Tobacco use, most people would say. Smoking tobacco increases the risk of developing many types of cancer and is responsible for approximately one-third of all cancer deaths. The association between tobacco use and lung cancer is well known; lung cancer occurs about 20 times more often in heavy smokers than in nonsmokers [1]. However, many lung cancers are diagnosed in never smokers [2], and most smokers do not develop lung cancer [3,4].

Ubiquitin-specific protease 2 (USP2) maintains mitochondrial integrity in culture myoblasts. In this study, we investigated molecular mechanisms underlying the protective role of USP2 on mitochondria. Knockout (KO) of the Usp2 gene or chemical inhibition of USP2 induced robust accumulation of mitochondrial reactive oxygen species (ROS), accompanied by defects in mitochondrial membrane potential, in C2C12 myoblasts. ROS removal by N-acetyl-L-cysteine restored the mitochondrial dysfunction induced by USP2 deficiency. Comprehensive RT-qPCR screening and following protein analysis indicated that both genetic and chemical inhibition of USP2 elicited a decrease of uncoupling protein 2 (UCP2) at mRNA and protein levels. Accordingly, the introduction of a Ucp2-expressing construct effectively recovered mitochondrial membrane potentials, entailing an increment of the intracellular ATP level in Usp2KO C2C12 cells. In contrast, USP2 deficiency also decreased peroxisome proliferator-activated receptor  coactivator 1 (PGC1 protein in C2C12 cells, while it upregulated Ppargc1a mRNA. Overexpression studies indicate that USP2 potentially stabilizes PGC1 in an isopeptidase-dependent manner. Given that PGC1 is an inducer of UCP2 in C2C12 cells, USP2 might ameliorate mitochondrial ROS by maintaining the PGC1–UCP2 axis in myoblasts.

Laser-induced fluorescence spectroscopy (LIFS) is actively used for remote sensing of atmospheric aerosols and currently is one of the most sensitive and selective techniques for determining small concentrations of substances inside particles. The use of high-power femtosecond laser sources for LIFS-based remote sensing of aerosol contributes to the development of new-generation fluorescence atmospheric lidars since it makes it possible overcoming the energy threshold for the nonlinear-optical effects of multiphoton absorption in particles and receiving the emission signal at long distances in the atmosphere. Our study is aimed to the development and experimental demonstration the technique of nonlinear laser-induced fluorescence spectroscopy (NLIFS) based on the remote excitation of aerosol fluorescent emission stimulated by a spatially-structured high-power femtosecond laser pulse. Importantly, for the first time to our knowledge, we demonstrate the advances of using stochastically-structured plasma-free intense light channels (postfilaments) specially formed by propagation of femtosecond laser radiation through a turbulent air layer for improving NLIFS efficiency. A multiple increase in the received signal of two-photon-excited fluorescence of polydisperse dyed aqueous aerosol by the structured postfilaments is reported.

Tumor cells display abnormal growth and division, avoiding the natural process of cell death. These cells can be benign (non-cancerous growth) or malignant (cancerous growth). Over the past few decades, numerous in vitro or in vivo tumor models have been employed to understand the molecular mechanisms associated with tumorigenesis in diverse aspects. However, our comprehension of how non-tumor cells transform into tumor cells at molecular and cellular levels remains incomplete. The nematode C. elegans has emerged as an excellent model organism for exploring various phenomena, including tumorigenesis. Although C. elegans does not naturally develop cancer, it serves as a valuable platform for identifying oncogenes and the underlying mechanisms within a live organism. In this review, we describe three distinct germline tumor models in C. elegans, highlighting their associated mechanisms and related regulators. Given the conservation of many of the regulators implicated in C. elegans tumorigenesis, it is proposed that these unique models hold significant potential for enhancing our comprehension of the broader control mechanisms governing tumorigenesis.

The UK government and many international experts have pointed out that nuclear energy has an important role to play in the transition towards a decarbonized energy system since it is the only freely manageable very low-carbon energy technology with 24/7 availability to complement renewables. Besides current investments in light water reactor technologies, we need innovation for improved fuel usage and reduced waste creation, like offered by iMAGINE, for the required broad success of nuclear technologies. To allow quick progress into innovative technologies like iMAGINE and their regulation, a timely investment into urgently needed experimental infrastructure and expertise development will be required to assure the availability of capacities and capabilities. The initial steps to start the development of such a new reactor physics experimental facility to investigate molten salt fast reactor technology are discussed and a stepwise approach for the development of the experimental facility is described. The down selection to the choice for a diverse control and shutdown system is described through manipulating the reflector (control) and splitting the core (shutdown). The developed innovative core design of having the two core parts in two different rooms opens completely new opportunities and will allow to manifest the request for separated operational and experimental crews, as nowadays requested by regulators into the built environment. The proposed physical separation of safety relevant operational systems from the experimental room should on the one hand help to ease the access to the facility for visiting experimental specialists. On the other hand, the location of all safety relevant systems in a now separated access-controlled area for the operational team will limit the risk of misuse through third party access. The planned experimental programme described with the major steps: core criticality experiments, followed by experiments to determine the neutron flux, neutron spectrum, and power distribution as well as experiments to understand the effect of changes in reactivity and flux as a function of salt density, temperature and composition change.

This study investigates the effects of chanting Nam-Myoho-Renge-Kyo by a long-term Nichiren Shoshu Buddhist practitioner on sound frequencies (A), brain activity (B), and microbial metabolism(C).A. Analysis of sound frequencies: Spectral analysis of chanting revealed peaks at 8 Hz and 116 Hz, corresponding to the first Schumann resonance and a frequency linked to chloride ion movements, respectively. Additionally, five peaks (417, 528, 639, 741, 852 Hz) corresponding to solfeggio frequencies were identified. These frequencies are known to exert a positive impact on the human endocrine and autonomous nervous systems; improve survival of human brain cells; decrease anxiety in rats; reverse cognitive and endocrine deficits in zebra fish; reduce total concentration of reactive oxidative species in brain tissue. B. Study of Brain activity: Brain activity changes were measured using functional near-infrared spectroscopy. Prefrontal cortex activity increased modestly during chanting compared to a pre-chanting baseline, but significantly increased afterwards. This suggests a shift towards focused attention during chanting and enhanced activity afterward. C. Effects on microbial metabolism: Probiotic cultures exposed to chanting, either directly or indirectly, showed increased metabolic activity. This suggests local and non-local effects, similar to previously reported phenomena. Importantly, this study clarifies that the spiritual practice of Nichiren Shoshu Buddhism transcends mere neurophysiological explanations. While brain activity and other bodily processes may be correlated with the practice, the religious and spiritual experience of chanting Nam-Myoho-Renge-Kyoencompasses a mystical dimension that, though not contradicting science, cannot be fully explained by scientific methods alone.

The processability of conductive polymers such as polyaniline (PANI) still poses a challenge due to their properties. The use of stabilizers, compatible and able to interact with PANI, to obtain dispersible and stable colloids is described in this work. To this aim, potato starch has been used as a steric stabilizer for the preparation of polyaniline (emeraldine salt, ES)/starch biocomposites, by exploiting oxidative polymerization of aniline in aqueous solutions containing different ratios of aniline and starch (% w/w). The polyaniline/starch biocomposites were subjected to structural and spectroscopic analyses, thermal analysis, morphological analysis and electrochemical analysis. The samples were then tested for their dispersibility/solubility in various organic solvents. The results showed the formation of PANI/starch biocomposites with an overall smaller size than starch particles, with improved aqueous dispersion and solubility in organic solvents. Although X-ray diffraction and differential scanning calorimetry analyses indicated a loss of crystallinity in the biocomposites, the cyclic voltammetry tests showed that all PANI ES/starch biocomposites display improved redox exchange properties.

Last Chance Tourism (LCT) is an increasingly popular phenomenon whereby tourists seek encounters with vanishing landscapes, cultures, and endangered species. However, there are concerns that it is not sufficiently ecologically informed, has a large carbon footprint, and may put further pressure on vulnerable ecosystems and communities. The Arctic has emerged as a major global frontier for LCT, and at the same time is at the forefront of disruptive and accelerating climate change. Here a review of important LCT literature is combined with a review of key insights from the concept of Ecological Grief, which calls for explicitly mourning the losses of formerly ecologically rich landscapes, species diversity, and traditional knowledge. While there is currently insufficient engagement with grief and mourning in LCT, Ecological Grief can provide a new research focus as well as a pathway to share empathy, concern, and sorrow between scientists, communities, and visitors—thereby offering an alternative way to critically reflect upon our connections with the vanishing cryosphere in the Anthropocene.

Despite ample warning and significant lead time, global society has not acted sufficiently to combat climate change, and global carbon dioxide emissions are now about 60% higher today than in 1990 [1]. This paper uses marine fisheries as an analog model to compare with the many similar management issues faced with global climate change. Both marine fisheries and global climate change are complex systems that have similar properties that make management very difficult. A simple fishery prototype model is used to educate citizens about similar issues of dynamic complexity found in climate change models. We highlight how our slow reaction time to global climate change can be thought of as a mismatch between our cognitive abilities and the nature of global collective problems. Understanding the history and system structure of marine fisheries can provide insight into managing global climate change. We suggest ways to improve communication between science and citizens for updating mental models and changing climate policy.

This article develops algorithms for the characterization and the visualization of micro-scale features by using a small number of sample points, and with a goal to mitigate for the measurement shortcomings which are often destructive or time consuming. We implement the algorithms to rapidly examine the microscopic features of a Microelectromechanical System (MEMS) surface. Such images are highly dense; therefore, traditional image processing techniques might be computationally expensive. The contribution of this research include first, we develop local and global algorithm based on modified Thin Plate Spline (TPS) model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives by using low resolution images. Second, we obtain a bending energy algorithm from our modified TPS model, and use it to filter out image defects. Finally, we develop a computationally efficient Windowing technique, which combines TPS and Linear Sequential Estimation (LSE), to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.

In recent years, urbanization and industrialization have significantly increased the levels of outdoor noise pollution, affecting the quality of life in residential areas. In Uzbekistan, rapid development in urban centers has led to heightened concerns about the impact of noise on residents' health and well-being. Noise pollution can result from various sources, including traffic, construction, and industrial activities, causing disturbances and potential health issues such as stress, sleep disorders, and cardiovascular problems. Addressing this issue is crucial for creating a healthier living environment. This article explores effective strategies for mitigating the impact of outdoor noise on residential buildings in Uzbekistan.

Facial Emotion Recognition (FER) is crucial across psychology, neuroscience, computer vision, and machine learning due to the diversified and subjective nature of emotions, varying considerably across individuals, cultures, and contexts. This paper investigates the impact of histogram equalization, data augmentation and model optimization strategies on three well-known FER datasets using pre-trained VGG models. Additionally, this paper showcases the effectiveness of different regularization techniques, callbacks, and learning schedulers in enhancing model performance by conducting extensive experiments. The model evaluation is discussed in terms of the following metrics: Accuracy, Area Under the Receiver Operating Characteristic Curve (AUC-ROC), Area Under the Precision-Recall Curve (AUC-PRC), and Weighted F1 score. Notably, the fine-tuned VGG models exhibit state-of-the-art performance compared to more complex conventional transfer learning models resulting in accuracies of 100%, 95.92%, and 69.65% on the CK+, KDEF, and FER2013 datasets, respectively.

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed in January 17 and 26-27, 2013 under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms, but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations of foF2 from median values observed during the night/morning periods on 13-15 and 20-23 January which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in foF2, h’F and daily averaged foF2 values with quasi-period of 5-8 days and peak-to-peak amplitude from about 1MHz to 2 MHz (from 20% to 40%) and ~40 km are observed during the 9-28 January, after registration the occurrence of the major SSW event on 6-7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionosheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F-region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms.

