In this study, a full-scale pilot testing was performed with side-by-side operation of a conventional enhanced biological phosphorus removal (EBPR) process and a side-stream EBPR (S2EBPR) process. A comparison of the performance, activities and population dynamics of key functionally relevant populations between the two configurations were carried out. The results demonstrated that, with the same influent wastewater characteristics, S2EBPR configuration showed more effective and stable orthophosphate (PO₄-P) removal performance (up to 94% with average effluent concentration down to 0.1 mg P/L) than conventional EBPR, especially when the mixers in side-stream reactor were operated intermittently. Mass balance analysis illustrated that both denitrification and EBPR performance have been enhanced in S2EBPR configuration through diverting primary effluent to anoxic zone and producing additional carbon (~40%) via fermentation in side-stream reactor. Microbial characterization showed that there was no significant difference in the relative abundances of Ca. Accumulibacter (~5.9%) and Tetrasphaera (~16%) putative polyphosphate-accumulating organisms (PAOs) between the two configurations. However, lower relative abundance of known GAOs was observed in S2EBPR configuration (1.1%) than the conventional one (2.7%). A relatively higher PAO activity and increased degree of dependence on glycolysis pathway than TCA cycle was observed in S2EBPR configuration using P release and uptake batch test. Adequate anaerobic solid retention time (SRT) and conditions that generate continuous and slow feeding/production of volatile fatty acid (VFA) with higher composition percentage of propionate in the side-stream reactor of S2EBPR process likely provide a competitive advantage for PAOs over GAOs.

Side-stream EBPR process (S2EBPR) is a new alternative to address the common challenges in EBPR related to weak wastewater influent and to improve EBPR process stability. A systematic evaluation and comparison of the process performance and microbial community structure between four S2EBPR with conventional EBPR configurations in US was conducted. The statistical analysis suggested higher performance stability in S2EBPR than the conventional EBPRs, although possible bias is recognized due to variations in the target permit levels and plant-specific factors among the plants. Total and known PAOs and GAOs abundance and identities were investigated with FISH, DAPI, 16S rRNA gene sequencing and Raman microspectroscopy. The results suggested comparable relative PAO and Candidatus Accumulibacter abundances in S2EBPR and conventional EBPR systems. Tetrasphaera, a putative PAO, was also found at similar abundance in S2EBPR as in conventional facilities, whereas the relative abundance of known GAOs was lower in S2EBPR than those typically seen at conventional EBPRs. Microbial community analyses via 16S rRNA gene amplicon sequencing revealed differences in the community phylogenetic fingerprints between S2EBPR and conventional plants. Shannon and Inverse Simpson indices, which are combined measures of richness and evenness evaluation of the microbial communities, suggested that the microbial diversity in S2EBPR plants were higher than those in conventional EBPRs.

Quantum computers are machines that are designed to use quantum mechanics in order to improve upon classical computers by running quantum algorithms. One of the main applications of quantum computing is solving optimization problems. For addressing optimization problems, we can use linear programming. Linear programming is a method to obtain the best possible outcome in a special case of mathematical programming. Application areas of this problem consist of resource allocation, production scheduling, parameter estimation, etc. In our study, we look at quantum speedup ratios of HHL Algorithm for different scenarios of linear programming. In a first scenario we look quantum speedup ratio (S(N)) as a function of phase transition and the ratio (κ) between the greatest and smallest eigenvalues of the matrix in linear equation system. As a second scenario, we investigate the changes in S(N) as a function of κ and s, which is the coefficient for defining the matrix as s-sparse.

Quantum computers are machines that are designed to use quantum mechanics in order to improve upon classical computers by running quantum algorithms. One of the main applications of quantum computing is solving optimization problems. For addressing optimization problems we can use linear programming. Linear programming is a method to obtain the best possible outcome in a special case of mathematical programming. Application areas of this problem consist of resource allocation, production scheduling, parameter estimation, etc. In our study, we looked at the duality of resource allocation problems. First, we chose a real world optimization problem and looked at its solution with linear programming. Then, we restudied this problem with a quantum algorithm in order to understand whether if there is a speedup of the solution. The improvement in computation is analysed and some interesting results are reported.

Dark pigmentation can be observed in various parts of the plant, ranging from foliage to petals to berries. The molecular basis of black pigmentation appears to vary among species, with anthocyanins playing a significant role, although specific anthocyanin types and their mechanisms differ. These findings suggest that the development of phenotypes is species-specific or varies between larger taxonomic groups; this is further supported by the polyphyletic nature of dark pigmentation. Additionally, several different regulatory mechanisms have been described for the occurrence of dark pigmentation. Firstly, the repression or knockout of the competing flavone biosynthesis has been shown to lead to darker pigmentation while another mechanism is based on the activation and upregulation of the anthocyanin biosynthesis genes in the presence of MYB transcription factors. Potential ecological functions of dark pigmentation were identified as the protection of the photosynthesis apparatus, camouflage against herbivores, and the attraction of pollinators. Promising industrial applications include microbial factories for the production of natural food colourants, induction of novel phenotypes for the ornamental plant industry and lastly the increase of anthocyanins within agriculturally relevant crops.

To meet the growing interest in the development of innovative biological nutrient removal (BNR) alternatives for energy neutrality, resource recovery, and decarbonization, the adsorption/bio-oxidation (A/B) process has been widely studied for carbon capture and shortcut nitrogen (N) removal, while limited research has focused on incorporating enhanced biological phosphorus (P) removal (EBPR), mainly due to the differential carbon usage characteristics of functionally relevant microorganisms. Here, a full-scale pilot testing with an integrated system combining A-stage high-rate activated sludge (HRAS) with B-stage partial (de)nitrification/anammox and side-stream EBPR (HRAS-P(D)N/A-S2EBPR) was conducted treating real municipal wastewater. The results demonstrated that, despite the low influent carbon load, the B-stage P(D)N-S2EBPR system achieved effective and stable P removal performance, especially when the volatile fatty acid (VFA) load from A-stage was elevated. Sludge fermentation in both A-stage and B-stage promoted carbon redistribution and likely provided more competitive advantages for ammonium-oxidizing bacteria and polyphosphate accumulating organisms, leading to carbon-efficient shortcut N removal mainly through partial nitrification pathway and influent carbon-independent EBPR simultaneously. Exposure to high VFA levels was considered a potential selection factor for the suppression of nitrite-oxidizing bacteria in the system. The involvement of internal carbon-accumulating organisms would potentially play an important role in endogenous denitrification. This study provided new insights into the effects of incorporating side-stream EBPR into the A/B process on microbial ecology, metabolic activities, and system performance.

Many fundamental molecular techniques (PCR, Microarray, Southern and northern hybridization, siRNA, CRISPR/Cas9 etc.) developed so far shows errors. I wish to highlight these molecular techniques are developed on basis of Watson-Crick DNA model, ignoring the concept of parallel stranded DNA. Through this opinion article, I wish to highlight specificity and accuracy of these molecular techniques can be enhanced by considering both parallel and anti parallel hybridization of DNA. Hopefully my views will also solve issue of irreproducibility in life science research.

In the preparation of polymer-clay nanocomposites the chemical incompatibility between the clay surface and polyolefins can be overcome by using clays organically modified with short chain organic cations. The compatibility can be further enhanced by using functionalized polymer that wets the clay surface while being miscible with the non-polar polymer matrix. In this work we tried to modify the host polymer polypropylene (PP) by irradiating it with gamma-rays in air knowing that it undergoes oxidation and chain scission simultaneously. Thus lower molecular weight PP with highly polar surface due to oxidation can be expected to play double role of clay modifier and functional compatibilizer. This has been observed to be the case. Finely ground PP granules were irradiated in air in a ⁶⁰Co γ-irradiator at the dose rate of 0.08 kGy/h (low dose rate to enhance oxidation) to 5, 10, and 20 kGy total doses. The extent of oxidation and change in molecular weight were determined by ATR-FTIR and Melt Flow Rate measurements respectively. PP/MMT nanocomposites were prepared by using 20% γ-PP, 1-5 % MMT and pristine PP to make up the total 100 in a torque rheometer. Maleated PP was also used in similar quantities to compare the effectiveness of γ-PP as a compatibilizing agent. Nanocomposites prepared with 10 kGy irradiated PP was found to show optimum mechanical properties among all formulations, with 26% increase in E-modulus and 10% increase in tensile strength as compared to pristine PP. Ternary PP nanocomposites were characterized by XRD, SAXS and PALS studies.

Background and objective: Analysis of inflammatory biomarkers, along with the neutrophil/lymphocyte ratio (NLR) or platelets/lymphocyte ratio (PLR), supports the connection between inflammation and carcinogenesis. Methods: We conducted a retrospective observational study at the Clinical County Hospital Mureș, including patients with lung cancer. The parameters analyzed included: histopathological type (NSCLC - squamous cell carcinoma or adenocarcinoma; SCLC), molecular mutations (EGFR, ALK, PD-L1), parameters from the complete blood count, inflammatory parameters and associated comorbidities. Results: 380 patients were included: 115 patients in the cancer group and 265 patients in the control group. Among patients in the lung cancer group, 88 were diagnosed with NSCLC (44 adenocarcinomas, 44 squamous cell carcinomas) and 27 with SCLC. Both NLR and PLR were significantly higher in cancer patients than in the control group (5,30 versus 2,60, p<0,001; 217 versus 136, p< 0.001, respectively). NLR and PLR differs between men and women (p = 0.005, respectively p=0.056). C-reactive protein was not correlated with either NLR (p-value: 0.0669) or PLR (p-value: 0.6733) in lung cancer patients. Conclusion: The NLR and PLR values ​​may serve as new predictive biomarkers for the diagnostic of disease in patients with lung cancer, especially those with NSCLC.

With recent advancements in network technology and spread of Internet, use of social network services and Internet of Things devices has flourished, leading to a continuous generation of large volumes of graph stream data, where changes, such as additions or deletions of vertices and edges occur over time. Additionally, owing to the need for efficient use of storage space and security requirements, graph stream data compression has become essential in various applications. Even though various studies on graph compression methods have been conducted, most of them do not fully reflect the dynamic characteristics of graph streams and complexity of large graphs. In this paper, we propose a compression scheme using provenance data to efficiently process and analyze large graph stream data. It obtains provenance data by analyzing graph stream data and builds a pattern dictionary based on this to perform dictionary-based compression. By improving the existing dictionary-based graph compression methods, it enables more efficient dictionary management through tracking pattern changes and evaluating their importance using provenance. Furthermore, it considers the relationships among sub-patterns using an FP-tree and performs pattern dictionary management that updates pattern scores based on time. Our experiments show that the proposed scheme outperforms existing graph compression methods in key performance metrics, such as compression rate and processing time.

The role that aquatic aerosols might play in inter-ecosystem exchange in freshwater riparian environments has largely been understudied. In these environments, where freshwater streams are used both as drinking water and for treated waste disposal, water features like waterfalls, downed trees, and increased streamflow can serve as bioaerosol producers. Such water features could have an important role in the bacterial colonization of surrounding surfaces, including the riparian phyllosphere. In this study, we explore the influence of a freshwater stream’s bacterial community composition and micropollution on riparian maple leaves exposed to bioaerosols produced from the stream. Using culture-based and non-culture-based techniques, we compared phylloplane microbial communities in riparian zones, adjacent non-riparian forested zones, and the surface waters of the stream. In this system, riparian zone maple leaf surfaces had higher bacterial counts than non-riparian zone trees. Using metagenomic profiling of the 16S rRNA gene, we found that, while microbial communities on leaves in both riparian zone and forested sites were diverse, riparian zone bacterial communities were significantly more diverse. In addition, we found that riparian leaf bacterial communities shared more amplicon sequence variants (ASVs) with stream bacterial communities than forest leaves, indicating that the riparian zone phyllosphere is likely influenced by bioaerosols produced from water surfaces.

