Previous evidence links the formation of extranuclear inclusions of transcription factors, such as ERK, Jun, TDP-43, and REST with oxidative, endoplasmic-reticulum, proteasomal, and osmotic stress. To further characterize its extranuclear location, we performed a high-content screening based on confocal microscopy and automatized image analyses of an epithelial cell culture treated with hydrogen peroxide, thapsigargin, epoxomicin, or sorbitol at different concentrations and times to recreate the stresses mentioned above. We also performed subcellular fractionation of the brain from transgenic mice overexpressing the Q331K mutated TARDBP, and we analyzed REST-regulated mRNAs. The results show that these nuclear proteins exhibit a mitochondrial location, together with significant nuclear/extranuclear ratio changes, in a protein and stress-specific manner. The presence of these proteins in enriched mitochondrial fractions in vivo confirmed the results of image analyses. TDP-43 aggregation was associated with alteration in mRNA levels of REST target genes involved in calcium homeostasis, apoptosis, and metabolism. In conclusion, cell stress increased mitochondrial translocation of nuclear proteins, increasing the chance of proteostasis alterations. Further, TDP-43 aggregation impacts REST target genes, disclosing an exciting interaction between these two transcription factors in neurodegenerative processes.

Pregnant women with diabetes often present impaired fetal growth, which is less common if maternal diabetes is well-controlled. However, developing strategies to estimate fetal body composition beyond fetal growth that could better predict metabolic complications later in life is essential. This study aimed to evaluate subcutaneous fat tissue (femur and humerus) in fetuses with normal growth among pregnant women with well-controlled diabetes using a reproducible 3D-ultrasound tool and offline TUI (Tomographic Ultrasound Imaging) analysis. Additionally, three artificial intelligence classifier models were trained and validated to assess the clinical utility of the fetal subcutaneous fat measurement. A significantly larger subcutaneous fat area was found in three-femur and two-humerus selected segments of fetuses from women with diabetes compared to the healthy pregnant control group. The full classifier model that includes subcutaneous fat measure, gestational age, fetal weight, fetal abdominal circumference, maternal body mass index, and fetal weight percentile as variables, showed the best performance, with a detection rate of 70%, considering a false positive rate of 10%, and a positive predictive value of 82%. These findings provide valuable insights into the impact of maternal diabetes on fetal subcutaneous fat tissue as a variable independent of fetal growth.

Interferon-beta is one of the most widely prescribed disease-modifying therapies for multiple sclerosis patients. However, this treatment is only partially effective, and a significant proportion of patients do not respond to this drug. This paper proposes an alternative fuzzy logic system based on the opinion of a neurology expert to classify relapsing-remitting multiple sclerosis patients: high, medium, and low responder to interferon-beta. Also, a pipeline prediction model trained with biomarkers associated to interferon-beta response is proposed for predicting whether patients are potential candidates to be treated with this drug, in order to avoid ineffective therapies. The classification results shows that the fuzzy system presents a 100% efficiency compared with an unsupervised hierarchical clustering method (52%). So, the performance of the prediction model is evaluated, and a 0.8 testing accuracy is achieved. Hence, a pipeline model including data standardization, data compression, and a learning algorithm, can be a useful tool for getting reliable predictions about the response to interferon-beta.

Steel is one of the essential materials in the world's civilization. It is essential to produce many products such as pipelines, mechanical elements in machines, vehicles, profiles, and beam sections for buildings in many industries. Until the '50s of the 20th century, steel products required a complex process known as ingot casting; for years, steelmakers focused on developing and simplifying this process. The result was the con-tinuous casting process (CCP); it is the most productive method to produce steel. The CCP allows producing significant volumes of steel sections without interruption and is more productive than the formal ingot casting process. The CCP begins by transferring the liquid steel from the steel-ladle to a tundish. This tundish or vessel distributes the liquid steel, by flowing through its volume, to one or more strands having wa-ter-cooled copper molds. The mold is the primary cooling system, PCS, solidifying a steel shell to withstand a liquid core and its friction forces with the mold wall. Further down the mold, the rolls drive the steel section in the SCS. Here the steel section is cooled, solidifying the remaining liquid core, by sprays placed in every cooling segment all around the billet and along the curved section of the machine. Finally, the steel strand goes towards a horizontal-straight free-spray zone, losing heat by radiation mechanism, where the billet cools down further to total solidification. A moving torch cutting-scissor splits the billet to the desired length at the end of this heat-radiant zone.

Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub (e.g. airports) or to evacuate a disaster zone. Many methods have been used to solve this issue, including the implementation of a variety of sensors and other signal receiving systems. Most interestingly, camera-based techniques have increasingly become more popular in this kind of applications, given their robustness and scalability. In this paper, we have implemented an end-to-end strategy to address this scenario, allowing a robot to solve a maze in an autonomous way, by using computer vision and path planning. In addition, this robot shares the generated knowledge to another by means of communication protocols, having to adapt its mechanical characteristics to be able to solve the same challenge. The paper presents experimental validation of the four components of this solution, namely camera calibration, maze mapping, path planning and robot communication. Finally, we present the integration and functionality of these methods applied in a pair of NAO robots.

The growth of urban population, combined with an increase of extreme events due to climate changes call for a better understanding and representation of urban floods. Rainfall and infiltration are two important factors that affect the watershed response to a given precipitation event. In this paper, we evaluate the influence of the representation of infiltration and spatially variable rainfall on the computer simulation of the floods that affected the city of Hull, UK in June 2007. This work compares a uniform rainfall with one generated using Kriging with External Drift and a constant infiltration equal to the soil hydraulic conductivity with a neglected infiltration. The results of the four simulations are then compared with the flood extents observed by public authorities. It results that the computer model is able the reproduce the general dynamic of the flood and identify the main inundated areas. We found that neglecting the infiltration induce a better representation of this flood event. Furthermore, the use of radar rainfall results in an accuracy similar to the one obtained with a constant rainfall. This study indicates that when the spatial resolution of the rainfall data is low compared to the catchment size and the precipitation distribution is uniform, the spatial variability of the rainfall might not add significant information.

The numerical simulation of entropy generation at mixed natural free and forced convection flow in a square lid-driven cavity filled with an eletrically conducting binary fluids saturated porous media in the presence of a magnetic field is performed in this investigation. Both the top and bottom horizontal walls of the cavity are kept at constant and different temperatures while the left and right vertical walls are adiabatic and insulated. The magnetic field is applied in normal direction to the cavity. The Darcy model, including Brinkman term relative to viscous effects and Forchheimer term due to inertial forces, is used for the momentum equations, and the SIMPLER algorithm, based on the control volume finite-element method approach is used to solve the pressure –velocity coupling. The flow pattern and the heat transfer characteristics inside the cavity are presented in the form of isotherms, streamlines and isentropic lines and average Nusselt number trend. The entropy generation rate is determined for various values of Darcy number (10^-3 ≤ Da ≤ 1) and for a range of Hartmann number (0 ≤ Ha ≤ 10²). This study is limited to Pr = 7 which corresponds to water. It is observed that entropy generation is very affected by the variations of dimensionless control parameters considered.

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

One of the most burning topics in cybersecurity in 2023 will undoubtedly be the compliance with the Software Bill of Materials. Since the US president issued the Executive Order 14028 on Improving the Nation’s Cybersecurity, software developers have prepared and bills are transmitted to vendors, customers, and users, but they don’t know what to do with the reports they are getting. In addition, since software developers have identified the values of the Software Bill of Materials, they have been using the reports extensively. This article presents an estimate of 270 million requests per month, just from form one popular tool to one vulnerability index. This number is expected to double every year and a half. This simple estimate explains the urgency for automating the process. We propose solutions based on artificial intelligence and machine learning, and we base our tools on the existing FAIR principles (Findable, Accessible, Interoperable, and Reusable). This methodology is supported with a case study research and Grounded theory, for categorising data into axis, and for verifying the values of the tools with experts in the field. We showcase how to create, and share Vulnerability Exploitability eXchange data, and automate the Software Bill of Materials compliance process with AI models and a unified computational framework combining solutions for the following problems: (1) the data utilisation problem, (2) the automation and scaling problem, (3) the naming problem, (4) the alignment problem, (5) the pedigree, and provenance problem, and many other problems that are on the top of mind for many security engineers at present. The uptake of these findings will depend on collaborations with government and industry, and on the availability and the ease of use of automated tools.

This document makes a comprehensive analysis of the inequality of the water market in Chile, measured by the Gini coefficient method. The situation of water rights in Chile is of particular interest because it is a completely privatized system, where rights are traded in the market and therefore water is presented as a commodity. This privatization of water in Chile occurred as part of the process of neoliberalization since the 1981 Water Code. The results of this study indicate that both the concentration and the inequality in the distribution of water rights is very high. It proposes a profound revision of applying a mercantile logic to a scarce basic resource for life such as water and exploring the importance of its role as a national good for public use.

This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/ independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

We present the real number system as a natural generalization of the natural numbers. First, we prove the co-finite topology, $Cof(\mathbb N)$, is isomorphic to the natural numbers. Then, we generalize these results to describe the continuum $[0,1]$. Then we prove the power set $2^{\mathbb Z}$ contains a subset isomorphic to the non-negative real numbers, with all its defining structure of operations and order. Finally, we provide two different constructions of the entire real number line. We see that the power set $2^{\mathbb N}$ can be given the defining structure of $\mathbb R$. The constructions here provided give simple rules for calculating addition, multiplication, subtraction, division, powers and rational powers of real numbers, and logarithms. The supremum and infimum are explicitly constructed by means of a well defined algorithm that ends in denumerable steps. In section 5 we give evidence our construction of $\mathbb N$ and $\mathbb R$ are canonical; these constructions are as natural as possible. In the same section, we propose a new axiomatic basis for analysis. In the last section we provide a series of graphic representations and physical models that can be used to represent the real number system. We conclude that the system of real numbers is completely defined by the order structure of $\mathbb N$.}

The European mink (Mustela lutreola) is one of Europe's most endangered species, and it is on the brink of extinction in the Iberian Peninsula. The species' precarious situation requires the application of new ex-situ conservation methodologies that complement the existing ex-situ and in-situ conservation measures. Here, we report for the first time the establishment of a biobank of European mink mesenchymal stem cells (emMSC) and oocytes from specimens found dead in the Iberian Peninsula, either free or in captivity. New emMSC lines were isolated from different tissues: bone marrow (emBM-MSC), oral mucosa (emOM-MSc), dermal skin (emDS-MSC), oviduct (emO-MSc), endometrium (emE-MSC), testicular (emT-MSC), and adipose tissue from two different adipose depots: subcutaneous (emSCA-MSC) and ovarian (emOA-MSC). All the eight emMSC lines showed plastic adhesion, detectable expression of characteristic markers of MSCs and, when cultured under osteogenic and adipogenic conditions, differentiation capacity to these lineages. Additionally, we were able to keep 227 Cumulus-oocyte complexes (COCs) in the biobank, 97 of which are grade I or II. The European mink MSC and oocyte biobank will allow for the conservation of the species' genetic variability, the application of assisted reproduction techniques, and the development of in vitro models for studying the molecular mechanisms of infectious diseases that threaten the species' precarious situation.

Abstract Chaga´s disease caused by Trypanosoma cruzi infections is included in the group of neglected diseases, and efforts to develop new therapeutic or immunoprevention approaches have not been successful. After the publication of the T. cruzi genome, the number of molecular and biochemical studies on this parasite have increased considerably, many of which are focused on families of variant-surface-proteins, especially the trans-sialidases, mucins and mucin-associated proteins. The disperse gene protein 1 family (DGF-1) is one of the most abundant families in the T. cruzi genome, however, the large gene size, high copy numbers, and low antibody titers detected in infected humans make it an unattractive study target. Here, we argue that the DGF-1 gene family although not being the most obvious participant of the host-parasite immunological gamble, where T. cruzi appears to have the upper hand, it may play an important role in more basic host-parasite interactions that deserve further examination.

