Deep learning has increasingly been employed to identify minerals. However, deep learning can only be used to identify minerals in the distribution of the training set, while any mineral outside the spectrum of the training set is inevitably categorized erroneously within a predetermined class from the training set. To solve this problem, the study introduces the approach that amalgamates One-Class Support Vector Machines (OCSVM) with the ResNet architecture for the out-of-distribution mineral detection. Initially, ResNet undergoes training using a training set comprising well-defined minerals. Subsequently, the earlier layers of the trained ResNet are employed to extract the discriminative features of the mineral under consideration. These extracted mineral features then become the input for OCSVM. When OCSVM discerns the mineral in the training set's distribution, it triggers the subsequent layers within the trained ResNet, facilitating the accurate classification of the mineral into one of the predefined categories encompassing the known minerals. In the event OCSVM identifies the mineral out of the training set's distribution, it is unequivocally categorized as an unclassified or 'unknown' mineral. Empirical results substantiate the method's capability to identify out-of-distribution minerals while concurrently maintaining a commendably high accuracy rate for the classification of the 36 in-distribution minerals.

Triticale is known for being an alternative energy source to usual cereals such as maize and wheat in poultry nutrition. Several studies suggested opposite results regarding its incorporation as a feed ingredient on laying hens’ production parameters. This article used a meta-analysis to assess the factors influencing the effects of triticale on layers’ performance. In July 2022, papers studying the effect of triticale on layers’ egg production (EP), egg weight (EW), egg yolk color (EYC), feed intake (FI), and feed conversion ratio (FCR) were identified on Google Scholar, PubMed, and Science Direct. According to the eligibility criteria of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, 6 articles were registered and segmented into 16 experiments for our meta-analysis. Overall, the trim and fill method revealed that triticale had similar impacts to conventional cereals on laying hens' performance. However, the meta-ANOVA and the meta-regression emphasized that triticale percentage, triticale strains and laying hens strains could significantly influence the effect of triticale on layers' performance. Indeed, the meta-Anova highlighted that the Hy-Line Brown strain and Joesong and Juanilo triticale strains in-duced the best laying hens’ performance. Moreover, the meta-regression emphasized a positive correlation between the triticale inclusion percentage and the EW in Juanilo triticale diets and a negative correlation between the triticale inclusion percentages and the EYC in the triticale and laying hens strains studied. Even though the funnel plot and the Egger linear test suggested sig-nificant publication bias, the present meta-analysis remains consistent research to understand how certain factors could influence the impact of triticale on layers' performance.

Optical materials with a tunable localized surface plasmon resonance (LSPR) are of a great interest for applications in photonics and optoelectronics. In the present study we explored the potential of generating the LSPR band with an ultra-broad range of over 1000 nm in gold nanoparticles (NPs) precipitated through the thermal treatment in ZnO-Al2O3-SiO2 glass. Using the optical absorption spectroscopy, we demonstrated that the LSPR band's position and shape can be finely controlled by varying the thermal treatment route. Comprehensive methods including Raman spectroscopy, X-ray diffraction and high-resolution transmission electron microscopy were used to study the glass structure, while computational approaches were used for the theoretical description of the absorption spectra. Obtained results allowed us to suggest a scenario responsible for such abnormal LSPR band broadening which includes possible interparticle plasmonic coupling effect taking place during the liquid-liquid phase separation of the heat-treated glass. The formation of gold NPs with an ultra-broad LSPR band in glasses holds promise for sensitizing rare earth ion luminescence for new photonics devices.

The use of Light Amplification by Stimulated Emission of Radiation (i.e., LASERs or lasers) by the U.S. Department of Defense is not new and includes laser weapons guidance, laser-aided measurements, even lasers as weapons (e.g., Airborne Laser). Lasers in support of telecommunications is also not new. The use of laser light in fiber optics shattered thoughts on communications bandwidth and throughput. Even the use of lasers in space is no longer new. Lasers are being used for satellite-to-satellite crosslinking. Laser communication can transmit orders-of-magnitude more data using orders-of-magnitude less power and can do so with minimal risk of exposure to the sending and receiving terminals. What is new is using lasers as the uplink and downlink between the terrestrial segment and the space segment of satellite systems. More so, the use of lasers to transmit and receive data between moving terrestrial segments (e.g., ships at sea, airplanes in flight) and geosynchronous satellites is burgeoning. This manuscript examines the technological maturation of employing lasers as the signal carrier for satellite communications linking terrestrial and space systems. The purpose of the manuscript is to develop key performance parameters (KPPs) to inform U.S. Department of Defense initial capabilities documents (ICDs) for near-future satellite acquisition and development. By appreciating the history and technological challenges of employing lasers rather than traditional radio frequency sources for satellite uplink and downlink signal carrier, this manuscript recommends ways for the U.S. Department of Defense to employ lasers to transmit and receive high bandwidth, large-throughput data from moving platforms that need to retain low probabilities of detection, intercept, and exploitation (e.g., carrier battle group transiting to a hostile area of operations, unmanned aerial vehicle collecting over adversary areas). The manuscript also intends to identify commercial sector early-adopter fields and those fields likely to adapt to laser employment for transmission and receipt.

Pain is a multifaceted multisystem disorder that adversely affects neuro-psychological processes. This study compares the effectiveness of central-stimulation (tDCS) and peripheral-stimulation (TENS) in pain-inhibition during a cognitive-task in healthy volunteers and to observe potential neuro-cognitive improvements. Healthy eighty volunteers went through a complete experimental protocol comprising pain-induction (CPT), administration of tDCS/TENS, EEG-data acquisition, and cognitive assessments. The protocol for this study is categorized into 04-groups: G1(Control), G2(TENS), G3(Anodal-tDCS), and G4(Cathodal-tDCS). Paired t-tests (p

Cancer treatment is a significant focus in medicine owing to the increasing global incidence. Patients with advanced cancers that do not respond to conventional therapies have limited options and an unfavorable prognosis. Consequently, researchers are investigating complementary approaches to conventional treatments. One such approach is alkalization therapy, which aims to neutralize the acidic tumor microenvironment (TME) by increasing its pH level. The acidic TME promotes inflammation, tumor progression, and drug resistance. Alkalization therapy has been demonstrated to be effective for various cancers. In addition, natural products, such as triterpenoids, parthenolides, fulvic acid, Taxus yunnanensis, and apple pectin have the potential to alleviate symptoms, maintain physical fitness, and improve treatment outcomes of cancer patients through their anti-inflammatory, antioxidant, and anticancer properties. In this review, we focus on the effects of alkalization therapy and natural products on cancer. Furthermore, we present a case series of advanced cancer patients who received alkalization therapy and natural products alongside standard treatments, resulting in long-term survival. We posit that alkalization therapy together with the supplementation of natural products may confer benefits to cancer patients by mitigating the side effects of chemotherapy and complementing standard treatments. However, further research is warranted to validate these clinical findings.