The rehabilitation of the road embankments alongside the irrigation canal, which is constructed on a Bangkok soft clay foundation, has resulted from land use growth for several decades. As a result, the embankment is always confronted with the problem of instability. Numerous articles have demonstrated that rapid drawdown of the water level in the canal could be one of the most significant reasons, whereas vehicle cyclic loading may potentially contribute to some effect of the embankment failure. To explore and assess the effects of the influence factors, the finite element method (FEM) and conventional and dynamic triaxial approaches were employed. The study also investigated the consequences of varying thicknesses of soft clay and cyclic loading with different magnitudes and frequencies. Consequently, cyclic loading can lead to an augmentation in strain distribution and excess pore water pressure. Likewise, more significant deformation and excess pore water pressure were induced by a lower frequency and deeper thickness of soft clay compared to a higher frequency and thinner thickness. In brief, vehicle repetitive loading is one of the primary factors contributing to embankment failure, with the threshold stress being approximately three-fourths of the undrained shear strength. In contrast, threshold strain is approximately one to two-fold of the monotonic strain condition.

This paper proposes a product design model for internalising users’ positive experiences through attachment. First, the research commences with a literature review to define the concepts and research status of positive experience design (PED) and product attachment. Subsequently, the design model is constructed, accompanied by relevant formulas for concept generation. Finally, the model’s validity is verified through a workshop, and its effectiveness is evaluated and discussed using the USE questionnaire. This study incorporates the seven factors of product attachment to activate positive states within the user–product relationship and facilitate the cultivation of positive thinking. Grounded in theories of PED and embracing a product attachment perspective, the attachment-driven PED model offers a systematic approach for generating design concepts that are relevant to user experience.

The ambient air quality data for particulate matter as well as criteria of gaseous pollutants were assembled during December 2013 to December 2015 from the Continuous Air Quality Monitoring Station (CAMS) located at Agrabad, Chittagong. The observation showed that during April- October, 24 hour average concentration of PM10 and PM2.5 were within the National Ambient Air Quality Standard (NAAQS) level but it increased occasionally by more than two and a half times during the whole non-monsoon period (November-March). The highest values found of PM2.5 were 321.1 µg/m³ in January, 2013 and 220.34 µg/m³ in December 2015. Whether, the highest alarming concentration of PM10 was reported as 474 µg/m3 in January 2007. The other gaseous pollutants such as SO₂, NO₂, O₃, CO and Hydrocarbons remain well within the permissible limit except dry non-monsoon period. The yearly average increase of Air Quality Index (AQI) value indicates the growth rate of air pollution in Chittagong city. The main responsible pollutant for air pollution is found PM_2.5.

Orthogonal Frequency Division Multiplexing (OFDM) while being an efficient scheme for high data rate wireless communications has drawbacks such as higher Peak-to-Average Power Ratio (PAPR). To reduce PAPR, use of multiple signal representation technique such as Partial Transmit Sequence (PTS) is one of the favored techniques. However, the use of conventional PTS technique need excessive number of complex calculations in order to search for all permissible combinations of phase sequences causing steep increase in complexity in terms of complex computations. Paper aims to reduce the cumbersome process of phase selection by making use of the similarity of the phase vectors. The phase vectors are obtained sequentially and thus minimize the number of changes from one phase vector to another. Theoretical analysis shows that computational complexity is significantly reduced with the help of this proposed novel technique. We have also demonstrated that PAPR values are similar i.e. PAPR reduction capability remains similar but at reduced complexity.

Due to the vast conformational space proteins can adopt, accurate and efficient prediction of protein structure remains still a challenging task, coupled with the intricacies of interatomic interactions and the limitations of current computational models in effectively navigating this complex molecular landscape. Additionally, the lack of comprehensive experimental data for all protein structures further exacerbates the difficulty in reliable machine learning-based prediction of the three-dimensional conformations of the proteios building block of life. Geometrically, Cartesian coordinate system (CCS, X, Y and Z) and spherical coordinate system (SCS, ρ, θ and φ) are two interconvertible coordinate systems, and are like two sides of one coin. Since the beginning of Protein Data Bank (PDB) in 1971, CCS has been the default approach to specify atomic positions with X, Y and Z in PDB. In this manuscript, therefore, I present a novel method for the reversible spherical geometric conversion of protein backbone structure coordinate matrices to three independent vectors: ρ, θ and φ. This reversible conversion facilitates lossless extraction of essential structural features from protein backbone structural data, enabling the development of advanced novel algorithms for protein structure prediction in future. In short, this inter-atomic SCS approach offers a comprehensive yet efficient means of representing protein backbone geometry, leveraging spherical coordinates to capture spatial relationships in a compact and intuitive inter-atomic manner, and to provide a robust framework for reversible feature extraction for the ongoing efforts in advancing the field of protein structure prediction, the holy grail of computational structural biology.

Tomato brown rugose fruit virus (ToBRFV) is an emerging tobamovirus infecting tomatoes and peppers. Due to its ability to trigger seed contamination, efficient mechanical transmission, and to break the popular resistance genes (Tm-1, Tm-2 and Tm-22), the virus has resulted in a global pandemic on greenhouse tomato production in recent years despite the implementation of strict hygiene and disinfection measures. The objective of this study was to evaluate whether ToBRFV can be transmissible through recirculating hydroponic systems and search for effective approach to contain its spread under such circumstances. We not only detected the presence of ToBRFV in the runoff water solutions collected from ToBRFV-infected tomato greenhouses, but also demonstrated the infectivity of detected virus through initiating ToBRFV infection on tomato plants using bioassay. We then conducted treatment using cold plasma-generated ozone on ToBRFV-contaminated water reservoir and further assessed the efficacy of the treatment to inac-tivate the virus. Results showed the effectiveness of the cold-plasma ozone treatment was de-pendent on the ozone concentrations (0.1 mg/L to 1.0 mg/L), the periods of exposure (24 min to 72 min), and the relative virus titers (1:100 to 1:10,000 - dilution of virus-infected tissue extract), demonstrating the cold-plasma ozone treatment could offer a promising solution to cope with the potential ToBRFV spread through a recirculating hydroponic system in a greenhouse.

Pharmacy compounding, the art and science of preparing customized medications to meet individual patient needs, is in a verge of transformation. Traditional methods of compounding often involve manual and time-consuming processes, presenting challenges in terms of consistency, dosage accuracy, quality control, contamination and scalability. However, the emergence of cutting-edge technologies has paved a way for a new era for pharmacy compounding, promising to redefine the way medications are prepared and delivered as pharmacy-tailored personalized medicines. In this multi-site study, more than 30 hospitals and community pharmacies from 8 countries in Europe utilized a novel automated dosing approach inspired by 3D printing for compounding of non-sterile propranolol hydrochloride tablets. CuraBlend® excipient base, a GMP manufactured pharma-ink, intended for automated compounding applications was used. A standardized study protocol to test the automated dosing of tablets with variable weights was performed in all participating pharmacies in 4 different iterative phases. Integrated quality control was performed with an in-process scale and NIR spectroscopy supported by HPLC content uniformity measurements. In total, 6088 propranolol tablets were produced at different locations during this study. It was shown that the dosing accuracy of the process increased from about 90% to 100% from phase 1 to phase 4 by making improvements to the formulation and the hardware solutions. The results indicate that through this novel automated and quality-controlled compounding approach extemporaneous pharmacy manufacturing can take a giant leap forward towards automation and digital manufacture of dosage forms in hospital pharmacies and compounding pharmacies.

Vehicular ad hoc networks (VANET) are a subset of mobile ad hoc networks used to communicate between vehicles and infrastructure. During vehicular congestion communication, nodes compete to acquire channels, causing the channels to become congested. The congestion on the vehicle network results in increased delay and packet loss, resulting in reduced VANET performance. To address this problem, we developed a load-aware and priority adaptive traffic congestion control method in vehicular ad hoc networks (VANETs). The proposed scheme identifies less-congested road segments based on the network's load and reduces traffic congestion by suggesting other routes between nearby roadside units (RSUs). This research aims to improve the efficiency of the vehicular environment by utilizing the movement of vehicles with (RSUs) and sharing the traffic load between them. Simulation results demonstrate the effectiveness of the proposed protocol in reducing congestion and enhancing the overall performance of VANETs. To validate the proposed algorithm, we have implemented and tested the proposed algorithm using Network Simulator 3 (NS3) for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication scenarios and computed the performance of the algorithm on different parameters of the network. The simulation result of the proposed load aware and priority adaptive traffic congestion control method in VANET improved the packet delivery ratio, packet lost ratio, and end-to-end delay by 96%, 4.1%, and 1102 milliseconds, when compared to TDCCA value of 92%, 5.7%, and 1154 milliseconds, respectively

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

Pagiophloeus tsushimanus, a new record of wood-boring pest first reported in China in 2014, has significantly infested Cinnamomum camphora across various administrative districts in Shanghai. And it shows a concerning trend of spread. The larval stage of the insect, being concealed within the trunks of C. camphora, exhibits characteristics such as hidden activity, strong destructiveness, and difficulty in control. This severely affects the normal growth of the host trees. While the primary host plant for P. tsushimanus is the C. camphora, preliminary observations have shown that the pest can also complete its life cycle on Cinnamomum chekiangensis and Phoebe chekiangensis. Both of them are significant species for urban greening. To explore the host selection preference of this beetle, this study investigates the olfactory selection behavior of adult P. tsushimanus towards C. camphora, C. chekiangensis, and P. chekiangensis. Results from choice tests, no-choice tests, and "Y"-shaped olfactometer experiments indicated that both male and female adults exhibited a feeding preference for C. camphora branches, with females showing a preference for laying eggs on C. camphora branches as well. Behavioral responses demonstrated a positive chemotaxis towards volatiles from C. camphora and a negative chemotaxis towards volatiles from C. chekiangensis and P. chekiangensis. Overall, the findings suggest that both male and female adults have a selective preference for volatiles emitted by C. camphora. These provides a theoretical basis for monitoring and controlling host shift occurrences in P. tsushimanus.

The dominant part of energy performance of a building consists of consumption of heating and lighting. Both heating and lighting systems of buildings work at their designed efficiency for most of the buildings’ lifetimes. Interference with existing systems is costly considering replacements and construction adjustments. Therefore, considerable effort must be put into the design of these systems during the building design phase. The article is focused on luminaire layout design strategy, which affects the number of luminaires in a building and therefore their power consumption and the sustainability of the building. A genetic algorithm with radiosity implemented has been used to find suitable placements of luminaires of a single type in a model room to decrease the number of luminaires as much as possible. Three outcomes of optimal luminaire layout design are presented in this paper, including design strategy conclusions. Results of calculation outcomes are verified by software DIALux, that is commonly used for designing lighting systems.

The presenting pattern of celiac disease (CD) at diagnosis in children has changed over time, with a reduction of malabsorption-related phenotypes and an increase in regular or even excessive growth patterns. We retrospectively reviewed the body mass index (BMI) distribution of all patients with a new diagnosis of CD made in a Pediatric Gastroenterology Outpatient Clinic in 1990-2011, compared to those diagnosed in 2012-2022, according to their clinical and serological characteristics. The 1990-2011 and 2012-2022 cohorts included 250 (M:F=90:160, mean age 7.3±6.1 years) and 243 children (M:F=81:162, mean age 7.1±3.7 years, NS), respectively. The prevalence of underweight (UW) was higher in the 1990-2011 cohort (61/250, 24.4% in 1990-2011 vs. 31/243, 12.7% in 2012-2022, p=0.0001), whereas that of overweight (OW) and obese (OB) subjects was significantly higher in 2012-2022 (10/250, 4% in 1990-2011 vs. 24/243, 9.9% in 2012-2022, p=0.012, and 1/250, 0.4% in 1990-2011 vs 8/243, 3.3% in 2012-2022, p=0.018, respectively). In both cohorts, gastrointestinal symptoms were more frequent in OW/OB than in UW children (6/11, 54.5% vs. 5/61, 8.2% in 1990-2011, p<0.0001, and 24/32, 75% vs. 10/31, 32.3%, p<0.0001 in 2012-2022) and the extent of anti-transglutaminase antibodies increase was similar in OW/OB and UW subjects. The prevalence of children with a normal or even high BMI at CD diagnosis has increased in the past three decades, therefore CD should be suspected regardless of the BMI status.