Tinnitus is a common phantom auditory percept, believed to be related to plastic changes in the brain due to hearing loss. However, tinnitus can also occur in absence of any clinical hearing loss. Then, since there is no hearing loss, the mechanisms that drive plastic changes remain largely enigmatic. Previous studies showed subtle differences in sound-evoked brain activity associated with tinnitus in subjects with tinnitus and otherwise, normal hearing, but the results are not consistent across studies. Here, we aim to investigate those differences using monaural rather than binaural stimuli. Sound-evoked responses were measured using functional magnetic resonance imaging (MRI) in participants with and without tinnitus. All participants had clinically normal audiograms. The stimuli were pure tones with frequencies between 353 and 8000 Hz, presented monaurally. A Principal Component Analysis (PCA) of the response in the auditory cortex revealed no difference in tonotopic organization, which confirmed earlier studies. A GLM analysis showed hyperactivity in the lateral areas of the bilateral auditory cortex. Consistent with the tonotopic map, this hyperactivity mainly occurred in response to low stimulus frequencies. This may be related to hyperacusis, which was associated with tinnitus found in the parahippocampus. This may reflect an interference between tinnitus and spatial orientation.

Vitamin A, or retinol, is one of the most effective anti-ageing molecules, but it presents issues with photo-sensitivity and irritation. Retinol-like alternatives are emerging, but have so far been less effective. Here, we present a Silibum marianum extract (SME) as a retinol-like ingredient providing both safety and efficacy. SME was compared to the reference compound, retinol, and to the main alternative, bakuchiol. In ex vivo tests, skin explants from a 58-year-old donor were treated with pure retinol (0.1%), bakuchiol (0.2%) or SME (0.8%). After 5 days, collagen and hyaluronic acid levels were analysed. A placebo-controlled study involving 57 volunteers (ages 45-73 years) was also conducted, with products applied twice-daily for 56 days. Results were measured by AEVA-HE and VISA. Levels of collagen III were significantly increased by SME, by 23% and 16% compared to bakuchiol and retinol, respectively. Compared to bakuchiol, SME treatment increased hyaluronic acid production by 36%. In clinical tests, SME had a significantly stronger anti-wrinkle effect than bakuchiol – reducing the number of wrinkles on the forehead by 21%, and their circumference by 17% – producing effects similar to retinol, and better than bakuchiol. In the self-assessment, 43% of volunteers reported discomfort while using retinol, as compared to 0% for the SME formulation. By enhancing levels of collagen III – the youth collagen – and hyaluronic acid in the skin, SME paves the way for the maturation of collagen I fibrils and skin plumping. With its stronger efficacy compared to bakuchiol and enhanced safety profile compared to retinol, SME may be the next-generation of natural alternatives to retinoids.

A new mesogenic non-symmetric dimeric monomer with a terminal olefin function, forming a twist bend nematic (Ntb) as well as a nematic (N) phase was synthesized, using an enhanced synthetic methodology, which avoids isomerization of the terminal double bond in the preparation of the dimer. This monomer was attached to a pentamethyldisiloxane group, resulting in SmA LC phase behaviour of the ensuing material. Linking the monomer to a siloxane main chain resulted in nematic phase behaviour. Detailed studies with the Ntb phase forming dimer DTC5C7 show full miscibility of the dimer and the new LC polymer in the LC state, suggesting that the side-chain LC polymer forms a Ntb phase as the low temperature nematic phase. Copolymerizing the monomer with a cyanobiphenyl based monomer allows to tune the glass transition and phase behavior further.

Fractal array antennas are multiband arrays having ultra wide band and space filling facility. But Side lobe levels and large number of antenna elements are the major designing challenges of these arrays. In this paper, design and analysis of octagonal fractal array antenna is investigated with Morse-Thue fractal density tapering technique (MTFDT). Due to the proposed technique, a remarkable improvement has observed in Side lobe levels and thinning of the elements can also be attained at the various iterations of octagonal fractal array antenna. These arrays are analyzed and simulated by MATLAB-15 programming.

This paper deals with the merger of the two lightweight stream ciphers—A5/1 and Trivium. The idea is to make the key stream generation more secure and to remove the attacks of the individual algorithms. The bits generated by the Trivium cipher (output) will act as the input of the A5/1 cipher. The registers used in the A5/1 cipher will be filled by the output bits of the Trivium cipher. The three registers will then be connected to generate an output which will be our required key stream.

This review paper aims to understand the current processing plant maintenance systems and further identify on-stream phased array corrosion mapping (PACM) to reduce turnaround maintenance (TAM) activity during plant operations. Reducing the TAM duration and extending the TAM interval are common goals of most researchers. Thus, a detailed review was performed to understand the maintenance systems and the problems faced. Furthermore, a review of the current PACM application and the possibility of applying it during on-stream inspection was also per-formed. PACM has better detectability for localized corrosion, and the results can be obtained for a range of thicknesses, which is the main advantage of this method. The challenge is to apply it to a surface with high temperatures, owing to the greater probe contact and the limitation of ultrasonic properties. This literature review provides a more precise direction for future research to evaluate PACM on piping that can be utilized in inspection during plant operation at elevated temperatures. Detecting and monitoring corrosion growth without shutdown.

Biomimetic materials are substances that replicate natural structures. There are several methods for producing such materials with highly developed surfaces from a wide range of polymers, but electrospinning is of particular interest due to its simplicity of implementation and the ability to modify the produced fibrous materials resembling structures found in living organisms. This study explores new biomimetic materials based on polyhydroxyalkanoates, specifically poly-3-hydroxybutyrate, modified with chlorophyll derivatives. The research investigates the impact of chlorophyll derivatives on the morphology, supramolecular structure, and key properties of nonwoven materials. The obtained results are of interest for the development of new biomimetic environmentally friendly materials for biomedicine with special properties.

The research was conducted in the Kırklareli stream, which flows southwest through the city of the same name toward the village of Kavaklı. The aim of the study is to evaluate water analysis results and assess the potential that the European Union drinking water standard for lead can be achieved in the Kırklareli stream by reliance on the low solubility of lead phosphate minerals. The present study used Visual MINTEQ 3.1 for all water chemistry simulations. The European Union drinking water standard for lead, which is 10 μg L⁻¹, is exceeded at least once and as many as three times at seven of the ten sites during the 2018 sampling season. Although the database solubility of hydroxypyromorphite is exceeded in most samples, it appears this may be the result of major ion substitutions in the hydroxypromorphite that forms in the Kırklareli stream which increases the effective solubility of lead in the stream.

Pedestrian detection is the core of driver assistance system, which collects the road conditions through the radars or cameras on the vehicle, judges whether there is a pedestrian in front of the vehicle, supports decisions such as raising the alarm, automatically slowing down or emergency stopping to keep pedestrians safe, and improves the security when the vehicle is moving. Suffered from weather, lighting, clothing, large pose variations and occlusion, the current pedestrian detection still has a certain distance from the practical applications. In recent years, deep networks have shown excellent performance for image detection, recognition and classification. Some researchers employed deep network for pedestrian detection and achieve great progress, but deep networks need huge computational resources which make it difficult to put into practical applications. In real scenarios of autonomous vehicle, the computation ability is limited. Thus, the shallow networks such as UDN (Unified Deep Networks) is a better choice since it performs well on consuming less computation resources. Base on UDN, this paper proposes a new deep network model named as two-stream UDN, which augments another branch for solving traditional UDN’s indistinction of the difference between trees / telegraph poles and pedestrians. The new branch accepts the upper third part of the pedestrian image as input, and the partial image has less deformation, stable features and more distinguished characters from other objects. For the proposed two-stream UDN, multi-input features including HOG feature, Sobel feature, color feature and foreground regions extracted by GrabCut segmentation algorithms are fed. Compared with the original input of UDN, the multi-input features are more conducive for pedestrian detection since the fused HOG features and significant objects are more significant for pedestrian detection. Two-stream UDN is trained through two steps: First, the two sub-networks are trained until converge; then we fuse results of the two subnets as the final result and feed it back to the two subnets to fine tune network parameters synchronously. To improve the performance, Softplus is adopted as activation function to obtain faster training speed, and positive samples are mirrored and rotated with small angle to make positive and negative samples more balanced.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Artificial Intelligence (AI) in healthcare has ushered in a revolutionary era by transforming the way we provide care and reduce adverse consequences. This paper explores the field of AI applications in healthcare, including side effect management, streamlined administrative procedures, and customized treatment programs.

Integrating artificial intelligence (AI) and natural language processing (NLP) technologies with project-based learning experiences in Science,Technology, Reading, Engineering, Arts, and Mathematics (STREAM) education offers the potential to enhance student engagement, critical thinking,problem-solving, and interdisciplinary learning. This paper presents a comprehensive approach to implementing AI and NLP technologies, such as ChatGPT, in STREAM project-based learning experiences, highlighting the potential advantages and challenges of this innovative educational approach. The proposed method encompasses personalized learning pathways, AI-powered research assistance, collaborative AI tools, real-time feedback, virtual mentoring, advanced simulation, and objective assessment. We also discuss the implications of this integration for educators, institutions, and students, along with recommendations for future research and development in this emerging field.

Histones display a wide variety of post-translational modifications, including acetylation, methylation, and phosphorylation. These epigenetic modifications can influence chromatin structure and function without altering the DNA sequence. Histones can also undergo post-translational O-GlcNAcylation, a rather understudied modification that plays critical roles in almost all biological processes and is added and removed by O-linked N-acetylglucosamine transferase and O-GlcNAcase, respectively. This review provides a current overview of our knowledge of how O-GlcNAcylation impacts the histone code both directly and by regulating other chromatin modifying enzymes. This highlights the pivotal emerging role of O-GlcNAcylation as an essential epigenetic marker.

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

Hill stream loaches are a group of fish that inhabit fast flowing shallow freshwater. The family has radiated over Asia. For some species their range is limited to single catchments; they provide an excellent example of biogeographical speciation on multiple scales. Hill stream loaches have a range of adaptations which help them exploit environments where competitors and predators would be washed away. They have streamlined bodies and keeled scales reminiscent of Mako sharks and potentially many other as yet undiscovered drag reducing features. They adhere to rocks, crawl over shallow films of water, glide over hard surfaces using ground effects and launch into currents to attack prey or evade predation. They offer a test of modern approaches to organismal biology and a broad range of biomimetic potential. In this paper we analyse what behaviour is associated with their physical adaptations and how this might relate to their evolution and radiation. Our intent here is to review information that is presently available but also to derive new insight through combination and statistical analysis of existing material. We also use our own observations and critically argue several contradictory, or poorly supported assertions in the existing scientific literature. Our conclusion is that, although extensively studied, there remain major gaps in knowledge about their organismal biology. We summarise the research opportunities in the form of hypotheses that are worth testing.

Substance abuse is a significant public health issue both globally and nationally. Substance abuse involves the detrimental or risky consumption of psychoactive substances, posing a significant global issue, particularly among the youth. In India, cannabis abuse is a major concern. Cannabis is consumed legally in many states as Bhang, also known as marijuana or weed, while Charas and Ganja are illegal under both international drug conventions and the Indian NDPS Act of 1985. The Cannabis users are at great risk of developing Cannabis use disorder which is a pattern of problematic cannabis use leading to clinically significant impairment or distress. It is the most widely used illegal substance worldwide, showing a high prevalence in India.

Unmanned aerial vehicle (UAV) photogrammetry allows the generation of orthophoto and digital surface model (DSM) rasters of a terrain. However, DSMs of water bodies mapped using this technique often reveal distortions in the water surface, thereby impeding the accurate sampling of water surface elevation (WSE) from DSMs. This study investigates the capability of deep neural networks to accommodate the aforementioned perturbations and effectively estimate WSE from photogrammetric rasters. Convolutional neural networks (CNNs) were employed for this purpose. Two regression approaches utilizing CNNs were explored: direct regression employing an encoder and solution based on prediction of the weight mask by an encoder-decoder architecture, subse-quently used to sample values from the photogrammetric DSM. The dataset employed in this study comprises data collected from five case studies of small lowland streams in Poland and Denmark, consisting of 322 DSM and orthophoto raster samples. Each sample corresponds to a 10 by 10 meter area of the stream channel and adjacent land. A grid search was employed to identify the optimal combination of encoder, mask generation architecture, and batch size among multiple candidates. Solutions were evaluated using two cross-validation methods: stratified k-fold cross-validation, where validation subsets maintained the same proportion of samples from all case studies, and leave-one-case-out cross-validation, where the validation dataset originates entirely from a single case study, and the training set consists of samples from other case studies. The proposed solution was compared with existing methods for measuring WSE in small streams using a drone. The results indicate that the solution outperforms previous photogrammetry-based methods and is second only to the radar-based method, which is considered the most accurate method available. The solution is characterized by a high degree of explainability and generalization.

