Antimicrobial resistance (AMR) poses a critical global health threat, leading to approximately 1.27 million deaths annually from infectious diseases resistant to existing antibiotics. Factors such as antibiotic misuse and environmental contamination have accelerated AMR, with the COVID-19 pandemic exacerbating the issue due to increased antibiotic usage. However, the development of new antibiotics has stagnated, with only a few approved in recent years, and many facing resistance. Among the priority pathogens identified by the WHO, Pseudomonas aeruginosa stands out as a significant concern due to its multidrug resistance and virulence. P. aeruginosa infections are challenging to treat due to intrinsic and acquired resistance mechanisms, as well as its ability to form biofilms. Additionally, P. aeruginosa produces a plethora of virulence factors, including proteases, siderophores, and toxins, further complicating treatment. Quorum sensing (QS) systems play a crucial role in regulating bacterial physiology and virulence factor expression. P. aeruginosa employs three QS systems, making it an attractive target for quorum quenching (QQ) strategies. Enzymes such as AHL lactonases, acylases, and oxidoreductases have shown promise in inhibiting QS, thus reducing virulence without impacting bacterial growth. Furthermore, natural QS inhibitors produced by various organisms offer potential therapeutic alternatives. Despite promising results in vitro, translating QQ strategies to clinical settings remains challenging. Nevertheless, QQ represents a novel approach in combating multidrug-resistant infections and warrants further investigation as a complementary therapeutic strategy alongside traditional antibiotics. This review summarizes enzymes with Qurorum Quenching activity evaluated against the pathogen P. aeruginosa and their potential applications in combination therapies.

Millions of children in developing countries face preventable deaths due to inadequate vaccination and malnutrition, in part due to insufficient monitoring and the absence of official identification. A reliable fingerprint recognition system can be a practical solution to address this issue. However, the scarcity of longitudinal fingerprint datasets for young children leads to unresolved questions regarding the earliest age for fingerprint biometric use, the frequency of enrollment required for reliable recognition, and the methods to accommodate agerelated changes. A few recent studies introduced high-resolution fingerprint scanners and showed promising recognition performance for young children. However, these studies were conducted on a small dataset over a shorter period with limited diversity; further evaluation of their finding is essential. This study assessed the effectiveness of a high-resolution contactless scanner in a controlled, diverse longitudinal dataset of children (0-15 years). Our results indicate that infants can be enrolled at five days old and reliably recognized after two months with a TAR= 100% @ FAR = 0.1%, and children aged 4-15 years can be recognized after one year with a TAR= 98.72% @ FAR = 0.1%.

The integration of artificial intelligence (AI) into academic settings in Sabah, Malaysia, is transforming education and research landscapes. While AI technologies promise to enhance teaching, learning, and scholarly activities, they also pose challenges such as ethical concerns and skill gaps among academic staff. This study addresses the multifaceted impacts of AI adoption on academicians in Sabah, focusing on two key research questions: the impact of AI-based intelligent tutoring systems on student engagement, learning outcomes, and educational equity, and the challenges and opportunities in building academicians' capacity to integrate AI technologies effectively. Through a multidisciplinary approach, incorporating insights from education, computer science, social sciences, and ethics, this research aims to evaluate the effectiveness of AI tools in educational settings and identify strategies for skill development and infrastructure support. The study recommends empirical assessments within Sabah's educational institutions, considering contextual factors and fostering collaborative partnerships with local communities. Professional development programs, collaboration with industry partners, and improved access to AI infrastructure are proposed strategies. Longitudinal studies and interdisciplinary research initiatives are suggested for future research, along with qualitative methods to capture diverse perspectives. Ultimately, by embracing a collaborative and multidisciplinary approach, Sabah's academic community can harness the transformative potential of AI to advance education, research, and scholarship while promoting ethical and inclusive practices.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

A proof is given showing the Collatz Conjecture is true for all positive integers. The proof was possible once the perspective of the proof was changed from looking at the pattern of the positive integers to looking at the conjecture rules. The conjecture rule for even numbers organizes all positive integers into unique sets and the rule for odd numbers interconnects the unique sets into dendritic pathways to “1.” Infinite loops, other than the minor 4-2-1 loop after reaching “1,” and pathways to infinity are shown to be mathematically impossible. The proof predicted a general equation that shows all positive integers ultimately reach a final value of “1," and calculates the values and locations of the odd positive integers during the iterations for each tested positive integer.

Blockchain technology has emerged as a necessity for the decentralization of payment methods and transactions, but it has brought with it many properties of distributed systems that have made it a crucial technology for overcoming some of society's challenges, especially in the context of decentralizing services, transparency of information, availability, and security. Its architecture and communication methods, although possessing some complex nuances to understand, particularly for the lay audience in the field of distributed systems, protocols, and computer networks. In this article, we will explore some topics of distributed systems related to blockchain technology.

In this paper is proposed an analytical technique which can be used to obtain the forced response of a cantilevered tube conveying fluid. Considering the pipe subjected to an arbitrary harmonic force either distributed or concentrated, an analytical solution is found using Green’s function method. The solution obtained of the closed form satisfies the differential equations in a classical sense. The presented method giving the exact solutions is more precise than the classical eigenfunction expansion or Galerkin’s method with no need to the eigenfunctions or eigenvalues.

Background: The resurgence of syphilis, primarily in MSM populations, has necessitated novel prophylactic strategies, such as the use of doxycycline post-exposure prophylaxis (doxy-PEP). However, the potential for increased doxycycline use to select for tetracycline resistance represents significant challenges in managing this sexually transmitted infection. This study aims to identify chromosomal mutations associated with tetracycline resistance in Spirochaetales to inform treatment strategies and surveillance measures.Methods: Whole genome sequences (WGS) from the Spirochaetales order, including 4,355 genomes, were analyzed for the presence of mutations in 16S rRNA and non-synonymous mutations in the rpsC and rpsJ genes. The study utilized WGS from GenBank® and sequence data from the PubMLST Treponema pallidum isolate collection. Genetic resistance to tetracycline was detected using a combination of BLASTN searches and gene-gene analysis. Results: A transition mutation TGA to TGG at positions 965-967 in the 16S rRNA gene was detected in 5.6% of Treponema spp. and 3.97% of Spirochaeta spp. genomes. The rpsJ gene exhibited a V57G amino acid substitution across a significant subset of Treponema spp. Notably, the V57K mutation was common in Spirochaeta spp. The rpsC gene had the H178Q mutation and was found to be present in the Spirochaetales bacterium.Conclusion: The identification of mutations associated with tetracycline resistance in Spirochaetales provides a foundation for the development of rapid molecular diagnostics and guides the clinical selection of antibiotics for syphilis treatment. This study underscores the complexity of antibiotic resistance mechanisms and the critical importance of surveillance in the era of antibiotic prophylaxis for STI management.

Parkinson's disease is a neurodegenerative disorder resulting from progressive damage to specific brain regions. Key symptoms encompass involuntary movements (tremor), slowness of movements (bradykinesia), and muscle rigidity. Although the precise cause remains uncertain, a combination of genetic and environmental factors is believed to contribute to its development. This study focuses on the interaction of the E3 ubiquitin-protein ligase parkin with natural compounds. Docking investigations revealed that Amentoflavone exhibited an excellent binding energy score of approximately -10 kcal/mol. The E3 ubiquitin-protein ligase parkin displayed a robust binding affinity with docked amentoflavone, evident from a high binding energy of -10 kcal/mol. Nonetheless, additional biological studies are crucial not only to validate its potential efficacy against Parkinson's and assess safety in terms of toxicity but also to perform further computational analyses confirming these preliminary assessments.

This study delves into the therapeutic potential of two natural compounds, Amentoflavone and Bilobetin, by investigating their interactions with the BPIFB4 protein. BPIFB4, a member of the BPI fold-containing superfamily, has been associated with various biological processes, particularly in longevity and cardioprotection( LAV-BPIFB4). Molecular docking analyses revealed promising binding energies for Amentoflavone and Bilobetin with BPIFB4, suggesting favorable interactions.Additionally by pKCSM database are showed the predicted toxicity properties of Amentoflavone and Bilobetin respectively.This research contributes to the growing body of knowledge on natural compounds and their therapeutic implications in the context of vital biological processes. However, these findings underscore the need for further investigations, including in vivo studies and clinical trials, to validate the observed effects and explore the translational potential of Amentoflavone and Bilobetin in promoting cardiovascular health and longevity.

Diabetes mellitus is acknowledged as a significant contributor to severe complications. The present work has explorated the potential role amentoflavone as an aldose reductase inhibitor through Docking Simulations. From these results this compound has shown excellent results with this enzyme with a high binding energy of -11 kcal/mol. If amentoflavone,a natural biflavonoid, proves effective in inhibiting aldose reductase, it could hold therapeutic promise for managing diabetic complications. However, it's crucial to emphasize that while computational studies offer valuable insights, experimental validation is essential to confirm the actual inhibitory effects and to establish the safety and efficacy of amentoflavone for this purpose. Further research and clinical studies are warranted to fully understand and harness the potential therapeutic benefits of amentoflavone in the context of diabetes.

Cells respond to DNA double-strand breaks by initiating DSB repair and ensuing a cell cycle checkpoint. The primary responder to DSB repair is non-homologous end joining, an error prone repair pathway. However, when DSBs are generated after DNA replication in the G2 phase of the cell cycle, a second DSB repair pathway, homologous recombination, can come into action. Both ATM and ATR are important for DSB-induced DSB repair and checkpoint responses. One method of ATM and ATR working together is through the DNA end-resection of DSBs. As a readout and marker of DNA end-resection, RPA is phosphorylated at Ser4/Ser8 of the N-terminus of RPA32 in response to DSBs. Here, the significance of RPA32 Ser4/Ser8 phosphorylation in response to DNA damage, specifically in S phase to G2 phase of the cell cycle is examined. RPA32 Ser4/Ser8 phosphorylation in G2 synchronized cells is necessary for increases in TopBP1 and Rad9 accumulation on chromatin and full activation of the ATR-dependent G2 checkpoint. In addition, our data suggest RPA Ser4/Ser8 phosphorylation modulates ATM-dependent KAP-1 phosphorylation and Rad51 chromatin loading in G2 cells.