Coal fly ash (CFA) generated from coal-fired power plants (C-FPPs) is continuing to be an environmental health concern due to its potential to contaminate groundwater, surface water, air, and soil, leading to the degradation of land. This study investigated the effectiveness of Helichrysum splendidum Less. for phytoremediation of CFA-polluted sites by conducting pot trials experiments in 14 weeks. Plants of the same age were transplanted into CFA collected from Hendrina Power station to assess their potential in assimilating metallic pollutants (As, Cd, Co, Cu, Mn, Ni, Pb, and Zn) into their tissues and untreated plants were used as controls. Inductively coupled plasma-mass spectrometry was used to quantify the amount of trace elements in samples and the translocation factor (TF) and bioconcentration factor (BCF) were determined to evaluate the phytoremediation potential of Helichrysum splendidum. The results revealed that higher concentrations of As, Ni and Zn were accumulated in the aerial parts as indicated by the TF values greater than 1. In contrast, higher amounts of Cu, As and Zn were found in the roots for CFA grown plants, as demonstrated by their BCF values 1.22, 1.19 and 1.03, respectively. Although CFA medium had restricted growth of some plants as compared to the controls, the results showed an interesting removal efficiency ranging between 18.0 to 56.7% with highest reported for Cu and Zn. Gas exchange analysis revealed that photosynthetic parameters were almost similar in the CFA and control soil pots. The study can confirm that Helichrysum splendidum has phytoextraction and phytostabilization potentials and can be effectively employed for restoration of CFA dams.

The paper examines the evolution and crucial role of energy communities in the context of the transition to renewable energy sources. Such communities are presented as an innovative and resilient response to the challenges posed by climate change. Their importance emerges from their ability to decentralise energy production, increasing local security and reducing dependence on non-renewable energy sources and external suppliers. However, despite the obvious benefits, the contribution highlights several challenges, such as the need for significant upfront investment and the presence of regulatory barriers that may hinder the integration of these solutions into existing energy systems. A detailed bibliometric analysis is used, focusing on specific research areas and using tools to map the most relevant keywords and emerging trends. The results of the bibliometric analysis highlight how energy communities are emerging as key players in the sustainability landscape, capable of addressing and overcoming contemporary environmental challenges. The research reaffirms the transformative potential of energy communities in promoting a more sustainable and resilient future.

In the quest for more efficient solar thermal systems, accurately determining the thermal emittance of low-emissive materials is crucial in determining the power losses. This paper describes the calorimetric method designed to precisely measure the thermal emittance of Selective Solar Absorbers (SSAs) to be used in High Vacuum Flat Plate Collectors (HVFPCs). The method's capability is demonstrated through the successful correction of thermal emittance values for copper samples of varying sizes, including dimensions down to 49 cm². Results highlight the method's potential to significantly reduce measurement errors associated with small-size and/or low-emittance samples, providing a path forward to improve the design and efficiency of SSAs. This research marks a significant step in advancing solar thermal technology by enabling emittance measurements with a precision better than 0.003, which is essential for the development of high-performance solar thermal absorbers. The method has also been applied to correct the thermal emittance value of SSA measured in previous measurement campaigns, and it allows a better estimation of the SSA efficiency conversion curve.

The potential adverse effects of coronavirus disease 2019 (COVID-19) vaccinations raise public concerns. Data from Taiwan’s Vaccine Injury Compensation Program (VICP) can provide valuable insights. This study analyzed preliminary application data for COVID-19 vaccine compensation in Taiwan’s VICP, focusing on applicants receiving vaccines between March 2021 and June 2022. Among the 2941 adverse events, 113 cases (3.8%) were deemed causally associated with vaccination, 313 (10.6%) were indeterminate, and 2515 (85.5%) had no causal association. Nearly half (47.6%) of applicants were over 60 years old, and 76.6% had a history of preexisting chronic dis-eases. Among the 426 vaccine-associated or indeterminate cases, the most common causes were hematological diseases and thrombosis. There were 920 mortality cases reported, and 97.4% were unassociated with vaccination. Only five deaths were judged to be associated with the COVID-19 vaccination, all involving the adenovirus vector vaccine and thrombosis with thrombocytopenia syndrome. In conclusion, most compensation applications were not causally linked to vaccination. Compared to other countries, the number of applications in Taiwan’s VICP is relatively high. These findings may indicate a need to adjust the application requirements for compensation in Taiwan’s program.

With the rapid development of gene therapy technology in recent years, its abuse as a method of sports doping in athletic has become a concern. However, there is still room for improvement in gene doping testing methods, and a robust animal model needs to be developed. Therefore, the purposes of this study were to establish a model of gene doping using recombinant adeno-associated virus vector-9 including the human erythropoietin gene (rAAV9-hEPO), and to establish a relevant testing method. First, it was attempted to establish the model using rAAV9-hEPO on mice. The results showed a significant increase in erythrocyte volume accompanied by an increase in spleen weight, confirming the validity of the model. Next, we attempted to detect proof of gene doping by targeting DNA and RNA. Direct proof of gene doping was detected using a TaqMan-qPCR assay with certain primers/probes. In addition, some indirect proof was identified in RNAs through the combination of a TB Green qPCR assay with RNA sequencing. Taken together, these results could provide the foundation for an effective test for gene doping in human athletes in the future.

WHO reported an estimated 249 million malaria cases and 608,000 malaria deaths in 85 countries in 2022. A total of 94% of malaria deaths occurred in Africa, 80 % of which were children under 5. In other words, one child dies every minute from malaria. The RTS,S/AS01 malaria vaccine, that uses the Plasmodium falciparum circumsporozoite protein (CSP) to target sporozoite infection of the liver, achieved modest efficacy. The Malaria Vaccine Implementation Program (MVIP), coordinated by the WHO and completed at the end of 2023, found that immunization reduced mortality by only 13%. To further reduce malaria death, development of a more effective malaria vaccine is a high priority. Three major malaria vaccine targets being considered are the level of sporozoite liver infection, merozoite red blood cell (RBC) infection, and mosquito midgut infection. These targets involve specific ligand-receptor interactions. However, current malaria vaccine candidates that target two major parasite population bottlenecks, liver infection and mosquito midgut infection, do not focus on such parasite ligands. Here we evaluate the potential of newly identified parasite ligands as novel malaria vaccine antigens.

Parkinson’s disease (PD) is a progressive neurodegenerative disease characterized by resting tremor, bradykinesia, rigidity, postural instability, that also includes non-motor symptoms such as mood dysregulation. Dopamine (DA) is the primary neurotransmitter involved in this disease, but cholinergic imbalance has also been implicated. Current intervention in PD is focused on replenishing central DA, which provides remarkable temporary symptomatic relief but does not address the neuronal loss and the progression of the disease. It has been well established that neuronal nicotinic cholinergic receptors (nAChRs) can regulate DA release and that nicotine itself may have neuroprotective effects. Recent studies have identified nAChRs in nonneuronal cell types including glial cells, where they may regulate inflammatory responses. Given the crucial role of neuroinflammation in dopaminergic degeneration, and the involvement of microglia and astrocytes in this response, glial nAChRs may provide a novel therapeutic target in prevention and/or treatment of PD. In this review, following a brief discussion of PD, we focus on the role of glial cells and specifically their nAChRs in PD pathology and/or treatment.

Cu₆Sn₅ whiskers precipitated in Sn3.0Ag0.5Cu/Cu interconnection in concentrator silicon solar cells solder layer were found and investigated after reflow soldering and during aging. Ag₃Sn fibers can be observed around Cu₆Sn₅ whiskers in the matrix microstructure, which can play an active effect on the reliability of interconnection. Different morphologies of Cu₆Sn₅ whiskers can be observed, and hexagonal rod structure is the main morphology of Cu₆Sn₅ whiskers. A hollow structure can be observed in hexagonal Cu₆Sn₅ whiskers, and a screw dislocation mechanism was used to represent the Cu₆Sn₅ growth. Based on mechanical property testing and finite element simulation, Cu₆Sn₅ whiskers were regarded as having a negative effect on the durability of Sn3.0Ag0.5Cu/Cu interconnection in concentrator silicon solar cells solder layer.

In air quality management, at urban and regional levels, road transport remains the cornerstone of residential, commercial, and industrial activities, and the vehicle exhaust emissions maintain the position of one of the key contributing sources. In Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads, contribute to as much as 50% of particulate matter pollution in a year. So, having access to a vehicle exhaust emissions inventory that is reliable and replicable is critical for air quality management and this exercise starts with access to vehicle stock numbers. These numbers are typically obtained from vehicle registration databases, traffic surveys, and other governmental records, and often require time consuming data cleaning protocols before they can used for emissions and pollution baseline analysis. This paper provides a cleaned and open-access vehicle stock database, as registered and in-use fleet, for the period covering 1993 and 2018, for all India and states, along with an estimate of age-mix of the vehicles using survival functions.

Friction stir processing (FSP), a severe plastic deformation process, was applied on commercially pure Ti to obtain an improved microstructure. The process yielded a refined microstructure and higher mechanical properties at room temperature (RT). Yet the microstructure was found to contain bright bands demonstrating high hardness values of about 500 HV. High resolution scanning electron microscopy (HRSEM) as well as electron back scattering diffraction (EBSD) analysis indicated that these bands were composed of extra-fine equiaxed α-Ti grains with an average radius of 1-2 microns. In addition, a retained β-phase was detected at the boundaries of these α-Ti grains, together with a small quantity of separate β grains. The results of a fractography study conducted on broken tensile specimens showed that the FSP’ed material was free of defects and that the fracture started at these bands. It is proposed that these bright bands are due to excessive deformation occurring during the processing stage, leading to an accelerated dynamic recrystallization (DRX) process. In turn, these heavy deformation regions act as a strengthening constituent, making the material superior to the parent material as far as its mechanical RT properties are concerned. Consequently, this means that FSP of CP-Ti has the potential to serve as an industrial means of improving the mechanical properties of the material.

The integration of generative AI (GAI) into the financial sector has brought about significant advancements, offering new solutions for various financial tasks. This review paper provides a comprehensive examination of recent trends and developments at the intersection of GAI and finance. By utilizing an advanced topic modeling method, BERTopic, we systematically categorize and analyze existing research to uncover predominant themes and emerging areas of interest. Our findings reveal the transformative impact of finance-specific large language models (LLMs), the innovative use of generative adversarial networks (GANs) in synthetic financial data generation, and the pressing necessity of a new regulatory framework to govern the use of GAI in the finance sector. This paper aims to provide researchers and practitioners with a structured overview of the current landscape of GAI in finance, offering insights into both the opportunities and challenges presented by these advanced technologies.

Based on the composite perspective of environment-building-resource(EBR), influencing factors of the greenness of rural buildings were sorted out by brainstorming and expert consultation, an innovative comprehensive evaluation system was constructed and the weight ofthe impact factors were calculated by fuzzy analytic network process(FANP). The EBR greenness comprehensive scoring standards of each influence factor were established by means of questionnaire, field measurement and numerical simulation. As a typical representative of human populated areas in southwest China, 13 villages in the second circle of Chengdu were selected as case study areas by means of the regional average distribution theory and minimum sampling criteria. Innovative combination of obstacle degree model and spatial interpolation analysis, the key factors affecting the greening of rural buildings were diagnosed. The results showed that, indoor thermal environment(E21), indoor light environment(E22), popularity of biogas facilities (R12), green building material usage(R13) have a significant impact on the EBR greenness score. The EBR score of study area shows a spatial distribution pattern of high in the west and low in the east, with extremely uneven scores in various dimensions. According to the key factors obtained from the systematic evaluation, the refined exploration of promotion strategies and measures was carried out, the greenness improvement suggestion was put forward.

