The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is currently under construction and has been filling at a fast rate without sufficient known analysis on possible impacts on the body of the structure. The filling of GERD not only has an impact on the Blue Nile Basin hydrology, water storages and flow but also pose massive risks in case of collapse. Rosaries Dam located in Sudan at only 116 km downstream of GERD, along with the 20 million Sudanese benefiting from that dam, would be seriously threatened in case of the collapse of GERD. In this study, through the analysis of Sentinal-1 satellite imagery we show concerning deformation patterns associated with different sections of the GERD’s Main Dam (structure RCC Dam type) and the Saddle Dam (Embankment Dam type). We processed 109 descending mode scenes from Sentinel-1 SAR imagery, from December 2016 to July 2021, using the Differential Synthetic Aperture Radar Interferometry technique to demonstrate the deformation trends of both - the GERD’s Main and Saddle Dams. The time-series generated from the analysis clearly indicates different displacement trends at various sections of the GERD as well as the Saddle Dam. Results of the multi temporal data analysis on and around the project area show inconsistent subsidence at the extremities of the GERD Main Dam, especially the west side of the dam where we recorded varying displacements in the range of 10 mm to 90 mm at the crest of the dam. We conducted the current analysis after masking the images with a coherence value of 0.9 and hence, the subsequent results are extremely reliable and accurate. Further decomposition of the subsiding rate has revealed higher vertical displacement over the west side of the GERD’s Main Dam as compared to the east side. The local geological structures consisting of weak zones under the GERD’s accompanying Saddle Dam adds further instability to its structure. We identified seven critical nodes on the Saddle Dam that match the tectonic faults lying underneath it, and which display a varying degree of vertical displacements. In fact, the nodes located next to each other displayed varying displacement trends: one or more nodes displayed subsidence since 2017 while the other node in the same section displayed uplift. The geological weak zones underneath and the weight of the Saddle Dam itself may somewhat explain this inconsistency and the non-uniform vertical displacements. For the most affected cells, we observed a total displacement value of ~90 mm during the whole study period (~20 mm/year) for the Main Dam while the value of the total displacement for the Saddle dam is ~380 mm during the same period (~85 mm/year). Analysis through CoastSat tool also suggested a non-uniformity in trends of surface water-edge at the two extremities of the Main Dam.

Abstract Aim: The study aimed to evaluate the clinical laboratory features of moderate and severe COVID-19 patients among a cohort of the Egyptian population. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) of various detected parameters in predicting the severity of COVID-19 infection. Patients and methods: One hundred diagnosed COVID-19 patients and fifty healthy participants in total were involved in current study. COVID-19 patients were categorized based on how severe their symptoms into two groups. Estimates were made for serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin, lactate dehydrogenase (LDH) and C-reactive protein (CRP) as well as white blood cells (WBCs) count, lymphocytes count, and hemoglobin content (Hb) content. Results: COVID-19 patients displayed increased serum levels of liver enzymes and CRP as well as WBCs count when compared to healthy individuals. On the other hand, Hb content, lymphocytes count, and albumin level fell in all COVID-19 patients. The severe group showed a statistically significant rise in liver enzymes, WBCs, and CRP levels, compared with moderate group. WBCs and lymphocytes counts were closely correlated with age, ALT, LDH, and CRP in all cases. WBCs and lymphocytes counts also had a negative correlation with albumin Level. Additionally, WBCs count, lymphocytes count, LDH activity and CRP level have higher AUC in severe than in moderate cases. WBCs count, LDH activity and CRP level have AUC above 0.80 in the severe group. Conclusion: The current investigation found a significant correlation between WBCs count, lymphocytes count, CRP level and liver injury in COVID-19 patients. WBCs count, lymphocytes count, LDH activity and CRP level were effective indicators for determining the severity of COVID-19.

Purpose: The study aimed to investigate if there were any links between liver function biomarkers and immunoglobulins levels in serum, and Toll-like receptors (TLRs) and neuropilin-1 (NRP1) in COVID-19 patients. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) by the receiver operator curve (ROC) analysis for immunoglobulins levels and TLRs expressions. Patients and Methods: This study included 150 patients (100 patients with confirmed COVID-19 and 50 healthy volunteers as a control group). Patients with COVID-19 were subdivided into two groups according to the severity of symptoms (moderate and severe, with 50 patients each). Serum C-reactive protein (CRP), alanine aminotransaminase (ALT), aspartate aminotransaminase (AST), albumin, lactate dehydrogenase (LDH), immunoglobulin (Ig) G, and IgM levels were estimated. TLRs (TLR2 and TLR4) and NRP1 gene expression in blood samples were investigated using quantitative real-time polymerase chain reaction (qRT-PCR). ROC analysis was also applied to determine the accuracy of various detected parameters in predicting the possibility of COVID-19 infection. Results: In COVID-19 patients, serum parameters related to liver function, except serum albumin, CRP, IgG, IgM, and TLR2, TLR4, and NRP1 mRNA expression levels, significantly elevated compared to controls. Severe COVID-19 patients exhibited significantly higher liver enzymes (ALT, AST and LDH), CRP, and TLR2 mRNA expression levels and lower albumin levels than the moderate group. In the moderate and severe groups, ALT, CRP, TLR2, and TLR4 had a significant positive correlation with IgM levels. ALT, AST, LDH, CRP, TLR2, and TLR4 showed a significant positive correlation with IgG levels in both groups. In both the moderate and severe groups, NRP1 expression was found to be significantly correlated with CRP, IgG, IgM, TLR2, and TLR4. In contrast, serum albumin levels exhibited a significant negative correlation with IgG and IgM levels only in the severe group, but they showed a significant negative correlation with TLR2, TLR4, and NRP1 expression in both moderate and severe groups. Serum ALT and AST activities were positively correlated with NRP1 expression in the moderate group but not in the severe group and as well as TLR2 and TLR4 expression in both the moderate and severe groups. ROC analysis indicated that AUC was higher than 0.800 for serum IgM level and TLR4 gene expression in moderate COVID-19 group. Conclusions: The increased liver function biomarkers in serum and NRP1 expression are closely correlated with sustained activations in humoral and innate immune responses during COVID-19 infection. As a result, TLR2, TLR4, and NRP1 could be targets for limiting COVID-19 infection and impairment effects on liver function. Moreover, detection of IgM level in serum and TLR4 expression in blood have a good accuracy in predicting the possibility of infection with COVID-19 in moderate cases.

The present study was aimed to evaluate the suitability of agro-wastes and crude vegetable oils for the cost effective production of poly-β-hydroxybutyrate (PHB), to evaluate growth kinetics and PHB production in Alcaligenes faecalis RZS4 and Pseudomonas sp. RZS1 with these carbon substrates and to study the biodegradation of PHB accumulated by these cultures. Alcaligenes faecalis RZS4 and Pseudomonas sp. RZS1 accumulate higher amounts of PHB corn (79.90% of dry cell mass) and rice straw (66.22% of dry cell mass) medium respectively. The kinetic model suggests that the Pseudomonas sp. RZS1 follows the Monod model more closely than A. faecalis RZS4. Both the cultures degrade their own PHB extract under the influence of PHB depolymerase. Corn waste and rice straw appear as the best and cost-effective substrates for the sustainable production of PHB from Alcaligenes faecalis RZS4 and Pseudomonas sp. RZS1. The biopolymer accumulated by these organisms is biodegradable in nature. The agro-wastes and crude vegetable oils are good and low cost sources of nutrients for the growth and production of PHN and other metabolites. Their use would lower the production cost of PHN and the low cost production will reduce the sailing price of PHB based products. This would promote the large scale commercialization and popularization of PHB as ecofriendly bioplastic/biopolymer.

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

Quite a number of cottonseed varieties are existed. The seeds of each variety produce a different amount of gossypol as a natural toxic compound. The increased interest in this natural product and its toxic effects were enhanced the demand for establishing simple silica-gel-based methods for its isolation, purification, and characterization. Historically, silica gel plays a significant role in isolation and purification of many different natural products. Silica gel is variants and can intro-duce a lab, simple tool for tracking a compound in certain plants during its purification process. In this study, gossypol was isolated and purified in the form of yellow crystals as gossypol acetic ac-id. Several methods and tools were used for its characterization including TLC, preparative TLC, silica gel column, UV/IR spectrophotometer and HPLC (Robust spherical silica gel). A compara-tive study between its amounts in both Egyptian and Chinese varieties were performed. Under the experimental condition, the Egyptian cottonseeds contain 8.705 gm/kg, while the Chinese contains 5.395 gm/kg. Thin Layer Chromatography (TLC) had been flourished the science of the phytochemistry and still popular till nowadays and is recommended for fast, accurate, and inex-pensive evaluation and quantification of gossypol. It is recommended to isolate and purify gossy-pol as gossypol acetic acid using optimized combined methods used in this study. Using Silica gel different protocols will assist and facilitate the parallel comparison and save the compact column from any unexpected contaminants during the purification steps. During each step the silica gel itself could be simply removed by paper filtration.

This paper develops a two-layer optimization approach that provides energy-optimal control for vehicles and traffic signal controllers. The optimizer in the first layer computes the traffic signal timings to minimize the total energy consumption levels of approaching vehicles from upstream traffic. The traffic signal optimization can be easily implemented in real-time signal controllers, and it overcomes the issues in the traditional Webster’s method of overestimating the cycle length when the traffic volume-to-capacity ratio exceeds 50 percent. The second layer optimizer is the vehicle speed controller, which calculates the optimal vehicle brake and throttle levels to minimize the energy consumption of individual vehicles. The A-star dynamic programming is used to solve the formulated optimization problem in the second layer to expedite the computation speed so that the optimal vehicle trajectories can be computed in real-time and can be easily implemented in simulation software for testing. The proposed integrated controller is first tested on an isolated signalized intersection, and then an arterial network with multiple intersections to investigate the performance of the proposed controller under various traffic demand levels. The test results demonstrate that the proposed integrated controller can greatly improve energy efficiency with fuel savings up to 17.7%, at the same time enhancing traffic mobility by up to 47.18% reduction in traffic delay and up to 24.84% reduction in vehicle stops.

Beta thalassemia is an inherited blood disorder that results in inefficient erythropoiesis due to genetic mutation that leads to reduction or absence of the hemoglobin beta-globulin protein. Approximately 8.5% of UAE residents suffer from β-thalassemia, a significant health and financial problem. The treatment options available for β-Thalassemia major are limited and associated with a wide range of complications. β-thalassemia gene therapy is emerging as a potential novel treatment option that eliminates the complications caused by the current long-term treatment modalities and the associated economic burden. This paper reviews the scientific literature related to emerging gene-therapy for β-Thalassemia by analyzing all the articles published from January 2010 to December 2023 in the English language on Databases like PubMed, Scopus, ProQuest, and CINAHL. The use of gene therapy has demonstrated promising outcomes for a permanent cure of β-Thalassemia. ZYNTEGLO (Betibeglogene autotemcel) is the only cell-based gene therapy which was approved by the FDA on 19th August, 2018. To conclude, Gene therapy is an innovative solution. It demonstrates a promising future, but does come with its own set-backs and is something that must be tackled in-order to revolutionize it in the medical world. FDA approved ZYNTEGLO is a potentially one-time curative treatment for β-Thalassemia. Although cutting-edge, its use is limited because of the high cost; a price of $2.8million per patient.

Unique analytical challenges arise when drivers, who face a route choice between a toll lane and a set of free lanes, have different values of time. The most complex situation is one in which multiple sub-populations of drivers exist, each with their own unique mean and coefficient of variation of value of time. This situation, when imbedded within a larger network cannot be tackled using existing planning models, and consequently is usually only approximated. This paper examines these different approximations, the resulting numerical solutions and the implications of these approximations on the estimate of the number of expected toll lane users. The paper also shows how this problem can be solved using a combined traffic assignment/simulation model. The first part of this paper develops an analytical formulation for solving the toll lane scenario using the “value of time” representations range from the simplest to the most complex. It is shown that one of the most critical issues is a determination of who the marginal users are of the toll lane, at each level of usage, as the perceived disutility of the last marginal toll lane user depends dynamically upon that driver’s value of time. Analytical formulations based on these different approximations are then solved numerically in the second part of the paper. These numerical solutions show that significant different lane use estimates result, depending upon the representation of value of time. Consequently, it is clear that solving this problem with the fewest approximations is both of theoretical and practical importance. The third part of the paper illustrates the solution to the toll lane problem, with each level of approximation, using a combined traffic assignment/simulation model. The simulated resulting estimates of the toll lane usage for each case matches both the relative and absolute trends found in analytical solutions. However, the solution using the assignment/simulation model is not only much faster and simpler to obtain, but is also scalable both in size and complexity. The additional complexities, that are associated with a less approximate representation of value of time, should therefore be incorporated in all future assessments of toll lane facilities, be they analyzed analytically or through simulation.

In this study, we use descriptive statistics and data visualization techniques to analyze datasets and identify patterns and relationships between bikeshare and other transportation modes. We also use regression analysis to quantify the impact of various factors on bikeshare usage. Our results indicate that bikeshare trips during the pandemic were much longer compared to pre-pandemic times. Moreover, usage of bikeshare differed by user group, with casual users showing a greater increase in usage compared to subscribers. We plotted bivariate choropleth maps to visualize the spatial distribution of changes in bikeshare usage. Our findings suggest that an increase in bikeshare travel was associated with a reduction in travel by ride-hailing and public transit, especially in the northern part of the city, indicating a potential replacement of other modes of transportation. On the western and southern boundary of the city, bikeshare had a complementary effect with other modes. Overall, the data acquired for this study provides a valuable opportunity to understand the behavior of bikeshare users in Chicago, the intercorrelation of bikeshare with other transportation modes, and the impact of infrastructure on bikeshare usage. The findings of this study can inform the design and implementation of bikeshare systems in other cities and contribute to the development of a more sustainable transportation system.