Autonomous Underwater Vehicles (AUVs) are emerging as pivotal tools in underwater applications such as seafloor exploration and the inspection of pipelines or cables. Traditional land-based avoidance methods prove insufficient when applied to the complex underwater environment, largely due to the unique constraints presented by marine environments and the specific dynamics of AUVs. In this study, we introduce an improved stream function-based obstacle avoidance algorithm specifically tailored for autonomous underwater vehicles. The proposed algorithm is based on a stream function that is derived from the stream function. The stream function is characterized by a radial histogram for the cost function. In addition, constraints related to the maximum path curvature are discussed to optimize the utility of the path. Our exhaustive simulation cases validate the robustness and adaptability of the proposed algorithm, demonstrating its ability to produce feasible and optimized avoidance paths in a variety of scenarios.

Live streaming conferences increase the participation of a diverse audience, help defray travel costs and overcome problems related to travel restrictions. In this article, we lay out tips for implementing live-streaming in scientific meetings. We also cover legal, ethical, and technical aspects implicated with live-streaming scientific talks. To write this article, we leveraged knowledge from our experience in organizing the symposium “Deciphering the Denisovans,” presented at the 88th Annual Meeting of the American Association of Physical Anthropology (AAPA) in Cleveland, OH, in 2019, as well as literature on the topic.

In previous work, a quantum mathematical formalism associated an element of experience with a single sensory neuron, as a local reduction of a global mental state. In contrast to the binary objective states of neuronal polarisation/depolarisation, neuronal experience was modeled as a continuous variable, the instantaneous value of which could only be estimated statistically from an ensemble of evoked responses to stereotyped stimulus presentation. In the present work, the quantum operations formalism of energy dissipation through amplitude damping is adopted to explain how smooth evolution of conscious experience might arise from discrete spikes and discontinuous synaptic transmission between neurons.

Introduction: In the recent years alternate day dosing has been recommended in iron deficieny treatment. The aim of this study is to compare the efficacy and side effects of oral iron treatments given daily 1x1, alternate day 1x1 and 2x1 alternate day dosing in iron deficieny anemia patients. Methods: A total of 52 patients with a diagnosis of iron deficiency anemia with serum ferritin level of 25 µg/L or less were included in this retrospective study. Statistical analyzes were done with SPSS V.25. Results: The patients included in our study were between the ages of 18-51. All of the patients included in the study were female. A statistically significant increase was found between 0-14 days(p<0.001), 14-28 days(p<0.001) and 0-28 days(p<0.001) hemoglobin values in all patients. There was no statistically significant difference between 0-14 days (p=0.397) and 0-28 days(p=0.310) ferritin values in all patients. A statistically significant difference was found between 14-28 days(p<0.001) ferritin values. When the rate of change of hemoglobin and ferritin values between the groups was compared and no statistically significant difference was observed between the groups. The rate of change of ferritin values for 14-28 days was significant (p=0.012). There was no significant difference in the frequency of symptoms in the 14th day and 28th day controls for each group (p>0.05). The incidence of metallic taste and bloating symptoms was found to be statistically significant in the third control in the group with 2x1 drug use alternate day (p=0.094). Discussion: The only difference in efficacy was observed in ferritin values between 14th and 28th days. The increase in ferritin values was higher in the group that used 1x1 oral iron every day. However, since no difference was observed between the groups in terms of ferritin and hemoglobin values on days 0 and 28, all three groups were considered equally efficient. Side effects were mainly gastrointestinal side effects. Since the group that received 2x1 oral treatment alternate day had a statistically significantly higher rate of side effects, the patients’ treatment tolerance will be lower compared to the other groups. In conlusion, there is no difference in efficacy and side effects between the patient groups receiving 1x1 daily and 1x1 alternate day oral iron therapy, so 1x1 use alternate day is the most appropriate treatment method for oral iron therapy in terms of patient tolerance, adherence to treatment and pharmacoeconomics.

The Chat Generative Pre-training Transformer (GPT), also known as ChatGPT, is a powerful generative AI model that can simulate human-like dialogues across a variety of domains. However, this popularity has attracted the attention of malicious actors who exploit ChatGPT to launch cyberattacks. This paper examines the tactics that adversaries use to leverage ChatGPT in a variety of cyberattacks. Attackers pose as regular users and manipulate ChatGPT’s vulnerability to malicious interactions, particularly in the context of cyber assault. The paper presents illustrative examples of cyberattacks that are possible with ChatGPT and discusses the realm of ChatGPT-fueled cybersecurity threats. The paper also investigates the extent of user awareness of the relationship between ChatGPT and cyberattacks. A survey of 253 participants was conducted, and their responses were measured on a three-point Likert scale. The results provide a comprehensive understanding of how ChatGPT can be used to improve business processes and identify areas for improvement. Over 80% of the participants agreed that cyber criminals use ChatGPT for malicious purposes. This finding underscores the importance of improving the security of this novel model. Organizations must take steps to protect their computational infrastructure. This analysis also highlights opportunities for streamlining processes, improving service quality, and increasing efficiency. Finally, the paper provides recommendations for using ChatGPT in a secure manner, outlining ways to mitigate potential cyberattacks and strengthen defenses against adversaries.

Blood stream infections (BSI) due to carbapenem-resistant gram-negative bacilli (CR-GNB), especially Klebsiella pneumoniae carbapenemase (KPC) and New-Delhi metallo-β-lactamase (NDM) producers, are a major concern of public health, as they are associated with high morbidity and mortality. We conducted a single-center, retrospective, observational study at a tertiary-care, teaching Greek hospital, to determine the incidence, 30-day and overall, in-hospital, crude mortality, risk factors and efficacy of best available treatment options in patients with BSIs from KPC- or NDM-producing GR-GNB. During the one-year study period, from 1st January to 31st December 2023, we recorded 133 episodes of BSIs in 118 unique patients; 79 episodes were due to KPC-producing and 54 to NDM-producing CR-GNB. Our study showed relatively high incidence of BSIs by both KPC- and NDM-producing CR-GNB (0.49 and 0.31 episodes per 1000 patient-days respectively). We found high 30-day crude mortality rates for patients with BSIs due to KPC- producing CR-GNB (26.4 %), and NDM-producing CR-GNB (37%), while BSIs due to NDM-producing P. aeruginosa had the highest 30-day (47.1%) and overall (70.6%) in-hospital, crude mortality. Beta-lactam/beta-lactamase inhibitors as monotherapy or in combination with other active agents used to treat KPC-producing CR-GNB were associated with improved survival rates (p=0.009).

Brain tumor being one of the major health hazards always needs a prompt diagnosis for the early treatment options to improve the chances of the survival of the patients. Traditional manual assessment of MRI (magnetic resonance imaging) to identify these conditions is a common practice. Hence, automation of the diagnosis practices can considerably improve the quality of the treatment procedures. In recent years almost every method for the automated diagnosis of brain tumor detection uses a deep learning technique. Despite decent works current techniques need a significant improvement to produce better results. Along with failure to produce decent results, the current deep learning models present very complex architectures which sometimes require huge computational resources. Therefore, in this paper we present a novel method that uses a lightweight dual-stream model with dual-input to detect brain tumors on MRI images. Both the inputs use different pre-processing mechanisms based on Contrast Limited Adaptive Histogram Equalization (CLAHE) and White Patch Retinex algorithm in order to enhance the feature learning capabilities of the proposed model. In addition, the proposed method uses a two-fold margin loss to boost training process for better feature learning. The proposed method produces state-of-the-art results for the detection of Glioma, Meningioma and Pituitary tumors. The model presents accuracy of 99%, 98% and 99% respectively for Glioma, Meningioma and Pituitary tumor detection.

Recent years have witnessed a rapid growth of code-reuse attacks in advance persistent threats and cyberspace crimes. Carefully crafted code-reuse exploits circumvent modern protection mechanisms and hijack the execution flow of a program to perform expected functionalities by chaining together existing codes. The sophistication and intrication of code-reuse exploits hinder the scrutinization and dissection on them. Although the previous literature has introduced some feasible approaches, effectiveness and reliability in practical applications remain severe challenges. To address this issue, we propose Horus, a data-driven framework for effective and reliable detection on code-reuse exploits. In order to raise the effectiveness against underlying noises, we comprehensively leverage the strengths of time-series and frequency-domain analysis, and propose a learning-based detector that synthesizes the contemporary twofold features. Then we employ a lightweight interpreter to speculatively and tentatively translate the suspicious bytes to open the black box and enhance the reliability and interpretability. Additionally, a functionality-preserving data augmentation is adopted to increase the diversity of limited training data and raise the generality for real-world deployment. Comparative experiments and ablation studies are conducted on a dataset composed of real-world instances to verify and prove the prevalence of Horus. The experimental results illustrate that Horus outperform existing methods on the identification of code-reuse exploits from data stream with an acceptable overhead. Horus does not rely on any dynamic executions and can be easily integrated into existing defense systems. Moreover, Horus is able to provide tentative interpretations about attack semantics irrespective of target program, which further improve system's effectiveness and reliability.

Tuberculosis (TB) is a leading infectious disease with serious antibiotic resistance. The benzothiazinone (BTZ) scaffold PBTZ169, an inhibitor of the decaprenylphosphoryl-β-D-ribose 2'-oxidase (DprE1) in Mycobacterium tuberculosis (Mtb), showed anti-TB potential in animal model and piloted clinical tests. Although highly potent, the BTZ type DprE1 inhibitors in general shows extremely low aqueous solubility, which adversely affect the drug like property. To improve the compounds physiochemical properties, we generated a series of BTZ analogues. Several optimized compounds had MIC values against Mtb in single digit nanomolar. The representative compound 37 displayed improved solubility and bioavailability compared to the lead compound. Additionally, compound 37 shows Mtb-killing ability in an acute infection mouse model.

This study purposes the use of plug-in electric vehicles for demand side management (DSM) considering uncertainties in demand as well as uncertainties due to mobility of PEV to mitigate peak demand. The solution also seeks to reduce electric cost in addition to reducing the effects of greenhouse gases. In recent years DSM using distributed storage system such as battery energy management system (BESS) and plugged-in electric vehicles (PEV) have become very prevalent with most implementations resorting to deterministic load forecast. These methods do not consider the potential growth in demand making their solutions less robust. In this study we propose a real-time density demand forecast and stochastic optimization for robust operation of PEV for a building. This method accounts for demand uncertainties in addition to uncertainties in mobile energy storage as found in PEV, making the resulting solution robust as compared to the deterministic case. A case study on a real site in South Korea is used for verification and testing. The proposed study is verified and tested against existing algorithms. The result verifies the effectiveness of the proposed approach

A Demand-side management technique are deployed along with battery energy-storage systems (BESSs) to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand

Even despite rapid advances in colorectal surgery, morbidity and mortality rates in elective gastrointestinal surgery play a significant role. For decades, there have been tempestuous discussions on preventive measures to minimize the risk of anastomotic dehiscence. When mechanical bowel preparation before elective procedure, one of the key hypotheses, has been introduced into practice, it was assumed that it would decrease number of infectious complications and anastomotic dehiscence. The advancements in antibiotic treatment supported concomitant administration of oral antibiotics and mechanical bowel preparation. In the prospective study conducted at our clinic, we performed left-side colorectal procedures without the prior mechanical preparation. All patients enrolled in the study underwent the surgery and had been observed in the 3rd Surgical Clinic, Faculty of Medicine, Comenius University in Bratislava, Slovakia, from January 2019 to January 2020. As a control group we used similar group of patients with MBP. Our observed group included 87 patients with tumors in the left part of their large intestine (lineal flexure, descendent colon, sigmoid colon, and rectum). Dixon laparoscopic resection was performed in 26 patients. Sigmoid laparoscopic resection was performed in 27 patients. In 12 patients, the procedure was started laparoscopically but had to be converted due to adverse anatomical conditions. The conservative approaches mostly included Dixon resections (19 patients), sigmoid colon resection (5 patients) and left side hemicolectomy (6 patients), and Miles´ tumor resection with rectal amputation (4 patients). Our study highlighted the fact that MBP does not have the unequivocal benefit for patients with colorectal infection, which has an impact on development of anastomotic dehiscence.

