A bacterium known as Akkermansia muciniphila (AkkermansiaA. muciniphila) was detected in human feces in 2004. It is defined as a gram-negative, anaerobic, and mucin-degrading microbe belonging to the Verrucomicrobia species. Although the majority of A. muciniphila is found in the human intestinal tract playing a role in the gut microbiome, there are also smaller levels detected in breast milk and oral cavities as well as in the pancreas and appendix.Evidence suggests that having A. muciniphila present in the gut microbiome has positive effects on human health. As a result, A. muciniphila has been shown to have health benefits when taken as a dietary supplementation where it is considered a promising next-generation probiotic. However, the large-scale production of A. muciniphila remains a challenge due to its need for a stable environment. While culturing A. muciniphila in a mucin-based medium is one option, other strategies that use plate-based mediums have also been explored. Currently, both live and pasteurized forms of A. muciniphila are available on the market and shown to have promising outcomes in animal models. Additionally, researchers are investigating various prebiotics to increase the abundance of A. muciniphila in the human gut. This article presents a detailed summary of the phenotypic characteristics of A. muciniphila and its associations with various human health condition illnesses. Finally, the paper explores A. muciniphila's potential as an effective next-generation probiotic.

One of the main problems is handling rainwater management in urban areas is water quality from urban run-off. Currently, the emphasis is on using rainwater in cities as much as possible. The concentration of pollutants is the most problematic in rainwater. After precipitation falls on surfaces, surface water is immediately contaminated. This pollution must be cleaned or contained and transported to a wastewater treatment plant through the sewer network. Among the primary pollutants that we can identify in surface water are, for example, heavy metals. In our research, we focus on the analysis of real surface waters taken from 13 lo-cations on the territory of the Slovak Republic. The result of the research is an analysis of the suitability of reusing these waters. From the results of the analyses, it is clear that not a single sample is suitable for irrigation, as the limits of at least one monitored parameter were exceeded in all samples. The monitored lead concentration parameter was exceeded in all monitored samples.

The worldwide prevalence of type 2 diabetes (T2D) and prediabetes is rapidly increasing, particularly in children, adolescents, and young adults. Oxidative stress (OxS) has emerged as a likely initiating factor in T2D. The role of natural antioxidant products in combating T2D is best evaluated in the context of the complex physiological processes that modulate T2D-OxS such as glycemic control and exercise. The role of natural antioxidant compounds such as vitamin E in T2D must likewise be considered beyond their roles as inhibitors of OxS. In addition to antioxidant properties, vitamin E vitamers (tocopherols and tocotrienols) also exhibit distinct abilities to regulate cellular signal transduction pathways important to T2D progression. Most research on the role of vitamin E in T2D or prediabetes has been limited to tocopherols (Ts) but emerging trials with tocotrienols (T3s) show promise. Minimizing factors that induce chronic damaging OxS and maximizing natural antioxidant protective factors may provide a means of preventing or slowing T2D progression. This “optimal redox” (OptRedox) approach also provides a framework in which to discuss the potential benefits of natural antioxidant factors such as antioxidant products. Since early, effective intervention is critical, the OptRedox strategy would be optimally effective if implemented in the pediatric population.

Biofilms are congregations of bacteria on a surface, and they grow into obstacles for the functionalities of any device or machinery involves anything biological. Biofilms are developed through a biochemical system known as ‘Quorum Sensing’ that accounts for the chemical signaling that direct either biofilm formation or inhibition. Computational models that relate chemical and structural features of compounds to their performance properties have been used to aide in the discovery of active small molecules for many decades. These quantitative structure-activity relationship (QSAR) models are also important for predicting the activity of molecules that can have a range of effectiveness in biological systems. This study uses QSAR methodologies combined with and different machine learning algorithms to predict and assess the performance of several different compounds acting in Quorum Sensing. Through computational probing of the quorum sensing molecular interaction, new design rules can be elucidated for countering biofilms.

Observer-based control is the most commonly used method in the control of electro-hydraulic servo system (EHSS) with uncertainties, but it suffers from the drawback of low accuracy under the influence of large external load forces and disturbances. To address this problem, this paper proposes a novel compensation function observer-based backstepping sliding mode control (BSMC) approach to achieve high-accuracy tracking control. In particular, the model uncertainties, including nonlinearities, parameter perturbations and external disturbances are analyzed and treated together as a lumped disturbance. Then, a fourth-order compensation function observer (CFO) is constructed, which fully utilizes the system state information to accurately estimate the lumped disturbance. On this basis, the estimate of the lumped disturbance is incorporated into the design of an backstepping sliding mode controller, allowing the control system to compensate for the disturbance effect. The stability of the closed-loop control system under the CFO and BSMC is rigorously proven through the use of Lyapunov theory, which guarantees that all the tracking error signals converge exponentially to the origin. Comparative simulations are carried out to show the effectiveness and efficiency of the proposed approach, i.e., compared with PID and ESO-based BSMC methods, the tracking accuracy is improved by 99.93% and 99.76%, respectively.

Ensuring precise electric locomotive stopping is pivotal for achieving intelligent and unmanned auxiliary transportation systems. Currently, human drivers' expertise plays a central role in the stopping process, posing challenges for automation and cargo location accuracy, particularly in coal mining. This paper focuses on achieving accurate electric locomotive stopping under diverse conditions by utilizing permanent magnet synchronous motor-driven locomotives. This technique introduces a novel stopping control method that combines a fuzzy Proportional-Integral-Derivative (F-PID) controller and a vector control model for permanent magnet synchronous motors (PMSM). After this, we design the F-PID using the PMSM technique based on the new fuzzy rules for each sub-system. In the end, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed, which demonstrate the effectiveness of the proposed control method. From the simulation results, it confirming that the ability to achieve precise stopping under various working conditions.

Lignin fibers typically influence the mixture performance of stone matrix asphalt (SMA), such as strength, stability, durability, noise level, rutting resistance, fatigue life, and water sensitivity. However, limited studies were conducted to analyze the influence of fibers on the percent voids in mineral aggregate in bituminous mixture (VMA) during the mixture design. This study analyzed the effect of different fibers and fiber contents on the VMA in SMA mixture design. A surface-dry condition method test and Marshall Stability test were applied on the SMA mixture with four different fibers (i.e., flocculent lignin fiber, mineral fiber, polyester fiber, blended fiber). The test results indicated that the bulk specific gravity of SMA mixtures and asphalt saturation decreased with the increasing fiber content, whilst the percent air voids in bituminous mixtures (VV), Marshall Stability and VMA increased. Mineral fiber had the most obvious impact on the bulk specific gravity of bituminous mixtures, while flocculent lignin fiber had a minimal impact. The mixture with mineral fiber and polyester fiber had significant effects on the volumetric properties, and, consequently, exhibited better VMA over the conventional SMA mixture with lignin fiber. Modified fiber content range was also provided, which will widen the utilization of mineral fiber and polyester fiber in the applications of SMA mixtures. The mixture evaluation suggested no statistically significant difference between lignin fiber and polyester fiber on the stability. The mineral fiber required a much larger fiber content to improve the mixture performance than other fibers. Overall, the results can be a reference to guide SMA mixture design.

Bicycle transport stands at the forefront of sustainable mobility initiatives, a cornerstone of European Union policy. While support for cycling is crucial, its advancement hinges upon the presence of high-quality, secure infrastructure for cyclists. Safety emerges as a paramount concern, influencing the viability of cycling as a mode of transportation, yet its perception varies among user demographics. Considering this, this article endeavours to examine and contrast cycling infrastructure across various European nations, alongside analysing statistics pertaining to fatal traffic accidents involving cyclists. In our paper, we have chosen the Netherlands as a representative of building quality cycling infrastructure with many years of experience, and two countries that are developing conditions for cyclists, Slovakia and Poland. We have applied a correlation between the length of the transport infrastructure and the number of cyclists killed. The findings point to the substantial correlation between the quality of cycling infrastructure and the incidence of accidents. This correlation underscores the pressing need for robust infrastructure development and safety measures to bolster cycling as a safe and viable transportation option. We have employed the Shapiro-Wilk test for normal distribution to verify the input data and process the Pearson correlation to investigate the correlation between cycling infrastructure and road accident fatalities of cyclists.

Whey protein was pretreated with multi-frequency ultrasound in mono, dual, and tri-frequency modes. The effect of multi-frequency ultrasound pretreatment on the hardness, chemical forces, and microstructure of acid-induced whey protein gel was investigated. Whey protein gels pretreated with dual and tri-frequency ultrasound showed higher hardness (p3.35 mm) in those samples were resisted to gastric digestion. Moreover, the tri-frequency ultrasound pretreatment of whey protein gel released the least free amino group during gastric digestion. In contrast, whey protein gel with the mono-frequency ultrasound pretreatment released the highest amount of free amino acid group during intestinal digestion. Findings from this study suggested that gel hardness and network density could modulate the digestion behaviors of protein gels.

The efficient preparation of single-stranded DNA (ssDNA) rings, as a macromolecular construction approach with topological features, has aroused much interest due to their numerous applications in biotechnology and DNA nanotechnology. However, an extra splint is essential for enzymatic circularization, and by-products of multimers are usually present at high concentrations. Here, we proposed a simple and robust strategy of using permuted precursor (linear ssDNA) for circularization by forming an intramolecular dynamic nick using a part of the linear ssDNA substrate itself as the template. After the simulation of the secondary structure for desired circular ssDNA, the linear ssDNA substrate is designed to have its ends on the duplex part (≥5 bp). By using this permuted substrate with 5'-phosphate, the splint-free circularization is simply carried out by T4 DNA ligase. Very interestingly, formation of only several base pairs (2–4) flanking the nick is enough for ligation, although they form only instantaneously under ligation conditions. More significantly, the 5 bp intramolecular duplex part commonly exists in genomes or functional DNA, demonstrating the high generality of our approach. Our findings are helpful for understanding the mechanism of enzymatic DNA ligation from the viewpoint of substrate binding.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

Conductive hydrogels combine the properties of both hydrogels and electrical conductivity, making them soft, flexible, and biocompatible. These properties enable them to conform to irregular surfaces, stretch and bend without losing their electrical conductivity, and interface with biological systems. Conductive hydrogels can be utilized as conductive traces, electrodes, or as a matrix for flexible electronics. Exciting applications in sensors, tissue engineering and human-machine interaction have been demonstrated worldwide. This review comprehensively covers the progress in this field, focusing on several main aspects: functional materials, performance improvement strategies, and wearable applications in human-related areas. Furthermore, the major approaches and challenges for improving their mechanical properties, conductivity, and long-term stability are systematically summarized.

