflammatory effects. Peripheral blood levels of TRYCATs are dissociated from CNS findings except for a modest increase in serum IDO activity.

Abstract: Plant types and soil bacterial communities had a close relationship, understanding the profound association between them contributes to better learn bacterial ecological function for plant growth. In this study, rhizosphere soil of six different chemotype Cinnamomum camphora trees were collected, including C. bodinieri var. citralifera, [C. camphora (Linn.) Presl], camphora-type, cineole-type, linalool-type and isoborneol-type. Soil properties content and bacterial communities were analyzed. Two chemotype C. camphora, including [C. camphora (Linn.) Presl] and linalool-type, shaped similar bacterial community structure, decreased Firmcutes relative abundance. richness estimators (Chao1 index and Ace index) of [C. camphora (Linn.) Presl] were decreased compared with the others. Furthermore, soil bacterial community structure was also similar among bodinieri var. citralifera, camphora-type, cineole-type and isoborneol-type. Hence, different chemotype C. camphora altered soil nutrient and shaped rhizosphere bacterial communities.

The world of science is drowned in a wealth of information. How to make sense of this wealth of published articles, blog posts and abstracts has become an important challenge given the importance of science to different aspects of societal function. At the crux of the issue lies the increasing trend where scientific discovery informs decision making at the societal level. One example, is the elucidation of the ozone hole to the promulgation of the Montreal Protocol in 1987, and documenting increasing atmospheric carbon dioxide concentration led to climate action and signing of the Paris Agreement in 2015. Hence, understanding a research field becomes an important need for many decision makers across different sectors of society. But, the scientific literature is cryptic and esoteric, and presents a significant barrier to comprehension. One approach to ameliorate the problem is statistical machine reading, which provides the critical capability of identifying key concepts that underpins a research field. Such important concepts help provide an incision point to gain further understanding of the field and initiating further conversation about the field. This work sought to validate the concept of whether applying statistical machine reading to a body of literature comprising short blog posts and abstracts of published articles help in understanding the field of metabolic engineering. One important angle pursued in this research is whether the tabulated list of terms and phrases identified by statistical machine reading could be creatively analyzed to gain a deeper understanding of the research field. For example, the most frequently occurring terms and phrases could describe key concepts of the research field. Moving down in frequency occurrence would be terms and phrases that describe methodologies and approaches of the field. Finally, less frequently occurring terms and phrases may be tools and resources used in the research field. Results validated the utility of statistical machine reading in identifying important terms and phrases associated with the research field. But the small dataset of blog posts and abstracts used in this study severely hampered the identification of most of the key concepts of metabolic engineering, which is a fairly broad field of research. Overall, statistical machine reading shows utility in identifying terms and phrases that could describe a field. However, the level of understanding is closely tied in to the breadth and depth of reading material available, which meant that the methodology is data intensive in nature. Future use of supercomputing or quantum computing could help alleviate constraints of computational capacity, and help tackle the exponential rise in computational complexity as the size of the reading material for machine reading expands.

The study evaluated the association between nutrient patterns and body fat and regional adiposity in middle-aged black South African (SA) men and women and determined if this differed by sex. Body fat and regional adiposity (dual-energy x-ray absorptiometry), and dietary intake (7-day quantified food frequency questionnaire) were measured in black SA men (n=414) and women (n=346). Using principal component analysis, nutrient patterns were computed from 25 nutrients in the combined sample. Four nutrient patterns were extracted, explaining 67% of the variance in nutrient intake. Animal and fat, as well as the vitamin C, sugar and potassium driven patterns, were positively associated with total adiposity. In contrast, the retinol and vitamin B12 pattern was associated with the centralisation of fat. Notably, the strength of the association between the animal-driven nutrient pattern and BMI was greater in men (1.14 kg/m2, 95%CI (0.63-1.66)) than women (0.81 kg/m2, 95%CI (0.25-1.36)) (Pint=0.017). In contrast, the plant driven pattern was associated with higher abdominal subcutaneous adipose tissue (SAT) in women (44 cm2, 95%CI (22-67)) but not men (Pint =1.54 x 10-4). These interactions suggest that although men and women have similar nutrient patterns, the associations with the whole body and regional body fat are different.