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.

This paper develops a Green Light Optimal Speed Advisory (GLOSA) system for buses (B-GLOSA). The proposed B-GLOSA system is implemented on diesel buses, and field tested to validate and quantify the potential real-world benefits. The developed system includes a simple and easy to calibrate fuel consumption model that computes instantaneous diesel bus fuel consumption rates. The bus fuel consumption model, a vehicle dynamics model, the traffic signal timings, and the re-lationship between vehicle speed and distance to the intersection are used to construct an optimi-zation problem. A moving-horizon dynamic programming problem solved using the A-star algo-rithm is used to compute the energy-optimized vehicle trajectory through signalized intersections. The Virginia Smart Road test facility was used to conduct the field test on 30 participants. Each participant drove three scenarios including a base case uninformed drive, an informed drive with signal timing information communicated to the driver, and an informed drive with the recom-mended speed computed by the B-GLOSA system. The field test investigated the performance of using the developed B-GLOSA system considering different impact factors, including road grades and red indication offsets, using a split-split-plot experimental design. The test results demonstrated that the proposed B-GLOSA system can produce smoother bus trajectories through signalized in-tersections producing fuel consumption and travel time savings. Specifically, compared to the uninformed drive, the B-GLOSA system produces fuel and travel time savings of 22.1% and 6.1% on average, respectively.

Cellular Vehicle-to-Everything (C-V2X) is a communication technology that supports various safety, mobility, and environmental applications given its higher reliability properties compared to other communication technologies. The performance of these C-V2X-enabled Intelligent Transportation System (ITS) applications is affected by the performance of the C-V2X communication technology (mainly packet loss). Similarly, the performance of the C-V2X communication is dependent on the vehicular traffic density which is affected by the traffic mobility patterns, and vehicle routing strategies. Consequently, it is critical to develop a tool that can simulate, analyze, and evaluate the mutual interactions of the transportation and communication systems at the application level and to the evaluate the benefits of the C-V2X enabled ITS applications. In this paper, we demonstrate the benefits gained when using C-V2X Vehicle-to-Infrastructure (V2I) communication technology in an energy-efficient dynamic routing application. Specifically, we develop a Connected Energy-Efficient Dynamic Routing (C-EEDR) application using C-V2X as a communication medium in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles. The results demonstrate that the fuel savings increase with increasing levels of market penetration at lower traffic demand levels (25% and 50% the peak demand). At higher traffic demand levels (75% and 100%) the fuel savings increase with increasing levels of market penetration with maximum benefits at a 50% market penetration rate. Although the communication system is affected by the high density of vehicles at the high traffic demand levels (75% and 100% the peak demand), the C-EEDR application manages to perform reliably producing system-wide fuel consumption savings.The C-EEDR application achieves fuel savings of 15.2% and 11.7% for the IDEAL communication and 14% and 9% for the C-V2X communication at the 75% and 100% market penetration rates, respectively. Finally, the paper demonstrates that the C-V2X communication constraints only affect the performance of the C-EEDR application at the full demand level when the market penetration of connected vehicles exceeds 25%. This degradation, however is minimal (less than a 2.5% reduction in fuel savings).

FLASH-RT represents a novel therapeutic radiation modality that holds remarkable potential for mitigating radiation therapy’s adverse side effects. This cutting-edge technology allows for the sparing of healthy tissue while precisely targeting cancerous cells by administering an ultra-high dose-rates of typically between 10 and 30 Gy in less than a few hundred milliseconds. FLASH-RT has demonstrated impressive results in small-animal models, prompting scientists to adapt and advance existing technologies to make it a viable treatment option for humans. However, producing the ultra-high-dose-rate radiation required for the therapy remains a significant challenge. Several radiation sources, such as very high energy electrons (VHEEs), low energy electrons, x-rays, and protons, have been studied for their ability to deliver the necessary dose. Among them, FLASH-x-ray has gained the most attention owing to its capacity to penetrate deeply seated tumours. Despite the complexity of the process, the potential advantages of FLASH-RT make it an exciting area of research. To achieve the FLASH effect, high-frequency, pulsed irradiated accelerator technology can be employed. Sparing healthy tissue, it may allow for more aggressive and effective cancer treatments, leading to a better quality of life for patients. Ongoing research and development will be necessary to refine and optimize this approach to radiation therapy.

In this paper, bikeshare data in Chicago on weather-friendly days in 2019 and 2020 were analyzed to investigate the variation in bikeshare travel before and during the pandemic. Our results show that bikeshare trips during the pandemic were much longer than prior to the pandemic. The increased rate of bikeshare usage was unbalanced spatially and varied significantly for different user types. Specifically, bikeshare was used significantly more by casual users than by subscribers, and the increase occurred much more in the outskirts of the city. The increase in bikeshare travel was associated with a reduction in travel by ride-hailing and public transit, especially in the urban periphery. The correlation of bikeshare use with the bus system was much less significant than with the rail system. Bike lanes/facilities had a mixed effect on bikeshare travel. Weekend bike trips increased in areas where there was no bike lane. Weekday trips, on the contrary, increased in the vicinity of bike greenways.

This study introduces a comparative analysis of two deep learning (multilayer perceptron neural networks (MLP-NN) and the long short term memory networks (LSTMN)) models for transit travel time prediction. The two models were trained and tested using one-year worth of data for a bus route in Blacksburg, Virginia. In this study, the travel time was predicted between each two successive stations to all the model to be extended to include bus dwell times. Additionally, two additional models were developed for each category (MLP of LSTM): one for only segments including controlled intersections (controlled segments) and another for segments with no control devices along them (uncontrolled segments). The results show that the LSTM models outperform the MLP models with a RMSE of 17.69 sec compared to 18.81 sec. When splitting the data into controlled and uncontrolled segments, the RMSE values reduced to 17.33 sec for the controlled segments and 4.28 sec for the uncontrolled segments when applying the LSTM model. Whereas, the RMSE values were 19.39 sec for the controlled segments and 4.67 sec for the uncontrolled segments when applying the MLP model. These results demonstrate that the uncertainty in traffic conditions introduced by traffic control devices has a significant impact on travel time predictions. Nonetheless, the results demonstrate that the LSTMN is a promising tool that can has the ability to account for the temporal correlation within the data. The developed models are also promising tools for reasonable travel time predictions in transit applications.

This review presents a comprehensive and systematic study of the field of bacterial plant biostimulants and considers the fundamental and innovative principles underlying this technology. Plant biostimulants are an important tool for modern agriculture as part of an integrated crop management (ICM) system; helping make agriculture more sustainable and resilient. Plant biostimulants contain substance(s) and/or microorganisms whose function when applied to plants or the rhizosphere, is to stimulate natural processes to enhance plant nutrient uptake, nutrient use efficiency, tolerance to abiotic stress, biocontrol, and crop quality. The use of plant biostimulants has gained substantial and significant heed worldwide as an environment-friendly alternative for sustainable agricultural production. Presently, there is an increasing curiosity of industry and researchers in microbial biostimulants especially, bacterial plant biostimulants (BPBs) to improve crop growth and productivity. The BPBs that are based on PGPR (plant growth-promoting rhizobacteria) play plausible roles to promote/stimulate the crop plant growth through several mechanisms that include, i) nutrient acquisition by nitrogen (N₂) fixation and solubilization of insoluble minerals (P, K, Zn), organic acids and siderophores, ii) antimicrobial metabolites and various lytic enzymes, iii) action of growth regulators and stress-responsive/induced phytohormones, iv) ameliorating abiotic stress like drought, high soil salinity, extreme temperatures, oxidative stress, and heavy metals by using different modes of action, and v) plant defense induction modes. Presenting here is a brief review emphasizing the applicability of BPBs as an innovative exertion to fulfill the current food crisis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) continues to wreak havoc threatening the public health services and imposing economic collapse worldwide. Tailoring public health responses to the SARS-CoV-2 pandemic depends on understanding the mechanism of viral replication, disease pathogenesis, and accurately identifying acute infections and mapping the spreading risk of hotspots across the globe. However, effective identification and isolation of persons with asymptomatic and mild SARS-CoV-2 infections remain the major obstacles to efforts in controlling the SARS-CoV-2 spread and hence the pandemic. Understanding the mechanism of persistent viral shedding, reinfection, and the post-acute sequalae of SARS-CoV-2 infection (PASC) is crucial in our efforts to combat the pandemic and provide better care and rehabilitation to survivors. Here we present a living literature review on SARS-CoV-2 viral persistence, reinfection and PASC. We also highlight potential areas of research to uncover putative links between viral persistence, intra-host evolution, host immune status, and protective immunity to guide and direct future basic science and clinical research priorities.

El Niño is warming of the sea surface temperature of the Pacific Ocean. Extreme flooding, drought, lack of potable water for livestock and domestic use, food insecurity and market imbalance are associated with El Niño and La Niña in Ethiopia. Drought following El Niño caused 50 to 90% crop failure, in the eastern parts of Ethiopia. El Niño episodes are detected using different statistical indices such as Oceanic Nino Index (ONI), Agricultural Stress Index System (ASIS) and the Southern Oscillation Index (SOI), with magnitude ranging from weak to strong. Identifying the El Niño and La Niña seasons it is very important to adopt suitable adaptation strategies, which can resolve and/or reduce the negative impacts. Early warning and immediate support to the impacted areas have been carried out to minimize risks from El Niño animal feed for livestock from other areas has been transported to the vulnerable areas. Planting early maturing and drought resistant crops, supplementary irrigation, early waning information on weather and climate have been exercised as climate change adaptation strategies, early warning mechanisms by the government of Ethiopia. El Niño and La Niña are natural phenomena; however, it is necessary to study the occurrence and distribution of El Niño and La Niña episodes to enable early warning and identify suitable adaptation strategies and policy implications in the country.

Existing literature on the relationship between ride-hailing (RH) and transit services is limited to empirical studies that lack real-time spatial contexts. To fill this gap, we took a novel real-time geospatial analysis approach. With source data on ride-hailing trips in Chicago, Illinois, we computed real-time transit-equivalent trips for all 7,949,902 ride-hailing trips in June 2019; the sheer size of our sample is incomparable to the samples studied in existing literature. An existing Multinomial Nested Logit Model was used to determine the probability of a ride-hailer selecting a transit alternative to serve the specific O-D pair, P(Transit|CTA)[1]. We find that 31% of ride-hailing trips are replaceable, whereas 61% of trips are not replaceable. The remaining 8% lie within a buffer zone. We measured the robustness of this probability using a parametric sensitivity analysis and performed a two-tailed t-test. Our results indicate that of the four sensitivity parameters, the probability was most sensitive to the total travel time of a transit trip. The main contribution of our research is our thorough approach and fine-tuned series of real-time spatiotemporal analyses that investigate the replaceability of ride-hailing trips for public transit. The results and discussion intend to provide perspective derived from real trips and we anticipate that this paper will demonstrate the research benefits associated with the recording and release of ride-hailing data. [1] This value defines the replaceability of the trip, where a value ranging from 0 to 0.45 is considered not-replaceable (NR), and a value ranging from 0.55 to 1.0 is considered replaceable (R).

Klebsiella pneumoniae is one of the most common causes of clinical and asymptomatic mastitis in dairy cattle, also in milk and dairy products affecting its quality. Mastitis caused by K. pneumoniae is even more serious due to its poor response to antibiotic therapy. This study was conducted to detect and identify the presence of K. pneumoniae in milk and dairy products. A total of 234 samples were randomly collected from various locations in Libya. Samples were examined for the presence of K. pneumoniae by conventional cultural techniques that included cultivation in violet red bile agar plus 4-methylumbelliferyl-ß-D-glucuronide (VRBA + MUG) broth, and CHROM agar followed by identification by PCR and partial sequencing of 16S rRNA. Out of the 234 samples of milk and dairy products collected, 16 (6.8%) of the isolates revealed mucoid colonies on agar media phenotypically suggested to be K. pneumoniae. The isolates identification was confirmed by molecular techniques (16S rRNA). Among examined samples, K. pneumoniae was recovered from she camel’s milk, raw cow’s milk, raw fermented milk, Maasora cheese, Ricotta cheese, soft cheese, full cream milk powder, milk powder infant formula, cereal baby food and growing up formula. From the 16 K. pneumoniae isolates; antibiotic susceptibility testing was performed on 12 isolates, the results showed that K. pneumoniae isolates were resistant to more than 8 antibiotics, interestingly, two isolates revealed MBL production. This study emphasized the relationship between K. pneumoniae and raw milk, cheese, milk powder and infant milk retailed in Libya, which is considered as a risk for human health as many of these products did not comply with microbiological criteria of international and/or Libyan standards. The necessary precautions have to be taken to carry out effective sanitary practices during the production in dairy plants, handling and distribution in the markets particularly at local small manufacture scale.

With the rapid development of communication technology, connected vehicles (CV) have the potential, through the sharing of data, to enhance vehicle safety and reduce vehicle energy consumption and emissions. Numerous research efforts have been conducted to quantify the impacts of CV applications, assuming instant and accurate communication among vehicles, devices, pedestrians, infrastructure, the network, the cloud, and the grid, collectively known as V2X (vehicle-to-everything). The use of cellular vehicle-to-everything (C-V2X), to share data is emerging as an efficient means to achieve this objective. C-V2X releases 14 and 15 utilize the 4G LTE technology and release 16 utilizes the new 5G new radio (NR) technology. C-V2X can function without network infrastructure coverage and has a better communication range, improved latency, and greater data rates compared to older technologies. Such highly efficient interchange of information among all participating parts in a CV environment will not only provide timely data to enhance the capacity of the transportation system but can also be used to develop applications that enhance vehicle safety and minimize negative environmental impacts. However, before the full benefits of CV can be achieved, there is a need to thoroughly investigate the effectiveness, strengths, and weaknesses of different CV applications, the communication protocols, the varied results with different CV market penetration rates (MPRs), the interaction of CVs and human driven vehicles, the integration of multiple applications, and the errors and latencies associated with data communication. This paper reviews existing literature on the environmental, mobility and safety impacts of CV applications, identifies the gaps in our current research of CVs and recommends future research directions. The results of this paper will help shape the future research direction for CV applications to realize their full potential benefits.