Snow cover products are primarily derived from the Moderate-resolution Imaging Spectrometer (MODIS) and Advanced Very High-Resolution Radiometer (AVHRR) datasets. MODIS achieves both snow/non-snow discrimination and snow cover fractional retrieval, while early AVHRR-based snow cover products only focused on snow/non-snow discrimination. The AVHRR Climate Data Record (AVHRR -CDR) provides a nearly 40-year global dataset that has a potential to fill a gap in long term snow cover fractional monitoring. Our study selects the Qinghai-Tibet Plateau as the experimental area, utilizing AVHRR-CDR surface reflectance data (AVH09C1) and calibrating with MODIS snow product MOD10A1. The snow cover percentage retrieval from the AVHRR dataset is performed using Surface reflectance at 0.64μm (SR1) and Surface reflectance at 0.86μm (SR2), along with a simulated Normalized Difference Snow Index (NDSI) model. Also, in order to detect the effects of land cover type and topography on snow inversion, we tested the accuracy of the algorithm with and without these influences, respectively (vanilla algorithm & improved algorithm). The accuracy of the AVHRR snow cover percentage data product is evaluated using MOD10A1、 ground snow-depth measurements and ERA5. Results indicate that the logic model based on NDSI has the best fitting effect, with R-square and RMSE values of 0.83 and 0.10, respectively. Meanwhile, the accuracy was improved after taking into account the effects of land cover type and topography. The model is validated using MOD10A1 snow-covered areas, showing snow cover area differences of less than 4% across 6 temporal phases. Improved algorithm results in better consistency with MOD10A1 than vanilla algorithm. Moreover, the RMSE reaches greater levels when the elevation is below 2,000 meters or above 6,000 meters, and is lower when the slope is between 16° and 20°. Using ground snow-depth measurements as ground truth, the multi-year recall rates are mostly above 0.7, with an average recall rate of 0.81. Results also show a high degree of consistency with ERA5. The validation results demonstrate that the AVHRR snow cover percentage remote sensing product proposed in this study exhibits high accuracy in the Tibetan Plateau region, also demonstrating that land cover type and topographic factors are important to the algorithm. Our study lays the foundation for the global snow cover percentage product based on AVHRR-CDR，furthermore lays a basic work for generating a long-term AVHRR-MODIS fractional snow cover dataset.

Evidence suggests that COVID-19 infection increases the risk of type 1 (T1D) and type 2 diabetes (T2D). Diabetes, in turn, increases COVID-19 susceptibility and contributes to increased COVID-19 morbidity and mortality. Oxidative stress (OxS) has emerged as a common factor driving the pathogenesis of diabetes and COVID-19 caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2). The mechanistic links between OxS, T2D, and COVID-19 have primarily been studied in adults and will be summarized in this review. However, we suggest that studying these interconnections in children and young adults is critical since early intervention is optimal for improving outcomes. At the height of the pandemic, COVID-19 was a leading cause of death in children and young people, and people in this age group are as susceptible to COVID-19 as adults and the elderly. Glutathione (GSH) is the primary water-soluble intracellular antioxidant and can be deficient in both diabetes and COVID-19. GSH is a tripeptide containing cysteine (CYS), glutamic acid (GLU), and glycine (GLY). Strategies to increase GSH levels may be beneficial in helping to manage COVID-19-induced diabetes as well as diabetes-induced COVID-19 risk. Dietary supplementation with GlyNAC may be optimal since it contains two metabolic GSH precursors, i.e., n-acetyl-l-cysteine (NAC) and GLY.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

Tea (Camellia sinenesis) is a health beneficial beverage and is also a source for extracting bioactive components such as theanine, tea polyphenols (TPP) and tea polysaccharides (TPS). TPS is a group of hetero-polysaccharides bounded with proteins. There were tests showing that TPS had various bioactivities, such as antioxidant, antitumors, antihyperglycemia, anti-inflammation and improving immunity. However, inconsistent results concerning chemical composition and bioactivity of TPS were published in recent years. The advances in chemical composition and bioactivities of TPS were reviewed in the present paper. The inconsistent and controversial results regarding composition and bioactivities of TPS were also discussed.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

(1) Background: A simple approach to map irrigated landcover has been introduced by using measures derived from optical spectral range as an alternative to thermal range. It has been demonstrated that substituting surface temperature (Ts, ‘thermal approach’) with SWIR transformed reflectance (STR, ‘optical approach’) to detect surface moisture is feasible with comparable results. (2) Methods: Using an iterative thresholding procedure to minimize within-class variance, the bilevel segmentation of variables derived from Landsat-8 representing surface moisture and vegetation cover was achieved for the 2020-21 summer for a key irrigation district in Australia. (3) Results: The results of irrigated landcover by optical approach found to be comparable with those by thermal approach. The classification accuracy was assessed using water delivery records at farm level. Though the overall accuracy is high in both cases, the optical approach (97.6%) performed slightly better than the thermal approach (93.9%). (4) Conclusions: The feasibility of using STR to map irrigated landcover has been confirmed by a high-level overall accuracy assessment. This has broader implications in terms of irrigated landcover assessment, as the use of satellite imagery in these applications may not necessarily be limited to microwave or thermal sensors.

Genetic engineering has become an essential element in developing climate-resilient crops and environmental sustainable solutions to respond to the increasing need for global food security. Genome editing using CRISPR/Cas [Clustered regulatory interspaced short palindromic repeat (CRISPR)-associated protein (Cas)] technology is being applied to a variety of organisms, including plants. This technique has become popular because of its high specificity, effectiveness, and low production cost. Therefore, this technology has the potential to revolutionize agriculture and contribute to global food security. Over the past few years, increasing efforts have been seen in its application in developing higher-yielding, nutrition rich, disease resistant, stress-tolerant “crops” fruits and vegetables. Cas proteins such as Cas9, Cas12, Cas13, and Cas14, among others, have distinct architectures and have been used to create new genetic tools that improve features that are important for agriculture. The versatility of Cas has accelerated genomic analysis and facilitated the use of CRISPR/Cas to manipulate and alter nucleic acid sequences in cells of different organisms. This review provides the evolution of CRISPR technology exploring its mechanisms and contrasting it with traditional breeding and transgenic approaches to improve different stress tolerance. We have also discussed the CRISPR/Cas system and explored three Cas proteins that are currently known to exist: Cas12, Cas13, and Cas14 and their potential to generate foreign DNA free or non-transgenic crops that could be easily regulated for commercialization in most countries.

Vanilla planifolia is grown as a high-value orchid spice for its odor and savor attributes that increase due to the curing process associated with microbial colonization. This tends to influence the aromatic properties of vanilla. Hence, 11 Bacillus sp. strains were isolated from V. planifolia and identified with 16S rRNA gene sequencing. The liquid culture (1 mL of 107 CFU mL-1) of selected Bacillus vallismortis NR_104873.1:11-1518, B. velezensis ZN-S10, and B. tropicus KhEp-2 effectively fermented green-blanched vanilla pods kept at 10 ℃ during the sweating stage. GC-MS analysis showed that the methanol extract of non-coated, and B. vallismortis treated vanilla detected three (3) volatile compounds, whereas seven (7) components were obtained in B. tropicus and B. velezensis treatment. 4H-pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl was found in B. velezensis ZN-S10, B. tropicus KhEp-2, B. vallismortis while it was not present in the control samples. This ketone compound suggested a Maillard reaction resulting in brown-increased aroma pods. Linoleic acid and Hexadecanoic acid ethyl esters were detected only in ZN-S10 strain-coated vanilla. A novel 3--Deoxy-d-mannoic lactone was detected only in B. vallismortis treated vanilla characterized as a new compound in V. planifolia which suggested that the new compound can be altered with the coating of bacteria in vanilla during fermentation. Thus, the Bacillus strains improved the volatile profile and exhibited a new aroma and flavor profile of vanilla owing to bacteria fermentation during the curing process.

This study explores the implementation of the ANSI/373: Sustainable Production of Natural Dimension Stone standard within the North American dimension stone industry to identify driving forces behind the initiative and consider potential outcomes as it advances. The method involves a thorough review of ANSI/373, comparing it with voluntary sustainability initiatives (VSIs) in the forest industry to assess its effectiveness and challenges, and semi-structured interviews with contacts in the dimension stone field. Key drivers such as corporate social responsibility and market pressures influence the adoption of sustainability standards. The results highlight the embedded environmental considerations within the emerging dimension stone standards and their implications for sustainable practices in the industry. While the ANSI/373 standard promotes sustainable awareness and practices, it faces challenges in certification credibility and industry acceptance, particularly due to inconsistency among firms in their response, rigorous certification demands, and skepticism about certification credibility. The research advocates for enhanced collaborative frameworks to increase the standard’s adoption and impact, suggesting that industry stakeholders prioritize showcasing dimension stone as a practical, environmentally considerate material.

Background: By 2025, road traffic injuries are projected to rank third in the global burden of disease, posing a significant challenge that affects health, social well-being, and economic aspects. According to data from the Romanian Police National Statistics Center, there has been an average of 342 traffic accidents per year involving pediatric patients over the past 10 years. Materials and Methods: A retrospective research study was conducted, encompassing 358 cases of road traffic accidents identified for the study. Data collection was conducted at "St. Mary’s" Emergency Hospital for Children in Iasi, Romania, from January 2015 to December 2022. To facilitate statistical analyses, participants were categorized into three specific age groups, correlating between the anatomical region affected and different types of accidents was examined, and the classification of injury types was determined based on the characteristics of the harm inflicted. Results: An oscillating trend is observed from 2015 to 2020, with its lowest value recorded in 2017 at around 6.8% and its peak in 2019 at 20.1%. Notably, post-pandemic (Covid-19), the cases underwent a substantial decline of approximately 50%. At least 78.7% of those who did not undergo orthopedic reduction required surgery, whereas among those who underwent orthopedic reduction, only 23.4% needed surgery. Regarding the frequency of complications 7,9% of the total cases experienced complications. Conclusion: The increased frequency of pediatric traffic accidents is attributed to the extensive services provided by "St. Mary’s" Emergency Hospital for Children, Iasi, to a significant number of patients from both rural and urban areas across the seven counties of the Moldova, Romania.

This study aimed to investigate the fatigue performance and interfacial strengthening mechanisms of Al6061-to-Cu dissimilar lap joints via electromagnetic pulse welding (EMPW). The load-bearing capacity of the joints at discharge voltages of 14 kV and 16 kV was superior to that of 12 kV. Furthermore, the fatigue life of the 14 kV joints was one order of magnitude higher compared to the 12 kV joints. SEM observation of the fatigue fracture surface revealed the presence of typical "tire-mark" fatigue striations only in the 14 kV joint, indicating higher ductility and the ability to withstand extended plastic deformation. Notably, ultra-fine nanocrystalline Al2Cu phase, amorphous phase, and numerous dislocations hindered EBSD acquisition in the transition zone. Nevertheless, dense low-angle grain boundaries (LAGBs) and refined grains were examined at the bonding interface. This suggests that the high-velocity collision caused severe plastic deformation and led to the formation of substructures. The interfacial strength was attributed not only to the "wave-like" or "inverted hook-like" diffusion layer but also to the presence of refined grains along the interface and nanocrystalline Al2Cu in the transition zone. Furthermore, the hybrid nanocrystalline-amorphous microstructure strengthened the joint by regulating the balance between strength and ductility.

The traffic light detection and recognition are crucial for enhancing the security of unmanned systems. This study proposes a YOLOv5-based traffic light detection algorithm to tackle the challenges posed by small targets and complex urban backgrounds. Initially, the mosaic-9 method is employed to enhance the training dataset, thereby boosting the network’s ability to generalize and adapt to real-world scenarios. Furthermore, the network incorporates the Squeezed-and-Excitation (SE) attention mechanism to improve. Moreover, the YOLOv5 algorithm’s loss function has been optimized by substituting it with EIoU_loss, which addresses issues like missed detection and false alarms. Experimental results demonstrate that the model , trained with this enhanced network, achieves a 99.4% mAP on a custom dataset, which is 6.3% higher than the original YOLOv5, while maintaining a detection speed of 74 f/s. Therefore, this algorithm offers higher detection accuracy and effectively meets real-time operational requirements.