A method was developed to perform shape optimization of a tidal stream turbine hydrofoil using a multi-objective genetic algorithm. A bezier curve parameterized the refrence hydrofoil profoil NACA 63815. Shape optimization of this hydrofoil maximized its lift-to-darg ratio and minimized its pressure coefficient, thereby increasing the turbines power output power and improving its cavitation characteristics. The Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was employed to perform the shape optimization. A comparative study of two-and three-dimensional optimizations was carried out. The effect of varing the angle of attack on the quality of optimized results was also studied. predictions based on two-dimensional panel method results was also studied. Preditions based on a two-dimensional panel method and on a computational fluid dynamics code were compared to experimental measurments.

The central nervous system (CNS) is the final frontier in drug delivery because of the blood-brain barrier (BBB), which poses significant barriers to the access of most drugs to their targets. Kynurenic acid (KYNA), a tryptophan (Trp) metabolite, plays an important role in behavioral functions and abnormal KYNA levels have been observed in neuropsychiatric conditions. The current challenge lies in delivering KYNA to the CNS owing to its polar side chain. Recently, C-3 side chain modified KYNA analogs have been shown to cross the BBB; however, it is unclear whether they retain the biological functions of the parent molecule. This study examined the impact of KYNA analogs, specifically SZR-72, SZR-104, and the newly developed SZRG-21, on behavior. The analogs were administered intracerebroventricularly (i.c.v.), and their effects on the motor domain were compared with those of KYNA. Specifically, open field (OF) and rotarod (RR) tests were employed to assess motor activity and skills. SZR-104 increased horizontal exploratory activity in the OF test at a dose of 0.04 μmol/4 μL, while SZR-72 decreased vertical activity at doses of 0.04 and 0.1 μmol/4 μL. In the RR test, however, neither KYNA nor its analogs showed any significant differences in motor skills at either dose. Side chain modification affects affective motor performance and exploratory behavior, as the results show for the first time. In this study, we showed that KYNA analogs alter emotional components such as motor-associated curiosity and emotions. Consequently, drug design necessitates the development of precise strategies to traverse the BBB while paying close attention to modifications in their effects on behavior.

Since association between myocardial infarction (MI) and respiratory infections has been described for influenza-viruses and other respiratory viral agents, understanding possible physiopathological links between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and acute coronary syndromes (ACS) is of the greatest importance. First data suggest an underestimation of ACS cases all over the world, but acute MI still represents a major cause of morbidity and mortality worldwide and should not be overshadowed during the coronavirus disease (Covid-19) pandemic. No common consensus regarding the most adequate healthcare management policy for ACS is currently available. Indeed, important differences have been reported between the measures employed to treat ACS in China during the first disease outbreak and what currently represents clinical practice across Europe and the USA. This review aims to discuss: pathophysiological links between MI, respiratory infections, and Covid-19; epidemiological data related to ACS at the time of the Covid-19 pandemic; what emerged so far from several catheterization labs and coronary care units all over the world, in order to shed some light on the current strategies for optimal management of ACS patients with confirmed or suspected SARS-CoV-2 infection.

The large areas being targeted for tropical forest restoration as part of the UN Decade on Ecosystem Restoration will have major consequences for the flow of water through landscapes. Whilst the prevailing mantra that ‘more forest implies less streamflow’ remains true in terms of annual water yields, we demonstrate that opportunities for increased tree cover to improve seasonal flow regimes of streams, particularly baseflows, are important. We discuss several potential positive feedbacks of forest restoration on hydrological processes at various scales, including ‘trade-offs’ between changes in vegetation water use and infiltration after foresting degraded land; the recovery of the capacity of vegetation to capture ‘occult’ precipitation in specific coastal and montane settings; and enhanced moisture recycling and transport at various scales. Modelled changes in baseflow after foresting all degraded land climatically capable of carrying forest in the tropics suggested a positive effect in 10% of the land. For an additional 8%, the effect was predicted to be about neutral (<2 mm/y). We conclude that a more positive narrative regarding the relationship between tropical forestation and water availability is justified. It is time for greater involvement of hydrologists and atmospheric scientists in the development and assessment of forest landscape restoration efforts.

The study of dog point following has been increasingly popular, at least partially due to the initial claims that dogs outperform apes and the suggestion that our domestication process caused dogs to have a biological capacity to communicate with humans. We take the view that dog pointing is more complicated than was initially reported, and in this study, we explore several potential variables that may make a difference. Our variables include point type (ipsilateral (same-side) vs contralateral (cross-body) points), position (standing vs seated), and distance (proximal vs distal). We find that most dogs follow ipsilateral points while less than half of the dogs in our sample follow contralateral points, and that position and distance also affect dogs’ success. We suggest that dogs acquire ipsilateral points via associative mechanisms, but that contralateral points require the dogs to understand the humans’ communicative intent.

Pancreatic cancer leads the most common lethal tumor in America. This lethality is related to limited treatment options. Conventional treatments involve a non-specific use of chemotherapeutical agents like 5-FU, capecitabine, gemcitabine, cisplatine, oxaliplatine, or irinotecan, that produce several side effects. This review we focus on the use of targeted nanoparticles as an alternative to the standard treatment for the pancreatic cancer. The principal objective of the use of nanoparticles is the reduction in side effects that conventional treatments produce, mostly because of their nonspecificity. Currently, several molecular markets of pancreatic cancer cells have been studied to target nanoparticles and improve the actual treatment. Therefore, properly functionalizated nanoparticles with specific aptamers or antibodies can be used to recognize pancreatic cancer cells and once cancer is recognized, these nanoparticles can attack the tumor by drug delivery, hyperthermia, or gene therapy.

Bioluminescence – i.e., the emission of visible light by living organisms - is defined as a biochemical reaction involving, at least, a luciferin substrate, an oxygen derivative, and a specialised luciferase enzyme. In some cases, the enzyme and the substrate are durably associated and form a photoprotein. While this terminology is educatively useful to explain bioluminescence, it gives a false idea that all luminous organisms are using identical or homologous molecular tools to achieve light emission. As usually observed in biology, reality is more complex. To date, 11 different luciferins have indeed been discovered, and several non-homologous luciferases lato sensu have been identified which, all together, confirms that bioluminescence emerged independently multiple times during the evolution of living organisms. While some phylogenetically related organisms may use non-homologous luciferases (e.g., at least four convergent luciferases are found in Pancrustacea), it has also been observed that phylogenetically distant organisms may use homologous luciferases (e.g., parallel evolution observed in some cnidarians, tunicates and echinoderms that are sharing a homologous luciferase-based system). The evolution of luciferases then appears puzzling. The present review takes stock of the diversity of known “bioluminescent proteins”, their evolution and potential evolutionary origins. A total of 134 luciferase and photoprotein sequences have been investigated (from 75 species and 11 phyla), and our analyses identified 12 distinct types – defined as a group of homologous bioluminescent proteins. The literature review indicated that genes coding for luciferases and photoproteins have potentially emerged as new genes or have been co-opted from ancestral non-luciferase/photoprotein genes. In this latter case, the homologous gene’s co-options may occur independently in phylogenetically distant organisms.

There are introduced two new steganalytic methods not depending on the statistics of the cover objects, namely side attacks stegosystems. The first one assumes that the plaintext, encrypted before embedding, is known by the attacker. In this case, the stegosystem’s detection is based on the calculation of mutual information between message and extracted encrypted data. For this calculation, a notion of the k-nearest neighbor distance is applied. The second method is applied to HUGO, one of the most efficient steganographic algorithms. In this case the stegosystem’s detection is based on a verification of the NIST tests to the extracted encrypted messages. Moreover, we show that the problem to find a submatrix of­ the embedding matrix determining a trellis code structure in the HUGO algorithm provides a search of the stegokey of the proposed stegosystem.

: Kentucky is one of the largest coal producing states and surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas and vegetation change and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age, mining percentage, reclaimed forest percentage, and reclaimed woods percentage) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n=9), summer (n=14), and fall (n=58) 2017 to study changes in water quality variables (SO42-, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+,Fe3+) in response to changes in land cover. Pearson correlation analyses indicated conductivity has strong to very strong relationships with other variables of water quality variables related to coal mining (except Al3+, Fe2+,Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate multivariate regression analyses were performed with conductivity values based on samples collected in the fall. First, conductivity response to mining percentage, reclamation age and topographic variables were examined (adjusted R2=0.818, p &lt; 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p &lt; 0.01). Finally, reclamation age and mining percentage were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p &lt; 0.01) with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal Mine Related Stream Chemistry in areas where agriculture and urban development are limited. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining as well as refining land reclamation practices.

In this paper, we introduced a comprehensive study, based on both numerical and experimental analyses, of side polished (SP) single mode fibers (SMF) to investigate their evanescent field interaction with air and liquid analytes. In particular, the finite element method (FEM) and the beam propagation method (BPM) are employed to predict the optical properties of the SP-SMF. An ad-hoc experimental setup has been designed and built to characterize the side polished single mode fiber when air, water, and isopropanol are set in the side polished region. The sensitivity of the analytes is obtained as 1.207 V/RIU. The performance in terms of effective refractive index and transmittance are reported to show how these SP-SMF can be efficiently used for calculating the liquid refractive index. The simulation and experimental results display the significant performance of the SP-SMF as a sensing element.

Human activities and natural events alter the earth’s surface and pose a constant threat to the environment. Thus, accurately monitoring and predicting these changes in a timely manner is crucial to provide solutions and mitigate the environmental consequences beforehand. This research introduces a novel framework, called HCD-Net, for change detection using bi-temporal hyperspectral images. The framework is based on double-stream deep feature extraction and an attention mechanism. The first stream focuses on deep feature extraction through 3D convolution layers and 3D Squeeze-and-Excitation (SE) blocks. The second stream focuses on deep feature extraction through 2D convolution and 2D SE blocks. The extracted deep features are then concatenated and fed to dense layers for decision-making. The efficiency of HCD-Net is compared to the state-of-the-art change detection methods. Additionally, the bi-temporal Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) hyperspectral dataset was used for further evaluation of the change detection results. The results show that HCD-Net has a higher accuracy and the lowest false alarm rate, where the overall classification accuracy is above 96%, and the kappa coefficient is over 0.9.

Agricultural activities within watersheds can have negative effects on river ecosystems, but numerous conservation practices can be implemented that reduce soil erosion, increase water infiltration, slow runoff, and improve soil quality. Our study focused on analyzing overall stream health (instream and riparian physical, instream biological) at 56 stream sites within an agricultural watershed (83,000 hectares, 70% croplands and rangelands) with a 30+-year history of targeted conservation practices to protect local water resources of importance for tourism and recreation. After implementation of >900 best management practices (BMPs) over the last 20 years in the study subwatersheds, only 20% of the stream sites examined exhibited good stream health and 40% were in poor condition, based on a combination of instream and riparian factors and aquatic community integrity. Time since implementation, location, and total coverage of BMPs within the relatively large subwatersheds all may have contributed to the apparent limited effectiveness of these conservation management practices toward producing observable improvements in stream health to date. Many indicators of stream health (e.g., fine sediments, sediment embeddedness, fish biotic integrity) differed significantly among subwatersheds, but those differences could not be explained by differences in numbers or coverages of BMPs in those subwatersheds. Longitudinal stream health patterns were similar among subwatersheds (moderate health in headwaters, poor in mid-reaches, good in lower reaches), likely due, in part, to similarities in locations of spring discharges and channel instability. New rules protecting stream riparia, maintenance of existing BMPs, and future BMPs targeting remaining problem areas should lead to improving stream health in this large watershed.

We analyzed the peak spring tidal current speeds, annual mean tidal power densities (TPD) and annual energy production (AEP) obtained from experiment 06.1, referred as the "HYCOM model" throughout, of the three dimensional (3D), global model HYCOM in an area covering the Baja California Pacific and the Gulf of California. The HYCOM model is forced with astronomical tides and surface winds alone, and therefore is particularly suitable to assess the tidal current and wind-driven current contribution to in-stream energy resources. We find two areas within the Gulf of California, one in the Great Island Region and one in the Upper Gulf of California, where peak spring tidal flows reach speeds of 1.1 meters per second. Second to fifth-generation tidal stream devices would be suitable for deployment in these two areas, which are very similar in terms of tidal in-stream energy resources. However, they are also very different in terms of sediment type and range in water depth, posing different challenges for in-stream technologies. The highest mean TPD value when excluding TPDs equal or less than 50 W/m² (corresponding to the minimum velocity threshold for energy production) is of 172.8 W/m², and is found near the town of San Felipe, at (lat lon) = (31.006 -114.64); here energy would be produced during 39.00% of the time. Finally, wind-driven currents contribute very little to the mean TPD and the total AEP. Therefore, the device, the grid, and any energy storage plans need to take into account the periodic tidal current fluctuations, for optimal exploitation of the resources.