Circular RNAs (circRNAs) are covalently closed RNAs that are present in all eukaryotes tested. CircRNAs are less abundantly expressed than mRNAs. Recent RNAseq analyses indicate that more than 800,000 circRNA isoforms exist in humans, which is more than twice the number of currently known mRNA isoforms. CircRNAs are generated through backsplicing that depends on pre-mRNA structures, which are influenced by intronic elements, for example primate-specific Alu elements, leading to species-specific circRNAs. CircRNAs are mostly cytosolic, stable and influence cells by sequestering miRNAs and RNA-binding proteins. We review the increasing evidence that circRNAs are translated into proteins using several cap-independent translational mechanisms, that include internal ribosomal entry sites, N6-methyladenosine RNA modification, adenosine to inosine RNA editing and interaction with the eIF4A3 component of the exon junction complex. CircRNA are translated under conditions that favor cap-independent translation, notably in cancer. CircRNA-encoded proteins are shorter than mRNA-encoded proteins and overall have a high propensity for phase separation. In summary, circRNA encoded proteins are translated under particular cellular conditions and contribute to proteome diversity and pathophysiology.

The use of thiosemicarbazones (TSCs) as ligands for the functionalization of nanoparticles (NP) for various purposes, such as the covalent immobilization is fueled by their modular character (thiosemicarbazides + carbonyl compound), allowing enormously broad variation of up to four substituents on the main R1R2C=N(1)–NH–C(S)–N(4)R3R4 core. For R1 and R2 we introduced di-2-pyridyl ketone for the coordination of metals and 9-anthraldehyde for luminescence. R3 and R4 substituents were varied for various purposes. Amino acids were functionalized at the N4 position to [R1R2TSC–spacer–amino acid] conjugates for future peptide conjugation or for direct anchoring to NP via their carboxylic function. Further direct NP anchoring functions such as phosphonic acid (OP(OH)2), glucose, o-hydroquinone, OH, and thiol (SH) were introduced with or without separation through hydrocarbon spacer units such as phenyl, cyclohexyl, benzyl, ethyl and methyl in [R1R2TSC–spacer–anchor group] conjugates. [R1R2TSC–spacer–end group] conjugates including OH, S-Bn (Bn = benzyl), NH-Boc (Boc = tert-butyloxycarbonyl), COOtBu, or N3 end groups were produced for the facile formation of amide, ester, or triazine conjugates through click chemistry. The synthesis of the thiosemicarbazides H2NH–C(S)–NR3R4 starting from amines, including amino acids, SCCl2 or CS2, and hydrazine and their condensation with dipyridyl ketone and anthraldehyde lead finally to 34 new TSC derivatives. They were synthesized in up to six steps with overall yields ranging from 10 to 85% and were characterized by a combination of elemental analyses, mass spectrometry, and magnetic nuclear resonance spectroscopy. UV-vis absorption and photoluminescence spectroscopy allowed to easily trace the dipyridyl imine and anthracene chromophores.

The layer-by-layer (LBL) fabrication method allows for controlled microstructure morphology and vertical component distribution, and also offers a reproducible and efficient technique for fabricating large-scale organic solar cells (OSCs). In this study, polymer D18 and PYIT-OD are employed to fabricate all-polymer solar cells (all-PSCs) using the LBL method. Morphological studies reveal that the use of additives optimizes the microstructure of the active layer, enhancing the crystallinity and charge transport capability. The optimized device with 2% CN additive significantly reduces bimolecular recombination and trap-assisted recombination. All-PSCs fabricated by the LBL method based on D18/PYIT-OD deliver a power conversion efficiency (PCE) of 15.07%. Our study demonstrates the great potential of additive engineering via LBL fabrication method in regulating microstructure of active layers, suppressing charge recombination, and enhancing the photovoltaic performance of devices.

Coal bottom ash (CBA) is a byproduct of coal-burning power plants. This material can be used as a fine aggregate replacement in concrete to reduce global natural material depletion. Concrete usage is increasing rapidly; subsequently, the industry’s carbon footprint is increasing. Using CBA in the construction industry will reduce the technical and economic problems associated with power plants by reducing solid waste. This project aimed to determine if adding new sustainable materials, such as CBA, to concrete will reduce natural raw material usage, energy consumption, and greenhouse gas emissions while improving performance. This study included two projects: comparing increased CBA content to the two-control project and determining the optimum content based on the compressive strength. The optimum CBA content is 50%, which reduces fine aggregate usage in a concrete mix by 50% while maintaining equivalent or better concrete strength than a pure Portland concrete mix without CBA. The air content of the concrete mix containing % CBA decreased with increased CBA content and compressive strength, possibly due to the spacing factor of the voids in the mix and CBA’s porous and fineness behavior. The CBA optimum content had a unit weight lower than the controls for both projects, which makes the CBA mix a lightweight concrete. Using this material can significantly reduce natural material usage and environmental harm by reducing CBA waste disposal and improving concrete performance.

Along with the familiar Rossby–Haurwitz waves, two-dimensional flows on the surface of a rotating sphere in the regime of zonostrophic turbulence harbour another class of waves known as zonons. Zonons are wave packets produced by energetic large-scale Rossby–Haurwitz wave modes `enslaving’ other wave modes. They propagate westward with the phase speed of the enslaving modes. Zonons can be visualized as enslaving modes’ `ringing’ in the enslaved ones with the frequencies of the former, the property that renders zonons non-dispersive. Zonons reside in high-shear regions confined between the opposing zonal jets yet they are mainly attached to westward jets and sustained by the ensuing barotropic instability. They exchange energy with the mean flow while preserving their identity in a fully turbulent environment, a feature characteristic of solitary waves. The goal of this study is to deepen our understanding of zonons’ physics using direct numerical simulations, a weakly non-linear theory, and asymptotic analysis, and ascertain that zonons are indeed isomorphic to solitary waves in the Korteweg - de Vries framework. Having this isomorphism established, the analysis is extended to eddies detected in the atmospheres of Jupiter and Saturn based upon the observed mean zonal velocity profiles and earlier findings that circulations on both planets obey the regime of zonostrophic macroturbulence. Not only the analysis confirms that many eddies and eddy trains on both giant planets indeed possess properties of zonons, but the theory also correctly predicts latitudinal bands that confine zonal trajectories of the eddies.

The Azores Archipelago is a collection of volcanic islands near northwestern Portugal in the Atlantic Ocean. Because of the importance of accurate environmental monitoring for the advancement of research, transportation and tourism, a LoRaWan Sensor Network was developed to monitor levels of air pollution across these islands. This study presents an approach to the implementation of a blockchain network that is both lightweight and scalable, with the goal of preventing man-in-the-middle attacks on the design of sensor networks.

Background: The aim of this audit is to evaluate the characteristics of dental infections requiring hospitalisations, which may help improve preventative and management policies. Methods: This study retrospectively evaluated the patients’ records admitted to a public hospital due to dental infections between 2018 and 2019. Results: A total of 102 patients, mostly in thirties with equal gender distribution were admitted with dental infections, presenting with pain (100%), swelling (99%), Trismus (40.2%), dysphagia (27.4%), fever (21%) >37°C, Tachycardia (24.75%) and Tachypnoea (9.3%). Most patients presented (68%) on weekends, outside regular working hours and public holidays. 54 (52.5%) patients had taken prior antibiotics. Dental Caries, smoking, mental health issues and illicit drug use were featured strongly. The majority of patients (56.4%) underwent treatment under local anaesthesia. The total length of hospital stay was 271 days (mean 2.66). Augmentin was the most prescribed antibiotics. Complications were reported in 8.8% patients, primarily related to airway compromise. Conclusion: Dental infections leading to hospitalizations continue to be a burden on the healthcare system. A notable finding was the presentations primarily on weekends, outside regular hours and public holidays and the majority requiring dental intervention under local anaesthesia. Provision of on call emergency dental services may reduce length of hospital stay and admissions.

Domestic crime, conflict, and instability pose a significant threat to many contemporary governments. These challenges have proven to be particularly acute within modern-day Mexico. While there have been significant developments in predicting intrastate armed and electoral conflict in various contemporary settings, such efforts have thus far been limited in their use of spatial as well as temporal correlations, as well as in the features they have consid- ered. Machine learning, especially deep learning, has been proven to be highly effective in predicting future conflicts using word embeddings in Convolutional Neural Networks (CNN) but lacks the spatial structure and, due to the black box nature, cannot explain the importance of predictors. We develop a novel methodology using machine learning that can accurately classify future anti-government violence in Mexico. We further demonstrate that our approach can identify important leading predictors of such violence. This can help policymakers make informed decisions and can also help governments and NGOs better allocate security and humanitarian resources, which could prove beneficial in tackling this problem. Using a variety of political event aggregations from the ICEWS database alongside other textual and demographic features, we trained various classical machine learning algorithms, including but not limited to Logistic Regression, Random Forest, XGBoost, and a Voting classifier. We considered a mix of CNN + Long Short Term Memory (LSTM) networks to decode the spatial and temporal relationship in the data. The performance of all the black box deep learning models was not at par with the classical machine learning models. We also evaluated the temporal relationships in the data to identify important predictors that fuel anti-government violence along with their directions using Shapley additive values. The voting classifier, utilizing a subset of features derived from LASSO across 100 simulations, consistently surpasses alternative models in performance and demonstrates efficacy in accu- rately classifying future anti-government conflicts. Notably, Random Forest feature importance indicates that some features, including but not limited to homicides, accidents, material conflicts, and positive worded citizen information sentiments emerge as pivotal predictors in the classification of anti-government conflicts. Finally, we conclude the research by analysing the spatial structure of the data using Moran’s I index extended version for spatiotemporal data to identify the global spatial dependency and local clusters followed by modelling the data spatially and evaluating the same using Gaussian Process Boost(GPBoost). The global spatial autocorrelation is minimal, characterized by local- ized conflicts cluster within the region. Furthermore, in Phase 3, the Voting Classifier method demonstrates superior performance over GPBoost, leading to the inference that no substantial spatial dependency exists among the various locations.

To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of cyberattacks, each of the existing state-of-the-art machine learning models depends on different algorithms for training which also impact their suitability for detection of a particular type of cyberattack. In this research, we analyzed each of the current state-of-theart machine learning models for different types of cyberattack detection from the past 10 years with a major emphasis on the most recent works for comparative study to identify the knowledge gap where work is still needed to be done with regard to detection of each category of cyberattack

Topological indices have important role in theoretical chemistry for QSPR researches. Among the all topological indices the Randić and the Zagreb indices have been used more considerably than any other topological indices in chemical and mathematical literature. Most of the topological indices as in the Randić and the Zagreb indices are based on the degrees of the vertices of a connected graph. Recently novel two degree concepts have been defined in graph theory; ev-degrees and ve-degrees. In this study we define ev-degree Zagreb index, ve-degree Zagreb indices and ve-degree Randić index by using these new graph invariants as parallel to their corresponding classical degree versions. We compare these new group ev-degree and ve-degree indices with the other well-known and most used topological indices in literature such as; Wiener, Zagreb and Randić indices by modelling some physicochemical properties of octane isomers. We show that the ev-degree Zagreb index, the ve-degree Zagreb and the ve-degree Randić indices give better correlation than Wiener, Zagreb and Randić indices to predict the some specific physicochemical properties of octanes. We investigate the relations between the second Zagreb index and ev-degree and ve-degree Zagreb indices and some mathematical properties of ev-degree and ve-degree Zagreb indices.