Accurate knowledge of the rain amount is an crucial driver in several hydro-meteorological applications. This is especially true in complex orography territories, which are typically impervious, thus leaving ungauged most of the mountain areas. Thanks to their spatial and temporal coverage, weather radars can potentially overcome such an issue. However, weather radar, if not accurately processed, can suffer from several limitations (e.g., beam blocking, altitude of the observation, path attenuation, indirectness of the measurement) that can hamper the reliability of the rain estimates performed. In this study, a comparison between rain gauge and weather radar retrievals is performed in the target area of the Abruzzo region in Italy, which is characterized by a heterogeneous orography ranging from the sea side to Apennine ridge. Consequently, the Abruzzo region has an inhomogeneous distribution of the rain gauges, with station density decreasing with the altitude reaching up to approximately 1500 m a.s.l. Notwithstanding, pluviometric inflow spatial distribution shows a sub-regional dependency as a function of four climatic and altimetric factors: coastal, hilly, mountain, and inner plain areas (i.e., Marsica). Such areas are used in this analysis to characterize the radar retrieval vs. rain gauge amounts in each of those zones. Compared to previous studies on the topic, the analysis presented an attention to the importance of an accurate selection of the climatic and altimetric sub-regional areas where undertake the radar vs. rain gauge comparison. This aspect is not only of great importance to correct biases in radar retrievals in a more selective way, but it also paves the way for more accurate hydro-meteorological applications (e.g., hydrological model initialization, quantify the aquifers recharge etc.) which, in general, require the accurate knowledge of rain amounts upstream of a basin. To fill the gap caused by the uneven rain gauge distribution, Ordinary Kriging has been applied on a regional scale to obtain 2D maps of rainfall data, which are cumulated on a monthly and yearly base. Weather radar data from the Italian mosaic are considered as well, in terms of rain rate retrievals and cumulations performed on the same time frame used for rain gauges. The period considered for the analysis is two continuous years: 2017 and 2018. The output of the elaborations are raster maps for both radar and interpolated rain gauges, where every pixel contains a rainfall quantity. Although the results show a general underestimation in the weather radar data especially in mountain and Marsica areas, even though within the 95% confidence interval of the OK estimation. Our analysis highlights that the average bias between radar and rain gauges, in terms of precipitation amounts, is a function of altitude and is almost constant in each of the selected areas. This achievement suggests that after a proper selection of homogeneous target areas, the radar retrievals can be corrected using the denser network of rain gauges typically distributed at lower altitudes and extend such correction at higher altitudes without loss of generality.

(1) Background: Gamma-aminobutyric acid (GABA) is one of the inhibitory neurotransmitters with beneficial effects including sedative property. However, despite various clinical trials, scientific evidence regarding the impact of orally ingested GABA, whether natural or synthesized through biological pathways, on sleep is not clear.; (2) Methods: The present study work evaluated GABA-A biding affinity of GABALAGEN(GBL), a low-molecular-weight collagen infused with GABA, through receptor binding assays. The sedative effects of GBL were investigated through electroencephalography (EEG) analysis in the electro foot shock (EFS) stress-induced sleep animal model and then we examined the expression orexin, GABAA receptor in the brain region using immunohistochemistry.; (3) Results: We found that on the binding assay, GBL displayed high affinity to GABAA receptor (IC50 value, 31.5µg/mL)). Also, after treatment of GBL, percent of total time of REM and NREM were significantly and dose-dependently increased compared to the Con group. Consistent with behavioral results, the GBL-treated groups showed that the expression of GABAA receptor immune-positive cells in the VLPO were markedly and dose-dependently increased compared to the Con group. Also, the GBL-treated groups showed that the expression of orexin immune-reactive cells in the LH were significantly decreased compared to the Con group.; (4) Conclusions: In conclusion, GBL showed efficacy and potential to be used as an anti-stress therapy to treat sleep deprivation through antagonism of GABA receptors and consequent inhibition of orexin activity.

Objectives: To study the differences between malignant hypermetabolic axillary lymphadenopathy (MHL) and COVID-19 vaccine-associated axillary hypermetabolic lymphadenopathy (VAHL) using clinical imaging. Methods: A total of 1,096 patients underwent Positron Emission Tomography-Computed Tomography (PET-CT) between June 1, 2021 and April 30, 2022, at Ehime University Hospital. In total, 188 patients with axillary lymphadenopathy after the COVID-19 vaccination were evaluated. The patients were classified into three groups such as VAHL (n=27), MHL (n=21), and equivocal hypermetabolic axillary lymphadenopathy (EqHL; n=140). Differences in lymph nodes (LNs) swellings were statistically analyzed using clinical imagings (echography, CT, and 18F-FDG PET) statistically. Results: MHL included a higher female population (90.5%) owing to a higher frequency of breast cancer frequency (80.9%). Axillary LNs of MHL did not show any LN fatty hilums (0%); however, those of VAHL and EqHL did (15.8 and 36%, respectively). After the logistic regression analysis of the patients who had axillary lymphadenopathy without any LN fatty hilums, the minor axis length and ellipticity (minor axis/major axis) in the largest axillary LN, SUVmax, and Tissue-to-Background Ratio (TBR) were useful in distinguishing malignant lymphadenopathies. Receiver-operating characteristic (ROC) analysis indicated that a cut-off value of ≥7.3 mm for the axillary LN minor axis (sensitivity: 0.714, specificity: 0.684) and of ≥0.671 for ellipticity (0.667 and 0.773, respectively) in the largest LN with the highest SUVmax and TBR were predictive of MHL. Conclusion: Axillary lymphadenopathy ≥7.3 mm of the minor axis and ≥0.671 of ellipticity in LN without fatty hilum suggests malignancy even in patients who have received COVID-19 vaccination. Further examinations such as 18F-FDG PET are recommended for such patients

In the study of relativistic jets one of the key open questions is their interaction with the environment on the microscopic level. Here, we study the initial evolution of both electron–proton (e^- - p⁺) and electron–positron (e^±) relativistic jets containing helical magnetic fields, focusing on their interaction with an ambient plasma. We have performed simulations of "global" jets containing helical magnetic fields in order to examine how helical magnetic fields affect kinetic instabilities such as the Weibel instability, the kinetic Kelvin-Helmholtz instability (kKHI) and the Mushroom instability (MI). In our initial simulation study these kinetic instabilities are suppressed and new types of instabilities can grow. In the e^- - p⁺ jet simulation recollimation-like instability occurs and jet electrons are strongly perturbed. In the e^± jet simulation a recollimation-like instability occurs at early times followed by a kinetic instability and the general structure is similar to a simulation without helical magnetic field. Simulations using much larger systems are required in order to thoroughly follow the evolution of global jets containing helical magnetic fields.

Dopaminergic replacement therapy remains the mainstay of symptomatic treatment for Parkinson’s disease (PD), but many unmet needs and gaps remain. Device based treatments or device-aided non-oral therapies are typically used in the advanced stages of PD, ranging from stereotactic deep brain stimulation to levodopa or apomorphine infusion therapies but there are concerns due to a number of procedural, hardware, or long-term treatment-related side effects of these treatments, and limited nonmotor benefit in PD. Therefore, there is an urgent unmet need for low risk adjuvants or standalone therapies which can address the range of burdensome motor and nonmotor symptoms that occur in PD. Recent studies suggest that non-invasive neurostimulation of the vestibular system may be able to address these gaps with stimulation of the vestibular brainstem sensory network which extensively innervates brain regions regulating both motor and a range of nonmotor functions. Therapeutic non-invasive vestibular stimulation is a relatively modern concept that may potentially improve a broad range of motor and nonmotor symptoms of PD, even at early stages of the disease. Here we review previous studies supporting the therapeutic potential of vestibular stimulation for the treatment of PD and discuss ongoing clinical trials and potential areas for future investigations.