Green spaces take part a vital role in reducing the harmful effects occurred through the process of rapid urbanization. This study focuses on evaluating the change of green space and per capita green space in Colombo District, Sri Lanka in between 2008 and 2015 using Landsat images. The NDVI differencing method and classification method were used to detect the change of land cover. According to the results, a gradual decline of green space from 629.1km2 to 591.16km2 with a rate of 6.03% can be depicted. The change is considerable in Kaduwela, Moratuwa and Maharagama DSDs and quite better in the areas such as Avissawella, Homagama and Padukka. The per capita green space has been decreased from 272.361 m2 to 248.811 m2. Though these rates are very well higher than the UN, EU and WHO standards for the district, Colombo DSD do not comply with UN and EU standards. The case would turn into worst in 2025, as the predictions with current rates. Therefore, the study recommends taking immediate actions to make a greener city. Further, a tax system is proposed to get the attraction of the general public.

Biological pre-treatment holds much promise as an innovative and sustainable strategy to improve biogas production from crop residues. In the present study, a novel hot spring cellulolytic microbial consortium (HSCMC) was used to pre-treat crop residues, such as maize stover, wheat straw and soybean straw to improve biogas production by anaerobic digestion (AD). Results indicated that the ash and volatile solids in maize stover were significantly reduced by maximum values of 21.3 % and 69.2 % respectively, after 7 days of pre-treatment over non-treated residues. The maximum decline of 83.9 % in total solid content was reported in wheat straw. The total reducing sugar content was increased by maximum yields of 60.9 %, 96.3 % and 84.7 % in maize stover, wheat straw and soybean straw, respectively. Furthermore, the HSCMC consortium enhanced the cumulative methane yield of wheat straw, maize stover and soybean straw by 50.6 %, 50.2 % and 56.6 %, respectively. Increased methane yield from pre-treated crop residues implies that this method could be an economically viable option for large-scale valorization of the AD process.

Wheat straw (WS) is a promising substrate for biogas production by anaerobic digestion (AD) due to its high carbohydrate content. An estimated 0.603 million t yr-1 of WS are generated from wheat production systems in South Africa. This is equivalent to an energy potential of 11 PJ. Despite, WS is still undervalued as a bioenergy resource in South Africa due to its structural complexity and low nitrogen content. WS disposal methods, such as use in livestock bedding, burning and burying into the soil, inter alia, are not sustainable and may contribute to global warming and climate change. Commercialization of the AD of WS needs to be further developed and promoted. Pre-treatment (i.e. physical, chemical, biological and hybrid methods) and anaerobic co-digestion (AcoD) are novel strategies that can support the conversion of WS into biogas and other value-added products. Current and future research should focus on optimizing pre-treatment and AcoD conditions towards industrialization of WS into valuable products. This paper focuses on the potential use of WS for biogas production by AD in South Africa. The aim is to create information that will promote research and development, and encourage policy makers and stakeholder participation and investment in WS biogas technology.

Optimal control is a critical tool for mechanical robotic systems, facilitating precise manipulation of dynamic processes. These processes are described through differential equations governed by a control function, addressing a time-optimal problem with bilinear characteristics. Our study utilizes the classical approach complemented by Pontryagin's Maximum Principle (PMP) to explore this inverse optimal problem. The objective is to develop an exact piecewise control function that effectively manages trajectory control while considering the effects of viscous friction. Our simulations demonstrate that the proposed control law markedly diminishes oscillations induced by boundary conditions. This research not only aims to delineate the reachability set but also strives to determine the minimal time required for the process. The findings include an exact analytical solution for the stated control problem.

Aim: The aim of this study was to investigate if tests used to assess core stability could be used to determine success in physiological tests applied to assess dynamic balance and agility for a young active population. Methods: Pearson's r correlation coefficient was used to assess the relationship between the core stability tests and the dynamic balance and agility tests. Evaluation of the tests was established using Cronbach's coefficient of variance as part of intra-rater reliability tests. An analysis of 18 active college aged students was conducted (males: n= 13, females: n= 5). The mean ± SD age for males was 19.2 years ± 3.22 years and for females was 19.4 years ± 1.14 years. Conclusion: The results indicate that there is no significant relationship between tests that assess core stability and tests conducted to assess dynamic balance in active young adults. With the exception of the abdominal flexion test, no significant relationship exists between the remaining core stability tests and agility T-Test. Core stability is not a determinant of balance and agility.

Observe the synergistic effect and dose-effect relationship of Trimethoprim (TMP) on bactericidal activity with Flos Lonicerae in vitro. Microamount chessboard dilution method was conducted to determine the minimal inhibitory concentration (MIC) of Trimethoprim, Flos Lonicerae, as well as the combination of Trimethoprim and Flos Lonicerae separately against Staphylococcus aureus, Escherichia coli in vitro and Salmonella. The pour plate count method was used to determine the combined bactericidal activity of Flos Lonicerae combined with Different concentrations TMP. The results showed that the MIC values of the combination of Flos Lonicerae with TMP was much less than the MIC values of the independent use of Flos Lonicerae or TMP, The FIC values of the combination of Flos Lonicerae with TMP were between 0.5 and 1, there was additive effect between them. The bactericidal rates were fitted with least square method, the 95% confidence intervals of the optimal blending quantity about the combination of Flos Lonicerae with TMP on the test organisms were 231μg·mL^-1-249μg·mL^-1, 237μg·mL^-1-259μg·mL^-1, and 235 -259μg·mL^-1

Amidst the escalating demands for efficient Intelligent Transportation Systems (ITS) management, the significance of accurate Origin-Destination (OD) data prediction has emerged as a paramount concern, given its indispensable role in the ITS domain. This paper introduces a groundbreaking integrated model, creatively fusing the unique strengths of Graph Convolutional Network (GCN), Residual Neural Network (ResNet), and Long Short-Term Memory Network (LSTM) into a single architecture, which we name GraphResLSTM, to exploit road segment average speed data for OD prediction. Compared with conventional road segment traffic volume data, average speed data is more readily available, significantly reducing the data accessibility barrier for OD prediction. We underscore the critical role of selection of key road segments and employs a combination of Entropy Weight Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to identify 41 representative road segments from the experimental road network. In the experimental phase, we simulate 86400000 seconds of traffic conditions, generating a total of 1440000 data records. Utilizing these simulated data, we design and conduct comparative experiments between models as well as data types. The results demonstrate that both the GraphResLSTM model and road segment average speed data outperform other models and data types notably in OD prediction tasks.

Road safety and the effectiveness of the transportation system as a whole are significantly impacted by driver comfort. Road surface quality can play a significant part in the driver’s comfort experienced on roads in any country. This study employs a Random Forest technique to examine the association between road roughness and drivers' comfort during long-distance driving. Using Random Forest, a dependable machine learning technique that can handle big datasets and detect nonlinear correlations, this work aims to shed light on the complex dynamics between road conditions and driver’s comfort. 1,048,576 rows of data from MIRANDA, an application developed at the University of Gustave Eiffel, were used in this study as part of the data collected from a probe vehicle. The data collected includes an International Roughness Index (IRI). The IRI thresholds offer a simple method for assessing driver comfort and road irregularity. While highlighting how uneven and uncomfortable the road is, the research's findings (Road Roughness: SD – 0.73; Driver's Comfort: - Mean, 10.01, SD – 0.64) also contribute to the standardization of road condition evaluation and maintenance communication. This finding is anticipated to aid in the development of strategies for improving the welfare of long-haul drivers and fixing road infrastructure to comply with standard road index, ultimately leading to the creation of more efficient and sustainable transportation systems.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

Background and aims: Despite recent advances in advanced prostate cancer treatments, there are no clinically useful biomarkers or treatments for men with such cancers. Targeted therapies have shown promise, but there remain fewer actionable targets in prostate cancer than in other cancers. This work aims to characterize BRD9, currently understudied in prostate cancer, and investigate its co-expression with other genes to assess its potential as a biomarker and therapeutic target in human prostate cancer. Materials and methods: Omics data from a total of 2053 prostate cancer patients across 11 independent datasets were accessed via Cancertool and cBioPortal. mRNA expression and co-expression, mutations, amplifications, and deletions were assessed with respect to key clinical parameters including survival, Gleason grade, stage, progression and treatment. Network and pathway analysis was carried out using Genemania, and heatmaps were constructed using Morpheus. Results: BRD9 is overexpressed in prostate cancer patients, especially those with metastatic disease. BRD9 expression did not differ in patients treated with second generation antiandrogens versus those who were not. BRD9 is co-expressed with many genes in the SWI/SNF and BET complexes, as well as those in common signaling pathways in prostate cancer. Summary and conclusions: BRD9 has potential as a diagnostic and prognostic biomarker in prostate cancer. BRD9 also shows promise as a therapeutic target, particularly in advanced prostate cancer, and as a co-target alongside other genes in the SWI/SNF and BET complexes, and those in common prostate cancer signalling pathways. These promising results highlight the need for wider experimental inhibition and co-targeted inhibition of BRD9 in vitro and in vivo, to build on the limited inhibition data available.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

Shigella and Salmonella have been implicated in neonatal sepsis, food poisoning, and bacteremia. Their increasing resistance to antibiotics has undermined treatment options, constituting a public health crisis. Also, the scarcity of new antibiotics in the development pipeline compounds multidrug-resistance (MDR). Hence, there is a need to potentiate antibiotics to mitigate resistance. This study leveraged riboflavin to re-sensitize fluoroquinolones and carbapenems against MDR Shigella and Salmonella spp. Disk diffusion, microbroth-dilution, chequerboard, and time-kill assays were used to determine resistance profiles and riboflavin-antibiotic activity. Biofilm-formation and bacterial viability (after riboflavin-antibiotic challenge) was determined with crystal-violet and Macrophage infection assays, respectively. Strains exhibited >80% resistance to fluoroquinolones and carbapenems, with 160–320 µg MIC ranges and 0.5–2 FIC, indicating no synergy. At 40–80 µg riboflavin, there was two-fold reduction in bacterial survival, with meropenem-riboflavin exhibiting significant reduction and FIC of 0.075 indicating high synergistic activity. Biofilm-formation was altered (from strong to weak phenotype) with 40 µg riboflavin-antibiotic treatment. There was a 40–70% reduction in bacterial survival in THP-1 cells treated with meropenem-riboflavin after 3 hours, and complete clearance between 24-48 hpi. Riboflavin potentiated fluoroquinolones and meropenem, leading to modulation of the host immune response for the clearance of the strains.