Summary— Introduction: HIV (human immunodeficiency virus) is a virus that attacks and destroys one type of white blood cell, in particular, the CD4 lymphocytes, which are responsible for the body's immune response. This weakens the immune system to such an extent that it can no longer fight other viruses, bacteria, protozoa, fungi, and tumors. Methods: We investigated the potential biological role of the natural compound Polydatin (or piceid) using SwissDock, a web service to predict the molecular interactions that can occur between a target protein and a small molecule. Discussion: For the first time, we have investigated the role of polydatin against HIV-1 protease and HIV-2 protease through a computational approach by comparing their estimated ΔG values (kcal/mol) and the nature of the interactions between the residues in the catalytic center of the HIV proteases.Conclusion: From these simulations, Polydatin has excellent physical properties and an excellent estimated ΔG value (kcal/mol) of about -9.9 kcal/mol against HIV-2 protease and ΔG value (kcal/mol) of about -9.5 kcal/mol against HIV-1 protease. In addition, Polydatin was able to bind to two key amino acids of the catalytic triad sequence common to asparagine proteases (Asp25 and Gly27)

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in cancer cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways to include amino acid metabolism, one-carbon metabolism, pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates the metabolic reprogramming which has become the hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for development of a new generation of therapeutics to treat cancer.

This lecture aims to survey the existing literature on the dynamic urban growth. Theapplication in this lecture is a small step in the long iterative process between theconstruction of a model and its use for practical purposes. In this lecture, we follow thenotion of urban development and conduct an analysis of conceptual modeling phases ofurban development by Paeliuck (1970).

The Japanese city presents a certain number of peculiarities in the organization of its physical space (weak zoning regulations, fast piecemeal destruction/reconstruction of buildings and blocks, high compacity, incremental reorganization). Compared to countries where urban fabrics are more perennial and easily distinguishable (old centers, modern planned projects, residential areas, etc.), in Japanese metropolitan areas we often observe higher heterogeneity and more complex spatial patterns. Even within such a model, it should be possible to recognize the internal organization of the physical city. The aim of this paper is thus to study the spatial structure of the contemporary Japanese city, generalizing on the case study of Osaka and Kobe. In order to achieve this goal, we will need to identify urban forms at different local scales (building types, urban fabrics) and to analyze them at a wider scale to delineate morphological regions and their structuring of the overall layout of the contemporary Japanese city. Several analytical protocols are used together with field observations and literature. The results, and more particularly the building and urban fabrics types and their location within the Osaka-Kobe metropolitan area, are interpreted in the light of Japanese history and model of urbanization. A synoptic graphical model of an urban morphological structure based upon Osaka is produced and proposed as an interpretative pattern for the Japanese metropolitan city in general.

In this article, we investigate both the Schrödinger and continuity equations in the presence of nonlocal potential that arising from electron-electron interaction and local one in the context of minimal uncertainty in momentum within commutative and noncommutative frameworks. Furthermore, the Frahn–Lemmer potential type is used. Interestingly, the combined effects of both the phase-space noncommutativity and nonlocality on the current density while considering a minimal uncertainty in momentum are examined. We find that the current density, as conventionally defined, does not fulfil the condition of current conservation, thus, a new definition of the current density that encompasses the aforementioned contributions is given. Thereafter, it is shown that the computed current using the new definition of the current density satisfies the current conservation. Noting that using both the $★$product and linear Bopp-Shift, the noncommutativity is inserted.

We investigated and quantified bacterial accumulation in facemasks used by the general population, using 16S rRNA (Sanger Sequencing), culture and biochemical analysis along with Rose Bengal staining. Additionally, a systematic overview of the literature on face mask contamination was undertaken. We found an average bacterial load of 4.24 × 10⁴ CFU recovered/mask, with a maximum load of 2.85 × 10⁵ CFU. This maximum is 310 times higher than the limit value for contamination of ventilation system outlet surfaces specified by the German standard VDI 6022. Biochemical and molecular identification predominantly found Staphylococcus species (80%), including Staphylococcus aureus, along with endospore-forming Bacillus spp. Literature reports also indicate contamination of masks by bacterial and fungal opportunists of the genera Acinetobacter, Aspergillus, Alternaria, Bacillus, Cadosporium, Candida, Escherichia, Enterobacter, Enterococcus, Klebsiella (including K. pneumoniae), Micrococcus, Microsporum, Mucor, Pseudomonas, Staphylococcus and Streptococcus. Bacterial counts increase linearly with wearing duration, and prolonged use may affect the skin and respiratory microbiomes, promoting consequential eye, skin, oral and airway conditions. These aspects underscore the urgent need for further research and a risk-benefit analysis in respect of mask use, particularly given their unproven efficacy in disrupting the transmission of respiratory viruses and their adverse social consequences.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

India has pledged ambitious initiatives to mitigate its growing economies’ impact on the climate, including a goal of net zero emissions by 2070. The transportation sector is one of the key sources of emissions. Therefore, fostering e-mobility within this sector is a key priority for the Indian government. The lifecycle of LiBs raises numerous concerns regarding its sustainability in production, use of rare materials, and most importantly waste management. Furthermore, this paper will highlight the case for EV battery recycling as a growing sector that also has the potential to foster circularity in the EV sector. Through the introductory section, this paper lays out rationale for battery recycling in a circular EV economy. The subsequent sections discuss the current and emerging battery technologies and their link to recycling methods whilst overviewing domestic and foreign battery recycling companies. Finally, the paper concludes with a gap assessment of the battery recycling ecosystem in India and makes recommendations to further integrate this industry into the EV supply chain. As India steers towards a sustainable future, it is imperative that the country integrates battery recycling to enhance circularity in the EV ecosystem, closing the gap between a growing number of EVs and waste management.

This paper provides an overview of modelling and simulation methods for complex systems, including queuing and life support systems. To realize and capture every aspect of a system or situation, a model is used in place of the actual one. Using a model and simulation, we may create scenarios and make decisions. Computer experiments with the model can save costs, time, and effort once its validity has been shown. A model of the thing under study is created by computer simulation, which then runs the model on a digital computer and examines the results. It's interesting to note that a knowledge base of data includes information about predicted behaviour of the model as well as coordinated determination of external variables and parameters. Selecting the precise model creation technique is the first and most difficult task in simulation. A review of techniques used in simulation model execution (serial and parallel discrete-event simulation), simulation model analysis (calibration, validation, verification, goal-seeking), and conceptual, declarative, functional, constraint, and multimodal design are presented in this paper.

_{he present study was conducted to quantify the heavy metals cadmium, lead, copper, chromium, nickel, and zinc in the bivalve mollusk concha prieta (Anadara tuberculosa) using in- ductively coupled plasma optical emission spectroscopy (ICP-OES). This research aims to identify whether the bioaccumulate content of heavy metals exceeds the maximum limits established by various public health bodies such as the ONU, FAO, Codex Alimentarius, EEC, and NHI. Samples of the species were collected randomly from three locations in Puerto El Morro, Playas Municipal Market, and La Libertad Seafood Market in the Gulf of Guayaquil. Thirty-three soft tissue samples of (Anadara tuberculosa) were evaluated, and the values quantified in mg/kg were in the following order: Zn>Cu>Cd>Ni>Cr>Pb.}

This study focused on the investigation of myeloperoxidase through a Molecular Docking approach with various natural compounds to identify potential substances for cardiovascular research. Recent research has linked elevated myeloperoxidase levels to the severity of coronary artery disease. The results of the docking analysis revealed Polydatin, Daidzin, Astringin, Ginkgetin, and Amentoflavone as promising compounds with excellent binding capacity. To complement this, toxicity prediction studies were conducted using pkCSM. Overall, all four investigated molecules (Amentoflavone, Daidzin, Ginkgetin, and Astringin) were found to be non-toxic, exhibiting high maximum tolerated doses (human) and favorable values for Oral Rat Acute Toxicity and Oral Rat Chronic Toxicity. Moreover, they showed non-AMES toxicity and non-hepatotoxicity. Astringin, in particular, stood out with the highest positive effects, including a high maximum tolerated dose (human) and favorable values for Oral Rat Chronic Toxicity, along with dual inhibition of hERG II and hERG I. These findings suggest the potential utility of these compounds in cardiovascular research with minimized unwanted effects.

“Energy” is probably the most important term in science and technology. The reason is energy can be converted while it is overall conserved, and thereby correlates changes of a wide variety. Despite its successful use in many areas over more than a century, an analysis of current literature shows that definitions of what energy is and explanations why it is conserved are inconsistent. With regard to energy forms not even a definition was found, and examples given are often wrong. Looking at two interacting objects in the most simple situations, with energy conservation but without conversion, a consistent understanding of energy and its conservation can be derived. Based on it, the systematic set of energy forms with a clear definition of each is then presented.

Passive marine listening, involving the acoustic monitoring of underwater environments, has become increasingly vital for scientific research, environmental monitoring, and defense applications. However, the success of such applications critically depends on the ability to extract meaningful information from the often noisy and dynamic underwater acoustic environment. In this context, Mel-frequency cepstral coefficients (MFCCs) have emerged as an essential tool for feature extraction, capturing the spectral characteristics of marine sounds and making them ideal for species identification and sound event detection. This research presents an innovative approach to enhance the robustness of MFCC-based passive marine listening through adaptive noise reduction techniques. The proposed approach utilizes dynamic spectral subtraction to counter underwater noise, resulting in enhanced signal-to-noise ratios for desired sounds. This adaptive system adjusts to dynamic underwater noise, allowing it to concentrate on target sounds and suppress interference effectively. The experimentation further validates the effectiveness of the proposed approach, with results reaching 99% on the full dataset of 570 mammals and vessels, demonstrating the effectiveness of SVM and Random Forests in the classification of underwater audio.