ZIKV is the latest addition to an ever-growing list of arboviruses that are causing outbreaks with serious consequences. 14 mild cases were recorded between 1960 and 1980 until the first major outbreak was recorded in 2007 on Yap island followed by more severe outbreaks in French Polynesia (2013) and Brazil (2015) leading to a 20-fold increase in GBS and Microcephaly cases respectively. Various transmission methods have been recorded ranging from Aedes mosquito vector transmission to sexual and vertical transmission. No current vaccines or treatments are available but recent studies have taken interest in the NS5 protein which has both the RdRp & MTase domains making it important for viral replication alongside other important functions such as inhibiting the innate immune system thus ensuring virus survival and replication. Structural studies can help design inhibitors while biochemical studies can help understand the various mechanisms utilized by NS5 thus counteracting them can inhibit or abolish the viral infection. Drug repurposing has proven to be an effective tool since hundreds of thousands of compounds can be screened in-silico thus saving time and resources while also having information available on such compounds especially if they are already used to treat other ailments.

This study introduces a novel algorithm tailored for the precise detection of lower outliers in univariate datasets, particularly suited for scenarios with a single cluster. The approach leverages a combination of transformative techniques and advanced filtration methods to efficiently segregate anomalies from normal values. Notably, the algorithm emphasizes high precision, ensuring minimal false positives, and requires only a few parameters for configuration. Its unsupervised nature enables robust anomaly filtering without the need for extensive manual intervention. To validate its efficacy, the algorithm is rigorously tested using real-world data obtained from photovoltaic (PV) module strings with similar DC capacities, containing various anomalies. Results demonstrate the algorithm's capability to accurately identify lower outliers while maintaining computational efficiency and reliability in practical applications.

As machine learning and computer vision techniques and methods continue to advance, the collection of naturalistic traffic data from video feeds is becoming more and more feasible. That is especially true for the case of bicycles, for which the collection of naturalistic data is not achievable in the traditional vehicle approach. This study describes a research effort that aims to extract naturalistic cycling data from a video dataset for use in safety and mobility applications. The used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research team applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles at a high level of precision. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined.

Although train simulation research is vast, most available network simulators do not track the instantaneous movements and interactions of multiple trains for the computation of energy/fuel consumption. In this paper, we introduce the NeTrainSim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. Trains are modeled as a series of moving mass points (each car/locomotive is modeled as a point mass) while ensuring safe following distances between them. The simulator considers the motion of the train as a whole and neglects the relative movements between the train cars/locomotives. Furthermore, the powers of the different locomotives are transferred to the first locomotive as such a simplification result in a reduced simulation time without impacting the accuracy of energy consumption estimates. While the different tractive forces are combined, the resistive forces are calculated at their corresponding locations. The output files of the simulator contain pertaining information to the train trajectories and the instantaneous energy consumption levels. A summary file is also provided with the total energy consumed for the full trip and the entire network of trains. Two case studies are conducted to demonstrate the performance of the simulator. The first case study validates the model by comparing the output of NeTrainSim to empirical trajectory data using a basic single-train network. The results confirm that the simulated trajectory is precise enough to estimate the electric energy consumption of the train. The second case study demonstrates the train-following model considering six trains following each other. The results showcase the model’s ability in relation to maintaining safe-following distances between successive trains. Finally, the NeTrainSim is demonstrated to be scalable with computational times of O(n) for less than 50 trains (n) and O(n²) for higher number of trains.

The transportation system has evolved into a complex cyber-physical system with the introduction of wireless communication and the emergence of connected travelers and connected automated vehicles. Such applications create an urgent need to develop high-fidelity transportation modeling tools that capture the mutual interaction of the communication and transportation systems. This paper addresses this need by developing a high-fidelity, large-scale dynamic and integrated traffic and direct cellullar vehicle-to-vehicle and vehicle-to-infrastructure (collectively known as V2X) modeling tool. The unique contributions of this work are (1) we developed a scalable analytical communication model that captures packet movement at the millisecond level; (2) we coupled the communication and traffic simulation models in real-time to develop a fully integrated dynamic connected vehicle modeling tool; and (3) we developed scalable approaches that adjust the frequency of model coupling depending on the number of concurrent vehicles in the network. The proposed scalable modeling framework is demonstrated by running on the Los Angeles downtown network considering the morning peak hour traffic demand (145,000 vehicles), running faster than real-time on a regular personal computer (1.5 hours to run 1.86 hours of simulation time). Spatiotemporal estimates of packet delivery ratios for downtown Los Angeles are presented. This novel modeling framework provides a breakthrough in the development of urgently needed tools for large-scale testing of Direct C-V2X enabled applications.

Prolonged fatigue is associated with non-pathological causes, and lacks an established therapeutic approach. The current study is aimed at assessing the efficacy of a new food supplement (Improve® Response) based on a chemically characterized pomegranate extract and hydro-soluble vitamins (B complex and C). UHPLC-HRMS analysis of pomegranate extract showed the presence of 59 compounds, with gallotannins and ellagitannins being the most abundant phytochemicals. For the clinical study, 58 subjects were randomized into two groups, 1 and 2 (n = 29, each), which received either the food supplement or placebo. The effects of the food supplement against fatigue were assessed via validated questionnaires, recorded at time intervals t0 (at baseline), t1 (after 28 days), t2 (56 days), and t3 (after follow-up) in combination with the analysis of biochemical markers at t0 and t2. Fatigue Severity Scale (FSS) questionnaire scores were significantly decreased at the t2 and t3 time intervals in subjects treated with the food supplements, while the effect of the food supplement on a 12-Item Short Form Survey (SF-12) was not considerable. Moreover, the food supplement did not significantly affect biochemical parameters associated with fatigue and stressed conditions. This study shows that the food supplement tested reduces prolonged fatigue following two months supplementation in healthy subjects with mild prolonged fatigue.

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.

Natural risks encompass a range of disasters and dangers, requiring comprehensive management through assessments, anticipations, and advanced alert systems. Our specific focus is on landslides in challenging terrains. The evaluation of landslide risks employs sophisticated multicriteria models, such as the weighted sum approach, integrating qualitative parameters. Despite the challenges of the rugged terrain in Northern Algeria, it paradoxically hosts a dense population attracted by valuable hydro-agricultural resources. Our research is dedicated to studying landslide risks in these areas, particularly in the Mila region, with the aim of constructing a statistical model integrating considerations of both danger and vulnerability. This complex process identifies threats and their determining factors, including geomorphology and socio-economic conditions. The result is a valuable tool for effective risk management, strengthening safety and resilience against natural disasters. By understanding the intricate interplay of geological, environmental, and social elements, our research can contribute to the development of targeted interventions, fostering a more resilient community in the face of natural adversities.

The coexistence of SAH with T2DM is a common comorbidity. In this present study, we investigated the link between altered plasma antioxidant trace elements (ATE: Manganese, Selenium, Zinc and Copper) and fatty acids ratio (FAR: polyunsaturated/saturated) imbalance as transition biomarkers between vascular pathology (SAH) to metabolic pathology (T2DM). Our data revealed strong correlation between plasma ATE and FAR profile which is modified during SAH-T2DM association compared to healthy group. This relationship is mediated by lipotoxicity (simultaneously prominent visceral adipose tissue lipolysis, significant flow of non-esterified free fatty acids release, TG-Chol-dyslipidemia, high association of Total SFA, Palmitic acid, Arachidonic acid and PUFA 6/ PUFA 3; drop in tandem of PUFA / SFA and EPA+DHA); oxidative stress (lipid peroxidation confirmed by TAS depletion and MDA raise, concurrently drop of Zn/Cu-SOD, GPx, GSH, Se, Zn, Se/Mn, Zn/Cu; concomitantly enhance Cu, Mn and Fe); endothelial dysfunction (endotheline-1 increase); athero-thrombogenesis risk (concomitantly raise of ApoB100/ApoA1, Ox-LDL, tHcy and Lp(a)) and inflammation (higher of Hs-CRP, Fibrinogen and Ferritin). Our study open to new therapeutic targets and to better dietary management, such as to establish dietary ATE and PUFA 6 / PUFA 3 or PUFA / SFA reference values for atherosclerotic risk prevention in hypertensive-diabetics patients.

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.

El Niño Southern Oscillation (ENSO) is an important of mode of climatic variability that through altering climate patterns exerts a discernible impact on ecosystems and society. For this reason, ENSO has attracted much interest in the climate and health science community with many analysts investigating ENSO health links through considering the degree of dependency of the incidence of a range of climate diseases on the occurrence of El Niño events. Because of the mounting interest in the relationship between ENSO as a major mode of climatic variability and health this paper presents an overview of the basic characteristics of the ENSO phenomenon and its climate impacts, discusses the use of ENSO indices in climate and health research and outlines the present understanding of ENSO health associations. Also touched upon are ENSO-based seasonal health forecasting and the possible impacts of climate change on ENSO and the implications this holds for future assessments of ENSO health associations. The review concludes that there is still some way to go before a thorough understanding of the association between ENSO and health is achieved with a need to move beyond analyses undertaken through a purely statistical lens with due acknowledgement that ENSO as a complex non-canonical phenomenon and that simple ENSO health associations should not be expected.

The El Niño-Southern Oscillation (ENSO) stands as the paramount tropical phenomenon of climatic magnitude resulting from ocean-atmosphere interaction. Due to its atmospheric teleconnection mechanism, ENSO wields influence over diverse environmental variables spanning distinct atmospheric scales, thereby potentially impacting the spatiotemporal distribution of atmospheric aerosols. Within this framework, this study aims to appraise the relationship between ENSO and atmospheric aerosols across the Legal Amazon during the period between 2006 and 2011. Over this quinquennium, four ENSO events were identified. Concurrently, an analysis was conducted on the spatiotemporal variability of aerosol optical depth (AOD) and AOD extinction for Black Carbon (EAOD-BC), concomitant with said ENSO events, utilizing data derived from the Aerosol Robotic Network (AERONET), MERRA-2 model, and ERSSTV5. Through the Windowed Cross Correlation (WCC) approach, statistically significant phase lags of up to 4 to 6 months were observed between ENSO indicators and atmospheric aerosols. Moreover, conspicuous increases of over 100% in atmospheric aerosol concentration were evidenced subsequent to El Niño periods, especially during the intervals encompassing the La Niña phase, particularly within the La Niña CP (Central Pacific)/Modoki category. By analyzing specific humidity anomalies (QA), exceptional scenarios in the region were detectable. This observation suggests a notable singularity when juxtaposed with antecedent investigations and typical average patterns characterizing the impacts on the Amazonian region.

This review is dedicated to sustainable practices in liquid chromatography. HPLC and UHPLC methods contribute significantly to routine analytical techniques. Therefore, the transfer of classical liquid chromatographic methods into sustainable ones is of utmost importance in moving toward sustainable development goals. Among other principles to render a liquid chromatographic method green, substitution of the organic solvent component in the mobile phase with a greener one received great attention. This review concentrates on choosing the best alternative green organic solvent to replace the classical solvent in the mobile phase for easy rapid transfer to a more sustainable normal phase or reversed-phase liquid chromatography. The main focus of this review will be on describing the transfer of non-green to green and white chromatographic methods in an effort to elevate the sustainability best practice in analytical chemistry. The greenness properties and greenness ranking in addition to the chromatographic suitability of seventeen organic solvents for liquid chromatography are mentioned to have a clear insight into the issue of rapidly choosing the appropriate solvent to transfer a classical HPLC or UHPLC method into a more sustainable one. A simple guide is proposed for making the liquid chromatographic method more sustainable.

Eating disorders are a global burden and present personal, family, and societal costs. Most evidence in the literature is based on the relationship between a poor family environment and eating disorders, and the evidence of gender interaction in eating disorders is inconsistent. This study aimed to investigate the relationship between family functioning and disordered eating patterns, the mediating role of negative automatic thoughts, and the moderating role of gender. A sample of 440 (70.9% females, aged 18–21) participated in this study. They completed the Eating Attitudes Test (EAT-26), the Automatic Thoughts Questionnaire (ATQ negative), and the Brief Family Relationship Scale (BFRS). PROCESS MACRO was used to study these relationships. The main findings revealed that family functioning was negatively associated with eating disorders, and that this relationship was negatively mediated by automatic thoughts. Moreover, gender moderated those relationships, and more intensely in females. The results of this study postulate that the prevention of eating disorders should be directed at training individuals to challenge negative thoughts and encourage healthy individuals to be gender mindful.

The variability of ozone over Egypt has been studied in this work. Higher values of coefficient of variation (COV) at eight stations occur at winter while lowest values occur at summer. The COV is function of latitude in annual, winter and spring where it decreases gradually from the north to south of Egypt. The trend analysis of ozone over the eight stations indicates negative trends over northern stations for both annual and seasonal time series with the greatest one at winter. The horizontal distribution of ozone trend values is negative over all Egypt in winter while it positive over middle and south Egypt in the other seasons. The long-term variability of the behavior of the annual ozone shows positive trend values in ozone are the dominant features during the period 1979- 1989 at the most stations. Negative trend values in ozone are the dominant features during the period 1990- 2014 at all stations. The Mann–Kendall test confirms that there is an abrupt change towards decreasing of ozone occurs in 1981, 1984, 2012, 1999, 2000, 1998 and 2010, while a change towards increasing of ozone appears in 2006, 2014, 1993 and 1989.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

Cervical cancer is preventable through vaccination, early detection, and treatment of precancerous lesions. However, global inequalities mean that the disease remains a leading cause of cancer death around the world, with over 80% of new cases and 90% of deaths occurring in low and middle-income countries (LMICs). In El Salvador, joint efforts between the Ministry of Health (MoH) and the non-profit organization Basic Health International (BHI) have been in place since 2008 with the goal of reducing the country’s disease burden. While the World Health Organization’s (WHO) call to action to eliminate cervical cancer provided worldwide momentum to implement new public health initiatives, the COVID-19 pandemic disrupted ongoing programs and jeopardized plans for the future. The purpose of this manuscript is to describe the progress that El Salvador has achieved in improving cervical cancer prevention, the impact of the pandemic on current strategies, and potential solutions that can help the country meet the WHO’s strategic targets by 2030 to accelerate the elimination of cervical cancer.