We provide an axiomatic base for the set of natural numbers, that has been proposed as a canonical construction, and use this definition of $\mathbb N$ to find several results on finite group theory. Every finite group $G$, is well represented with a natural number $N_G$; if $N_G=N_H$ then $H,G$ are in the same isomorphism class. We have a linear order, on the quotient space of isomorphism classes of finite groups, that is well behaved with respect to cardinality. If $H,G$ are two finite groups such that $|H|=m<n=|G|$, then $H<\mathbb Z_n\leq G\leq\mathbb Z_{p_1}^{n_1}\oplus\mathbb Z_{p_2}^{n_2}\oplus\cdots\oplus\mathbb Z_{p_k}^{n_k}$ where $n=p_1^{n_1}p_2^{n_2}\cdots p_{k}^{n_k}$ is the prime factorization of $n$. We find a canonical order for the objects of $G$ and define equivalent objects of $G$, thus finding the automorphisms of $G$. The Cayley table of $G$ takes canonical block form, and we are provided with a minimal set of independent equations that define the group. We show how to find all groups of order $n$, and order them. We give examples using all groups with order smaller than $10$, and we find the canonical block form of the symmetry group $\Delta_4$. In the next section, we extend our results to the infinite case, which defines a real number as an infinite set of natural numbers. A real function is a set of real numbers, and a sequence of real functions $f_1,f_2,\ldots$ is well represented by a set of real numbers, as well. In general, we represent mathematical objects using the smallest possible data-type. In the last section, mathematical objects are well assigned to tree structures. We conclude with brief comments on type theory and future work on computational aspects of these representations.

In this paper, we introduce a new class of open sets that is called is*-open set . Also, we present the notion of is*-continuous, is*-open, is*-irresolute, is*-totally continuous, and is-contra-continuous mappings, and we investigate some properties of these mappings. Furthermore, we introduce some is*-separation axioms, and is*-mappings are related with is*-separation axioms. . .

This work focused on the evaluation of some machine learning (ML) models and their application in e-health, using intermediate nodes within an Internet of Things (IoT) platform used for heartbeat anomaly detection. For the evaluation of ML models, a set of statistical validation metrics was selected. These metrics were applied in the training, testing and validation phases of the models. The results obtained can determine relevant factors for the selection of ML models, either based on the statistical and intrinsic efficiency of the ML models, or on their suitability to be implemented in intermediate nodes within an IoT platform. the more Lightweight models such as Simple Linear Regression, Logistic Regression, and K Nearest Neighbors, could easily operate in intermediate nodes, and they are models that require low processing and storage to work. In conclusion, the approach for intermediate nodes of Internet of Things platforms using cognitive networks decreases the processing cost in cloud computing and transfers it to the fog layer.

NSD3 is a member of the NSD histone methyltransferase family of proteins. In recent years, it has been identified as a potential oncogene in certain types of cancer. NSD3 gene encodes three isoforms, the full length, a short (NSD3S) and WHISTLE isoforms. Importantly, NSD3S isoform corresponds to the N-terminal of the full-length protein, lacking the methyltransferase domain. The chromosomal location of NSD3 is frequently amplified across cancer types, such as breast, lung, colon, among others. Recently, this amplification has been correlated to a chromothripsis event, that could explain the different NSD3 alterations found in cancer. Fusion proteins containing NSD3 have also been reported, such as leukemia NSD3-NUP98, and in NUT midline carcinoma (NMC), NSD3-NUT fusion. Its role as an oncogene has been described by modulating different cancer pathways through its methyltransferase activity, or the short isoform of the protein, through protein interactions. Specifically, in this review we will focus on stating the functions that have been characterized as methyltransferase dependent, and those that have been correlated with the expression of the NSD3S isoform. Altogether, there is evidence that both isoforms of NSD3 are relevant for cancer progression, establishing NSD3 as a therapeutic target. However, further functional studies are needed to differentiate NSD3 oncogenic activity as dependent or independent of the catalytic domain of the protein, as well as the contribution of each isoform and its clinical significance in cancer progression.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Urban planning is recognized as an interaction between the state and society, which aims to articulate public policies in the territory, facilitating their administration in favor of greater development and well-being of society. However, this interaction becomes complex because consumption demands increase, and the needs of the community exceed the capacity of the urban ecosystem to supply them, hindering its sustainable functionality. With this panorama, it becomes relevant to study urban planning from a sustainable environmental planning perspective, based on four topics: urban planning, sustainability, resilience and smart cities. The methodology used is based on a bibliometric study through a PRISMA adjustment to 87 articles, supported by VOSviewer® to construct and visualize the co-occurrence networks of important terms extracted from a body of scientific literature. The main result is to consider cities with a complex systems approach that works like a gear, that is, there is a connective element between inter- and intra-urban processes. This relationship is the key factor that allows understanding their synchronization, stating that the deepening of each of these topics is crucial to the ideal of a territorial administration through time scales, by means of adaptive cycles, allowing to provide new tools to concepts such as carrying capacity and the measurement of the environmental footprint.

The present study contributes to bridging the gap on research related to the presence and distribution patterns of carnivore mammals in the western state of Michoacán, highlighting the importance and need to increase efforts aimed at the study and monitoring of wildlife present in this region. The distribution of carnivore in western Mexico was modeled through the application a two-scale approach: a large, modeled region, corresponding to the western part of the country, for which models were obtained that represent the distribution potential of the species, and, the second modeled study area that includes only the western portion of the state of Michoacán, in which models of the current distribution of the species for this region were proposed. A series of predictive models were generated on the current distribution of 11 species of carnivore species (Canis latrans, Urocyon cinereoargenteus, Herpailurus yagouaroundi, Leopardus pardalis, Leopardus wiedii, Puma concolor, Panthera onca, Conepatus leuconotus, Bassariscus astutus, Nasua narica, Procyon lotor), from which, prioritization exercises were carried out on important areas for the conservation of these species, as well as the comparison and analysis of the existing natural protected areas (NPA) in the study area. The different exercises for prioritizing areas for conservation yielded similar results and show the potential percentages of the landscape that can be subjected to protection and conservation programs.

Due to the retrognathic mandible, an orthodontist frequently observes skeletal class II malocclusion in growing patients. The preferred technique for analyzing and monitoring the temporomandibular joint alterations caused by the functional device is magnetic resonance imaging [MRI]. The study aimed to assess and compare changes in the articular disc's dimension and location before and following the use of various class II correctors to correct the class II molar relation using MRI technology. Methods: 39 adolescent patients aged 15-23 years old [24 girls and 15 boys] who were diagnosed with skeletal Class II division 1 malocclusion based on clearly defined criteria underwent treatment with either the power scope II [PS], Sabbagh Advanced Repositioning Appliance [SARA] and or Dynaflex [DF] with fixed appliances. For fixed functional treatment, the average length of treatment was 5-7 months. The changes in the articular disc dimension and position and condylar position were assessed. The study was done at the Department of Orthodontics at the College of Dentistry, Hawler Medical University in Erbil City. Results: Group DF has a significant effect on the condylar position index and posterior joint space on the closed mouth and disc length on both open and close mouth techniques, and in the group SARA, disc position, and condylar position index on closed mouth technique have shown that significant differences were observed. Conclusion: Class II malocclusions can be effectively corrected by fixed functional appliances. The statistical significance forward movement of the condyle in the glenoid fossa and the posterior movement of the articular disc concerning the condylar head was observed. The mechanism of action of functional appliances appears to include the forward migration of the C-GF complex.

The development of sustainability, the improvement of the quality of life, and the protection of future generations have become of prime importance in light of climate changes and carbon emissions. Universities are at the top of institutions that should participate in creating an environmentally friendly infrastructure. This study thus aimed to explore the extent to which Saudi universities achieve sustainability in the light of the Saudi Green Initiative from the faculty members’ perspective. Surely, this investigation would produce a proposal to promote sustainability in Saudi universities. A questionnaire consisting of five dimensions, namely academic sustainability, community partnership, resource management, planning and administration, and innovation and leadership was developed and administered to 120 faculty members from five Saudi universities. The participants’ ratings of Saudi universities’ achievement of sustainability dimensions ranged from high to moderate. Based on the results, a proposal was offered to take sustainability in Saudi universities to a higher level.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

Mental Disorders are an important public health problem. The main of this study was to analyze the prevalence of Mental Disorders and Environmental Quality. Data on the Prevalence of Mental Disorders, Gross Domestic Product, and Median Years of Schooling from 178 countries were used. A positive association was observed and was independent of Gross Domestic Product and Median Years of Schooling.

The steep rise in reinforcement learning (RL) in various applications in energy as well as the penetration of home automation in recent years are the motivation for this article. It surveys the use of RL in various home energy management system (HEMS) applications. There is a focus on deep neural network (DNN) models in RL. The article provides an overview of reinforcement learning. This is followed with discussions on state-of-the-art methods for value, policy, and actor–critic methods in deep reinforcement learning (DRL). In order to make the published literature in reinforcement learning more accessible to the HEMS community, verbal descriptions are accompanied with explanatory figures as well as mathematical expressions using standard machine learning terminology. Next, a detailed survey of how reinforcement learning is used in different HEMS domains is described. The survey also considers what kind of reinforcement learning algorithms are used in each HEMS application. It suggests that research in this direction is still in its infancy. Lastly, the article proposes four performance metrics to evaluate RL methods.

The aim of this paper is to create a sensor model based on optical crystal fibers (PCF). The aim of this model is to find and identify zinc cadmium. This thesis looked at three different categories of concentrations. For sensor architecture, PCF was generated using single-mode fiber-to-end split fusion (SM-PCF-SM). In this experiment, a specific wavelength spectrum was used to alter the concentration of materials covering the fiber in order to demonstrate the fiber's sensing capability. The 550nm wavelength has been used as the optical source for the fiber. The change in the output power of the external light was monitored and changes were observed for each concentration of the concentrations around the fiber. It has been found that the fiber is sensitive to small changes in concentrations. The absorption of the fiber has been calculated for the incoming capacity, as well as the losses in the capacity outside the fiber.

Immune checkpoint inhibitors (ICIs) – anti-programmed death-1 (PD-1) and their ligands (PD-L1 and PD-L2) have become widely used in the treatment of several malignancies. Many immune-related adverse events have been linked to these agents. However, tuberculosis (TB) reactivation during their use is increasingly reported. Herein, we present a 58-year-old lady with advanced non-small cell lung cancer (NSCLC) ALK-negative, EGFR wild, and PD-L1 Immune histochemistry (IHC) strongly positive in 95% of tumor cells. The patient presented with high-grade fever and a history of productive cough for a 1-week duration. A few days later, she was diagnosed with pulmonary tuberculosis following the 6th cycle of Pembrolizumab, an anti-PD-1 monoclonal antibody. AFB smear and TB PCR from BAL were positive (rifampin resistance not detected), and she was accordingly started on Anti-TB medications. Immunotherapy was held. Of note, the patient had a history of sick contact with a patient with active TB infection ten years ago, but there was no documentation of latent TB or previous TB infection. Her HIV status is negative. Her sputum AFB smear continued to be positive after four weeks of anti-TB medications. Later, the patient was discharged after her sputum was cleared from AFB (negative x 2 sets). We assumed that our patient developed reactivation of pulmonary tuberculosis secondary to an immune checkpoint inhibitor (Pembrolizumab). She was not re-challenged with Pembrolizumab following TB diagnosis. To our knowledge, this is the first reported case from the Arab and the Middle East; it reinforces the previous observations of the association between ICIs administration and the development of MTB. Nevertheless, further studies in the clinical setting are necessary to establish the exact mechanism involved in this association. Oncologists' awareness & prompt recognition of this potential hazardous consequence are essential. Since there is no clear evidence whether LTBT prior PD-1/PD targeted immunotherapy is required, targeted LTBT before starting ICIs immunotherapy with TB chemoprophylaxis; yet to be explored, particularly in the regions where the MTB prevalence is high.

This work presents a design and model of the thermo-hydrodynamic behavior applying CFD for pin-fin heat sink with square shape (rectangular fin profile), through a novel pin arrangement that improves heat removal in the system. The novelty consist in the insertion of a deflector row that will help to direct the flow, so it hits the rectangular cross-sectional fins the presents in the system. The heat sink model is placed in channel designed in which air flows as suitable medium, and its overall performance is investigated. In addition, a constant heat flux is applied to the bottom wall of the heat sink model, equal values and amounts that​ correspond to the heat fluxes generated by current electronic equipment and devices. The numerical results of the global thermal resistance, the pressure drop and the Nusselt number are reported. The results allow determining best arrangement or geometry configuration, location and functionality of the fin-deflectors were collocated for evaluate thermal-hydraulic efficiency of system.