Single-sided deafness (SSD) refers to a condition where there is severe to profound Sensorineural hearing loss in one ear, while the other ear has normal or near-normal hearing. SSD can significantly impact an individual's ability to localize sounds, understand speech in noisy environments, and maintain spatial awareness, often resulting in a reduced quality of life and increased social isolation. In children with unilateral deafness, it can impede spoken language development and potentially impact cognitive abilities. Historically, there was a misconception that the unaffected ear could adequately support speech development in early cases and provide acceptable hearing function in adults. Consequently, SSD was frequently undertreated. However, advances in technology and a deeper understanding of the psychological and developmental impact of SSD have led to a shift in management strategies. Various treatment options are available for addressing SSD, but ongoing debate surrounds the most effective approach. These options include cochlear implants (CI), contra-lateral-routing-of-signal (CROS) devices, and bone conduction devices (BCDs). The aim of this study is to review the scientific evidence on different treatment options for SSD and compare their impact on the quality of life of individuals with this condition.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our intelligent image recognition system could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Τhe building automation control is a crucial factor for improving buildings energy efficiency and management, as well as improving the electricity grid's reliability indices. This paper presents the methodology, describes the necessary technology requirements and presents the decentralized building automation novel algorithm for Efficient demand side management in a building. All these are applied in an experimental university microgrid and the results are presented in terms of energy saving in kWh, money in € and working hours.

Spatial attentional biases can be observed during the processing of linguistic material. For example, we previously reported that healthy subjects overestimate the semantic distance between word stimuli in the right vs left space. Here we explored whether attentional biases are also observed in tasks requiring evaluation of phonological distance between words in the right and left hemispace. Forty-one healthy subjects were presented with triplets of words arranged in space and were asked to indicate the side of space in which the phonological distance between the middle word and an outer word was smaller. In Experiment 1 real words and pseudowords were used, while in Experiment 2 only pseudowords and consonant strings were used. Subjects overestimated the phonological distance between the middle and outer words in the right space. These findings were specific to word stimuli. These results are consistent with the idea that semantic and phonological information may be internally mapped onto spatial representations.

The combination of chemical cross-linking and mass spectrometry is currently a progressive technology for deriving structural information of proteins and protein complexes. In addition, chemical cross-linking is a powerful tool for stabilizing macromolecular complexes for single particle cryo-electron microscopy. Broad pallets of cross-linking chemistry, currently available for the majority of cross-linking experiments, still rely on the amine-reactive N-hydroxysuccinimide esters targeting mainly N-termini and lysine side chains. These cross-linkers are divided into two groups: water soluble and water insoluble; and research teams prefer one or another speculating on the benefits of their choice. However, the effect of cross-linker polarity on the outcome of cross-linking reaction has never been studied. Herein, we use both polar (bis(sulfosuccinimidyl) glutarate) and non-polar (disuccinimidyl glutarate) cross-linkers and systematically investigated the impact of cross-linker hydrophobicity on resulting distance constraints, using bovine serum albumin as a model protein.

With a view to sustainable development and circular economy, this work focused on the possibility to valorize a secondary waste stream of recycled carbon fiber (rCF) to produce a 3D printing usable material with PA6,6 polymer matrix. The reinforcing fibers implemented in the present research are the result of a double recovery action: starting with pyrolysis from which long fibers are obtained, used to produce non-woven fabrics and, subsequently, fiber agglomerate wastes obtained from this last process are ground in a ball mill. The effect of a different amount of reinforcement at 5% and 10% by weight on the mechanical properties of 3D printed thermoplastic composites was investigated. Although the recycled fraction was successfully integrated in the production of filaments for 3D printing and therefore in the production of specimens via Fused Deposition Modeling technique, the results showed that fibers did not improve the mechanical properties as expected, due to an unsuitable average size distribution and the presence of a predominant dusty fraction ascribed to the non-optimized ball milling process. PA6,6 + 10 wt.% rCF composites exhibited a tensile strength of 59.53 MPa and a tensile modulus of 2.24 GPa, which correspond to an improvement in mechanical behavior of 21 5 % and 5 21 % compared to the neat PA6,6 specimens, respectively. The printed composite specimens loaded with the lowest content of rCF provided the greatest improvement in strength (+ 9% over the neat sample). Then, a prediction of the “optimum” critical length of carbon fibers was proposed that could be used for future optimizations of the recycled fiber processing.

Sign Language Recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. Researchers still face challenges developing efficient SLR systems because of the video’s complex background, light illumination, and subject structures. Recently many researchers developed a skeleton-based sign language recognition system to overcome the subject and background variation of hand gesture signs. However, skeleton-based SLR is still under exploration due to the lack of information and annotations on hand key points. More recently, researchers included body and face information with the hand gesture for the SLR, but their performance and efficiency are unsatisfactory. We proposed a Multi-Stream Graph-based Deep Neural Network (SL-GDN) for a skeleton-based SLR system to overcome the problems. The main purpose of the proposed SL-GDN approach is to improve the efficiency and performance of the SLR system with a low computational cost based on the human body pose in the form of 2D landmark locations. In the procedure, firstly, we constructed a skeleton graph based on the selected 27 whole-body key points among 67 key points to solve the inefficiency problems. Then we proposed multi-stream SL-GDN to extract features from the whole-body skeleton graph for four streams. Finally, we concatenated the four different features and applied a classification module to refine the feature and recognize corresponding sign classes. Our data-driven and graph construction method increases the system’s flexibility and brings high generability to adapt various data samples. We used three large-scale benchmark SLR datasets to evaluate the proposed model: WLASL, AUTSL and CSL. The demonstrated performance accuracy table proved the superiority of the proposed model, and we believe this will be considered a great invention in the SLR domain.

The paper presents a synthesis of deep eutectic solvents (DESs) based on choline chloride (ChCl) as hydrogen bond acceptor and phenol (Ph), glycol ethylene (EG), and levulinic acid (Lev) as hydrogen bond donors in 1:2 molar ratio. DESs were successfully used as absorption solvents for removal of dimethyl disulfide from (DMDS) from model biogas steam. Several parameters affecting the absorption capacity and absorption rate has been optimized including kind of DES, temperature, the volume of absorbent, model biogas flow rate, and initial concentration of DMDS. Furthermore, reusability and regeneration of DESs by means of adsorption and nitrogen barbotage followed by the mechanism of absorptive desulfurization by means of density functional theory (DFT) as well as FT-IR analysis were investigated. Experimental results indicate that the most promising DES for biogas purification is ChCl:Ph, due to high absorption capacity, relatively long absorption rate, and easy regeneration. The research on the absorption mechanism revealed that van der Waal interaction is the main driving force for DMDS removal from model biogas.

The length of time it takes to experimentally make one-sided choppers, as found in the fossil record, bears a linear relationship to the knapping process of fabricating them. In addition, this temporal frame appears to be related to human heart rates measured as beats per minute, which act as a physiological metronome. We achieved these observations assuming that any paleolithic one-sided chopper has the information needed to estimate quantitatively the number of strikes on it. The experimental data allow us to establish the total timing needed for the standard fabricating of any one-sided chopper. We discuss issues derived from these experimental results, showing the evolution of human neurological abilities from 2.4 million years ago to the Modern period through the duration of time needed for making one chopper to that needed to play a 19th-century music score on a piano. Given that the neuronal and physiological distance between both actions differs by a factor of 6, we propose the concept of “technome” to measure human evolution by using methodological homogeneous metrics applied to these two human technologic objects, the chopper and the piano.

Yellow eels were sampled by electrofishing in 1979, 1980 and 1981 in Vester Vedsted Baeck, Denmark, stem 6 km, catchment 24 km², with outlet to the North Sea. Yellow eels were aged by burning the otoliths. The eels were not sexed, and they varied from 6.5 to 44 cm in length. The ages varied from 0+ to 10+ year. The annual growth rate ∆ varied from 3.4 cm for 0+ eel to 2.2 cm for 10+ eel with a mean of 3.1 cm. Body mass wet wt. was recalculated to Kcal energy, with an annual growth rate ∆ of 5.33 Kcal. In contrast to body mass, the annual growth rate ∆ in Kcal increased with age. Von Bertalanffy growth trajectory (cm) of length-at-age was calculated and L∞ = 118.4 cm. Annual natural mortality M was estimated, and M was significantly depending on body mass, i.e. high M and low body mass vs. low M at high body mass. The biological production was calculated to 13.5 g wet weight m^-2 year^-1. Total 780 eel stomachs were analyzed, of which 287 (37%) were empty. The weight of food content (2.1% of eel body mass) increased proportional with eel body mass. Chironomid larvae, Ephemeroptera nymph, Simulium larvae and Gammarus pulix were the dominating food taxa, followed by Trichoptera larvae. Size of prey were independent on length of eel.

Silver eel were sampled in 1981 and 1983 in River Brede, Denmark, with outlet to the North Sea. Yellow eel in River Køge-Lellinge, Denmark, with outlet to the Baltic Sea were sampled 1965-1968. Silver eel were aged by burning the otoliths. Silver male ages varied from 4 to 25 years, lengths 30.8 to 45.3 cm, and female silver eel varied from 7 to 25 years, lengths 42.3 to 77.3 cm. von Bertalanffy trajectories of length-at-age of male and female yellow eel were calculated in both rivers. Younger yellow eel had significantly higher annual growth rate compared to older age groups, and females grew significantly faster than males. Two models for natural mortality M were used to estimate number of glass eel needed to produce number of silver eel for each sex and silver age group. Annual silver eel production from River Brede Å was 49.2 kg ha-1, demanding 2,894 glass eel ha-1 and in River Køge-Lellinge, the silver eel production was 48.5 kg ha-1, demanding 5,570 glass eel ha-1. It was calculated that one (0.29 g) thousand glass eel contribute to 8.8 kg silver eel in River Køge-Lellinge, and 17.0 kg silver eel in River Brede. To fulfill the Danish EMP in rivers requires annual stocking of 33 tons or 9.4 million reared on-grown eel (3.5 g) to compensate for 183 tons lost silver eel.

The removal of sulfur from fossil fuels is one of the most important processes in modern refineries. It is accomplished via hydrodesulfurization (HDS) of the sulfur organic compounds in presence of heterogeneous catalysts. In the current work, heterogeneous catalysts containing cobalt and mo-lybdenum supported on mesoporous materials type SBA-15 and AlSBA-15 were synthesized for application in the HDS reactions of thiophene in n-heptane stream. The mesoporous materials were synthesized by hydrothermal method starting from TEOS, pseudobohemite, hydrochloric ac-id and water. Pluronic P123 was used as template. The best calcination conditions for removal of the organic template were optimized by thermogravimetry analysis (TG/DTG). The calcined SBA-15 and AlSBA-15 supports were submitted to co-impregnation with solutions of cobalt nitrate and ammonium heptamolybdate, aiming the production of 15% in mass of metal loading with atomic ratio of [Co/(Co+Mo)]=0.45. The obtained materials were dried and calcined for obtaining the mesoporous catalysts in the form of CoMo/SBA-15 and CoMo/AlSBA-15. The catalysts were char-acterized by XRD, TG/DTG, SEM and nitrogen adsorption. From XRD analysis, it was verified that after decomposition of the cobalt and molybdenun salts, were formed MoO3, Co3O4 and Co-MoO4 oxides on the supports, being attributed to these chemical species the activity for the HDS reactions. The activity of the obtained catalysts was evaluated in a continuously flowing tubular fixed-bed microreactor coupled on-line to a gas chromatograph, using n-heptane stream contain-ing 12070 ppm of thiophene (ca. 5100 ppm of sulfur) as a model compound. From the catalytic tests it was verified that the synthesized catalysts presented good activity for the reaction, and the main obtained products were cis- and trans-2-butene, 1-butene, n-butane and low amounts of iso-butane. The presence of 1,3-butadiene and tetrahydrothiophene (THT) were not detected. A mechanism of the primary and secondary reactions and subsequent formation of the olefins and paraffins, in the CoMo/SBA-15 and CoMo/AlSBA-15 mesoporous catalysts were proposed, con-sidering steps of desulfurization, hydrogenation, dehydrogenation, THT decyclization and isomerization.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our artificial intelligent image recognition system, AIIRS, could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Coronavirus disease 2019 (COVID-19) is a potentially serious acute respiratory infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Since the World Health Organization (WHO) declared COVID-19 a global pandemic, the virus has spread to more than 200 countries with more than 500 million cases and more than 6 million deaths reported globally. It has long been known that viral respiratory tract infections predispose patients to bacterial infections and that these co-infections often have an unfavourable clinical outcome. Moreover, nosocomial infections, also known as health care-associated infections (HAIs), are those infections that are absent at the time of admission and acquired after hospitalization. However, the impact of coinfections or secondary infections on the progression of COVID-19 disease and its lethal outcome is still debated. The aim of this review was to assess the literature on the incidence of bacterial co-infections and superinfections in patients with COVID-19. The review also highlights the importance of the rational use of antibiotics in patients with COVID-19 and the need to implement antimicrobial stewardship principles to prevent the transmission of drug-resistant organisms in healthcare settings. Finally, alternative antimicrobial agents to counter the emergence of multidrug-resistant bacteria causing healthcare-associated infections in COVID-19 patients will also be discussed.

