The distribution laws of various natural and anthropogenic processes in the world around us are stochastic in nature. The development of mathematics and, in particular, of stochastic modelling allows us to study regularities in such processes. In practice, stochastic modelling finds a huge number of applications in various fields, including finance and economics. In this work, some particular applications of stochastic processes in finance are examined in the conditions of financial crisis. More specifically, Autoregressive Integrated Moving Average (ARIMA) models and Modified Ordinary Differential Equations (ODE) models, which have been previously developed by the authors to predict assets’ prices of four Bulgarian companies, are validated on a time period during the crisis. Estimated rates of return are calculated from the models for one period ahead. The errors are estimated and the models are compared. The predicted return values with each of the two approaches are used to derive optimal risk portfolios based on the Markowitz Model. The resulting portfolios are compared in terms of distribution (weights of the stocks), risk and rate of return.

With a software-defined network (SDN), the control plane is separated from the data plane, allowing the control of network flows to be easy and dynamic at the same time. While the controller, which is equipped with various control applications, is capable of analyzing a large amount of data, it may become overburdened when it is faced with a large volume of traffic. The intrusion detection system (IDS) is an example of control applications that can be used to detect intrusions. It is recommended to deploy instances of the IDS across the data plane. This will improve the processing power and detection rate and as a result reduce the load on the controller at the same time. While there is no doubt that an IDS would be beneficial for improving detection rates, installing one at each switch in the data plane would be costly. To address this issue, this paper proposes the deployment of IDS chains across the data plane. The controller directs incoming traffic via alternative paths, including the IDS chain, which increases the detection rate while avoiding overloading. In order to improve transmission efficiency, our study proposes a method of balancing the distribution of flows and assigning them to specific IDS chains. This approach minimizes the cost of flow grouping through the use of a new incoming traffic grouping technique. Our method is tested and evaluated through the use of a test bed and trace-based simulation, and has been proven to effectively reduce delays and hop counts across various traffic scenarios.

The physical properties of coal reservoirs are the main restrictions to exploration and development of CBM. The study of the physical characteristics of coal reservoirs and their controlling factors is of great significance to the safe and efficient development and utilization of CBM resources in the mining area. The Pingdingshan No. 10 coal mine was chosen for this study because of its better gas production effect at the test wells. The reservoir properties of the main coal seams of the No. 10 coal mine were tested and analyzed to comprehensively evaluate the reservoir properties. The results indicate that (1) The gas content and methane purity of the No. 4 coal seam are significantly higher than the No. 2 seam, and therefore they have better development potential than the No. 2 seam; (2) The average adsorption time of the No. 2 coal seam is less than that of the No. 4 seam, making it easier to reach the peak production capacity of CBM wells in the short term, but is not conducive to long-term stable production of CBM. The Langmuir volume of the No. 2 coal seam samples was significantly greater than for the No. 4 coal seam; however, the No. 4 coal seam contains about three times the amount of gas in the No. 2 seam; (3) All three coal seams have high porosity, which is favorable for large amounts of CBM adsorption and storage. Micropores predominate, transitional pores are less frequent, and a few mesopores occur; macropores are the least common. Samples from the No. 4 seam contained the highest proportion of micropores; (4) Organic pores were common in the all coal samples, with pore diameters not more than 30 µm, mainly concentrated between 50.5 and 1000 nm. Microfractures with aperture less than 70 nm were relatively frequent, mainly in the 50–65 nm range. A large number of the nanoscale microfractures were curved or jagged; (5) Fractures in the No. 2 and No. 4 coal seam samples with widths of 50 nm to 20 µm were more developed, and many were filled with kaolinite, quartz and other minerals; (6) The samples contained mostly layered silicate minerals (kaolinite), with hard granular minerals (quartz) next, and a very small quantity of iron-type minerals such as siderite and pyrite in dendritic form. The results of this study can provide a reference basis for the large-scale development and utilization of subsequent CBM wells.

Apraxia of speech is a persistent speech motor disorder that affects speech intelligibility. Studies on speech motor disorders with transcranial Direct Current Stimulation (tDCS) have been mostly directed to post-stroke aphasia. Only a few tDCS studies have focused on apraxia of speech or childhood apraxia of speech (CAS), and no study has investigated individuals with CAS and people with trisomy 21 (T21, Down Syndrome). This study examined the effects of tDCS combined with a motor learning task in developmental apraxia of speech co-existing with T21 (ReBEC RBR-5435x9). The accuracy of speech sound production of nonsense words (NSWs) during Rapid Syllable Transition Training (ReST) under 10 sessions of anodal tDCS (1.5 mA, 25 cm) over the Broca’s area with cathode over the contralateral region was compared to 10 sessions of sham-tDCS and 4 control sessions in a 20-year-old male individual with T21 presenting moderate-severe childhood apraxia of speech (CAS). The accuracy for NSWs production progressively improved (gain 40%) under tDCS only (sham-tDCS and control sessions showed <20% gain). A decrease in speech severity from moderate-severe to mild-moderate indicated transfer effects in speech production. The speech accuracy under tDCS was correlated with Wernicke’s area activation (P3 current source density), which in turn, was correlated with the activation of the left supramarginal gyrus and the Sylvian Parietal Temporal Junction. Repetitive bihemispheric tDCS paired with ReST may have facilitated the speech sound acquisition in a young adult with T21 and CAS, possibly by recruiting brain regions required for the phonological working memory.

Patients hospitalized with COVID-19 are at a higher risk of thrombotic events following discharge, however the role of extended thromboprophylaxis remains controversial. The purpose of this study is to evaluate current extended post-discharge thromboprophylaxis practice and its outcomes.This study was a single-center, retrospective chart review of patients within Hennepin Healthcare hospitalized with COVID-19 from April 1^st 2020 to December 31^st 2021 with increased risk of thrombotic event based on D-dimer. The primary outcome was to describe current prescribing practices based on the number of patients who were eligible and received anticoagulants on discharge. Secondary outcomes included comparing the patient’s risk for thromboembolism based on a modified International Medical Prevention Registry on Venous Thromboembolism (IMPROVE-VTE) score to the current internal prescribing practice guideline, evaluating efficacy outcomes based on new thromboembolic events, and assessing safety of extended-thromboprophylaxis using the International Society of Thrombosis and Hemostasis criteria for major bleeding within 30 days of hospitalization discharge.Of 1984 patients who were hospitalized with COVID-19 infection, 961 patients were eligible to receive thromboprophylaxis at discharge, with a total of 191 patients who received anticoagulation according to the Hennepin Healthcare practice guideline. However, using the IMPROVE-VTE score, only 206 patients qualified for post-discharge thromboprophylaxis, and 63 total patients received anticoagulation. A new thromboembolic event occurred in 20 patients (5.8%) and 14 patients (4.1%) experienced major bleeding.The Hennepin Healthcare guideline for extended thromboprophylaxis at discharge encompassed more patients compared to the IMPROVE-VTE score. The incidence of a new thromboembolic event and major bleeding were low in both groups, although venous thrombotic events occurred more in thromboprophylaxis group than in patients who did not receive anticoagulation at discharge, more clinical data are needed for a conclusion.

With the engineering system becoming more and more complex, the uncertainty factors have a more and more profound influence on the reliability and security of the engineering system. In recent years, Reliability-Based Design Optimization (RBDO) has been studied extensively in complex engineering system design. The research on reliability optimization design considering stochastic uncertainty has been comprehensive and widely used. However, the reliability optimization design considering mixed uncertainty has the disadvantages of large computation and imprecise convergence. This study proposes an RBDO method based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to overcome this challenge. In the method, PSO is used to solve the most probable point, while SA has excellent global optimization capability to acquire the global optimal solution. Finally, three examples are given to illustrate the advantages of the proposed method.

We have developed a simple, rapid, high-throughput RBD-based ELISA to assess the humoral immunity against emerging SARS-CoV-2 virus variants. The cDNAs of the his-tagged RBD proteins of the virus variants were stably engineered into HEK cells secreting the protein into the supernatant, and RBD purification was performed by Ni-chromatography and buffer exchange by membrane filtration. The simplified assay uses single dilutions of sera from finger-pricked native blood samples, purified RBD in 96-well plates, and a chromogenic dye for development. The results of this RBD-ELISA were confirmed to correlate with those of a commercial immunoassay measuring antibodies against the Wuhan strain, as well as direct virus neutralization assays assessing the cellular effects of the Wuhan and the Omicron (BA.5) variants. Here we document the applicability of this ELISA to assess the variant-specific humoral immunity in vaccinated and convalescent patients, as well as to follow the time course of selective vaccination response. This simple and rapid assay, easily modified to detect humoral immunity against emerging SARS-CoV-2 virus variants, may help to assess the level of antiviral protection after vaccination or infection.

This paper aims to search for lump waves in a spatial symmetric (2+1)-dimensional dispersive wave model. Through an ansatz on positive quadratic functions, we conduct symbolic computations with Maple to generate lump waves for the proposed nonlinear model. A line of critical points of the lump waves is computed, whose two spatial coordinates travel at constant speeds. The corresponding maximum and minimum values are evaluated in terms of the wave numbers, and interestingly, all those extreme values do not change with time, either. The last section is the conclusion.

: For a long time, atherosclerosis has been regarded as a mere lipid deposit in the blood vessels. However, in the recent years a growing body of experimental and clinical evidence have highlighted the role of inflammation and immunity as a central mechanism of disease. Moreover, in the last decade the coming of next-generation sequencing and its application to large human population has broken the barrier between inflammation and cancer. Indeed, acquired mutation in key genes related to the control of hematopoiesis and myeloproliferation have paved the way to establish the new concept of clonal hematopoiesis of indeterminate potential. This phenomenon is being considered not such “indeterminate”, but as an emerging cardiovascular risk factor. Thus, this may explain the mechanisms of myeloproliferation and inflammation in atherosclerosis. And in a bidirectional journey, it has helped to explain the extremely high cardiovascular risk in cancer survivors, in particular in myeloprolfierative neoplasm patients. A deeper understanding of these mechanisms may pave the way for the future early diagnosis and potential preemptive treatments of the leading worldwide cause of death.

Keywords: Lightning; Land Cover and Land Use; Topographic Effects, Itacaiúnas River Hydrographic Basin

Wetting of the surface area of an electrode materials as complete as possible is desirable to achieve optimum specific capacity of an electrode material. Keeping this surface area utilized even at high current densities and even when inside of pores is required for high capacitance reten¬tion. The addition of surfactants at very small concentration to aqueous supercapacitor electro¬lyte solutions has been suggested as a way to improved performance in terms of capacitance, ca¬pacitance retention at increased current density and higher stability. Effects are pronounced with car¬bon materials used in electro-chemical double layer capacitors, they are also observed with re¬dox materials. Causes of the observed improvements and mode of operation of the added surfac¬tants seem to need further investigations; they are inconclusive beyond the obvious statement of in¬creased wetting. Reported examples and the current state of understanding are reviewed.

In this study, the objective is to analyze the economic viability of municipal household solid waste (organic matter + paper) for the production of gas, coke and biofuel through the pyrolysis and distillation process. The waste was collected in the city of Belém do Pará-Brazil and pre-treated at UFPA. The analyzed fraction (organic matter + paper) was subjected to pre-treatment of drying, crushing, sieving and was subsequently subjected to proximate characterization and finally pyrolysis of the organic fraction (organic matter + paper) in a fixed bed reactor. Initially, it was necessary to review the literature and with the yields obtained by pyrolysis of the frac-tion, economic feasibility analyzes were carried out. The economic indicators for evaluating the most viable pyrolysis process were: simple payback, discounted payback, net present value (NPV), internal rate of return (IRR), and profitability index (IL). The analysis of the indicators showed the economic viability considering an analysis horizon of 10 years, of materials based on organic material and paper. The break-even point obtained was 0.96 US$/L and the minimum biofuel sales price (MFSP – “Minimum Fuel Sale Price”) obtained in this work was 1.30 US$/L. The sensitivity analysis demonstrated that material costs (organic matter + paper), bio-oil yield, total project investment and electricity, respectively, are the variables that most affect the mini-mum biofuel sales price (MFSP).

As urban populations continue to grow, efficient traffic management becomes paramount in reducing congestion, enhancing air quality, and improving overall quality of life. This study addresses the critical issue of intersection efficiency through the implementation of smart green time allocation strategies at a signalized intersection equipped with two LiDAR sensors. This research aims to investigate optimal green time allocations provided by two LiDAR sensors and analyze the LiDAR results by microsimulation in AIMSUN. The research first introduces the concept of LiDAR-equipped signalized intersections and their potential to enhance traffic control precision. Two LiDAR sensors are strategically placed at the intersection of Marlboro Pike and Brooks Dr. in Coral Hills, MD, USA to capture real-time data on vehicle and pedestrian movements. The data are then processed to generate accurate and dynamic traffic profiles, ensuring the responsiveness of the green time allocation system to varying traffic conditions.The heart of this study lies in the integration of AIMSUN microsimulation with LiDAR data. Through meticulous modeling and simulation, the research explores the optimal green allocation at morning, mid-day, and afternoon peak hours’ scenarios to comprehensively assess the impact of LiDAR-enabled dynamic signal control. The findings demonstrate that smart green time allocation, informed by real-time LiDAR data and implemented through AIMSUN microsimulation, significantly enhances intersection efficiency. By adapting signal timings to real-time traffic demands, congestion, travel times, and emissions are reduced. Furthermore, this research highlighted that the optimal green time allocation in morning, mid-day, and afternoon peak hour intervals can improve the delay time by 55.3%, 59.7%, and 55.6%, respectively.In conclusion, this paper sheds light on the potential of LiDAR technology to transform intersection management. Through a case study involving two LiDAR sensors and AIMSUN microsimulation, it reveals the tangible benefits of dynamic signal control in enhancing intersection efficiency and creating more sustainable urban environments. These findings are pivotal in advancing the discourse on modern urban traffic management and promoting data-driven solutions for the challenges of today's cities.