Pavement crack detection is one of the key links in highway pavement maintenance management. In the current road crack detection, the network model easily ignores the shallow geometric features of cracks and cannot extract the key feature information of cracks. Aiming at the above problems, an EC-YOLOX network model is proposed. The CFPN is constructed to cross-fuse different scale features to solve the feature scale invariance. In the strengthen feature extraction layer, ECANet is fused to enhance the ability to pay attention to key information. The WEIoU loss function is proposed, which assigns different penalty terms to the target box in the vertical and horizontal directions. In terms of data, geometric distortion constraint correction is performed on the single-point perspective pavement image. The experimental data show that the accuracy of EC-YOLOX on the self-built data set reaches 76.34% [email protected], which is 4.45% higher than that of YOLOX. The loss curve of EC-YOLOX is smoother than that of YOLOX, and the minimum training loss value is 2.136, which is 0.648 lower than the minimum loss value 2.784 of YOLOX. Many experiments have verified the effectiveness of EC-YOLOX in improving the detection effect in pavement crack detection.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

The United Nations Convention on the Rights of Persons with Disabilities (hereafter CRPD) has provided a radical imperative for the reform of mental health and capacity legislation around the world. The interpretation of the CRPD has been controversial, ranging from complete abolition of detention, forcible treatment and substitute decision making, to acceptance that elements of these measures need to be retained but based on non-discriminatory criteria, additional safe-guards and a comprehensive shift towards supported decision-making. While the potential ef-fects of the CRPD on mental health social work and social work generally are considerable given their shared commitment towards social justice, to date there has been no review of research evi-dence exploring their relationship. In addressing this knowledge gap, this study held a prelimi-nary discussion with practitioners and academics at the European Association of Social Work Mental Health Special Interest Group in Amsterdam 2022, followed by a scoping literature re-view on the question: What impact, if any, has the CRPD had on social work practice? The review produced four main findings: impact on legislation; positive impact on practice; limited impact on practice; and impact on social work education and research. In sum, while there were some positive indications of social work and mental health social work practice being influenced by the CRPD, these were scant. Barriers to change included tendencies among some social workers to practise substitute decision-making, in part related to resourcing and policy contexts, and under-standings of disability aligned to individualised/medical rather than social perspectives. The results indicate that legal reform on its own is insufficient to impact social work practice, and that realising the potential of the CRPD will necessitate good quality training, as well as improv-ing social workers’ knowledge of the human rights of people with mental impairment.

Heavy metal pollution poses a significant threat to ecosystems and human health worldwide. In response to this pressing issue, bioremediation has emerged as a promising approach for mitigating contamination. This paper adopts a bibliographic method to explore the key techniques and applications of bioremediation. Furthermore, we delve into the most prominent threats to human environmental health and the corresponding remediation methods. Additionally, we discuss the future trajectory of bioremediation research, with a particular focus on the integration of big data and machine learning technologies. These advanced methodologies hold great potential for enhancing the effectiveness and efficiency of environmental remediation efforts in the face of escalating pollution challenges.

This paper takes the VR animation display of the Ming Xiao Mausoleum General stone statue life as an example to study the advantages of VR animation in the display of material heritage. Combined with literature and pictures, the digital restoration of the Ming Xiao Mausoleum stone statue is carried out in MAYA and Z brush, and the construction of the scene and the output of the final effect are realized in UE4.

Selecting road networks in cartographic generalization has consistently posed formidable challenges, driving research towards the application of intelligent models. Despite previous efforts, the accuracy and connectivity preservation in these studies, particularly when dealing with road types of similar sample sizes, still warrant improvement. To address these shortcomings, we introduce a Heterogeneous Graph Attention Network (HAN) for road selection, where feature masking method is initially utilized to assess the significance of road features. Concentrating on the most relevant features, two meta-paths are introduced within the HAN framework: one for aggregating features of the same road type within the first-order neighborhood, emphasizing local connectivity, and another extending this aggregation to the second-order neighborhood, capturing a broader spatial context. For a comprehensive evaluation, we introduce a set of metrics considering both quantitative and qualitative aspects of the road network. Compared to traditional neural networks, our HAN model demonstrates superior accuracy and F1-score, particularly for road types with comparable samples. Additionally, it enhances the overall connectivity of the selected network. In summary, our HAN-based method provides an advanced solution for road network selection, surpassing previous approaches in terms of accuracy and connectivity preservation.

Pharmacist-prescribed hormonal contraception (HC) is supported by a majority of pharmacists and pharmacy students; however, few studies have evaluated perceptions of non-community pharmacists, or differences in geographic areas. The primary objective of this study is assess differences between community and non-community pharmacists in perceptions of pharmacist HC prescribing. Secondary objectives include assessment of community pharmacist interest in prescribing HC, and differences in perceptions between pharmacists in metropolitan and nonmetropolitan areas. A survey was emailed in early 2022 to 2592 Georgia pharmacists, with Likert questions assessing interest, perceptions, comfort, and perceived barriers regarding pharmacist prescribed HC. Completed survey response rate was 11.8%. Regardless of practice site, a majority agreed pharmacists are well-trained to prescribe HC (Community 61.8% vs. Non-community 68.1%, p=0.25) and provision of HC services is within the pharmacist’s scope (Community 73.6% vs. Non-community 74.2%, p=0.90). Overall metropolitan and non-metropolitan community pharmacists' perceptions were similar, however more metropolitan pharmacists believed pharmacists are well trained to prescribe HC (66.7% vs 48.7%, p=0.049) and that it is within their scope of practice (78.1% vs. 61.5%, p=0.045). In summary, the majority of pharmacists, regardless of practice type, believe that pharmacists are prepared to prescribe HC and it is a part of pharmacist’s professional scope of practice.

Scedosporium species are human pathogenic fungi, responsible for chronic, localised, and life-threatening disseminated infections in both immunocompetent and immunocompromised individuals. Diagnosis of Scedosporium infections currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Scedosporium-specific biomarkers. Here we report the development of a rapid (30 min) and sensitive (pmol/L sensitivity) lateral-flow device (LFD) test, incorporating a Scedosporium-specific IgG1 monoclonal antibody (mAb), HG12, which binds to extracellular polysaccharide (EPS) antigens of between ~15 kDa and 250 kDa secreted during hyphal growth of the pathogens. The test is compatible with human serum, and allows the detection of the Scedosporium species most-frequently reported as agents of human disease (Scedosporium apiospermum, Scedosporium aurantiacum, and Scedosporium boydii), with limits of detection (LOD) of the EPS biomarkers in human serum of ~0.81 ng/mL (S. apiospermum), ~0.94 ng/mL (S. aurantiacum), and ~1.95 ng/mL (S. boydii). The Scedosporium-specific LFD (ScedLFD) test therefore provides a potential novel opportunity for the detection of infections caused by different Scedosporium species.

Rapid and accurate detection of road cracks is of great significance for road health monitoring, but currently this work is mainly completed through manual site surveys. Low-altitude UAV remote sensing can obtain images with centimeter or even subcentimeter ground resolution, which provides a new efficient and economical approach for rapid crack detection. Nevertheless, crack detection networks face challenges such as edge blurring and misidentification due to the heterogeneity of road cracks and the complexity of the background. To address these issues, we propose a real-time edge reconstruction crack detection network (ERNet) which adopts multi-level information aggregation to reconstruct crack edges and improve the accuracy of segmentation between the target and background. To capture global dependencies across spatial and channel levels, we propose an efficient bilateral decomposed convolutional attention module (BDAM) that combines depth separable convolution and dilated convolution to capture global dependencies across spatial and channel levels. To enhance the accuracy of crack detection, we use a coordinate-based fusion module that integrates spatial, semantic, and edge reconstruction information. In addition, we propose an automatic measurement of crack information for extracting the crack trunk and its corresponding length and width. Experimental results demonstrate that our network achieves the best balance between accuracy and inference speed.

Traditional lime-based materials have considerable potential for use as components of green materials for plastering and finishing building surfaces in both new construction and historic heritage conservation. The paper presents the preliminary results of a research activity aimed at developing pre-packaged products based on Traditional Lime Putty (TLP) by partially replacing natural aggregates with Stone Waste Sludge (SWS), with a low rate of recovery from Apricena limestone production district in Apulia. The mineralogical and chemical analysis carried out by means XRD (X-Ray Diffraction), TG-DTA (Thermo Gravimetry-Differential Thermal Analysis) and hydrochloric acid attack test showed that the SWS consisted of 98.4 % CaCO3 by mass. The particle sizes measured by laser diffraction technique are below 22.5 μm for the 92% by mass of the sample. The high fineness of the stone waste was confirmed by the Blaine specific surface method equal to 9273.79 cm2/gr. The behavior of three fresh mixtures for prepacked coarse plaster, fine plaster, and finishing plaster with 12.90%, 17.94%, and 18.90 by mass of SWS, respectively, was evaluated by spreading test and applicability tests on a perforated ceramic slab. The finishing plaster has the highest consistency value of 235 mm, while the fine plaster and the coarse plaster have values of 205 mm and 155 mm, respectively. The coarse plaster is suitable for the use as base plaster (arriccio) or second layer rendering (tonachino) up to a thickness of approximately 1 cm. Both the fine plaster and finishing plasters can be used for the surfaces finishing with the application of layers of a few millimeters thick.

Cumulative effects of landscape disturbance in forested source water regions can alter the storage of fine sediment and associated phosphorus in riverbeds, shift nutrient dynamics and degrade water quality. Here, we examine longitudinal changes in major element chemistry and particulate phosphorus (PP) fractions of river-bed sediment in an oligotrophic river during environmentally sensitive low flow conditions. Study sites along 50 km of the Crowsnest River were located below tributary inflows from sub-watersheds and represent a gradient of increasing cumulative sedi-ment pressures across a range of land disturbance types (harvesting, wildfire, and municipal wastewater discharges). Major elements (Si2O, Al2O3, Fe2O3, MnO, CaO, MgO, Na2O, K2O, Ti2O, V2O5, P2O5), loss on ignition (LOI), PP fractions (NH4CI-RP, BD-RP, NaOH-RP, HCI-RP and NaOH(85)-RP) and absolute particle size were evaluated for sediments collected in 2016 and 2017. While total PP concentrations were similar across all sites, bioavailable PP fractions (BD-RP, NaOH-RP) increased downstream with increased concentrations of Al2O3 and MnO and levels of landscape disturbance. This study highlights the longitudinal water quality impacts of increasing landscape disturbance on bioavailable PP in fine riverbed sediments and shows how the convergence of climate (wildfire) and anthropogenic (sewage effluent, harvesting, agriculture) drivers can produce legacy effects on nutrients.

: This study focuses on optimizing chlorophyll extraction techniques and strategically placing leaf disks to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal SPAD value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. Examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly the later incubated for 10 minutes at 85°C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% position along the sesame leaf blade is suggested, consistently yielding higher chlorophyll content. Our findings therefore, underscores insightful knowledge on chlorophyll gradients and encouraging for standardized protocols, that enabling researchers to refine experimental designs for precise and comparable chlorophyll measurements. Recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

To better understand farmers’ refusal and corresponding negative emotions to pay agricultural water fee under current policy in rural China, this paper applies mental accounting, a behavioral economics framework, to explore how the governmental policies of reform of rural taxes and fees, direct agricultural subsidy programs and agricultural water fee individually influence farmers’ decisions in paying agricultural water fee. Using fieldwork data from 577 farmers and 20 water managers in Sichuan, we explore farmers’ information processing regarding paying agricultural water fee via three sequential mental accounting processes, with the associated underlying principles and measures behind each process. We find that the information processing in three mental accounting scenarios related to the agricultural water fee elucidates farmers’ observed behaviors in rural China. Generally, in the three mental accounting scenarios, two conditional intuitive expectations and nine conditional intuitive preferences are formed, however, the conditions of those expectations or preferences cannot be matched with the facts due to the reform of rural taxes and fees, the direct agricultural subsidy programs and the internal attributes of agricultural water fee, which interpret those negative behaviors in rural China. Additionally, this paper offers a view into how previous policies create negative psychological externalities (such as farmers’ psychological dependence on the government) through mental accounting to negatively influence agents’ subsequent decision making; it highlights the significance of underlying mental factors and information processing of negative behaviors in policymaking for managing or conserving common pool resources.