Obstructive sleep apnea (OSA) may be linked to various factors that narrow the upper airways, such as obesity, adenotonsillar hypertrophy and craniofacial abnormalities. Hypothyroidism has also been described as a risk factor for OSA. However, the implication of goiter independently of thyroid function in the occurrence of OSA remains unclear. We present the case of a 66-year-old patient, with a large compressive multinodular goiter for whom total thyroidectomy was indicated. During the preoperative assessment, the patient showed a body mass index (BMI) of 37.8 kg/m2 with symptoms of OSA. Respiratory polygraphy confirmed the diagnosis of severe OSA (apnea hypopnea index: AHI=32) and treatment with continuous positive airway pressure (CPAP) was initiated prior to thyroid surgery. Surprisingly, after total thyroidectomy, OSA symptoms disappeared and the patient abandoned CPAP therapy. Subsequent respiratory polygraphy after thyroidectomy showed a decrease in AHI to a normal value (AHI < 5). Interestingly, there was no change in BMI or other factors explaining the resolution of OSA, except for thyroidectomy. This case report suggests that goiter can be considered a risk factor for OSA. However, prospective studies are needed to accurately assess the effects of goiter on occurrence of OSA according to its dimensions and local extension.

A complete understanding of groundwater dynamics and its interaction with surface water underthe impact of agricultural activities is vital for local agriculture, ecology, and residents of dry regions, which is not commonly recognized in arid areas. This research outlines the geochemical characteristics, recharge sources, and potential factors impacting groundwater quality in a new land reclamation located in the small basin of Abu Mina, which is part of the Western Nile Delta region.1 Thirty‑one groundwater samples and two surface water samples were collected in 2021 to represent the Pleistocene aquifer and were subjected to multivariate statistical, hydrochemical, and stable isotope analyses. Data analysis demonstrates that Na+ > Ca2+ > Mg2+ > K+ and SO4 2– > Cl– > HCO3 – > NO3 – are the predominant cations and anions, respectively. Groundwater salinity ranged from 465.60 to 6455.18 mg/l, with slightly alkaline. Most of the water samples fall into one of three types of facies: Ca–Cl, Na–Cl, and Mixed Ca–Mg–Cl, in decreasing order. The meteoric genesis index (r2) indicates that deep meteoric water percolation dominates the Pleistocene aquifer. The aquiline diagrams, correlation matrix, and different ionic ratios indicate that evaporation, reverse ion exchange reactions, and the dissolution of carbonate and silicate minerals are the main processes governing groundwater chemistry. Factor analysis (FA) indicated that three factors explain groundwater hydrochemistry, accounting for 71.98% of the total variance. According to the rotating components matrix (F1–F3), the chemistry of the Quaternary aquifer is principally affected by evaporation, ion exchange reactions, and anthropogenic influences. Additionally, salinity increases due to the return flow of irrigation activities and mixing between old and recent water. The stable isotopes (δ18O and δ2H) indicate that the Quaternary aquifer receives groundwater recharge through the return flow of excess irrigation and canal seepage. Under desert reclamation conditions, groundwater salinization processes should be given special consideration. All groundwater samples are appropriate for agricultural irrigation based on the Sodium Adsorption Ratio (SAR), Permeability Index (PI), Percent Sodium (%Na), and Residual Sodium Carbonate (RSC).

This cross-sectional study was aimed to investigate the relationship between gratitude and life satisfaction, and the mediation role of social support and enjoyment of life among older individuals. The Gratitude Resentment and Appreciation Test, the Enjoyment of Life Scale, the Satisfaction with Life Scale, and the Multidimensional Scale of Perceived Social Support Scale were administered to a sample of 260 older individuals aged between 60 and 80. The main findings revealed a positive association between gratitude and life satisfaction, and social support was a partial mediator in this relationship. Although enjoyment of life was not a direct mediator in the relationship between gratitude and life satisfaction, the final model indicated a significant serial pathway from gratitude to social support and then through enjoyment of life-to-life satisfaction. In conclusion, enhancing gratitude, promoting enjoyment of life, and social support in older individuals might increase their life satisfaction, which in turn might contribute to their successful aging

Researches are moving to iron and ammonia elimination from ground water. Here, we are using poly acrylic–poly acrylamide hydrogel which grafted with 3-chloroaniline. This copolymer was synthesized by addition polymerization. Effect of agitation time, dosage and adsorbents temperature on the removal process sensitivity has been investigated. The copolymer was described experientially and theoretically. Isothermal, kinetic adsorption models and were discussed. This hydrogel could be regenerated efficiently (98.3%removal of iron and 100% removal of ammonia). Density functional theory DFT method using B3LYP/6-311G(d,p),LANL2DZ level of the theory were managed to investigate stationary states of grafted co-polymer and the complexation energy of the hydrogel with the studied cations. NBO analysis is using DFT to investigate the negative centers on the hydrogel. The complexation energy showed selectively of hydrogel to studied cations.

The study of localized surface plasmons (LSPs) in nanoscale structures is an essential step towards identifying optimal plasmonic modes that can facilitate robust optomechanical coupling and deepen our understanding of light-matter interactions at the nanoscale. This paper investigates numerically, using the finite element method, LSPs modes in a design comprising two coupled nano-ridges deposited on a gold layer, with an interposing polymer spacer layer. Such a structure, usually referred to as particles-on-mirror, shows exquisite optical properties at the nanoscale. We first examine the LSPs modes of a single nano-ridge through the analysis of its scattering cross-section in the visible and infrared range. To enhance the plasmonic response, a thin polymer layer is placed at the middle of the ridge, which introduces additional LSPs modes confined within the former. Then, we extend the analysis to the dimer configuration, which exhibits more complex and enhanced plasmonic behavior compared to a single nano-ridge. In particular, the dimer configuration yields LSPs resonances with a quality factor enhancement of approximately threefold relative to single nano-ridge. Furthermore, the presence of the polymer layer within the ridges significantly improves plasmon field localization and quality factor. These findings underscore the potential of nano-ridge-based structures in advancing optomechanical coupling and plasmon-phonon interaction studies, offering valuable insights for the development of high-performance acousto-plasmonic devices. In particular, the proposed device could help significantly improve the design of nano-acousto-optic modulators operating in the visible or in the near infrared, that require enhanced light-photon coupling rate.

Due to the great nutritional and medicinal value of honey, there has been growing consumer’s preference towards honey of a known identity. However, honey now is the third food in the world subjected to adulteration. Therefore, the current study was focused on judging the identity of Sudanese honeys and checking whether there is any misdesignation from originality. Melissopalynology was used as a tool for this purpose. A number of 60 honey samples were purchased from honey sellers. Results indicated that honey bees foraged on a bio-diversified number of plant species constituted of 11 major families [Fabaceae (43.3%), being the predominant family] and 8 minor families. Respectively, 18.3% &amp; 2% of the honey samples were found to be misdesignated by the honey sellers from their botanical and geographical identities. Some samples were predicted by melissopalynology to be originated from Ethiopia by the presence of marker pollens such as Kniphofia foliosa, Guizotia abyssinica, and Acacia abyssinica an indigenous Ethiopian flora. Thus these findings proved that melissopalynology is an effective tool in judging the identity of honey and pro of being inexpensive.

Phylogenetic analysis of blood parasite infections including Babesia (B.) bovis, Babesia microti and Trypanosoma (T.) spp. in one-humped camel (Camelus dromedarius) (n= 142) breeds in Halayeb and Shalateen, in Upper Egypt were performed in the current study. Polymerase chain reaction (PCR) assays targeting the Rhoptry Associated Protein-1 (RAP-1), Babesia microti small subunit rRNA (ss-rRNA) and internal transcribed spacer 1 (ITS1) genes were used to detect the prevalence of B. bovis, B. microti and Trypanosoma spp. in camels, respectively. Nested PCR assays were used for the detection of Babesia spp. (B. bovis and B. microti). While, KIN-multi species PCR reaction was employed to detect and identify trypanosome DNA in camels. B. microti was detected in (17/142) with infection rate (11.97 %). Sequencing and phylogenetic analyses revealed that B. microti detected in camel was closely related to the German strain in rats and voles in France. B. bovis was also detected in (4/142) with infection rate (2.81%). The sequence and phylogenetic analyses revealed that the isolated B. bovis was closely related to strains isolated from Argentine, USA and Brazil. Moreover, T. evansi was detected in (8/142) with infection rate (5.63%). Sequence and phylogenetic analyses revealed that isolated T. evansi was closely related to T. theileri that was detected from cattle in Brazil. This study provides the first evidence of B. microti in camel in Egypt and highlights the possible role of one-humped camels in maintaining the enzootic cycle of Babesia transmission in Egypt.

Coronavirus (COVID-19) gained and will continue to gain a lot of global attention over the coming months (and maybe the coming few years). Since its outbreak in Wuhan (China), it has turned into one of the major challenges affecting the whole world. In a comparatively short time, the virus outbreak turned into a pandemic that led to massive negative impacts not only on people health and well-being, but also on the global economy, travel industry, pharmaceutical industry, tourism industry, and many other industries. This research paper aims to investigate the different effects of coronavirus on the global Halal tourism and Halal hospitality industry and whether the coronavirus pandemic is the end of Halal tourism and hospitality as we know it or not. The paper offers an in-depth theoretical examination of the different aspect of the pandemic on Halal tourism and hospitality industry and provides guidance on how to address these different aspects. The current paper is one of very few research papers addressing coronavirus on the tourism and hospitality industry.

Generative artificial intelligence tools are flourishing across various sciences, particularly in the educational domain. ChatGPT, with its versions 3.5 and 4.0, stands out for its multilingual capabilities, catering to both students and educators. This research aimed to evaluate the performance differences between these versions, and importantly, to compare the accuracy of ChatGPT's responses in English versus Arabic. In our study, we presented ChatGPT with 39 chemistry problems related to 6th-7th grade curriculum, including twenty-five open questions and fourteen multiple-choice questions. Each response was categorized as accurate, partially accurate, or inaccurate. Our analysis, focused on trends across versions and languages, revealed significant enhancements in version 4.0, particularly in its ability to process Arabic. However, despite these improvements, our findings indicate that responses in English consistently outperformed those in Arabic in terms of accuracy. In light of this discrepancy, we suggest that ChatGPT either incorporates additional Arabic databases into its training regimen or develops a code that adopts the following strategy to ensure more accurate responses in science education: questions should first be translated from Arabic to English, addressed, and then retranslated into Arabic before being presented to the user. This approach takes advantage of the greater accuracy of responses in English to benefit Arabic-speaking users, and it may also improve outcomes for speakers of other languages who experience less precise answers in the fields of chemistry or science education.

Excessive intake of fat and fatty acids is associated with major health hazards such as obesity or chronic diseases. The aim of this study was to provide the first data on total fat, saturated fatty acids (SFA) and trans fatty acids (TFA) intakes and their major food sources in Tunisian children. A total of 1200 children, aged 3 to 9 years old (yo), were randomly selected from primary schools and kindergarten under a cross-sectional design. The 24-hour recall method and food frequency questionnaire were used to assess dietary intake. The energy percentages of total fat, SFA and TFA in Tunisian children were respectively 29.6, 11.4 and 0.15. No sex differences were found. The WHO recommendations for total fat, SFA and TFA were adopted by 58 %, 39 % and 89 % of the study population, respectively. The leading food groups of fat and fatty acids were ultra-processed foods, breakfast cereals and dairy products. The meat, fish, eggs and fish alternatives were the fifth main contributors to the total fat and SFA intakes in Tunisian children. The implementation of a relevant strategy for fat reduction, especially from ultra-processed foods, considered as low nutrient energy-dense products, is needed to promote health among children and prevent diet-related chronic diseases.

This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility within pre-emerging stock markets, specifically the Moroccan and Bahraini stock markets. The findings suggest reevaluating the balance between model complexity and predictive accuracy. Future research directions include investigating the potential existence of threshold effects in market capitalization for optimal model performance. This research contributes to a deeper understanding of volatility dynamics and enhances forecasting models’ effectiveness in diverse market conditions.

Although laccase has been recognized as a wonder molecule, and green enzyme, the use of low yielding fungal strains, poor production, purification, and low enzyme kinetics have hampered its larger-scale applications. Hence the present research was aimed to select high yielding fungal strains and to optimize the production, purification, and kinetics of laccase of Aspergillus sp. HB_RZ4. Aspergillus sp. HB_RZ4 produced a copious amount of laccase on under meso-acidophillic shaking conditions in a medium containing glucose and yeast extract. A 25 µM of CuSO4 enhanced the enzyme yield. The enzyme was best purified on Sephadex G-100 column. Purified enzyme resembled with the laccase of A. flavus. Kinetics of purified enzyme revealed the high substrate specificity and good velocity of reaction with ABTS as substrate. The enzyme was stable over a wide range of pH and temperature. The peptide structure of the purified enzyme resembled with the laccase of A. kawachii IFO 4308. The fungus decolorized various dyes independent of the requirement of a laccase mediator system (LMS). Aspergillus sp. HB_RZ4 came out as a potent natural producer of laccase, it decolorized the dyes even in absence of LMS and thus can be used for bioremediation.