This work aims to shed light on the differential diagnosis of Complex Post-Traumatic Stress Disorder (cPTSD), Post-Traumatic Stress Disorder (PTSD), and Borderline Personality Disorder (BPD) within the context of Intimate Partner Violence (IPV), which represents an extremely inno-vative field of clinical research. To this end, a critical review of the literature was conducted to identify and compare the clinical patterns and symptomatic overlaps among cPTSD, PTSD, and BPD, with an emphasis on their manifestation in both victims and offenders. The results show that despite some symptomatic similarities, cPTSD, PTSD and BPD have distinct clinical patterns in IPV. Disturbances in Self-Organization (DSO), are more commonly in offenders, while the di-agnosis of cPTSD is more aligned with the victims. In addition, cPTSD and characteristics of BPD, such as fear of rejection and instability of identity, constitute risk factors for IPV victimiza-tion. cPTSD is a predisposing factor not only for victims but also for offenders, while PTSD emerges as a consequential factor. The specific pathways linking PTSD, cPTSD, and BPD with IPV have significant implications for clinical practice. Further research is needed to understand these profiles and the mechanisms linking trauma-related features to IPV, which is crucial for imple-menting effective violence prevention programs.

Background. Escalating global plastic production, expected to reach 34,000 million tons by 2050, poses a significant threat to human and environmental well-being, particularly in aquatic ecosystems. Microplastics (MP) and nanoplastics (NP), which originate from the degradation of plastics, are of concern due to their potential bioaccumulation and uptake of pollutants. This study addresses identification methods and focuses on insect meal, a raw material for aquaculture feed. Methods. By using different techniques, the study was able to detect MP and NP in insect meal samples. Chemical digestion with KOH at 60°C efficiently removed organic matter without affecting the synthetic polymer polyethylene (PE). Filtration, confocal Raman microscopy, SEM and TEM were used for comprehensive analysis and integrity tests on PE films were performed using Raman and FTIR spectroscopy. The results showed the presence of PE microplastic particles in the insect meal, which was confirmed by correlative Raman and SEM mapping on a positively charged surface. In addition, the increased resolution of the Raman microscope identified submicrometric PE NP (800 nm). Transmission electron microscopy (TEM) with energy dispersive X-ray spectroscopy (EDX) confirmed plastic-like structures in the insect meal, highlighting the presence of PE plastics characterized by irregular shapes and some agglomeration. The higher carbon concentration in the EDX analysis supported the plastic nature, which was also confirmed by Raman spectroscopy. Conclusions. The study provides a robust method for the detection of MP and NP in insect meal and provides valuable insight into the possible presence of plastics in insect-based aquafeeds. The combination of different analytical methods increases the reliability of the results and sets the stage for future investigations that could focus on the quantification of NP and the assessment of their potential environmental impact.

Cafestol, a bioactive compound found in coffee, has attracted considerable attention due to its potential impact on cardiovascular health. This review aims to comprehensively explore the association between cafestol and cardiovascular diseases. We delve into the mechanisms through which cafestol influences lipid metabolism, inflammation, and endothelial function, all of which are pivotal in cardiovascular pathophysiology. Moreover, we meticulously analyze epidemiological studies and clinical trials to elucidate the relationship between cafestol and cardiovascular outcomes. Through a critical examination of existing literature, we aim to provide insights into the potential benefits and risks associated with cafestol concerning cardiovascular health.

Hydroxyapatite and b-tricalcium phosphate have been clinically applied as artificial bone materials due to their high biocompatibility. The development of artificial bones requires the verification of safety and efficacy through animal experiments; however, from the viewpoint of animal welfare, there is necessary to reduce the number of animal experiments. In this study, we utilized machine learning to construct a model that estimates the bone-forming ability of bioceramics from material fabrication conditions, material properties, and in vivo experimental conditions. We succeeded in constructing the two models as follows: ‘Model 1’, which predicts material properties from their fabrication conditions, and ‘Model 2’, which predicts the bone-formation rate from material properties and in vivo experimental conditions. By an inverse analysis of the two models, we proposed candidates for material fabrication conditions to achieve target values of bone-formation rate. Under the proposed conditions, the material properties of the fabricated material were consistent with the estimated material properties. Furthermore, a comparison between bone-formation rates after 12 weeks of implantation in the porcine tibia and the estimated bone-formation rate. This result showed that the actual bone-formation rates existed within the error range of the estimated bone-formation rates, indicating that machine learning consistently predicts the results of animal experiments using material fabrication conditions. We believe that these findings will lead to the establishment of alternative animal experiments to replace animal experiments in the development of artificial bones.

Keywords: Biomass pyrolysis, Chemical Looping Combustion, Life Cycle Assessment, Environmental Impacts, Carbon Footprint.

Proteins play a pivotal role in supporting athletes by promoting muscle hypertrophy and minimizing protein catabolism during exercise. They stimulate muscle protein synthesis, aiding in the repair of exercise-induced muscle damage and serving as an energy source, particularly for post-exercise glycogen replenishment. In individuals with phenylketonuria (PKU), for whom protein intake is limited to essential phenylalanine (Phe), supplementation with Phe-free amino acids or glycomacropeptides is necessary. Tailored for macronutrient and micronutrient content, these protein substitutes fulfill most protein requirements, but lack Phe, unlike dietary sources of protein. Protein requirements for athletes with PKU exceed general recommendations due to limited availability in supplements and potential catabolism mitigation. Various factors influence tolerated dietary Phe in PKU, including protein substitute quantity, distribution, pharmacological treatment, age, growth rate, pregnancy, catabolic states, and physical activity. While general protein requirements for PKU surpass those of the general population, adherence to supplement regimens is crucial for athletes and patients with PKU. Strategically timed protein substitutes enhance muscle protein synthesis, body composition, and sports performance within safety limits. Individualized intake is essential for optimal outcomes, as proteins have a multifaceted role in optimizing athletic performance and addressing challenges in PKU.

Over the last two decades, a considerable amount of equipment has been acquired (spreaders, seeders, sprayers, among others) to respond to the challenges of Precision Agriculture (PA) concept. Most of this equipment has been purchased at a high cost. However, many of them, despite still being functional and equipped with sensors, actuators, and electronic processing units capable of adjusting to variations in speed, have become obsolete in terms of communication, and incompatible with new monitoring and control systems based on the “Isobus” protocol. This work aims to present a solution for updating the control system (“Ferticontrol”) of a “Vicon RS-EDW” spreader with variable rate application (VRA), making it compatible with the “InCommand” system from “Ag Leader”. The solution includes low-cost “Arduino” and “Raspberry Pi” microcontrollers and open-source software. The development shows that it is possible to implement a solution that is accessible to farmers in general. It also provides a niche business opportunity for young researchers to set up small technology-based enterprises associated with universities and research centers. These partnerships guarantee permanent innovation and represent a decisive step towards modern, technological, competitive, and sustainable agriculture.

Generalized Bayes is a Bayesian approach based on the learning rate parameter η. In this study, we examine the effect of parameter η on the estimation results considering joint type-I and type-II hybrid censored samples from k exponential populations. In addition to the learning rate parameter, we consider two loss functions, the Linex and general entropy loss functions in the Bayesian approach. Monte Carlo simulations are performed to compare the performances of the estimation results under losses and different values of η. An illustrative example is performed to study the effect of the learning rate parameter and the different losses with different parameters.

It is difficult to capture the real-time online measurement data for biochemical oxygen demand (BOD) in wastewater treatment processes. An optimized extreme learning machine (ELM) based on an improved cuckoo search algorithm (ICS) is proposed in this paper for the design of soft BOD measurement model. In ICS-ELM, the input weights matrices of the extreme learning machine (ELM) and the threshold of the hidden layer are encoded as the cuckoo's nest locations. The best input weights matrices and threshold are obtained by using the strong global search ability of improved cuckoo search (ICS) algorithm. The optimal results can be used to improve the precision of forecasting based on less number of neurons of the hidden layer in ELM. Simulation results show that the soft sensor model has good real-time performance, high prediction accuracy and stronger generalization performance for BOD measurement of the effluent quality compared to other modeling methods such as back propagation (BP) network in most cases.