This theoretical study presents a novel perspective on the potential anti-inflammatory properties of Bromelain, a natural agent extracted from pineapple stems. The investigation explores the binding capabilities of Bromelain to Apoptosis-associated speck-like containing CARD (ASC), a crucial adapter molecule known for its involvement in inflammatory processes and inflammasome formation. For the first time, these findings suggest that Bromelain exhibits a notable affinity for ASC, indicating its promising role as a natural anti-inflammatory agent. This study sheds light on the molecular interactions that may contribute to Bromelain's therapeutic potential in modulating inflammatory responses.

We use the Stefan-Boltzmann law to derive and investigate what we will call the black hole CMB temperature luminosity. Interestingly, the CMB luminosity is always the same for every black hole at a luminosity distance equal to the Schwarzschild radius, which is fully valid in black hole cosmology, a topic that is actively discussed to this day. The CMB black hole luminosity is always the same , regardless of the mass of the black hole. This is in contrast to the Bekenstein-Hawking luminosity, which is linked to the Hawking temperature, that is mass dependent.

Developmental stability (DS) is indicated by the ability of individuals to resist random environmental and/or genetic perturbations during their development. Fluctuating Asymmetry (FA) is the commonest mean of assessing DS in bilateral traits. FA is defined as small random deviations from an ideal morphological symmetry. To date, little attention has been paid to sexual differences in FA among tortoises. With this issue in mind, we assessed levels of carapace scutation symmetries in a sample of 45 wild adult red-footed tortoise, Chelonoidis carbonarius (13 males and 32 females) from Arauca plains, East Colombia. Procrustes ANOVA reflected statistically significative sex-related FA, with males tending to exhibit a more pronounced asymmetry. Although we cannot identify the potential sources responsible for detected developmental instability, our results suggest a high degree of stress and highlight that human intervention in Arauca are affecting wildlife. Similar studies in the future, correlated with an estimate of human impact, could provide irrefutable proof of causality between FA and environmental stressors. The results of this study can represent an estimate of the fitness status of the studied population at present.

The use of artificial intelligence technologies may help companies obtain the optimal use of resources and accomplish more activities with an increase in productivity by 40%. With access to real-time data and the ability to learn from patterns and behaviors, AI can perform these routine tasks more efficiently. Ambient intelligence, Ami, is one of the applications of artificial intelligence, which is called artificial environmental intelligence, which is a concept that focuses on using technology to create an environment that is intelligent and responsive to the needs of its users. This technology has the potential to revolutionize disaster response and management, which in turn facilitates access to necessary information and resources. necessary vitality in the event of a crisis. It may use ambient intelligence to create a network of sensors that can detect and respond to changes in the environment. So that this network can be used to monitor the environment for potential disasters, such as floods, fires and earthquakes. Sensors can also be used to detect changes in temperature, humidity, and other environmental factors that may indicate a potential disaster. This information can then be used to alert emergency responders and provide them with the information needed to respond quickly and effectively. Ambient intelligence can also be used to create a comprehensive database of resources and information that can be accessed in times of crisis. This database may include information about the location of shelters, medical facilities, and other resources that can be used to assist those affected by a disaster. It may also provide information about the condition of roads, bridges, and other infrastructure that may be affected by a disaster. This information can be used to inform response and management decisions, helping to ensure that resources are used in the most efficient way possible. Ambient intelligence can be used to create a communication platform between emergency responders and those affected by a disaster. This platform can also be used to provide updates on the emergency situation, in addition to providing information about available resources to those affected. This can help ensure that those affected by a disaster can access the resources they need in a timely manner.

The COVID-19 pandemic caused by the RNA virus SARS-CoV-2, has had a significant impact not only on bodily metabolism but also at the genomic level. This study utilizes a bibliometric approach to map and identify the relationship between COVID-19 and DNA damage, genomic instability, and cell cycle deregulation. The research began with the development of in-depth research questions and conducted two rounds of literature search in the Scopus database with stringent filters to ensure relevance and accuracy. From an initial 1098 documents, 576 relevant documents were selected for further analysis. The collected data was then visualized using bibliometric methods, enabling the identification of important patterns, trends, and relationships among the research variables. Key findings indicate that DNA damage, which can induce apoptosis, is the worst impact of the infection on cells. Term frequency analysis and science mapping revealed a close relationship between "DNA damage" and "apoptosis". Furthermore, discussions on genomic instability highlight telomere regulation issues, while cell cycle deregulation during virus replication in mammalian cells indicates the importance of maintaining cell membrane integrity.This study confirms the importance of bibliometric analysis in detecting and understanding the impact of COVID-19 at the genomic level, proposing several potential research targets and enhancing our understanding of the biological response to viral infection.

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

This paper studies the dividend optimization problem in the entropy regularization framework by following the same continuous-time reinforcement learning setting as in Wang et al. (2020). The exploratory HJB is established and the optimal exploratory dividend policy is a truncated exponential distribution. We show that, for suitable choices of the maximal dividend paying rate and the temperature parameter, the value function of the exploratory dividend optimization problem could be significantly different from the value function in the classical dividend optimization problem. In particular, the value function of the exploratory dividend optimization problem could be classified into three cases based on its monotonicity. Numerical examples are also presented to show the impact of temperature parameter on the solution.

Glial cells provide physical and chemical support and protection for neurons. Secreted neurotrophic factors, scaffolds and vesicles regulate in addition to normal homeostasis, repair following neural tissue injury or degeneration. We previously demonstrated that human CNS glia have revascularization capacity by inducing endothelial cell sprouting and microchanneling driven by glial cell secreted components. The clinical potential of using secreted factors and vesicles generated by glial cells in conditioned media was shown by their re-normalization of pathological blood vessels and 3D tissue wound healing and remodeling capacity. To identify secreted components of glial cells and how CNS and PNS glial cells differentially regulate neural tissue homeostasis, disease and injury response, we developed a novel culture method for various types of glial cells that allow for isolating and characterizing secreted glial components, free of animal factors and contaminants normally associated with serum-based culture conditions. Our culture method will enable to identify secreted components using ultrasensitive RNA, glycoconjugate and protein analysis technologies. The characterization of glial secreted factors involved microchanneling may help in development of new clinical therapies for glial and neural cells or axons to migrate and reform connections.

Today’s urban spaces face precipitous challenges and complications, which include the COVID-19 pandemic, urbanization, population growth, and climate change. Proximity plays an essential role in influencing the integrity of public spaces and urban environments, while proxemics studies people’s experience, and the benefits, of urban space, and is based on a behavioral system of activities that includes ‘territoriality’. There is a need to study the behavioural patterns of people in given situations with proxemic dimensions in order to sustain both human beings and the quality of urban space. However, people behave spontaneously within environmental settings and reflect each other’s responses, meaning it is important to distinguish between different cultures, which tend to respond in particular ways to the meaning of proximity. This suggests there is no universal indicator for phenomena such as crowding. The aim of this paper is to highlight the interrelationship between urban form and urban life. This study focuses on two patterns of activity - street life and social life - by adopting a descriptive-analytical approach to documentary and desk research. The findings reveal a vital distinction between social and public patterns of proximity, while other proximities, although critical, are not observed within interactions between people.

Climate change and rapid urbanization are adversely affecting the urban environment by exacerbating the widely reported Urban Heat Island effect in Dhaka, Bangladesh. Two wetland areas with variable riparian shadings in the warm-humid conditions of urban Dhaka had been investigated through field campaigns on microclimatic parameters for their cooling potential on the surrounding urban fabric. It was observed that an inversion layer of fully saturated air develops over the water surface of wetland, suppressing evaporation from the wetland water surface layer, which was effectively reducing the heat exchange between the water surface and the air layer above it through its action as an insulating vapor blanket. Because of this effect, the wetland was unable to render as a source of coolth for the surrounding overheated urban area. This effect of the inversion layer was more pronounced in the urban wetland without riparian shading either by urban form or tree canopy. A Multiphysics simulation study conducted on the selected urban wetlands indicates the effect of differential shading pattern on the relation between fetch and inversion layer thickness. This research hypothesizes that the wetland can act as an urban adaption measure against the urban heat island effect by potentially transforming them into Urban Cooling Island (UCI) towards a favorable urban bioclimate.

Adamantinomatous Craniopharyngioma (ACP) is a rare epithelial tumor located in the craniopharyngeal duct, often associated with high morbidity and a high long-term recurrence rate. ACP is predominantly diagnosed in children below the age of 15 and accounts for a majority of Craniopharyngioma cases in the United States. It is most commonly caused by a mutation in exon 3 of the CTNNB1 gene, which promotes overaccumulation of β-Catenin in the WNT pathway. As β-Catenin accumulates, it over-activates the transcription factor, causing an over-transcription of WNT proteins and uncontrolled cell growth. Current methods of treatment for ACP are centered around surgical intervention and radiotherapy, including gross-total resection (GTR), subtotal resection (STR), and a combination of subtotal resection and adjuvant radiotherapy (STR+XTR). These methods of treatment are associated with high risk due to the proximity of ACP to critical structures near the craniopharyngeal duct. High recurrence rates and morbidity are closely associated with current methods of treatment and other methods have yet to be attempted in craniopharyngioma. This review will explore two possible methods of non-surgical and non-radiological therapeutic interventions. The use of RNAi therapy and CRISPR may provide insight and be a potential way to treat ACP with increased quality of life and decreased recurrence rates.

Building defects are very prevalent and contribute significantly to a building's economic value. There are numerous information sources on building defects that have a lot potential for learning more about building defects. This study aimed to identify the information sources used in previous building defect studies and to identify the motivation for carrying out such studies. To fulfil this aim a scoping study was carried out. The information sources identified included insurance companies, private databases, questionnaire surveys, lawsuits, building surveys, client complaint forms, and maintenance reports. This study found that insurance company and client complaint forms include the largest collection of real building defect cases, but such databases may lack detailed descriptions of the causes of the defects. The main purposes of building defects studies identified here included design challenges, identification of defects, building maintenance management, quality management, systematization in data collection, providing an overview of typical defects, and classifying defects. Identification was found to be the most common purpose, indicating that the industry wants to learn more. This study identified research gaps in the climate perspective in relation to building defects. Most of the studies focused on the economical perspective, and none focused on the carbon footprint perspective.