In recent years, the use of solid waste fillers to partially replace natural fillers in asphalt mixtures to produce high-performance asphalt mixtures has received widespread attention. However, differences in the material properties of solid waste fillers remain a problem for this recycling method. To address this issue, limestone powder in asphalt mixtures was replaced by three solid waste fillers (steel slag powder, tailings powder and calcium carbide slag powder) in this study. The chemical composition of the fillers was first characterized to assess the homogeneity of the material. Then, AC and SMA asphalt mixtures were designed and produced and characterized for wet stability. The results showed that asphalt mixtures with solid waste fillers were superior to LP asphalt mixtures in terms of resistance to water damage, and steel slag powder showed the best improvement in moisture stability of asphalt mixtures. The optimum substitution of solid waste filler for limestone filler was 25%. In addition, the moisture stability of asphalt mixture with limestone filler was significantly improved with the addition of anti-stripping agents. In contrast, the moisture stability of asphalt mixtures with solid waste filler was slightly improved. Solid waste fillers could be used in asphalt mixtures and have a similar function as the anti-stripping agent. In summary, the use of solid waste fillers to replace mineral fillers in asphalt mixtures is a reliable, value-added, recycling option.

Although information theory resolves inconsistencies (known under the form of famous enigmas) of the traditional approach of thermostatistics, its place in the corresponding literature is not what it deserves. This is interpreted as being mainly due to epistemological rather than scientific reasons: the subjectivity introduced into physics is perceived as a problem. This paper attempts to expose and clarify where exactly this subjectivity lies: in the representation of the reality and in probabilistic inference. Two aspects which have been integrated into the practice of science for a long time and which should no longer frighten anyone, but which become explicit with information theory.

With increasing demand from unmanned driving and robotics, more attention has been paid to point cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features about reflectivity of the point cloud to maximizing the use of information in point cloud. Secondly, we enhanced the distance features and raw features that we collectively refer to them as self-features of the key points in Set Abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show the enhancement method proposed in this paper has excellent performance.

A rapid synthesis of chiral sulfoxide-functionalized meta-terphenyl derivatives by a 2,5-[C4+C2] ring transformation reaction of pyrylium salts with in-situ generated enantio-merically pure .alpha.-sulfinylacetaldehydes is described. This synthetic method demonstrates for the first time the use of .alpha.-sulfinylacetaldehydes in a reaction sequence initiated by nu-cleophilic attack of pyrylium salts by .alpha.-sulfinylcarbanions to generate chiral aromatic systems. The method presented shows broad applicability starting with various methyl sulfoxides and a number of functionalized pyrylium salts, furnishing meta-terphenyls with complex substitution patterns from readily accessible starting compounds.

NUSES is a pathfinder satellite project hosting two detectors: Terzina dedicated to the study of ultra-high-energy cosmic rays (UHECRs) above 100 PeV and Zirè focused on the study of protons and electrons below 250 MeV and MeV gamma rays. This work concerns mainly the description of the Cherenkov camera, composed of SiPMs, for the Terzina telescope. Cherenkov light produced by extensive air showers induced by Ultra High Energy Cosmic Rays in the atmosphere could be detected from space, thus ensuring huge exposures. The Terzina telescope is being designed to detect such light. It has an effective area of about 0.1 m2 and an equivalent focal length of about 930 mm with a diameter of the circle containing 80% of the photons of less than 1 mm2. The photo-detection plane is composed of 2×5 SiPM arrays with 8×8 channels of 3×3 mm2 pixels each. To increase the data-taking period NUSES orbit will be sun-synchronous (with a height of about 550 km), thus allowing Terzina to point always towards the dark side of the Earth’s limb. The sun-synchronous orbit requires small distances to the poles, and as a consequence the expected dose received by the SiPMs will be 10 Gy during three year of NUSES mission. About 70% of the integral dose is delivered by the electrons and secondary gammas created in the mechanical structure and about 30% from protons. This estimation is done with the Geant4 simulation of the preliminary telescope geometry, without taking into account solar wind protons. We study the SiPM photo sensors under the irradiation received by the 50 MeV protons up to 30 Gy of total integrated dose corresponding to 9 years of the satellite operation.

Chitin/chitosan and collagen are two of the most important bioactive compounds with applications in the pharmaceutical, veterinary, nutraceutical, cosmetic, biomaterials, and other industries. When extracted from fish and shellfish non-edible parts, by-catches, and invasive species, their use contributes to a more sustainable and circular economy. The present article reviews the scientific knowledge and publication trends along the marine chitin/chitosan and collagen value-chains and assesses how researchers, industry players, and end-users can bridge the gap between scientific understanding and industrial applications. Overall, research on chitin/chitosan remains focused on the compound itself rather than its market applications. Still, chitin/chitosan use is expected to increase in food and biomedical applications, while that of collagen is expected to increase in biomedical, cosmetic, pharmaceutical, and nutritional applications. Sustainable practices, such as the reuse of waste materials, contribute to strengthen both value-chains; the identified weaknesses include the lack of studies considering market trends, social sustainability, and profitability, as well as insufficient examination of intellectual property rights. Government regulations, market demand, consumer preferences, technological advancements, environmental challenges, and legal frameworks play significant roles in shaping both value-chains. Addressing these factors is crucial for seizing opportunities, fostering sustainability, complying with regulations, and maintaining competitiveness in these constantly evolving value-chains.

With nearly 1,700 species, Microsporidia represent a group of obligate intracellular eukaryotes with veterinary, economic and medical impacts. To help in understanding the biological functions of these microorganisms, complete genome sequencing is used routinely. Nevertheless, the proper prediction of their gene catalogue is challenging due to taxon-specific evolutionary features. As innovative genome annotation strategies are needed to obtain a representative snapshot of the overall lifestyle of these parasites, the MicroAnnot tool, a dedicated workflow for microsporidian sequence annotation using data from curated databases of accurately annotated microsporidian genes, has been developed. Furthermore, specific modules have been implemented to perform small genes (&lt; 300bp) and transposable element identification. Finally, functional annotation was performed using the signature-based InterProScan software. MicroAnnot’s accuracy has been verified by the re-annotation of four microsporidian genomes for which structural annotation had previously been validated. With its comparative approach and transcriptional signal identification method, MicroAnnot provides accurate prediction of translation initiation sites, efficient identification of transposable elements, as well as high specificity and sensitivity for microsporidian genes including those under 300 bp. Thanks to its web interface (https://microannot.org), MicroAnnot is available to the community to ensure high quality annotation of microsporidian genomes.

Abstract Objectives To investigate histopathological changes and serous carcinoma precursors such as secretory cell outgrowths (SCOUTs) and p53 signature in bilateral tubal ligation (BTL) materials performed during cesarean section (S/C). Materials and Methods 138 patients who underwent S/C and tubal sterilization (TS) between October 2020 and May 2021 at Konya City Hospital. Patients’ data were obtained from the haospital’s system. All data andd findings were investigated and statistically evaluated. Results The mean age was 34.62 years (22 - 44), the mean gravity was 4.89 (2-15) and the mean parity was 3.46 (1-10). 5.79% SCOUT, 7.24% atypia and 9.42% p53 signatures were observed. Significant correlations were shown between epithelial cell lineage and age and between KI-67, SCOUT, and gravity, between KI-67 results and gravity and parity, and between P53 score and age. Conclusion TS is a common, safe, and effective method worldwide. Today, BTL is increasing along with increasing S/C ratios. In addition to the reduced risk of ovarian cancers with ligation alone, precursor lesions such as hyperplasia, SCOUT, p53 signature, and STIL/ Serous tubal intraepithelial carcinoma (STIC) are encountered in the ampulla materials obtained. Considering the low rates of re-anastomosis, tubal excision may be recommended instead of ligation in women of relatively higher gravity and age.

The investigation aims to analyze the effect of homogenization heat treatment on the quantity, distribution, morphology, and chemical composition of δ ferrite and sigma phase in the 316L austenitic stainless steel cast billet. Microstructures of the cast billet at different locations, center, 0.5 R, R, and the subsequent 2/6-hour homogenization heat treatment at 1240 oC were examined. The microstructure at the radius R was much more uniform and expected a better performance in the following hot/cold forging processes due to the highest cooling rate compared with those at 0.5R and center. The δ ferrite often accompanies the generation of the sigma phase, and the transformation of δ ferrite into the sigma/(austenite) and retained δ ferrite is strongly related to the cooling rate after homogenization heat treatment. The sigma phase is hard and detrimental to the subsequent hot/cold forgings. It must be removed from the homogenization heat treatment before forging. Fast air cooling from 850 oC to room temperature after homogenization heat treatment cannot prohibit the sigma phase formation. Rapid cooling between 850 and 1240 oC after homogenization treatment is required to avoid the sigma phase formation in the 316L stainless steel cast billet.

Lung cancer, globally recognized as the leading cause of cancer-related mortality, presents a pressing need for innovative treatment strategies. Increasing evidence points towards the potential of monoamine oxidase (MAO) inhibitors in modulating cancer progression, primarily due to their role in regulating cellular metabolism and apoptotic pathways. This extraordinary study delves into the multifaceted therapeutic implications of MAO inhibitors in lung cancer management, elucidating their ability to pave the way for clinical advancement via novel targets and pathways. Capitalizing on recent advances in molecular biology, this research explores the molecular mechanisms underlying the anticancer actions of MAO inhibitors. By examining their impact on cell proliferation, migration, invasion, and apoptosis in lung cancer cell lines, we provide insight into the intricate signaling pathways and biochemical processes modulated by these compounds. The study also investigates the synergistic effects of MAO inhibitors in combination with established chemotherapeutic agents, elucidating their potential to enhance treatment efficacy and reduce cytotoxicity. Furthermore, we delve into the implications of MAO inhibitors on the tumor microenvironment, evaluating their influence on angiogenesis, immune regulation, and the epithelial-mesenchymal transition. This comprehensive analysis enables the identification of novel molecular targets, which hold promise for the development of advanced therapeutics tailored for specific lung cancer subtypes. To substantiate our findings, in this review, we thoroughly analyze the existing literature using state-of-the-art bioinformatics tools." in vivo orthotopic lung cancer models, and clinical patient cohorts. This robust and multidisciplinary approach permits the generation of clinical evidence supporting the integration of MAO inhibitors in lung cancer management. Conclusion: This ground-breaking study establishes the therapeutic potential of monoamine oxidase inhibitors in lung cancer management by unearthing novel pathways and targets for clinical advancement. The outcomes open doors for the development of innovative treatment strategies and inspire continued research efforts to combat the global burden of lung cancer.

This research article provides a comprehensive analysis of the Expectation of Life at Birth in India and its larger states and union territories (UTs), with a specific focus on rural and urban disparities. The data, obtained from the Ministry of Health and Family Welfare of India, highlights the variations in life expectancy by sex and area of residence, shedding light on the health and socio-economic conditions in different regions. The article discusses the implications of these findings and their relevance for public health policy and interventions.

Conclusion: When applied to the air-abraded Filtek™ Bulk Fill Flowable Restorative composite surface, 10-MDP-containing adhesives perform better than 10-MDP-free adhesives. The binding strength was unaffected by the 10-MDP-containing adhesives' chemical makeup. The bond strength endurance of adhesives containing 10-MDP decreases with age. Keywords: keyword 1; keyword 2; keywords: low-viscosity bulk fill composite, universal adhesives, self-etch adhesive, 10-MDP, aging, bond strength.

Nitrogen (N) is an important mineral nutrient for plant growth, as well as a limiting factor for crop yield, and how to improve the utilization efficiency of N fertilizer by plants is currently a research hotspot. This article uses bioinformatics methods to identify and analyze members of the glutamine synthetase (GS) and glutamate synthase (GOGAT) gene families in pecan. A total of 6 GS genes and 4 GOGAT genes were identified, and their physicochemical properties, gene structures, and homologous evolutionary relationships were analyzed. Analysis of tissue-specific expression of GS and GOGAT genes based on transcriptome data from pecan. The enzyme activities of GS and GOGAT and the gene expression were quantitatively analyzed under different N form ratios in pecan. According to the results, the promoter cis-acting elements of GS and GOGAT genes can be roughly divided into three types: light-responsive elements, hormone-responsive elements, and stress-responsive elements. The results of homologous evolution showed that there was no tandem duplication event for the two gene families, and GS and GOGAT have undergone purification during the evolutionary process. CiGS2s and CiFd-GOGATs were expressed mainly in leaves, and CiNADH-GOGATs were expressed mainly in fruits. The qPCR analysis results showed that T4 treatment significantly increased the expression levels of CiGS and CiGOGAT genes in the leaves. The enzyme activities of GS and GOGAT in pecan were significantly increased under T3, T4, and T5 treatments. In summary, a higher proportion of ammonium nitrogen (NH4+) in the nutrient solution was profit to pecan NH4+ assimilation. This study determined the appropriate nitrogen ratio for pecan, promoting a theoretical basis for reducing environmental pollution caused by nitrogen fertilizer and improving the nitrogen utilization efficiency of pecan. In summary, both CiGSs and CiGOGATs exhibit tissue specificity, and an ammonium-nitrate mixture with a higher proportion of NH4+ is more favorable for NH4+ assimilation in pecan. This study provides a reference basis for further understanding the functions of CiGSs and CiGOGATs in pecan, and offers a theoretical foundation for improving N use efficiency in pecan.