Flooding, exacerbated by climate change, poses a significant threat to certain areas, increasing in frequency and severity. In response, the construction of supplementary dams has emerged as a reliable solution for flood management. This study employs a Remote Sensing (RS) approach integrated with GIS to assess the feasibility of constructing a supplementary dam near Linville, Brisbane, Australia, with the aim of mit-igating floods and preventing overtopping failure at the Wivenhoe Dam. Using QGIS software and a 25-meter resolution DEM from the Queensland Spatial Catalogue ‘QSpatial’ website, four potential dam sites were analysed, considering cross-sections, watershed characteristics, and water volume calculations. Systematic selection criteria were applied to identify the most optimal option based on dam wall di-mensions, volume-to-area, and volume-to-cost ratios. The selected option was further assessed against predefined criteria, yielding one optimal choice. The study provides insights into the feasibility and ef-fectiveness of supplementary dam construction for flood mitigation in the region, with recommendations for future research and implementation.

Advanced Hepatocellular carcinoma (HCC) is no longer a terminal illness. This change was mainly attributed to the development of new treatments including tyrosine-kinase inhibitors (TKIs), vascular endothelial growth factor (VEGF) inhibitors and immune checkpoint inhibitors (ICPIs) but the financial toxicity of treating advanced HCC is of a major concern specially in low middle-income countries (LMICs) where the patients are still battling for their most basic rights. Most of advanced HCC patients in LMICs have very limited accessibility to the new treatments including ICPIs. Searching for out of the box solutions to improve access to treatments -mainly ICPIs- is an utmost necessity for LMICs advanced HCC patients.

Shewanella spp. are gram-negative bacteria that thrive in aquatic niches and also cause infectious diseases as opportunistic pathogens. Chromosomal integrons (CI) and mobile integrons (MI) were previously described in some Shewanella isolates. Here, we evaluated the occurrence of integrase genes, the integron systems and their genetic surroundings in the genus. We identified 22 integrase gene types, 17 of which were newly described, in different Shewanella species, evidencing multiple gain and loss events. Phylogenetic analysis showed that most of them were strain-specific, except for Shewanella algae, which seem to have co-evolve within the host as typical CIs. Noteworthy, co-existence of up to 5 different integrase genes, as well as their wide dissemination to Alteromonadales, Vibronales, Chromatiales, Oceanospirillales and Enterobacterales was observed. Identification of novel MIs suggests that lateral genetic transfer may have occurred resembling the behavior of class 1 integrons. The constant emergence of determinants associated to antimicrobial resistance worldwide, concomitantly with novel MIs in strains capable to harbor several types of integrons may be an alarming threat for the recruitment of novel antimicrobial resistance gene cassettes in the genus Shewanella, and its evolution towards the multidrug resistance.

A continuous spatio-temporal database of accurate soil moisture (SM) measurements is an important asset for agricultural activities, hydrologic studies, and environmental monitoring. The Advanced Microwave Scanning Radiometer 2 (AMSR2), launched in May 2012, has been providing SM data globally with a revisit period of two days. It is imperative to assess the quality of this data before performing any application. Since resources of accurate SM measurements are very limited in Puerto Rico, this research will assess the quality of the AMSR2 data by comparing with ground-based measurements and perform a downscaling technique to provide a better description of how the sensor perceives the surface soil moisture as it passes over the island. The comparison consisted of the evaluation of the mean error, root mean squared error, and the correlation coefficient. Two downscaling techniques were used and their performances were studied. The results revealed that AMSR2 products tend to underestimate. This is due to the extreme heterogeneous distributions of elevations, vegetation densities, soil types, and weather events on the island. This research provides a comprehensive study on the accuracy and potential of the AMSR2 products over Puerto Rico. Further studies are recommended to improve the AMSR2 products.

Colistin [polymyxin E] is a veterinary exclusive antimicrobial and one of the oldest antibiotics that is currently recognised as one of the highest priority critically important antimicrobials for humans. It is extensively used for multiple medical and non-medical purposes particularly for growth promotion, prophylaxis/metaphylaxis and therapeutic in food animals. As a result, colistin resistance was widespread along the food-chain linking to multidrug resistant bacterial infections in humans reflected by greater use of colistin in healthcare settings resulted in different types of bans/restrictions in food-producing animals, around the world. This report debates the testimonies of 23 countries representing the bulk of global food producing animal production, providing robust evidence on the essential need for colistin in animal production.

Urban and agricultural runoffs can transport contaminants and pesticides into freshwater ecosystems, particularly in the developing tropics. For instance, organophosphate and pyrethroids pesticides like glyphosate, malathion, and permethrin have been found in tropical streams. The uncontrolled application of these pesticides has become a growing concern due to their adverse effects on various non-targeted organisms. Unfortunately, most studies have focused on a few selected model species, ignoring the effects on other nontarget organisms, which may play an important role in tropical lotic ecosystems. In addition, the biological characteristics of aquatic crustaceans, including their morphology, physiology, and behavior, make them susceptible to toxic chemicals. For this reason, this study used the widely distributed freshwater shrimp Xiphocaris elongata as a model organism to determine the acute toxicity of permethrin, malathion, and glyphosate. Our results show that the proportion of mortality of X. elongata in each concentration group became progressively higher as the concentration of exposure increased. We also found that the synthetic pyrethroid permethrin is the most toxic pesticide tested, followed by organophosphate malathion and glyphosate. Experiments with this freshwater shrimp showed a good control performance and reproducibility for the tested pesticides. This study demonstrated that X. elongata is a suitable test organism that can be a representative bioindicator of pesticide toxicity in tropical streams.

Aptamers are synthetic single stranded oligonucleotides that exhibit selective binding properties to specific targets, thereby providing as powerful basis for the development of selective and sensitive (bio)chemical assays, such as biosensors. Electrochemical biosensors, utilizing aptamers as biological recognition elements, namely aptasensors, are at the forefront of current research. They exploit the combination of the unique properties of aptamers with the advantages of electrochemical detection with the view to fabricate inexpensive and portable analytical platforms for rapid detection in point-of-care (POC) applications or on-site monitoring. The immobilization of aptamers on suitable substrates is of paramount importance with the aim to retain their functionality and optimize the sensors’ sensitivity. This work describes different immobilization strategies for aptamers on the surface of semiconductor-based working electrodes, including metal oxides, conductive polymers and carbon allotropes. These are presented as platforms with tunable band gaps and different surface morphologies for the preparation of low cost, highly versatile aptasensor devices in analytical chemistry. A survey of the current literature is provided, discussing each analytical method. Future trends envisage for aptamer-based biosensing using semiconductors are also outlined.

Pozol is a Mexican beverage prepared from fermented nixtamalized maize dough. To contribute to understanding its complex microbial ecology, the effect of inoculating on MRS-starch pure and mixed cultures of amylolytic Sii-25124 and non-amylolytic W. confusa 17, isolated from pozol, were studied on their interactions and fermentation parameters. These were compared with L. plantarum A6, an amylolytic strain isolated from cassava. Microbial growth, kinetic parameters, amylolytic activity, lactic acid production, and hydrolysis products from starch fermentation were measured. The population dynamics were followed by qPCR. L. plantarum A6 showed higher enzymatic activity, lactic acid, biomass production, and kinetic parameters than pozol LAB in pure cultures. Mixed culture of each pozol LAB with L. plantarum A6 showed a significant decrease in amylolytic activity, lactic acid yield, specific growth rate, and specific rate of amylase production. The interaction between Sii-25124 and W. confusa 17 increased the global maximum specific growth rate (µ), the lactic acid yield from starch (Ylac/s), lactic acid yield from biomass (Ylac/x), and specific rate of lactic acid production (qlac) by 15, 30, 30, and 40%, respectively compared with the pure culture of Sii-25124. Interactions between the two strains are essential for this fermentation.

Floods are the most frequent and devastating disasters in Bangladesh. The riverine islands, known as char-lands, are particularly vulnerable to flooding. As flooding poses a significant threat to the lives and livelihoods of residents, especially farmers, it is crucial to understand how they perceive flood risk and assess their adaptation strategies in this geographically susceptible context. However, the existing literature has not adequately addressed these issues. Therefore, this study aims to analyze the factors influencing farmers' perceived flood risk and their assessments of flood adaptation. In a survey of 359 farmers in Bangladesh's char-land region, located in the Chowhali sub-district of Sirajganj district, we used the protection motivation theory (PMT) to measure farmers' perceived flood risk and adaptation assessments. Multiple regression analysis was employed to identify factors influencing them. Farmers prioritized the risk to livelihoods (production and income) over psychological aspects (health and diseases). Larger farms, more flood experience, and greater risk awareness are associated with higher overall flood risk perception; and better flood adaptation, indicating higher self-efficacy, response efficacy, and response cost among farmers. Farmers perceived lower flood risk in exchange for greater house distance from the river and more trust in government actions. Hence, strengthening campaigns and programs is crucial to understanding flood risk in char-lands for improved adaptation to floods. The study highlights the application of PMT to assess farmers' perceptions of flood risk and their attitudes towards adaptation, suggesting further research opportunities.

Robotic surgery is a rapidly developing and evolving surgical technique. This literature review evaluates the advantages and disadvantages in the context of gallbladder disease comparing robotic Cholecystectomy to the well-established laparoscopic Cholecystectomy. Significant advantages are reduced operative blood loss, hospital stays and post operative pain, alongside increased patient satisfaction and improved visualization and precision compared to the laparoscopic approach. Disadvantages include lack of tactile feedback, significant cost attributed to equipment, training requirements and increased procedural time due to the set-up sequences. The implementation of robotic surgery also poses significant changes for the training of future surgeons. Whilst it can standardize training and increases opportunity for simulation, the concern is the loss of traditional skills. Currently the evidence base remains mixed however the use of robotics in the right setting, with suitably trained operatives and appropriate patients can enable improved outcomes for patients with gallbladder disease. There is a lot of scope for development including the implementation of tactile feedback to aid operative technique and artificial intelligence to aid patient safety. Likely broadening the use and potential benefit of robotic surgery not only for cholecystectomy but many surgical specialties.

Prevalence of overweight and obesity are escalating globally among the general population. However, there are limited evidence on the trends and prevalence of overweight /obesity in the military setting. Increased rates of injuries, low work productivity, incurred higher healthcare costs and prematurely discharge from service are consequences of overweight/obesity among the military. Therefore, we aimed to systematically describe the trends and prevalence of overweight and obesity in the military population, by regions and military service branches. Databases including PubMed, Scopus, Web of Science and Google Scholar were used. Inclusion criteria were military population (inclusive of all service branches) with BMI reported as the overweight/obesity indicator. Population related to military but not exclusively military personnel such as the retirees, the veterans and their dependents were excluded. From the 27 included studies, 13 were published between year 2010 to 2014 and half were conducted in the United States. Overall, studies showed increasing trend in the prevalence of overweight (30% to 50%) and obesity (2% to 30%); only one study showed a decreasing trend of 0.9% and 0.6% for the prevalence of overweight and obesity respectively. However, the rates of increment differed between countries, where Asian countries demonstrated lower overweight prevalence compared to the United States and the European countries. In conclusion, the military population is not protected from overweight and obesity. Interventions should be implemented to prevent overweight / obesity among the military personnel.

This paper reports on the fabrication of alumina doped preforms using MCVD-vapor phase chelate delivery system with Al(acac)3 as the precursor. The objectives of the work are to study the deposition process, the efficiency of the fabrication process, and the quality of the fabricated fiber preforms. Two parameters are studied, Al(acac)3 sublimator temperature (TAl°C) and deposition direction (i.e. downstream and upstream). Other parameters such as oxygen flow and deposition temperature are fixed. The results showed that a high uniformity of refractive index difference (%RSD &lt; 2%) and core size (%RSD &lt; 2.4%) was obtained along the preform length using downstream deposition while for the combined upstream and downstream deposition the uniformity was deteriorated. The process efficiency was found to be about 21% for TAl°C of 185°C and downstream deposition. From the EDX elemental analysis, the refractive index was found to increase by 0.0025 per mole percent of alumina.