The coastal Peru, one of the driest deserts in the world, has recently experienced dramatic landscape changes and asset destruction during precipitation events due to El Niño. Nevertheless, catastrophic explanations for landscape variations and human responses to the so-called "Super" or "Mega" El Niños are recurrent in pre-Hispanic time, even if alternative hypotheses were provided in literature. A deeper understanding of the geological and archaeological record can improve the knowledge on the relationship between such a coupled atmosphere-ocean phenomenon and landscape processes. The bibliographic sources required for this purpose are scattered throughout various disciplines ranging from physical to human sciences, thus comprehensive databases were used to identify and screen the relevant studies. The results provide knowledge synthesis in order to identify critical gaps and suggest specific research goals. Inferred episodes of landscape change due to severe precipitations in late pre-Hispanic time are discussed and consistencies and inconsistencies exposed. Examples of variation in landscape response due to extensive human intervention are reported.

New Schiff base ofN'-((E)-3,3-diphenyl-2,3-dihydro-1H-inden-1-ylidene)-2-((Z)-2-oxoindolin-3-ylidene)hydrazine-1-carbothiohydrazide (HL) and its Co(II),Ni(II), Fe(III), Cu(II), Cd(II), Zn(II) and Mn(II) complexes were created, isolated, and characterized by analytical analysis in good yields of 60 to 90%, UV–Vis, magnetic measurements, molar conductivity, and FT-IR. Additionally, mass spectrometry was used to examine the new ligand complexes' structural characteristics.1H NMR spectroscopy and elemental analysis. Depending on the electronic spectra and magnetic susceptibility measurements, these complexes are predicted to have octahedral molecular geometry. As an example, the quantum chemical properties, bond lengths, and bond angles were discussed. The structural formula for the examined ligand was improved using the Gaussian09 tool. The DFT/B3LYP method was used to calculate the energy gaps and other crucial theoretical features. The prepared hydrazine ligand complexes Co (II), Ni (II), Fe (III), Cu (II), Cd (II), Zn (II) and Mn (II) complexes were evaluated for its antimicrobial properties. As antimicrobial agents, it was found that the organic ligand was less biologically active than the targeted complexes. Gram positive bacteria (3ty7-Staphylococcus), Gram negative bacteria (3t88-Escherichia coli), and fungi (5k04-Candida albicans) all have crystal structures that interact well with the chemicals in the title, according to molecular docking.

As the Autonomous Vehicle (AV) industry is rapidly advancing, classification of non-motorized (vulnerable) road users (VRUs) becomes essential to ensure their safety and to smooth operation of road applications. The typical practice of non-motorized road users’ classification usually takes numerous training time and ignores the temporal evolution and behavior of the signal. In this research effort, we attempt to detect VRUs with high accuracy be proposing a novel framework that includes using Deep Transfer Learning, which saves training time and cost, to classify images constructed from Recurrence Quantification Analysis (RQA) that reflect the temporal dynamics and behavior of the signal. Recurrence Plots (RPs) were constructed from low-power smartphone sensors without using GPS data. The resulted RPs were used as inputs for different pre-trained Convolutional Neural Network (CNN) classifiers including constructing 227×227 images to be used for AlexNet and SqueezeNet; and constructing 224×224 images to be used for VGG16 and VGG19. Results show that the classification accuracy of Convolutional Neural Network Transfer Learning (CNN-TL) reaches 98.70%, 98.62%, 98.71%, and 98.71% for AlexNet, SqueezeNet, VGG16, and VGG19, respectively. The results of the proposed framework outperform other results in the literature (to the best of our knowledge) and show that using CNN-TL is promising for VRUs classification. Because of its relative straightforwardness, ability to be generalized and transferred, and potential high accuracy, we anticipate that this framework might be able to solve various problems related to signal classification.

On the afternoon of January 31, 2022, the northwest and central part of the city of Quito (Ecuador) was hit by a mud-flow that originated in one of the ravines of the Pichincha volcanic complex. According to the official reports, there were 28 fatalities, one missing person, 52 injured, and 53 families affected. The mudflow was triggered by unusual and heavy rainfall in the upper part of the drainage. However, the analysis of the deposits allowed us to establish the existence of anthropogenic elements as crucial components of a local disaster that affected daily life in the city for more than a week. Based on the preliminary data, we were able to determine that the mud and water flowed through different streets of the city, reaching a maximum distance of 3.2 km from the overflow point (collector, construction works to dam the drainage under the city). The analysis of the multimedia material published on social networks and in the press also made it possible to detect the change in the behavior of the flow during its evolution, which went from a hyper-concentrated flow to muddy water. A similar event occurred in 1975, and although it was a larger event (52000 m3, seven times larger than in 2022), it caused two deaths and little damage in the same area. The main causes of the disaster included urban development that did not meet the needs of the area and a lack of awareness or ignorance about the management and intervention of drainage in Quito City.

In this paper for every number field K generated by a root α of a trinomial x⁷ + ax + b ∈ Z[x] and for every prime integer p, we calculate ν_p(i(K)), the highest power of p dividing the index i(K) of the field K. In particular, we calculate the index i(K). As application, when the index of K is not trivial, then K is not monogenic.

BackgroundThe novel virus COVID-19, also known as SARS-CoV‑2, is currently rapidly spreading around the globe and pushing healthcare systems to the limits of their capacity. One of the functions of predictive models is to timely act for epidemic preparedness including hospital preparedness. In Egypt, like many other countries in the world, the epidemic situation and forecasting have not yet sufficiently studied. ObjectiveThe study was carried out to develop a short-term forecast scenario for the COVID-19 epidemic situation in Egypt and predict the hospital needs to accommodate the growing number of cases.MethodsSecondary data from the COVID-2019 daily reports and the report issued 8^th of April by the Egyptian Ministry of Health and Population were used. Due to the daily changing level of knowledge and data, the article reflects the status up to 18 April 2020. The prediction was based on the exponential growth rate model. For the depiction of the situation, the full length of the epidemic timeline was analyzed (from February 14^th till April 18^th). The growth rates and their rates of decline during the period from the 22^nd of March till the 18^th of April were calculated and extrapolated in the coming 7 weeks. The predicted hospital needs were assessed against the announced allocated resources.ResultsThe epidemic curve in Egypt is on the ascending arm as of April, 18. The active cases showed exponential growth from the start of the epidemic till April, 18. At the end of this period time, the recovery rate was 23.12% and the case fatality rate (CFR) was7.39. The case fatality rate median level during the last four weeks was 6.64. The active cases are expected to reach more than 20,000 by late May then starts to decline. The allocated regular hospital beds are predicted to show shortage by the time of the release of the paper. The intensive care units (ICU) beds and ventilators are predicted to show insufficiency on May 6.Conclusions: The COVID-19 epidemic in Egypt is expected to continue on the rise for the next few weeks and expected to start to decline late in May, 2020. Our estimates should be useful in preparedness planning. Serious actions should be taken to provide ICU beds and ventilators enough for the predicted number of cases that would need them, not later than the end of April. Mitigation actions have to continue for the coming 6 weeks or until the epidemic situation is more clearly seen.

Has anyone ever missed an event because he was confused in days and dates? Do we remember the date of any day without looking at a calendar? Is the current Gregorian Calendar efficient enough for use, and does it facilitate our life or make it more complicated? Have you ever thought about a much simpler way to calculate days and dates in a year? All these questions are answered in this paper, in which the author proposes original optimization algorithm that creates optimal perennial calendars. Results show that there is more than one way to create a perennial calendar, in which the number of days in each month does not change, neither the dates. Hence, all months have the same sequence of days and dates. In other meaning, Monday becomes the first day of every month, and Sunday becomes the last day. Consequently, the calendars become much easier to memorize and very simple to predict the days and dates in any year.

This work aims to investigate the impact of chemical treatment of Juncus acutus fibers on the hygric and mechanical performances of an innovative bio-sourced clay-sand-Juncus acutus fibers composite. This lightweight specimen has been produced from a mixture of 60 % natural clay and 40 % sand by mass, as a matrix, and reinforced with different amounts of Juncus fibers. The fibers were used as a partial replacement of sand in mixture by volume at 0 % (Control Specimen), 5 %, 10 %, and 20 %. In order to enhance the fiber-matrix interfacial bound, the raw fibers have undergone an NaOH alkali treatment with different concentrations of 1, and 2 wt. %. Morphological and mineralogical evaluation based on SEM micrographs and EDX analyses revealed that, the alkaline concentration of 1 wt. % is the optimized one for natural fiber surface modifications (removal of impurities without any surface damage). This optimal concentration is confirmed by tensile strength tests, showing that the treated fibers with this alkali solution presents the higher tensile stress value of 81.97 MPa, compared to those of treated fibers with 2 % NaOH (74.45 MPa), and the untreated fibers (70.24 MPa). However, mechanical test-results highlighted the benefit effect of the fiber alkali treatment on both the compressive and flexural strengths, particularly for fiber contents of 5 % and 10 %, which corresponds to a strengthening rate of 25 % and 30 %, respectively. Results also showed that the sample containing treated fibers exhibited a better moisture regulating property than that produced with untreated fibers. The specimens are classified as excellent hygric regulator based on their moisture buffer performance (MBV > 2 g/(m2.%RH)), according to NORDTEST classification. Results also indicated that the capillary water absorption and the apparent moisture diffusivity of composites was lowered due to high fiber-matrix interfacial bound, after fiber treatment. Consequently, the composite with treated fibers is less diffusive compared to that with untreated fibers, and thus expected to be more durable in a humid environment. These results were confirmed by morphological analysis of fibers-matrix interfacial transition zone.

Remotely sensed data play a crucial role in monitoring the El-Niño/La-Niña Southern Oscillation (ENSO), which is an oceanic-atmospheric phenomenon occurring quasi-periodically with several impacts worldwide, such as specific biological and global climate responses. Since 1980, Earth has witnessed three strong ENSO events (1982–1983, This study aims, 2015-2016). In September 2022, La-Niña entered its third year and was unlikely to continue through 2023. Instead, since 2022 forecasts pointed to a transition from La-Nina to a Neutral phase in summer or late 2023. The onset of the El-Niño occurred around April 2023, and it is anticipated by sophisticated models to be a strong event through the Northern Hemisphere winter (December 2023 - February 2024). The aim of this study is to demonstrate the ability of the combination of two new methods to improve the accuracy of the above claim because El-Niño apart from climate anomalies, significantly impacts Earth’s ecosystems and human societies, regulating the spread of diseases by insects (e.g., malaria and dengue fever), and influencing nutrients, phytoplankton biomass, and primary productivity. This is done by exploring first the previous major El-Niño events in the period January 1876-July 2023. Our calculations show that the ongoing 2023-2024 El-Niño will not be the strongest.

The upper ocean heat content in the equatorial Pacific usually serves as a primary precursor for an upcoming El Niño, while the strong atmospheric perturbations such as westerly wind burst and easterly wind surge sometimes play a decisive role in determining the final intensity of the event. The tropical Pacific Ocean has just experienced a rare 3-year La Niña, which accumulated a huge amount of warm water in the western basin by the winter of 2022. Using a state-of-the-art climate prediction system, here we show that the restored warm water is sufficient to boost a strong El Niño toward the end of 2023, and that an extreme event could take place if a few sizable westerly wind bursts would occur in spring and early summer. This prediction is not sensitive to initial errors within the tropical Pacific, but may be subject to some uncertainties brought about by influences from elsewhere.

There is a growing interest in fibers supporting optoelectrical properties for textile and wearable display applications. Solution-processed electroluminescent (EL) material systems can be continuously deposited onto fiber or yarn substrates in a roll-to-roll process, making it easy to scale manufacturing. It is important to have precise control over layer deposition to achieve uniform and reliable light emission from these EL fibers. Slot-die coating offers this control and increases the rate of EL fiber production. Here, we report a highly adaptable, cost-effective 3D printing model for developing slot dies used in automatic coating systems. The resulting slot-die coating system enables rapid, reliable production of alternating current powder-based EL (ACPEL) fibers and can be adapted for many material systems. The benefits of this system over dip-coating for roll-to-roll production of EL fibers are demonstrated in this work.

Vitamin D and iron deficiencies are the most prevalent micronutrient deficiencies among women of reproductive age (WRA) in Morocco. Recent studies suggest that Vitamin D deficiency (VDD) may reduce iron bioavailability necessary for erythropoiesis, potentially leading to iron deficiency (ID) and anemia. This study investigates the association between vitamin D status, iron levels, and anemia risk among Moroccan WRA aged 18-49 years. A cross-sectional study was conducted with 463 participants. Serum levels of 25(OH)D, blood count parameters, iron, ferritin, C-reactive protein, and creatinine were measured. Lifestyle factors, including dietary intake, sun exposure, and physical activity, were evaluated using validated questionnaires, and anthropometric data were collected. Linear and logistic regression models assessed the relationships between variables, while Receiver Operating Characteristic (ROC) curve analysis evaluated the predictive accuracy of VDD for ID and anemia. VDD (25(OH)D &lt; 20 ng/ml) was significantly associated with lower levels of hemoglobin, hematocrit, red blood cells, and ferritin (all p &lt; 0.01), suggesting a role of vitamin D in erythropoiesis and iron storage. Multivariate logistic regression showed that VDD increased the risk of anemia (OR: 7.17, 95% CI: 3.19-19.28, p &lt; 0.001), ID (OR: 2.20, 95% CI: 1.32-3.77, p = 0.007), and IDA (OR: 4.10, 95% CI: 1.73-12.08, p = 0.004). Dietary iron intake was inadequate among all participants, with minimal protective effect against anemia and ID (β(SE): -0.08(0.03), p = 0.030 and β(SE): -0.05(0.02), p=0.037 respectively). ROC analysis demonstrated moderate discriminative power for VDD in diagnosing IDA and anemia (AUC: 0.643 and 0.603) but reduced accuracy for ID (AUC: 0.575). This study identifies VDD as a significant risk factor for impaired iron status and anemia among Moroccan WRA, underscoring the need for targeted nutritional interventions and further research to explore effective prevention strategies.