Climate change not only affects weather conditions, patterns, and the frequency and severity of extreme weather events but also changes how governments spend money. Agriculture is an important sector of the European Union (EU), and it is projected to decrease by 16% by 2050, therefore a third of the EU budget has been spent on agricultural funding, adaptation, and climate action. The effect of climate change on agriculture is mixed and dependent on the country and its location. The southern EU is adversely affected while the northern EU is positively affected by the changes in weather patterns. The main goal of this paper is to gain insight regarding the effect that climate change has on public spending in relation to the agricultural sector of the EU, by using the pooled OLS and GMM methods. The study concluded that agriculture has a significant impact on public spending in the southern countries of the EU, where it represents a significant portion of the GDP. Inflation influences public spending in the whole EU region, the northern and southern countries of the EU. Rain has a moderately significant impact on public spending in the whole EU region. It is advised that governments maintain a controllable level of inflation using fiscal and monetary policy that will implicitly control public spending.

By utilizing the Fourier transform, we present a practical method for evaluating a function of a derivative applied to any other arbitrary function of a single complex variable. As an illustration of this approach, we compute the actions of the displacement and squeeze operators on an arbitrary function, as well as the propagation of paraxial fields, Airy and number states, without the need for algebraic quantum operator techniques or the Fresnel integral.

Flails are one of the more contentious and misunderstood classes of medieval weaponry, despite their prevalence in popular media: some researchers question their existence entirely and the bulk of historians are sceptical of widespread temporal and geographical prevalence while others, and a significant volume of period evidence, would argue the contrary. While the expansive use of flails in Eastern Europe and Byzantium is familiar, many Central, Western, and Southern European sources are less well-known or largely forgotten, especially those stemming from the later-early and early-high medieval eras (up to 1250). In this work, I collate and discuss the bulk of the available literary references and artistic depictions of flails and their use alongside some of the archaeological finds from Western, Central, and Southern Europe, with an emphasis on the 12^th and 13^th Centuries. The significance of this volume of evidence is examined, and an assessment of flails as a part of medieval culture and warfare is considered. Collectively, this would suggest that knowledge of flails as instruments of war and associated cultural connotations, if not their actual prevalence and use in warfare, was far more widespread across Europe this time period than has been previously estimated.

In response to injury, vascular smooth muscle cells (VSMCs) of the arterial wall dedifferentiate into a proliferative and migratory phenotype, leading to intimal hyperplasia. The ERK1/2 pathway participates in cellular proliferation and migration while dual-specificity phosphatase 6 (DUSP6, also named MKP3) can dephosphorylate activated ERK1/2. We showed that DUSP6 was expressed in low baseline levels in normal arteries; however, arterial injury significantly increased DUSP6 levels in the vessel wall. Compared with wild-type mice, Dusp6-deficient mice had smaller neointima. In vitro, IL-1β induced DUSP6 expression and increased VSMC proliferation and migration. Lack of DUSP6 diminished IL-1β-induced VSMC proliferation and migration. DUSP6 deficiency did not affect IL-1β-stimulated ERK1/2 activation. Instead, ERK1/2 inhibitor U0126 prevented DUSP6 induction by IL-1beta, indicating that ERK1/2 functions upstream of DUSP6 to regulate DUSP6 expression in VSMCs rather than downstream as a DUSP6 substrate. IL-1β decreased levels of cell cycle inhibitor p27 and cell-cell adhesion molecule N-cadherin in VSMCs whereas lack of DUSP6 prevented their downregulation, revealing novel functions of DUSP6 in regulating these two molecules. Taken together, our results indicate that lack of DUSP6 attenuated neointima formation following arterial injury by reducing VSMC proliferation and migration, which were likely mediated via maintaining p27 and N-cadherin levels.

Measurements of systems taken along a continuous functional dimension, such as time or space, are ubiquitous in many fields, from the physical and biological sciences to economics and engineering. Such measurements can be viewed as realisations of an underlying smooth process sampled over the continuum. However, traditional methods for independence testing and causal learning are not directly applicable to such data, as they do not take into account the dependence along the functional dimension. By using specifically designed kernels, we introduce statistical tests for bivariate, joint, and conditional independence for functional variables. Our method not only extends the applicability to functional data of the Hilbert-Schmidt independence criterion (HSIC) and its d-variate version (d-HSIC), but also allows us to introduce a test for conditional independence by defining a novel statistic for the conditional permutation test (CPT) based on the Hilbert-Schmidt conditional independence criterion (HSCIC), with optimised regularisation strength estimated through an evaluation rejection rate. Our empirical results of the size and power of these tests on synthetic functional data show good performance, and we then exemplify their application to several constraint- and regression-based causal structure learning problems, including both synthetic examples and real socio-economic data.

Forward-bias hole injection from 10 nm-thick p-type Nickel Oxide layers into 10 um-thick n-type Gallium Oxide in a vertical NiO/Ga2O3 p-n heterojunction leads to more than a factor of 2 enhancement of photoresponse measured from this junction. While it takes only 600 seconds to obtain such a pronounced increase in photoresponse, it persists for hours, indicating feasibility of photovoltaic device performance control. The effect is ascribed to charge injection-induced increase of minority carrier (hole) diffusion length (resulting in improved collection of photogenerated non-equilibrium carriers) in n-type beta-Ga2O3 epitaxial layers, due to trapping of injected charge (holes) on deep meta-stable levels in the material and subsequent blocking of non-equilibrium carrier recombination through these levels. Suppressed recombination leads to increased non-equilibrium carrier lifetime, in turn determining a longer diffusion length and being the root-cause for the effect of charge injection.

In the realm of smart manufacturing, equipment plays a pivotal role, impacting the efficiency and quality of production. Ensuring equipment availability and optimal performance is crucial, necessitating effective maintenance strategies. This paper addresses the complexities of smart device maintenance, which often involves collaboration between multiple entities like device owners, manufacturers, suppliers, and external maintenance services. To enhance this cooperative maintenance, we propose a novel maintenance system based on permissioned blockchain technology, offering superior security and reliability compared to conventional cloud-based platforms. Our contributions include developing an integrated maintenance system framework for smart manufacturing, which facilitates interactions among diverse stakeholders. Additionally, we have developed a prototype of this maintenance system, serving as a practical model for real-world application. Our research primarily demonstrates the practicality and advantages of using permissioned blockchain for maintenance systems in the manufacturing sector, paving the way for more secure, efficient, and collaborative maintenance practices.

Background. Type 2 diabetes mellitus (T2DM) is becoming a major global health concern, especially in poorer nations. The high prevalence of obesity and the ensuing diabetes is attributed to rapid economic progress, physical inactivity, consumption of high-calorie foods, and changing lifestyles. Objectives. We investigated the role of pro-inflammatory chemokines; CCL1, 2, 4 and 5 with varying levels of obesity in T2DM in the Asir region of Saudi Arabia. Materials and methods. 170 confirmed T2DM patients and a normal control group were enrolled. The demographic data, serum levels CCL-1, 2, 4 and 5 and the biochemical indices were assessed in patients and control groups by standard procedures. Results. T2DM patients were divided into four groups: A (normal body weight), B (Overweight), C (obese), and D (highly obese). n controls. We observed that male and female control patients had similar mean serum concentrations of pro-inflammatory chemokines CCL 1, 2, 4, and 5. Chemokines CCL1, CCL2, and CCL4 in the serum of Type 2 Diabetes Mellitus patients with normal or overweight body weights were significantly higher than the control group, regardless of gender. In T2DM individuals with obesity and severe obesity, the rise was most significant. There was a progressive rise in the concentrations of CCL1, 2, and 4 in T2DM) patients with increasing BMI. Serum CCL5 levels increased significantly in all T2DM patient groups. The increase in CCL5 was more predominant in normal-weight people as compared to overweight and obese T2DM patients. Conclusions. Male and female control patients had similar serum levels of pro-inflammatory chemokines CCL 1, 2, 4, and 5. The progressive rise in blood concentrations of three Pro-inflammatory chemokines; CCL1, 2, and 4 in T2DM patients with increasing BMI supports the idea that dyslipidemia and obesity contribute to chronic inflammation and insulin resistance. Serum CCL5 levels increased significantly in all T2DM patient groups. The selective and more pronounced increase of CCL5 in the T2DM group with normal BMI as compared to patients with varying degrees of obesity, was rather surprising. Further research is needed to determine if CCL5 under-expression in overweight and obese T2DM patients is due to some unexplained counterbalancing processes.

According to traditional Chinese medicine, Qi and Blood circulate through the human body via pathways known as 'channels and collaterals'. This process supports the normal function of internal organs and the whole body. Pathological conditions can be attributed to abnormal circulation of Qi and Blood, which results in excess or deficiency of organs and channels. Therapeutic methods used in traditional Chinese medicine restore the balance of Qi and Blood.Since acupuncture was introduced in Europe, discussion and debate about the nature of 'acupoints,' 'channels,' and 'collaterals' has continued. Currently, opposing views exist on this subject, ranging from complete denial of the existence of the channels to uncovering the previously unknown system of intra-tissue gaps and microscopic vessels. The author offers an original hypothesis that regards the theory of channels and collaterals as the description of the physiology and pathology of intercellular space and the theory of organs as a description of the physiology and pathology of cells.

Objective: To identify risk factors(RF) related to abnormal glucose regulation(AGR) 3 years postpartum according to 3-month-postpartum glucose status. Research design: Normoglycemic pregnant women of the St. Carlos Gestational Study included before gestational week 12, during 2015-2017. Of 3,036 eligible women, 2529 were followed-up until delivery: 1400 participated in postpartum follow-up. AGR defined as fasting serum glucose (FSG)>5.6 mmol/L and/or HbA1c >5.7% (39 mmol/mol) and/or 2h-SG ≥140/mg/dL after 75-g OGTT. 12-modifiable and 3-unmodifiable RF were analyzed for associations with glycemic changes. Reinforcement of Mediterranean Diet adherence was provided to all women at the postpartum visit by a dietitian Results: 137/1400(9.8%) women presented AGR 3 years postpartum, 27/137(19.7%) also had at 3 months, whereas 110/137(80.2%) had not. The remaining 1,263(90.2%) women were normoglycemic 3 years postpartum, 1180/1263(84.3%) were at 3 months, while 83/1263(6.08%) had AGR and became normoglycemic. Women with GDM were more likely to progress to AGR 3 years postpartum (OR:1.60[1.33-1.92]) and less likely to remain normoglycemic (OR:0.22[0.15-0.33]) versus non-GDM women. Having >2/3 unmodifiable RF was associated with a reduced rate of maintained normoglycemia (OR:0.56[0.39-0.80]) and an increased risk of progression to AGR (OR:1.90[1.28-2.83]). Having >5/12 modifiable RF was associated with a reduced rate of maintained normoglycemic (OR:0.74[0.51-0.99]) and reversion of AGR (OR:0.49[0.25-0.97]), an increased progression to AGR (OR:1.40[1.00-2.09]), and persistence of AGR (OR:2.57[1.05-6.31]). Pre-gestational BMI≥25kg/m2 (OR:1.80[1.19-2.71]), post-delivery weight gain (OR:2.22[1.10-4.48]), and waist circumference >89.5cm (OR:0.54[0.36-0.79]), (all p<0.05) were the main modifiable RF. Conclusions: RF related to an increased probability for 3-year-postpartum AGR despite 3-month normoglycemia were identified, potentially useful when designing personalized strategies for pregnant women, directed towards minimizing unfavorable outcomes.

$\phi$CDM models provide an alternative to the standard $\Lambda$CDM paradigm, while being physically better motivated. These models lead to a time-dependent speed of sound for dark energy that is difficult to replicate by $w$CDM parametrizations. We review the most up-to-date status of observational evidence for the $\phi$CDM models in this paper. We start with an overview of the motivation behind these classes of models, the basic mathematical formalism, and the different classes of models. We then present a compilation of recent results of applying different observational probes to constraining $\phi$CDM model parameters. Over the last twenty years, the precision of observational data has increased immensely, leading to ever tighter constraints. A combination of the recent measurements favors the spatially flat $\Lambda$CDM model, but a large class of $\phi$CDM models is still not ruled out.

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. We developed a Machine Learning (ML)-driven prediction algorithm to trigger and explain a communication alert for BT based on anticipated peri-operative events irrespective of BT policies. We analysed prospectively collected data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. We calculated the estimated blood volume (EBV) using the formula EBV = weight x 80 and set off 10%EBV as threshold for individual intervention. Based on the known estimated blood loss (EBL) we identified two groups. We employed Receiver operating characteristic (ROC) curves for performance metrics. The model performance for the above threshold prediction was satisfactory (AUC 0.823, 95% CI 0.76-0.88). The top feature commonly shared between interrogators was operative time (OT). Intra-operative blood loss of at least 10%EBV was associated with OT&gt;250 minutes, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score &gt;4. Large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy were amongst sub-procedures clearly associated with increased intervention risk. Precise prediction of blood requirements is not possible unless a rough estimate of OT is known in advance.

Curriculum teaching is the basic unit to realize the cultivation and achievement of students’ ability in undergraduate colleges, and it is very important to investigate the influence mechanism of the curriculum system on the achievement states of students' ability. This paper first puts forward the theoretical system and framework of curriculum chains, and constructs a “double-energy and double-space” (DEDS) which consist of the curriculum energy efficiency space and student ability space respectively. Investigating the space-time transformation relationship of curriculum chains in the DEDS, the forward transformation model, inverse transformation model and the rheological model of the achievement states in the curriculum energy efficiency space and student ability space are established. Studying the dynamic evolution mechanism of curriculum chains within the DEDS, the dynamic evolution model, which presents the relationship between achievement states of curriculum energy efficiency/students' ability and curriculum/students' dynamic potential, are established; the control methods of courses/students' dynamic potential based on the proposed dynamic evolution model are developed to ensure the achievements of the graduates’ social ability; the evaluation and detection methods of achievement states of curriculum chains in DEDS are proposed to obtain the actual achievement states of curriculum energy efficiency and students’ ability, and this will provide effective input for the control of curriculums/students’ dynamic potential; the planning and design methods of curriculum chains facing social needs are presented, which can provide theoretical basis for the formulation of the talent training scheme and curriculum system in colleges and universities.