The use of different sources to energize a load is convenient in many applications, particularly those where two or more renewable energy sources are employed as: energy harvesting, hybrid vehicles, and off-grid systems. In these cases, a multi-input converter able to admit sources with different characteristics and, if necessary, select the output power of each source. Several topologies of multi-input converters have been proposed to this aim, however, most of them are based on multi-stage designs, which decreases efficiency and increases control complexity, particularly when more than two sources are used. In this work, a three-input step-up converter easy to control in open loop condition is analyzed. A designed procedure is described, and experimental results are presented for a 1 kW power converter. The implemented converter results in a higher voltage gain, less storage element keeping high efficiency compared to similar topologies. Using the procedure here proposed, this converter that was initially proposed for photovoltaic applications is enabled to be used in medium and high-power applications, for example when renewable energy sources are used.

Modern imaging strategies are paramount to studying living systems such as cells, bacteria, and fungi and their response to pathogens, toxicants, and nanomaterials as modulated by exposure and environmental factors. The need to understand the processes and mechanisms of damage, healing and cell survivability of living systems continues to motivate the development of alternative imaging strategies. Of particular interest is the use of label-free techniques that minimize interference of biological processes by foreign marking substances and reduce intense light exposure and potential photo-toxicity effects. This review focus on the potential synergic capabilities of atomic force microscopy (AFM) as a well-developed and robust imaging strategy with demonstrated applications to unravel intimate details in biomedical applications, with the label-free, fast, and enduring Holotomographic Microscopy (HT) strategy. We first review the operating principles that form the basis for the complementary details provided by these techniques regarding the surface and internal information provided by HT and AFM is essential and complimentary for the development of several biomedical areas studying the interaction mechanisms of nanomaterials with living organisms. First, AFM can provide superb resolution on surface morphology and biomechanical characterization. Second, the quantitative phase capabilities of HT enable superb modeling and quantification of the volume, surface area, protein content, and mass density of the main components of cells and microorganisms, including morphology of cells in microbiological systems. These capabilities result from directly quantifying refractive index changes without requiring fluorescent markers or chemicals. As such, HT is ideally suited for long-term monitoring of living organisms in conditions close to their natural settings. We present a case-based review of the principal uses of both techniques and their essential contributions to nanomedicine and nanotoxicology, emphasizing cancer and infectious disease control. The synergic impact of the sequential use of these complementary strategies provides a clear drive for adopting these techniques as interdependent fundamental tools.

Sustainability addresses environmental and social issues affecting this and future generations. When family businesses perceive that the community is disrupted, recognize an environmental problem and respond by implementing new environmental policies or regulations, the family business’s socio-emotional values press to transition to a more sustainable production system, such as the ‘Circular Economy.’ Drawing on the Dubin (1978) methodology—a paradigm for building models through deduction—we design a sustainable model, which shows family businesses’ responses to changes in the environment. It explains the reasons why family firms transition to the Circular Economy, based on the theory of Socio-Emotional Wealth (SEW). We check the model through the case study of the food retail leader in the Spanish market—Mercadona—which applies policies about energy, resources and waste to become a Circular Economy business model. Because of the strong family character of Mercadona, this case can be useful for the decision-making of other family businesses.

Antisense technologies consist of the utilization of oligonucleotides or oligonucleotide analogs to interfere with undesirable biological processes, commonly through inhibition of expression of selected genes. This field holds a lot of promise for the treatment of a very diverse group of diseases including viral and bacterial infections, genetic disorders, and cancer. To date, drugs approved for utilization in clinics or in clinical trials target diseases other than bacterial infections. Although several groups and companies are working on different strategies, the application of antisense technologies to prokaryotes still lags with respect to those that target other human diseases. In those cases where the focus is on bacterial pathogens, a subset of the research is dedicated to produce antisense compounds that silence or reduce expression of antibiotic resistance genes. Therefore, these compounds will be adjuvants administered with the antibiotic to which they reduce resistance levels. A varied group of oligonucleotide analogs like phosphorothioate or phosphorodiamidate morpholino residues, as well as peptide nucleic acids, locked nucleic acids and bridge nucleic acids, the latter two in gapmer configuration, have been utilized to reduce resistance levels. The major mechanisms of inhibition include eliciting cleavage of the target mRNA by the host’s RNase H or RNase P, and steric hindrance. The different approaches targeted resistance to β-lactams including carbapenems, aminoglycosides, chloramphenicol, macrolides, and fluoroquinolones.

Over recent years, nanocarriers have played an ever-increasing role in clinical and biomedical applications owing to their unique physicochemical properties and surface functionalities. Lately, much effort has been directed towards the development of smart, stimuli-responsive nanocarriers that are capable of releasing their cargos in response to specific stimulus. These intelligent-responsive nanocarriers can be further surface-functionalized so as to achieve active tumor targeting in a sequential manner, which can be simply modulated by the stimuli. By applying this methodological approach, these intelligent-responsive nanocarriers can be directed to different target-specific organs, tissues or cells, and exhibit on-demand controlled drug release that may enhance therapeutic effectiveness and reduce systemic toxicity. Light, an external stimulus, is one of the most promising triggers for use in nanomedicine to stimulate on-demand drug release from nanocarriers. Light-triggered drug release can be achieved by light irradiation at different wavelengths, either in UV, visible or even NIR region, depending on the photophysical properties of the photo-responsive molecule embedded in the nanocarrier system, the structural characteristics and material composition of the nanocarrier system. In this review, we highlighted the emerging functional role of light in nanocarriers, with emphasis on light-responsive liposomes and dual-targeted stimuli-responsive liposomes. Moreover, we provided the up-to-date phototriggered targeting strategies and mechanisms of light-triggered drug release from liposomes and NIR-responsive nanocarriers. Lastly, we addressed the current challenges, advances, and future perspectives for the deployment of light-responsive liposomes in targeted drug delivery and therapy.

The burden of hepatocellular carcinoma (HCC) continues to pose a significant global health problem. Several systemic therapies have recently been shown to improve survival for patients with unresectable disease. However, evidence is limited to support the use of neoadjuvant or adjuvant systemic therapies in patients with resectable disease, despite the high risk of recurrence. Neoadjuvant and adjuvant systemic therapies are being investigated for their potential to reduce recurrence after resection and improve overall survival. Our review identified various early-phase clinical trials showing impressive preliminary signals of pathologic complete response in resectable disease and others suggesting neoadjuvant therapies, particularly when combined with adjuvant strategies, may convert unresectable disease to resectable and cause significant tumor necrosis, potentially decreasing recurrence rates. The role of adjuvant therapies alone may also have a role in the management of these patients, particularly in reducing recurrence rates. Heterogeneity in trial design, therapies used, patient selection, and a scarcity of randomized phase III trials necessitate the cautious implementation of these treatment strategies. Future research is required to identify predictive biomarkers, optimize the timing and type of therapeutic combinations, and minimize treatment-related adverse effects, thereby personalizing and enhancing treatment strategies for patients with resectable and borderline resectable HCC.

Fire hazards present a multifaceted global challenge that endangers human lives and environmental safety. Despite advancements in fire risk management technologies and methods, fires continue to be a prime concern for human security. The Arabian Gulf region, influenced by its climatic and environmental conditions, is especially susceptible to these threats. The Emirate of Sharjah, part of the United Arab Emirates, has made significant progress in reinforcing fire safety measures within residential structures, achieving a decrease in the number of fire-related accidents compared to neighboring Emirates. However, the incidence rate remains relatively high. This study undertook a thorough review and assessment of the existing Fire Management System (FMS) for Sharjah's residential sector, leading to the recommendation of a more robust framework. Through a series of literature reviews, interviews with stakeholders, and surveys, using analytical techniques such as the Delphi method and Failure Mode Effect and Criticality Analysis, vital factors that influence the FMS's effectiveness were pinpointed. The study exposed that the current FMS was largely reactive. In response, a proactive framework incorporating nine essential components was designed to strengthen the Sharjah FMS. These components span across various domains such as fire assurance, assessment of fire risks, management of accidents, evaluation of performance, training programs, research and development initiatives, digital services, monitoring of regulatory compliance, firefighting strategies, automated responses to fires, recovery processes, as well as the use of resilient materials and architectural design considerations. Furthermore, the research introduced two specific fire indexes, the HRBFI and the EFRI. Anchored in the principles of Systems Thinking and Industry 4.0, this proposed framework is aimed at streamlining Sharjah's approach to fire management in dwellings, with the objective of diminishing the frequency of fire incidents yearly. The ultimate aspiration of this framework is to enhance the Emirate's standing in terms of safety and to guarantee a living environment that is safeguarded against the risk of fires..

This comprehensive analysis thoroughly examines the topic of adversarial attacks in artificial intelligence (AI), providing a detailed overview of the various methods used to compromise machine learning models. It explores different attack techniques, ranging from the simple Fast Gradient Sign Method (FGSM) to the intricate Carlini and Wagner Attack (C&W), emphasising the wide range of adversarial approaches and their intended goals. The discussion also distinguishes between targeted and non-targeted attacks, highlighting the adaptability and versatility of these malicious efforts. Additionally, the study delves into the realm of black-box attacks, revealing the capability of adversarial strategies to compromise models even with limited knowledge. Real-life examples illustrate the tangible consequences and potential dangers of adversarial attacks in various fields such as self-driving cars, multimedia, and voice assistants. These cases highlight the difficulties in ensuring the legitimacy and dependability of AI-powered technologies and programs. The article stresses the importance of ongoing research and innovation to address the growing difficulties posed by advanced methods like deepfakes and disguised voice commands in preserving the security of AI systems. This study provides valuable insights on how different adversarial strategies and defence mechanisms interact within AI. The results emphasise the urgent need for stronger and more secure AI models to combat the increasing number of adversarial threats in today's AI landscape. These findings can guide future research and innovations in developing more resilient AI technologies that can better withstand various adversarial vulnerabilities and challenges.

Abstract Plant uptake and assimilation of essential nitrogen compounds from the soil are mainly in the form of nitrate and ammonium ions. Plant nitrate transporters (NRTs) play a crucial role in nitrate uptake from the soil into the roots. NRT structural analysis reveals the mechanisms by which these transporters function. Similarly, plant ammonium transporters (AMTs) mediate the uptake of ammonium ions, and their structural analysis has provided valuable information on their mechanisms. After nitrogen uptake by plant roots, the nitrogen metabolism pathway involves the incorporation of nitrogen into organic compounds. Glutamine synthetase (GS) and glutamate synthase (GoGAT) are the master players in this pathway. They work together to convert ammonium ions into glutamine and glutamate, respectively. Different isoforms of GS and GoGAT exist, enabling plants to fine-tune nitrogen metabolism based on environmental cues. Under severe abiotic stress conditions, nitric oxide (NO) has been found to enhance plant survival under drought. Furthermore, the interaction between salinity stress and nitrogen availability in plants has been studied, with NO identified as a potential mediator of responses to salt stress. On the other hand, excessive use of nitrate fertilizers can lead to health and environmental issues. Therefore, alternative strategies, such as establishing nitrogen fixation in plants through diazotrophic microbiota, have been explored to reduce reliance on synthetic fertilizers. Ultimately, genomics can identify new genes related to nitrogen fixation, which could be harnessed to improve plant productivity. By deciphering the genetic basis of nitrogen-fixing traits, researchers aim to develop crops that efficiently utilize nitrogen from the environment.

El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, two methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.

This research introduces a pioneering solution to the challenges posed by gastrointestinal tract (GI) cancer in radiation therapy, focusing on the imperative task of precise organ segmentation for minimizing radiation-induced damage. GI imaging has historically used manual demarcation, which is laborious and uncomfortable for patients. We address this by introducing the ResECA-U-Net deep learning model, a novel combination of the UNet and ResNet34 architectures. Furthermore, we further augment its functionality by incorporating the Efficient Channel Attention (ECA-Net) methodology. By utilizing data from the UW-Madison Carbone Cancer Centre, we carefully investigate several image processing techniques designed to capture critical local characteristics. With its foundation in computer vision concepts, the ResECA-U-Net model is excellent at extracting fine details from GI images. Sophisticated metrics such as intersection over union (IoU) and the dice coefficient are used to evaluate performance. Our study's outcomes demonstrate the effectiveness of the suggested method, yielding an impressive 96.27% Dice coefficient and 91.48% IoU. These results highlight the significant contribution that our strategy has made to the advancement of cancer therapy. Beyond its scientific merits, this work has the potential to significantly enhance cancer patients' quality of life and provide better long-term outcomes. Our work is a significant step towards automating and optimizing the segmentation process, which can potentially change how GI cancer is treated completely.