The ever-evolving ways attacker continues to im prove their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack. Thus, current anti-phishing methods remain vulnerable to complex phishing because of the increasingly sophistication tactics adopted by attacker coupled with the rate at which new tactics are being developed to evade detection. In this research, we proposed an adaptable framework that combines Deep learning and Randon Forest to read images, synthesize speech from deep-fake videos, and natural language processing at various predictions layered to significantly increase the performance of machine learning models for phishing attack detection.

Shale gas production is associated with significant usage of fresh water and discharge of wastewater. Consequently, there is a necessity to create the proper management strategies for water resources in shale gas production and to integrate conventional energy sources (e.g., shale gas) with renewables (e.g., solar energy). The objective of this study is to develop a design framework for integrating water and energy systems including multiple energy sources, cogeneration process, and desalination technologies in treating wastewater and providing fresh water for shale gas production. Solar energy is included to provide thermal power directly to a multi-effect distillation plant (MED) exclusively (to be more feasible economically) or indirect supply through a thermal energy storage system. Thus, MED is driven by direct or indirect solar energy, and excess or direct cogeneration process heat. The proposed thermal energy storage along with the fossil fuel boiler will allow for the dual-purpose system to operate at steady-state by managing the dynamic variability of solar energy. Additionally, electric production is considered to supply a reverse osmosis plant (RO) without connecting to the local electric grid. A multi-period mixed integer nonlinear program (MINLP) is developed and applied to discretize operation period to track the diurnal fluctuations of solar energy. The solution of the optimization program determines the optimal mix of solar energy, thermal storage, and fossil fuel to attain the maximum annual profit of the entire system. A case study is solved for water treatment and energy management for Eagle Ford Basin in Texas.

The capacitated team orienteering problem with time windows (CTOPTW) is a NP-hard combinatorial optimization problem. In the CTOPTW, a set of customers is given each with a profit, a demand, a service time and a time window. A homogeneous fleet of vehicles is available for serving customers and collecting their associated profits. Each vehicle is constrained by a maximum tour duration and a limited capacity. The CTOPTW is concerned with the determination of a preset number of vehicle tours that begin and end at a depot, visit each customer no more than once while satisfying the time duration, time window and vehicle capacity constraints on each tour. The objective is to maximize the total profit collected. In this study we propose an iterated local search (ILS) algorithm to deal with the CTOPTW. ILS is a single solution based meta-heuristic that successively invokes a local search procedure to explore the solution space. A perturbation operator is used to modify the current local optimum solution in order to provide a starting solution for the local search procedure. As different problems and instances have different characteristics, the success of the ILS is highly dependent on the local search procedure, the perturbation operator(s) and the perturbation strength. The basic ILS uses a single perturbation operator and the perturbation strength remains the same during the optimization process. To address these issues, we use three different perturbation operators and a varying perturbation strength which changes as the algorithm progresses. The idea is to assign a larger perturbation strength in the early stages of the search in order to focus on exploring the search space. The perturbation strength is gradually decreased so that we focus more on exploitation. The computational results show that the proposed ILS algorithm is able to generate high quality solutions on the CTOPTW benchmark instances taken from the scientific literature, demonstrating its efficiency in terms of both the solution quality and computational time. Moreover, the proposed ILS produces 21 best known results and 5 new best solutions.

The deployment of Artificial Intelligence (AI) systems in decentralized environments is on the rise, yet representation of shared conceptualization in such scenarios remains a challenging issue. The absence of a shared understanding can lead to suboptimal performance of AI systems and hinders the ability to comprehend the knowledge and beliefs of agents in the domain. This paper proposes a formal model for modeling conceptualization in AI systems that integrates ontology, epistemology, and epistemic logic. The model aims to address the gap in representing shared conceptualization in decentralized environments and enhance the performance of AI systems operating in such environments. The proposed model is a hybrid structure that blends extensional and intensional structures and leverages logic-based languages for modeling purposes. A case study in the healthcare sector is presented to illustrate the application of the proposed model. The study contributes to the existing literature by providing a formal model for representing shared conceptualization in decentralized environments, which can be utilized to optimize the performance of AI systems in these environments.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, the imperative of employing natural antioxidants becomes apparent. In this study, we delve into the antioxidant and hepato-protective properties of Pistacia lentiscus against 7,12-dimethylbenz(a)anthracene-induced toxicity, alongside exploring its potential anticancer attributes. Our investigations unveil Pistacia lentiscus's anti-proliferative efficacy against human breast cancer cell lines. Notably, 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed-group compared to controls (p&lt;0.05). Nonetheless, Pistacia lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces Pistacia lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Our findings underscore Pistacia lentiscus's robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene-induced mammary cancer initiation. We posit that Pistacia lentiscus may serve as a prophylactic agent against breast cancer instigated by this carcinogen.

This study presents a novel technique utilizing high frequency vibration to shorten treatment time and preserve alveolar bone in challenging orthodontic cases treated with Invisalign® clear aligners. Four non-growing orthodontic patients (age range 14-47 years old) with Class II skeletal patterns (convex profiles with retrognathic mandibles) who sought correction of their crowded teeth and non-surgical correction of their convex profiles were included in this study. These patients were treated using Invisalign clear aligners together with high frequency vibration (HFV) devices (120 Hz) (VPro5™) that were used by all patients for five minutes per day during active orthodontic treatment. Vertical control and forward rotation of the mandible for each patient was achieved through pre-programming the Invisalign to produce posterior teeth intrusion. Successful forward rotation of the mandibles achieved in all patients led to improvement of their facial convex profiles (ANB improved 2.1 + 0.5 degrees; FMA improved 1.2 +1.1 degrees). Dental decompensation was achieved by lingual tipping of the lower incisors and palatal root torque of upper incisors. The use of HFV together with Invisalign facilitated achieving these results within a 12+6 month period. In addition, more bone labial to the lower incisors after their lingual movement was noted. In conclusion, the use of HFV concurrent with SmartTrack Invisalign aligners allowed complex tooth movement and forward projection without surgery in non-growing patients with skeletal Class II relationships. The clinical impact and implications of this case series is that the use of HFV facilitates complex orthodontic tooth movement including posterior teeth intrusion and incisor decompensation in addition to increased bone formation labial to lower incisors that may minimize future gum recession due to their labial inclination.

Self-compacting concrete (SCC) production is a complex operation that requires finding a good combination and a suitable dosage of each of its constituents. Several formulation methods have been developed to meet the workability requirements of SCC. In this paper, the relationships between the fresh properties of SCC based on local metakaolin (MK) and the spreading of its mortar was investigated. The results showed the existence of good correlations between the spreading of the mortar and the fresh state properties of the related SCC and that the MK substitution rate did not affect these correlations. The choice of the mortar flow rate should target appropriate fresh properties of the SCC and a viscosity enhancing agent (VEA) could be used if the mix is too fluid and present an instability.

Pruning is an important part in controlling the branching, good fruit size, and prodctivity of fruit trees. and consequently, ‘Valencia’ orange trees were grown many years ago, the trees were suffering from a decline in productivity in the newly reclaimed lands after certain years of plantation. This study elucidated the effect of pruning severity on growth, yield and fruit quality of ‘Valencia’ orange trees. Four levels of pruning were applied on 35 years old ‘Valencia’ orange trees as follows: T1: Control (un-pruned), T2: Light pruning ( 25% of main branches were removed); T3: Moderate pruning (50% of main branches were removed) and T4: Heavy pruning: 75% of main branches were removed. The treatments were done in February 15th (for each season). The results indicated that pruning severity increased vegetative growth paraments such as shoot length and leaf area and decreased canopy volume of Valencia orange trees in comparison to control. Maximum yield was gained from 75% followed by 50% and 25% pruning severity treatment. The pruning treatments improve in fruit weight, size, firmness, juice content, TSS%, TSS/acid ratio and vitamin C content. In addition, pruning produced an increasing in fruit yield per tree as well as yield increasing %. Hence, it might be concluded that pruning at different severity applied in February can be used effectively on ‘Valencia’ orange trees to improve vegetative growth, fruit physical and chemical properties. Besides, increasing fruit yield by nearly 20% in comparison to control.

El Olivo Cave (Pruvia de Arriba, Llanera, Asturias, Spain) is a small karst cave located in the Aboño River basin and formed in the Cretaceous limestone of the Mesozoic cover of the Cantabrian Mountains (north of the Iberian Peninsula). It contains an important upper Pleistocene sedimen-tary, archaeological and paleontological record, with abundant technological evidence and faunal remains. The archaeological record shows a first occupation that could correspond to the Middle Paleolithic and a second occupation in the Middle Magdalenian. The stratigraphic sequence inside and outside the cave was studied with geoarchaeological methodology. In this paper, the lithostratigraphic sequence is analyzed and the data from the granulometric, mineralogical, edaphological and radiometric analyses are presented. The results of these analyses enable an accurate interpretation of both the lithostratigraphy of the deposit as well as the processes re-sponsible for its formation and subsequent evolution. The available numerical dates allow us to locate the first sedimentation episode in the cave in OIS 7a, in the Middle Pleistocene, the base of the outer fluvial sedimentation in the cold OIS 3a stage of the Upper Pleistocene and the Magdalenian occupation in the Last Glacial Maximum (OIS 2) at the end of the Late Pleistocene.

The emergence of few-shot learning as a potential approach to address the problem of data scarcity by learning underlying pattern from a few training sample had so far given a mix-result especially on the suitability of model-agnostic meta learning, transfer learning, and optimization strategy to rapidly learn valid information from few sample. In this research, we did an in-depth evaluation of meta- learning to determine their plausibility and suitability for previously unknown cyberattack detection by first retrieving the original research artifacts of current state of the art meta learning to repeat the experiment with original dataset before replicating the experiment with two different malware dataset which had not been previously done with meta-transfer learning. On each of the experiments, meta-transfer learning gave good results on digital character recognition dataset but abysmal result on Malimg and Malevis malware images datasets thereby indicating its unreliability for detecting cyberattacks and the need for an improvement to the state-of-the-art meta transfer learning towards a better attack detection. Transfer learning performance is independent on imbalance and hence does not influence its performance since both malware dataset used for this experiment result in high validation loss and balancing the dataset doesn't result in reduced validation loss,the successful learning transfer seen on digital character recognition dataset is not unconnected to the fact that several languages have similar characters and digits thereby enhancing the successful learning transfer unlike malware datasets, and more importantly the finding that current meta-learning transfer approach doesn't generalize well on malware dataset and hence not suitable for detecting previously unseen out-of-distribution attack.

Reaction of 2-mercapto-3-phenylquinazolin-4(3H)-one (MPQ) with both 4-vinyl benzyl chloride and allyl bromide furnished the reactive heterocyclic monomers 3-phenyl-2-((4-vinylbenzyl) thio) quinazolin-4(3H)-one (PVTQ) and 2-(allylthio)-3-phenylquinazolin-4(3H)-one (APQ), respectively. Copolymerization of PVTQ monomer with styrene and methyl methacrylate in the presence of 2,2′-azobisisobutyronitrile (AIBN) afforded the copolymers PS-co-PPVTQ and PMMA-co-PPVTQ, respectively. Similarly, copolymerization of monomer APQ with styrene and methyl methacrylate (MMA) afforded the copolymers PS-co-PAPQ and PMMA-co-PAPQ, respectively. The resulted copolymers were characterized by using FT-IR, 1H-NMR and GPC techniques. Silver nanocomposites of PS, PMMA, PS-co-PPVTQ, PMMA-co-PPVTQ, PS-co-PAPQ and PMMA-co-PAPQ were synthesized by the addition of silver nitrate into the polymer solution. The reduction of silver ions into silver nanoparticles was performed in DMF and water. Thermogravimetric (TGA) analysis was used to determine the thermal stability of the copolymers and their silver nanocomposites. The X-ray diffraction (XRD) analysis indicated the amorphous structures of the co-polymers and confirmed the formation of silver nanoparticles. The antitumor and antibacterial activities were screened for the copolymers and enhanced by the formation of their silver nanocomposites. In vivo antitumor activity in Ehrlich Ascitic Carcinoma (EAC) mice model showed that PS-co-PPVTQ/Ag NPs, PMMA-co-PPVTQ/Ag NPs, and PMMA-co-PAPQ/Ag NPs displayed promising inhibitory effects against EAC and induce apoptosis against MCF-7 cells.

Indole derivatives are key components of natural products and possesses a wide range of biological and pharmaceutical applications. Here we present the synthesis of a new indole derivative namely 2-(1-ethyl-5-nitro-1H-indole-7-carbonyl) butyl 4-methylbenzenesulfonate (5). The structural elucidation of 5 was accomplished through comprehensive spectroscopic analysis, including Fourier-transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), and high-resolution mass spectrometry (HRMS). Our molecular docking study revealed that compound 5 exhibits strong affinity towards Tyrosinase, making it a promising candidate as an antioxidant agent. Keywords: Indole derivative; Tosyl group; Molecular docking; Antioxidant agent.

Interval-valued functions have been widely used to accommodate data inexactness in optimization and decision theory. In this paper, we study interval-valued vector optimization problems, and derive their relationships to interval variational inequality problems, of both Stampacchia and Minty types. Using the concept of interval approximate convexity, we establish necessary and sufficient optimality conditions for local strong quasi and approximate $LU$-efficient solutions to nonsmooth optimization problems with interval-valued multiobjective functions.