Vaccination is one of the most effective methods for preventing morbidity and mortality from COVID-19. Vaccine hesitancy has led to a decrease in vaccine uptake; driven by misinformation, fear, and perceptions of vaccine safety. Whole inactivated vaccines have been used in one-fifth of the vaccine recipients in Africa, however there is limited real-world data on their safety. We evaluated the reported side effects and factors associated with reported side effects following vaccination with whole inactivated COVID-19 vaccines - BBiBP-CorV (Sinopharm) and CoronaVac (Sinovac). A quantitative survey evaluating attitudes and side effects from vaccination was administered to 1016 adults presenting at vaccination centers. Two follow-up telephone interviews were conducted to determine side effects after the first and second vaccination dose. Overall, the vaccine was well tolerated; 26.0% and 14.4% reported side effects after the first and second dose respectively. The most frequent local and systemic side effects were pain at the injection site and headaches respectively. Most symptoms were mild, and no participants re-quired hospitalization. Participants who perceived COVID-19 vaccines as safe or had a personal COVID-19 experience were significantly less likely to report side effects. Our findings provide data on the safety and tolerability of whole inactivated COVID-19 vaccines in an African population, providing the necessary data to create effective strategies to increase vaccination and support vaccination campaigns.

Myxobacteria generate natural products with unique chemical structures, which not only feature remarkable biological functions but also demonstrate unprecedented biosynthetic assembly strategies. The stigmatellins have been previously described as potent inhibitors of the mitochondrial and photosynthetic respiratory chain and originate from an unusual polyketide synthase assembly line. While previous biosynthetic investigations were focused on the formation of the 5,7-dimethoxy-8-hydroxychromone ring, side chain decoration of the hydrophobic alkenyl chain in position 2 was investigated less thoroughly. We report here the full structure elucidation as well as cytotoxic and antimicrobial activities of three new stigmatellins isolated from the myxobacterium Vitiosangium cumulatum MCy10943T with side chain decorations distinct from previously characterized members of this compound family. These findings provide further implications considering the side chain decoration of these aromatic myxobacterial polyketides and their underlying biosynthesis.

Renewable sources and electric distribution network can produce or make available a surplus of electric and thermal energies. The Intermediate Temperature Solid Oxide Electrolyzer (IT-SOE) fed by CO2-steam mixtures can store these electric and thermal energies producing CO-H2 mixtures with high conversion efficiency. Inside the IT-SOE, the CO2-steam mixtures are converted to CO-H2 mixtures and O2 through the cathode and anode electrochemical reactions and reverse water gas shift chemical reaction. In this article an IT-SOE stack fed by different types of steam mixtures was tested at different operating temperatures and the stack polarization and electric power curves were detected experimentally. At the highest hydrogen production operating temperature of the stack fed by steam mixtures, the experimental polarization and electric power curves of the stack fed by steam and CO2-steam mixtures were compared. A simulation model of the IT-SOE system (stack and furnace) fed by CO2-steam mixtures was formulated ad hoc and implemented in a Matlab environment and experimentally validated. At the highest hydrogen production stack operating temperature, the IT-SOE system thermal equilibrium current was evaluated through the simulation model. Moreover, the influence of this current on the IT-SOE system efficiency and the CO-H2 mixture degree of purity was highlighted.

Increasing of the imaging rate of conventional atomic force microscopy (AFM) is almost impossible without impairing of the imaging quality, since the probe tip tends to lose contact with the sample. We propose to apply the additional nonlinear force on the upper surface of a cantilever, which will help to keep the tip and surface in contact. In practice this force can be produced by the precisely regulated airflow. Such an improvement affects the AFM system dynamics, which were evaluated using a mathematical model presented in this paper. The model defines the relationships between the additional nonlinear force, the pressure of the applied air stream and the initial air gap between the upper surface of the cantilever and the end of the air duct. It was found that the nonlinear force created by the stream of compressed air (aerodynamic force) prevents the contact loss caused by the high scanning speed or higher surface roughness, and at the same time has minimal influence on the interaction force, thus maintaining stable contact between the probe and the surface. This improvement allows to effectively increase the scanning speed by at least 10 times using a soft (spring constant of 0.2 N/m) cantilever by applying the air pressure of 40 Pa. If a stiff cantilever (spring constant of 40 N/m) is used, the potential of accuracy improvement reaches 92 times. This method is suitable for use with different types of AFM sensors and can be implemented practically without essential changes in AFM sensor design.

Hillslope and mountain roads are often the source of erosion, which in turn can lead to larger landslides and other types of mass-movements. For this reason, low-cost repeat surveys that can be done by practitioners and not solely scientists and engineers is essential. To solve this issue the present contribution shows the testing and applicability of a mix of SfM-MVS and low-cost SLAM technology to provide erosion information. The low-cost SLAM generated between 300 ~ 900 points per square meter, while SfM-MVS created between ~11,000 to 900,000 points. The density is however a trade-off against a spatially varying error, although the variability at the road-cut scale only ranges from 2 cm vertically to 2.5 cm in x,y,z based on the C2C algorithm. Furthermore, this error tends to be more important in the higher section of the cutout (further away from the sensor and at a flatter angle). It is thus possible to measure small-scale roadside change, providing that the change is in the range of >5 cm (adding the maximum potential error twice) and providing that the road-cut is such that the sensors can be brought close to the surface (camera or sensor on a pole). The authors suggest that it can be a solution for state and agencies with limited funding and that cannot afford regular laser or for roadside that are difficult to access.

The Internet of Things (IoT) is experiencing exponential growth, revolutionizing various industries with its ability to connect devices and enable advanced applications. In the realm of energy production, IoT offers significant potential for optimizing processes and improving efficiency. This study presents a comprehensive monitoring and energy management strategy for the University of Cuenca's microgrid photovoltaic (PV) system, utilizing IoT and ThingSpeak as key technologies. The proposed strategy leverages intelligent environments and utilizes ThingSpeak as a robust platform for data presentation and analysis. By integrating IoT devices and sensors, real-time monitoring of PV system parameters such as solar radiation and temperature is achieved. The collected data is then analyzed using advanced algorithms and visualized through ThingSpeak, enabling effective energy management and decision-making. The developed monitoring system was rigorously tested in a laboratory microgrid setting, where the PV system is interconnected with other generation and storage systems, as well as the electrical grid. Through the seamless integration of these components, the monitoring system provides enhanced visibility and control over the microgrid's energy production. The results demonstrate the successful implementation of the monitoring system, showcasing its ability to improve the supervision, automation, and analysis of daily energy production. By leveraging IoT technologies and ThingSpeak, stakeholders can access real-time data, analyze performance trends, and optimize energy resources.

Side-scan sonar (SSS) detection is a key method in applications such as underwater environmental security and subsea resource development. The use of acoustic images for seabed target detection has gradually become a mainstream underwater detection method. However, many existing detection approaches primarily concentrate on tracking the evolution path of optical image object detection tasks, resulting in complex structures and limited versatility. To tackle this issue, we introduce a pioneering Dual-Domain Multi-Frequency Network (D2MFNet) meticulously crafted to harness the distinct characteristics of SSS image detection. In D2MFNet, aiming at the underwater detection requirements of small scenes, we introduce a novel method for optimize and improve the detection sensitivity of different frequency ranges and propose a Multi-Frequency Combined Attention Mechanism (MFCAM). This mechanism amplifies the relevance of dual-domain features across different channels and space. Moreover, recognizing that SSS images can provide richer insights after frequency domain conversion, we introduce a Dual-Domain Feature Pyramid Network (D2FPN). By incorporating frequency domain information representation, D2FPN significantly augments the depth and breadth of feature information in underwater small datasets. Our methods are seamlessly designed for integration into existing networks, offering plug-and-play functionality with substantial performance enhancements. We have conducted extensive experiments to validate the efficacy of our proposed techniques, and the results showcase their state-of-the-art performance. MFCAM improves the mAP by 16.9% in the KLSG dataset and 15.5% in the SCTD dataset. The mAP of D2FPN was improved by 8.4% in the KLSG dataset and by 9.8% in the SCTD dataset. We will make our code and models publicly available at https://dagshub.com/estrellaww00/D2MFNet.

In this paper Brinkman type fluid over an infinite plate between side walls is being investigated. The flow is generated by oscillating shear stress of the bottom plate and the solutions are obtained by using Fourier integral transformation. The obtained results are presented in steady and transient states for both sin and cos shear stresses. The general solutions are reduced to some special cases corresponding, namely to the Brinkman type fluid over an infinite plate and flow of a Newtonian viscous fluid. Graphical illustrations are carried out to have in depth analysis of the involved physical parameters

The accumulation of process waste in the production line causes fluctuations, bottlenecks, and increased inventory in workstations disrupting process flow. In this paper, the aim is the use a simulated value stream mapping (SVSM) as a lean assessment tool for decision-making in the continuous improvement process to influence and provide consideration and consistency on productivity improvement in the production system. The proposed methodology applied discrete event simulation for production process operations improvement to eliminate non-value adding times and provides good quality products at the lowest cost and highest efficiency. The results are the analysis of the current state of the production system in a South African truck manufacturing industry small and medium enterprise (SMEs) as a potential solution for the production system future state. The identified non-value adding times in the 6 most critical workstations was eliminated by SVSM which resulted in a productivity improvement of 4%, most importantly bringing the productivity to 95% and total cycle time improvement to 451 for small units and 466 for large units. The results proposed combined VSM and Simulation techniques which enhance the LEAN application by DES to increase productivity and performance improvement to remain competitive in the global economy.

Komagataeibacter spp. have been used for the bioconversion of industrial wastes and lignocellulosic hydrolysates to bacterial cellulose (BC). Recently studies have demonstrated the capacity of Komagataeibacter spp. in the biotransformation of inhibitors found in lignocellulosic hydrolysates, aromatic lignin-derived monomers (LDMs) and acetate. In general, detoxification and BC synthesis from lignocellulosic inhibitors requires a carbon flow from acetyl-coA towards tricarboxylic acid and gluconeogenesis, respectively. However, the related molecular aspects have not yet been identified in Komagataeibacter spp. In this study, we isolated a cellulose producing bacteria capable of synthesizing BC in a minimal medium containing crude glycerol, a by-product from biodiesel production process. The isolate, affiliated to Komagataeibacter genus, synthesized cellulose in minimal medium containing glucose (3.3±0.3 g/L), pure glycerol (2.2±0.1 g/L) and crude glycerol (2.1±0.1 g/L). Genome assembly and annotation identified four copies of bacterial cellulose synthase operon and genes for redirecting the carbon from central metabolic pathway to gluconeogenesis. According to the genome annotations, a BC production route from acetyl-CoA, a central metabolic intermediate, was hypothesized and was validated using acetate. We identified that when K. rhaeticus ENS9b was grown in minimal medium supplemented with acetate, BC production was not observed. However, in presence of readily utilizable substrate, such as spent yeast hydrolysate, acetate supplementation improved BC synthesis.