About 14% of adolescents experience mental illnesses globally. The rate increased after the COVID-19 pandemic. This study aimed to estimate the prevalence of COVID-related major mental illnesses (depression and anxiety) and their predictors among adolescents. This community-based cross-sectional study was conducted among 350 adolescents aged 10-19 years, recruited from rural communities in West Bengal, India. The study areas included 27 subcenters in the Budge Budge II Block, which comprised 1,91,709 population and 45,333 households. Data were collected from randomly selected households by trained research assistants through house-to-house interviews. Pretested standardized questionnaires, Patient Health Questionnaire (PHQ) for depression, Generalized Anxiety Disorder (GAD) for anxiety, and a demographic questionnaire were used for data collection. The prevalence of anxiety was 35.7% (125 out of 350), and the prevalence of depression was 30.0% (105 out of 350). Females had significantly higher scores of anxiety (6.67 ± 4.76 vs. 3.42 ± 3.17, respectively, p <0.001) and depression (5.51 ± 4.99 vs. 3.26 ± 3.86, respectively, p <0.001) compared to males. Adolescents who had COVID-19 cases or deaths in the family had significaly higher scores of anxiety and depression compared to those who didn’t have these events. In multivariate analysis, the statistically significant predictors of anxiety were COVID-19 death in the family, COVID-19 cases in the family, female gender, and a lower income group (p <0.001 for all). For depression, the significant predictors included COVID-19 death in the family, COVID-19 cases in the family, female gender, a lower income group, and a higher age group in adolescents (p <0.001 for all). Based on the study results, we recommend that immediate attention is needed for adolescents’ mental health support and coping with stresses following COVID-19.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

Solid waste management in Accra is a major challenge to the Metropolitan Authorities and inhabitants. The rapidly increasing population coupled with poor capacity of the municipal and private waste management companies to management waste effectively has created issues of environmental concern. Due to poor waste managements systems, most household dispose waste indiscriminately leading to floods and health issues. The study showed that about 60% of household waste is organic materials which has the potential to be converted to compost for agriculture purpose. Meanwhile plastics and rubbers which litters the environment as well as blocking major storm drains and gutters hence creating huge environmental hazard is made of 11% of the total component of most household waste generated daily. The study also revealed that among the methods of disposing waste, dumping waste in skip containers located at authorized places was the preferred means of disposing waste by household though others also dispose waste by other means such as burying and burning. Inadequate skip containers per population of household in an area coupled with irregularity of tracks picking these containers makes skip containers dumping site ugly scene, hence creating health issues. Among the constraints that impact negatively on sustainable waste management in Accra Metropolis, economic constraints was perceived as the main challenge which affect efficient waste management. Currently the country is going through serious economic challenges so government does not release money timely to fund projects which waste management is key. Most donor partners that use to support the government with funds have either reduced or redrawn their services as they have no confidence in the state of Ghana economy. Aside the constrains, the study also indicated that factors such as poor public attitude towards waste management, poor enforcement of sanitation by-laws, inadequate and untimely release of government funds were also seen as the main factors affecting waste management.

Tunnel fires are generally detected using various sensors, including measuring temperature, CO concentration, and smoke concentration. To address the ambiguity and inconsistency in multi-sensor data, this paper proposes a tunnel fire detection method based on an improved Dempster-Shafer (DS) evidence theory for multi-sensor data fusion. To solve the problem of evidence conflict in DS theory, a two-level multi-sensor data fusion framework is adopted. The first level of fusion involves feature fusion of the same type of sensor data, removing ambiguous data to obtain characteristic data, and calculating the basic probability assignment (BPA) function through the feature interval. The second level fusion derives basic probability numbers from the BPA, calculates the degree of evidence conflict, normalizes to obtain the relative conflict degree, and optimizes the BPA using the trust coefficient. The classical DS evidence theory is then used to integrate and obtain the probability of tunnel fire occurrence. Different heat release rates, tunnel wind speeds, and fire locations are set, forming four fire scenarios. Sensor monitoring data under each simulation condition are extracted and fused using the improved DS evidence theory. The results show that the proposed improved DS evidence theory method detects the probability of fire occurrence in the four scenarios as 67.5%, 71.0%, 82.8%, and 83.5%, respectively, and identifies fire occurrence in approximately 2.4 seconds, an improvement of 64.7% to 70% over traditional methods. This demonstrates the feasibility and superiority of the proposed method, highlighting its significant importance in ensuring personnel safety.

Type 2 diabetes mellitus (T2DM), a multifactorial and complicated metabolic disorder, is a growing public health problems. Numerous studies indicated that bioactive compounds from herbal medicine have beneficial effects on T2DM prevention and treatment, owing to their numerous biological properties. Curcumin, the major curcuminoid of turmeric, is one of the most studied bioactive components of herbal supplements, which has a variety of biological activities. Clinical trials and preclinical research have recently produced compelling data to demonstrate the crucial functions of curcumin against T2DM via several routes. Accordingly, this review systematically summarizes the antidiabetic activity of curcumin, along with various mechanisms. Results showed that effectiveness of curcumin on T2DM is due to it being anti-inflammatory, anti-oxidant, anti-hyperglycemic, anti-apoptotic, anti-hyperlipidemia and other activities. In light of these results, curcumin may be a promising prevention/treatment choice for T2DM.

Global environmental and societal changes threaten the cultures of Indigenous Peoples and Local Communities (IPLC). Despite the importance of IPLC worldviews and knowledge systems to human well-being and biodiversity, risks to these cultural resources are commonly simplified or neglected in environmental impact assessments, in part because cultural impacts are often indirect and therefore difficult to demonstrate. Here, we show that dependency of a culture on the environment can be mapped through human connections with biophysical elements in their environment. We illustrate a rich variety of cultural values that connect an indigenous Māori tribe in New Zealand with their local environment, then evaluate the resilience of this socio-environmental value system to environmental changes. Our results detail how loss of access to key environmental elements can have extensive direct and cascading impacts on multiple facets of indigenous cultural heritage. Consequently, considering only direct effects of environmental change on cultural heritage, or treating the richness of IPLC environmental relations simplistically, can severely underestimate the seriousness of environmental impacts on IPLC culture. Thus, protecting Earth’s cultural and biological diversity requires inclusion of human-environment relationships in environmental impact assessments.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

Lane detection is a foundational technology for autonomous driving systems. It involves identifying the boundaries of lanes on the road and ensuring the vehicle stays within these boundaries. Accurate lane detection is crucial for safety, navigation and traffic management. This paper presents an artificial intelligent based autonomous road lane detection and navigation system for vehicles. The system can detect and analyze road lanes accurately and efficiently in real-time, with frame rates of up to 17 FPS. By utilizing image processing techniques, the system can identify the location and boundaries of road lanes and obstacles on the road and provide accurate and reliable navigation guidance to the driver. The system is integrated with sensors and actuators to provide comprehensive autonomous navigation. The efficiency of the proposed system is demonstrated using accuracy of lane detection on straight and curve lanes covering frames per second and motor of the speed as parameters for assessment. Results show that the proposed system detects lane as entire lane detection, partial lane detection and no detection status on different settings.

Antisense oligonucleotides (ASOs) are short oligodeoxynucleotides designed to bind to specific regions of target mRNA. ASOs can modulate pre-mRNA splicing, increase levels of functional proteins and decrease levels of toxic proteins. ASOs are being developed for the treatment of several diseases, including motor neuron diseases (MNDs), a group of neurodegenerative disorders characterised by the loss of motor neurons, including spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and spinal and bulbar muscular atrophy (SBMA). The biggest success has been the ASO known as nusinersen, the first effective therapy for SMA, able to improve symptoms and slow disease progression. Another success is tofersen, an ASO designed to treat ALS patients with SOD1 gene mutations. Both ASOs have been approved by the FDA and EMA. On the other hand, ASO treatment in ALS patients with the C9orf72 gene mutation did not show any improvement in disease progression. The aim of this review is to provide an up-to-date overview of ASO research in MND, from preclinical studies to clinical trials and, where available, regulatory approval. We highlight the successes and failures, underline the strengths and limitations of the current ASO research, and suggest possible approaches that could lead to more effective treatments.

Phosphatidylserine (PS) has significant applications in various sectors, such as the medical and food industries. However, its production relies heavily on phospholipase D (PLD), a crucial tool that is hindered by issues like poor stability and irrecoverability. Immobilization presents itself as an effective solution to overcome these limitations. In this study, magnetic graphene oxide (MGO) modified with amino (-NH₂) were synthesized and utilized for PLD immobilization. The activity of the immobilized PLD (MGO-PLD) reached 3062 U/g_MGO, with a specific activity of 33.9 U/mg_PLD, virtually identical to that of the free PLD. MGO-PLD was utilized to synthesize PS efficiently in a biphasic system. Under optimal conditions, PS yield reached 18.66 g/L, with a conversion rate of 92.8% and a productivity of 3.11 g/L/h. Notably, MGO-PLD retained an impressive PS conversion rate of 77.4% even after seven repetitive usages. Moreover, MGO-PLD displayed enhanced thermal and pH resistance properties compared to free PLD, alongside an augmented storage stability. Post a 8-week preservation at 4°C, its residual activity was able to maintain at 76.3%. This study provides a sustainable and highly efficient pathway for biocatalytic synthesis of PS.

Two ferrocene derivatives, namely, 1,2-(tetramethylene)-ferrocene and 1,2,1’,2’-bis(tetramethylene)-ferrocene, were synthesized in a four-step reaction sequence starting from ferrocene. Friedel-Craft acylation of ferrocene with succinic anhydride gave mono- or bis(3-carboxypropinoyl)ferrocene depending on the stoichiometry of succinic anhydride. The reduction of the keto groups to methylene, followed by ring-closing using trifluoroacetic anhydride gave 1,2-(α-ketotetramethylene)-ferrocene or 1,2,1’,2’-bis(α-ketotetramethylene)ferrocene. The diastereomeric mixture of the latter diketones was separated by column chromatography, characterized by single-crystal X-ray analysis, and assigned their stereochemistry. Reduction of the keto groups to methylene under Clemmensen conditions gave homoannular mono- or bis(tetramethylene) ferrocene derivatives. The molecular structure of 1,2-(tetramethylene)-ferrocene revealed that the ipso carbon atoms of the cyclopentadienyl group are 0.023(3) Å farther away from Fe(II) compared to the remaining three carbon atoms. Both complexes exhibit lower half-wave oxidation potentials than ferrocene, possibly due to the electron-releasing effects of the tetramethylene bridges.

Globally increasing antibiotic resistance has been connected to the use of antibiotics in medical, veterinary, and agricultural medicine, contributing to the burden of antibiotic resistance in Asia and Europe. The main objective of this study was to correlations of antimicrobial-resistant of various pathogens in three compartments: humans, animals and the environment in India and Germany. A systematic search was carried out in Medline via PubMed, Google Scholar, and science direct, including studies published in 2022. Out of 532 papers, 24 were considered for meta-analysis. This study reveals that in India, β-lactam is highly resistant in animals. Quinolone, on the other hand, was highly resistant in humans. Furthermore, in the environment and integrated studies, aminoglycosides and β-lactams is resistant. While in Germany, a high rate of AMR resistance in all three sectors was reported in β-lactam. However, E. coli was the most frequent pathogen in both countries and is highly resistant to β-lactam, followed by cephalosporin in all the compartments. Monitoring and evaluating antibiotic-sensitivity patterns and developing proper antibiotic regimens may lead to improved outcomes for inhibiting and controlling E. coli infections in various parts of the world.