Rat H9c2 cardiomyocytes overexpressing the abscisic acid (ABA) hormone receptors LANCL1 and LANCL2 have an increased mitochondrial proton gradient, respiration and vitality after hypoxia/reoxygenation. Our aim was to investigate the role of the ABA/LANCL1-2 system in ROS turnover in H9c2. H9c2 cells were retrovirally infected to induce overexpression or silencing of LANCL1 and LANCL2, without or with the concomitant silencing of the transcription factor ERRα. Enzymes involved in radical production or scavenging were studied by qPCR and Western blot. Mitochondrial proton gradient and ROS were measured with specific fluorescent probes. ROS generating enzymes decreased, ROS-scavenging enzymes increased, and mitochondrial ROS were reduced in LANCL1/2-overexpressing vs. control cells infected with the empty vector, while the opposite occurred in LANCL1/2-silenced cells. Knock-down of ERRα abrogated all beneficial effects on ROS turnover in LANCL1/2 overexpressing cells. Taken together, these results indicate that the ABA/LANCL1-2 system controls ROS turnover in H9c2 via ERRα. The ABA/LANCL system emerges as a promising target to improve cardiomyocyte mitochondrial function and resilience to oxidative stress.

Background: This study aims to develop a research framework for the Social Life Cycle Assessment (S-LCA) of public services by conducting a systematic review of existing literature from 2013 to 2022. The research question focuses on how the results of the literature review can inform the advancement of S-LCA for public services. Methods: To answer this question, a qualitative and quantitative analysis of data from the Web of Science and Scopus databases was carried out. The quantitative analysis determined the total number of S-LCA and SO-LCA papers published by main journals, and main authors. The qualitative analysis highlighted the different themes and research objectives addressed in the work relating to the S-LCA of products/services and organizations. Results: The results show that 222 papers dealing with S-LCA were published in 94 journals and revealed a scarcity of work on public services, with most papers focusing on products/services and organizations. While there is a lack of direct scientific data, the study identified 17 actors, 74 impact sub-categories, and 178 indicators that could be considered for the S-LCA of public services. Conclusions: Due to the diverse nature of public services, it is crucial to develop specific stakeholder categories, sub-categories, and performance indicators for each public service. This will support the scientific community and S-LCA practitioners in applying assessing the social impacts of public services.

A single water pollution by dyes is a huge environmental problem; there is a necessity to produce new decolorization methods that are effective, cost-attractive, and suitable in industrial use. Magnetic chitosan polymers offer the advantage of easy separation from the dye solution. In this work, a Chitosan-Fe polymer was synthesized, characterized, and tested for removal of the azo dye Direct Red 83:1 from water. The polymer was characterized in terms of surface morphology (SEM), elemental analysis (EA), differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), infrared spectrophotometry (IR), X-ray powder diffraction (XRD) and density functional theory (DFT). The reported results hint that 1 g and pH 7.0 were the best conditions to carry out both kinetic and isotherm models. To understand the adsorption behavior of Direct Red 83:1 onto the polymers, adsorption rate and maximum adsorption capacity were calculated using kinetic tests and isotherm curves respectively. The kinetic data and mechanism of the adsorption process were analyzed by three models and the equilibrium data by three adsorption isotherms. The results indicated that the adsorption process follows a pseudo-second-order kinetics (R2= 0.999) and fits the Temkin isotherm (R2= 0.946), indicating that the adsorption occurred on heterogeneous surfaces. The newly synthesized Chitosan-Fe polymer exhibited good adsorption properties and easy separation of cleaned water.

Abstract This study investigates the assessment literacy, perceived practice, and observed practice of CBA practices among TVET teachers and assessors in private TVET colleges in South Gonder Zone, Ethiopia. The participants included 49 teachers and 14 assessors. Data collection utilized a modified four-option multiple-choice test, the Teacher Assessment Competency Inventory Questionnaire, a five-point Likert scale for perceived and observed practices, a semi-structured observation checklist, and interviews. Descriptive analysis, including mean scores, standard deviation, one-sample t-test, and proportions (%), was employed to analyze the data. Pearson correlation test was used to explore relationships between teacher assessment test scores, observed practices, and perceived practices. Findings revealed that private TVET teachers in the Amhara National Regional State lacked competence in assessing students' competence, falling short of overall and specific standards in both the assessment competence test and real classroom practice. Despite this, teachers modestly perceived their assessment practices across competency domains. Consequently, there were significant differences between teachers' actual competence and practice in educational assessments and their self-perceived practice. Qualitative approaches, employing theme analysis of assessment practice from semi-structured observations and interviews, highlighted poor performance among teachers on most assessment criteria. A small percentage demonstrated competence in specific concepts. Overall, the majority of teachers exhibited low levels of assessment literacy, suggesting a need for professional support in educational assessment approaches to enhance competence among TVET teachers.

Sleep fragmentation (SF) can increase inflammation and production of reactive oxygen species (ROS), leading to metabolic dysfunction. SF is associated with inflammation of adipose tissue and insulin resistance. Several studies suggested that melatonin may have beneficial metabolic effects by activating AMP-activated protein kinase (AMPK). However, it is unclear whether melatonin affects the AMPK signaling pathway in SF-induced metabolic dysfunction. Therefore, we hypothesize that SF induces metabolic impairment and inflammation in white adipose tissue (WAT), as well as altered intracellular homeostasis. We further hypothesize that these conditions could be improved by melatonin treatment. We conducted an experiment using adult male C57BL/6 mice, which were divided into three groups: control, SF, and SF with melatonin treatment (SF+Mel). The SF mice were housed in SF chambers, while the SF+Mel mice received daily oral melatonin. After 12 weeks, glucose tolerance test, insulin tolerance test, adipose tissue inflammation, and AMPK assessments were performed. The SF mice showed increased weight gain, impaired glucose regulation, inflammation, and decreased AMPK in WAT compared to the controls. Melatonin significantly improved these outcomes by mitigating SF-induced metabolic dysfunction, inflammation, and AMPK downregulation in adipose tissue. The therapeutic efficacy of melatonin against cardiometabolic impairments in SF may be due to its ability to restore adipose tissue homeostatic pathways.

A two-factor account has been proposed as an explanatory model for the formation and maintenance of delusions. The first factor refers to a neurocognitive process leading to a significant change in subjective experience; the second factor has been regarded as a failure in hypothesis evaluation characterized as an impairment of metacognitive ability. This study was focused on the assessment of metacognition in patients with schizophrenia. The aims of the study were to measure the overconfidence in metacognitive judgments through the prediction of word list recall; and to analyze the correlation between basic neurocognition: memory and executive function and metacognition through a metamemory test and the severity of psychotic symptoms. Method: 51 participants with diagnosis the of Schizophrenia were evaluated. The PANNS was used to assess the severity of psychiatric symptoms and the subtest of Metamemory included in the BANFE Battery was used to evaluate overconfidence and underestimations errors, intrusion and perseverative response, and total volume of recall. Results. The strongest correlation are observed between overconfidence errors and the positive factor of the PANSS (r= 0.774, p

This article presents a low-cost insurance system developed for small-hold farms in disaster-prone regions, primarily using free Earth Observation (EO) data and Free Open Source Software (FOSS) – collectively termed sustainable geoinformatics - with a proprietary mobile phone app that enables verification. The study examined 30 farms in Risaralda department, Colombia. A Digital Elevation Model (12.5m pixels) from the ALOS PALSAR satellite sensor was used with a Geographical Information System (GIS) to map the terrain, drainage and geohazards of each farming district. Google Earth Engine (GEE) was used to carry out Time Series Analysis of 15 EO and weather datasets for 1998 to 2020. This analysis enabled the levels of risk from hydrometeorological hazards to be determined for each farm of the study, providing key data for the setting of insurance premiums. A parametric insurance product was piloted using GPS-tagged, time-stamped mobile phone photos to verify crop health. Key features of this insurance system are its low operational cost and rapid damage verification, relative to conventional approaches to farm insurance. It is an affordable form of insurance for small-scale farmers, with the rapid verification and payment of claims. This relatively fast, low-cost and affordable approach to insurance for small-scale farming enhances sustainable development by enabling policy-holder farmers to recover more quickly from disasters.

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

The wood-based panel industry is experiencing an excessive accumulation of solid residues from the production of medium-density fiberboard (MDF) panels and moldings. It is possible to create new MDF products with acceptable physical and mechanical properties by revaluing MDF residues. Additionally, those products’ thermal properties can be improved by incorporating phase change materials (PCMs). This study aims to develop a wood-based fiberboard made of MDF residues, capable of storing thermal energy. Two types of PCMs, two PCM ratios, and two types of adhesives were used to produce eight different types of panels. The vertical density profile, thickness swelling, water absorption, internal bond (IB), and static bending properties – modulus of elasticity (MOE) and modulus of rupture (MOR) – were determined for each panel type. The specific heat of the panels was also determined. The results show the panels’ densities were greater than 700 kg/m3. Thickness swelling in water improved by 23% compared to the reference value of the control panel PCMs after PCM incorporation. The highest IB value was 1.30 MPa, which is almost three times the minimum required by regulation standards. The incorporation of PCMs reduced the panels’ bending properties compared to the properties of the control panels. Even though the values obtained are sufficient to comply with the minimum values set out in ANSI standard A208.2 with a MOE value of 2072.4 MPa and the values obtained are sufficient to comply with the minimum standards with a MOE value of 2072.4 MPa and a MOR value of 16.4 MPa. When microencapsulated PCM is used, the specific heat of the panels is increased by more than 100% over that of the control panels. This study develops a feasible alternative for using MDF residues: to create fiberboard that is capable of storing thermal energy and has adequate physical and mechanical properties.

Self-report measurement is frequently used in human sports to assess training adaptations [1, 2]. This is a technique novel to the equestrian sport. The aim of this study was to describe how elite event riders of Germany evaluate their own fitness as well as that of their horses for the entire duration of an eventing season. Additionally, correlations with possible influencing external factors such as type of training or duration of grazing were also investigated. Short online questionnaires were used to allow eight riders to describe the training of their horses. Five criteria (general performance, ability to concentrate, general state of mind, general muscular condition and emotional wellbeing) were used to assess both, their horse's, as well as their own wellbeing. A 1-10 rating scale was used to score each criterion resulting in an average of 38 points out of 50 (maximum wellbeing) for horse (Std. dev. 0.55) and rider (Std. dev. 0.65) respectively. A total of 120 questionnaires were analysed. A correlation could be demonstrated (Spearman's correlation coefficient = 0.5) between rider and horse score, whereby it only became a linear correlation above 30 points. In addition, the horse score correlates positively with its success at competitions. While the horses were rated similarly throughout the season, the riders’ perceived welfare was higher in the middle of the season compared with the beginning and end of the season. Regularly turned-out horses resulted in higher horse scores (Linear mixed model, p=0,04, n=120). It can be concluded that the self-report measurement of fatigue and wellbeing can be a useful tool for trainers and riders to better determine the horse’s fatigue and recovery. It should be noted that external factors influence both, rider and horse assessment.

Nowadays, the transparency of governments with respect to the sustainability of public services is a very interesting issue for stakeholders and academics. It has led to previous research and international organisations (EU, IMF, OECD, United Nations, IFAC, G-20, World Bank) to recommend promotion of the online dissemination of economic, social and environmental information. Based on previous studies about e-government and the influence of administrative cultures on governmental accountability, this paper seeks to identify political actions useful to improve the practices of transparency on economic, social and environmental sustainability in European local governments. We perform a comparative analysis of sustainability information published on the websites of 72 local governments in 10 European countries grouped into main three cultural contexts (Anglo-Saxon, Southern European and Nordic). Using international sustainability reporting guidelines, our results reveal significant differences in local government transparency in each context. The most transparent local governments are the Anglo-Saxon ones, followed by Southern European and Nordic governments. Based on individualized empirical results for each administrative style, our conclusions propose useful policy interventions to enhance sustainability transparency within each cultural tradition, such as development of legal rules on transparency and sustainability, tools to motivate local managers for online diffusion of sustainability information and analysis of information needs of stakeholders.