In the last few decades, a lot has been written on the use of sustainable agriculture to improve ecosystem services for resilience to climate change. However, no tangible and systematic evidence exists on how this would participate in alleviating impacts on vulnerable rural communities. This paper provides a narrative systematic review (SR) integrated with a bibliometric analysis and a concept network analysis to understand how, in a changing climate, sustainable agriculture builds the resilience of agro-systems. The search was set from the date of the first relevant article until the end of 2018. Results generated have demonstrated that: a. Only single practices and methods have been studied to assess impacts on single ecosystem services. b. Soil quality and health are considered a key indicator of sustainable agriculture. c. Albeit the assessed practices and methods have shown to improve the biodiversity of agro-systems, which makes them more resilient to extreme climate events, we are still far from reaching interdisciplinary and multi-dimensional agriculture which integrates all management aspects and generates a full range of ecosystem services. In conclusion, the study addressed the following recommendations for the scientific community and for decision-makers to orient future research strategies and efforts: a. Integration of all agro-systems services into sustainable management using an ecosystem-based approach on a life-cycle basis using Life Cycle Assessment (LCA) method; b. Improving the scientific understanding of traditional knowledge for higher synergies and for further integration; c. Unification of assessment methods and indicators for the quantification of impacts; d. Creation of a platform to share, monitor, screen, and approve assessments and evaluations of sustainable agriculture by region.

Since the 1950s sugarcane production has grown rapidly from less than 0.5 billion tonnes in the late 50s to reach over 1.9 billion tonnes in 2012 on about 27 million hectares of agricultural land. This expansion has been boosted by the high demand for bioethanol promoted as a sustainable bioenergy source which accounted in 2010 for the biggest share of the global biofuel market. Despite its benefits, the scientific debate on sugar is growing especially that counterarguments are so many, including negative impacts on different interacting ecosystems and human well-being, e.g. bigger stress on land and water resources, environmental externalities on air, a harmful impact on the biodiversity and endemic species, negative environmental externalities, health, and socio-economic aspects. This paper provides a narrative systematic review (SR) of the impacts of sugarcane production on these different ecosystems employing the ecosystem services framework for its acceptance by policy-makers. The references included for the SR were 163 and results showed that the majority of the studies are from Brazil, Australia, South Africa and the USA (≈ 75% of the literature), most of them were from peer-reviewed journals (85%), and most of the case studies adopted a quantitative research approach (93%). The literature assessed showed that sugarcane, like all agro-systems, depends on the practices and techniques to transform negative impacts into positive externalities on ecosystems and human well-being. However, the literature studied failed to include the inter-linkage in sugarcane production impacts’ and therefore to evaluate the related ecosystem services with respect to the Millennium Ecosystem Assessment (MA) framework to account for existing trade-offs. Therefore, the findings are addressed to the scientific community and decision-maker for an intensification of interdisciplinary and integrated research based on the MA framework to cover all ecosystem services, for sustainable development of the sugarcane sector.

In Ecuador, particularly in the El Oro province, gold mining has been historically hampered by arsenic contamination in the ores. This research addresses the persistent issue of arsenic in gold-bearing ores from Miraflores Mine in Cerro Azul, Atahualpa Canton, and the challenges it presents to mining operations. The study's purpose is to evaluate the effectiveness of an alkaline leaching process for arsenic removal. The ore underwent thorough characterisation, employing advanced techniques like fire assay and atomic absorption. Once the ore's nature was discerned, an arsenic extraction experiment using a leaching solution was conducted. The implemented process achieved an arsenic removal efficiency of 90.54%. This enhanced ore quality facilitates efficient metallurgical applications and, more notably, reduces the environmental footprint by diminishing the need for harmful reagents like sodium cyanide. However, a significant implication of this method is the added cost due to the need for heat during the leaching test, amounting to an approximate $30 per ton increase. The alkaline leaching process emerges as a promising solution for arsenic challenges in El Oro’s mining sector. While the findings are encouraging, further expansive tests are recommended to validate the results and underscore the urgency for sustainable and hazard-conscious mining practices.

The resonance spectra of neutral silver indicate self-absorption for the studied Ag I lines at the wavelengths of 327.9 nm and 338.2 nm. The center dip is associated with self-reversal due to self-absorption in the plasma. The Q-switched radiation of 355 nm, 532 nm, or 1064 nm from a Nd:YAG laser device generates the plasma at the surface of silver nano-material targets, with experiments conducted in standard ambient temperature and pressure laboratory air. Procedures for recovery of the spectral line shapes confirm that over and above the effects of self-reversal, line shape distortion are important in the analysis. The work discusses parameters describing self-absorption when using fluence levels of 2 to 33 J/cm² to generate the plasma. Furthermore, subsidiary calibration efforts that utilize the hydrogen alpha line of the Balmer series show that the Ag I lines at 827.35 nm and 768.7 nm are optically thin.

Background: The present study was carried out to evaluate the roles of proliferation and angiogenesis in locally aggressive biologic behavior of ameloblastoma versus ameloblastic fibroma; Methods: 30 formalin-fixed paraffin embedded blocks (15 cases of ameloblastoma & 15 cases of ameloblastic fibroma) were used. To evaluate the proliferation, the tissue sections were stained with AgNORs stain. CD105 was used as immunohistochemical marker of angiogenesis. Quantitative evaluations of AgNORs were performed. The mean vascular density was evaluated as a measure for CD105 protein expression by using image analyzer computer system; Results: The mean number of AgNORs dots per nucleus was significantly higher in ameloblastoma as compared to ameloblastic fibroma. Also, the protein level of CD105 showed positive expression and wide distribution that the mean vascular density was significantly higher in ameloblastoma as compared to ameloblastic fibroma; Conclusion: Quantitative evaluation of AgNORs stain & the mean vascular density utilizing CD105 protein expression may reflect a higher proliferative activity and a more locally aggressive biologic behavior of ameloblastoma when compared to ameloblastic fibroma, that other factors may be involved in biologic behavior of ameloblastic fibroma.

As bread is the most consumed food by Tunisian population and the major source of salt, a pilot experience of salt reduction in bread has already begun in Bizerte city. Salt analysis in bread collected from Bizerte city was realized with Volhard titration method. Application of the “salt reduction programme” allowed a gradual decrease of salt content in bread by 35 % during three years without detection by Tunisian consumers. A final salt concentration of 1.1 ± 0.1 g/100 g was then achieved. The establishment of an effective salt reduction strategy with lifestyle education is needed to reduce hypertension that is the first cause of death in Tunisia.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

The human gastrointestinal tract is inhabited by trillions of commensal bacteria collectively known as the gut microbiota. Our recognition of the significance of the complex interaction between the microbiota, and its host has grown dramatically over the past years. A balanced microbial community is a key regulator of the immune response, and metabolism of dietary components, which in turn, modulates several brain processes impacting mood and behavior. Consequently, it is likely that disruptions within the composition of the microbiota would remotely affect the mental state of the host. Here, we discuss how intestinal bacteria and their metabolites can orchestrate gut-associated neuroimmune mechanisms that influence mood and behavior leading to depression. In particular, we focus on microbiota-triggered gut inflammation and its implications in shifting the tryptophan metabolism towards kynurenine biosynthesis while disrupting the serotonergic signaling. We further investigate the gaps to be bridged in this exciting field of research in order to clarify our understanding of the multifaceted crosstalk in the microbiota-gut-brain interphase, bringing about a novel microbiota-targeted therapeutics for mental illnesses.

The use of antibiotics as growth promotors or for the prevention of some poultry diseases has face global concern and serious criticism. Their addition to poultry feed show hazardous effects including development of antimicrobial resistance and the potential harmful effect on humans’ health. To eliminate these threats, there is increasing interest to search for natural alternatives. Plant derivatives such as garlic (Allium sativum L.) and its derivatives are nowadays extensively used in poultry production system. Dietary supplementation of broilers and layers with garlic induced improvement of production parameters, carcass quality, and intestinal integrity. Modulation of the immune response against important viral diseases and increasing the immune organs body weight ratio resulting from supplementation of poultry with garlic. Moreover, garlic showed modulation of gut health through the antibacterial and antiparasitic activities. Treatment with garlic also can mitigate the oxidative stress and reduce the free radicals production. Reduction of cholesterol level, but improvement of some liver and blood parameters were also reported following dietary inoculation of garlic. This review was designed to search on the impact of garlic as feed additives on performance, immunity, gut health, antioxidant status, and blood parameters of poultry.

N-shot learning has emerge in recent year as potential learning approach to solve the problem of data scarcity by learning underlying pattern from a few training sample. Despite recent state-of-the-art research on model-agnostic metal learning, transfer learning, and optimization strategy to rapidly learn valid information from few sample, there remains a big challenge on an actual out-of-distribution zero-day without any similarity to previously known malware family or new variant of an existing malware family. This ultimately questions the effectiveness of current state-of-the-art few-shot learning approach. In this research, we did an in-depth investigation into the performance of state-of-the-art Zero-shot, Single-shot, and few-shot learning approaches on zero-day out-of-distribution malware attack detection based on their static properties using Malimg and Malevis malware dataset. We ensure our model was aware of an out-of-distribution class during training while varying the number of samples in the out-of-distribution class accordingly zero-shot(no sample), single-shot (1 sample), few-shot(5 samples) while using confusion matrix to get the actual number of correct prediction on out-of-distribution malware validation samples. we assert that the model should be smart enough to detect and classify previously unseen data into an empty family as an out-of-distribution considering that the model was made to be aware of the existence of such distribution during training. Result shows 0, 0, and 3 correct out-of-distribution predictions on Zero-shot, single-shot, and few-shot experiments respectively, thereby showing limitation of the current state-of-the-art N-shot approaches on out-of-distribution attack.

Reactive oxygen species (ROS) are intermediates in oxidation-reduction reactions with the capacity to modify biomolecules and temporarily or permanently alter cell behaviour through signalling pathways under physiological and pathophysiological conditions where there is an imbalance between oxidative factors and the antioxidant response of the organism, a phenomenon known as oxidative stress. Evidence suggests that differential modulation of ROS-mediated oxidative stress occurs in the pathogenesis and progression of melanoma, and that this imbalance in redox homeostasis appears to be functionally linked to microRNA-mediated non-mutational epigenetic reprogramming involving genes and transcription factors. The relationship between ROS-mediated stress control, tumour microenvironment and microRNAs expression in melanoma is not fully understood. The aim of this review is to analyze the involvement of miRNAs in the modulation of signalling pathways involved in ROS-mediated oxidative stress in melanoma. It is hoped that these considerations will contribute to the understanding of the mechanisms associated with a potential epigenetic network regulation, where the modulation of oxidative stress is consolidated as a common factor in melanoma and therefore a potential footprint poorly documented.

Although vitamin D deficiency has been correlated with an increased risk of cardiovascular disease (CVD), there are few data on the association between 25-hydroxyvitamin D (25(OH) D) and atherogenic indices predictive of CVD. This study aimed to investigate the relationship of vitamin D status with lipid profile and atherogenic indices in adult women in Morocco. Three hundred healthy women, aged 18 to 50 years, from Meknes were included. Fasting 25(OH) D and lipid concentrations were determined using a one-step electrochemiluminescence-based immunoassay and an enzymatic method, respectively. Atherogenic indices (Atherogenic index of plasma (AIP), non-HDL cholesterol (Non-HDL-C), Atherogenic coefficient (AC), Castelli risk indices I and II (CRI-I and II), and CHOLIndex (CI)) were calculated using conventional lipid parameters. Logistic regression models and operating characteristic curve (ROC) analysis were used to assess the relationship of the variables and estimate the threshold of 25(OH) D levels associated with high atherogenic indices. 25(OH) D below 20 ng/ml was significantly associated with an enhanced risk of hypertriglyceridemia and elevated values of AIP, AC, Non-HDL-C, and CRI-I with an OR (95% CI) of 4.904 (1.856-12.959); 3.637(2.149-6.158); 3.589(1.673-7.700); 2.074(1.215-3.540), and 2.481(1.481-4.123), respectively. According to ROC analysis, the likelihood of hypertriglyceridemia and high values of AIP, AC, Non-HDL-C, and CRI-I were associated with 25(OH)D thresholds ≤15.15 ng/ml, ≤ 17.5 ng/ml, ≤ 19.8 ng/ml, ≤ 20.1 ng/ml and ≤ 19.5 ng/ml, respectively, all p &lt; 0.01. Based on atherogenic indices, this study indicates that vitamin D below 20 ng/ml may increase the risk of cardiovascular disease in adult women. Additional health efforts are needed to raise awareness among women and healthcare providers in preventing and controlling cardiovascular risk factors.

Background: Diabetes mellitus (DM) and periodontitis are two chronic diseases that are interconnected. The coexistence of these conditions leads to increased severity of periodontitis and challenges in controlling blood glucose levels in diabetic patients. Objectives: The aim of this study was to evaluate both the influence of periodontal disease and its treatment in patients with DM in terms of a reduction in glycosylated hemoglobin levels at 3 and 6 months after treatment. Methods: A sequential, nonprobabilistic, controlled, prospective and longitudinal case−control study was carried out at the University Dental Clinic of the Morales Meseguer Hospital in Murcia, Spain. Thirty diabetic patients were divided into two groups: patients with periodontitis (test group) and patients without periodontitis (control group). The periodontal and endocrine-metabolic variables were measured at baseline and at 3 and 6 months after periodontal treatment for both groups. Results: Statistically significant differences were found at 3 and 6 months after periodontal treatment with respect to HbA1c levels in the group of periodontal patients. However, these differences were not observed in the control group. Conclusion: The presence of periodontal disease increased HbA1c levels in patients with DM. Nonsurgical periodontal treatment significantly decreased the degree of periodontal inflammation and the HbA1c level at 3 and 6 months after treatment.