The purpose of this work was analysing the compaction of a cohesive material using different DEM simulators to determine the equivalent contact models and identify how some parameters of the simulations affect the compaction results (maximum force and compacts appearance) and computational costs. For that purpose, three cohesion contact models were tested (‘linear cohesion’ in EDEM; ‘SJKR’ and ‘SJKR2’ in LIGGGHTS). The influence of the particle size distribution (PSD) on the results was also investigated. Further assessments were performed on the effect of selecting different timesteps, using distinct conversion tolerances for exporting the 3D models to STL files and moving the punch with different speeds. Consequently, it was possible to determine that a timestep equal to a 10% Rayleigh timestep, a conversion tolerance of 0.01 mm and a punch speed of 0.2 m/s are adequate for simulating the compaction process using the contact models in this work. In addition, the results determined that the maximum force was influenced by the PSD because of the rearrangement of the particles. The PSD was also related to the computational cost because of the number of simulated particles and their sizes. Finally, an equivalence was found between the linear cohesion and SJKR2 contact models

Medium polarity plays a crucial role in charge-transfer processes and electrochemistry. The added supporting electrolyte in electrochemical setups, essential for attaining the needed electrical conductivity, sets challenges for estimating medium polarity. Herein, we resort to Lippert–Mataga–Ooshika (LMO) formalism for estimating the Onsager polarity of electrolyte organic solutions pertinent to electrochemical analysis. An amine derivative of 1,8-naphthalimide proves to be an appropriate photoprobe for LMO analysis. An increase in electrolyte concentration enhances the polarity of the solutions. This effect becomes especially pronounced for low-polarity solvents. Measured refractive indexes provide a means for converting Onsager to Born polarity, which is essential for analyzing medium effects on electrochemical trends. This study demonstrates a robust optical means, encompassing steady-state spectroscopy and refractometry, for characterizing solution properties important for charge-transfer science and electrochemistry.

In today's context of rising sea levels and subsiding land topography, coastal flooding is a major concern for coastal areas, both nationally, regionally, and internationally. A detailed understanding of these two phenomena is a prerequisite for effective coastal flood management. The main objective of the present study is to contribute to the understanding of the impact of subsidence and sea-level rise on coastal flooding in Saint-Louis, and in particular the Langue de Barbarie, by producing a vulnerability map of submerged surfaces. To this end, the Synthetic Aperture Radar (SAR) interferometry technique is used to process a time series of Sentinel-1 images and estimate land subsidence in the Saint-Louis and Langue de Barbarie area. Interferometric SAR (InSAR) measurements are merged with RCP 2.6 sea-level rise scenarios to identify predicted flooded areas and provide a flood vulnerability map. At the Langue de Barbarie, topographic subsidence is estimated at between -6.4 and -0.4mm/year. In this study, we show that local land subsidence may increase vulnerability to flooding caused by sea-level rise based on 2100 projections. This may represent an increase in the flood zone in the study area. Based on the RCP 2.6 scenario and the subsidence rates obtained, a significant part of the St. Louis coastline and city would be subject to coastal and fluvial flooding for the years 2040 and 2100. For these dates, 29 to and 36 Km2 of the studied area would be occupied by water. Given this situation, research in Saint-Louis needs to focus on adaptation scenarios to coastal risks, to protect coastal communities and safeguard the city's historical heritage.

Zinc is a redox-inert trace element that is second only to iron in abundance in biological systems. In cells, zinc is typically buffered and bound to metalloproteins, but may also exist as a labile or chelatable (free ion) form. Zinc plays a critical role in prokaryotes and eukaryotes ranging from structural to catalytic to replication to demise. This review discusses the influential properties of zinc on various mechanisms of bacterial proliferation and synergistic action as anti-microbial element. We also touch upon the significance of zinc among eukaryotic cells and how it may modulate their survival and death through its inhibitory or modulatory effect on certain receptors, enzymes, and signaling proteins. A brief discussion on zinc chelators is also presented and chelating agents may be used with or against zinc to affect therapeutics against human diseases. Overall, the multidimensional effects of zinc in cells attest to the growing numbers of scientific research that reveal the consequential prominence of this remarkable transition metal in human health and disease.

In the present work, three different atmospheric plasma sprayed (APS) alumina coatings were fabricated using three fused and crushed alumina powders of different particle size fine, medium and coarse. The influence of the particle size on thermal properties and micro-structural features of the produced coating were investigated by thermal insulation test and detailed image analysis technique, respectively. The analyzed micro-structural features include the total porosity, pore size (fine, medium, and large) and cracks. All types of cracks were considered in calculations as voids and were evaluated according to their sizes as pores. All spray parameters except the particle size were fixed throughout the spraying process. The results revealed that the fine starting powder has produced the densest coating with the lowest total porosity and that the total porosity increases with an increasing particle size. This was expected as powders of smaller particle size will reach a higher in-flight temperature and velocity than powders of bigger particle sizes as long as the same spray parameters are applied. However, a detailed image analysis investigation on the three produced coatings showed that the fraction of fine pores and cracks versus the total porosity is substantially higher in coatings produced by using fine starting powders than those produced using medium and coarse powders. In this work, a connection between the thermal insulation and the porosity fraction, which includes fine pores and cracks, was revealed.

This article aims to delve into the Equity, Diversity and Inclusivity (EDI) issues prevalent in the engineering disciplines in Canada and Spain, shedding light on the common obstacles faced by underrepresented individuals and highlighting potential strategies to foster a more inclusive and diverse engineering community in these nations. Two strategic lines have been identified: (a) facilitating university education access to underrepresented and minority groups, and (b) Accompanying and guiding such students during university training, setting them up for successful future careers. The article also shows the sets of strategies employed in Canada and Spain, clearly distinguishing the approach taken in the two countries. While in Canada, there is a more decentralized approach wherein the universities device their strategies and agenda to address EDI issues, in Spain there is a stronger and direct involvement of the government to ensure a comprehensive, system-wide approach to tackling EDI issues in academia.

Human milk (HM) feedings are associated with reduced risks of neurodevelopmental and neurocognitive delays and systemic inflammatory diseases in infants born prematurely and/or at a low birth weight. Utilizing a neonatal piglet model, HM feedings were compared to bovine milk-derived infant formula (IF)-feedings with the aim of understanding the underlying mechanisms involved in reducing these risks. Six male piglets at postnatal-day (PD)2 were randomized into two feeding groups: HM-fed (n = 3) or IF-fed (n = 3) for 28 days. At 3- and 4-weeks-old, piglet memory and learning performance were assessed using novel object recognition (NOR). At PD30 piglets were euthanized, and whole brains were excised, weighed, and preserved for further analyses, and brain microglial morphology, and systemic inflammatory cytokines were quantified. During NOR, HM-fed piglets had significantly more non-novel revisits at both 3- and 4-weeks-old compared to IF-fed piglets. Microglia of HM-fed piglets had longer processes, more branch points, more endpoints, and a larger territorial volume compared to IF-fed piglets at PD30. In a neonatal piglet model, HM-feedings may improve cognition and reduce brain inflammatory response compared to IF-feedings.

Brain-stimulation reward, also known as intracranial self-stimulation (ICSS), is a commonly used procedure for studying brain reward function and drug reward. In electrical ICSS, an electrode is surgically implanted into the medial forebrain bundle in the lateral hypothalamus or the ventral tegmental area in the midbrain. Operant lever responding leads to the delivery of electrical pulse stimulation. The alteration in the stimulation frequency-lever response curve is used to evaluate the impact of pharmacological agents on brain reward function. If a test drug induces a leftward or upward shift in the ICSS response curve, it implies a reward-enhancing or abuse-like effect. Conversely, if a drug causes a rightward or downward shift in the functional response curve, it suggests a reward-attenuating or aversive effect. A significant drawback of electrical ICSS is the lack of cellular selectivity in understanding the neural substrates underlying drug reward versus aversion. Excitingly, recent advancements in optical ICSS (oICSS) have facilitated the development of at least three cell type-specific oICSS models – dopamine-, glutamate-, and GABA-dependent oICSS. In these new models, a comparable frequency-rate response curve has been established and employed to study the substrate-specific mechanisms underlying brain reward function and a drug's rewarding versus aversive effects. In this review article, we summarize recent progress in this exciting research area. The findings in these new behavioral models have not only increased our understanding of the neural mechanisms underlying drug reward and addiction but have also introduced a novel experimental approach in preclinical medication development for treating substance use disorders.

This paper presents the results of aerodynamical performance research focused on maintaining the thermal comfort and increasing the energy efficiency of a typical social housing unit located in a high-density urban area. Bioclimatic design strategies are used to develop a sustainable and economic technology in existing housing clusters in Mexico City. A full-scale prototype, built on campus facilities, was used to study the flow conditions around the design. All scaled prototypes implement similar criterion. Furthermore, a scaled prototype is evaluated within a low speed wind tunnel installation. Additionally, numerical simulations were performed at transient state based on previous physical measurements and historical local climatic conditions to determine preferable modifications.

The quickest path problem in the multistate flow networks, also known as the quickest path reliability problem (QPRP), aims at calculating the probability of transmitting a minimum of d units of flow/dat/commodity from a source node to a destination node through one single path within T units of time. Several exact and approximation algorithms have been proposed in the literature to address this problem. Most of the exact algorithms in the literature need prior knowledge of all the network’s minimal paths (MPs), which is considered a weak point. In addition to the time, the budget is always limited in real-world systems, making it an essential consideration in the analysis of systems’ performance. Hence, this study considers the QPRP under the cost constraints and provides an efficient approach based on the node-child matrix to address the problem without knowing the MPs. We show the correctness of the algorithm, compute its complexity results, illustrate it through a benchmark example, and conduct extensive experimental results on the known benchmarks and one thousand randomly generated test problems to demonstrate its practical superiority compared to the existing algorithms in the literature.

The financial inclusion, including all the people with the finance, is very concerned issue all over the world where Bangladesh is also trying to include all the people with the finance. Bangladesh lies in such a group of countries where only 17.6% - 38.6% adults are presently under the reach of the formal financial services. This is because the present banks and other formal financial modes consider the outcome and profitability in a way that, the rural and non-developed areas are always out of the consideration. But these areas consist of the most population of Bangladesh. And only then financial inclusiveness will be successful in Bangladesh when people from these regions will be under formal financial consideration. The paper seeks for a solution to the issue and presents the Unit Banking System as a probable way towards financial inclusion. For implementing the system in Bangladesh, the system needs a slight modification to cope in Bangladeshi economic condition and address the specific needs without hampering the surroundings. Considering all these, the paper shows the status, problems and key points of financial scenario of inclusion in Bangladesh and shows policy for a Modified Unit banking System.

We review past and present results on the non-local form-factors of the effective action of semiclassical gravity in two and four dimensions computed by means of a covariant expansion of the heat kernel up to the second order in the curvatures. We discuss the importance of these form-factors in the construction of mass-dependent beta functions for the Newton's constant and the other gravitational couplings.

Buildings consume 30% of the total energy consumption around the globe and 29% of the energy consumption in Egypt which in 2022 had a total population of 102 million, out of which 43 % live in urban areas . The operation of buildings contributes to around 30% of global CO2 emissions due to their high energy consumption (IEA, 2022a). Among the efforts made towards improving the energy efficiency of buildings are Advanced Energy Design Guides (AEDGs), building rating systems, codes, and standards. Furthermore, numerous research studies that are either literature review studies, experimental studies, or computational studies addressed the topic of energy efficiency in buildings. These are all examined in this literature review with the purpose of identifying the research gap in available research with a focus on Egypt. The identified gap is the development of a prescriptive path for the GPRS energy efficiency category based on whole building energy simulations.