Video self-supervised learning (VideoSSL) offers significant potential for reducing annotation costs and enhancing a wide range of downstream tasks in video understanding. The ultimate goal of VideoSSL is to achieve human-level video intelligence across a spectrum of tasks, from low-level tasks such as pixel temporal correspondence to high-level complex spatio-temporal tasks like action recognition. However, most existing VideoSSL methods focus on isolated aspects of this spectrum and fail to integrate different levels of task complexity. Our study presents the first comprehensive survey that connects all families of VideoSSL methods. We provide a detailed review of the full spectrum of VideoSSL, from low to high levels, by conceptually linking their self-supervised learning objectives and including a comprehensive categorization. Our extensive evaluation highlights the strengths and limitations of each SSL objective across various downstream task families. We also detail the challenges in current VideoSSL research such as data curation, interpretability, deployment, and privacy concerns, an area that previous surveys have not thoroughly explored. In addressing these challenges, we recognize the strengths of existing methods in addressing these challenges and outline future directions for research.

Orthodontic appliances may cause discomfort for patients. It could influence person‘s psychological well–being. The aim was to examine psychological health of patients wearing orthodontic appliances. It is important to analyze well-being of patients during orthodontic treatment because it is started in a young age and it may affect one’s psychological health. Therefore, for doctors and patients it is important to understand and take every aspect of the treatment into consideration when deciding when to start the treatment and what appliance to choose. 339 patients answered anonymous questionnaire. They were divided into four groups according to their age and type of appliance. Main reasons to seek treatment were crooked teeth and bad bite. Statistically signifi-cant difference was between women and men as women seeked treatment because of crooked teeth, meanwhile men indicated bad bite as main reason. 48.7% of subjects noted that they were feeling good during treatment, however, 4% of all patients noted that they were feeling bad. 45% of subjects stated that they felt unhappy at least sometimes. 43% of subjects felt stress. Even though patients indicated various negative aspects on their well-being during treatment, for the majority of the subjects end results significantly increased their psychological well-being.

Background/Objectives: We defined the value of a machine learning algorithm to distinguish between the EEG response to no light or any light stimulation, and between red or green light stimulation in awake volunteers with closed eyelids. This new method of EEG analysis is visionary in the understanding of visual signal processing and will facilitate anaesthetic depth research. Methods: X-gradient boosting models were used to classify the cortical response to VEP stimulation (no light vs. any light stimulation; red vs. green light stimulation). For each of the two classifications, three scenarios were tested: training and prediction in all participants (all), training and prediction in one participant (individual), training across all but one participant with prediction in the participant left out (one out). Results: Ninety-four Caucasian adults were included. The machine learning algorithm had a very high predictive value and accuracy in differentiating between no light and any light stimulation (AUCROCall: 0.96; accuracyall: 0.94; AUCROCindividual: 0.96±0.05, accuracyindividual: 0.94±0.05; AUCROConeout: 0.98±0.04; accuracyo-neout:0.96±0.04). The machine learning algorithm was highly predictive and accurate in distinguishing between green and red colour stimulation (AUCROCall: 0.97; accuracyall: 0.91; AUCROCin-dividual: 0.98±0.04, accuracyindividual: 0.96±0.04; AUCROConeout: 0.96±0.05; accuracyoneout: 0.93±0.06). The predictive value and accuracy of both classification tasks was comparable between males and females. Conclusions: Machine learning algorithms could almost continuously and reliably differentiate between the cortical EEG responses to no light or any light stimulation and between green or red colour stimulation using VEPs in awake female and male volunteers with eyes closed. Our findings may open new possibilities for using VEPs in the intraoperative setting.

Recently, many authors have been interested to introduce fuzzy implications over t-norms and t-conorms. In this paper, we introduce (S,N) and residuum fuzzy implication for Dubois t-norm and Hamacher's t-norm. Also, new concepts so-called (T,N) and residual fuzzy co-implication in dual Heyting Algebra are investigated. Some examples as well as application are discussed as well.

: Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems, including zero-shot in-context learning scenarios. This study explores the ability of MLLMs in visually solving the Traveling Salesman Problem (TSP) and Multiple Traveling Salesman Problem (mTSP) using images that portray point distributions on a two-dimensional plane. We introduce a novel approach employing multiple specialized agents within the MLLM framework, each dedicated to optimizing solutions for these combinatorial challenges. Our experimental investigation includes rigorous evaluations across zero-shot settings and introduces innovative multi-agent zero-shot in-context scenarios. The re-sults demonstrated that both multi-agent models—Multi-Agent 1, which includes the Initializer, Critic, and Scorer agents, and Multi-Agent 2, which comprises only the Initializer and Critic agents—significantly improved solution quality for TSP and mTSP problems. Multi-Agent 1 ex-celled in environments requiring detailed route refinement and evaluation, providing a robust framework for sophisticated optimizations. In contrast, Multi-Agent 2, focusing on iterative re-finements by the Initializer and Critic, proved effective for rapid decision-making scenarios. These experiments yield promising outcomes, showcasing the robust visual reasoning capabilities of MLLMs in addressing diverse combinatorial problems. The findings underscore the potential of MLLMs as powerful tools in computational optimization, offering insights that could inspire further advancements in this promising field.

Civil construction is one of the oldest known activities in humanity, reports indicate that builders of the Roman Empire already sought the reuse of materials. Currently, considering the depletion of the supply of natural resources, the recycling of solid waste from construction and demolition (CDW), not only provides new products, but also offers ecological and economic alternative. In this context, this research seeks new variables for the disposal of waste from construction and demolition having in the composition of artificial finishing stones an odd possibility to be analyzed. In this research was developed and analyzed a new composite from the construction and demolition waste using as a binder an orthophthalic polyester resin. The residue was sieved and separated by granulometry by the simplex centroid method, the best compacted mixture was determined statically by ANOVA and the Tukey test. The residue was characterized by X-ray fluorescence and the resin by infrared spectroscopy by Fourier transform. Artificial rock plates were produced with 85% residue and 15% resin, by mass, by vibro system, compression and vacuum, later were cut for mechanical, physical and chemical tests. Analysis was performed by scanning electron microscopy of fractured compositions as well as grain sizes. The artificial stone with the best results presented density of 2,256 g/cm3, water absorption of 0.69%, apparent porosity of 1.55%; bending strength of 34.74 MPa and compression of 111.96 MPa; good results in the alterability and thermal tests. In this satisfactory scenario, the use of this waste in the composition of artificial rocks is promising because it directly meets the concept of sustainable development; replacing the concept of end-of-life of the linear economy, by new circular flows of reuse, restoration and renovation, in an integrated process the circular economy; as well as the quality of the final product with properties similar to the artificial rocks already marketed.

Chemical analysis of the organic components in beers has applications to quality control, authenticity and improvements to the flavor characteristics and brewing process. This study aims to show the complementary nature of two instrumental techniques which in combination can identify and quantify the majority of organic components in a beer sample. Nuclear Magnetic Resonance (NMR) was used to provide concentrations of twenty five different organic compounds including alcohols, organic acids, carbohydrates, and amino acids. Calorie content was also estimated for the samples. NMR data for ethanol concentrations were validated by comparison to a Fourier Transform Infrared Spectrometry (FTIR) method. Headspace Solid-Phase Microextraction (SPME) Gas Chromatography Mass Spectrometry (GCMS) was used to identify a range of volatile compounds such as alcohols, esters and hop derived aroma compounds. A simple and inexpensive conversion of a Gas Chromatography Flame Ionization Detector (GC FID) instrument to allow the use of Solid-Phase Microextraction was found to be useful for the quantification of volatile esters.

Poultry litter was converted to biochar by torrefaction and to hydrochar by hydrothermal carbonisation. Many parameters were measured for the resulting chars, to investigate the effect of production method and production temperature. SEM showed the presence of large quantities of crystalline material on the surface of the biochars. The elemental composition of some crystals was determined as 35% K and 31% Cl. This was confirmed as sylvite (KCl) crystals, which explains the high levels of water extractable potassium in the biochar and may also be important in germination inhibition. Biochars almost totally inhibited germination, whilst hydrochars decreased germination. Although germination occurred on hydrochar, root growth was severely inhibited. Consequently, germination index may be better to determine total phytotoxicity as it measures both effects and could be used as a bioassay for chars used as soil amendments. Washing removed germination inhibition in a low temperature char (3500C), possibly by removing KCl, however root toxicity remained. There were very low levels of heavy metals, suggesting they are not the source of toxicity. In biochars, pore mean size decreased with temperature from 3500C to 6000C, due to changes in pore size distribution. Mean pore size was measured directly using SEM. The merits of this method are discussed. Low temperature biochars seem best suited for fuel as they have high calorific value, high hydrophobicity, low ash content and high yield. Higher temperatures are better for soil amendment and sequestration applications with a smaller mean pore size, higher surface area, and higher pH.

Financial fraud poses a severe threat to the integrity of corporate financial statements and market efficiency. While auditors play a crucial role in detecting and preventing such fraud, the unique characteristics of this domain, including class imbalance, high misclassification costs, and am-biguous attributes, pose significant challenges. Traditional classification algorithms may not be optimally suited for this task. This paper proposes a novel stacking ensemble learning approach to enhanced detecting of Financial Statement Scam. By combining the strengths of multiple base learners, including Random Forest, XGBoost, and Gradient Boosting Decision Trees, our model leverages their diverse predictions to improve overall performance. A Logistic Regression me-ta-learner is employed to integrate the outputs of the base learners, capturing their collective wisdom while mitigating individual weaknesses. Extensive experimentation using a real-world dataset shown the superiority of our approach, achieving remarkable recall, precision, accuracy, and area under the curve metrics. The proposed model outperforms individual base learners, under-scoring the efficacy of ensemble learning in tackling the intricate problem of financial fraud detection. This research contributes to the creation of substantial and robust fraud detection systems, fostering trust and transparency in financial markets.

Biological systems have a unique ability inherited through their genome. It allows them to build, operate, and manage a society of cells with complex organizational structures where autonomous components execute specific tasks and collaborate in groups to fulfill systemic goals with shared knowledge. The system receives information from various senses, makes sense of what is being observed, and acts using its experience, while the observations are still in progress. We use the General Theory of Information (GTI) to implement a digital genome, specifying the operational processes that design, deploy, operate, and manage a cloud-agnostic distributed application that is independent of IaaS and PaaS infrastructure, which provides the resources required to execute the software components. The digital genome specifies the functional and non-functional requirements that define the goals and best-practice policies to evolve the system using associative memory and event-driven interaction history to maintain stability and safety while achieving the system’s objectives. We demonstrate a structural machine, cognizing oracles, and knowledge structures derived from GTI used for designing, deploying, operating, and managing a distributed video streaming application with autopoietic self-regulation that maintains structural stability and communication among distributed components with shared knowledge while maintaining expected behaviors dictated by functional requirements.

Lung cancer is the leading cause of cancer death worldwide therefore studies about the etiological factors and carcinogenesis are important.The aim of the study is to detect the presence and types of Human papilloma virus (HPV) in lung cancer and non-tumoral lung and Epidermal Growth Factor Receptor (EGFR) mutation prevalance in lung cancer with Polymerase Chain Reaction (PCR) method.Fifty patients who were histopathologically diagnosed lung cancer and 7 patients with non-neoplastic lung disease were enrolled in the study. HPV positivity was detected in 75.4% of the patients. The rate of high-risk HPV positivity was 100% in adenocarcinomas, 64.5% in squamous cell carcinomas, and 57% in non-neoplastic lung. HPV 51 was the most frequent type followed by HPV 16 (43.9%). There was no statistically significant relationship between HPV infection and age, gender and smoking history and EGFR mutation. The prevalence of HPV positivity is variable in lung cancer in different studies and this may be due to many factors including HPV detection methods, number of patients, geographic regions. New studies about the role of HPV infection need to be performed in order to obtain information about the use of prophylactic and theurepatic agents in lung cancer.