The recyclable paper based on photochromic materials not only reduces the pollution in the paper manufacture process, but also reduces the pollution caused by the use of ink, which receives wide attention. In this paper, a serial of PMoA-PWA/ZnO/PVP hybrid films which had different ratio of PMoA/PWA was prepared by the ultrasonic composite method. The results indicated that the hybrid film prepared when the ratio of PMoA to PWA was 3 had the best photochromic performance. In this system, ZnO was the photosensitizer while PMoA/PWA was the chromophore. The photochromic mechanism of PMoA-PWA/ZnO/PVP hybrid film was based on the photogenerated electron transfer mechanism. ZnO generated photoelectron under the excitation of visible light, then PMoA and PWA obtained the photoelectron and produced photoreduction reaction to generate heteropolyblue. The visible light photochromic paper was prepared by loaded PMoA-PWA/ZnO/PVP hybrid film (A3) on A4 paper. Application test showed that the prepared paper had extremely stable, excellent and reversible visible light photochromic properties, whether it was printing patterns or words and could replace the ordinary paper to realize the reuse of paper.

The reasons for the circular sense of human color perception generated by two sorts of color opponent neurons and three cone types are not well understood. Here we use geometrical analysis to examine the hypothesis that opponency, the recursive nature of color perception, and trichromacy arise as the most efficient ways of distinguishing spectrally different points on a plane using a minimum of color classes and receptor types.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

A flow chart is presented depicting coupling in ocean-atmosphere system, initiated by solar decadal variability that involves El Niño Southern Oscillation (ENSO). Possible mechanisms for Canonic ENSO, Modoki ENSO and Canonic-Modoki ENSO are proposed considering their relevance to the decadal variation of Hadley, Walker circulation and mid-latitude jets. It also discusses subsequent teleconnections by ENSO on Indian Summer Monsoon (ISM) with a special emphasis on later two decades of the last century. Possible mechanisms relating to a disruption of the usual ENSO-ISM teleconnection for those decades are emphasised; the role of volcanos and the change in the sun- NAO (North Atlantic Oscillation) connection were attended. The regional Hadley circulation, via the NAO in the northern hemisphere and Indian Ocean Dipole in the southern hemisphere, during that period, may have a role in the change in ISM behaviour- which though captured in observation but missed by models. The representation of flow chart helps to improve understanding of various types of ENSO in both temporal as well as spatial scale. The overall study subsequently can benefit the modelling community by not only improved the representation of ENSO in models but also better representation of ISM teleconnection via regional Hadley cell.

Furazolidone (FZD) is a synthetic nitrofuran with the antiprotozoal and antibacterial activity. The proper mechanism of FZD induced toxicity is still unclear. This study aimed to investigate the protective effect of curcumin on FZD induced oxidative stress, DNA injury and apoptosis in human hepatocyte L02 cells. The results showed that curcumin treatment significantly ameliorated FZD induced cytotoxicity, characterized by decreasing the production of reactive oxygen species (ROS) and malondialdehyde, as well as increasing superoxide dismutase, catalase activities and glutathione contents. Moreover, curcumin pretreatment significantly inhibited FZD induced the loss of mitochondrial membrane potential, the activation caspase-9 and -3 and apoptosis. Comet assay showed that curcumin attenuated FZD induced DNA injury in a dose-dependent manner. Correspondingly, curcumin markedly reversed the up-regulation of p53, Bax, caspase-9 and -3 mRNA expressions and the down-regulation of Bcl-2 mRNA (all p<0.05 or 0.01). These results reveal that curcumin protects against FZD induced oxidative stress, DNA injury and cell apoptosis via inhibiting oxidative stress and mitochondrial pathway, which may be attributed to ROS scavenging and anti-oxidative ability of curcumin. Importantly, our study highlights that curcumin may be a potential way to prevent FZD-mediated oxidative DNA injury and apoptosis in human or animals.

This comprehensive review paper provides a detailed analysis of the extraction methods employed in the dimension stone industry. Natural rock materials used in construction, have been historically extracted using primitive techniques such as thermal shock, hammer and chisel, and plug and feather. However, significant technological advancements have revolutionized the industry, leading to the widespread adoption of mechanized methods. One highly efficient technique is diamond wire cutting, which involves the utilization of diamond-engraved bits affixed to a tensioned steel wire. This method has demonstrated remarkable capabilities in minimizing waste generation and ensuring exceptional machining quality. Nonetheless, challenges such as high operating costs and wire breakage persist and require further investigation. In addition to diamond wire cutting, this review explores the utilization of circular diamond saws and frame sawing as alternative extraction methods. The geotechnical characteristics of the stone play a critical role in the selection of appropriate machinery, and researchers worldwide have conducted numerous studies to investigate the impact of each parameter on the extraction efficiency of these mechanized techniques. Moreover, controlled blasting with explosives emerges as a promising alternative for dimension stone extraction, warranting further exploration and optimization.

Chemical analysis of the organic components in beers has applications to quality control, authenticity and improvements to the flavor characteristics and brewing process. This study aims to show the complementary nature of two instrumental techniques which in combination can identify and quantify the majority of organic components in a beer sample. Nuclear Magnetic Resonance (NMR) was used to provide concentrations of twenty five different organic compounds including alcohols, organic acids, carbohydrates, and amino acids. Calorie content was also estimated for the samples. NMR data for ethanol concentrations were validated by comparison to a Fourier Transform Infrared Spectrometry (FTIR) method. Headspace Solid-Phase Microextraction (SPME) Gas Chromatography Mass Spectrometry (GCMS) was used to identify a range of volatile compounds such as alcohols, esters and hop derived aroma compounds. A simple and inexpensive conversion of a Gas Chromatography Flame Ionization Detector (GC FID) instrument to allow the use of Solid-Phase Microextraction was found to be useful for the quantification of volatile esters.

Knowledge of the genetic diversity of the available germplasm is an important foundation for crop conservation, management, and improvement. Successful breeding strategies rely on a sound understanding of the genetic diversity of the crop germplasm. This study was conducted to evaluate and compare the genetic diversity of 49 soybean [Glycine max (L.) Merrill] genotypes using SSR markers as well as to evaluate parental potential of these genotypes in cultivar improvement. The bulk of the genotypes were developed in the national soybean breeding program in Zimbabwe between 1940 and 2013. The genetic diversity and relatedness were estimated using 30 SSR markers and produced 5 clusters that generally matched the pedigree information of the germplasm. The SSR analysis detected a total of 135 alleles. The polymorphic information content ranged from 0.10 to 0.77 with a mean of 0.45. The SSR primer, Satt012 was the most informative. The SSR marker analysis showed a wide genetic diversity in the germplasm. To date, there are no reports regarding the genetic diversity analysis of soybean germplasm in Zimbabwe. The genotypes, EL41 and EL7; EL41 and EL1; as well as EL41 and EL42 were the most divergent thus, indicating their potential use as parental lines in the genetic improvement of soybean in the region.

Land transportation is contributing to global greenhouse gas (GHG) emissions significantly. Switching from gasoline-powered vehicles to electric vehicles (EVs) is the most practical way to decarbonize land transportation. Some regions of the world have seen significant advancements in the adoption of electric vehicles, largely due to government policies through subsidies and other rules and laws that globally made the cost of acquisition and ownership more advantageous for EV owners compared to their internal combustion engine (ICE) counterparts. The success of EV adoption in Norway, China, the United States of America (USA), the European Union (EU), and India has been linked to the favorable government policies. At present, China is the largest EV market in the world, enjoying a better advantage than any other market. It also has the highest manufacturing capacity and the largest number of EVs in operation. Norway has the highest EV penetration rate, with over 90% of newly registered cars, and one of the lowest costs of ownership globally. In this review, we present the current state of EV technology and performance, together with consumer perspectives and barriers, EV regulations in the regions with the highest penetration rates, and the decarbonization of land transportation. China is competing with the USA for leadership in manufacturing and technology, especially in the areas of artificial intelligence (AI) and batteries. In order to achieve the goal of decarbonizing road transportation, we proposed that a number of factors, including government energy policies and regulatory standard development, necessary infrastructure investments and developments, AI incorporation in EVs, innovation in EV and battery technologies, and consumer perspectives, play a crucial role.

Many historic buildings and monuments on the Salento Peninsula (Apulia, southern Italy) were built from locally quarried Miocene calcarenites belonging to the Pietra Leccese Formation (Late Burdigalian-early Messinian). The main facies consists of a homogeneous and porous biomicrite, pale yellow in color and fine- to medium-grained, very rich in planktonic Foraminifera and massive or thick-bedded in outcrop. Additionally, there are other facies among which Piromafo stands out for its aesthetic appearance, which is enhanced by its greenish-brown or greenish-grey colors. Its physical characteristics, in terms of thermal properties mainly due to the mineral content and fabric, make it a good refractory and insulation material. Piromafo occurs in the upper part of the Pietra Leccese Fm. and is repre-sented by a fine- to medium-grained glauconitic and phosphatic biomicrite with macrofossils, es-pecially Bivalves and Gastropods. Despite its important historical use as building and ornamental material, especially in the Roman and Baroque architecture, a research gap exists in the scientific literature describing the properties of the stone and their correlation. Therefore, the aim of this paper is to present a wide range of properties useful to explain the in-situ behavior and damage susceptibility of the stone in monu-ments and buildings, but also for selecting preservation treatments and strategies. Thus, an overall assessment of the main petrophysical and mechanical properties especially for restoration/conservation purposes was performed using both standard and unconventional tech-niques. Starting from rock fabric inspection, particular attention was given to the relationship be-tween pore-size distribution and, hydraulic and thermal properties of the material. Unconfined compressive strength, flexural strength and indirect tensile strength were also estimated.

Annually, more than 1.5 million preventable new hepatitis B (HBV) infections continue to occur, with an estimated global burden of 296 million individuals living with chronic hepatitis B infection. This substantial health challenge results in over 820,000 annual deaths attributed to complications such as liver cirrhosis and hepatocellular carcinoma (HCC). HBV vaccination remains the cornerstone of public health policy to prevent chronic hepatitis B and its related complications. It serves as a crucial element in the global effort to eliminate HBV, as established by the World Health Organization (WHO), with an ambitious 90% vaccination target by 2030. However, reports on global birth dose coverage reveal substantial variability, with an overall coverage rate of only 46%. This comprehensive review thoroughly examines global trends in HBV vaccination coverage, investigating the profound impact of vaccination on HBV prevalence and its consequences across diverse populations, including both high-risk and general demographics. Additionally, the review addresses the formidable challenges and facilitating factors essential for achieving WHO's HBV vaccination coverage objectives and elimination strategies in the coming decade and beyond.

The rise in population density, vehicle ownership, and urban development has significantly influenced travel demand and altered travel patterns, leading to traffic congestion in rapidly growing urban centers like Accra, Ghana. The traditional approach of expanding roadways to accommodate rising traffic is no longer environmentally sustainable. Instead, emphasis has shifted towards travel demand management (TDM) strategies as a more sustainable solution. This study aimed to investigate a range of TDM strategies that can be adopted in Accra to improve traffic flow through the lenses of everyday road users. The study employed a questionnaire survey and a stratified sampling technique to gather data from 615 respondents for relative importance index (RII) ranking, and Chi-square statistical analysis. The findings reveal that the topmost preferred strategies were mass transit improvements, walking and cycling improvements, and alternative work schedules. Notably, mass transit improvements emerged as the most preferred strategy. The study also unveiled a statistically significant correlation between variables such as age, education level, marital status, income level, and mode of transportation with all selected TDM preferences. However, no significant relationship was found between gender and car ownership with all selected TDM preferences. The study provides valuable insights regarding road users’ preferences for TDM strategies that can aid in planning future urban mobility systems to proactively manage travel demand, alleviate congestion, and promote sustainable transportation options for the city’s residents.