Biochar (BC) is a carbonaceous material obtained by pyrolysis at 200−1000 °C in the limited presence of O2 of different vegetable and animal biomass feedstocks. BC has demonstrated great potential, mainly in environmental applications, due to its high sorption ability and persistent free radicals (PFRs) content. These characteristics enable BCs to carry out the direct and PFRs-mediated removal/degradation of environmental organic and inorganic contaminants. The types of PFRs possibly present in BC depend mainly on the pyrolysis temperature and the kind of pristine biomass. Since they also can cause ecological and human damage, a systematic evaluation of the environmental behavior, risks, or management techniques of BC-derived PFRs is urgent. PFRs generally could consist of a mixture of carbon- and oxygen-centered radicals, and of oxygenated carbon-centered radicals, depending on the pyrolytic conditions. Here, to promote a more productive and beneficial use of BC and related PFRs and stimulate further studies to make them environmentally safer and less hazardous to humans, we have first reviewed the most common methods used to produce BC, its main environmental applications, the primary mechanisms by which BC remove xenobiotics, as well as the reported mechanisms for PFRs formation in BCs. Secondly, we have discussed the PFRs environmental migration and transformation; we have reported the main PFRs-mediated applications of BCs to degrade inorganic and organic pollutants, the correlated environmental potential risks, and the possible strategies to limit them.

The cultivation of Hevea brasiliensis, the primary commercial source of natural rubber, is strongly impacted by South American Leaf Blight (SALB) disease, caused by the fungus Pseudocercospora ulei. Various management strategies have been implemented, including the selection of resistant genotypes and the identification of escape zones. This study evaluated the growth, early yield, and resistance to SALB of nine Colombian elite genotypes from the ECC-100 series and IAN 873 clone (control) in a large-scale clone trial in a low SALB pressure zone in the Colombian Amazon, 2017 - 2020. Favorable early performance was evident, although there was a significant increase in the severity and sporulation of P. ulei over time, especially in the ECC 35, ECC 60, and IAN 873 genotypes. However, these scores represented a low susceptibility. Genotypes with higher resistance to SALB demonstrated greater growth and early yield compared to higher susceptible genotypes. The ECC 64, ECC 73, ECC 90, ECC 25, and ECC 29 genotypes were more desirable in low SALB pressure zones due to their higher resistance and early performance. It is important to highlight that this research contributes to the selection of new SALB-resistant Colombian genotypes of H. brasiliensis in the growth stage. Therefore, it is necessary to evaluate their productivity in the mature stage and long-term resistance to SALB, before recommending and promoting their commercial adoption in the Colombian Amazon.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

The organic fraction of municipal solid waste (OFMSW) is a significant environmental threat, and an economic and social challenge to manage. As such, the efficient treatment of OFMSW is a significant key factor in achieving sustainable waste management. Decentralized Composting (DC) develops a new framework of waste management. The DC Analysis Model (DCAM), proposed in our previous study, provides a powerful tool for decision makers, based on the quantification of the DC project characteristics. In this paper, we focus on the qualitative analysis as a complementary tool to support decision making, in cases where quantitative analysis is unequivocal. The qualitative analysis identifies the main players in the field, the critical stakeholders and the potential conflicts between them. It also reveals the root problems and the core competencies for the project's implementation. DCAM qualitative analysis in Shefa-Amr (case study) indicates that unresolved root problems, such as the “lack of national regulation”, “clear ownership of the project” and “lack of ongoing budget” can result in an unsustainable composting system. Countering that, “the commitment of the municipality”, together with “economic viability” and securing “suitable areas for placing composters” are among the most important core competencies for the effective implementation of DC projects.

Maize (Zea mays) is one of the most important staple food and primary source of livestock feed in the world. As the consumption of maize grown on the selenium-enriched soils of Naore Valley is one of the apparent causes of selenosis in the area, this work collected and analyzed total Se, Se fractions, and Se species distributions in maize plant samples, including grains, leaves, stalks, roots, rhizosphere soils, and the most representative parent rock materials from Naore Valley, Ziyang County, China. The Se distribution in soils markedly correlated with the weathered Se-enriched bedrocks, but most of the Se in the analyzed soils is enclosed as recalcitrant residual Se and organic-sulfide bound Se. In contrast, Se in rocks had a comparatively higher bioavailability and is bounded mainly to organic matter and sulfides minerals, with very few of the Se enclosed in the residual fraction. Maize plants might take a large amount of Se from the organic-sulfide bound Se fraction in the Se-rich soils, the weathered products from bedrocks or plant litters. Total Se concentrations in the collected samples were observed in descending order soil>leaf>root>grain>stalk. The predominant Se species detected in maize plants was SeMet. Se inorganic forms, mainly Se(VI), decreased from root to grain and were possibly assimilated into organic forms. Se (IV) was barely present. The natural increases in Se concentration affected mainly leaf and root dry-weight biomass as they are the organs that coped with the highest Se accumulation. This paper offers an insight into the uptake, accumulation, and distribution of Se forms in natural Se-rich maize crops and an opportunity for shifting Se-rich soils from menaces to valuable resources for growing Se-rich agricultural products.

This 16-month study aimed to evaluate the extended effects of administering direct-fed microbials (DFM) on milk yield and components in 150 dairy cows. The cows were randomly divided into two groups: control (n=75) and DFM (n=75) based on parity and days in milk. Throughout the study, the two groups of cows were housed separately in a free stall yard, and each group had their own feeding area. The DFM group received 10 ml/cow of the Lacticaseibacillus- and Lentilactobacillus-based DFM via top dressing of the feed during lactation and drying off. Milk yield and liveweight were recorded daily. Milk samples were collected every two months for milk components analysis. Both groups produced less milk in the second production season due to adverse weather conditions. DFM cows gained more liveweight across the study (19.40 kg, 95% CI 0.44; 38.30) compared to controls. In the second season, DFM cows lost weight at a slower rate (-6.06, 95% CI -10.49; -1.61) during the postpartum period and produced more milk (0.39 L/d 95% CI 0.10; 0.89). Over a full lactation, DFM cows yielded at least 258L (95% CI 252L; 265L) more milk than controls. No significant differences were found in fat yield, protein yield, or somatic cell counts. The study suggests that prolonged DFM administration positively impacted milk production, but further research is needed to understand the underlying mechanism.

The Ni-laterite deposit at the San Felipe plateau, located 30 km northwest of Camagüey, in cen-tral Cuba, is the best example of a clay-type deposit in the Caribbean region. San Felipe resulted from weathering of mantle peridotites of the Cretaceous Camagüey ophiolites. In this study, a geochemical and mineralogical characterization of two profiles (83 and 84) from the San Felipe deposit has been performed by XRF, ICP-MS, quantitative XRPD, oriented aggregate mount XRD, SEM, FE-SEM and EMPA. Core 83 with a length of 23 m, and drilled in the central part of the plateau, presents a notable concentration of cryptocrystalline quartz fragments and a rather poor content in NiO, averaging 0.87% wt. Core 84, which is 12 m long, and drilled at the border of the plateau, lacks silica fragments and presents a higher NiO content, averaging 1.79 %wt. The smectite structural formulae reveal that they evolve from trioctahedral to dioctahedral towards the top of the laterite profiles. Quantitative XRD analyses indicate that smectite is a dominant Ni bearing phase, accompanied by serpentine and minor chlorite. Serpentine, as smectite, is en-riched in the less soluble elements Fe3+, Al and Ni towards the top of the profiles. Core 83 seems to have been affected by collapses, replenishments, whereas core 84 may have remained undis-turbed.

This article introduces a new fractional approach to the concept of information dimension of complex networks, based on a (q,q′)-entropy proposed in the literature. The q parameter measures how far is the number of subsystems (for a given size ε) from the mean number of overall sizes. The q′ (interaction index) measures when the interactions between subsystems are greater (q′&gt;1), lesser (q′&lt;1) or equal to the interactions into these subsystems. The computations of the proposed information dimension are carried out on several real-world and synthetic complex networks. The results from the proposed information dimension are compared with those from the information dimension based on the Shannon entropy.

A four stage semi-pilot scale RFR reactor with ceramic disks as support for TiO₂ modified with silver particles was developed for the removal of organic pollutants. The design presented in this article is an adaptation of the rotating biological reactors (RBR) and its coupling with the modified catalyst provides additional advantages to designs where a catalyst in suspension is used. The optimal parameter of rotation was 54 rpm and the submerged surface of the disks offer a total contact area of 387 M². The modified solid showed a decrease in the value of its bandgap compared to commercial titanium. The system has a semi-automatic operation with a maximum reaction time of 50 h. Photo-activity tests show high conversion rates at low concentrations. The results conform to the Langmuir heterogeneous catalysis model.

There are currently around 78 Nuclear Power Plants (NPP) in the world based on Boiling Water Reactors (BWR). The current parameter to assess BWR instability issues is the linear Decay Ratio (DR). However, it is well known that BWRs are complex non-linear dynamical systems that may even exhibit chaotic dynamics that normally preclude the use of the DR when the BWR is working at a specific operating point during instability. In this work a novel methodology based on an adaptive Shannon Entropy estimator and on Noise Assisted Empirical Mode Decomposition variants is presented. This methodology was developed for real-time implementation of a stability monitor. This methodology was applied to a set of signals stemming from several NPPs reactors (Ringhals-Sweden, Forsmark-Sweden and Laguna Verde-Mexico) under commercial operating conditions, that experienced instabilities events, each one of a different nature

The escalating environmental challenges that stem from urban residential waste in densely populated areas have become increasingly prominent in recent times. As a result, the waste management sector has experienced significant growth nationwide. However, due to the predominantly manual nature of these processes, their effectiveness falls short of meeting the current demand. Addressing these issues requires process enhancement. In this context, Industry 4.0, particularly the concept of Digital Twins, emerges as a potential avenue for refining processes. To tackle both current and future industry challenges, it is imperative to create a comprehensive methodology capable of generating effective solutions within the waste management sector. This paper provides an explanation of digital twins, outlines the methodological framework comprising an architectural structure and layered model, and details a series of sequential methodical stages for implementing digital twins based on the specific scope determined by the end-user. A noteworthy aspect is the transformative potential of digital twins in enhancing efficiency and precision within waste management practices. By providing a virtual real-time representation of the waste management system, digital twins empower simulations and experimentation to fine-tune processes. Furthermore, they facilitate informed decision-making by offering a detailed visualization of the complete system, simplifying the identification of challenges and opportunities for improvement. that this article derives from the presentation titled "Digital Twin application methodology for the improvement of production and service systems. Application to waste management processes" at the "Sustainable Smart Cities and Territories International Conference" held in the city of Manizales, Colombia, from 21st to 23rd June 2023.

Research Highlights: The study determined that selective thinning causes different responses, the initial size of the tree released is an influential factor in the growth of species. The temporality of climate and physiological conditions of each species are influential in the growth. It is evident that the defoliation of certain species is an important factor that limits the growth of the species causing thinning to have a negative response. Background and Objectives: The objective is to analyze the behavior of nine timber species, respective to diametric growth after their liberation. This research aims to answer the following questions: (i) How do the selected tree species react to the liberation? (ii) Can the productivity of the trees (diametric growth) be enhanced by liberation? (iii) Are there other factors that influence the diametric growth of the released trees? Materials and Methods: The study was executed in the “Reserva Biológica San Francisco” were 488 trees were monitored, including nine timber species. Therefore, 197 trees were released (removal of competitors) and 251 trees served as reference. To check whether the initial DBH or other factors, like the selective thinning or climate conditions, determine the diameter growth a linear mixed model GLMM was applied. To adjust the linear mixed model a one-way Anova test was executed. Results: Timber species responded differently to the thinning in comparing to reference trees. Therefore, the species analyzed were separated into three groups (positive, negative, and no response to liberation). Conclusions: Liberation potentiates the growth of certain timber species that do not defoliate and considered semi-tolerant to shade. Precipitation and temperature affect all species, but in the defoliate species, it would not be convenient to release them or at least the evidence of these first three years does not show clear differences with control trees. Increase in trees released are higher in trees of the first two diametric classes in all species, this means that larger trees (i.e., older) release does not affect them in a positive way so release should occur in the youngest trees.