Background The distinctive feature of liver fibrosis is the progressive replacement of healthy hepatic cells by extracellular matrix protein, which is abundant in collagen I and III with impaired matrix remodelling. The activation of myofibroblastic cells enhances a fibrogenic response of complex interactions of hepatic stellate cells, fibroblasts and inflammatory cells to produce excessive deposition of extracellular protein matrix. This process is activated by multiple fibrogenic mediators and cytokines such as TNF-α and IL-1ß with decrease in the anti-fibrogenic factor NF-ҡß. Mesenchymal stem cells (MSCs) represent a promising therapy for liver fibrosis giving more advanced regenerative influence when cultured with extrinsic or intrinsic proliferative factors, cytokines, anti-oxidants, growth factors, and hormones such as Melatonin (MT). However, previous studies showed conflicted findings concerning the therapeutic effects of adipose (AD) and bone marrow (BM)-MSCs, therefore, the present work aimed to accomplish a comparative and comprehensive study investigating the impact of MT pre-treatment on the immunomodulatory, anti-inflammatory and anti-apoptotic effects of AD and BM-MSCs and to critically analyse whether MT pre-treated both AD-MSCs and BM-MSCs reveal equal or different therapeutic and regenerative potentials in CCl4-injured liver of experimental rat models. Materials and methods Six groups of experimental rats were used with ten rats in each group; group I (control group), group II (CCl4-treated group), group III (CCl4 and BM-MSCs treated group), group IV (CCl4 and MT pre-treated BM-MSCs group), group V (CCl4 and AD-MSCs treated group) and group VI (CCl4 and MT pre-treated AD-MSCs group). Liver function tests, gene expression of inflammatory, fibrogenic, apoptotic and proliferative factors were analysed. Histological and immunohistochemical changes were assessed. Results The present study compared the capability of AD and BM-MSCs, with and without the pre-treatment of MT, to reduce hepatic fibrosis. Both types of MSCs improved hepatocyte function by reducing the serum levels of (ALT), aspartate aminotransferase (AST), alkaline phosphatase (AKP), and total bilirubin (TBIL). In addition, the changes in the hepatocellular architecture including the hepatocytes, liver sinusoids, central veins, portal veins, biliary ducts and hepatic arteries showed decrease hepatocyte injury and cholestasis with reduction of inflammation, apoptosis and necrosis of the hepatic cells together with inhibition of liver tissue fibrosis. These results were augmented by the analysis of the expression of the anti-inflammatory cytokines TNFα and IL-1β, the anti-fibrogenic factor NF-ҡß, the apoptotic factor caspase-3 and the proliferative indicators antigen Ki-67 and proliferating cell nuclear antigen (PCNA). These findings were found statistically significant, with the best results in the rats received AD-MSCs pre-treated with MT, denoting better regenerative and therapeutic effects. Conclusion AD-MSCs, pre-treated with MT, are superior to BM-MSCs due to their better efficacy in improving hepatic fibrosis and promoting the therapeutic and regenerative capability of liver tissue. They represent a very significant tool for future stem cell use in tissue regeneration strategy for the treatment of liver diseases.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, liver damage can be found and the imperative of employing natural antioxidants becomes apparent. In this study, we first showed that 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed group compared to controls (p&lt;0.05). Interestingly, P.lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces P.lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Furthermore, our investigations unveil P.lentiscus’s anti-proliferative efficacy against different human breast cancer cell lines. Thus, our findings underscore P.lentiscus‘s robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene induced mammary cancer initiation. We posit that P.lentiscus may serve as a prophylactic agent against breast cancer and liver oxidative damage instigated by this carcinogen.

The central reason behind emergence of clinically-detectable tumors is evasion from immune surveillance due to lack of cancer cells surface membrane expression of tumor-specific peptides in association with MHC class I molecules, concealment of natural killer cells-activating molecules, and absence of inflammation resulting from inefficient stimulation of innate immunity receptors and co-stimulatory molecules. The tumor microenvironment (TME) also contributes to tumor initiation, progression and resistance to therapeutic interventions because of its dense, fibrogenic, barrier-like composition, aberrant vasculature, and production of cytokines and chemokines responsible for recruitment of immune suppressive cells, notably myeloid-derived suppressor cells, M2 macrophages, regulatory T cells, extracellular trap-forming neutrophils, and cancer-associated fibroblasts. We herein show that the relentless efforts and strategies to overcome the TME elusive tumor-promoting impact produced contrasting, opposed, controversial effects, characterized by limited efficacy and proven adversity, and most importantly deterred from attempts to discover and counteract the fundamental inherent mechanisms initiating, and not consequent to, carcinogenesis.

Salinity is the most significant abiotic stress affecting crop yield worldwide, breeders are Salinity is the most important abiotic stress limiting crop production throughout the world, and breeders are encouraged to test novel genotypes for their resistance to this selection agent. However, getting a sufficient number of plants for the evaluation can be a lengthy and time-consuming procedure that might be shortened by applying in vitro techniques. An experiment was conducted under controlled saline circumstances using a tissue culture technique to investigate the influence of salt on several physic-biochemical parameters. Micro-shoots of Volkamariana lemon, sour orange, trifoliate orange, and Cleopatra mandarin rootstocks were re-cultured on MS media supplemented with NaCl from 25, up to 150 mM. Following the experiments, all of the tested rootstocks' morphological and biochemical characteristics, stomata behavior, and element accumulation were measured. As a result, adding NaCl from 25 to 150 mM to MS media caused a reduction in all morphogenetic parameters such as shoot number, shoot length, leaves number, and survival percentage was measured compared with control. Photosynthesis pigment, RWC, K, and Ca ions were decreased by increasing NaCl from 100 to 150 mM. On the contrary, proline, Cl, and Na were increased. Cleopatra mandarin and Trifoliate orange are more tolerant to salt stress than Volkamariana lemon and sour orange citrus.

The objective of this research was to analyze the evolution and trend of the generation gap and nursing education from 1968 to 2021 through bibliometric indicators. The method used is a bibliometric, descriptive and retrospective study of documents in Scopus, with descriptors “Nursing educat*”, “generation* and the Boolean operator “AND”, N= 653 web documents from 1968 to 2021, and filters of the type bib, csv. The search was carried out on October 9, 2021, using the Bibliometrix R Package software and the Biblioshiny tool. The Results indicate high scientific production in 2020 (54 articles disclosed). This study demonstrates patterns and lines of research in nursing education, such as educational models, interpersonal relationships, and organizational innovation.

Q-switched laser radiation at wavelengths of 355 nm, 532 nm, and 1064 nm from a Nd: YAG laser was used to generate plasma in laboratory air at the target surface made of compressed nano-silver particles of size 95 ± 10 nm. The emitted resonance spectra from the neutral silver at wavelengths of 327.9 nm and 338.2 nm indicate existence of self-reversal in addition to plasma self-absorption. Both lines were identified in emission spectra at different laser irradiation wavelengths with characteristic dips at the un-shifted central wavelengths. These dips are usually associated with self-reversal. Under similar conditions, plasmas at the corresponding bulk silver target were generated. The recorded emission spectra were compared to those obtained from the nano-material target. The comparisons confirm existence of self-reversal of resonance lines that emerge from plasmas produced at nano-material targets. This work suggests a method for recovery of the spectral line shapes and discusses practical examples. In addition, subsidiary calibration efforts that utilize the Balmer series Hα-line reveal that other Ag I lines at 827.35 nm and 768.7 nm are optically thin under variety of experimental conditions and are well-suited as reference lines for measurement of the laser plasma electron density.

This work communicates results from optical emission spectroscopy following laser-induced optical breakdown at or near nanomaterial. Selected atomic lines of silver are evaluated for consistent determination of electron density. Comparisons are presented with Balmer series hydrogen results. Of particular interest are measurements free of self-absorption effects. For several silver lines, asymmetries are observed in the recorded line profiles. Electron densities of interest range from 0.5 to 3 × 10¹⁷ cm^-3, for 5 nanosecond Q-switched Nd:YAG radiation at wavelengths of 1064, 532, and 355 nm, and for selected silver emission lines including 328.0, 338.2, 768.7, and 827.3 nm, and the hydrogen alpha Balmer series line at 656.3 nm. Line asymmetries are presented for the 328.0 nm Ag I line that is measured following generation of the plasma due to multiple photon absorption. This work explores electron density variations for different irradiance levels, and reports spectral line asymmetry of resonance lines for different laser fluence levels.

Invasive fungal infections, notably candidemia, have been associated with COVID-19. The epidemiology of candidemia has significantly changed during the COVID-19 pandemic. We aim to identify the microbiological profile, resistance rates, and outcomes of COVID-19 associated candidemia (CAC) compared to patients with candidemia not associated with COVID-19. We retrospectively collected data on patients with candidemia admitted to the American University of Beirut Medical Center between 2004 and 2022. We compared the epidemiology of candidemia during and prior to the COVID-19 pandemic. Additionally, we compared the outcomes of critically ill patients with CAC to those with candidemia without COVID-19 from March 2020 till March 2022. Among 245 candidemia episodes, 156 occurred prior to the pandemic and 89 during the pandemic. Of the latter, 39 (43.8%) were CAC, most of which (82%) were reported from intensive care units (ICU). Non-albicans Candida (NAC) spp. were predominant throughout the study period (67.7%). Candida auris infection was the most common cause of NAC spp. in CAC. C. glabrata had decreased susceptibility rates to fluconazole and caspofungin during the pandemic period (46.1% and 38.4% respectively). Mortality rate in the overall ICU population during the pandemic was 76.6%, much higher than the previously reported mortality of candidemia from previous studies at our center. There was no significant difference in 30-day mortality between CAC and non-CAC (75.0% vs 78.1%; P =0.76). Performing ophthalmic examination (P = 0.002), CVC removal during the 48 hours following the candidemia (P = 0.008) and identifying the Candida spp. (P = 0.028) were significantly associated with a lower case-fatality rate. The epidemiology of candidemia has been significantly affected by the COVID-19 pandemic at our center. Rigorous infection control measures and proper antifungal stewardship are essential to combat highly resistant species like C. auris.

The production of coffee leaf tea (Coffea arabica) in El Salvador and the influences of processing steps on non-volatile compounds and volatile aroma-active compounds were investigated. The tea was produced according to process steps of conventional tea (Camellia sinensis) with available possibilities on the farm. Influencing factors were the leaf type (old, young, yellow, shoots), processing (blending, cutting, rolling, freezing, steaming), drying (sun drying, oven drying, roasting) and fermentation (wild, yeast, Lactobacillus). Subsequently, the samples were analysed for the maximum levels of caffeine, chlorogenic acid, and epigallocatechin gallate permitted by the European Commission. The caffeine content varied between 0.37 g/100 g dry mass (DM) and 1.33 g/100 g DM, the chlorogenic acid between not detectable and 9.35 g /100 g DM and epigallocatechin gallate could not be detected at all. Furthermore, water content, essential oil, ash content, total polyphenols, total catechins, organic acids, and trigonelline were determined. Gas chromatography—mass spectrometry-olfactometry and calculating of the odour activity values (OAVs) were carried out to determine the main aroma-active compounds, which are β-ionone (honey-like, OAV 132-927), decanal (citrus-like, floral, OAV 14-301), α-ionone (floral, OAV 30-100), (E,Z)-2,6-nonadienal (cucumber-like, OAV 18-256), 2,4-nonadienal (melon-like, OAV 2-18), octanal (fruity, OAV 7-23), (E)-2 nonenal (citrus-like, OAV 1-11), hexanal (grassy, OAV 1-10), and 4-heptenal (green, OAV 1-9).

In this work, we developed a highly sensitive multiplexed immunosensor for direct simultaneous detection of both N-terminal Natriuretic Peptide (NT-proBNP) and Cortisol in human artificial saliva (AS). The developed biosensor platform based on silicon nitride was composed from four gold working microelectrodes (WEs) and an integrated counter and reference electrode. Gold WEs were biofunctionalized through carboxyl diazonium (4-APA) to immobilize both anti- NT-proBNP and anti-Cortisol antibodies for simultaneous detection. The electroaddressing of the 4-APA onto the gold WE surfaces was realized by cyclic voltammetry (CV), while the interaction between antibodies and antigens in PBS was monitored by electrochemical impedance spectroscopy (EIS). The antigen detection in human AS was realized by EIS combined with the standard addition method. The immunesensor was highly sensitive and selective toward the corresponding biomarkers in both PBS and artificial human saliva as well as in the presence of other potential interfering biomarkers such as tumor necrosis factor alpha (TNF-α) and interleukin-10 (IL-10). The limit of detection (LOD) was at 0.2pg/mL for NT-proBNP within the range 0.03 to 0.9pg/mL, while the LOD for Cortisol was 0.06 ng/mL within the range 0.02 to 0.6 ng/mL for Cortisol in artificial saliva. The developed immunosensor is very promising for significant detection time reducing as it allows the simultaneous detection of various biomarkers.

Dentinal Hypersensitivity (DH), a prevalent oral health issue affecting approximately one-third of adults. In this six-months retrospective study, a comparison was made to assess the effectiveness of two diode lasers with different wavelengths (980 nm and 1064 nm) in the treatment of tooth affected by DH. In total, 160 patients were divided into two treatment groups: one receiving treatment with a 980 nm diode laser (n=80) and the other with a 1064 nm diode laser (n=80). Pain was assessed using the Visual Analogue Scale (VAS) at baseline, immediately post-treatment, and at 3- and 6-months follow-up. Both groups followed the same treatment protocol, involving the application of a graphite paste to the exposed dentin before laser irradiation. Both lasers operated at an output power of 0.5 W in continuous and non-contact mode, with a 320 µm spot size. A significant reduction in mean VAS scores at all follow-up intervals compared to baseline was noted. 980 nm group had mean VAS scores of 7.9, 2.36, 2.31, and 2.38, while the 1064 nm group had scores of 8.01, 1.01, 1.16, and 1.13 at baseline, immediately post-treatment, and at 3 and 6 months, respectively. At all times of follow-up, the 1064 nm wavelengths showed a statistically significant reduction in mean values of VAS compared to the 980 nm. The findings may inform future research on optimizing laser-based treatments for DH.