Background: Experiential learning (EL) experiences are an important component of a university education, positively impacting career-related attitudes, knowledge, and skills. Students also require EL opportunities to gain experiences required for admission to competitive graduate and professional programs. Students with disabilities face barriers accessing and benefiting from such opportunities. Purpose: This study examined the degree to which demographic factors, type and severity of disability, dispositional factors, and overall adjustment and wellbeing are predictive of the quality of EL experiences among university students with disabilities. Methodology/approach: A survey was distributed to undergraduate students with disabilities who have participated in EL courses. Results were analyzed using multiple linear regression. Findings/conclusions: Dispositional and adjustment and wellbeing variables, including the environmental mastery dimension of their psychological wellbeing rather than demographic factors, such as gender or type and severity of disability, are significant predictors of the quality of EL experiences among students with disabilities. Implications: For students with disabilities to have academically and professionally successful EL experiences, post-secondary institutions must continue to provide appropriate accommodations and educate instructors about the diverse and complex needs of this student group. This must include an understanding of the uniqueness of each individual student’s needs.

On return to campus after the pandemic, students were subjected to receiving lectures online, in class, or by the emerging hybrid approach. This study reports students' preference over the three approaches based on the experience gained during the 2022/23 academic session. One hundred and twenty-seven (127) on-campus Education students in one public university in Malaysia participated in the study. Data was collected through an online forum and interviews with the participants. The data collected was analyzed using content and thematic analysis. Preference for the hybrid approach emerged as a finding with three themes describing what makes the wholly online class unpopular (themes one and two); and, the popularity of the hybrid approach (theme three): 1. On-campus learner-environment challenges; 2. Perceived lack of Faculty engagement and support in the online learning environment; and, 3. Student engagement through faculty presence and technology innovation. What the students valued most in the hybrid approach is the face-to-face technology-enhanced classroom interaction that is retained, believing that learning is more effective and interesting in class than online. They considered the additional online learning activities as complementing the classroom learning. The approach provides an opportunity for fundamental learning in class and supplementary learning online. These findings imply that institutions should prioritize technology integration into face-to-face instruction, leveraging innovative approaches to enhance student engagement and learning outcomes. Lecturers should consider adopting hybrid teaching models that combine the benefits of in-person interaction with the flexibility of online learning, catering to diverse student preferences and optimizing the educational experience.

Experiments to measure a single molecule/particle, i.e. an individual molecule/particle, at room temperature or under physiological conditions without immobilization, for example on a surface, or without significant hydrodynamic flow have so far failed. This failure has given impetus to the underlying theory of Brownian molecular motion towards its stochastic due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

The introduction of the Industrial Internet of Things (IIoT) has led to major changes in the industry. Thanks to machine data, business process management methods and techniques could also be applied to them. However, one data source has so far remained untouched: The network data of the machines. In the business environment, process mining, for example, has already been carried out based on network data, but the IIoT, with its particular protocols such as OPC UA, has yet to be investigated. With the help of design science research and on the shoulders of CRISP-DM, we first develop a framework for process mining in the IIoT in this paper. We then apply the framework to real-world IIoT network traffic data and evaluate the outcome and performance of our approach in detail. We find tremendous potential in network traffic data but also limitations. Among other things, due to the dependence on process experts and the existence of case IDs.

Background: Individuals living in rural areas often face challenges in accessing healthcare, increasing their risk of poor health outcomes. Farmers, a sub-population in rural areas, are particularly vulnerable to mental health issues and suicide, yet exhibit low rates of help-seeking behavior. The aim of our study was to develop an in-depth understanding of the issues influencing mental help-seeking among farmers living in rural areas from the perspectives of healthcare providers, as well as to explore the strategies providers use to navigate through these issues to effectively engage with this vulnerable population. Methods: We used a descriptive phenomenological approach to understand healthcare providers’ perspectives, experiences, and approaches to providing mental healthcare to farmer clients in rural areas. Semi-structured interviews were conducted with 21 participants between March and May 2023. Results: Our analysis yielded five thematic areas: (1) ensuring accessibility, (2) establishing relatability, (3) addressing stoicism and stigma, (4) navigating dual roles, and (5) understanding community trauma. Conclusions: Healthcare service delivery for farmers is multifaceted. This study fills a gap in knowledge by translating these the data to inform an evidence-based model and a list of recommendations for implementing agriculturally-informed practices in rural areas.

Abstract: Although experimental attempts to measure a single molecule/particle at room temperature or under physiological conditions without immobilization, for example on a surface, or without hydrodynamic flow have so far failed, this failure has given impetus to the underlying theory of Brownian motion towards its stochastic due to diffusion. Quantifying the thermodynamic jitter of molecules/particles inspires many and forms the theoretical basis of single-molecule/single-particle biophysics and biochemistry. For the first time, our simulation results for a live cell (cytoplasm) show that the tracks of individual single molecules are localized in Brownian motion, while there is fanning out in fractal diffusion (anomalous diffusion).

Background: Renal cancers are among the top ten causes of cancer-specific mortality, of which the ccRCC subtype is responsible for most cases. The grading of ccRCC is important in determining tumour aggressiveness and clinical management. Objectives: The objectives of this research were to predict the WHO/ISUP grade of ccRCC pre-operatively and characterise the heterogeneity of tumour sub-regions using radiomics and ML models, including comparison with pre-operative biopsy-determined grading in a sub-group. Methods: Data were obtained from multiple institutions across two countries, including 391 patients with pathologically proven ccRCC. For analysis, the data were separated into four cohorts. Cohorts 1 and 2 included data from the respective institutions from the two countries, cohort 3 was the combined data from both cohort 1 and 2, and cohort 4 was a subset of cohort 1, for which both the biopsy and subsequent histology from resection (partial or total nephrectomy) were available. 3D image segmentation was carried out to derive a voxel of interest (VOI) mask. Radiomics features were then extracted from the contrast-enhanced images, and the data were normalised. The Pearson correlation coefficient and the XGBoost model were used to reduce the dimensionality of the features. Thereafter, 11 ML algorithms were implemented for the purpose of predicting the ccRCC grade and characterising the heterogeneity of sub-regions in the tumours. Results: For cohort 1, the 50% tumour core and 25% tumour periphery exhibited the best performance, with an average AUC of 77.9% and 78.6%, respectively. The 50% tumour core presented the highest performance in cohorts 2 and 3, with average AUC values of 87.6% and 76.9%, respectively. With the 25% periphery, cohort 4 showed AUC values of 95.0% and 80.0% for grade prediction when using internal and external validation, respectively, while biopsy histology had an AUC of 31.0% for the classification with the final grade of resection histology as a reference standard. The CatBoost classifier was the best for each of the four cohorts with an average AUC of 80.0%, 86.5%, 77.0% and 90.3% for cohorts 1, 2, 3 and 4 respectively. Conclusion: Radiomics signatures combined with ML have the potential to predict the WHO/ISUP grade of ccRCC with superior performance, when compared to pre-operative biopsy. Moreover, tumour sub-regions contain useful information that should be analysed independently when determining the tumour grade. Therefore, it is possible to distinguish the grade of ccRCC pre-operatively to improve patient care and management.

The fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing kThe fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing knowledge for the information- theoretic fractal dimensions. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.

Software stands as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity which leads to challenges in quality assurance. Software Defect Prediction (SDP) emerges as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. Machine Learning (ML) and Deep Learning (DL) methodologies exhibit superior accuracy and adaptability compared to traditional statistical approaches catalyzing active researches in this domain. However, it makes us hard to generalize not only because of the disparity between open-source project and commercial project but also the difference on each industrial sectors. Consequently, further research utilizing datasets sourced from diverse real-world sectors becomes imperative to bolster the applicability of these findings. In this study, we utilized embedded software for telecommunication systems of SAMSUNG ELECTRONICS, supplemented by the introduction of nine novel features to train the model, and subsequent analysis of results ensued. Experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolster the application of SDP methodologies within analogous industrial sectors.

By using 0.35-um CMOS process, this work achieves a design of analogous band-gap reference voltage circuit with low temperature coefficient. The proposed circuit operates at 3V and generates a reference current of 44 uA. The HSPICE simulation results show the temperature coefficient of this circuit is 23 ppm/℃ at range of -10 ℃ to 100 ℃, and the line regulation (the ratio of output current variation to supply voltage variation) is estimated as 1.95 uA/V from supply voltage variation of 3 V to 5 V. The experimental chip is fabricated and measured. The circuit provides adjustable capability for output voltage among temperature variation of -10 - 100 ℃. The chip area is 534 × 695 um^2. In this new design, the operational amplifier is not necessary. The chip design effort can be great reduced.

In the present study, the new biological sources in the form of lichen Usnea orientalis Motyka was screened for its antidermatophytic potential. Six species of dermatophytes were chosen on the basis of their prevalence for antidermatophytic assays, and the Clinical Laboratory Standard Institute (CLSI)-recommended broth microdilution procedure was used to detect the efficacy of extract against dermatophytes. Thin layer chromatography of lichen extracts reveals the presence of two secondary metabolites viz. salazinic acid and usnic acid. U. orientalis extract exhibited promising antidermatophytic activity against all tested pathogens. Amongst all tested pathogens, E. floccosum exhibited most susceptibility towards extract, whereas T. mentagrophytes exhibited the least susceptibility. Topical application of U. orientalis extract might be helpful in the cure of dermal infections.

Conclusion: This review provides evidence that major foodborne pathogens, such as E. coli O157:H7, Salmonella spp., L. monocytogenes, and hepatitis A virus, can persist on food for prolonged periods to cause harm. These insights underscore the importance of implementing appropriate control measures to contribute to a safer and more secure food supply chain.

Green hydrogen is a fuel that in the coming years will play a very important role in the energy transition process in developed countries, especially those seeking to reach a level of zero emis-sions, for which reason its demand is expected to increase significantly. This article analyzes the fundamentals to produce hydrogen, with a focus on the oxidation reaction of a thermochemical solar cycle for the dissociation of water vapor. Solar thermochemical cycles have been extensively investigated, but it is still in the development stage by groups of researchers who have focused on finding the right materials and conditions to improve the efficiency of the process, especially at high temperatures. The theoretical foundations are analyzed, compiled from exhaustive scientific investigations related to the oxidation of iron in water vapor, the relationship with the activation energy of the corrosive process, thermodynamic aspects and the kinetic model according to a heterogeneous reaction. In addition, some high temperature oxidation mechanisms, pH effects, reactors and materials (fluidized beds) used are presented. The scientific review indicates that the production of hydrogen through a thermochemical cycle is more efficient than electrochemical processes (electrolysis), if the limitations of the reduction stage of the cycle are overcome.

The development requirements for reusable liquid rocket engines have set higher standards for the reliability design of turbopump structures. To address the issue of bearing failure in turbopumps under harsh conditions such as low temperature, high speed, heavy load, and repeated start-stop cycles, this paper proposes replacing ball bearings with thrust foil bearings. We used liquid nitrogen instead of liquid hydrogen and liquid oxygen to simulate the ultralow temperature and low viscosity operating environment of turbopumps, evaluating the potential feasibility of using thrust foil bearings in this context. The numerical calculations primarily include the formulation of the foil deformation equations based on the link-spring model for the wavy foil and the thin plate finite element model for the top foil. These equations are solved by coupling the Reynolds lubrication equation, the fluid film thickness equation, and the foil deformation equations using the finite difference method, Newton-Raphson method, and finite element method. A detailed analysis is conducted on the effects of rotational speed, fluid film thickness, thrust disk inclination angle, and wavy foil interface friction coefficient on the static and dynamic characteristics of thrust foil bearings. The research findings provide guidance for the application of thrust foil bearings in liquid rocket turbopumps.