This article analyzes the assessment of the four development levels of the Digital Teaching Competence (DTC) to recognize the needs and formulation of challenges in training and educational innovation required in the pedagogical practices of university professors under the current context of the Covid-19 pandemic. The study used an empirical-analytical methodology with a non-experimental, transactional, descriptive design. The sample design was probabilistic, estimated with 95% confidence and 5% error among 252 teachers from various faculties of the University of La Guajira. The selected instrument corresponded to the rubric's application to evaluate the university professor's digital teaching competence in Latin America. Among the study's significant results, we highlight that the rubric presented a high Cronbach's alpha reliability (α: 0.947). In the general assessment of DTC development, it was estimated that 78.2% of teachers are in the first two levels of DTC development assessment (Beginning and Middle). The evaluation rubric allows identifying challenges and opportunities that teacher training must address to advance the professional development of professors.

Objectives: The aim of our current study was to analyze whether the use of important measures of methodological quality and reporting of randomized clinical trials published in the field of cardiovascular disease research have changed over time. Further aim was to investigate whether there was an improvement over time in the ability of these trials to provide a good estimate of the true intervention effect. Methods We conducted two searches in the Cochrane Central Register of Controlled Trials (CENTAL) database to identify cardiovascular clinical research trials published in either 2012 or 2017. Randomized clinical trials (RCTs) trials in cardiovascular disease research with adult participants were eligible to be included. We randomly selected 250 RCTs for both publication year 2012 and 2017. Trial characteristics, data on measures of methodological quality and reporting were extracted and risk of bias for each trial was assessed. Results As compared to 2012 in 2017 there were significant improvements in the reporting of the presence of a data monitoring committee (42.0% in 2017 compared to 34.4% in 2012), and a positive tendency of registering cardiovascular disease research RCTs in clinical trial registries (83.6% in 2017 compared to 72.0% in 2012). On the other hand, we also observed that significantly fewer RCTs reported sample size calculation (60.4% in 2017 compared to 98.4% in 2012) in 2017 as compared to 2012. RCTs in 2017 were more likely to have low overall risk of bias ( RoB ) than in 2012 (29.2% in 2017compared to 21.2% in 2012). Conclusion: As compared to 2012 in 2017 there were significant improvement in some, but not all the important measures of methodological quality. Although more trials in the field of cardiovascular disease research had a lower overall RoB in 2017, the improvement over time was not consistently perceived in all RoB domains.

In 2023, the technological landscape witnessed an unprecedented surge of transformative innovations, including Web 3.0 and machine learning, poised to revolutionize various aspects of our daily lives. At the forefront of this revolution stands artificial intelligence (AI), which has evolved from a concept once confined to science fiction into an indispensable force reshaping industries on a global scale. Notably, recent years have seen remarkable strides in AI functionalities, particularly in machine learning, computer vision, and natural language processing. These advancements have empowered AI to generate diverse interactions and media autonomously. This study ultimately provides invaluable insights into the dynamic intersection of AI and Advertising, con-tributing to a deeper comprehension of this evolving field. This study conducts a comprehensive review of Artificial Intelligence within the advertising domain, employing network analysis. By meticulously examining the evolution of AI through co-occurrences of terms, keywords, and co-authorship analysis, we aim to unveil the relationship of AI & Advertising through the lens of Generative models to identify pivotal trends, core concepts, and seminal studies that have profoundly influenced the industry. The analysis charts the trajectory leading to the emergence of Generative Artificial Intelligence (GenAI), a transformative development poised to revolutionize advertising practices and consumer engagement. In tandem with these objectives, the results highlight vital trends, emphasizing the growing prominence machine learning tools and techniques such as deep learning techniques and advanced natural language processing methods like word2vec, GANs, and more in shaping the future of advertising practices.

After the arrival of a new airborne virus to the world, science is aiming to develop solutions to withstand the spread and contagion of the SARS-CoV-2 coronavirus. The most severe among the adopted measures is to remain in home isolation for a significant number of hours per day, in order to avoid the spreading of the infection in an uncontrolled way through public spaces. Recent literature showed that the major route of transmission is via aerosols produced especially in poorly ventilated inner spaces. With regard to contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain has reached very high levels, therefore this article develops a quantitative and qualitative analysis of the requirements established in Spain with respect to the European framework in reference to ventilation parameters indoors. For this, a case study has been analyzed, representing a common residence in current Spanish residential developments. Results show that the criteria established in the applicable regulations are not sufficient to ensure health as well as to avoid contagion by aerosols indoors.

Prefrontal cortex (PFC) is one of the brain regions with more prominent changes in human aging. The molecular processes related to the aging cognitive decline and mood changes are not completely understood. In order to improve our knowledge, we integrated transcriptomic data of four studies of human PFC from old people -58-80 years old- compared with young people -20-40 years old- using a meta-analytic approximation combined with molecular signature analysis. We identified 1816 differentially expressed genes -561 up-regulated and 1256 down-regulated. Pathway analysis revealed down-regulation of synaptic genes with conservation of gene expression of other neuronal regions. Additionally, we identified up-regulation of markers of astrogliosis with transcriptomic signature compatible with A1 neurotoxic astrocytes and A2 neuroprotective astrocytes. Response to interferon is related to A1 astrocytes and the A2 phenotype is mediated in aging by activation of SHH pathway and up-regulation of metallothioneins I and genes of the family EZR -ezrin, radixin, and moesin-. The main conclusions of our study are the confirmation that in aged PFC there is a global dysfunction of the synapses and we reported for the first time opposite phenotypes of astrogliosis because of brain aging.

During the pandemic, educational digitization experienced a significant increase. In Mexico, social service is a crucial component of technical and professional training, a phase during which individuals apply the knowledge gained throughout their university education. The aim of this study is to standardize a digital model for the management of social service in the health care sector within health care units. This study employed an analytical, observational, retrospective, and longitudinal approach, involving two groups of trainees: Group A (n=133), utilizing a Non-Digital Model, and Group B (n=50), employing a Digital Model. In Stage I. the model design underwent validation through the Delphi method with a panel of three experts. The model was implemented on a Classroom® digital platform with the integration of the elements 1) a monthly rotation rubric 2) care services rubric 3) clinical cases or nursing process rubric, and 4) innovation project rubric. The validation of the model achieved 100% agreement (K=1). The variables measured for each group included the school of origin, career, unit of assignment, timely enrolment, and timely delivery of rubrics on the platform. The difference between the two groups was measured using Chi-Square. To measure the impact, the difference in the timeliness of the products was considered. From the University of Quintana Roo, the difference was 20.3 vs 34%. According to the Unit of Attachment the most frequent was HGR No. 17 with Group A at 22.5 vs 52%. According to the product the least delivered was Product 4, with 69% vs 81%. Timely enrollment was observed in Group A at 89% vs Group B at 80% p=0.001. Overall timely delivery in Group A was 81% vs Group B at 91% p=0.001 in the first 6 months post-implementation. Demonstrating that the implementation of the digital platform was effective, representing a significant advance in the adaptation of medical education to the circumstances imposed by the pandemic, highlighting the feasibility and effectiveness of digital teaching methods in the training of health professionals.

L-asparaginase from bacterial sources have been used in antineoplastic treatments and the food industry. A novel type II L-a sparaginase encoded by the N-truncated gene ansZP21 of halotolerant Bacillus subtilis CH11 isolated from Chilca salterns in Peru was expressed using a heterologous system in Escherichia coli BL21 (DE3)pLysS. The recombinant protein was purified using one-step nickel affinity chromatography and exhibited activity of 234.38 U mg-1 and a maximum catalytic activity at pH 9.0 and 60 °C. The enzyme shows a homotetrameric form with an estimated molecular weight of 155 kDa by gel filtration chromatography. The enzyme half-life at 60 °C was 3 h 48 min, and L-asparaginase retained 50% of initial activity for 24 h at 37 °C. The activity was considerably enhanced by KCl, CaCl2, MgCl2, mercaptoethanol, and DL-dithiothreitol (p-value &lt; 0.01). Moreover, the Vmax and Km were 145.2 µmol mL-1 min-1 and 4.752 mM, respectively. These findings evidence a promising novel type II L-asparaginase for future industrial applications.

This paper presents a new method for the design of separable denominators 2-D IIR filters with nearly linear phase in the passband. The design method is based on a balanced-realization model reduction technique. The nearly linear-phase 2-D IIR filter is designed using 2-D model reduction from a linear-phase 2-D FIR filter, which serves as the initial filter. The structured controllability and observability Gramians $P^s$ and $Q^s$ serve as the foundation for this technique. These Gramians are block diagonal positive-definite matrices that satisfy 2-D Lyapunov equations. An efficient method is used to compute these Gramians by minimizing the traces of $P^s$ and $Q^s$ under linear matrix inequalities (LMI) constraints. The use of these Gramians ensures that the resulting 2-D IIR filter preserves stability and can be implemented using a separable denominator 2-D filter with fewer coefficients than the original 2-D FIR filter. Numerical examples show that the proposed method compares favorably with existing techniques.

All over the world, externally bonded fiber-reinforced polymer systems used to strengthen concrete elements improve building sustainability. However, reports issued by the American Concrete Institute Committee 440 called for heavy scrutinizing before actual field implementation. The very limited number of proposed equations lacks reliability and accuracy. Thus, further investigation in this area is needed. In addition, machine learning techniques are being implemented successfully in developing strength models for complex problems. This study aims to provide a reliable machine learning model based on an experimental database. The proposed model was developed and validated against the experimental database and the very limited models in the literature. The model showed improved agreement with the experimental results compared to the previous models.

Mastitis-causing bacteria can establish persistent infections in the mammary gland of commercially important dairy animals despite the presence of strong specific humoral and cellular immune mechanisms. The aim of this study was to encapsulate vitamin D3 by complex coacervation with sulfur-saturated bovine lactoferrin-alginate using microbial transglutaminase-catalyzed crosslinking and investigate the oral administration of encapsulated vitamin D3 in blood serum biomarkers of the immune response in late-lactating dairy goats. Dairy goats (n = 18) in late lactation were randomly assigned to three experimental groups (n = 6), after balancing weight. Dairy goats were orally administered with 0.35 mg vitamin D3/day in the unencapsulated form and 0.35 mg vitamin D3/day in the encapsulated powder form. Another group received the basal diet. The experimental period lasted 6 weeks. The blood serum concentrations of 25-hydroxyvitamin D3 [25-(OH)-D3], lactoferrin, immunoglobulin A (IgA), and interferon-gamma (INF-γ) were measured. The delivery of vitamin D3 to dairy goats resulted in a marked increase of 25-(OH)-D3 concentration in serum while the serum level of lactoferrin also increased. Alternatively, the serum levels of IgA and the immunomodulatory cytokine INF-γ were elevated following supplementation with the encapsulated vitamin D3. Overall, the capsules in the powder form used in this study kept vitamin D3 highly bioavailable.

Past exploration for U deposit in the Philippines discovered the mineralization of radioactive allanite in Palawan. The allanite occurs as sand component in the heavily populated beach of Erawan, San Vicente, Palawan. This work assessed the risks associated with the radionuclides in Erawan beach by in situ ground radiometric survey of K, U, and Th in 694 sampling points. Principal component analysis (PCA) and Pearson correlation coefficient were used to determine the similarity between the radionuclides and to identify other probable anthropogenic sources of radionuclides. Our results show that the mean activity concentrations of K (597.8 Bq kg^-1) and Th (93.15 Bq kg^-1) are equivalent to 1.5 and 3.1 times of the world average natural radioactivity levels in soil, respectively, while the mean U (34.7 Bq kg^-1) is similar to the world average. The mean radiological risk assessments like radium equivalent, gamma specific activity index, external hazard index, internal hazard index, absorbed gamma dose rate, annual effective dose equivalent, annual gonadal equivalent dose, and excess lifetime cancer risk are 213.96 Bq kg^-1, 0.78, 0.58, 0.67, 97.24 nGy h^-1, 119.25 µSv y^-1, 684.39 µSv y^-1, and 0.42 (10^-3), respectively. Th consistently correlated most to the risks. We attribute the occurrence of Th to the presence of allanite, K to fertilizer use for farming, and U to both the allanite and farming. The results of our study can provide important baseline data for future detailed studies or monitoring of the long-term effects of elevated radiation levels to the local population of Erawan.