The escalating levels of atmospheric carbon dioxide (CO₂) due to anthropogenic activities have raised significant concerns regarding their far-reaching consequences, including potential impacts on human brain function. This study employs Agent-Based Modeling (ABM) and a comprehensive literature review to comprehensively examine the effects of varying atmospheric CO₂ concentrations on human brain activity. Historical and projected CO₂concentration data, along with neuroscientific insights, were integrated into the ABM framework to simulate brain activity responses under different CO₂ scenarios. The simulations revealed that elevated CO₂ levels disrupt neural activity and alter neurotransmitter profiles, indicating potential cognitive consequences. Sensitivity analysis emphasized the importance of accurate parameterization for robust simulations. The findings underscore the urgent need to address global CO₂ emissions to preserve cognitive health. Further research is essential to validate and refine the model, incorporating additional factors for a comprehensive understanding of the cognitive repercussions of rising CO₂ levels, crucial for informed policy-making and public awareness campaigns.

Abstract: Social media has become a vital tool in ensuring productivity among Undergraduates, as studies have shown an increased number of users globally. This study assessed the impact of social media usage on undergraduates’ academic performance and working memory. Participants from three different universities such as the University of Georgia (UG), Eastern European University (EEU), and Batumi State University (BSU) completed this study using online google forms. UG and EEU are in the capital city, and BSU is in Batumi City. The study questionnaires were approved by the institutional review board before the data collection. Descriptive analyses were assessed for all study populations, characteristics, frequencies, percentages, means, and standard deviations using Statistical Package for Social Science (SPSS Inc., Chicago, IL, version 25.0 for Windows) software. 41.3% were male students, as most of the participants were foreign students living and studying in Georgia. Male students had the risk of ‘conflict’ with families and friends because of social media. Female students are at increased risk of using social media as an ‘escape’ from negative feelings. 89.7% of students that perform physical activities, considering their academic workload had the risk of preoccupation complaints. 87.9% felt dissatisfied regularly because they wanted to spend more time on social media. Utilization of social media differed based on the characteristics of the participants such as age, gender, and geography. We observed the increase in prevalence of social media addiction, its effect on academic performance and working memory among undergraduate students.

Polydatin, a polyphenolic compound sourced from various natural origins, has garnered attention due to its potential anti-tumor properties and low toxicity. This research utilized Molecular Docking methods to investigate the molecular interactions between Polydatin and the Crystal Structure of Human UDP-glucuronic acid decarboxylase (UXS1), aiming to uncover the mechanisms contributing to its anti-tumor effects. The study revealed a substantial binding energy value of approximately -10 kcal/mol for the Polydatin-UXS1 interaction, indicating a robust and favorable binding. This suggests that Polydatin holds significant promise in cancer research, offering insights into its ability to interact with and potentially modulate the activity of UXS1. Moreover, the additional step of predicting toxicity properties using the pKCSM server provides valuable insights into the safety profiles of polydatin ( or piceid). From these results, the parameters for polydatin: —Max. tolerated dose (human),- Oral Rat Acute Toxicity (LD50), and - Oral Rat Chronic Toxicity (LOAEL)—suggest a favorable safety profile.These findings position Polydatin as a compelling candidate for further exploration in cancer research, highlighting both its efficacy and safety considerations.

Subacute sclerosing panencephalitis (SSPE) is a progressive neurological complication that affects the central nervous system. It occurs as a late complication of the measles infection the young children and adolescents who are commonly affected present with personality changes and neurological deficits. The diagnosis can be done via clinical features, electroencephalography, and cerebrospinal fluid analysis. At present, there is no cure for SSPE. The immunisation against measles is the main strategy in preventing this condition. Here, we present a case of a 22-year-old Indian male diagnosed with Subacute sclerosing panencephalitis.

The Swiss Personalized Health Network has developed a national framework for enabling the semantic representation of health data within a Knowledge Graph. This framework has been implemented in all Swiss university hospitals, promoting seamless sharing and integration of clinical routine data with other health-related data, including omics and clinical research data. While research projects often have flexibility in selecting terminologies and specific versions, historical clinical routine data are typically coded for billing or administrative purposes using predefined terminologies in various (sometimes even unknown) versions over time. Some of these terminologies do not adhere to best practices for ontology design, presenting significant challenges to the retrospective re-use of such coded data for research. Common issues with these terminologies include the lack of machine-readable traceability across versions and non-adherence to FAIR principles. Terms from older versions frequently disappear in newer ones, making it challenging to distinguish outdated from invalid terms. Additionally, 'semantic drift' occurs, where the meaning of terms changes across versions. To address these challenges, we have implemented FAIR and historized versions of ATC, CHOP, and ICD-10-GM. We represent each version in RDF using versioned URIs and track meaning changes between versions in a machine-readable way using OWL and RDFS. The integration of these historized terminologies into our quality control framework, based on SHACLs, enables comprehensive data quality control in hospitals and empowers researchers to effectively utilize this data. Our work aims to bridge the gap between health data coded in different terminology versions, ensuring a consistent and reliable semantic representation.

(1) Background: Breast cancer (BC) is the second largest cause of mortality in female worldwide. Besides from basic risk factors, there are several hereditary variables that contribute to BC. Breast cancer has been linked to a variety of nuclear DNA changes as well as mitochondrial DNA alterations. The aim of this study was to analysis the association of mitochondrial tRNA leucine2 gene with BC. (2) Material and methods: In the current study, 24 samples have been collected from various families in Peshawar. DNA was extracted from Blood. PCR was used to amplify the mitochondrial tRNA MT-TL2 gene, and 22 samples were sequenced. The sequence was compared with accession #NC-012920.1 of the revised Cambridge Reference Sequence (rCRS). (3) Results: The results (Chromatograph, nucleotide sequence and rCRS alignment) shows mutations in mitochondrial tRNA MT-TL2 gene in our participants is not the cause of Breast cancer. (4) Conclusion: Yet, a significant number of BC patients must be studied, and their full mitochondrial DNA must be analyzed. This will provide an indication of the potential DNA marker that might be used to prevent BC deaths at the earliest stages.

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

The contribution aims to reconstruct the trajectory of urban morphology studies focused on the graphical understanding of the transformation phenomena within historical and contemporary fabrics. Highlighting some analogies with urban morphology studies present in the theories and design experiments of authors such as Aldo Rossi, Carlo Oswald W. Ungers, Hans Kollhoff, Saverio Muratori, Gianfranco Caniggia, and Giancarlo De Carlo. These studies mostly matured and de-veloped within a favorable cultural environment, which, albeit with due distinctions, saw them aligned on the same front in the practice of analogical procedures (Zambelli, 2021), expressing and anticipating in architectural facts the contemporary concept of urban acupuncture (M. Casagrande, 2010). An emerging notion used to designate the episodic and local character, with urban and ter-ritorial impact of new interventions that aim to oppose the contemporary practice of grand self-celebratory authorial interventions intentionally in dissonance with the context. These inter-ventions are promoted both by liberal and capitalist culture as well as by socialist-inspired culture (Sudjic, 2012). Lastly, it highlights the multiscale nature present in urban morphology studies as well as, at least in intentions, in urban acupuncture projects. Evident in the correlation between expression and content, form and emerging significance, wherein (Foucault, 1969) each change in form, to-gether with a change in scale, corresponds to a new morphological adaptation and consequently a redefinition of rules and 'urban grammar', usable in urban projects with territorial significance. Today, enriched by new digital monitoring tools that graphically render real-time socio-economic flows and dynamics, confirming those insights and syntheses that morphology and typology had suggested in forms that we could now define as acupuncture urban interventions.

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

In recent years, urban planners and designers have paid attention to improve the creative factors in big and small cities in order to make the urban environment more attractive. It seems that improving desirable urban environmental qualities and walkability approaches such as flexibility, happiness, and vitality, provides the necessary background for creating creative urban spaces. The case study zone is urban walkways in Rasht that which has been completed four years ago. In this paper, after conceptualizing the nature of the creative city, as well as reviewing the views of the thinkers regarding the qualities of the environment, a conceptual model of creative urban space has been developed. Then, the indicators and criteria of creative urban space have been evaluated through the questionnaire and analysis through SPSS software and regression model, Pearson and Friedman. The result of the analyses of the five spatial, functional, social, perceptual, and environmental components and their relationship is expressed that factors such as paving streets, the development of local markets, the Suitability of urban walkways for physically and mentally handicapped people, the use of cultural elements, the use of diverse urban furniture and nightlife after building urban walkways play an important role in the realization of urban creative space in Rasht city.

The present study investigated the effect of art on promoting the meaning of the urban space. In this regard, after considering the semantic dimension of the urban space and the mechanism of transferring the meanings of art through the views of experts, a model is presented for examin-ing the art’s cooperation in promoting urban space meaning in Tehran. In this study, a mixed method was used. In the first stage, the categories of space meanings influenced by art were ex-tracted through using the qualitative method of interpretive phenomenology and by examining 61 in-depth interviews in six urban spaces eligible for urban art in Tehran. In the second stage, these categories were surveyed in these spaces through 600 questionnaires after converting to the questionnaire items. Based on the results, "the possibility of the experience and perception", "social participation", and "the relationship with the context" were the main themes of the se-mantic relationship of art and urban space. Further, the lower scores related to the theme of "so-cial participation" in the quantitative investigations indicated that this theme was weaker than the other themes in promoting the meaning of the urban space through the art in the selected urban spaces.