Aim: Glioblastoma multiform (GBM) is a prevalent brain cancer which accounts for 80% of cases globally with a noticeably short life expectancy subsequent diagnosis. There are several factors associated with GBM including alterations and over expressions of oncoproteins. Analysis of SEC61G expression in GBM patient’s favor tumour progression, which promotes an environment of oxidative stress, while preventing apoptosis. Methods: In this article using in silico tools including GEPIA2, ULCAN, LinkedOmics, Gene MANIA and mirTEd, we observed the role of SEC61G gene in GBM progression by analyzing the expression, positive correlation associated with metabolic, mitochondrial gene, immune cell infiltration level, gene interaction networks, miRNA association as well as survival analysis. Results: The expression of the mitochondrial, metabolic genes PGLS, PGK1, EIF6, and EIF3K which are involved in redox metabolism and CD63 immunoregulation, as well as other genes that promote tumour progression and invasion, including EGFR, LANCL2, BCL2L12, SEC61G-DT, KDELR1, CDKN2A, IFNA16, IFNA10, and BCL7C were positively correlated with the increased/high expression of SEC61G.We also found hsa-mir-380-5p to be unregulated in glioblastoma phenotypes. Conclusion: Our findings suggest that SEC61G associated redox metabolism, complement system and immunoregulation, as well as miRNA expression can be targeted to develop a potential therapeutic approach for GBM patients.

Background: Cervical cancer prevention in regions with limited access to screening and HPV vaccination necessitates innovative approaches. This study explored the potential of a test-and-treat strategy using mRNA HPV tests to impact cervical cancer prevention in a high-prevalence HIV population. Methods: A cervical screening study was conducted at three South African hospitals involving 710 under-screened, non-pregnant women (25 to 65 years) without known cervical diseases. Cytology, HPV testing, colposcopy, and biopsies were performed concurrently. Histopathologists determined final histological diagnoses based on biopsy and LLETZ histology. mRNA-HPV-genotyping for 3 (16, 18, 45) to 8 (16, 18, 31, 33, 35, 45, 52, 58) high-risk types was performed on leftover liquid-based cytology material. The preventive potential of the test-and-treat approach was estimated based on published data, reporting the causative HPV types in cervical cancer tissue from South African women. Treatment was provided as needed. Results: HPV positivity rate more than doubled from 3-type (15.2%; 95% CI: 12.6-17.8) to 8-type mRNA (31.5%; 95% CI: 28.8-34.9) combinations, significantly higher among HIV-positive women. CIN3+ prevalence among HIV-positive women (26.4%) was double that of HIV-negative women (12.9%) (p&lt;0.01). The 6-type combination showed the best balance of sensitivity, specificity and treatment group size, and effectiveness to prevent cervical cancer. A 4-type combination (16, 18, 35, 45) could potentially prevent 77.6% (95% CI: 71.2-84.0) of cervical cancer burden by treating 20% and detecting 41.1% of CIN3 cases in the study group. Similarly, a 6-type combination (16, 18, 31, 33, 35, 45), treating 25% and including 62% of CIN3 cases, might prevent 85% of cervical cancer cases (95% CI: 79.6-90.6) among HIV-positive and negative women. Conclusion: Employing mRNA HPV tests within a test-and-treat approach holds huge promise for targeted cervical cancer prevention in under-screened populations. Testing for mRNA of the 6 highest-risk HPV types in this population and treating them all is projected to effectively prevent progression from CIN3 to invasive cervical cancer while reducing overtreatment in resource-constrained settings.

Widely used estimates of food-insecure populations are likely to be biased upwards, lacking adjustment for global increases in sedentary behavior in recent decades. We first construct a household model to account for sedentary choices during leisure and work time decisions. The model rationalizes increasing sedentary behavior from the household by accounting for increasing returns to cognitive human capital vs physical capital, alongside increased productivity of more sedentary activities both at work and at home. The household model then informs an empirical model that makes use of our unique international pseudo-panel data on sitting time, which serves as a proxy for sedentarism. We econometrically estimate a transfer function linking sedentarism to widely available covariates, which then are used to make out-of-sample predictions and can be applied to a large set of countries. The estimated sedentary time can be used to adjust the physical activity level reflected in the minimum dietary energy requirement used to determine a cutoff for food insecurity.

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

Waste heat recovery stands out as a promising technique to tackle both energy shortages and environmental pollution. Currently, this valuable resource, generated from processes like fuel combustion or chemical reactions, is often dissipated into the environment, despite its potential to significantly contribute to the economy. To harness this untapped potential, a travelling-wave thermo-acoustic generator has been designed and subjected to comprehensive experimental analysis. Fifty-two data corresponding to different working conditions of the system were extracted to build ANN, ANFIS and ANN-PSO models. Evaluation of performance metrics reveals that the ANN-PSO model demonstrates the highest predictive accuracy (R^2=0.9959), particularly in relation to output voltage. This research demonstrates the potential of machine learning techniques for the analysis of thermo-acoustic systems. By doing so, it is possible to get an insight into nonlinearities inherent to thermo-acoustic systems. This advancement empowers researchers to forecast the performance characteristics of alternative configurations with a heightened level of precision.

Two austenitic stainless steel (ASS) plates, 304L and 316L, were cold-rolled (304R and 316R) with a 10 % reduction in thickness then subjected to laser welding. Cold-rolling caused a slight surface hardening and introduced residual tensile stress into the ASS plates. The susceptibility to stress corrosion cracking (SCC) of the welds (304RW and 316RW) was determined using the U-bend test pieces in a salt spray. To highlight the stress concentration at the weld’s fusion boundary (FB), the top weld reinforcement was not ground off before bending. Moreover, micro-shot peening (MSP) was performed to mitigate the SCC of the welds by imposing high residual compressive stress and forming a fine-grained structure. Cold-rolling increased the susceptibility of the 304R specimen to pitting corrosion (PTC) and intergranular (IG) microcracking. Moreover, PTC and SCC were found more often at the FBs of the 304RW. The corrosion pits of the peened 304RW (304RWSP) were finer but greater in amount than the un-peened one. The results also indicated that the 316L ASS welds with MSP was resistant to the incidence of PTC and SCC in a salt spray. The better reliability and longer service life of dry storage canister could be achieved by using 316L ASS for construction and application of MSP on it.

As the COVID-19 pandemic has caused enormous damage to society, economy and public health security, it is crucial to combat the epidemic and allocate social and health resources effectively. Global optimization algorithms are extensively used in many domains to find optimal solutions to complex problems. Thus, a survey of three typical global optimizations applied on the COVID-19 pandemic is timely. This article is structured into three typical global optimization algorithms - Genetic Algorithm, Particle Swarm Optimization, and Cat Swarm Optimization - and summarizes the framework models and practical applications, as well as other optimization methods that may be applied to COVID-19. Finally, current unresolved challenges and future research opportunities to be explored are summarized.

: Background: Cartilage harvest and transplantation is a common surgery using costal, auricular, and septal cartilage for craniofacial reconstruction. However, absorption and warping of the cartilage grafts can occur due to inflammatory factors associated with wound healing. Transcriptional factor nuclear factor κB (NFκB) is activated by cytokines, such as interleukin-1 (IL-1), and plays a central role in the transactivation of this inflammatory cytokine gene. Inhibition of NFκB may have anti-inflammatory effects. The aim of this study was to explore the potential of an NFκB decoy oligodeoxynucleotide (Decoy) as a chondroprotective agent. Materials and Methods: Evaluation of safe and efficacious concentrations of Decoy were assessed using rabbit nasal septal chondrocytes (rNSCh) and assays for cytotoxicity, proteoglycan (PG) synthesis, and PG turnover. The efficacious concentration of Decoy determined from the rNSCh was then applied to human nasal septal cartilage (hNSC) in vitro and analyzed for PG turnover, the level of inflammatory markers, and catabolic enzymes in explant-conditioned culture medium. Results: Over the range of Decoy conditions and concentrations, no inhibition of PG synthesis or cytotoxicity was observed. Decoy at 10 μM effectively inhibited PG degradation in the hNSC explant, prolonging PG half-life 63% and decreasing matrix metalloprotease 3 (MMP3) by 70.7% (P = 0.027). Conclusions: Decoy may be a novel chondroprotective therapeutic agent in cartilage transplantation due to its ability to inhibit cartilage degradation due to inflammation cytokines.

The use of nanoparticles as antimicrobial agents can be one of the strategies to overcome the tendency of microbes to become resistant to antibiotics’ action. In this study, two composites ZnO/Au and ZnO/Ag, having 1% wt. of noble metal content, were synthesized by simple aqueous solution methods. The structure and morphology of the resulting nanocomposites were analyzed by standard structural and optical characterization methods. The formation of Au NPs and Ag NPs in these experiments was also discussed. The antimicrobial properties of ZnO, ZnO/Au and ZnO/Ag nanomaterials were investigated against Gram-negative bacteria (Pseudomonas aeruginosa) and Gram-positive bacteria (Staphylococcus aureus). The electrostatic interaction between ZnO and noble metals nanoparticles have contributed to a better visible light adsorption, which led to an enhanced antimicrobial activity. The photocatalytic tests indicated an improvement in photocatalytic degradation of the methylene blue (MB) under UV irradiation using ZnO/Au and ZnO/Ag nanocomposites compared to bare ZnO. The introduction of noble metallic nanoparticles in ZnO matrix proved to be an effective strategy to increase their antimicrobial activity against P. aeruginosa and S. aureus and their photocatalytic activity evaluated through the degradation of MB dye. Comparing the enhancing effects of Au and Ag, it was found that ZnO/Au was a better antimicrobial agent while ZnO/Ag was more effective photocatalyst under UV irradiation.

This study investigates the therapeutic potential of new compound, potassium 2-[2-(2-oxo-4-phenylpyrrolidin-1-yl) acetamido]ethanesulfonate (Compound I), in depression. Willner's chronic unpredictable mild stress model of depression in 48 male Wistar rats was used a depression model. The rats were randomized into four groups, including an intact group, a Compound I group, a Fluoxetine group, and a control group receiving saline. Behavioral tests, such as the Porsolt forced swim test, hole-board test, elevated plus maze test, and light-dark box, were used to assess the animals' conditions. Our results demonstrated that Compound I effectively reduced the immobilization time of rats in the forced swim test, increased orientation and exploratory behavior, and decreased the latency period of going into the dark compartment compared to the control group. Hippocampal and striatal serotonin concentrations were increased in the Compound I group, and the compound also reduced the level of corticosterone in the blood plasma of rats compared to intact animals. These results suggest that Compound I has a reliable antidepressant activity, comparable to that of the reference antidepressant Fluoxetine.

Super-resolution technology is important not only in bio-related fields but also in nanotechnology, particularly in the semiconductor industry, where fine patterning is required and super-resolution is essential. However, observing microstructures beyond the diffraction limit proposed by Abbe and Rayleigh is considered impossible because of diffraction in traditional optical microscopy ob-servation techniques. However, in recent years, it has been possible to observe microstructures beyond the Rayleigh criterion by analysing the phase distribution of light. This study investigated the physical reasons why phase analysis makes this new analysis technique possible using simula-tions. The results confirmed that the phase component of the zero-order diffracted light reflected from the microstructure and able to pass through the lens system contained the phase information related to the shape of the measured object. Analysis of this information demonstrates the possi-bility of realising super-resolution based on speckle interferometry.

We examine a linear q-difference differential equation which is singular in complex time t at the origin. Its coefficients are polynomial in time and bounded holomorphic on horizontal strips in one complex space variable. The equation under study represents a q-analog of a singular partial differential equation, recently investigated by the author, which comprises Fuchsian operators and entails a forcing term that combines polynomial and logarithmic type functions in time. A sectorial holomorphic solution to the equation is constructed as a double complete Laplace transform in both time t and its complex logarithm log t and Fourier inverse integral in space. For a particular choice of the forcing term, this solution turns out to solve some specific nonlinear q-difference differential equation with polynomial coefficients in some positive rational power of t. Asymptotic expansions of the solution relatively to time t are investigated. A Gevrey type expansion is exhibited in a logarithmic scale. Furthermore, a formal asymptotic expansion in power scale is displayed, revealing a new fine structure involving remainders with both Gevrey and q-Gevrey type growth.

This review summarizes the currently known biochemical neuroadaptive mechanisms of remote ischemic conditioning. In particular, it focuses on the significance of the pro-adaptive effects of remote ischemic conditioning, which allow prevention of neurological and cognitive impairments associated with hippocampal dysregulation after brain damage. The neuro-immuno-humoral pathway of transmitting a conditioning stimulus, as well as the molecular basis of the early and delayed phases of neuroprotection, including anti-apoptotic, antioxidant and anti-inflammatory components, are also outlined. Based on the close interplay between the effects of ischemia, especially mediated by interaction of HIF factors and steroid hormones, the involvement of the hypothalamic-pituitary-adrenocortical system in remote ischemic conditioning is also discussed.