Decompression sickness (DCS) with neurological disorders is the leading cause of diving accidents. Exposure to high levels of CO2 during diving is a safety concern for occupational , groups at risk of DCS. However, the effects of prior exposure to CO2 have never been evaluated. The purpose of this study was to evaluate the effect of CO2 breathing prior to a provocative dive on the occurrence of DCS in mice. 50 mice were exposed to a maximum CO2 concentration of 70 hPa for one hour at atmospheric pressure. Another 50 mice breathing air under similar conditions served as controls. In the AIR group (controls), 22 out of 50 mice showed post-dive symptoms compared to 44 out of 50 in the CO2 group. We found that CO2 breathing is associated with a decrease in body temperature in mice and that CO2 exposure dramatically increases the incidence of DCS. More unexpectedly, it appears that a lower temperature of the animals even before exposure to the accident-prone protocol leads to an unfavorable prognosis. This study also suggests that the composition of the microbiota may influence thermogenesis and thus accidentology. Depending on prior exposure, some bacteria identified in this work could be perceived as protective or pathogenic.

Superior mesenteric artery (SMA) syndrome or Wilkie’s syndrome is a vascular compression disorder that causes abnormal compression of the third portion of the duodenum by the SMA. It has a low incidence rate, higher in young women, and is rarely associated with the Nutcracker phenomenon: a condition of compression of the left renal vein between the SMA and the aorta, which manifests as pain in the left flank and pelvis. Here we report the case of a 54-year-old woman with a history of repeated episodes of abdominal pain caused by the Nutcracker syndrome and Wilkie's syndrome.

With the rapid developments that have been made in computer vision and computer technology, semantic segmentation of high-resolution images has emerged as a mainstream and challenging task. The, segmentation of water areas remains a complex task due to the similar features between water areas or between water areas and other land objects. Meanwhile, since coastlines and riverbanks are typically presented in irregular shapes, it is difficult to obtain the categories of pixels at boundaries. This paper proposed the use of a Water-Land Boundary Attention Network (WLBANet) to improve the accuracy of pixels at boundaries between water and land. This network also reinforced the performance of contextual information extraction into distinguishing between water areas and other land objects. To prove the validity of this proposed network, WLBANet was performed on the Water Land Dataset (WLD), which is also by this paper, and which contains water areas and other land objects categories. The results demonstrates that the proposed method has significant effectiveness.

In this study, the microbial community during the barley yeast fermentation of stevia leaves and its correlation with antioxidant, antiobesity, and anti-inflammatory properties, as well as metabolites, were investigated using UPLC-Q-TOF-MS. Stevia was fermented using commercial TSB media (TSB 1, TSB 2, and TSB 3) and sucrose (Sucrose 1, Sucrose 3, and Sucrose 3) for 1, 3, and 5 days, respectively. Stevia ferments showed higher DPPH and ABTS radical scavenging capacity compared to samples incubated with sucrose for 5 days, and all six ferments inhibited nitric oxide production in a concentration-dependent manner in LPS-induced mouse macrophages. Furthermore, UPLC-QTOF-MS analysis identified 23 related substances, including 10 terpenoids, including rubusoside, steviolbioside, and rebadioside derivatives; dulcoside A; and phlomisoside II, which are indicators of stevia, as well as five flavonoids, four phenolic acids, and four fatty acids. We also identified the microbial community during fermentation via the next-generation sequencing of the 16S rRNA gene for bacteria and the internal transcribed spacer (ITS) gene for fungi. The results showed that TSB 1 and Sucrose 1 ferments were dominated by the pathogens Enterococcus hirae (58.93%) and Cronobacter sakazakii (80.92%), while samples fermented for more than 3 days were pathogen-free and dominated by lactic acid bacteria such as Pediococcus stilesii (73.37%). Microbial community analysis using the ITS region showed that Saccharomycopsis fibuligera, classified as a yeast rather than a mold, dominated the stevia fermentation regardless of the fermentation duration. In particular, the microbial community of the fermentation with a sugar solution was dominated by S. fibuligera by more than 99% throughout the fermentation periods of 1, 3, and 5 days. Finally, to apply the stevia ferments topically to human skin, skin irritation tests were performed on 30 volunteers. The results showed that the highly concentrated extracts (1 mg/mL) of all six stevia ferments were hypoallergenic. Taken together, these findings suggest that brewer's yeast fermented from stevia leaves with a sugar solution offers promise as a natural ingredient for use in functional foods and cosmetics.

Business-to-business (B2B) manufacturing companies are increasingly confronted with transformative trends such as sustainability, digitalization, and servitization. These trends are changing how product portfolios are developed, and value contributions are assessed, and therefore have disruptive potential. Dealing with these disruptive factors in Product Portfolio Management (PPM) is a largely unexplored topic. This study presents an empirical-qualitative exploration that contributes significantly to the field. The aim is to clarify the extent to which disruptive factors influence the evaluation and shaping of the product portfolio in B2B manufacturing companies. The Gioia method was used to evaluate 21 semi-structured interviews with experts from leading B2B manufacturing companies. Eight overarching challenges in PPM resulting from the disruptive factors were identified. Based on the eight overarching challenges and their associated causal relationships, two aggregated dimensions of action were derived: (1) increasing speed and flexibility by using generative artificial intelligence (AI) in a defined PPM process and (2) adjusting the product portfolio evaluation to consider various strategic drivers. These two dimensions of action call for future research to overcome the disruptive factors in PPM.

Subacute rumen acidosis (SARA) is a prevalent issue in intensive livestock farming, particularly associated with high-concentrate diets. This study investigates the prevalence and impact of SARA in Greek dairy sheep farming and explores the use of computerized rumen colorimetry as a management and diagnostic tool for SARA in dairy sheep farms. Forty-two dairy sheep flocks were monitored regularly for rumen pH, milk composition, and milk yield over an approximately 9-month milking period. Computerized Rumen Mucosal Colorimetry was applied to 280 culled, aged ewes from these farms, with rumen wall samples taken for histological examination. SARA cases were identified in 19 farms (45%, n=48). Farms with SARA cases had lower milk fat levels, although milk yield was higher in these farms, while milk protein levels did not differ based on the SARA status of the farms. In culled ewes, rumen color was significantly associated with the farm's SARA status. Additionally, ewes from farms with more SARA cases exhibited increased thickness in the ruminal epithelium layers, particularly in the non-keratinized and total epithelium layers. In conclusion, SARA is a common disorder in the Greek dairy sheep industry, lowering the fat content of milk. The study suggests that computerized rumen epithelium colorimetry in aged culled ewes shows promise as a diagnostic tool for SARA in dairy sheep farms.