Generating electricity from coal combustion is highly associated with ongoing pollution problems that negatively impact the environment. Coal fly ash (CFA) is a predominant waste by-product of coal combustion which is disposed of in exposed ash dams constructed in the vicinity of power stations. Its disposal requires a large piece of land and therefore more land is converted to unproductive disposal sites, degrading the ecosystem. This waste material is classified as a hazardous substance in South Africa due to unacceptable levels of inorganic and persistent organic pollutants and its potential for dust creation. CFA is recycled and sold to the building and construction sectors, but the rate of its utilization is far less than the production rate resulting to high volumes that is stockpiled in disposal sites. More than 500 million tons CFA is produced yearly and over 200 million tons yearly remain unused globally and more CFA will continue to be produced due to high consumer energy demands, especially in countries with heavy reliance on coal for power generation. In this context, the paper discusses production of CFA, pollution problems due to its disposal, examines existing gaps within the scope of ash dam restoration processes and presents opportunities offered by phytoremediation (a low-cost and environmentally friendly technology that utilizes plants to restore the degraded environments). Ecological restoration through the use of socio-economically valuable plants (aromatic plants, legumes and grasses) has potential in addressing societal challenges and consequently impacting positively the livelihood of communities.

Periacetabular osteotomy (PAO) is an effective approach for surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip and limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 which is a state-of-the-art (SOTA) optical see-through head-mounted display (OST-HMD). For AR guidance, we propose an optical marker-based virtual-physical registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS, such that virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns the bone saw with osteotomy planes planned in preoperative images, and then provides surgeons with not only robot assistance but also AR guidance. Comprehensive experiments were conducted to evaluate both virtual-physical registration accuracy and osteotomy accuracy of the developed navigation system. The proposed virtual-physical registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The developed system achieved an average distance deviation of 0.82 ± 0.17 mm and an average angular deviation of 3.77 ± 0.85 . Experimental results demonstrated high virtual-physical registration accuracy. The sub-millimeter distance deviation demonstrated the osteotomy accuracy of the proposed system.

Studies on Medical Geology have up till recently tended to emphasise the harmful effects of geological material and processes. This is perhaps justifiable, given the realisation that many environmental diseases could have causal links with some geo-environmental variables as co-factors, making such studies extremely valuable in the improvement of diagnoses and therapy. However, this review aims to show that in addition to the high value of such research, studies conducted on the beneficial properties of Earth materials also have considerable merit, given their enormous potential for assuaging a wide range of environmental health disorders. For instance, certain geological materials including clay minerals contain active substances that show considerable promise in various applications such as pharmaceutical formulations, aesthetic medicine, and indigenous medicine. This review synthesises current knowledge of how certain geological materials can be exploited in formulating remedies for some human health problems. Reports of the therapeutic uses of clay minerals, zinc oxide (zincite), zeolite, and kaolin are appraised. The review shows that ancient and contemporary use of geological materials such as clay minerals have played crucial roles in the treatment of several human diseases, with recent and ongoing research revealing further development in these applications. Well strategised clinical trials using available resources could give impetus to further research in elucidating the potential of various geomaterials as innovative clinical remedies for some human diseases and infections as well as aid the proper scientific documentation of their natural uses.

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km²) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

In orthopedics, bone drilling is a crucial part of a surgical method commonly carried out for internal fixation in bone fracture treatment. The primary purpose of bone drilling is the creation of holes for screw insertion to immobilize fractured parts. The bone drilling task depends on the orthopedist and surgeon’s high level of skill and experience. This paper aimed to provide a summary of previously published review studies in the field of bone drilling. This review paper also presents a comprehensive review of the application of machine learning for bone drilling and as a future direction for the automation system. This review can also help medical surgeons and bone drillers understand the latest improvements through parameter selection and optimization strategies to reduce bone damage in bone drilling procedures. Apart from the review study, bone drilling vibration data collected in the University laboratory experiment is also presented in this study. The vibration data consist of three different layers of femur cow bone which are processed and classified using several machine learning methods. LSTM is, used in the bone drilling classification study to prove that the layers of the bone drilling are associated with the vibration signal and can be classified and predicted using the machine learning method.

BACKGROUND Detecting total cholesterol in dried blood spots could aid in identifying individuals with a high likelihood of familial hypercholesterolemia and could be used as a screening measure. This study aims to assess the diagnostic accuracy of dried blood spots on Whatman 903 paper cards using a manual enzymatic technique. METHODS A total of 394 samples collected as serum and dried blood spots were compared. Cholesterol was determined in serum using the automated reference method, while cholesterol on paper was measured using a manual enzymatic method. Within- and between-day diagnostic variability were analyzed. The correlation between both methods was assessed using Passing-Bablok regression and Bland-Altman plot. Internal validation of our correlation formula was performed on 149 samples, along with external validation of the formula proposed by Corso et al. RESULTS The within- and between-day coefficient of variation was found to be lower than 10.14% and 14.09%, respectively. Method comparison yielded an area under the curve of 0.976, with a standard error of 0.009. Passing-Bablok regression indicated a precision of 0.803 and an accuracy of 0.96. Internal validation precision was measured at 0.716. Regarding internal validation, calculated cholesterol with our regression line did not differ from serum cholesterol analysis, while significant differences were observed in calculated cholesterol levels using the external formula. CONCLUSIONS Total cholesterol analysis in dot blood spots demonstrates high precision and reproducibility. This method reliably enables the incorporation of this biological marker into neonatal screening for familial hypercholesterolemia detection.

Epigenetic changes regulate gene expression through histone modifications, chromatin remod-eling and proteins interpreter of these modifications. The PRC1 and PRC2 complexes shape gene repression via histone modifications. Specifically, the CBX protein family aids PRC1 recruitment to chromatin, impacting the progressive multistep process driving chromatin silencing. Among family members, CBX3 is a complex protein involved in aberrant epigenetic mechanisms that drive lung cancer progression. CBX3 promotes lung tumorigenesis by interacting with key pathways such as PI3K/AKT, Ras/KRAS, Wnt/β-catenin, MAPK, Notch, and p53, leading to in-creased proliferation, inhibition of apoptosis, and enhanced resistance to therapy. Given our current lack of knowledge, additional research is required to uncover the intricate mechanisms underlying CBX3 activity, as well as its involvement in molecular pathways and its potential biomarker evaluation. Specifically, the dissimilar roles of CBX3 could be reexamined in order to gain a greater insight into lung cancer pathogenesis. This review aims to provide a clear overview of the context-related molecular profile of CBX3, which could be useful for addressing clinical challenges and developing novel targeted therapies based on personalized medicine.

This study investigated how the type and homogenisation parameters of the feed mixture affect the efficiency of the encapsulation process and the microcapsule properties of phenol-rich grape pomace extract (GPE) during the spray drying process with goat whey protein (GW) as wall material. GPE was obtained by solid-liquid extraction of grapes with 50% ethanol. Effects of ultrasonic homogenisation parameters (UB): temperature: 30-50 °C; time: 5-30 min; stabilisation time after homogenisation: 15-45 min, and homogenisation parameters on a magnetic stirrer (MS): temperature (25-50 °C), time (10-60 min) and homogenisation speed (600-1200 rpm) were tested using response surface methodology (RSM) and Box-Behnken design. After selecting the optimal homogenisation conditions, the spray drying process parameters were optimised in the same way, namely: inlet air temperature (160-190 °C), GW fraction (0.5-3.5) and feed flow (6-10 mL/ min). The results showed that GW has a high potential as a wall material in the spray drying process, especially for the purpose of protecting polyphenolic compounds from GPE.

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

The integration of Artificial Intelligence (AI) in predicting and managing risks for coastal port developments significantly enhances planning and operational efficiency. This paper presents a theoretical framework utilizing AI to predict future scenarios based on geological, hydrodynamic, and oceanographic factors. Focusing on the effective implementation of AI in ports, with a specific emphasis on Bulgarian Black Sea coastal areas such as Nesebur, Sarafovo, Sozopol, St. Anastasia Island, and the region of Karantinata in Varna, the study explores AI applications for site selection, risk assessment, and operational optimization to ensure resilient, efficient, and sustainable port infrastructure.

The three dimensional conformable time fractional Kadomtsev-Petviashvili and the conformable time fractional modified Kawahara equations are solved by implementing the Kudryashov's procedure. The corresponding wave transformation reduces both equations to some ODEs. Balancing the nonlinear and the highest order derivative terms gives the structure of the solutions in the finite series form. The useful symbolic tools are used to solve the resultant algebraic systems. The solutions are expressed in explicit forms.

Exact solutions to conformable time fractional (3+1)- dimensional equations are derived by using the modified form of the Kudryashov method. The compatible wave transformation reduces the equations to an ODE with integer orders. The predicted solution of the finite series of a rational exponential function is substituted into this ODE. The resultant polynomial equation is solved by using algebraic operations. The method works for the Jimbo-Miwa, the Zakharov-Kuznetsov and the modified Zakharov-Kuznetsov equations in conformable time fractional forms. All the solutions are expressed in explicit forms.

Glucose-6-phosphatase (G6Pase), an enzyme found mostly in the kidneys and the liver, acting significant role of supplying glucose through starvation. This study includes (84) subjects, their age ranged from (40 to 54) years. (20) subjects were healthy chosen as control group and (64) patients with type 2 diabetes mellitus were divided into three groups according to their type of anti diabetic therapy : (23) newly diagnosed group without therapy (Group1), (20) with metformin therapy (Group2) and (21) with metformin plus glibenclamide therapies( Group3). The study found that G-6-Pase activity is increased, thereby leading to an increase in endogenous glucose production (EGP) in patients with type 2 diabetes and, therefore FPG will increase. The result found that increasing G-6-Pase activity will increase the concentration of glucose in the blood and that will increase the long-term glycemic control (HbA1c%).

This review deals with the functionalization of double bonds carried out in the presence of a chiral catalyst exploiting the intramolecular attack to haliranium ions by nucleophilic nitrogen of amides or carbamates prepared from achiral aminoalkenes, and the C-N bonds formation leads to highly enantioenriched non-aromatic heterocycles. A range of protocols are reported, emphasizing the synthesis of many natural and biologically active products of pharmacological interest prepared according to this methodology.

Ménière's disease (MD) has an unclear cause. The microvascular dysregulation of the inner ear has been increasingly pointed as a potential contributor. This study investigates the prevalence of cardiovascular risk factors (CVRFs) in MD patients compared to those with posterior circulation cerebral infarction (POCI). CVRFs like hypertension, diabetes, dyslipidemia, obesity, coronary heart disease, and smoking were assessed in both MD and POCI patients. Brain MRI identified POCI etiology as "small vessel occlusion" (SVO) or "other etiology" (OE). The study included 64 MD and 84 POCI patients. Compared to MD, POCI OE showed a higher prevalence of CVRFs across various age groups, including hypertension, diabetes, dyslipidemia, and smoking. Notably, the odds of having POCI OE were significantly higher for individuals with hypertension and smoking. On the other hand, POCI SVO showed similar prevalence of CVRFs compared to MD. This study reveals no significant difference in CVRF prevalence between MD and smaller vessel POCI. However, a clear distinction emerges when comparing MD to POCI with involvement of larger blood vessels. Further research is needed to confirm these findings and explore potential shared risk factors between POCI (SVO) and MD.

Abstract: Development of the fast neutron radiography with higher penetration capability in Non-Destructive Testing (NDT) techniques is rapidly. The detection efficiency and the imaging spatial resolution are the main problem of the radiography detector for many fast neutron imaging systems. In this paper, a detector composed of pixelated EJ200 scintillator array，an 16 × 16 silicon-photomultipliers (SiPM) array, and a capacitive multiplexing network readout electronics is designed. Using Monte-Carlo simulations，the main parameters of the detector was optimization. Then the detector prototype was fabricated and tested at a 14 MeV D-T neutron source. The preliminary test results showed that the prototype has spatial resolution of 1.26 mm. Using pixelated scintillator structure，the conflict between spatial resolution and detect efficiency could improved. Moreover, SiPMs offer a flexibility for the expansion of application field of the imaging system due to their excellent photon detection performance, relatively low price and joint possibility for large area.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.