In this study, we introduce the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers and conduct a comprehensive analysis to explore its theoretical aspects and examine the crossover effect within the HBV model. To investigate the crossover behavior of the operators, we divide the study interval into two subintervals. In the first interval, the classical derivative is employed to study the qualitative properties of the proposed system, while in the second interval, we utilize the ABC fractional differential operator. Consequently, the study is initiated using the piecewise Atangana-Baleanu derivative framework for the systems. The HBV model is then analyzed to determine the existence, Hyers-Ulam (HU) stability, and disease-free equilibrium point of the model. Moreover, we showcase the application of an Adams-type predictor-corrector (PC) technique for Atangana-Baleanu derivatives and an extended Adams-Bashforth-Moulton (ABM) method for Caputo derivatives through numerical results. Subsequently, we employ computational methods to numerically solve the models and visually present the obtained outcomes using different fractional-order values. This network is designed to provide more precise information for disease modeling, considering that communities often interact with one another, and the rate of disease spread is influenced by this factor.

Chronic lymphocytic leukemia (CLL) is a hematologic malignancy characterized by progressive accumulation of a rare population of CD5+ B lymphocytes in peripheral blood, bone marrow and lymphoid tissues. CLL exhibits remarkable clinical heterogeneity, with some patients presenting with indolent disease and others progressing rapidly to aggressive CLL. The significant heterogeneity of CLL underscores the importance of identifying novel prognostic markers. Recently, the RAS-related gene RRAS2 has emerged as both a driver oncogene and a potential marker for CLL progression, with higher RRAS2 expression associated with poorer disease prognosis. Although missense somatic mutations in the coding sequence of RRAS2 have not been described in CLL, this study reports the frequent detection of three somatic mutations in the 3' untranslated region (3'UTR) affecting positions +26, +53, and +180 downstream of the stop codon in the mRNA. An inverse relationship was observed between these three somatic mutations and RRAS2 mRNA expression, which correlated with lower blood lymphocytosis and better prognosis. These findings highlight the importance of RRAS2 overexpression in CLL development and prognosis and point to somatic mutations in its 3'UTR as novel mechanistic clues. Our results may contribute to the development of targeted therapeutic strategies and improved risk stratification for CLL patients.

Quinoa, known as the "golden grain" for its high nutritional value, is a significant source of essential nutrients, including proteins, minerals, vitamins, polyphenols, phytosterols, and flavonoids. However, the biological functions of quinoa polysaccharides remain understudied. In this research, two crude quinoa polysaccharides extracts (Q-40 and Q-60) were obtained extracting by 40% and 60% alcohol. The purity of Q-40 and Q-60 was 58.29% and 62.15%, with protein contents of 8.27% and 9.60%, respectively. Monosaccharide analysis revealed that Q-40 contained glucose (Glc), galacturonic acid (GalA), and arabinose (Ara) in a molar ratio of 0.967:0.027:0.006. Q-60 was composed of xylose (xyl), arabinose (Ara), galactose, and galacturonic acid (GalA) with a molar ratio of 0.889:0.036:0.034:0.020. The average molecular weight of Q-40 ranged from 47484 to 626488 Da, while Q-60 showed a range of 10025 to 47990 Da. Rheological experiments showed that Q-40 exhibited higher viscosity, while Q-60 demonstrated more elastic properties. Remarkably, Q-60 showed potent antioxidant abilities, with scavenging rates of 98.49% for DPPH and 57.5% for ABTS. Antibacterial experiments using the microdilution method revealed that Q-40 inhibited the growth of Methicillin-resistant Staphylococcus aureus (MRSA) and E. coli, while Q-60 specifically inhibited MRSA. At lower concentrations, both polysaccharides inhibited MDA cell proliferation, but at higher concentrations, they promoted proliferation. Similar proliferation-promoting effects were observed in HepG2 cells. The research provides important information in application of quinoa in food and functional food industries.

The semantic segmentation of high-resolution remote sensing images (HR-RSI) is crucial for a wide range of applications, such as precision agriculture, urban planning, natural resource assessment, and ecological monitoring. However, accurately classifying pixels in HR-RSI faces challenges due to densely distributed small objects and scale variations. Existing techniques, including Convolutional Neural Networks (CNNs) and other methods for hierarchical feature extraction and fusion of remote sensing image, often do not achieve the desired accuracy. In this paper, we propose a novel approach called the Hierarchical Rich-scale Fusion Network (HRFNet) to address these challenges. HRFNet utilizes advanced information rating and image partition techniques to extract rich-scale features within image layers. This allows for the adaptive exploration of both local and global contextual information. Moreover, we introduce a structured intra-layer to inter-layer feature aggregation module, which enables the adaptive extraction of fine-grained details and high-level semantic information from multi-layer feature maps in a highly flexible manner. Extensive experimentation has been conducted to validate the effectiveness of our proposed method. Our results demonstrate that HRFNet outperforms existing techniques, achieving state-of-the-art (SOTA) results on benchmark datasets, specifically the ISPRS Potsdam and Vaihingen datasets.

A study of curvature along the contour provides important sources of information about the shape of an object. Knowledge of contour curvature allows for the perception of and interaction with 3D objects. In this review, we will explore the value of contour curvature in the field of neurophysiology, psychophysics, computer vision, and psychology. The serial consolidation of disjoint edges, oriented in a particular manner, into composited curves allows building of identifiable shapes in occluded natural environments [Hess1999, Wertheimer1923, Zucker1989, Feldman2001]. Examples are our ability to pick objects, sort and manage shapes otherwise hidden or confounded by occlusion in messy natural environments. Contour curvature has been intensively studied in psychology as it forms the first steps in 2D shape building which eventually becomes 3D object recognition in the human brain.

The port environments have some structures that still need regular control. However, the nature of these environments presents a number of challenges in determining an accurate vehicle position and consequently performing successful image similarity detection. These scenarios, however, can have poor visibility conditions and are highly dynamic, making place recognition difficult because the appearance of a place can change over time. Under these operational conditions, imaging sonars are a promising solution. There are some factors that affect the quality of the captured images, but the fact that they do not suffer from haze is a plus. Therefore, in this paper, a purely acoustic similarity detection method based on forward-looking sonar (FLS) data is proposed to overcome the inherent perceptual problems in a port scenario. Considering the lack of available data in this context and to facilitate the variation of environmental parameters and sensor configurations, a port scenario was simulated using the Stonefish simulator. Experiments were conducted on predefined trajectories near structures. The place recognition approach performs better compared to the results obtained with optical imagery. In general, it provides a good compromise in terms of distinctiveness and achieves a performance of 87.5% when appropriate constraints and assumptions are made.

Cambodian spices Amomum kravanh, Citrus hystrix and Piper nigrum 'Kampot' have long history of seasoning of food products. In this study, essential oils (EOs) and supercritical CO2 extracts from all three species have been analyzed using GC-MS with two columns of different polarity, whereas EO and CO2 extract from P. nigrum fruits and CO2 extract from the peel of C. hystrix have been isolated and analyzed for the first time. The results showed that A. kravanh EO contained mostly eucalyptol (78.8/ 72.6 %), while CO2 extract was rich in oleic acid (29.26 %) and tricosane (14.74 %). C. hystrix EO was rich in β-pinene (29.95/29.45 %), followed by D-limonene (24.54/23.24 %) and sabinene (9.94/10.23 %). β-pinene (30.2/28.9 %), D-limonene (23.99/23.74 %) and sabinene (13.36/19.55 %) were also predominant in the CO2 extracts. β-Caryophyllene was the main constituent of both EO and CO2 extract from P. nigrum 'Kampot' with contents ranging from 37.84 to 55.84 %, followed by 3-carene (from 7.18 to 18.72 %). Such findings suggest that supercritical CO2 can potentially be used for extraction of all three Cambodian spices. Nevertheless, further research determining the most efficient extraction parameters will be needed before its application in the spice processing practice.

The effective implementation of a sustainable supply chain leadership (SSCL) strategy at each organization’s level, positively impacts on corporation’s competitive advantage and sustainable development. While fears have been acknowledged in previous literature, the benefit of designing Sustainable supply chain models for operational excellence and sustainable development is a noteworthy exploration. The study collected statistical data using an online Survey- monkey questionnaire from 46 of the top 100 JSE-listed companies with the intention to elucidate the large firms’ transition from longstanding linear approaches to sustainable production and consumption to a more circular approach. A bivariate data analysis was used to generate the results in SPSS. The results indicate a positive contribution of SSCL strategy to operational excellence and sustainable development of large corporations if only the entire supply chain system is well-coordinated and implemented. This study makes a vital contribution by proposing a new SSCL model for fast-tracking corporate sustainability and enhancing corporate contributions to sustainable growth.

The use of Geographical Information Systems (GIS) for biodiversity monitoring and conservation, shortened to Conservation GIS, is an influential tool that has revolutionized conservation efforts by providing spatially explicit data to inform conservation decision-making. However, Conservation GIS also faces challenges related to data quality and availability, technical limitations, as well as policy and governance issues. The diverse and rising uses of GIS for conservation has resulted in a need for continued research and development of Conservation GIS, including advancements in technology and data collection, integration with other fields such as machine learning and artificial intelligence, and collaborative approaches to Conservation GIS. Conservation GIS has the potential to make a significant impact on conservation efforts, and this article emphasizes the importance of its implementation to achieve the broader goal of biodiversity conservation for planetary health. In this review, we discuss the various applications of Conservation GIS, including biodiversity conservation and monitoring, habitat mapping and restoration, climate change mitigation and adaptation, wildlife tracking and management, and protected area management. We highlight some of the key knowledge gaps or research questions that need to be addressed in the future to further advance the field of Conservation GIS. By addressing these challenges and knowledge gaps, Conservation GIS can become a powerful tool for addressing the challenges facing biodiversity and ecosystems worldwide, and for promoting sustainable land-use practices.

African indigenous herbs and medicinal plants are extensively reported for their protective and therapeutic potential against Diabetes. However, most of the constituent phytochemicals that may account for the therapeutic activity are largely uninvestigated. Exploring novel phytochemical–target interactions in silico could help to provide useful insights into the mechanism underpinning the biological activities of these plants and their constituent phytochemicals. The aim of this study was to explore the interactions of terpene struc-tures previously reported from selected African antidiabetic with two emerging drug targets in diabetes. Structure-based virtual screening was used to screen 107 terpene structures against DPP-4 and PTP1B enzymes. The MD simulation, MM-GBSA free energy calculation and DFT were used to clarify the inter-actions of the in silico hits with the target enzymes. Molecular docking, post-docking Prime MM-GBSA analysis revealed the top terpenes with high binding affinity with the active site regions of DPP-4 and PTP1B. Ensemble docking revealed three triterpenes viz: cucurbitacin B (T1), 6-Oxoisoiguesterin (T4) and 20-Epi-isoiguesterinol (T2) as in silico hits which exhibit strong interaction potential with critical residues that define the catalytic triad (Ser630 and His740); oxyanion cavity (Ser631); hydrophobic S1 pocket (Tyr662) and the charged S2 pocket (Arg125) in the active site region of DPP-4. The interactions of these compounds with DPP-4 exhibited structural stability and conformational flexibility during 100 ns full atomistic MD simulation as indicated by the structure dynamics parameters including RMSD, RoG, SASA and hydrogen bond number. The post-MD MM/GBSA calculations further revealed the stability of the triterpene-DPP-4 complexes. Furthermore, Frontier molecular orbital calculations showed that, the triterpenes possess high interaction potential with the enzyme. The triterpenes showed desirable ADMET properties and drug-likeness. Therefore, cucurbitacin B, 6-Oxoisoiguesterin and 20-Epi-isoiguesterinol are recommended for experimental validation.

During the hand-eye calibration process of the manipulator, the Euclidean distance error of the calibration results cannot be calculated because the true values of the hand-eye conversion matrix cannot be obtained. In this paper, a new method of projection error analysis is presented. Error analysis is carried out by using a priori knowledge that the location of AR markers is fixed in the calibration process. The coordinates of the AR marker center point are reprojected to the pixel coordinate system, and then compared with the true pixel coordinates of the AR marker center point obtained by corner detection or manual labeling in order to obtain the Euclidean distance between the two coordinates as the basis for error analysis. Experimental results show that the proposed optimization method can greatly improve the accuracy of hand-eye calibration results.

Compton cameras detect scattered gamma rays and estimate the distribution of gamma-ray sources. Nonetheless, crafting a camera tailored to a specific application presents formidable challenges, often necessitating the implementation of diverse image reconstruction techniques. Delving into the factors influencing these cameras can pave the way for design optimization and performance enhancement. This study introduces an inventive detector design for Compton imaging systems, building upon the achievements of prior designs. The proposed system contains eight scatterer detectors and a semiconductor absorber detector, spaced at 1 mm and 30 mm intervals, respectively. The source-to-first-scatterer-detector distance is 5 mm, with scatterer and absorber detector plates measuring 70× 70× 2.125 mm³ and 70× 70× 10 mm³, respectively. Geant4 simulation toolkit models the Compton imaging system, and an analytical method reconstructs Compton camera images. Unlike more straightforward techniques, the analytical method directly reconstructs Compton camera images by solving the equation relating to the reflected image data. This approach is implemented in the C++ programming language. The study's findings reveal that the analytical method discerns optimal conditions and parameters that significantly influence efficiency, yielding a full width at half maximum (FWHM) of 3.7 mm with an angular uncertainty of approximately 2.7 degrees at an energy level of 0.662 MeV. Compared to another experimental design employing the analytical image reconstruction approach, the FWHM value decreased by 0.7 mm. This study presents an innovative detector design and an analytical reconstruction method for Compton imaging systems, showcasing improved efficiency and accuracy.