K+ channels do play a role in cell shape changes observed during cell proliferation and apoptosis. Research suggested that the dynamics of aggregation of Aquaporin-4 (AQP4) into AQP4-OAPs isoforms can trigger cell shape changes in malignant glioma cells. Here, we investigated the relationship between AQP4 and some K+ channels in the malignant glioma U87 line. The U87 cells transfected with the human M1-AQP4 and M23-AQP4 isoforms were investigated for morphology, gene expression of KCNJ8, KCNJ11, ABCC8, ABCC9, KCNMA1, and Cyclin genes by RT-PCR, recording the whole-cell K+ ions currents by patch-clamp experiments. AQP4 aggregation into OAPs increases the plasma membrane functional expression of the Kir6.2 and SUR2 subunits of the KATP channels, and of the KCNMA1 of the BK channels in U87 cells leading to a large increase in inward and outward K+ ion currents. These changes were associated with changes in morphology with a decrease in cell volume in the U87 cells and an increase in the ER density. These U87 cells accumulate in the mitotic and G2 cell cycle. The KATP channel blocker zoledronic acid reduced cell proliferation in either M23 AQP4-OAPs and M1 AQP4-tetramers transfected cells leading to early and late apoptosis, respectively. BK channel sustains the efflux of K+ ions associated with the M23 AQP4-OAPs expression in the U87 cells, but it is downregulated in the M1 AQP4-tetramers cells; KATP channels are effective in the M1 AQP4-tetramers and M23 AQP4-OAPs cells. Zoledronic acid can be effective in targeting pathogenic M1 AQP4-tetramers cell phenotype inhibiting KATP channels and inducing early apoptosis.

Manuka honey (MH) exhibits potential antitumor activity in preclinical models of a number of human cancers. Treatment in vitro with MH at concentrations ranging from 0.3-5.0% (w/v) led to significant dose-dependent inhibition of proliferation of human breast cancer MCF-7 cells, but anti-proliferative effects of MH were less pronounced in triple-negative MDA-MB-231 breast cancer cells. Effects of MH were also tested on non-malignant human mammary epithelial cells (HMEC) at 2.5% w/v, and it was found that MH reduced proliferation of MCF-7 cells but not that of HMEC. Notably, the antitumor activity of MH was in the range of that exerted by treatment of MCF-7 cells with the antiestrogen tamoxifen. Further, MH treatment stimulated apoptosis of MCF-7 cells in vitro, with most cells exhibiting acute and significant levels of apoptosis that correlated with PARP activation. Additionally, effects of MH induced activation of AMPK and inhibition of AKT/mTOR downstream signaling. Treatment of MCF7 cells with increased concentrations of MH induced AMPK phosphorylation in a dose dependent manner that was accompanied by inhibition of phosphorylation of AKT and mTOR downstream effector protein S6. In addition, MH reduced phosphorylated STAT3 levels in vitro which may correlate with MH and AMPK-mediated anti-inflammatory properties. Further, in vivo, MH administered alone significantly inhibited the growth of established MCF-7 tumors in nude mice by 84%, resulting in an observable reduction in tumor volume. Our findings highlight the need for further research into the use of natural compounds, such as MH, for antitumor efficacy and potential chemoprevention and investigation of molecular pathways underlying these actions.

In the past two decades, several floods have affected people and their properties in Burkina Faso, with the unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other flood-prone regions in Burkina Faso. Specifically, there is a data and knowledge gap about the flood risk in the Haut-Bassins region, which in turn hampers the development of mitigation strategies and risk reduction measures in communities. This study demonstrates how data collected at the household level can be used to understand flood risk and its components at the village level in this data-scarce region. Using an indicator-based method, we analyze both flood risk and flood risk perception at the village level. Moreover, we determine the factors influencing flood risk perception at the household level using an ordered logit model. We find that 12 out of the 14 villages considered, experience high levels of flood risk. The management of runoff from the nearest urban areas and poorly designed civil engineering infrastructures, such as roads, were highlighted by the households as significant factors that increase their vulnerability. Hence, dependencies in space and between urban and rural areas may play a substantial role in modifying risk. The perceived flood risk consistently exceeds the estimated flood risk, with an insignificant positive correlation between both risk indices. Regression results indicate that flood risk perception is mainly influenced by informational and behavioral factors of the households. The findings of this study can provide valuable information to municipal and regional authorities involved in disaster risk management in the study area. Moreover, the method is transferable to other data-scarce regions

Secondary prevention after SCA (acute coronary syndrome) is of paramount importance to reduce the incidence of MACE and improve prognosis in follow-up. The control of avoidable risk factors, lifestyle modifications, but especially careful control of cholesterolemia (with a target of LDL-C

Mutations affecting codon 172 of the isocitrate dehydrogenase 2 (IDH2) gene define a subgroup of sinonasal undifferentiated carcinomas (SNUCs) with a relatively favorable prognosis and a globally hypermethylated phenotype. They are also recurrent (along with IDH1 mutations) in gliomas, acute myeloid leukemia, and intrahepatic cholangiocarcinoma. Commonly reported mutations, all associated with aberrant IDH2 enzymatic activity, include R172S, R172T, R172G, and R172M. We present a case of SNUC with a never-before-described IDH2 mutation, R172A. Our report compares the methylation pattern of our sample to other cases from the GEO database. Hierarchical clustering suggests a strong association between our sample and other IDH-mutant SNUCs and a clear distinction between sino-nasal normal tissues and tumors. Principal component analysis (PCA), using 100 principal components explaining 94.5% of the variance, shows the position of our sample within 1.02 standard deviation of the other IDH-mutant SNUCs. Molecular modeling analysis of the IDH2 R172A versus other R172 variants provides a structural explanation to how they affect the protein active site. Our findings thus suggest that the R172A mutation in IDH2 confers a gain of function similar to other R172 mutations in IDH2, resulting in a similar hypermethylated profile.

During the coronavirus disease 2019 (COVID-19) pandemic, individuals with immune-mediated inflammatory diseases (IMIDs), such as systemic lupus erythematosus and rheumatoid arthritis, face a heightened risk of infection and severe outcomes due to immunological alterations resulting from their underlying conditions and immunosuppressive treatments. Even as the pandemic has transitioned to an endemic state, it remains crucial to recognize that these patients continue to be at risk. In this narrative review, we analyzed existing literature to explore the impact of IMIDs, clinical risk factors, and the influence of immunosuppressive therapies on COVID-19-related risks and outcomes. Notably, certain disease-modifying antirheumatic drugs (DMARDs), like rituximab, are associated with worse COVID-19 outcomes, and rituximab-treated patients show impaired immune responses to COVID-19 vaccination. Additionally, we outline the diverse effects of glucocorticoids on COVID-19 outcomes and management. To highlight real-life challenges faced by clinicians caring for patients with IMIDs, we present an illustrative scenario that underscores the importance of effective vaccination, timely boosting, and additional mitigation strategies against COVID-19. Given the clinical heterogeneity and diverse disease states within IMIDs, it is crucial to understand the ongoing implications and risks associated with COVID-19 in these patients, to guide the implementation of appropriate measures and optimize care and outcomes in the current endemic era.

Beyond factors such as smoking and obesity, the risk of getting gastrointestinal cancer is passed down from parents to offspring, inherited by a gene mutation, predisposing them to develop cancer in their lifetime. Here we describe the clinical history of family members affected by gastrointestinal pathologies often leading to cancer. In the epidemiological study, the cohort of members of this family shared a high risk of developing gastrointestinal diseases. The subjects were monitored from May 2006 to December 2017 by collecting periodically clinical and endoscopic data, and determining both auto-modification of lymphocyte Poly(ADP-ribose)Polymerase as early signal of DNA damage, and erythrocyte membrane lipid composition (Fat Profile). Both biomarkers were demonstrated to be non invasive and easy tools, to monitor over time family members, first the oldest members (nine siblings), and thereafter their offspring, whose cell status evolved from physiological even to cancerous one. All subjects developed gastrointestinal pathologies of different kind and seriousness. Some diseases evolved to cancer, sometimes as a sudden and lethal event. The results of the two molecular approaches, agreed and even predicted the clinical and imaging paths. This cohort study supported the hypothesis that both noninvasive molecular analyses can predict altered cell states and support clinical and imaging tests.