Optimal planning and design of microgrids is a priority for electrification of off-grid areas. Indeed, according to one of the Sustainable Development Goals (SDG) 7, the UN recommends universal access to electricity for all but, at the lowest cost. To achieve this goal, several optimization methods with different strategies have been proposed in the literature. This paper proposes a microgrid installation and planning model based on a combination of several techniques. Python 3.10, the programming language, has been used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. The results obtained enabled us to simulate the model obtained, with a cluster considered as a case study, based on the elbow and k-means clustering method; then, in a second phase, to size the microgrid with a capacity of 40 kW, by optimizing all the resources available on the site: the example of the various resources in the case of Togo was considered (solar, wind, hydropower). This study therefore highlighted the optimal resources obtained by integrating battery systems by the optimization model formulated on the basis of the various technology costs, such as investment, maintenance and operating costs, based on the technical limits of the various technologies. For the optimum results obtained, solar systems account for 80% of the maximum load considered, compared with 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed, based on the constraints of a voltage stability limit estimated at 10% of the maximum voltage drop. The substation capacity limit was also taken into account. The results obtained from the case studied enabled us again, to present selective results for load nodes in relation to the substation node. And finally, the spatial technology planning tool made it possible to obtain results on the different strategies for the various technologies required for the electrification planning study of the Togo case. The various results obtained from the different techniques provide the leads needed for a feasibility study for optimal electrification of off-grid areas, using microgrid systems.

Though nowadays germanium do not reach the range of popularity than other metals, i.e. rare earth elements, its utility in target industries makes of it also a strategic metal. Though germanium can be find in a series of raw materials, the principal source for its recovery is from secondary wastes of the zinc industry, and also, the recycle of germanium-bearing waste materials is becoming of interest. In this recovery, Hydrometallurgy is performing a key role to the successful achievement of this goal. The present work reviews the most recent applications (2023 and 2024 years) of hydrometallurgical operations on the recovery of germanium from different solid and liquid sources.

The liver diseases are posing serious threat to human health associated with abusive use of allopathy medicines, especially in developing economies like Pakistan. The strengthening of detoxification system using natural products might be a suitable option to minimize the liver problems. In this current research, Zingiber officinale and Azadirachta indica were evaluated for their hepatoprotective role. For the purpose, 20 Sprague Dawley rats were equally divided into four groups i.e., negative control, paracetamol positive control, 2.5% ginger and 2% neem powder, respectively. During 42 days study, the levels of bilirubin and liver enzymes significantly elevated due to liver damage. Although, the values dropped (20-25%) in treatment group. Serum glucose and serum lipid profile increased in positive control group, but reduced (5-10%) in both ginger and neem groups. The serum protein profile declined in liver damage group, however, improved (~5%) in treatment groups. The hematological parameters slightly declined in liver damage group, but increased in ginger and neem groups. Moreover, the white blood cells differential count and renal parameters showed abnormal values in liver damage group, but improved after treatment. This study is promising and highlighted the hepato-protective role of neem and ginger that may open several avenues of research.

A difficult open problem that has never been fully resolved in the literature to date is the behaviour of the (TDCDP) third approximation. As a giant step towards modern control theory, this cutting-edge paper will advance control theory and other relevant inter-disciplinary subjects. Because control theory is important in industry and engineering, this study will be especially beneficial to anyone working in these disciplines who wish to understand more about recent advances in control theory settings. In contrast, the wealth of applications of Fokker Planck Kolmogorov (FPK) equations numerous disciplines As a result, the study instantly gains more taste and credibility. At the end of the paper, there are several challenging open problems, some concluding remarks, and recommendations for further investigation.

The therapeutic, attenuative, and morphological effects of proprietary neural stem cell-derived extracellular vesicles (NSC EVs, AB126) produced by Aruna Bio, Inc. were assessed in a range of in vitro and in vivo models of stroke. We emphasize that modulation of neuroinflammation is a key target and suggest further studies to advance our understanding of the mechanisms of action and ultimately how best to dose and monitor the benefits of AB126 in stroke patients.

Introduction: Parameters used for neonatal mortality calculation vary among publications. Mortality in < 33 weeks gestational age at birth display global variations across different healthcare units. Objective: This study aims to explore trends in neonatal mortality among infants born preterm in the different units in Latin America and the Caribbean utilizing the EpicLatino Network Database in comparison to Canadian Neonatal Network (CNN) 2022. Materials and Methods: This study focused on an eight-year period, with a particular attention to mortality rates during the pre-pandemic (2015-2019) and pandemic/post pandemic (2020-2022) periods. Survival rates from CNN 2022 were included in the comparison analysis. Logistic regression analysis was confined to the 2020-2022 period. Adjustments were made for factors including gestational age, small for gestational age (SGA), Snape II score, inborn/outborn status, and center. As major malformations could account for mortality differences among units. The incidence of major congenital malformations, as defined by CNN, was compared among deceased patients. Results: A total of 15,454 records from 2015-2019 and 10,711 records from 2020-2022 were scrutinized. Overall, there were no significant differences in mortality rates between the two time periods (p=0.22). Moreover, the originating unit during the 2020-2022 period significantly influenced all statistical computations. Conclusions: Survival rates among infants < 26 weeks of gestation in Latin America and the Caribbean are on an upward trajectory, with the healthcare unit playing a pivotal role in this outcome within the EpicLatino database. Major malformations do not seem to be a significant contributing factor. These findings underscore the imperative of implementing quality improvement initiatives to elevate neonatal care standards in Latin America and the Caribbean.

Graph databases (GDBs) are becoming increasingly popular across scientific disciplines, being highly suitable to store and connect complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph (KG) databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available GDB technologies. Relevant publications are then categorised according to their domain and application. We detail different approaches and highlight advantages of outstanding resources, such as UniProtKB, Disease Ontology, and Reactome, which provide graph-based solutions. We discuss ongoing efforts of the systems biology community to standardise and harmonise KG creation and the maintenance of integrated resources. Outlining prospects, including the use of GDBs as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of GDBs will be key for knowledge generation in systems biology and other research fields with heterogeneous data.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Prostate cancer is the second most frequent malignancy (after lung cancer) in men worldwide. Prostate tissue biopsies are usually graded using scores according to the Gleason grading system. This Gleason score is the most popular prognostic marker that reveals the potential aggressiveness of the disease. However, inter-observer variability in rating by human assessors is a major limiting factor. Such variability could lead to missing a severe case or suggesting unnecessary treatments. This study explores the discriminative ability of artificial intelligence (deep learning models) for Gleason score assessment. The study was designed to use whole-slide images of digitized H&E-stained biopsies of prostate tissues to automate the grading process and provide a remotely accessible clinical decision support system. Custom convolutional neural network architectures were trained on 10,616 images of prostate tissues. Gaussian filters were applied to pre-process the images and improve model performance. Transfer learning was applied to train eight machine learning architectures namely: Xception, VGG16 & 19, ResNet101, MobileNet, DenseNet121, EfficientNetB5 & B7. Efficient NetB7 had the best performance 85.2% compared with ground-truth classification by experts. Performance improves as more data is available. The model was deployed and hosted as a web application API on Google cloud service to ensure remote access. Tissue biopsy images can be uploaded and the corresponding Gleason score recovered immediately. This system reduces diagnostics turnaround time, increase throughput, and compensate for limited skills, especially in low resource settings.

This paper shows the firsts results of a methodological approach in which Remote Sensing technologies (Satellite imagery and LiDAR) combined with Least Cost Path algorithm on GIS are being tested like tools to overcome locally-based interpretations about populational patterns and communication routes during Flavian municipality in the Comarca de El Condado region. The identification of fourteen hypothetical communication routes between already known archaeological sites thanks to a recent archaeological prospection, and the confirmation of three sections of them and a new archaeological site demonstrate that the combined use of the aforementioned technics has a very useful to delve more deeply, more widely and at a variety of different scales into the relation between the twelve known/selected Early Roman Empire sites and the surrounding landscape in the right bank of Guadalén River. It is expected that, in next phases, this methodological approach will allow us to go deeper in analysing and understanding spatial distribution, exploitation, and interrelation between different Early Roman Empire sites, helping us to fill the aforementioned gaps in our understanding of the archaeological continuum in the region reducing time and costs.

Rising demand and urbanization have led to the global increase and intensification of livestock production. Intensive production has harmful effects on the environment, public health (due to the emergence of zoonotic diseases), and animal welfare. In order to better understand how livestock production intensifies as countries develop and incomes rise, we examine the relationship between income per capita and intensification of poultry and cattle, using the states of India as a study region. We also replicate this analysis at the district level to test whether the relationship holds at different spatial scales. We identify outlying states and districts to see if there are policies that can keep agriculture production largely extensive, even as economic growth occurs. The results support the relationship of income being positively correlated with the proportion of livestock in intensive conditions. However, there are notable outlier states which have grown wealthy while still maintaining largely extensive production, indicating that there may be some cases where economic growth can occur without intensification.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

We show succinctly a natural origin of the beautiful Gamma function in light of the WJ distribution, linking to quite distinct fields.

Modern research applies the Open Science approach that fosters the production and sharing of Open Data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. In the geospatial context this is generally achieved through the setup of OGC Web services that implements open standards that satisfies the FAIR requirements. Nevertheless, the requirement of Findability is not fully satisfied by those services since there’s no use of persistent identifiers and no guarantee that the same dataset used for a study can be immutably accessed in a later period: a fact that hinders the replicability of research. This is particularly true in recent years where data-driven research and technological advances have boosted frequent updates of datasets. Here, we review needs and practices, supported by some real case examples, on frequent data or metadata updates in geo-datasets of different data types. Additionally we assess the currently available tools that support data versioning for databases, files and log-structured tables. Finally we discuss challenges and opportunities to enable geospatial web services that are fully FAIR: a fact that would provide, due to the massive use and increasing availability of geospatial data, a great push toward open science compliance with ultimately impacts on the science transparency and credibility.

Star copolymer films were studied for confirming the role of film morphology in antimicrobial activity previously reported. With this scope, films of a two-branches copolymer, namely m-PEG-(MMA-ran-DMAEMA)2, containing ≈ 40 % in mol of non-quaternized 2-(dimethylamino)ethyl methacrylate, were produced by using spin-coating, drop-casting and casting deposition techniques, thus obtaining ultra-thin, thin and thick films, respectively. The morphology is generally flat for thin and thick films, but it becomes substrate dependent for ultra-thin films where the film planarization effect is not efficient. Mechanical properties of such films were investigated by Force Volume Maps in both air and liquid. In air, ultra-thin films are in the substrate-dominated zone and thus the elastic modulus E is overestimated, while E reaches its bulk value for thin and thick films. In liquid (water), E follows an exponential decay for all films with a minimum soaked time t0 of 0.37 and 2.65 h for ultra-thin and thin and thick films, respectively. After this time, E saturates to a value in average 92 % smaller than that measured in air due to films swelling. Such results confirm the role of morphology envisaged in literature, suggesting also an additional role of mechanical properties in the antimicrobial activity.