In metropolitan regions, which are particularly vulnerable to seismic damage, numerous reinforced concrete (RC) buildings are being constructed. Public safety has been an important consideration to safeguard and protect people, buildings, and infrastructure from the potential effects of earthquakes. The assessment of seismic vulnerability within urban areas encompassed an analysis of both building vulnerability and the scale of seismic hazards prevalent in the locality. This assessment aimed to ascertain the likelihood of building damage resulting from ground motion induced by an earthquake of a specific magnitude. In recent decades, considerable efforts have been made to develop and improve methods for assessing earthquake damage to reinforced concrete (RC) buildings. These efforts included the creation of seismic hazard and seismic risk indices that were used to quantify the potential destruction of individual building components or the entire building. This scholarly review article presents an in-depth analysis and concise summary of the primary techniques (including qualitative or empirical, quantitative, analytical, and experimental test methods) devised for appraising the seismic vulnerability of reinforced concrete frame buildings, pre- and post-earthquake occurrences. It is a valuable reference for policymakers, engineers, researchers, and specialists engaged in earthquake risk mitigation efforts.

The transition from Building Information Modelling (BIM) to Heritage Building Information Modelling (H-BIM) is intended to pursue an adequate knowledge of the artefact that is to be preserved, progressively replacing the traditional methods of the restoration and structural reinforcement projects with new tools for managing both existing information and new interventions. The aim of the paper is to show the application of the H-BIM method to a stone pavement road located in the Archaeological Site of Pompeii. In detail, starting from a Laser Scanner based survey, juxtaposed by coordinated points georeferenced through a total station, points clouds were handled by means of several BIM-based tools to perform the road design process, starting from the digital elevation model (DEM) to the corridor representation. Subsequently, a visual programming application based on Python language was adopted to update corridor information by means of the object property set. As preliminary results, a tool, complete with graphical and non-graphical information, is proposed to be used in conservation, maintenance and restoration project.

Acetamiprid is a broad-spectrum neonicotinoid insecticide used in agriculture to control aphids. While recent studies have documented resistance to acetamiprid in several aphid species, the underlying mechanisms are still not fully understood. In this study, we analyzed the transcriptome and metatranscriptome of a laboratory strain of the pea aphid, Acyrthosiphon pisum (Harris, 1776), with reduced susceptibility to acetamiprid after nine generations of exposure to identify candidate genes and the microbiome involved in the adaptation process. Sequencing of the transcriptome of both selected (RS) and non-selected (SS) strains allowed the identification of 14858 genes and 4938 new transcripts. Most of the differentially expressed genes were associated with catalytic activities and metabolic pathways involving carbon and fatty acids. Specifically, the alcohol-forming fatty acyl-CoA reductase (FAR) and acyl-CoA synthetase (ACSF2), both involved in the synthesis of epidermal wax layer components, were significantly upregulated in RS, suggesting that adaptation to acetamiprid involves the synthesis of a thicker protective layer. Metatranscriptomic analysis revealed subtle shifts in the microbiome of RS. These results contribute to a deeper understanding of acetamiprid adaptation by the pea aphid and provide new insights for aphid control strategies.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Permutation Entropy(PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine(RELM), Multi-head Attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high, mid,and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Betele Optimizer(DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. Empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM,and MHA-BiGRU. In comparison to other benchmark models, the proposed model exhibits a reduction in Root Mean Square Error(RMSE) values of over 10%, conclusively affirming its superior predictive accuracy.

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

Multiple sensor nodes known as detection stations make the sensor networks; each node is light and portable. Every sensor node contains power source, microcomputer, transducer and transceiver. Power source provides power to each node. Micro-computer is used for storing and processing the output coming from the sensors. The transducer is used to generate the signals and the transceiver is used to receive and transmit data to the central computer. Eavesdropping gets facilitated with wireless communication, and it has many useful applications in military, homeland, hostile and uncontrolled environments. So it is prone to the high level of security. The process in which information is gathered to form a summarized type for analysis is known as data aggregation, as it is used to reduce the energy consumption in wireless sensor networks. The security issues have become crucial in data aggregation, especially when gets deployed in hostile and remote environment. In wireless sensor networks many secure aggregations have been proposed. It still faces some resource constrained that’s why new techniques are needed. In our survey we will discuss those approaches and their pros and cons.

In the second half of the 19th century new methods for quarrying and processing natural stone are developed. In the Nordic countries Sweden, Norway and Finland this technological pro­gress goes hand in hand with a systematic geological mapping and large-scale exploitation of natural stone deposits. As a result, new constructions are developed—changing the building practice in these countries. With the end of historicism a new architecture arises that particularly in Norway and Finland acquires a national-romantic character. This paper examines the interaction between geological exploration, commercial development, technical inventions and the development of a national-romantic architecture.

The accurate wellbore pressure control not only prevents from lost circulation/blowout and fracturing formation by managing density of drilling fluid, but also improves productivity by mitigating reservoir damage. The geothermal pressure calculated by constant parameters for geothermal well would bring big error easily, as the changes of physical, rheological and thermal properties of drilling fluids with temperature were neglected. This paper researches the wellbore pressure coupling by calculating the temperature distribution with existed model, fitting the rule of density of drilling fluid with temperature and establishing mathematical models to stimulate the wellbore pressures, which is expressed as the variation of Equivalent Circulating Density (ECD) under different conditions. With this method, temperature and ECDs in the wellbore of the first medium-deep geothermal well ZK212 Yangyi Geothermal Field in Tibet were determined, and the sensitivity analysis was simulated by assumed parameters, i.e. circulating time, flow rate, geothermal gradient, diameters of wellbore, rheological models and regimes, the results indicated the geothermal gradient and flow rate were the most influence parameters on the temperature and ECD distribution, and additives added in drilling fluid should be careful which would change the properties of drilling fluid and induce the temperature redistribution. To make sure the safe drilling, velocity of pipes tripping into the hole, depth and diameter of wellbore are considered to control the surge pressure.

According to many research groups, high glucose induces over production of superoxide anions, and reactive oxygen species (ROS) in general is the link between high glucose levels and the toxicities seen at cellular levels. Respiratory complex anomalies could lead to the production of ROS. Calcium [Ca2+], at physiological levels serves as a second messenger in many physiological functions. Accordingly, mitochondrial calcium [Ca2+]m overload leads to ROS production which could be lethal to the mitochondria through various mechanisms. The F1F0-ATPase (ATP syn-thase or complex V) is the enzyme that is responsible for catalyzing the final step of oxidative phosphorylation. It does so by coupling the translocation of protons in the mitochondrial in-termembrane space and shuttling them to the mitochondrial matrix for ATP synthesis to take place. Mitochondrial complex V T8993G mutation specifically blocks the translocation of protons across the intermembrane space thereby blocking ATP synthesis leading to Neuropathy, Ataxia and Retinitis Pigmentosa Syndromes (NARP). This study seeks to explore the possibility of [Ca2+]m overload mediating the pathological roles of high glucose in defective respiratory chain mediated mitochondrial stress. The NARP cybrids are the in vitro experimental models for the cells with F1FO-ATPase defects, these cells harbor 98% of mtDNA T8993G mutation. Their coun-terparts 143B osteosarcoma cell lines are the parental cell lines used for comparisons. We uncov-ered that, NARP cells mediated and enhanced the death of the cells (apoptosis) when incubated with hydrogen peroxide (H2O2) and high glucose respectively as depicted by the MTT assay of cell viability. Furthermore, using the fluorescence probe-coupled laser scanning confocal imag-ing microscopy, NARP cells significantly enabled mitochondrial reactive oxygen species (mROS) formation and enhanced the depolarization of the mitochondrial membrane potential (ΔΨm). Elucidating the mechanisms of sugar enhanced toxicity on mitochondria would help in the fu-ture to alleviate the symptoms of patients associated with (NARP) syndromes.

This review explores the challenges and emerging trends in pancreatic cancer therapy. In particular, we focus on the tumor microenvironment and the potential of immunotherapy in pancreatic cancer. We discuss novel strategies targeting the desmoplastic barrier and immunosuppressive cells to enhance immune cell infiltration and activation. Recent clinical trials, particularly those involving novel immunotherapeutic agents and tumor vaccines, are examined to understand their efficacy and limitations. This review aims to highlight the ongoing efforts to refine immunotherapy approaches for better patient outcomes.

Comprehensive next-generation sequencing (NGS) assays enable identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and lead to resistance mechanisms are reshaping precision oncology. We report, workflow, informatics validation of OncoIndx NGS platform – a comprehensive genomic profiling (CGP)-base assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot findings using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 1080 cancer related genes. We show the outcome in the form of -tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene rearrangements (fusion). OncoIndx® also enables tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). We show maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with high precision detection of actionable variants, validated by established reference standards.

Interrelationships between traditional dental variables are becoming more evident in far reaching aspects of life such as psychosocial interaction, self-esteem, overall health and even occupational performance. This study compares quality of life (QoL) in postmenopausal women (PMW) with poor oral health (POH) with QoL in PMW with good oral health. 200 randomly recruited PMW received a dental evaluation and completed Utian Quality of Life Survey. The participants were divided into POH and healthy groups based on dental exam. Mean scores were calculated for each QoL item, domain and the overall summary score. For each of the four parameters for periodontitis diagnosis, periodontitis patients’ QoL outcomes were compared to those of healthy patients using T-test with threshold of significance at p<0.05. QoL in all fields measured were significantly poorer in the POH compared to the healthy patients, occupational (19.95±5.35vs. 27.56±6.13), health (18.02±8.23 vs. 26.59 ±6.45), emotional (15.68±10.22vs. 21.15±9.15), sexual (6.2±5.98vs. 10.02±5.35), and total score (60.21±25.85 vs. 84.26±22.35). This study finds that PMW with POH, report significantly poorer quality of life. Clinicians caring for PMW should be aware of that oral health impacts QoL and make appropriate referral decisions for patients’ dental care. Keywords: Quality of Life, Oral Health, Post-menopause, Women

In the context of global climate change, the frequency of sudden natural disasters is increasing. Assessing traffic road damage post-disaster is crucial for emergency decision-making and disaster management. Traditional ground observation methods for evaluating traffic road damage are limited by the timeliness and coverage of data updates. Relying solely on these methods does not adequately support rapid assessment and emergency management during extreme natural disasters. Social media, a major source of big data, can effectively address these limitations by providing more timely and comprehensive disaster information. Motivated by this, we utilized multi-source heterogeneous data to assess the damage to traffic roads under extreme conditions and established a new framework for evaluating traffic roads in cities prone to flood disasters caused by rainstorms. The approach involves several steps: First, extracting the surface area affected by precipitation using a threshold method constrained by confidence intervals derived from microwave remote sensing images; Second, collecting disaster information from the Sina Weibo platform, where social media information is screened and cleaned. A quantification table for road traffic loss assessment was defined, and a social media disaster information classification model combining text convolutional neural networks and attention mechanisms was proposed (TextCNN-Attention Disaster Classification); Finally, matching traffic road information on social media with basic geographic data, visualizing the classification of traffic road disaster risk levels, and completing the assessment of traffic road disaster levels based on multi-source heterogeneous data. Using the "7.20" rainstorm event in Henan Province as an example, this study categorizes the disaster impact on traffic roads into five levels: particularly severe, severe, moderate, mild, and affected, as interpreted from remote sensing images. The evaluation framework for flood disaster traffic roads based on multi-source heterogeneous data provides important data support and methodological support for enhancing disaster management capabilities and systems.