The study aimed to isolate and characterize bacteriocin-producing Enterococcus species from Ethiopian traditional fermented foods and beverages. The bacteriocin bioassay was tested against food-borne pathogens at various temperatures, pH, solvents, additives, and enzymes. A solvent extraction method was established to concentrate bacteriocins from Enterococcus species. The study found that crude extracts with proteinase K, pepsin, and trypsin deactivated antimicrobial activity, confirming their proteinaceous nature. Organic solvents were more effective at extracting bacteriocins from CFS, with chloroform alone and in combination providing rapid and efficient recovery. The optimal bacteriocin production and strong inhibition activity were achieved at 37°C with a pH range of 5.5 to 6.5 incubated for 16-18 hours. The six Enterococcus faecium species were the best bacteriocin-producing isolates. Optimizing bacteriocin production and changing environmental growing circumstances can enhance the application of bacteriocins as food preservation agents. Traditional fermented products are potential sources of bacteriocin-producing LAB.

A key response to glucose stress is an increased production of unsaturated fatty acids to balance the increase of saturated fatty acids in the membrane. The C. elegans homolog of stearoyl-CoA desaturase, FAT-7, introduces the first double bond into saturated C18 fatty acids yielding oleic acid and is a critical regulatory point for surviving cold and glucose stress. Here, we incorporated 13C stable isotopes into the diet of nematodes and quantified the 13C-labelled fatty acid by GC-MS and HPLC/MS-MS to track the metabolic response to various concentrations of glucose. Previous work has analyzed membrane composition of C. elegans when responding to mild glucose stress and showed few alterations in overall fatty acid composition in the membrane. Here, in nematodes exposed to higher concentrations of glucose, a specific reduction of oleic acid and linoleic acid was observed. Using time courses and stable isotope tracing, the response of fatty acid me-tabolism to increasing levels of glucose stress has been characterized, revealing a funneling of monounsaturated fatty acids to preserve polyunsaturated fatty acid abundance. Taken together, higher levels of glucose unveil a specific reduction of oleic and linolenic acid in the metabolic re-wiring required to survive glucose stress.

We introduce a special vector field ω on a Riemannian manifold (N^m, g), such that the Lie derivative of the metric g with respect to ω is equal to ρRic, where Ric is the Ricci curvature of (N^m, g) and ρ is a smooth function on N^{m} and call this vector field a ρ-Ricci vector field. We use ρ-Ricci vector field on a Riemannian manifold (N^m, g) and find two characterizations of m-sphere S^m(α). In first result, we show that an m-dimensional compact and connected Riemannian manifold (N^m, g) with nonzero scalar curvature admits a ρ-Ricci vector field ω such that ρ is nonconstant function and the integral of Ric(ω,ω) has a suitable lower bound is necessary and sufficient for (N^m, g) to be isometric to m-sphere S^m(α). In second result, we show that an m-dimensional complete and simply connected Riemannian manifold (N^m, g) of positive scalar curvature admits a ρ-Ricci vector field ω such that ρ is a nontrivial solution of Fischer-Marsden equation and the squared length of the covariant derivative of ω has an appropriate upper bound, if and only if, (N^m, g) to be isometric to m-sphere S^m(α).

This study investigates why young adults live with their parents in Sweden. As young adults’ living arrangements affect decisions about marriage, education, childbirth, and participation in the workforce, more knowledge for policy makers is crucial to implementing effective policies to support young adults and promote financial independence and well-being. Using a data set from 1998 to 2021 at the municipal level in Sweden, we used a spatial autoregressive panel data model to examine the proportion of young adults living at home and regional disparities. The study uncovers intraregional variations, illustrating how different municipalities within Sweden exhibit different patterns of young adults living at home. Our findings reveal that economic factors, such as unemployment, significantly impact this pattern. The dynamics of the housing market, demographic factors, cultural differences, and location-specific characteristics also play an essential role in explaining this pattern. The findings suggest that the key drivers are the lack of rental housing, high unemployment rates, a high degree of urbanisation, interregional migration, and lack of social capital.

In this paper, we explore a new norm on L^p-space called r-norm, and hence producing a new normed space called r-normed space. Measure theoretic and functional analytic properties are covered such as the relation between r-norm and the classical p-norm. An application of r-normed space in probability theory and statsitics is also presented, notably, its role as a rigorous framework in describing the coefficient of determination.

High-performance insulation and airtight building envelopes are the two most important factors to optimize the building energy efficiency and thermal performance. However, thermal performance of building envelopes can be significantly affected by thermal bridging. Thermal bridges can take place at different locations of the building envelope, causing added transmission losses, increasing heat flow, lower inner surface temperatures. Thermal bridges are regarded in all national regulations for new buildings of all states of European Union (EU) but there are no specifications assessing balconies to wall junctions and the impact on the building thermal performance is not well regulated. In this paper, balcony to wall thermal bridge assessment using infrared thermography is highlighted. The originality is that, infrared thermography, has been applied to a real living latest building in the north east of France showing that there is noncompliance in the national regulations as some exigencies are not met. Thermography of thermal break windows and window doors has also revealed air leakage. The goal, is to illustrate that thermal imaging is a means of quality assurance to new building specifications and should include a clause specifying quality assurance procedure for balconies junction in national building regulations for all states if the EU.

Due to the complexity of the microstructure of porous media, it is of great significance to explore the heat transport mechanism in porous media in many engineering applications. In this study, an expression for effective thermal conductivity（ETC） of porous media with randomly distributed damaged tree-like bifurcation networks is derived based on the theory of thermodynamics and fractal features of tree-like bifurcation networks. We investigate the effect of heat conduction and heat convection in porous media with randomly distributed damaged tree-like bifurcation networks on the ETC of the porous media. It is found that our fractal model is in good consistency with the existing available experimental data. In addition, the influence of the micro-structural parameters of the model on heat transfer in the porous media have been analyzed in detail. The research results can provide significant theoretical guidance for the development and design of heat transfer systems.

Background: Given that VR is applied in multiple domains, understanding the effects of cybersickness on human cognition and motor skills and the factors contributing to cybersickness gains urgency. This study aimed to explore the predictors of cybersickness and its interplay with cognitive and motor skills. Methods: 30 participants, 20-45 years old, completed the MSSQ and the CSQ-VR, and were immersed in VR. During immersion, they were exposed to a roller coaster ride. Before and after the ride, participants responded to CSQ-VR and performed VR-based cognitive and psychomotor tasks. Post VR session, participants completed the CSQ-VR again. Results: Motion sickness susceptibility, during adulthood, was the most prominent predictor of cybersickness. Pupil dilation emerged as a significant predictor of cybersickness. Experience in videogaming was a significant predictor of both cybersickness and cognitive/motor functions. Cybersickness negatively affected visuospatial working memory and psychomotor skills. Overall cybersickness’, nausea and vestibular symptoms’ intensities significantly decreased after removing the VR headset. Conclusions: In order of importance, motion sickness susceptibility and gaming experience are significant predictors of cybersickness. Pupil dilation appears as a cybersickness’ biomarker. Cybersickness negatively affects visuospatial working memory and psychomotor skills. Cybersickness and its effects on performance should be examined during and not after immersion.

We investigated the liquid water path and global solar irradiance at ground (Q) according to the ICON model, CLOUDNET measurements in Lindenberg, Munich, Jülich, and BSRN observations in Lindenberg. The liquid water path is underestimated, while global irradiance is overestimated. The lower liquid water path is due to liquid water content underestimation practically in all atmosphere layers and lower frequency of liquid clouds occurrence compare to observations. The latter is partly associated with a reduced model’ sensitivity to the cloud condensation nuclei (CCN). An increase in CCN from 250 cm-3 (typical background value for the region of interest) to 1700 cm-3 (characteristic of polluted continental clouds) leads to an increase in grid-scale liquid water path by 40% and a decrease in Q under overcast conditions by 12%. However, we also showed that liquid water path is not a key factor of Q overestimation. The main factor is an inaccurate description of the cloud spatial structure, where the correct prediction of the direct to global irradiance ratio as a spatial characteristic of clouds plays the most important role compared to standard cloud fraction.

Intracranial compliance (ICC) plays a pivotal role in understanding the underlying mechanisms of various brain disorders and is of great clinical importance. Therefore, addressing the challenges in practical application of ICC is crucial for neurosurgeons. This study explored the significance of ICC assessment considering the time-dependency of specific brain disorders through two distinct approaches: short and large time elapsed (TE) in measuring volume or intracranial pressure (ICP) changes in the ICC equation (∆Volume/∆ICP). Variations in ICC values were observed across various ICC assessment methods and different TE values. Notably, the compensatory response of the brain exhibited non-monotonic and variable changes in a large TE for certain brain disorders, diverging from patterns observed in short TE assessments. Furthermore, the recovery behavior of the brain changed under different brain disorders when exposed to short and long TE conditions. These findings emphasized the dynamic nature of ICC and provided valuable insights into the correct practical assessment of ICC by selecting the appropriate TE, as well as considering the differences in strain rates and loading durations on the brain in different brain disorders. These insights also shed light on the reasons why, despite its clinical significance, ICC monitoring has not yet become a standard component of clinical care, unlike ICP monitoring.

Arthroscopic capsular release (ACR) is used for persistent shoulder stiffness after an index surgery. No cases of post-ACR humeral head osteonecrosis have been reported to date. A 56-year-old male patient underwent open reduction and internal fixation using a hook plate for acromioclavicular joint dislocation. Despite hardware removal, the patient presented with unresolved shoulder pain and range-of-motion (ROM) limitation. He had a history of hypertension, chronic hepatitis B infection, and alcohol consumption. Preoperative ROM was forward flexion 90°and internal rotation sacral level. Preoperative functional status was visual analog scale (VAS) score 4, American Shoulder and Elbow Surgeons (ASES) score 51, and Constant–Murley (CMS) score 48, and normal radiography and magnetic resonance imaging. Standard ACR was performed with 360° release of the joint capsule via electrocautery ablation. Six-months post-ACR, ROM (forward flexion: 135°, abduction: 135°, external rotation: 70°, internal rotation: T10 vertebra) and functional outcomes (VAS 2; ASES79; CMS 75) were significantly improved, without interval change in radiographic assessment. However, 21 months later, he had recurrent shoulder pain and decreased ROM. Radiography revealed humeral head osteonecrosis. Patients with intrinsic or extrinsic risk factors related to humeral head circulation disturbance should be monitored for humeral head osteonecrosis post-ACR.

Cell migration crucial contributor to metastasis, a critical process associated with the mortality of cancer patients. The initiation of metastasis is triggered by epithelial-mesenchymal transition (EMT), along with the changes of the expression of EMT marker proteins. Inflammation plays a significant role in carcinogenesis and metastasis. Lipopolysaccharide (LPS), a typical inflammatory agent, promoted the generation of superoxide through the activation of p-Tyr42 RhoA, Rho-dependent kinase 2 (ROCK2) and the phosphorylation of p47phox. In addition, p-Tyr42 RhoA activated phospholipase D1 (PLD1), with PLD1 and phosphatidic acid (PA) being involved in superoxide production. PA also regulated the expression of EMT maker proteins. Consequently, we have identified MHY9 (Miosin IIA, NMIIA) as a PA-binding protein in response to LPS. MYH9 also contributed cell migration and the alteration of the expression of EMT marker proteins. P-Tyr42 RhoA, PLD1 and MYH9 associated to form a complex, which was distributed in both the cytosol and nucleus. In addition, we have found that p-Tyr42 RhoA and PLD1 associated with the ZEB1 promoter. Taken together, we propose that p-Tyr42 RhoA and PLD1, responsible for producing PA, and PA-bound MYH9 are involved in the regulation of ZEB1 expression, thereby promoting cell migration.

Utilization of medicine derived from plants has been documented in various traditional systems of medicines throughout the world for different diseases. Therefore, the current research work was carried out to evaluate the phytochemical and biological potential of Ficus carica L ethanolic leaf extract. For this purpose, physicochemical and phytochemical analysis, total phenolic and flavonoids contents was performed. Antioxidant potential was determined by FRAP, DPPH and H2O2 assay. Proteinase inhibition, heat induced hemolysis and BSA denaturation assay was carried out for inflammation. Antiglycation potential was assessed by fructosamine assay, Congo-red assay and estimation of free carbonyl groups. In-vivo antidiabetic, anti-obesity, effect on liver and kidney were investigated by high fat high sugar diet model. FTIR, HPLC and LCMS/MS analysis was performed to find out the compounds. Tablet based formulation was developed using wet granulation method and tested for physicochemical parameters. Results shows that total phenolic and flavonoids content was (333 mg GAE/g) and (123 mg RE/g) respectively, H2O2 assay shows 35.6% free radical inhibition potential, DPPH assay shows (IC50) inhibitory concentration at 0.58 mg/mL, and 88.769 µg/g Fe2SO4 solution FRAP values. Proteinase inhibition assay, Heat induced hemolysis and BSA-denaturation assay shows percentage inhibition of 28 ± 0.01, 55 ± 0.03 and 51.2 ± 0.05 respectively. In Antiglycation activity β-amyloid formation assay shows absorption of 0.017, Fructosamine assay shows inhibition of 19.4±0.06 and free carbonyl group estimation shows inhibition of 17.0±0.03. In in-vivo study FLE at (500 mg/kg) significantly decreased total bilirubin (p ≤ 0.001), decreased (p ≤ 0.05) alanine transferase, aspartate aminotransferase, alkaline phosphatase, decreased blood glucose, triglycerides and total cholesterol (p ≤ 0.01) while HDL (p ≤ 0.01) was significantly increased in comparison to obesity and diabetic-obesity groups. Different functional groups presence was confirmed by FTIR spectrum. HPLC analysis revealed the existence of ferulic acid, rutin, chlorogenic acid, coumarin and thymoquinone and these results are corelated by LC-MS/MS. Pre-compression characterization showed angle of repose (33.04°), bulk density (0.54 g/cm3), tapped density (0.73 g/cm3), compressibility index (35.179 %) and Hausner’s ratio (1.35), while the post-compression characterization showed weight variation 826±4.17 mg, thickness 10.50±0.25 kg/cm2, friability 0.57 %, and disintegration time 8.19 min. From the above results it is concluded that F. carica L. leaves extract has strong antioxidant, antidiabetic and hypolipidemic potential and can be used for an obesity and diabetes treatment.