Evaluating flood risk though numerical simulations in areas where hydrometric and bathymetric data are scarcely available is a challenge. This is however of paramount importance, particularly in urban areas, where huge losses of human life and extensive damage can occur. This paper focuses on the June 2-3, 2023 event at Léogâne in Haiti, where the Rouyonne River partly flooded the city. Water depths in the river were recorded since April 2022 and a few discharges were measured manually but it was not sufficient to produce a reliable rating curve. Using a uniform flow assumption combined with the BaRatin method (Bayesian rating curve), it was possible to extrapolate the existing data to higher discharges. From there, a rainfall-runoff relation was developed for the site using the AtHyS distributed hydrological model, which allowed to determine the discharge of the June 2023 event, which was estimated as twice the maximum conveying capacity of the river in the measurement section. Bathymetric data were obtained using drone-based photogrammetry and two-dimensional simulations were carried out using the WATLAB computational environment to represent the flooded area and the associated water depths. By comparing the water depths of 21 measured high-water marks with the simulation results, we obtain KGE and NSE criteria of, respectively, 0.890 and 0.882. This allows us to conclude that the model is sufficiently accurate and could be used by flood managers and decision-makers to assess flood risk and vulnerability in Haiti.

This study investigated the effects of a ten-visit individual coordinative locomotor training (CLT) program, including both a hands-on and a hands-off approach, on static and dynamic trunk stability in healthy adults with sedentary occupations. During the ten-visit program, the performance of eight subjects was monitored using a modified one-leg stance test in the sprinter and skater position, the Y-balance test, and the scapula and ischial tuberosity control test in the four-legged position. The data were analyzed using parametric and nonparametric statistics at an overall level of significance α=0.05. In the one-leg stance test, all subjects achieved a maximum value of 60 s on all ten visits. The improvement over time in the Y-balance test results was statistically significant for all directions (p<0.001). In addition, a statistically significant improvement in the Y-balance test composite score was observed between the first and the last visit (p=0.015-0.041). Subject-specific patterns were observed in the results of the Y-balance test. Significant improvements were observed over time in the four-legged position test score (p=0.008-0.010). Overall, the CLT program led to a significant improvement in trunk stability and leg extension in the anterior and posterolateral directions, as well as a reduction in instability as determined by the composite score of the Y-balance test.

This study delves into the impact of artificial intelligence on students’ learning.The paper pioneers the use of kmeans classification to reduce the dimensionality of features before the classification process, which minimizes redundant information and computational overhead. This step is not commonly found in prior research.Firstly, a random forest model is established with “whether AI assistance was used to complete the paper” as the output, and various features as inputs. The analysis of the predictive accuracy when changing input features reveals the degree of influence of each feature on using AI to complete the paper. After feature selection, the remaining 6 features can still effectively predict the use of AI to complete the paper, indicating the representativeness of the extracted indicators. Subsequently, the PCA-K-means algorithm is employed to classify the use of artificial intelligence. PCA algorithm is used for dimensionality reduction of the extracted features to better characterize students’ use of AI. Three representative variables are selected, and the contribution of each feature is computed based on the factor loading matrix. Finally, the K-means algorithm is used to classify students based on the three dimensional features, showing that students can be effectively classified into 2 categories. The results indicate that the majority of students support the use of AI technology to enhance their abilities, although some students may only intend to use AI to cope with exams and similar tasks.

A mathematical procedure enabling the transformation of an arbitrary tessellation of a surface into a bi-colored complete graph is introduced. Polygons constituting the tessellation are represented by vertices of the graphs. Vertices of the graphs are connected by two kinds of links/edges, namely, by a green link, when polygons have the same number of sides, and by a red link, when the polygons have a different number of sides. This procedure gives rise to a semi-transitive, complete, bi-colored Ramsey graph. The Ramsey number was established as R_trans (3,3)=5. Shannon entropies of the tessellation and graphs are introduced. Ramsey graphs emerging from random Voronoi and Poisson Line tessellations were investigated. The limits ζ=lim┬(N→∞)⁡〖N_g/N_r 〗, where N is the total number of green and red seeds, N_g and N_r, were found ζ=0.272±0.001 (Voronoi) and ζ= 0.47±0.02 (Poisson Line). The Shannon Entropy for the random Voronoi tessellation was calculated as S= 1.690±0.001 and for the Poisson line tessellation as S =1.265±0.015.

Abstract: Background: COVID-19 is associated with various changes in immunity, including signaling through the pattern-recognition receptors (PRR). However, the role of these processes is poorly understood. The present study aimed to evaluate the relationships of the serum levels of the cyclic dinucleotide 2’3’-cyclic GMP-AMP (cGAMP) marker of PRR activation with immunoglobulin G antibodies against severe acute respiratory syndrome-linked coronavirus (IgG-SARS)-positive status and endothelial dysfunction in apparently healthy subjects and in patients with coronary heart disease (CHD). Methods: The present study investigated selected groups from two cohorts, including cohort 1 of 307 healthy volunteers and cohort 2 of 218 CHD patients. COVID-19 infection was confirmed by the detection of IgG-SARS against SARS-CoV-2 S1 protein receptor-binding domain. Cohort 1 (24–69 years of age; 44.8 ± 8.6 years; 80.4% men) was examined for systematic coronary risk evaluation by European Society of Cardiology (SCORE) starting from 2019 before the onset of the COVID-19 pandemic. Cohort 2 (63±10.9 years of age, 54% men) was processed starting from 2017 (three years prior to the COVID-19 pandemic) in a hospital setting to undergo coronary angiography to assess coronary lesions as Gensini score. The levels of cGAMP and endothelial markers (nitrate and nitrite combined as NOx and endothelin-1) were assessed in the serum to evaluate the associations with IgG-SARS status, SCORE, and extent of coronary lesions by correlation and receiver operating characteristic (ROC) analyses. Results: Serum cGAMP did not discriminate between SARS-positive and SARS-negative healthy subject of cohort 1. Moreover, the level of cGAMP was not associated with endothelial biomarkers in healthy subjects. However, serum cGAMP was associated with atherosclerosis in cohort 2 in patients with CHD (area under the curve (AUC) 0.69; 95% CI 0.587-0.806; P=0.001), indicating that serum cGAMP was lower in patients with coronary stenosis compared to that in patients without coronary lesions. Conclusions: Low levels of serum cGAMP were associated with atherosclerosis and markers of endothelial dysfunction in patients with CHD. However, cGAMP was not associated with endothelial biomarkers or IgG-SASR immune status in healthy subjects, suggesting that cGAMP may be a new biomarker of coronary lesions in the context of sterile inflammation.

Within the polyurethanes market, only 0.1% are from renewable sources. With the continuing concern about climate change and greenhouse gases in the atmosphere, the substitution of monomers and processes derived from petrochemical sources is crucial for the development of biomaterials. Therefore, polyhydroxyurethanes have propose due to their synthesis route with the incorporation of monomers from renewable sources such as vegetable oils and the substitution of isocyanates known for their high toxicity, carcinogenicity and petrochemical origin, and the use of carbon dioxide. There are few reports on the use of soybean oil and the possible application of these materials in wound healing applications. Based on this, polyhydroxyurethanes were obtained from carbonated soybean oil and two diamines, one aliphatic: 1,4-butadiamine (putrescine), and one cycloaliphatic: 1,3-cyclohexanobis(methylamine), and they were physiochemically, mechanically, and thermally characterized. Four polyhydroxyurethanes were obtained, with stability to hydrolytic and oxidative media, thermal stability above 200 °C, tensile strength between 0.9-1.1 MPa, elongation at break between 81 and 222%. And water absorption up 102% and contact angle between 63,70 and 101,39. Achieving new formulations of biobased NIPHUs that represent a more sustainable process which allow to achieve the physicochemical, mechanical, and thermal properties required for the preparation of wound dressings.