Background: The cumulative number of patients during the COVID-19 pandemic led to a significant shortage of hospital beds. Many patients may not require hospitalization and can be clinically observed in home settings. However, some psychosocial factors are correlated with unsuccessful home isolation (HI), which might negatively affect the transmission control in the community. Therefore, we developed a new psychosocial screening tool (CCPHIET) for assessing HI suitability and examined its validity and reliability.Methods: This cross-sectional descriptive study included COVID-19 patients who were deemed to be medically safe for 14 days of HI. The CCPHIET is comprised of 8 clinical domains pertinent to HI behavioral compliance and risk. We explored its statistical validity and reliability and discussed the potential utility of this tool. Results: A total of 65 COVID-19 patients participated in this study. Most patients (58.5%) were evaluated as good candidates for HI. The CCPHIET has an acceptable content validity (IOC index > 0.5), moderate internal consistency (Cronbach’s alpha = 0.611) and substantial to excellent inter-rater reliability (Intraclass correlation coefficient = 0.944, Cohen’s kappa= 0.627).Conclusions: To compromise between strict and costly absolute institutional quarantine and the potentially unsuccessful absolute HI, the CCPHIET may help to identify good candidates for HI in mild and asymptomatic COVID-19 patients. This psychosocial information would support the physicians in matching each patient to the most suitable setting. Therefore, safe medical care is provided, unnecessary use of medical resources is spared, and local transmission is contained.

The adoption of health information technology (HIT) has increased considerably, contributing to better communication between physicians and patients and providing technological bases for learning and institutional improvement. This type of technology brings many challenges; therefore, understanding its adoption and assimilation is important to assess its potential for engendering desirable outcomes in health management. The assimilation of health information systems should be highlighted as their importance in health organisations is now recognised as a key facilitator assisting in providing better health outcomes. Thus, this study aimed to analyse HIT adoption based on models such as Technology, Organisation and Environment (TOE), which analyses at the organisational level, with other models, such as the Technology Acceptance Model (TAM), which analyses at the individual level, and the assimilation of the adopted technologies.

Business processes are continuously evolving in order to adapt to changes due to various factors. One important process drift perspective yet to be investigated is the detection of branching condition changes in the process model. None of the existing process drift detection methods focus on detecting changes of branching conditions in process models. Existing branching condition detection methods do not take changes within the process into account, hence results are inadequate to represent the changes of decision criteria of the process. In this paper, we present a method which can detect branching condition changes in process models. The method takes both process models and event logs as input, and translates event logs into decision sequences for change points detection. The proposed method is evaluated by simulated event logs.

The screening and treatment of acid mine drainage (AMD) using Na₂FeO₄ has been explored. Elemental composition was performed using an ICP-OES for the raw and treated AMD. The AMD samples were collected from three different sampling sites (RTW1, RTW2 and RTW3) in Pretoria, South Africa with acidic pH ranging between 2.50 and 3.13. Total dissolved solids and Electrical Conductivity of AMD samples ranged between 960 and > 1000 mg. L^-1, 226 and 263 µS. cm^-1, respectively. The final pH of treated water samples increased up to ≥ 9.5 after treatment with Na₂FeO₄. Sodium ferrate showed dual functions by removing metals and raising the pH of the treated water. Concentrations of most trace elements were not complying with WHO and DWAF guideline standards in raw AMD while after treatment with Na₂FeO₄ the concentrations were below guidelines for domestic and irrigation purposes.

Over the years, Artificial Intelligence (AI) has seen a steady progress in development and evolution that can aid many sectors. Today, AI plays an essential role in the Fourth Industrial Revolution, and it is making its way into the military sector as well. Many countries are actively looking into AI military technology. Some of these innovations include image recognition, text analysis, Self-driving vehicles (SDV), gaming, robotic process automation (RPA) & Robotic and Autonomous Systems (RAS), and Autonomous Weapons Systems (AWS). In this research, we discuss the advantages of each innovation mentioned and analyze the many different cybersecurity threats that awaken due to military artificial intelligence systems. We then discuss the open research areas to better improve the current state of military artificial intelligence applications in terms of ethics, system security, proper strategy plan, accepted responsibility matrix, and introduction of relevant laws.