Organic Medium Enclosed Trough (OMET) is a new non-drainable growing technique. The study envisioned to investigate the interactive effects of OMET and Amaranth species vari-ation on some growth attributes, bioactive compounds and nutrients. Three Amaranth species: A. caudatus, A. cruentus and A. tricolor were grown in an OMET and non-OMET growing conditions. Growth attributes, irrigation water, bioactive compounds and nutri-ents were determined. Non-OMET and A. cruentus showed the highest total phenolics and flavonols followed by A. caudatus and A. tricolor, whilst tannins were predominant in A. caudatus followed by A. cruentus and A. tricolor. The use of unsupervised PCA showed major metabolic variation based on Amaranth species and the use of supervised OPLS-DA showed clear metabolic variation based on OMET and non-OMET. OMET and A. cruentus showed the highest plant height, stem diameter, biomass, and some nutrients (%protein, Ca, P, Cu, Se, Zn), followed by A. caudatus based only on growth and biomass, and A. tricol-or based only on some nutrients (Mg, K, Mn, and Fe). The use OMET system on A. cruentus and A. tricolor can be recommended to mitigate climate change effects on nutritional com-position using low irrigation water.

The aims of this paper can be traced back to goals number seven, twelve and thirteen introduced by Agenda 2030, namely "affordable and clean energy", “responsible consumption and production” and "climate action”, respectively. This is due to the fact that the present work supports decarbonization processes acting in a direct way on the electricity consumption achieved by plants pertaining to the waste industry; in fact, this study aims at the realization of a machine learning model for predicting the energy consumption achieved by a mechanical biological treatment (MBT) waste plant located in central Italy, given the distribution of the entering waste. This model is implemented in MATLAB. The model can be used to tune the distribution of the entering waste in order to adapt the plant energy consumption to the capability of the energy sources and can serve as a play-ground model for other energy transformation plants. The results of the study, which feed the literature on the application of artificial intelligence to real industrial plants, could be used to determine energy efficiency actions that could be incorporated into Property’s strategic planning.

Effective sports training should be attuned to the athlete's specific conditionings and characteristics. In motor learning research, two often neglected factors that influence this resonance are the learner's athletic background and the structural diversity of exercises (e.g., relative similarity). This study examines the effects of three learning approaches (i.e., contextual interference (CI), differential learning (DL), and free-play control condition (CO)) on the parallel learning of Handball (HB), Volleyball (VB), and Basketball (BB) skills, considering participants' prior sport backgrounds. Forty-five males (15 HB, 15 VB, and 15 BB players) with a mean age of 22±1.4 years and at least 6 years of experience in the mastered discipline voluntarily participated in this study. A pre-post-retention test design including a 6-week-intervention program was employed. In terms of short-term (pre-post) gain, only the DL- group significantly improved their performance in both non-mastered disciplines (p=0.03 for the BB free-throw and p=0.05 for the HB shooting tests), with a trend (ES=0.53) towards an improvement in the performance of the mastered VB underarm-pass skill. In terms of relatively permanent gains, the CI group significantly improved their performances from pre- to retention-test only in the non-mastered BB free-throw skill (p=0.018). In contrast, the DL group significantly improved their performance at retention compared to the pre-test in both non-mastered BB (p=0.004) and HB (p=0.003) skills, with a trend (ES=0.4) towards improvement in the mastered VB test. In both short, and relatively permanent terms, higher composite score gains were observed in DL compared to CI (p=0.001 and 0.002) and CO (p=0.001 and <0.0001). In conclusion, the present findings provide additional support for the potential advantages of the DL model over those of CI. These findings can serve as the basis for tailored training and intervention strategies and provide a new perspective for addressing various issues related to individual and situational learning.

Prosthetic attack is a problem that must be prevented in the current finger vein recognition application. To solve this problem, a finger vein living detection system was established in this article. The system first captures short-term static finger vein video by uniform near-infrared lighting, segments the veins by Gabor filters with current removing, calculates the multi-Scale spatial-Temporal maps(MSTmap) from the selected vein blocks, and trains the MSTmaps in the proposed Light-ViT network for the liveness detection. The MS maps are used to extract the coarse feature and Light-ViT is used to refine the liveness feature and predict the liveness result. Light-ViT, featuring an enhanced L-ViT backbone as its core, is constructed by interleaving multiple MN blocks and L-ViT blocks. This architecture effectively balances the learning of local image features, controls network parameter complexity, and substantially improves the accuracy of liveness detection. The accuracy of the Light-ViT network is verified to be 99.63% on the self-made living / prosthetic finger vein video dataset. This proposed system can also be directly applied to the finger vein recognition terminal after the model lightweighting.

Cloud platforms are widely employed in today's educational context to enhance collaborative learning and the overall quality of the teaching-learning process. In 2016, Nextcloud was im-plemented in the Faculty of Chemical Engineering at the Technological University of Havana "José Antonio Echeverría" (CUJAE), Cuba. Subsequently, an evaluative phase was conducted to ensure the continuous development of the platform. The objective was to assess the use and ac-ceptance of the Nextcloud platform from the perspective of students and professors in the Fac-ulty. An exploratory, non-experimental, and cross-sectional study was conducted. Data was col-lected through observation and a survey. Matomo Analytics tool was employed for observation, revealing low visitation numbers. The survey was based on the Unified Theory of Acceptance and Use of Technology model. Better results were obtained in positive acceptances compared to negative ones, both for professors and students. It is concluded that the evaluation of the Next-cloud platform is infrequently used by users; however, there were higher positive acceptances than negatives from the perspectives of both students and professors.

Age estimation is an important tool when dealing with human remains or undocumented minors. Although the skull, the skeleton or the hand-wrist are used on age estimation as maturity indicators, they often present lack of good conditions for a correct identification or estimation. Few systematic reviews (SRs) have been recently published; therefore, this umbrella review critically assesses their level of evidence and provides a general comprehensive view. An electronic database search was conducted in four databases (PubMed, Cochrane, WoS, LILACS) up to December 2022, focusing on SRs of age estimation through forensic dentistry procedures. The methodological quality was analyzed using the measurement tool to assess SRs criteria (AMSTAR2). Eighteen SRs were included, five of critically low quality, six of low quality, three of moderate quality and four of high quality. The SRs posited that Willems’ method is more accurate and less prone to overestimation; most methods seem to be geographically sensitive; and 3D-Imaging and artificial intelligence tools demonstrate high potential. The quality of evidence on age estimation using dental approaches was rated as low to moderate. Well-designed clinical trials and high standard systematic reviews are essential to corroborate the accuracy of the different procedures of age estimation in forensic dentistry.

Nowadays, semantic segmentation is increasingly used in exploration by underwater robots, for example in autonomous navigation, so that the robot can recognise the nature and elements of its environment during the mission and act according to this classification to avoid collisions. Other applications can be found in the search for archaeological artefacts, in the inspection of underwater structures or in species monitoring. Therefore, it is necessary to try to improve the performance in these tasks as much as possible. To this end, we compare some methods for improving image quality and for data augmentation and test whether higher performance metrics can be achieved with both strategies. The experiments are performed with the SegNet implementations and the SUIM dataset with 8 common underwater classes to compare the obtained results with the already known ones. The results obtained with both strategies show that they are beneficial and lead to better performance results by achieving a mean IoU of 56% and an increased overall accuracy of 81.8%. The single result shows that there are 5 classes with an IoU value above 60% and only one class with an IoU value below 30%, which is a more reliable result and easier to use in real contexts.

This study aims to develop a novel retention method combining the retrievability of the screw retention method with the ideal occlusal table and the aesthetics capability of cement retention. Coping was developed to have lateral screw access allowing the screw to lock coping using lateral forces from screw tightening and friction between the tip of the screw and the sandblasted surface of an abutment. Sandblasting parameters varied based on particle size. Results show a positive correlation to surface roughness and indicate a positive correlation to retention force. The highest surface roughness and retention force result was shown by groups that were sandblasted using 686 μm of aluminum oxide. Experiment on the tightening strength of 48 subjects measured in simulated conditions similar to assembly conditions of lateral screw retention implant resulted in a mean of 69.75 Nmm with the highest and lowest values of 120.67 Nmm and 34.67 Nmm. This result became the basis of tightening torque variation. Each group's retention capability is measured and compared to cement-retained dental implants. Results show that tightening torque correlates positively with retention force, with the highest average retention score showed by lateral screw retained under tightening torque of 200 Nmm with 317.87 N higher than cement-retained.

This study focused on the precise detection and concordant analysis of circulating tumor cells (CTCs) to verify the usefulness of CTCs as promising clinical markers. CTCs are traditionally achieved using immune-fluorescence and morphological techniques. By combining two prostate cancer-specific genes (PSA and PSMA) and two epithelial-specific genes (EpCAM and KRT19), the CTC detection efficiency can be enhanced. The detection rates of localized prostate cancer (LPC), locally advanced prostate cancer (LAPC), metastatic hormone-sensitive prostate cancer (mHSPC), and metastatic castration-resistive prostate cancer (mCRPC) were 63.04 % (29/46), 70.59% (34/51), 94.34% (50/53), and 90% (126/140), respectively. Subsequent correlation analysis between the four genes, baseline PSA, and CTC count revealed that only the CTC count correlated with baseline PSA in the localized stages of prostate cancer, whereas all four genes were correlated with baseline PSA and CTC count in the metastatic stages of prostate cancer. The precise detection of CTCs using both numerical and transcriptomic analyses can improve the accuracy of biomarker investigations. This study provides valuable insights into the limitations of serum PSA testing and offers a promising alternative to diagnose and manage prostate cancer via the CTC number and specific genes for prostate cancer.

This study aims to explore the utilization of deep learning models, specifically the innovative Multi-Modal Contextual Fusion Convolutional Neural Network (MSHA), for the detection and diagnosis of Adrenocortical Carcinoma (ACC) using computed tomography (CT) images. The objective is to develop an accurate and reliable model that can assist in the effective detection and classification of ACC. The study utilizes a dataset comprising contrast-enhanced CT images from 53 confirmed ACC patients. The MSHA model is employed, which incorporates a combination of mixed-scale dense convolution, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information techniques. Evaluation metrics are used to assess the performance of the MSHA model, and a comparison is made with other established models, including ResNet50, VGG16, VGG19, and InceptionV3. The evaluation of the MSHA model demonstrates high performance, with an accuracy of 96.65% and precision, sensitivity, specificity, and F1 score of 96.0%. These results highlight the MSHA model's capability in accurately detecting and classifying ACC. Furthermore, compared to other models, the MSHA model outperforms ResNet50, VGG16, VGG19, and InceptionV3, indicating its superior performance in ACC detection and diagnosis. The findings of this study suggest that the MSHA model holds significant potential in assisting healthcare professionals with the detection and diagnosis of ACC. With its advanced features and contextual fusion techniques, the MSHA model achieves high accuracy and performance. The results highlight the clinical significance of this novel model and its potential to improve patient management and outcomes in the detection and diagnosis of ACC using CT images.

Background: The purpose of this study was to compare the immediate and long-term complications that are associated with the utilized techniques for the insertion of indwelling central venous catheters, that is the open surgical technique, the ultrasound-guided technique and the transcutaneous technique based on external anatomical landmarks in the right internal jugular vein, to a pediatric population. Methods: This was a prospective randomized trial based on a pediatric patient population, under 16 years of age, of a tertiary pediatric-oncological hospital. Procedure was performed by a medical team with varying experience regarding the percutaneous and open insertion methods. We studied the outcome of our procedure, based on the immediate and delayed complication rate, as well as the needed time in order to complete the procedure and mean duration of line use. Results: The patients that were inserted in our protocol were divided into three subgroups, based on the selected technique for the insertion of the central venous catheter. A total number of 88 insertions (25.4%) (out of 346) were based on the technique that was using external anatomical landmarks, 121 insertions were based on the ultrasound-guided transcutaneous technique (34,9%), whereas in 137 cases (39.5%) the open surgical technique was preferred. All cases that were related to catheter re-insertion were excluded from our study. We performed a statistical analysis regarding the catheter dwell time between the three subgroups of patients and no significant difference was recorded. Moreover, the development of thrombosis was investigated, and we mentioned that the higher percentage of this complication was related with the transcutaneous external landmark and open surgical technique. Also, the incidence of infection was taken into consideration, which manifested an increased incidence when the transcutaneous technique based on external landmarks was used. Conclusions: Ultrasound guided percutaneous insertion was considered to be a safe and effective technique for the insertion of central venous catheters. Our study also demonstrated a decrease in operating times, when performed by operators with increasing expertise, increased preservation of the diameter of the venous lumen, and no increase in complication rates when the ultrasound-guided technique was selected.