The rehabilitation of abandoned mining sites is an increasingly pressing issue in the context of sustainable development. Recent research has emphasized the need for a holistic approach to the abandoned mining sites and their environmental rehabilitation. Based on field analysis, environmental assessments, satellite imagery processing and geographic information operations, this paper pushes forward the existing knowledge by doing a comprehensive assessment of abandoned mining sites in the Romanian Carpathians and by proposing innovative and sustainable rehabilitation solutions. Our findings highlight that abandoned mining sites and their surrounding territories in the Romanian mountains have significant ecological imbalances and complex socio-economic issues. The findings also suggest that by adopting innovative, integrated, and sustainability-oriented approaches, territories affected by mining can be transformed into valuable and sustainable spaces to meet human needs. We conclude by presenting the importance of innovation in ecological reconstruction and spatial-functional reintegration of mining sites in mountain areas as a useful tool in making fair decisions, both in the context of implementing appropriate development policies as well as for resilience and environmental sustainability of mining-affected mountain areas.

The energy efficiency of existing buildings is a crucial factor in addressing Europe’s energy con-sumption challenges, accounting for nearly 40% of the total energy usage. The ongoing energy crisis, driven by the reliance on fossil fuels and increasing prices, has underscored the urgency of adopting sustainable and energy efficient practices especially to the existing building stock. Cyprus is par-ticularly vulnerable due to its heavy dependence on imported fuels for electricity generation and faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. Extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings. This study examines an existing cultural hall. The case study of the Cultural Hall represents the building stock before 2010 which is lacking thermal in-sulation, double glazing and any energy efficient element. It then offers an ideal case study to ex-plore sustainable solutions which can be easily adopted from the construction industry and from the building owners. The primary objective of this research is twofold: first, to develop a comprehensive retrofit plan to transform the cultural hall into a net-zero energy building; and second, to explore how this transformation can give value back to the local community. After running two simulation scenarios and providing two energy performance certificates, one with at the existing state and one with the intended retrofit measures, it is clear that the building can be a net zero energy consump-tion building. Some interesting results derived, present also how this building can provide value back to the community i.e. through solar carports for EV charging.

Sulfate, the main dissolved contaminant in acid mine drainage (AMD), is ubiquitous in watersheds affected by coal and metal mining operations worldwide. Engineered passive bioremediation systems (PBS) are low-cost technologies that remediate sulfate contamination by promoting (1) precipitation of sulfate-bearing compounds, such as schwertmannite and gypsum; and (2) microbially-mediated sulfate reduction (BSR) to sulfide with subsequent precipitation of sulfide minerals. In this study, chemical and sulfur isotopic data are used to infer multiple pathways for sulfate sequestration in the Tab-Simco PBS. By simultaneously monitoring sulfate concentrations and δ34SSO4 values at four sampling points across the PBS, we (1) identified that the organic layer within the bioreactor was the primary site of BSR processes contributing to sulfate sequestration; (2) observed seasonal variations of BSR processes; (3) estimated that initially the BSR processes contributed up to 30% to sulfate sequestration in the Tab-Simco bioreactor; and (4) determined that BSR contribution to sulfate sequestration continuously declined over the PBS operational lifetime. Together, our results highlight the utility of combining geochemical and microbial fingerprinting techniques to decipher complementary processes involved in sulfur cycling in a PBS as well as the value of adding the sulfur isotope approach as an essential tool to help understand, predict, prevent and mitigate sulfate contamination in AMD-impacted systems.

Polymeric Intraocular lenses (IOLs) are vital for restoring vision following cataract surgery and for correcting refractive errors. Despite technological and medical advancements, challenges persist in achieving optimal vision and preventing complications. Surface modifications aim to mitigate the risk of posterior capsule opacification (PCO), while pre-operative measurements aid in selecting suitable IOLs. However, individualized solutions are lacking and there is a clear demand for the development of fully customised IOL surfaces. We employ laser micromachining technology for precise modifications via ablation on PMMA and Acrylic IOLs, using femtosecond (fs), nanosecond (ns), and diode continuous wave (CW) lasers, at wavelengths ranging from near-ultraviolet to infrared. Characterization reveals controlled ablation patterning, achieving feature sizes from as small as 400 nm to several micrometers. Regular and confocal Micro-Raman spectroscopy revealed alterations of the IOL materials' structural integrity for some pattering cases, thus affecting the optical properties, while these can be minimised by proper selection of micromachining conditions. The results suggest the feasibility of accurate IOL patterning, which could offer personalized vision correction solutions, based on relevant corneal wavefront data, thus surpassing standard lenses, marking a significant advancement in cataract surgery outcomes.

Long COVID (Post-Acute Sequelae of COVID-19, PASC) is a consequence of infection by SARS-CoV-2 that continues to disrupt the well-being of millions of affected individuals for many months beyond their first infection. While the exact mechanisms underlying PASC remain to be defined, hypotheses regarding the pathogenesis of Long COVID are varied and include (but are not limited to) dysregulated local or systemic inflammatory responses, autoimmune mechanisms, viral-induced hormonal imbalances and long-term persistence of virus and/or fragments of viral RNA or proteins. This review article is based on a comprehensive review of the wide range of symptoms most often observed in long COVID and an attempt to integrate that information into a plausible hypothesis for the pathogenesis of PASC. In particular, it is proposed that longterm dysregulation of the gut in response to viral persistence could lead to the myriad of symptoms observed in PASC.

Accurate segmentation of the Left Ventricle (LV) in Echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing the YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed-accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction, while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO based model on a well-annotated Echo image dataset, we can leverage the model's strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31%and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care.

Zinc nanoparticles (ZnNPs) open new opportunities for biomedical applications as a strategy against microbes and dye removal in an efficient way. The composite ZnNPs using Rhododendron arboreum (R. arboreum) stem bark were synthesized and characterized for UV-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The synthesized nanoparticles showed zones of inhibition of 23±0.09, 18±0.1 and 16±0.05 mm, against the Klebsiella pneumoniae (K. pneumoniae), Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli strains. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values against K. pneumoniae, S. aureus, and E. coli were found to be 34±0.21 and 72.71±0.47, 47±0.11 and 94.86±0.84 and 94±0.18 and 185.43±0.16 µg/mL, respectively. The biosynthesized ZnNPs resulted in significant eradication of the outer and inner membranes of the bacterial cells. Likewise, the synthesized ZnNPs showed time-dependent photocatalytic degradation activity and revealed 65% methyl orange dye degradation with an irradiation period of 6 hours. The findings of this study suggest the suitability of the novel R. arboreum stem bark-based ZnNPs as an effective ameliorant against bactericidal activities and photocatalysts for the removal of hazardous water contaminants.