This study investigated the influence of land-use and precipitation change and variability on Lake Victoria’s water-level fluctuations. Extreme precipitation events, corresponding to extreme water-levels, over the lake and its catchment area were identified and their return periods estimated by fitting them into a generalized extreme value (GEV) distribution. Using general circulation models from the 6^th phase of the Coupled Model Intercomparison Project (CMIP6)’s Detection & Attribution Model Intercomparison Project (DAMIP), an assessment of the potential contribution of human-induced climate change on the observed precipitation patterns over the study area was done. The greatest precipitation anomalies for the period 1900-2020 were recorded in 1961’s October-December (OND) season and 2019’s June-August (JJA) and OND seasons, corresponding to the period when the highest water-levels were recorded in Lake Victoria. While land-use change in the study domain was observed, extended and unusually heavy June to December 2019 precipitation bore the greatest responsibility for the 2019/2020 high water-levels in Lake Victoria. The OND precipitation event of 2019 was a 1-in-52-year event compared to the 1961’s 1-in-693 years. Differences in return periods at various parts of the lake imply a high spatial climate variability within the lake itself. An analysis of the fraction of attributable risk (FAR) showed natural variability to have a greater influence on the JJA and OND precipitation patterns over Lake Victoria than human-induced climate change. However, variability over the land area of the study domain was mainly driven by human-induced climate change rather than natural variability, implying a unique climate system over Lake Victoria. Findings from the current study enhance the understanding of Lake Victoria’s water budget and motivate for further research to inform effective strategies on the planning and use of Lake Victoria’s water resources in a changing climate.

The spreading global sea turtle fibropapillomatosis (FP) epizootic is threatening some of Earth’s ancient reptiles, adding to the plethora of threats faced by these keystone species. Understanding this neoplastic disease, and its likely aetiological pathogen, chelonid alphaherpesvirus 5 (ChHV5), is crucial to understand how the disease impacts sea turtle populations and species and the future trajectory of disease incidence. We generated 20 ChHV5 genomes, from three sea turtle species, to better understand the viral variant diversity and gene evolution of this oncogenic virus. We revealed previously underappreciated genetic diversity within this virus (with an average of 2,035 single nucleotide polymorphisms [SNPs], 1.54% of the ChHV5 genome) and identified genes under the strongest evolutionary pressure. Furthermore, we investigated the phylogeny of ChHV5 at both genome and gene level, confirming the propensity of the virus to be interspecific with related variants able to infect multiple sea turtle species. Finally, we revealed unexpected intra-host diversity, with up to 0.15% of the viral genome varying between ChHV5 genomes isolated from different tumours concurrently arising within the same individual. These findings offer important insights into ChHV5 biology and provide genomic resources for this oncogenic virus.

The education system has become even more complex following the global pandemic, which saw face-to-face teaching transition to virtual teaching. To cope with this abrupt transition, it is essential that teachers had a sufficient level of digital teaching competence. This article aims to increase awareness of teachers' self-perception of their digital teaching competences in the educational field. Specifically, this study explores Spanish secondary school teachers’ knowledge and use of different ICT tools by evaluating their competence based on different areas proposed by The National Institute of Technology and Professional Development (Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado, INTEF), Madrid, Spain. From the results of the questionnaires, we have determined that teachers consider themselves to have an upper intermediate level of digital teaching competence, although there are still shortcomings that need to be addressed in order to improve this level of competence, and its true integration in the teaching–learning process.

Health and wellness tourism should be particularly valued in the post-pandemic phase, as a stra-tegic product to enhance the population's well-being and quality of life indicators, at social, phys-ical, and environmental dimensions, with different proposals for specialized experiences that complement the destination's offer, positioning regions as health and wellness destinations. Thermal tourism should be encouraged, as a specific product, due to the innovation and diversi-fication observed in the services made available and the benefits recognized at different age levels of tourists and destinations communities. Considering the relevance of thermal springs and thermal tourists for tourism destinations image, positioning, and development, this research aims to identify the specific motivations of tourists to the practice of thermal tourism, to understand how the benefits that thermal tourists search for, and their sociodemographic profile influence the motivations, and how the motivations determine the travel characteristics. This research was de-veloped on the North and Centre of Portugal, for their relevance in the context of thermal springs and related tourism activities. To achieve the research objectives, a questionnaire survey was ap-plied to thermal tourists, through a non-probability by convenience sampling, using bivariate tests, such as Pearson’s chi-squared test, one-way ANOVA, and t-student. The results highlight that most respondents practiced thermal tourism due to leisure and relaxation benefits, such as the escape from daily stress, spend time with family, and being "pampered"; relaxation is the most valued motivation, followed by the search for psychological and physical wellbeing. The research found relations between the benefits expected by thermal tourists, and their travel characteristics such as the composition of the group, the general travel motivation, the thermal destination cho-sen, and the number of nights spent. In thermal tourism, new challenges emerge, demanding the development of strategies, products, and services responding to the needs of specific market segments.