Vitamin D is crucial for athletes' health and performance. Although the exact vitamin D requirements for athletes have not been established, maintaining 25(OH)D levels of at least 40 ng/ml is considered beneficial. This study aimed to determine whether an individual loading dose formula for vitamin D supplementation is suitable to meet a target value of 40 ng/ml and is more effective than standardized supplementation. In a 10-week supplementation study during the winter months in Germany, 90 athletes with insufficient vitamin D levels (25(OH)D<30ng/ml) were randomly assigned to receive either a universal dose of 2000 IU/day of vitamin D or a loading dose of 4000 IU/day, followed by a maintenance dose of 1000 IU/day. Total 25(OH)D concentration was measured from dried blood spots at three time points: at baseline, at the computed date of 40ng/ml, and after the 10-week period. Additionally, a vitamin D-specific questionnaire was issued. On the day when 25(OH)D blood concentrations of 40 ng/ml were calculated to prevail, the individualized group had a significantly higher 25(OH)D level than the standardized group (41.1+-10.9 ng/ml vs. 32.5+-6.4 ng/ml, p<0.001). This study demonstrated that the examined formula is suitable for athletes to achieve a 25(OH)D concentration of 40 ng/ml. This indicates that a personalized approach is more effective than a one-size-fits-all approach in restoring adequate vitamin D levels in athletes.

Dacomitinib is an irreversible epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor indicated for the treatment of patients with advanced non-small cell lung cancer (NSCLC) and EGFR-activating mutations. Proton pump inhibitors decreased dacomitinib exposure. This anal-ysis summarizes the effect of H2RA on dacomitinib exposure. A within-patient comparison of steady-state trough concentrations (Ctrough,ss) of dacomitinib and its active metabolite and active moiety with and without concomitant use of H2RA was conducted using a linear mixed effects model with pooled data from 11 clinical studies in patients with NSCLC. An oral absorption PBPK model was constructed and verified using clinical PK data after a single dose of dacomitinib in healthy volunteers to estimate the effect of gastric pH altered by an H2RA on dacomitinib PK. The adjusted geometric mean of dacomitinib Ctrough,ss of dacomitinib parent, metabolite and active moiety following co-administration with H2RA was approximately 86%, 104% and 100% relative to that following dacomitinib 45 mg administration without H2RA (P>0.05). The PBPK modeling showed negligible change in dacomitinib Cmax and AUC over 0-24 hours after H2RA administra-tion, when compared with those administered dacomitinib alone. Co-administration of an H2RA with dacomitinib is not expected to have any clinically relevant effect on dacomitinib exposure.

This study explores the perspectives and practices of architects regarding the reuse of wood in construction across five South-Central European countries: Slovenia, Serbia, North Macedonia, Bosnia and Herzegovina (BiH), and Montenegro. Based on a survey of architectural professionals, the research explores their attitudes, challenges, and motivations for using reclaimed wood, with a focus on circular construction principles. Key findings reveal unanimous agreement among re-spondents that both their profession and government entities inadequately support or promote wood reuse within the context of circular construction. While architects value reclaimed wood, there are country-specific variations. Environmental benefits, unique aesthetics, historical value, and sustainability are cited as primary motivators for reclaimed wood use. Additionally, re-spondents emphasize the ecological aspect as the most important consideration in wood product reuse, followed by economic and technological factors. Common concerns revolve around the long-term quality and maintenance of wood products. This research provides insights into the challenges and opportunities surrounding reclaimed wood use in South-Central Europe, high-lighting the need for support mechanisms and increased awareness to advance circular construc-tion practices in the region. These findings can have implications for architects and investors by identifying market opportunities, promoting eco-friendly practices, and providing valuable in-sights for future building designs with a focus on reclaimed wood elements within circular con-struction.

Arginine shows Jekyll and Hyde behavior in several respects. It participates in protein folding via ionic and H-bonds and cation-pi interactions; the charge and hydrophobicity of its side chain makes it a disorder-promoting amino acid. Its methylation in histones; RNA binding proteins; chaperones regulates several cellular processes. The arginine-centric modifications are important in oncogenesis and as biomarkers in several cardiovascular diseases. The cross-links involving arginine in collagen and cornea are involved in pathogenesis of tissues but have also been useful in tissue engineering and wound-dressing materials. Arginine is a part of active site of several enzymes such as GTPases, peroxidases, and sulfotransferases. Its metabolic importance is obvious as it is involved in production of urea, NO, ornithine and citrulline. It can form unusual functional structures such as molecular tweezers in vitro and sprockets which engage DNA chains as part of histones in vivo. It has been used in design of cell-penetrating peptides as drugs. Arginine has been used as an excipient in both solid and injectable drug formulations; its role in suppressing opalescence due to liquid-liquid phase separation is particularly very promising. It has been known as a suppressor of protein aggregation during protein refolding. It has proved its usefulness in protein bioseparation processes like ion-exchange, hydrophobic and affinity chromatographies. Arginine is an amino acid, whose importance in biological sciences and biotechnology continues to grow in diverse ways.

This article presents the development of an innovative Maximum Power Point Tracking (MPPT) strategy, utilizing a Particle Swarm Optimization (PSO) algorithm to improve the effectiveness of PV systems and expedite convergence. The new MPPT method incorporated a unique Swarm Self-Reinforcement Mechanism (SSRM) within the PSO algorithm, targeting quick convergence and excellent tracking accuracy. This approach enables the PSO to eliminate the fitness function that has the lowest value and subsequently reinforce it in the next iteration, revolving around the global maximum power point (GMPP). By applying this novel PSO-based method, the MPPT performance of PV systems was significantly improved, facilitating the algorithm to proficiently navigate through the solution space and quickly locate the GMPP, even in rapidly changing environmental conditions. The outcomes derived from this novel approach were contrasted with other algorithmic optimization methods, validating its superior convergence speed and tracking accuracy. Different swarm sizes were examined using SSRM, and the optimal swarm size for the system employing MPPT was identified to achieve the lowest convergence time (CT). The results showcased the impressive performance capabilities of this novel strategy, resulting in a time con-traction of up to 28% compared to the conventional PSO technique, where the optimal swarm size was found to be 5. This achievement marks a significant milestone in the evolution of PSO-based MPPT techniques, and paves the way for future advancements in this exciting field.

Website defacement is an illegal electronic act of changing a website. In this paper, robust machine learning classifiers’ capabilities were exploited to select the best input feature set for evaluating a website’s defacement risk. Zone-H, a private organization, offered us a defacement mining dataset. A sample of 93644 datapoints was concisely pre-processed and used for modelling purposes. Considering multidimensional features as input, reason and hackmode variables were chosen as outputs. Massive machine learning models were examined; however, decision tree (DT), k-nearest neighbour (k-NN), and random forest (RF) were the most powerful algorithms used to predict the target model. The input variables 'domain', 'system', 'web_server','redefacement', 'type', 'def_grade', and 'reason/hackmode' were tested and used to shape the final model. Using the cross-validation (CV) technique, the model’s key performance factors were calculated and reported. After calculating the average scores for the hyperbolic metrics (i.e., max-depth, min-sample-leaf, weight, max-features, and CV), both targets were evaluated, and the learning algorithms were ranked as RF, DT, and k-NN. The reason and hackmode variables were thoroughly analysed. The average score accuracies for the reason and hackmode targets were 0.85 and 0.585, respectively. The results showed a significant development in terms of modelling and optimizing website defacement risk. The study also successfully addresses the main cybersecurity concerns, in particular website defacement.

In this work, we tried to emphasize whole transcriptome expression changes in the Wistar rats brainstem two hours after acute stress. Most of the genes were upregulated. We detected massive shift of neuropeptides Crh, Trh,Cga, Tshb, Uts2b, Tac4, Lep and neuropeptide receptors Hcrtr1, Sstr5, Bdkrb2, Crhr2 signaling, as well as Glutamate Grin3b, Grm2 and GABA Gpr156, Acetylcholine Chrm4,Chrne, Adreno- Adra2b receptors expression uprising. Intensive increase in expression of intermediate filaments Krt83/Krt86/Krt80/Krt84/Krt87/Krt4/Krt76 and motor proteins Myo7a, Klc3 was detected. Remarkably, at this time we also observed signs of microglia activation. Both expression of anti-inflammatory cytokines Il13, Ccl24 and proinflammatory cytokin’s receptors Il9r, Il12rb1, Tnfrsf14, Tnfrsf13c, Tnfrsf25, Tnfrsf1b were increased. In the Wnt signaling pathway, we have seen increased expression of ligands-receptors Wnt1, Wnt11, Ror2, and also negative regulators Notum, Sfrp5, Sost. Also we conducted cDNA libraries normalization with duplex specific nuclease and compared results. On the basis of our RNAseq data, we chose reference genes for RT-qPCR best suitable for experiments with acute stress.

The advent of artificial intelligence has ushered in a new era of digital tools, including chatbots and virtual assistants, for educational purposes. ChatGPT, an advanced language model, has gained popularity as an educational aid. However, concerns have emerged regarding its potential negative impact on student learning behavior. This experimental research study investigates the influence of ChatGPT on student learning behavior and offers insights into its potential drawbacks.

Renal cell carcinoma (RCC), alternative term for kidney cancer, is becoming more common worldwide each year, and there are many different contributing factors. Among all cancers, RCC is the 14th most prevalent; and it ranks as the 14th and 9th most prevalent cancer overall for women and men respectively. RCC cases increased by more than 430,000 in 2020. While disease burdens are highest in Eastern Europe (Belarus and Russia) and North America (Canada and the United States), Africa, Asia, and Latin America are predicted to report increase in prevalence as these regions embrace change in lifestyle. The majority of RCC cases are accidentally found on imaging, and survival is greatly impacted by the disease stage at diagnosis, with a metastatic cancer having a 5-year survival rate of 12%. As a consequence of early discovery and more improved treatments, RCC mortality has declined. The key epidemiologic variables of RCC include vast regional and geographical heterogeneity in prevalence rates, and the cause is largely unclear. Recognized risk factors include smoking, being overweight, having previous episodes of hypertension, and suffering chronic renal illness. Unexpectedly swift, RCC diagnosis and therapy have advanced. RCC prevalence continues to rise although survival rates have sharply improved. Cancer survival and treatment have improved, and more gains are projected as a result of clinical and translational research. In this review, kidney cancer statistics and recent literatures are examined on a global scale. It covered aspects of kidney cancer, including its epidemiology, causes, risk factors, current immunotherapy, chances for prevention, and future planning.

Deep Learning (DL) has made significant advances in computer vision with the advent of Vision Transformers (ViT). Unlike Convolutional Neural Networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then use residual connections to feed these features directly into a fully networked multilayer perceptron head. In hospitals, hematologists prepare peripheral blood smears (PBSs) and read them under a medical microscope to detect abnormalities in blood counts such as leukemia. However, this task is time-consuming and prone to human error. This study investigates the transfer learning process of Google ViT and ImageNet CNNs to automate the reading of PBSs. The study used two online PBS datasets, PBC and BCCD, and transferred them into balanced datasets to investigate the influence of data amount and noise immunity on both neural networks. The PBC results show that Google ViT is an excellent DL neural solution for data scarcity. The BCCD results show that Google ViT is superior to ImageNet CNNs in dealing with unclean, noisy image data because it is able to extract both global and local features and use residual connections, despite the additional time and computational overhead.

This study focuses on the increased risk of high heat release and asphyxiation (toxic gas poisoning) in the event of a fire of polyurethane (PU) and MDF-based building materials, which are commonly used in building fires. Among them, polyurethane (PU) building materials are essential for buildings except in Europe and some other countries due to their excellent thermal insulation performance, but problems of short-term heat release and spread of toxic gases in the event of a fire continue to occur. To overcome these problems, researchers are actively working on introducing various flame retardants into building materials. Therefore, in this study, we produced a laboratory-sized (500mm*500mm) plate flame retardant board that can be utilized as a building material with a lower heat release rate and a lower toxicity index by mixing expanded graphite and ceramic binder as flame retardants in a main material based on the cellulose of waste paper by replacing the existing building materials with a hot-press method. According to the ISO-5660-1 test on the heat release rate of the plate flame retardant board, the THR value was 2.9 (MJ/m2) for 10 minutes, showing an effect of reducing the THR value by 36.3 (MJ/m2) compared to the THR value of 39.2 (MJ/m2) of the specimen made using only paper. In addition, the toxicity index of the flame retardant board was checked through the NES 713 test. As a result, the test specimen showed a toxicity index of 0.7, which is 2.4 lower than the toxicity index of 3.1 of MDF, which is utilized as a conventional building material. Based on the results of this study, the cellulose fire retardant board showed the effect of reducing the heat release rate and toxicity index of building materials in a building fire, which reduces the risk of rapid heat spread and smoke toxicity. This has the potential to improve the evacuation time (A-SET) of evacuees in fires. It is also important to show that recycling waste paper and utilizing it as the main material for building materials can be an alternative in terms of sustainable development.

Transportation tasks in nursing are common and shorten the time for direct patient care in times of nursing shortage and an aging society. There is a lack of research on transportation needs, with most studies focusing on overall nursing task analysis without a deeper analysis of transportation tasks. In July and September 2023, we conducted weekly observations of nurses to assess clinical transportation needs. We aim to understand the economic impact and the methods nurses use for transportation tasks. We conducted a participant observation using a standardized app-based form over a seven-day observation period in two rural clinics. N=1,830 transports were made by nurses and examined by descriptive analysis. Non-medical supplies account for 27.05 % (n=495) of all transports, followed by medical supplies at 17.32 % (n=317), pharmacotherapy at 14.10 % (n=258) and other other categories like meals or drinks contributing 12.68 % (n=232). Most transports had a factual transport time of under a minute, with patient transport and lab samples displaying more variability. In total, 77.15 % of all transports were made by hand. Requirements to collect items or connect transports with patient care were included in 5 % of all transports. Our economic evaluation spotlighted meals as the most costly transport, with 9,596.16€ p.a. in the observed clinics. Budget-friendly robots would amortize over one year by transporting meals. We support understanding nurses’ transportation needs via further research on assistive robots to validate our findings and determine the feasibility of transport robots.