Introduction: In the medical area, teaching is essential since it must offer the appropriate instruments to demonstrate that graduates have acquired the necessary skills. Objective: Evaluate the quality of research in residents of medical specialties after a standardized digital training program with rubrics. Methods: An observational, prospective research study in resident physicians of seven medical specialties first-year of an introductory program to methodology. It is integrated with the result variable through the quality of the final product and the quality variable will be measured with an ad hoc questionnaire validated by the Delphi method with a consistency level of 3-3. The data will be integrated into a base of the SPSS system and determined with the Chi-square test considering a minimum significance of 0.05. Results: 85 first-year medical residents (n=85) enrolled in the Research Seminar. The mean age was 31.34 years (± 3.96). About gender Male 38±31.13 Female 31.51±3.83. The global final grade was 80.61 (± 9.59) and the global sat-isfaction of the course was referred to as good by 62.2%. We observed a positive relationship between the scope of evaluation and the level of satisfaction. Conclusion: The research seminar implementation in a b-learning mode in response to the educational needs in medical residents for the field of health education showed a relationship between higher qualification, higher satisfaction, as well as determining that the comprehensive evaluation through the use of rubrics standardized allowed to delimit the deficiencies and strengths for timely feedback influencing the process of acquiring skills and the quality of the final product.

The study reports the effect of some metal carbides (niobium carbide, vanadium carbide, titanium carbide, and manganese sulfide) on hydrogen embrittlement in the pipeline industry using plane wave’s density functional theory (DFT). Our results predicted that the interaction of hydrogen molecules with these metals carbide occurs in the long range with binding energy varying in the energy window [0.70eV to 0.043eV]. Also, our study shows the desorption of H2 molecules from these metal carbides in the chemisorptions. Since, hydrogen embrittlement, occurs in the atomic state of hydrogen, therefore our finding in the atomic interaction of hydrogen with NbC, VC, TiC, and MnS showed that the strength of the trapping of the hydrogen atom could be classified as: TiC+H>VC+H>NbC+H> MnS+H. In addition, our study reveals that the carbon site is the most favorable hydrogen trapping site than the metal one. Furthermore, our results demonstrate that increasing the layer can also be an efficient way to enhance the trapping capacity.

Deep neural networks with powerful auto-optimization tools have been widely applied in various research fields, e.g., NLP and computer vision. However, existing neural network architectures typically are constructed using different inductive biases, e.g., preconceptions, expecting to decrease parameter search space during training, reduce computational cost or introduce expert knowledge in the neural network design. As an alternative, Multilayer Perceptron (MLP) provides much better freedom for exploration, has a lower inductive bias than convolutional neural networks (CNNs), and offers good flexibility in learning complex patterns. Even though, such neural architectures are commonly built in a flat Euclidean space, which is not necessarily the optimal space for any data, and is especially not good for modeling hierarchical correlations. Hyperbolic neural networks (HNNs) have gained attention for their ability to capture hierarchical structures present in complex data types like graphs. Recently, there has been an increasing interest to extend HNNs to computer vision tasks, motivated by the observations that images possess rich hierarchical relations. However, this is generally applied by employing a Euclidean backbone for learning higher-level semantic representations and only incorporating a hyperbolic classifier for classification, which, we argue, does not make full use of the advantage of hyperbolic space. Considering the recovery of the attention-free Multilayer Perceptron(MLP), in this paper, we extend it to non-Euclidean space and propose a novel architecture, named Hyperbolic Res-MLP (HR-MLP), that leverages fully hyperbolic layers to learn feature embeddings and perform image classification in an end-to-end fashion. With the help of the proposed Lorentz cross-patch and cross-channel layers, we can directly perform operations in the hyperbolic domain with fewer parameters, making it faster to train and providing comparatively better performance than its Euclidean counterpart. Experiments on CIFAR10, CIFAR100, and MiniImageNet demonstrate a comparable and superior performance when compared to Euclidean baselines. Our code is available at (https://github.com/Ahmad-Omar-Ahsan/HR-MLP)

The purpose of this paper is to develop an index system for measuring the compliance of high-rise residential buildings with fire requirements and also to develop an index system for measuring the fire response efficiency, which is linked to the index of compliance with fire requirements. The higher the compliance rate, the greater the chance of a successful response. The two systems de-pend on the automation of the firefighting system management processes using the techniques of the fourth industrial revolution and developed based on the consultation of subject matter experts in the field. The main elements of the indexes were identified, which were based mainly on several variables, including the fire administrative system, the firefighting system, the residents, the loca-tion of the high-rise residential buildings from the fire extinguishing station, and the height of the high-rise residential building. The two systems can contribute to improving emergency prepared-ness in high-rise residential buildings in the Emirate of Sharjah and are also considered as a measurement index for compliance with fire requirements in the Emirate of Sharjah.

On the basis of a limited number of reasonable axioms, we discuss the classification of all the possible universality classes of diffeomorphisms invariant metric theories of quantum gravity. We use the language of the renormalization group and adopt several ideas which originate in the context of statistical mechanics and quantum field theory. Our discussion leads to several ideas that could affect the status of the asymptotic safety conjecture of quantum gravity and give universal arguments towards its proof.

Exploring the biological significance of mutations in SARS-CoV-2 coronavirus, causing the COVID–19 pandemic, has recently become an area of paramount interest for many researchers, who are pouring their tremendous efforts, in cracking the COVID–19 pandemic code. One of many such mutations that have occurred in the viral genome is V483A mutation, which is a part of the receptor-binding motif (RBM), present in the S1 domain of the spike protein. V483A mutant virus is becoming popular in North America with 36 cases so far, due to its frequent occurrences in recent days. In this review, we have assembled all information, currently available on V483A mutation, and have made a critical analysis based on the perspectives of many researchers all around the world. Comparison is made between the wild type and the V483A mutants to analyze certain factors like the type of interaction between the virus and host cell interface, binding affinity, stability, partition energy, hydrophobicity, occurrence rate, and transmissibility. Insilico dynamic analysis shows minimal alteration in the receptor-binding domain (RBD) of V483A mutant protein in free-state and no significant change of mutant tertiary structure of RBM upon binding to the ACE2 receptor. Comprehensive details about infectivity and evasion of the immune system by the virus are discussed. This information can in turn be of monumental importance in the field of vaccine and drug development because the mutants are becoming resistant to the vaccines and monoclonal antibodies.

The use of haptic devices in rehabilitation of impaired limbs has become rather popular, given the proven effectiveness in promoting recovery. In a standard framework, such devices are used in rehabilitation centers, where patients interact with virtual tasks, presented on a screen. To track their sessions, kinematic/dynamic parameters or performance scores are recorded. However, as Internet access is now available at almost every home, and in order to reduce the hospitalization time of the patient, the idea of doing rehabilitation at home is gaining wide consent. Medical care programs can be synchronized with the home rehabilitation device; patient data can be sent to the central server that could redirect to the therapist laptop (tele-healthcare). The controversial issue is that the recorded data do not actually represent the clinical conditions of the patients according to the medical assessment scales, forcing them to frequently undergo clinical tests at the hospital. To respond to this demand, we propose the use of a bilateral master/slave haptic system that could allow the clinician, who interacts with the master, to assess remotely and in real time the clinical conditions of the patient that uses the home rehabilitation device as the slave. In this paper, we describe a proof of concept to highlight the main issues of such an application, limited to one degree of freedom, and to the measure of the stiffness and range of motion of the hand.

We study the performance of a classical and quantum magnetic Otto cycle with a quantum dot as a working substance using the Fock-Darwin model with the inclusion of the Zeeman interaction. Modulating an external/perpendicular magnetic field, we found in the classical approach an oscillating behavior in the total work that is not perceptible under the quantum formulation. Also, we compare the work and efficiency of this system for different regions of the Entropy, $S(T,B)$, diagram where we found that the quantum version of this engine always shows a reduced performance in comparison to his classical counterpart.

Air pollution is a global issue, and the transportation sector is recognized as the third-largest contributor to anthropogenic greenhouse gas emissions. Vehicles emit a range of chemical compounds as a direct result of the combustion process. The nature and quantity of these emissions depend on the vehicle's characteristics, road, and local weather conditions. As a result, these emissions require special attention due to the adverse effects contributing to global warming and significantly impacting human health. In this regard, diagnosing and monitoring air quality is crucial for understanding the nature and quantity of emissions generated by various sources. However, in developing countries, the necessary inputs, and data for conducting such analyses are not always available. Therefore, the purpose of this study is to estimate emissions specifically generated from road operations. To achieve this, HDM-4 calculation tool is utilized to quantitatively estimate these emissions. This tool was applied in Baja California, Mexico, on the Centinela-La Rumorosa highway. The results obtained show that annually, 372.5 tons of pollutant emissions are generated, composed of HC, CO, CO2, NOx, Par, SO2, and PB, covering a mere 128 kilometers of length within a state road network spanning 11,429 kilometers. This highlights the necessity of implementing strategies to reduce emissions or the environmental impact generated by vehicular operations on roads in developing countries.

Objectives: Social distancing measures are currently implemented to control COVID-19 pandemic in many countries, including Saudi Arabia. The aim of this study was therefore to evaluate the awareness and adherence of the Saudi population to these measures. Methods: A web-based questionnaire was designed with 16 questions (8 questions related to demographics, 3 in relation to awareness about social distancing and 5 related to overall practice of social distancing). Results: 5105 participants completed the survey [58.4% female, 66.3% young individuals (aged 18-37 years), 55.8% bachelor degree holders, and 51.0% from the western region]. The Saudi Ministry of Health (MOH) was the main source of information about COVID-19 for most participants (78.2%). High awareness (81.3%) regarding social distancing was observed, associated mainly with female participants, those from the middle region and those with high education and income. Overall implementation of social distancing was satisfactory (score 3.13/5), with 37.8% never leaving home during the home-stay period. Better adherence to social distancing was observed for female participants, higher degree holders and those aged over 38 years. Conclusions: Organised plans by the Saudi MOH have been effective in raising awareness and improving practice of social distancing among public. However, the observed lower practice of social distancing by individuals with lower education and income indicates the need for targeted interventions to achieve better outcome.

Concrete being one of the most frequently used construction materials in the field of construction. The use of concrete has increased with the passage of time as the more and more construction activities are taking place around the globe. Different materials have been added in to the concrete mix to provide the concrete more strength and make it more durable and long lasting. This paper looks into a detailed comparison of concrete strength when casted with in the presence of carbon fibers, steel fibers and glass fibers. The compressive strength for cubes and cylinder with carbon fibers is the highest as compare to steel fibers as well as glass fibers. The compressive strength of concrete is measured on 3 day, 7 day, 14 day and 28 day strength. The compressive strength of cube on 28th day strength is 37.52 MPa for carbon fiber steel, for steel fiber it is 34.22 MPa and with glass fiber the strength is 29.335 MPa whereas the compressive strength of cylinder with carbon fibers the 34.88 MPa, with steel fiber it is 34.22 MPa and with glass fiber the strength is 27.447 MPa. For the cubes the maximum difference between different fibers inducted concrete sample is 28% approximately and for cylinder it is 27%, respectively. On the other hand, the tensile strength of concrete was also gained with the carbon fiber. It was determined that carbon fiber provided about 16% and 12.8% tensile strength higher than glass and steel fibers respectively.

Lynch syndrome (LS) is an inherited cancer predisposition disorder associated with an elevated risk of various epithelial cancers. Despite sharing the same pathogenic variant (PV), Lynch syn-drome variant heterozygotes (LSVH) exhibit considerable phenotypic variability in cancer risk. The role of Human Leukocyte Antigen (HLA) in modifying cancer risk prompted our investiga-tion into whether HLA variations act as genetic modifiers influencing age at cancer diagnosis in a unique cohort of LSVH carrying a PV in the hMLH1 gene in South Africa. Within our extensive LS cohort, 426 individuals carried the same hMLH1 PV (MLH1:c.1528C>T). We selected 100 indi-viduals with the greatest diversity in age at cancer diagnosis and the oldest unaffected individu-als for high-throughput HLA genotyping of 12 HLA class I and II loci using next-generation se-quencing. Statistical analyses employed Kaplan-Meier survival analyses with Logrank tests and Cox proportional hazards. Following the robust application of statistical correction methods, six HLA alleles (3.2%) were significantly associated with a young age at cancer diagnosis. Notably, HLA-B*15:17 and HLA-DPB1*55:01 correlated significantly with very young colorectal cancer (CRC) diagnosis (Mean age: 21y [17-25]; HR = 71.59; q