Colorectal cancer is one of the most common causes of cancer mortality worldwide, and innovative drugs for the treatment of colorectal cancer are continually being revealed. 5-Fluorouracil (5-FU) is a common clinical chemotherapeutic drug. Acquired resistance to 5-FU is a clinical challenge in colorectal cancer. Parecoxib is a selective COX-2-specific inhibitor, which has been demonstrated to inhibit metastasis in colorectal cancers in our previous study. This study aimed to investigate the synergistic antimetastatic activities of parecoxib to 5-FU in human colorectal cancer cells and determine the underlying mechanism. parecoxib and 5-FU synergistically suppressed metastasis in colorectal cancer cells. Treatment with the parecoxib /5-FU combination induced an increase in E-cadherin and decrease in β-catenin. The parecoxib/5-FU combination could inhibit MMP-9 and MMP-2 expression and MMP-9 activity, and the NF-κB pathway might be suppressed as well. Mechanistic analysis denoted that the parecoxib/5-FU combination hindered the essential molecules of the PI3K/Akt route to obstruct metastatic colorectal cancer. Furthermore, the parecoxib/5-FU combination could inhibit reactive oxygen species. Our work showed the antimetastatic capacity of the parecoxib/5-FU combination for colorectal cancers via targeting the PI3K/Akt /NF-κB pathway.

In this study, the separation conditions of UHPLC-QTOF-MS and the extraction conditions of QuEChERS were optimized. The analytical process for determining Broflanilide residues in different soil types was successfully established and applied to its adsorption, desorption and leaching in soil. Broflanilide was extracted from soil with acetonitrile as extraction solvent, and purified with 50 mg PSA + 150 mg MgSO4. The modified UHPLC-QTOF-MS method was used for determination. In different types of soil, the average recovery of Broflanilide was 87.7% -94.38%, and the RSD was lower than 7.6%. In the analysis and determination of the adsorption, desorption and leaching properties in four soils, the RSD was less than 9.2%, showing good stability and can be applied to the analysis and determination of the residue of Broflanilide in different soils.

In a bandsaw machine the blade guides provide additional stiffness and help to align the blade near the cutting region. Typically these are either in form of blocks made of carbide or ceramics or as sealed bearings. Abrasive particles, generated while cutting hard and brittle materials like natural stones, settle between the contact surfaces of the guides and the blade causing wear and premature failure. The hydrostatic guide system as presented in this work, is a contactless blade guiding method that uses force of several pressurized water jets to align the blade to the direction of the cut. For this investigation, cutting tests were performed on a marble block using a galvanic diamond coated bandsaw blade with the upper roller guides replaced by hydrostatic guides. The results show that the hydrostatic guides help to reduce the passive force while cutting to a constant near zero in contrast to the traditional guides. This also resulted in reduced surface roughness of the stone plates that were cut indicating a reduction in lateral vibration of the band. Additionally, it has also been shown that using hydrostatic guides the bandsaw blade can be tilted to counter the bandsaw drift opening opportunities for further research in active alignment control. This original research work has shown that the hydrostatic guide systems are capable of replacing and in fact perform better than state of the art bearing or block guides particularly for stone cutting applications.

Liver X receptors (LXR) are deemed as potential drug targets for atherosclerosis, whereas a role in adipose tissue expansion and its relation to insulin sensitivity remains unclear. To assess the metabolic effects of LXR activation, C57BL/6 mice on a high-fat diet (HFD) were treated with the dual LXRα/β agonist T0901317 (30 mg/kg per day) for 3 weeks. Differentiated 3T3-L1 was used for analysing the effect of T0901317 on glucose uptake.T0901317 reduced fat mass, accompanied by a massive fatty liver and lower adipokine levels in circulation of HFD mice. Increased adipocyte apoptosis and macrophage infiltration were found in epididymal fat of T0901317-treated HFD mice. In addition, T0901317 treatment promoted basal lipolysis, but blunted the anti-lipolytic action of insulin. Furthermore, LXR activation antagonized PPARγ target genes in epididymal fat and PPARγ-PPRE binding activity in 3T3-L1 adipocytes. Although the glucose tolerance was comparable to that in vehicle-treated HFD mice, the insulin tolerance was significantly decreased in T0901317-treated HFD mice, indicating decreased insulin sensitivity by T0901317 administration, and which was further supported by impaired insulin signalling found in epididymal fat and decreased insulin-induced glucose uptake in 3T3-L1 by T0901317administration. These findings reveal that LXR activation impairs adipose expansion which contributes to decreased insulin sensitivity.

The construction industry, a vital sector of the global economy, is projected to grow significantly over the next 15 years. Despite its importance, this industry struggles with inefficiency, high costs, prolonged timelines, and substantial ecological impacts. These challenges have led governments to advocate for Building Information Modeling (BIM) to enhance Efficiency and sustainability through comprehensive digital representations of physical and functional characteristics. The effective integration of BIM technology hinges on the active participation of industry providers, raising the question of how these providers can positively contribute to improving BIM dimen-sions. This study investigates the potential of coopetition networks within the Portuguese Orna-mental Stone industries (OS-PT) to address this challenge. Coopetition networks, which blend competition and cooperation, foster collaborative networks among companies to enhance their re-sponse to digital supply chains. The research employs an Experimental Pilot Network facilitated by an Industrial Internet of Things (IIoT) artefact to assess the benefits of coopetition networks. The findings demonstrate that transitioning from current practices (CB.P) to coopetition network practices (CN.P) significantly improves operational Efficiency, labour productivity, and sustaina-bility. Specifically, the transition resulted in a 15.6% increase in on-time delivery performance, a 27.38% improvement in labour productivity, and a 21.8% reduction in CO₂ emissions per part produced. These improvements align with Sustainable Development Goals (SDGs) 8, 9, 11, and 13, highlighting the strategic value of coopetition in driving innovation and sustainability in the construction industry. Future research should explore the scalability of these findings across different sectors and further refine methodologies to maximize the benefits of coopetition net-works.

Previous literature has linked working for pay while attending university with negative academic and health outcomes, yet working students are often resilient when experiencing such adverse circumstances. This makes it crucial to explore potential psychological mechanisms which transform adverse experiences into sources of motivation and persistence for working students. We explore one mechanism – social identification – and its different foci – identifying as a student, employee, working student, or as a student of one’s discipline of study – as potential predictors of important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes in three cross-sectional studies. In Study 1, part-time working hours (but not identification processes) were associated with academic self-efficacy. In Study 2, discipline identification and part-time working hours were associated with using deep approaches to learning. In Study 3, student identification was associated with increased status in society. Overall, discipline identification may be solely linked to academic outcomes, yet student identification should be explored further as a potential enhancer of social and graduate outcomes. We discuss additional mechanisms which can help to transform working students’ experiences through their social identities and suggest boundary conditions which can affect the link between these identities and important outcomes.

This paper deals with identifying the accident black spots and the influencing factors causing accidents using factored analysis in the medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the black spots and the factors causing accidents was used for analysis. The most influencing factors driving the accident were identified and ranked based on the repetitive occurrence of accidents in the black spot area. The spearman ranking system obtained the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners to understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.

Hydrological processes are complex to compute on hilly areas when compared to the plain areas. Most of the hydrological model do not take into account the critical rainfall-runoff generation processes such as subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix requires detailed hillslope hydrological modelling. In present study, a hillslope experimental plot is designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the north western Himalayas, India where high intensity storm event occurs frequently. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through macropore dominated area has been estimated/analyzed on the pixel basis. Over the experimental hillslope plot, a rainfall simulator was installed to generate the rainfall intensity in the range of 15 to 150 mm/hr which represented the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at 100 mm and 300 mm depth at different locations of the plot to observe soil moisture variations. It was found that once the soil is saturated, it remains in the field capacity for next 24-36 hours. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. Dye infiltration test was also performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The surface runoff predicted using the developed hillslope hydrological model compared well with the observed surface runoff under high intensity rainfall conditions.

Hypoxia is a hallmark of solid tumors, including hepatocellular carcinoma (HCC). Hypoxia has proved to be involved in multiple tumor biological processes and associated with malignant progression and resistance to therapy. Transarterial chemoembolization (TACE) is a well-established locoregional therapy for patients with unresectable HCC. However, TACE-induced hypoxia regulates tumor angiogenesis, energy metabolism, epithelial-mesenchymal transition (EMT), and immune processes through hypoxia-inducible factor 1 (HIF-1), which may have adverse effects on the therapeutic efficacy of TACE. Hypoxia has emerged as a promising target for combination with TACE in treatment of HCC. This review summarizes impact of hypoxia on HCC tumor biology, adverse effects of TACE-induced hypoxia on its therapeutic efficacy, highlighting the therapeutic potential of hypoxia-targeted therapy in combination with TACE for HCC.

Cranberries are rich in bioactive constituents reported to influence a variety of health benefits, ranging from improved immune function and decreased infections to reduced cardiovascular disease and more recently cancer inhibition. A review of cranberry research targeting cancer revealed positive effects of cranberries or cranberry derived constituents against 17 different cancers utilizing a variety of in vitro techniques; whereas, in vivo studies supported the inhibitory action of cranberries toward cancers of the esophagus, stomach, colon, bladder, prostate, glioblastoma and lymphoma. Mechanisms of cranberry-linked cancer inhibition include cellular death induction via apoptosis, necrosis and autophagy; reduction of cellular proliferation; alterations in reactive oxygen species; and modification of cytokine and signal transduction pathways. Given the emerging positive preclinical effects of cranberries, future clinical directions targeting cancer or premalignancy will be considered

Berberine (BBR), as a natural isoquinoline alkaloid, has been demonstrated various pharmacological activities, and widely applied in the treatment of diseases. The quantitative analysis of BBR is important for its pharmacological researches and clinical applications. In the work, utilizing the specific interaction between BBR and triplex DNA, a sensitive and selective fluorescent detecting method was established with DNA-templated silver nanoclusters (DNA-AgNCs). After binding with the triplex structure in the template of DNA-AgNCs, BBR quenched the fluorescence of DNA-AgNCs and formed BBR-triplex complex with yellow-green fluorescence. The ratiometric fluorescence signal showed a linear relationship with BBR concentration in a range between 10 nM to 1000 nM, with a detect limit of 10 nM. Our method exhibited excellent sensitivity and selectivity, and it was further applied in BBR detection in real samples.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

A general consensus is that the conventional linear modalities guarantee no industrial sustenance in long run for many obvious reasons. This is where the topicality of circularity has been accentuated for the last two decades or so in socio-political arena. However, anecdotal evidence suggests that the emphasis given to circularity in the construction industry is relatively low. Tackling this issue essentially warrants a rigorous co-production of integrated knowhow preferably beyond sectorial boundaries. The present study sheds light on interdisciplinary approaches taken to deal with the slowness in transmuting circularity into construction sector. A comprehensive literature survey was undertaken to understand this phenomenon at policy, firm and site level. The analysis included one hundred twenty-eight (128) articles published in high impact journals between 2003 and 2024. Eighty seven (87) gaps in terms of theory, knowledge, practice, method, empiricism and policy were observed. Forty four (44) thematic sub-clusters have the potential of empirical research. A new framework was finally proposed to scaffold the systemic transition towards a circular construction sector. On a practical level, the study offer valuable insights and instruments for the industry personnel to gauge the efficacy of their own circular approaches and initiatives.