Traditional methods of non-metallic materials joining for industrial uses are limited to lasers, or induction or conduction heating. The precision and efficiency for large-scale applications are difficult to be achieved at the same time. Here in this paper, we report a precise microwave welding method induced by localized surface plasmon of metallic macro-gaps under microwave excitation. The proposed method utilizes energy from well-developed commercial microwaver, and benefits from the precision of localized surface plasmon, an oscillating electron cloud excited by electromagnetic waves, which is currently under hot investigation only at micro- or nano-scales. The method is applied to the welding of polymers to solve the problems of complex processing equipment and high processing energy consumption in the traditional welding process, so as to cope with the growing energy and environmental crisis. Finite element numerical simulations are used to study the distribution characteristics of electric fields and temperature fields. The results show that the process is a high quality, efficient, low consumption and environmentally friendly green process compared to traditional polymer welding methods.

Coral reefs are one of the most productive yet vulnerable ecosystems on Earth. An important step in understanding the functioning of coral communities is studying the environmental impact on the state of reefs. The present study aimed to assess the impacts of the water temperature, precipitation, wave action and population density on the seasonal bleaching, partial and complete mortality of shallow-water branching corals of Pocillopora verrucosa species complex. The present study was conducted at the Dam Bay research station (Nha Trang Bay) from 26 April 2020 to 2 April 2021. Throughout the study the percentage of bleached coral colonies varied from 1 to 41.5% with two peaks, in autumn (October) and spring (April). Rates of the development of partial mortality varied from 0 to 10%, with a pronounced peak in December. At the end of the experiment, the percentage of coral colonies suffering from partial mortality reached 47%. Only 4,5% of experimental colonies died by the end of the study. Analysis revealed that water temperature and partial mortality are the drivers of bleaching, while wave action, temperature and bleaching are the factors with a significant impact on partial mortality. In the present study, the main cause of coral death was the development of algal fouling at the sites of colony lesions, which gradually spread over the entire surface of the colony. We showed also that the impact of individual stress on mortality prevailed over the impact of seasonal bleaching and partial mortality events.

The possibility of a shock wave recovery at a discrete closed interface with a heated gas has been investigated. A two-dimensional model applied to conditions of optical discharges featuring spherical, elliptical, and drop-like configurations demonstrated that non-symmetry in the shock refraction contributes to the specific mechanism of recovery other than simply its compensation. Even though the full restoration of the hypersonic flow state doesn’t occur in a strict sense of it, clear reverse changes toward the initial shape of the shock front eventually take place, thus creating an appearance of a full recovery seen in experiments. From analysis for different interfaces symmetries, the factors determining the recovery dynamics are identified. The results are directly applicable to the problem of energy deposition into a hypersonic flow, however it can be useful anywhere else where the flow modifications following the interaction are important. The dimensionless form of the equations allows applications on any scale other than that demonstrated for the optical discharges.

The study conducted in this paper is focused on a predominantly residential area of the City of Ljubljana – Koseze, which is characterized by generally favorable (bio)climatic conditions. Nonetheless, thermal satellite imaging showed that residential neighborhoods within the Koseze district display unexpected variations in summer temperatures. This observation called into question the benefits of existing bioclimatic features and indicated the need to investigate and compare two neighborhoods with similar urban parameters, with the aim to identify morphological differential characteristics impacting urban heat island (UHI) intensity. By applying the study methodology based on a literature review, surveys of key precedents, detailed mapping in two Koseze locations, in situ measurements, observations and recordings, thermal imaging and the analyses of statistical data, as well as by defining the four main categories of morphological urban parameters – structure, cover, fabric and metabolism, it was concluded that both neighborhoods have common morphological elements mitigating the UHI effect. Additionally, it was found that the neighborhood with higher UHI intensity has several less favorable features, such as busier roads, larger surface of parking corridors, and the existence of underground parking space. The traffic as an element of urban morphology hence represents the main cause of differences among UHI levels in the two Koseze neighborhoods.

Urban forests are critical infrastructure for mitigating environmental and social challenges cities face. Municipalities and non-governmental entities, among others, often set goals (e.g., tree planting or canopy targets) to support urban forests and their benefits. We focus on canopy goals and develop conceptual underpinnings for an analysis of where additional canopy, as one important dimension of the urban forest, can fit within the landscape, while considering factors that influence where trees can be planted and where canopy can grow – ‘practical canopy.’ We apply this in New York City (NYC) to inform the setting of a canopy goal by the NYC Urban Forest Task Force (UFTF) for the NYC Urban Forest Agenda, which may trigger a virtuous cycle that supports the urban forest there. We further develop framing for a ‘priority canopy’ analysis to understand where urban forest expansion should be prioritized given more context (e.g., environmental hazards, local preferences), which can inform how expansion of the urban forest is achieved. We estimate an opportunity for 15,899 ha of new canopy in NYC given existing opportunities and constraints (practical canopy), which, if leveraged, could result in nearly doubling the canopy as of 2017 (17,253 ha). However, like existing canopy, practical canopy is not evenly distributed, in general, or across jurisdictions and land uses. Relying solely on areas identified as practical canopy to expand the urban forest would exacerbate inequities in its distribution. We discuss how the NYC UFTF established an aspirational but achievable goal of 30% canopy cover by 2035, which was informed by this analysis and guided by priorities of equity, health, and resilience. Achievement of this goal will ultimately require a combination of protecting and stewarding the existing resource, and leveraging opportunities for tree planting. Achieving a more equitable urban forest will also require identification of priority canopy, and, in cases, creation of new opportunities for tree planting and canopy expansion. Overall, the collaborative establishment of such goals based on local context can be instrumental in creating a virtuous cycle, moving conservation actors toward exercising influence and agency within the social ecological system.

Cities’ delineation remains a hot topic of debate in a time where comparisons between cities are becoming increasingly based on different issues that address various scales of interventions and thus different concepts of cities. Aiming to compare cities and their insertion into globalization, we suggest that the “urban field of influence” is the best way to approach cities for this specific perspective. However, after reviewing the different existing possible concepts, we replace this concept with four different approaches proposed by Pumain et al. (1992): political entities, morphological agglomerations, functional urban areas and conurbations/Mega city regions. We discuss the top-down and bottom-up existing initiatives launched at the world scale and then use a mixed top-down and bottom-up approach to propose a new delineation of a large urban region (LUR), denoting a concept close to the conurbation or Mega city-region concept. The compositions of these LURs are published as an initial incomplete framework, suggesting the need for further critical comments and contributions to improve them.

We have an aversion to density in America. Density is a continual trope in this country, blamed for all of the ills of urban life, from crime and racial unrest in the middle of the 20th century to public health concerns today. In the early stages of the COVID pandemic density was the culprit, even though we’ve subsequently seen outbreaks in rural areas and sprawling cities across the United States. This paper will look into the root of America’s problems with density and argue that density is not the problem but the solution to the challenges of today’s and tomorrow’s cities. As we deplete the resources of the planet, density is our most direct pathway to recover some balance with nature. Dense living is more efficient, less carbon intensive and more environmentally sustainable. As geospatial differentiations matter less due to advances in communication technology, it's the density of people and ideas that will continue to fuel innovation. Finally, in a world that is increasingly dominated by pluralism, denser living promotes openness, tolerance and diversity.

Building more energy efficient and sustainable urban areas that will both mitigate the effect of climate change and adapt for the future climate, requires the development new tools and methods that can help urban planners, architect and communities achieve this goal. In the current study, we designed a workflow that links different methodologies developed separately, to derive the energy consumption of a university school campus for the future. Three different scenarios for typical future years (2039, 2069, 2099) were run as well as a renovation scenario (Minergie-P). We analyse the impact of climate change on the heating and cooling demand of the buildings and determined the relevance of the accounting of the local climate in this particular context. The results from the simulations showed that in the future there will a constant decrease in the heating demand while for the cooling demand there will be a significant increase. It was further demonstrated that when the local climate was taken into account there was an even higher rise in the cooling demand but also that the proposed renovations were not sufficient to design resilient buildings. We then discuss the implication of this work on the simulation of building energy consumption at the neighbourhood scale and the impact of future local climate on energy system design. We finally give a few perspective regarding improved urban design and possible pathways for the future urban areas.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

Using assembly theory, we investigate the assembly pathways of binary strings of length N formed by joining bits present in the assembly pool and the strings that entered the pool as a result of previous joining operations. We show that the string assembly index is bounded from below by the shortest addition chain for N, and we conjecture about the form of the upper bound. We define the degree of causation for the minimum assembly index and show that for certain N it features regularities that can be used to determine a shortest addition chain. We show that a string with the smallest assembly index for N can be assembled by a binary program of length equal to this index if the length of this string is expressible as a product of Fibonacci numbers. We conjecture that there is no binary program that has a length shorter than the length of the string having the largest assembly index for N that could assemble this string. The results confirm that four Planck areas provide a minimum information capacity that corresponds to a minimum thermodynamic (Bekenstein-Hawking) entropy. Knowing that the problem of determining the assembly index is at least NP-complete, we conjecture that this problem is NP-complete, while the problem of creating the string so that it would have a predetermined largest assembly index is NP-hard. The proof of this conjecture would imply P ≠ NP, since every computable problem and every computable solution can be encoded as a finite binary string.