Silver powder, as the primary component of solar silver paste, significantly influences various aspects of paste performance, including printing, sintering, and conductivity. Silver powders prepared using the liquid-phase reduction method exhibit different microstructures depending on whether the growth process is dominated by aggregation or crystalline growth. This study explores the impact of different silver powder microstructures on packing density and sintering activity. It is observed that polycrystalline aggregated silver powder possesses higher surface energy, lower packing density, and greater sintering activity. Investigation into the influence of different silver powders on the electrical conductivity, adhesion, and structural density of silver paste reveals that polycrystalline aggregated silver powder is more suitable for lower sintering temperature pastes, whereas crystalline growth-type silver powder is better suited for higher sintering temperature pastes, resulting in a denser sintered silver layer. Finally, an analysis of the impact of various silver powders on the aspect ratio and electrical performance of solar cell silver grid lines yields higher aspect ratios (0.40) and photoelectric conversion efficiency (19.26%).

Abstract: Because of outstanding heat resistance and processing qualities, benzoxazine resins are widely employed in a variety of applications. However, traditional benzoxazine resins still confront hurdles in today's engineering applications, such as can’t long-term service in high-temperature settings and inadequate toughness. Four alkyne-functionalized benzoxazines with phthalide side group and cyano group of varying molecular weights were produced in this study. Fourier trans-form infrared spectroscopy (FT-IR) and hydrogen nuclear magnetic resonance spectroscopy ( 1H-NMR ) were used to characterize the resin structure, and differential scanning calorimetry (DSC) was used to investigate the thermal curing kinetics at different warming rates, the apparent activation energy was 116.9 kJ/mol. In-situ FTIR was used to investigate the cure mechanism. Dynamic mechanical analysis (DMA) was used to evaluate the gelationation time of BOZ series resins at various temperatures, and the curing process was designed by combined the results of DSC. The Tg of the composites made using BOZ-1N21 as the matrix was 336°C, which was much higher than the Tg of the BP-a resin made with aniline, phenolphthalein, and formaldehyde (Tg=251°C). As a result, the resin system is expected to be employed in applications requiring high-temperature resistance and toughness.

A set of aromatic copolyimides was obtained by reaction of 4,4′-(hexafluoroisopropylidene) diphthalic anhydride (6FDA), and mixtures of the diamines 1,4-bis(4-amino-2-trifluoromethylphenoxy)-2,5-di-tert-butylbenzene (CF3TBAPB) and 3,5-diamino benzoic acid (DABA). These polymers were characterized and compared with the homopolymer derived from 6FDA and CF3TBAPB. All copolyimides showed high molecular weight values and good mechanical properties. The presence of carboxylic groups in these copolymers allowed their cross-linking by reaction with 1,4-butanediol. The crosslinked polymer films were extensively characterized and it was observed that the degree of crosslinking was low in the copolyimides possessing a small number of carboxyl groups. The degradation temperature of these crosslinked copolyimides was lower than their corresponding non-crosslinked ones. Glass transition temperatures were higher than 260 oC, showing the non-crosslinked copolyimides the highest values. Young moduli of these crosslinked showed values higher than 1.9 GPa, and slightly lower elongation at break when compared with the precursor copolyimides. All copolyimides (precursor, and crosslinked ones) films could be tested as gas separation membranes. It was seen that CO2 permeability values were around 100 barrer, having better selectivity than that of the homopolymer. Moreover, the plasticization resistance of the crosslinked material having a large number of carboxylic groups was excellent.

The object of this work is to determine the correlation on the Nusselt number on the individual rows of a four-row tubular finned heat exchanger with continuous fins with a staggered tube arrangement using CFD modelling. Correlations for calculating Darcy-Weisbach friction factors on individual tube rows were also determined. Relationships for the Nusselt number and friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature determined using experimental data. The maximum relative differences between the Nusselt number for a four-row exchanger determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube's outside diameter of 1,000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the friction factor for a four-row exchanger determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1,000 to 10% for a Reynolds number of 13,000. The CFD modeling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1,400, the Nusselt number for the first row in a four-row finned heat exchanger is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2,800 to 6,000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations on Nusselt numbers and friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.

In this paper, we synthesized MC(BeA-co-MMA) copolymer microcapsules through suspension polymerization. The pendent n-behenyl group of BeA is highly crystalline, and it acts as the side-chain in the structure of BeA-co-MMA copolymer. The highly crystalline n-behenyl side-chain provides BeA-co-MMA copolymer thermal-energy-storage capacity. In order to investigate the correlation between thermal properties and crystal structure of BeA-co-MMA copolymer, the effects of monomer ratio, temperature changing and changing rate, as well as synthesis method were discussed. The monomer ratio influenced crystal transition behavior and thermal properties greatly. The DSC results proved that when the monomer ratio of BeA and MMA was 3:1, MC(BeA-co-MMA)3 showed the highest average phase change enthalpy ΔH (105.1 J·g–1). It indicated that the n-behenyl side-chain formed relatively perfect crystal region, which ensured a high energy storage capacity of copolymer. All the DSC and SAXS results proved that the amount of BeA had a strong effect on the thermal-energy-storage capacity of copolymer and the long spacing of crystals, but barely on the crystal lamella. It was found that MMA units worked like defects in the n-behenyl side-chain crystal structure of BeA-co-MMA copolymer. Therefore, a lower fraction of MMA, that is, a higher fraction of BeA contributed to a higher crystallinity of BeA-co-MMA copolymer for providing a better energy storage capacity and thermoregulation property. ST(BeA-co-MMA) copolymer sheets with the same ingredients as microcapsules were also prepared through light-induced polymerization aiming at clarifying the effect of synthesis method. The results proved that synthesis method mainly influenced the copolymer chemical component, but lightly on the crystal packing of n-behenyl side-chain.

Identifying ambient noise-based (ANb) signatures of streams can help in the estimation of their erosive potential (EP) that promotes reverie landslides and soil losses in the fluvial valleys. This is particularly imperative on flooding or rainy days, leading to stronger erosion-prone conditions (colluvium and boulders) of the valley beds inferred from georadar attribute analysis. Developing such research direction can benefit the local communities, as is the case with the Cerrado region of Brazil, where these phenomena have high destructive potential with social, economic, and climatic implications. For the present study, a seasonal stream in the Federal District of Brazil was investigated by ANb monitoring supported by Ground Penetration Radar (GPR) for site characterization. The ANb monitoring was conducted (at a safe distance) with a seismometer over several durations of dry and rainy conditions. The power spectral density (PSDs) was computed as a function of several variables, including weather conditions (rainfall, wind speed, and pressure), time-frequency spectrograms, and ambient noise displacement root mean square (RMS). This analysis also considered the single station horizontal-to-vertical spectral ratio (HVSR), where rain, wind, pressure, river flow and anthropogenic signatures were evident (at selective frequency ranges). Multi-peaks that emerged on the HVSR curve were further analyzed to identify amplitude and frequency changes, and the three peaks shift on average to a lower position during the rainy period. The GPR amplitude and waveform variation features were attributed to the stratigraphy (i.e., the boundary between valid and invalid regions and coherence value) of the floodplain and regions susceptible to erosion (erosion-prone lithological spots). This approach provides the basis for non-destructive monitoring tools enabling the detection of 'seismic signatures' and weak spots of the fluvial channels for improving environmental management.

Multivariate predictive analysis of the Stream-Water (SW) parameters (discharge, water level, temperature, dissolved oxygen, pH, turbidity, and specific conductance) is a pivotal task in the field of water resource management during the era of rapid climate change. The highly dynamic and evolving nature of the meteorological and climatic features have a significant impact on the temporal distribution of the SW variables in recent days making the SW variables forecasting even more complicated for diversified water-related issues. To predict the SW variables, various physics-based numerical models are used using numerous hydrologic parameters. Extensive lab-based investigation and calibration are required to reduce the uncertainty involved in those parameters. However, in the age of data-informed analysis and prediction, several deep learning algorithms showed satisfactory performance in dealing with sequential data. In this research, a comprehensive Explorative Data Analysis (EDA) and feature engineering were performed to prepare the dataset to obtain the best performance of the predictive model. Long Short-Term Memory (LSTM) neural network regression model is trained using over several years of daily data to predict the SW variables up to one week ahead of time (lead time) with satisfactory performance. The performance of the proposed model is found highly adequate through the comparison of the predicted data with the observed data, visualization of the distribution of the errors, and a set of error matrices. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. This model can be transferred to other locations with proper feature engineering and optimization to perform univariate predictive analysis and potentially be used to perform real-time SW variables prediction.

The construction of large-scale water diversion projects alleviated effectively the current situa-tion of uneven distribution of water resources in China. However, due to the siltation of very fine sediment and organic matter on the side wall of the open channel, and the slow velocity of the side wall flow field, it is easy to produce epipelic algae, which affects water quality. For the prototype observation cannot be used to predict the series of flow in real time, and the mathe-matical model calculation is affected by parameter limitations, these two methods often cannot truly reflect the hydrodynamic characteristics of open channel with epipelic algae. Therefore, by referring to the design parameters of the water diversion project channel, this paper takes the epipelic algae growing on the side wall of the open channel as the research object, and uses the scale of 1:30 to carry out the generalized flume experiment. Through the analysis of the physical characteristics of the prototype sample, and the simulation of the cohesive force between the oblique side wall and the epipelic algae, the multi-group and multi-series hydrodynamic tests are carried out. The flow velocity distribution law and the development and change of the tur-bulent vortex on the side wall are analyzed. It has important scientific guiding significance and practical value for water quantity regulation water regulation and water quality safety protec-tion of long-distance projects.

Humans can recombine thousands of different facial expressions. This variability is due to the ability to voluntarily or involuntarily modulate emotional expressions, which, in turn, depends on the existence of two anatomically separate pathways. The Voluntary (VP) and Involuntary (IP) pathways mediate the production of posed and spontaneous facial expressions, respectively, and might also affect the left and right sides of the face differently. This is a neglected aspect in the emotion literature, where posed expressions instead of genuine expressions are often used as stimuli. Two experiments with different induction methods were specifically designed to inves-tigate the unfolding of spontaneous and posed facial expressions of happiness along the facial vertical axis (left, right) with a high-definition 3D optoelectronic system. The results showed that spontaneous expressions were distinguished from posed facial movements as revealed by relia-ble spatial and speed key kinematic patterns in both experiments. Moreover, VP activation pro-duced a lateralization effect: compared with the felt smile, the posed smile involved an initial acceleration of the left corner of the mouth, while an early deceleration of the right corner oc-curred in the second phase of the movement, after the velocity peak.

The current study investigated the use of two-dimensional spatial distribution mapping representing the chlorophyll-a level in a river generated via an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV). A domestically developed UAV (Remo-M, Uconsystem Inc., Korea) and a USV developed by our research team were used to collect data from the Nae Seong stream in Korea. An adaptation of the “Data Cleaner” tool was developed and used for USV data processing and analysis. The operation of the autonomous USV was successful. Four previously described indices for quantifying algal blooms in rivers were utilized to create chlorophyll-a images, the normalized difference vegetation index (NDVI), the normalized green red difference index, the green normalized difference vegetation index (GNDVI), and the normalized difference red edge index. The suitability of the linear regression analysis of the correlation between the spectral indices obtained using the UAV and the in situ chlorophyll-a data obtained using the USV was evaluated with the coefficient of determination (R2) at a significance level of p &lt; 0.001. In field application and correlational analysis the NDVI was strongly correlated with chlorophyll-a (R2 = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R2 = 0.74, p < 0.001). The map of chlorophyll-a was successfully quantified using the UAV and USV hybrid platforms.

Acemetacin (ACM) is a new non-steroidal anti-inflammatory drug with anti-inflammatory, analgesic, and antipyretic effects. However, the poor water solubility and gastrointestinal side effects limit its use. Recently, the co-amorphous (CAM) strategy has attracted great interest to improve solubility for poorly water-soluble drugs, and basic amino acids have the potential to protect the gastrointestinal tract. In order to develop highly efficient and low toxic ACM formulation, we propose to prepare ACM CAM, with basic amino acids (lysine, arginine and histidine) as co-formers, using a cryo-milling method. The solid-state behaviors of the ACM CAMs were characterized by polarizing light microscopy, differential scanning calorimetry and powder X-ray diffraction. Fourier transform infrared spectroscopy and molecular docking were carried out to understand the formation mechanism. Moreover, the gastro-protective effects of ACM CAMs were evaluated in a rat gastric ulcer model. The results demonstrated CAMs improved the dissolution rates of ACM compared with the neat amorphous counterpart. Furthermore, ACM CAMs are significantly effective in mitigating the ACM-induced gastric ulcer in rats, and the ulcer inhibition rates were almost 90%. More importantly, this study provided a useful method for mitigating drug-induced gastrointestinal damage and broadened the applications of drug-amino acid CAMs.