The urban planning transformations modify the morphological shape of the territory changing land uses and permeability of the areas involved in the evolution processes, thus also altering the hydrologic responses to climatic events, namely the urban drainage runoffs that impact on the environmental risk of modern cities. Using the watershed hydrologic concept, in its dynamic evolution, it is possible to consider the morphological layout together with the transformations implemented by the human activities and any different territorial portions could be analyzed in connection with the other areas related by the dynamics of the surface runoff, thus highlighting the reciprocal influences between the different areas. By examining the morphological shapes impacting surface outflows, the hydrological roles of upper-mountain, intermediate-hillside, and lower-valley areas reveal urban and non-urban connections. This elucidates hydromorphic complexities in urban transformations and assesses climate change adaptability. The proposed approach has been applied to the urban district of “Sasso Caveoso”, belonging to the city of Matera and consents to quantitatively synthesize the response of the context analyzed, referring to different scenarios and providing useful decision support tools.

Objective To investigate nailfold capillary parameters in community-dwelling individuals aged over 60 years who have hypertension and do not exercise regularly. Furthermore, the study examined the correlations between capillary function and other health-related indicators. Design A single- center pilot trial Setting Faculty of Health, Tsukuba University of Technology, Japan Participants hypertensive community-dwelling elderly people Intervention Microcirculation was observed before and 1 min after arm-curl exercise by means microscopy of capillary with non-exercised limb. Additionally, we examined other health-related indicators. Outcome measures: Acute effects of reperfusion on nailfold density, flow, and diameters. Secondary outcomes included the correlations between microvascular parameters and other health-related indicators. We hypothesized that brief exercise could enhance microcirculation reperfusion and correlate with other health-related parameters.　 Results: There were 20 participants with a mean (SD) age of 67.1 (5.8) years. The capillary flow rate changed from 2.3±6.7 to 2.7±0.2 log µm/s (P

In genetic conflicts, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables a selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

Understanding clinical significance of variants of unknown significance (VUS) reported in next-generation sequencing (NGS) has become essential in cancer treatment. Our study examined six widely used in silico tools: PolyPhen-2, Align-GVGD, MutationTaster2, CADD, REVEL, and Chat-GPT. We utilized a dataset of gene variants known to potentially affect immune therapy. No single tool could comprehensively determine mutation variant pathogenicity. MutationTaster2021 showed the highest overall accuracy and MCC among the tools. Notably, REVEL and Chat-GPT exhibited 100% specificity, suggesting their proficiency in accurately identifying pathogenic variants and minimizing false positives. In contrast, CADD displayed optimal sensitivity, making it suitable for effectively ruling out benign variants.

Based on recent progress in cosmological thermodynamics, we present a new thermody- namic formulation of the Friedmann equations in the new Haug-Tatum cosmology model, as well as for other similar models put forward in the literature from different solutions to Einstein’s field equation. Since the CMB temperature has been measured much more accu- rately than the Hubble constant, we demonstrate that our thermodynamic formulation of the Friedmann equation dramatically narrows the acceptable range for the critical density of the universe. Furthermore, we show how our thermodynamic formulation leads to a more precise cosmological constant estimate.

We are losing love. By studying porn movies to understand love, I discovered that love originally comes from the body, from positive emotions and vibrations of the wonderful body, from the heart and all other parts of the body, such as sexual organs. António Damásio made Descartes’ error by postulating that feelings increase their power from homeostasis (mechanisms of life regu-lation from bacteria to humans). He made this mistake unconsciously because many people un-consciously have a very bad opinion of sexual organs. We consider them ugly because they come from the prehistoric period. I have combined António and Hanna Damásio’s work (body emotions, thinking and language). I discovered that porn actors do not talk during sex, and this is striking. Porn actors mirror what happens in society. This means that people come from prehistory, do not talk during sex, and still unconsciously behave like primitive animals during sexual intercourse; we do not respect the body sufficiently during sex. Therefore, love, which comes from the body, is smothered and buried. We must very delicately talk to the wonderful, delicious and respectful body to wake up love feelings, body emotions and vibrations during sex. We must invent talking movies with porn films. Language of positive emotions associated with the language of wonderful and delicious body will warm love feelings and will give envy to love through sexual intercourse because António Damásio discovered that emotions are social.

In many countries, increasing concern for animal welfare is driving retailer commitments and government legislation that aim to improve the lives of farmed fish. One aspect of fish welfare involves stunning fish prior to slaughter. The feasibility of stunning depends on the species of fish and physical farm characteristics. In this article, we provide an overview of stunning before slaughter in European sea bass and sea bream aquaculture, one of the largest finfish farming industries in the developed world that does not yet stun most of its production. Sea bass and sea bream stunning necessitates the use of electrical stunning equipment aboard harvest vessels, often a significant distance from the shoreline; this presents an interesting engineering and policy challenge. Together, Türkiye, Greece, Spain, and Italy produced over 400,000 t of sea bass and sea bream in 2020. In Türkiye and Greece, farms are numerous and located very close to the shoreline. In Spain and Italy, farms are few and located far from the shoreline. The highest average production is found in farms from Türkiye (1,000 t) and Spain (1,300 t, and lower average production is found in Greece (300 t) and Italy (350 t). Producer progress towards the installation of electrical stunning appears comparatively well-developed for Türkiye, Spain, and Greece, though we emphasise that producers and other stakeholders require continued support to realise this opportunity. Producers in Italy appear slower to make progress on this aspect of animal welfare and may require additional support.

The Casimir effect can either work over very short distances or at very low temperatures. At the cosmic scale, we naturally deal with long distances, but at the same time, we encounter extraordinarily low temperatures, namely the CMB (Cosmic Microwave Background) tem- perature. Recently, there has been increased interest in the Casimir effect and its implications in cosmology. Here, we briefly demonstrate that the luminosity and radiation pressure of the CMB is mathematical identical to a theoretical Casimir effect within the Hubble sphere, or actually our solution seems to be valid for any Schwarzschild black hole. The Casimir effect forevery Schwarzschild black hole is identical. This also include the Hubble sphere if we treat it as a Schwarzschild black hole that is related to increased interest in black hole cosmology.

Caused by age or trauma, collapsed connective tissue can cause nerve entrapment and damage within the tarsal tunnel. Tarsal tunnel syndrome is relatively underdiagnosed. This study presents an intervention targeting damaged tissues surrounding the nerves and replacing the structural cushioning with a Wharton’s jelly tissue allograft. The eight selected patients from four clinical sites had tarsal tunnel-related defects. Patient outcomes were tracked on a 90-day calendar utilizing the Numeric Pain Rating Scale (NPRS) and the Western Ontario and McMaster University Arthritis Index (WOMAC). All patients had failed standard care practices for at least six weeks. Each patient received a Wharton’s jelly tissue allograft to sites around the affected tarsal tunnel. No patients experienced adverse reactions. Percent change calculated from the initial application to the 90-day follow-up showed an improvement of 59.43% in NPRS and a 37.58% improvement in WOMAC. This study provides evidence that WJ allograft applications are safe, minimally invasive, and efficacious for patients who have failed standard care treatments for tissue defects associated with Tarsal Tunnel syndrome. Limitations include the small cohort size and nonblinded nature. The results of this study warrant further research to confirm the efficacy, optimal dose, protocol, and durability of Wharton's jelly.

The hyperspectral vegetation index was defined based on the distinctive features of the spectral curve. In alignment with the growth and development characteristics of cotton, the spectral reflectivity of the cotton canopy was computed at different growth stages. The aim of this study was to clarify the association between cotton yield and canopy spectral indices and to develop yield estimation models utilizing hyperspectral imaging. The ASD Field Spec Pro VNIR 2500 spectrometer radiometer was employed to collect spectral reflectance data from cotton canopies at various growth stages. Using spectral analysis techniques, quantitative models were developed based on hyper-spectral vegetation indices, including Normalized Difference Vegetation Index (NDVI) (NDVI) and Radar Vegetation Index (RVI) to extract characteristic information from the cotton canopies. Following thorough testing and precise monitoring of the estimation models, the most optimal models representing cotton canopy structure parameters were identified. Results demonstrate that the power function model, relying on NDVI, provides the most accurate forecasting for Leaf Area Index (LAI)). Additionally, the exponential function model based on RVI proves to be the most effective for predicting cotton unit area above-ground fresh biomass, while another exponential function model based on RVI is identified as the best for predicting cotton unit area above-ground fresh biomass. Clearly, the application of hyper-spectral remote sensing technology enables the analysis, simulation, assessment, and providing scientific basis for precision cotton planting and cotton field management strategies.

The dermatological manifestations of Long Covid (LC) have languished in the shadows of chronic fatigue and brain fog. Yet they are all linked by gut dysbiosis and the cytokine triad of TNF-α, IL-1β, and IL-6. The gut microbiome common not only to LC, psoriasis, AA, and vitiligo but also to neurodegenerative disease has been recently described. This gut microbiome induces an altered tryptophan metabolism linked to autoimmune disease. SARS CoV2 invades enterochromaffin cells rich in ACE2 receptors and curtails absorption of the essential amino acid tryptophan and subsequent synthesis of serotonin and melatonin. This review suggests that an etiologic prebiotic (d-mannose)/probiotic (lactobacilli, bifidobacteria)/postbiotic (butyrate) approach to autoimmune skin disease that improves intestinal barrier integrity and that suppresses the triad of TNF-α, IL-6, and IL-1β may enhance or even eliminate the traditional immunotherapy of targeted monoclonal antibodies, Janus kinase inhibitors, and steroids. Health benefits of this approach extend well beyond suppression of autoimmune skin disease.

Upon the outbreak of the COVID-19, countries worldwide developed policies with the goal to introduce restrictive measures geared towards mitigating the spread of the virus. Although these health initiatives were put in place through top-down public directives, they relied heavily on the cooperation of citizens who had to be willing to carry them out. As a consequence, we could observe differences in compliance with governmental restrictions within and between countries. Increasing policy stringency was the method adopted overall to promote people’s compliance. This article used survey data from 10308 participants in Brazil to examine whether there was a positive correlation between policy stringency and compliance with restrictive measures to reduce the spread of COVID-19. The results revealed, however, that there was no direct influence of policy stringency on people’s health behaviors. Accordingly, I hypothesized that individual differences in personality traits were one of the drivers behind policy compliance, as they would support self-interests such as the duty to support authorities as well as the perceived health risks of certain behaviors and ultimately motivate compliance. The findings’ implications for both compliance research and for authorities wanting to nurture voluntary compliance with public health orders are discussed and suggestions are provided.