Power systems have been going through a barrage of transformations due to the recent developments in the field, such as deregulation and restructuring of the electric power supply chain, the proliferation of distributed generation (DG), and advancements in information and communications technologies. These have significantly impacted the approach to the planning, design, and operation of active distribution networks or systems. Due to this constant change, the system has become more complex to plan, maintain, and control. In this paper, the benefits, and challenges of active distribution systems relative to traditional passive and active distribution systems are evaluated and investigated while the management and operational characteristics of demand-side resources in Active Distribution Systems (ADS) are studied. In a typical ADS, there exist several vulnerabilities and threats that eventually pose a challenge in the control and automation of substations. These vulnerabilities and threats are reviewed, and potential mitigation measures are suggested. Also in this paper, the communication technologies, and their implementation in terms of control and automation capabilities in active distribution networks are also studied. From this work, it is concluded that communication technologies play an integral role in the realization of a more active distribution networks and that the internet of energy (IoE) is a major player in ADS in the reduction of faults due to human error, fast responses, and improving the stability of power supply. Cyber threats are also and will still be a continuous challenge in smart metering technologies and in substation automation systems (SAS) which will require frequent evaluation and mitigation measures so as not to prevent the power supply system from collapsing.

In recent years, the chiral biological effects of nanomedicines have become a subject of widespread interest. The research focus has been on understanding the influence of material chirality on cellular transcription and metabolism. Stress granules are membraneless organelles formed through liquid-liquid phase separation of G3BP1 proteins and related compartments. They have been extensively studied and proven to be closely associated with cellular damage repair and metabolism. However, the role and mechanism of chiral nanomaterials in modulating stress granules remain unknown. The aim of this study was to investigate the expression and structural characteristics of stress granules under the individual influence of chiral nanomaterials and in combination with chemotherapy. To achieve this, we constructed a library of chiral ligand-modified materials and employed immunofluorescence, live-cell imaging, and fluorescence recovery after photobleaching assays. We also used proximity labeling techniques combined with proteomics analysis to identify the protein corona adsorbed on the surface of the nanomaterials and explore their relationship with nanomaterial chirality. Our results demonstrate that the assembly of stress granules is chiral-dependent and can be regulated by chiral nanomaterials. Furthermore, we achieved enhanced chemotherapy sensitivity in cancer cells and protected normal cells by exploiting the chiral-dependent modulation of material assembly in stress granules. This study provides important insights into the regulation of membraneless cellular structures based on chiral biological effects.

We used atomistic molecular dynamics (MD) simulations to study polyelectrolyte brushes based on anionic α-L-glutamic acid and α-L-aspartic acid grafted on cellulose in the presence of divalent CaCl2 salt at different concentrations. The motivation is the search of the ways to control properties such as sorption capacity and the structural response of the brush to multivalent salts. For this detailed understanding of the role of side chain length, chemical structure and their interplay is required. It was found that in the case of glutamic acid oligomers, the longer side chains facilitate attractive interactions with the cellulose surface, which forces the grafted chains to lie down on the surface. The additional methylene group in the side chain enables side chain rotation enhancing this effect. On the other hand, the shorter and more restricted side chains of aspartic acid oligomers prevent attractive interactions to a large degree and push the grafted chains away from the surface. The difference in side chain length also leads to differences in other properties of the brush in divalent salt solutions. At a low grafting density, the longer side chains of glutamic acid allow the adsorbed cations to be spatially distributed inside the brush resulting in a charge inversion. With an increase in grafting density, the difference in the total charge of the aspartic and glutamine brushes disappears, but new structural features appear. The longer sides allow for ion bridging between the grafted chains and the cellulose surface without a significant change in main chain conformation. This leads to the brush structure being less sensitive to changes in salt concentration.

The rapid urban expansion requires an effective management of water resources in small basins, where data are often limited. This article addresses a combination of an empirical hydrological model and Steven Method, a flow extrapolation method that considers the morphological char-acteristics of the cross-section. It also proposes an approach for overcoming the challenges asso-ciated with the lack of information on small water basins in rural to urban transition. A rain-fall event occurred in Pau de Caixeta stream basin (33,7 km²), in the Federal District (DF), in De-cember 2022, was evaluated. The simulation was carried out on the decision support system, Analysis of Complex Basins (ABC), using the rainfall registred by the rain gauge instaled within the monitered area with 3 hours duration and 38 mm of total rainfall, in addiction to the mor-phological and hydraulics characteristics of the study section. The basin presented in this study, has a classification regarding land use: i) urban area: horizontal and vertical residential neigh-borhoods (in the study phase) and rapidly expanding urban infrastructure, ii) rural areas and iii) environmental preservation areas. The results were within the acceptable range of flow extrap-olation errors (16%), indicating the integration of the proposed approaches can guide the devel-opment of impact mitigation strategies and promote sustainable practices in sub-basins.

This work proposes a methodological approach applied to ephemeral gravel-bed streams to verify the change in the magnitude and frequency of hydrological events affecting the morphological dynamics and sediment budget in this type of channel. For the case study the Azohía Rambla, located in southeastern Spain, was chosen, emphasizing the research on two reference riverbed sections (RCRs): an upper one, with a predominance of erosion, and a middle one, where processes of incision, transport, and deposition converge. First, this approach focuses on relationships between peak discharges and sediment budgets during the period 2018 to 2022. For this purpose, water level measurements from pressure sensors, a One-Dimensional Hydrodynamic model, and findings from comparative analyses of high-resolution differential digital elevation models (HRDEM of Difference - HRDoD) based on SfM-MVS and LiDAR datasets were used. In a second phase the GeoWEPP model was applied to the period 1996-2022 in order to simulate runoff and sediment yield at the event scale for the watersheds draining into both RCRs. During the calibration phase a sensitivity analysis was carried out to detect the most influential parameters in the model and to confirm its capacity to simulate peak flow and sediment delivery in the area described above. Values of NS (Nash-Sutcliffe efficiency) and PBIAS (percent bias) equal to 0.86 and 7.81%, respectively, were found in the calibration period, while these indices were 0.81 and -4.1% in the validation period. Finally, different event class patterns (ECPs) were established for the monitoring period (2018-2022), according to flow stage and morphological channel adjustments (overtopping, bankfull and sub-bankfull, and half-sub-bankfull), and then retrospectively extrapolated to stages of the prior simulated period (1996-2018) from their typical sequences (PECPs). The results revealed a significant increase in the number of events and PECPs leading to lower bed incision rates and higher vertical accretion, which denotes a progressive increase in bed armoring and bank erosion processes.

An online survey assessed the awareness of Nelson region’s residents, comparing responses between those who experienced the installation and those who did not. Findings indicated that eco-art installations can significantly enhance public understanding of ALAN's environmental and health impacts. The installation successfully increased specific knowledge about ALAN, with 92% of visitors reporting learning something new, however overarching knowledge and levels of concern were largely similar between the groups. Emotional engagement was high, with 62% of viewers stating that the installation invoked an emotional response. While the study did not measure behavioural changes, 94% of festival participants found it at least ‘somewhat appropriate’ and 64% ‘very’ or ‘entirely appropriate’ to raise awareness of these issues at such events, suggesting a potential foundation for future action. This research underscores the promise of art-science collaborations in environmental education and public engagement.

Introduction: Fractures in older individuals are often caused by falls, with approximately 90% of hip fractures resulting from falls. The risk of falling increases with age, and while a significant portion of individuals over 65 fall at least once per year, only a small percentage of these falls result in hip fractures. Factors that influence the likelihood of a fracture occurring include the intensity of the fall and the quality of the bone, with lower bone mineral content increasing the risk of fracture. Older women, particularly those in their 70s, are significantly more prone to hip fractures and any type of fracture. Efforts to reduce the likelihood of falls or mitigate the associated trauma are more complex than treating osteoporosis, due in part to a lack of understanding of the causes and contributing factors of falls in older age.Methods: This study analyzed data from patients admitted to Carmel medical center with upper or lower limb fractures between 2017 and 2019 to determine the side of wrist fractures and compare it to patient age in order to examine whether there was a difference in the distribution of sides in distal radius fractures based on age and test the hypothesis that falls are more likely to occur on the left side due to the assumption that dominant hand gross motor skills are better preserved. The study received approval from the Institutional Helsinki Committee and used statistical analysis with a significance level of 0.05. Potential sources of bias include limited availability of reliable data for many patients and the risk of errors in fracture registration or diagnosis, although the small sample size is expected to minimize these biases.Results: In this analysis of patient data from 2019 to 2017, a binomial test found that the probability of breaking the left wrist is significantly greater than the probability of breaking the right wrist (p < 0.05), while a t-test found no difference in the distribution of fractures between the right and left wrists of the distal radius based on age (p = 0.2774). Discussion: The findings of the study are consistent with previous research, and indicate that there is no change in side preference for fractures with age. Conclusion: The probability of breaking the left wrist is approximately 1.5 times greater than the probability of breaking the right wrist.

Biorefining by enzymatic hydrolysis (EH) of lignocellulosic waste material due to low costs and affordability has received enormous interest amongst scientists as a potential strategy suitable for the production of bioactive ingredients and chemicals. In the present study, a sustainable and eco-friendly approach to the extraction of bound ferulic acid (FA) has been demonstrated using a single-step EH by a mixture of lignocellulose-degrading enzymes. For comparative purposes of the efficiency of EH, an online SFE-SFC-MS extraction and analysis approach was applied. The experimental results demonstrated up to 369.3 mg 100 g−1 FA released from rye bran after 48 h EH with Viscozyme L. The EH of wheat and oat bran with Viscoferm for 48 h resulted in 255.1 and 33.5 mg 100 g−1 of FA, respectively. The extraction of FA from bran matrix using the SFE-CO2-EtOH delivered up to 464.3 mg 100 g−1 of FA, though the extractability varied depending on the parameters used. The 10-fold and 30-fold scale-up experiments confirmed the applicability of EH as a bioprocessing method valid for industrial-scale. The highest yield of FA in both scale-up experiments was obtained from rye bran after 48 h of EH with Viscozyme L. In purified extracts, the absence of xylose, arabinose, and glucose as final degradation products of lignocellulose was proven by a HPLC-RID system. Up to 94.0% purity of FA was achieved by SPE using the polymeric reversed-phase Strata X column and 50% EtOH as eluent.

Let us all take a moment to talk, once again, about this new coronavirus pandemic that the world has been facing since November 2019 and about its global response. After a short period marked by the pandemic underestimation risk by most governments, the Western world went nuts and overreacted, most probably so as not to be accused of inaction. In many cases, the overall benefits of the chosen policies were not sufficiently questioned, which resulted in many side effects on global health .The medical motto “primum non nocere”, a moral principle everyone should at least consider following, was evidently not taken into account. It has been overlooked, and the virus has become an obsession, to the extent that nearly everything else, even the most valuable things in life, is still now under appreciated if not simply ignored. This review highlighted facts against this simplistic, one-dimensional view.

Two sufi women take part in activities related to sufism and create an attraction point in the secular side in Turkey.The most striking point is that both women do not wear headscarves although they are muslim women. This article attempts to show how sufi women Cemalnur Sargut and Hayatnur Artıran have idealized a Muslim woman's identity, the work they are doing to achieve this ideal, their attidue toward Rebublic values, and the effects of these attidues on their followers. This article was created from my doctoral thesis and based on Qualitative research which has been established on the basis of 2-year long participant observation and data obtained from in-depth and focus interviews. 31 women and 20 men were interviewed in depth and focus interviews.The main conclusions of my qualitative research are that the influence of theese sufi women is related with process of modernization by accelerating the establishment of the republic in Turkey. It seems that a perception has established concerning that “public apparency’’ of woman will disappear if the “apparency of body’’ disappears and the woman will return to its role which had relapsed into silence for centuries. Besides not using the headscarf, religious conversation have been created by theese sufi women in the balance of religion, philosophy and science and the fact that they are conducting their works under secular institutions such as foundations and associations have also been observed to have a very important effect on seculer side.