This work introduces a novel facial image capture system that utilizes computer vision technology and artificial intelligence for real-time detecting, tracking, and capturing of human faces. The objective of this study is to address the challenges posed by poor-quality facial images in biometric authentication, especially in passport photo acquisition and recognition. By combining face-aware capture technology with AES encryption for secure image storage, we present a completely open-source hardware solution that consists of a Jetson processor, a 16MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. Pilot data collection demonstrates the system's ability to capture high-quality images, achieving a 98.98% accuracy in storing images of acceptable quality. The integration of AES encryption ensures data security, making the proposed system suitable for real-time applications in other domains beyond identity verification in passport applications, such as security systems, video conferencing, etc

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

Exosomes, a subset of extracellular vesicles, have emerged as pivotal mediators of intercellular communication, revolutionizing our comprehension of cellular interactions. Their diverse cargo, comprising proteins, nucleic acids, and bioactive molecules, plays a crucial role in various physiological and pathological processes. In the intricate landscape of adult neurogenesis, exosomes wield significant influence, actively participating in the generation of new neurons within the adult mammalian brain. Originating predominantly from non-niche cells, these vesicles contribute substantially to the regulation of neuroinflammation, thereby impacting neurogenesis and offering therapeutic promise for neurological disorders. In the specific context of Parkinson's disease (PD), exosomes assume a multifaceted role, prominently implicated in the propagation of α-synuclein oligomers and the orchestration of neuroinflammation. Stem cell-derived exosomes present themselves as promising therapeutic agents, capable of reshaping the microenvironment, repairing neuronal damage, and mitigating apoptosis. The ongoing exploration of exosomes continues to unravel intricate biological processes, paving the way for innovative medical interventions and treatments, particularly within the challenging landscape of neurodegenerative diseases such as PD. The comprehensive understanding of exosomal functions holds the potential to advance our therapeutic approaches, offering new avenues for intervention and treatment strategies in the realm of neurodegenerative disorders.

Among the number of hurdles that the vaccines based in modRNA platforms have been facing, there is now another critical one: immune imprinting which decreases even more the effectiveness of the modRNA Covid vaccines.

The initiation of micro-cracks in concrete is primarily due to its brittleness, which causes severe impacts on the overall behavior of the concrete. However, incorporating fibers in concrete could significantly improve its mechanical properties. The current study demonstrates the influence of two types of fibers on the mechanical properties of concrete. Nylon Fiber Threads (NFT) and Nylon Fiber Strands (NFS) at a fiber content of 2.5 kg/m³ were incorporated in the concrete mix. Concrete with a compressive strength of 30 MPa and a water-cement ratio of 0.4 was produced to investigate the fresh and mechanical properties of conventional and nylon-fiber reinforced concrete (NFRC). The concrete prims and cylinders were tested for compressive, splitting, and flexural strength using ASTM standards (ASTM C-39, C-496, and D-790, respectively). It was found that NFT-reinforced samples achieved higher mechanical properties of concrete (13.05%) compared to NFS-reinforced samples. Test results showed that incorporation of nylon fibers (NF) in concrete decreased the compressive strength of cylindrical and cubical specimens by 0–10% and 5–15%, respectively. However, it increased the splitting tensile and flexural strengths by 0-15%, and 5-15% respectively. Furthermore, the incorporation of NF in concrete significantly improved the ductility and delayed the crack initiation in concrete.

The Power Theory of Exchange and Money (PTEM) refines the economic neoclassical two-equation model of exchange. PTEM replaces the statistical average condition of exchange, which represents the equality of supply and demand for all transactions in the market, with a more specific equation of the equality of the generalized power of the parties in relation to their objects of exchange. The purpose of the article is to show the application of PTEM for the study of various social phenomena. Along with a brief summary of the main statements of this theory, its integration into the existing corpus of theories and ideas in economics and sociology is considered. The conclusions of power theory are then applied to consider the following topics: the objective motivation of exchange by the desire to increase power, the power nature of market equilibrium, the power nature of money, the accumulation of power through profit, the creation of money as a power act, the role of the state in the creation of money, the measure of power as a possible tool for social and political research.

In the domain of financial trading, where accuracy and swift response to data discrep- ancies are paramount for maintaining clienttrust, our research paper delves into the development of a real-time alert system utilizing SpringBoot, a framework renowned for its robustness and adaptability in enterprise applications. We embark on a comprehensive journey, beginning with addressing thefoundational challenges inherent in monitoring trade inquiries - the necessity for real-time processing, unwavering data accuracy,and ensuring unwavering system reliability. The study then methodically transitions to the architectural design, where we explore howSpringBoot’s capabilities are optimally utilized to meet these challenges. Following this, we delve into the im- -plementationphase, detailing the strategic selection of compatible technologies and methods for effective data management and discrepancydetection. The paper culminates in a thorough evalu- ation of the system, where we assess performance across various operationalscenarios, scrutinize the accuracy of the discrepancy detection mechanisms, and integrate real-world feedback from users in thetrading sector. This holistic approach not only highlights the versatility and efficiency of SpringBoot in creating reliable alert systems in the high-stakes world of financial trading but also serves as a detailed guide for similar endeavors in this field

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

In this study we investigated the association between weather types (WTs) and the Urban Heat Island Intensity (UHII) in the region of Attica (Greece). The application of the methodology results in ten WTs over Attica region. The UHII was calculated for every hour of the day from 2008 to 2017, using a new air temperature dataset produced by Copernicus Climate Change Service. To have more clear results concerning the association between WTs and UHII, we have used also the upper 5% of UHII (Urban Overheating-UO). The UO have been estimated for two-time intervals (daytime and nighttime) and for the warm period (June-September). The UHII frequency distribution as well as the spatial characteristics of the UO were also investigated. It was found that UO was amplified under WT2 during the night while, WT10 was mainly responsible for exacerbated UO magnitude at daytime, in all months. Furthermore, analysis results revealed that the UO effect is more pronounced in Athens during the night, especially at Athens center. The daytime hot-spots identified mainly in sub-urban and rural areas. Therefore, this methodology may help for heat mitigation strategies and climate adaptation measures, in urban environments.

This review paper delves into the multifaceted aspects of pineapple cultivation, focusing on morphology studies, harvesting challenges, and mechanization efforts. Pineapple, renowned for its commercial value and unique flavor, holds a prominent position in global agriculture, with India alone producing 19.64 lakh tonnes annually. However, the hilly terrains of regions like northeastern India pose significant hurdles to traditional harvesting methods, necessitating innovative solutions. Understanding the morphology of pineapple plants is crucial for optimizing cultivation practices and designing efficient harvesting equipment. Insights from various studies shed light on leaf structure, fruit maturity, and growth patterns, providing valuable information for engineering tailored solutions. Mechanization endeavors, including semi-mechanized harvesting machines and semi-manual harvesters, demonstrate promising results in improving efficiency and reducing labor-intensive practices. Despite challenges such as increased crop losses and operational costs, continued research and development in mechanization hold the key to sustainable pineapple cultivation. This paper underscores the importance of integrating morphology studies and mechanization efforts to address the unique challenges faced by pineapple farmers, particularly in hilly terrains, and highlights the need for ongoing innovation to ensure the long-term sustainability of pineapple cultivation.

The differential distribution, size, and quality of urban green spaces (UGS) among localities generate a differential distribution of benefits provided to users. We analyzed the spatial distribution of five size categories of UGS among 15 municipalities of Mexico City, compared their total surface per capita and associated them with the social marginality index. We found 1,353 UGSs accessible for public use with a total area of 2,643 ha. Seventy-four percent of them had &lt;1 ha of surface area, and 51% were located in only three municipalities that were mostly middle- and high-income. These municipalities concentrated a higher area of green spaces per capita. We found a negative correlation between the marginality index and the area of UGS per municipality; the lower the marginality index, the higher the area of green spaces. We consider this a situation of environmental injustice since urban environmental services are distributed unequally with respect to marginalized populations.

The Covid-19 pandemic and the initial focus on handwashing measures have again highlighted the importance of water access as an essential service in protecting human health. Yet, especially in southern cities, uneven geographies of water access – often mediated by fragmented and unequal infrastructure systems – may hamper the fight against infectious diseases. The spread of SARS-CoV-2 presented a dilemma for water providers as well as residents in water-deprived urban areas as they had to adhere to new hygiene standards and requirements, despite limited access to basic water infrastructure. Therefore, a deeper understanding of pandemic urban waterscapes – the infrastructure and governance systems as well as everyday practices and technologies – is necessary for ongoing debates on (post-) pandemic or zoonotic cities. In our paper, we focus on changes in urban (water) governance and government water projects in Nairobi since early 2020. We show that Covid-19 has contributed to changes in Nairobi’s waterscape but only in conjunction with recent changes in the city’s overall governance structure. However, if these waterscape changes lead to greater equity in water access, and if they have helped to curb the spread of SARS-CoV-2, is more than questionable.

The reality of people’s lives has shifted from rural to urban areas, where an ever-increasing proportion of the world’s population lives. Providing infrastructure to serve these areas, especially in the Global South, is a key task of sustainable development. A deep understanding of the spatial arrangement and scales of these urban structures and their temporal evolution can help to develop innovative solutions to issues of energy, water, or transportation infrastructures. For this purpose, in this work we study the temporal evolution of urban built-up structures (Global Artificial Impervious Area) and population distributions (Global Human Settlement Population) in four regions of the Global South (Argentina, India, Egypt, and Nigeria). We qualitatively analyze regularity through the pair correlation function and subsequently identify typical scales within the different interurban systems. In doing so, we identify that especially the large settlement objects arrange themselves in a regular way and thus typical scales exist in urban systems. Thus, settlement objects are usually located about 20 to 40 km apart from each other. This information can be used to develop sustainable infrastructure concepts, for example for passenger transport between settlements.