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7,738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method. We further applied Cochran’s Q statistical analysis, MR-Egger intercept, and MR-PRESSO for heterogeneity and pleiotropy assessment, alongside a Bonferroni correction ((P

This study aims to unravel the paradox of perceptions and knowledge of the flood victims towards the causes of the disaster in both internal and external context. Internal context comprises of a comparison of perceptions and knowledge based on individual characteristics (age, gender, education and income). Whereas, the external context includes the factors of the awareness of the victims towards the amount of rainfall, the impact of land use changes as well as the negligence of the responsible parties. The main objective of this study is to determine the differences of perception and knowledge of December 2014 flood victims in Kelantan towards the factors that lead to the flood. This disaster had resulted in huge amount of money loss as well as traumatize the victims in which can be felt to this day. Since that incident, there were various points of view and different perceptions in finding the cause of the disaster occurred. Besides that, the study found that the level of perception and knowledge as to the cause of the disaster is different in the internal context (individual characteristics). This difference has a significant influence on the awareness of the causes of the floods that occurred in the external context. Significant relationships at the level of p <0.05 has existed between perception and knowledge of the causes of the disaster victims affected by environmental changes in the last 10 years. This indicates that although the victim is aware of the physical environment changes happening around them, but all that is seen as not a major contributing factor to the cause of the floods in Kelantan in 2014.

This comprehensive review explores the advancements in processing-in-memory (PIM) techniques for deep learning applications. It addresses the challenges faced by monolithic chip architectures and highlights the benefits of chiplet-based designs in terms of scalability, modularity, and flexibility. The review emphasizes the importance of dataflow-awareness, communication optimization, and thermal considerations in designing PIM-enabled manycore architectures. It discusses different machine learning workloads and their tailored dataflow requirements. Additionally, the review presents a heterogeneous PIM system for energy-efficient neural network training and discusses thermally efficient dataflow-aware monolithic 3D (M3D) NoC architectures for accelerating CNN inferencing. The advantages of TEFLON (Thermally Efficient Dataflow-Aware 3D NoC) over performance-optimized SFC-based counterparts are highlighted. Overall, this review provides valuable insights into the development and evaluation of chiplet and PIM architectures, emphasizing improved performance, energy efficiency, and inference accuracy in deep learning applications.

Some evidence supports the influence of the implant macro-design and primary stability. Additionally, tactile perception can be used to assess implant stability when placing the implant. This research aimed to quantify the primary and secondary stability of three implant systems with two different macro geometries (cylindrical and conical) determined through the insertion torque and the implant stability quotient (ISQ) at the moment of implant placement as a function of implant-related factors (length, width, dental arch, and implant location in the arch), intraoperative factors (bone density determined subjectively by the clinician's tactile perception), and patient-related factors (age, gender and bone density determined objectively in the cone beam computed tomography (CBCT). Methods: 102 implants of three implant systems with two different macro geometries (conical and cylindrical) were placed in 53 patients. The insertion torque, the ISQ at the implant placement (ISQ0), and bone quality according to the clinician's tactile sensation were recorded on the day of the surgery. After a three-month healing period, the ISQ was re-evaluated (ISQ3). Results: Cylindrical implants exhibited significantly higher insertion torque and ISQ at the moment of the surgery and after three months than conical implants. Cylindrical implants also showed significantly lower indices of tactile evaluation of bone quality during the implant placement surgery. However, no differences were demonstrated in the bone density measured objectively in the CBCT. (4) Conclusions: The cylindrical implants achieved the highest values for primary stability (Ncm and ISQ) and secondary stability (ISQ after three months). Insertion torque was the variable that most influenced ISQ on the day of the surgery. Implant location (incisors-canines, bicuspids-molars) and the implant macro geometry were the variables that most influenced the secondary stability (ISQ at three months).

Polyphenols are the most prevalent naturally occurring phytochemicals in the human diet and range in complexity from simple molecules to high-molecular-weight polymers. They have a broad range of chemical structures and are generally categorized as "neuroprotective," "anti-inflammatory," and "antioxidant" given their main function of halting disease onset and promoting health. Research has shown that some polyphenols and their metabolites can penetrate the blood-brain barrier and hence increase neuroprotective signaling and neurohormonal effects to provide anti-inflammatory and antioxidant effects. Therefore, multi-targeted modulation of polyphenols may prevent the progression of neuropsychiatric disorders and provide a new practical therapeutic strategy for difficult-to-treat neuropsychiatric disorders. Therefore, multi-target modulation of polyphenols has the potential to prevent the progression of neuropsychiatric disorders and provide a new practical therapeutic strategy for such nervous system diseases. Herein, we review the therapeutic benefits of polyphenols on autism-spectrum disorders, anxiety disorders, depression, and sleep disorders, along with in vitro and ex vivo experimental and clinical trials. Although their methods of action are still under investigation, polyphenols are still seldom employed directly as therapeutic agents for nervous system disorders. Comprehensive mechanistic investigations and large-scale multicenter randomized controlled trials are required to properly evaluate the safety, effectiveness, and side effects of polyphenols.

CGP do not substantially differ between initial tumor vs tumor recurrence and recurrent thymomas vs non-recurrent thymomas. Cell-cycle control genes alterations are associated with an early recurrence after thymectomy. Multiple target therapies are potentially available by performing a comprehensive CGP, suggesting that a precision medicine approach on these patients could be further explored.

Nepal, primarily an agricultural country, heavily relies on agricultural residue and fuelwood for daily energy requirements. In 2022, total energy consumption was 640 PJ, with traditional sources accounting for 64.17%, and fuelwood comprising 58.53% of total fuel consumption. The estimated potential supply of agricultural residue is 26 million tonnes, yielding about 442 million GJ of energy in 2021. Biomass trading often emphasizes volume or weight, necessitating a rapid and non-destructive assessment of energy properties for mutual benefit, aiding in the identification, management, and utilization of biomass sources. In this study, 200 biomass samples were collected in two batches (126 and 74 samples) from various locations in Nepal. Using Partial Least Squares Regression (PLSR), a model was developed correlating higher heating value (HHV) from a bomb calorimeter and spectral data from Fourier Transform near-infrared spectroscopy (FT-NIRS) (3595 – 12,489 cm-1) sensor. PLSR models incorporated raw spectra, eight preprocessing techniques, the multi-preprocessing five-range method, and a genetic algorithm. Outliers in the first batch were identified, and the first batch divided into an 80% calibration set and a 20% validation set, while the second batch was designated as an unknown sample set. The optimum PLSR model, utilizing first derivative preprocessing, improved accuracy by 6.77%, with coefficients of determination in the calibration set, validation set, and unknown set as 0.9694, 0.9578, and 0.8089, respectively. Root mean square errors were 132.4790 J/g, 189.4800 J/g, and 360.8845 J/g for the calibration set (RMSEC), validation set (RMSEP), and unknown set (RMSEUN), respectively. The prediction to deviation ratio (RPD) for the validation set and unknown set was 4.9 and 2.4, respectively. The cross validation model of combined sample data of every sets showed the R2CV of 0.95 and RPDCV of 4.6 indicating the model could serve as a reliable and swift non-destructive alternative for evaluating biomass HHV using NIRS and ready for updating for industrial use. However, incorporating a larger number of representative samples is crucial to enhance accuracy and develop a more comprehensive global model for predicting biomass HHV.

The extraocular muscles (EOMs) possess unique characteristics that set them apart from other skeletal muscles. These muscles, responsible for eye movements, exhibit remarkable resistance to various muscular dystrophies and aging, presenting a significant contrast to the vulnerability of skeletal muscles to these conditions. In this review, we delve into the cellular and molecular underpinnings of the distinct properties of EOMs. We explore their structural complexity, highlighting differences in fiber types, innervation patterns, and developmental origins. Notably, EOM fibers express a diverse array of myosin heavy chain isoforms, retaining embryonic forms into adulthood. Moreover, their motor innervation is characterized by a high ratio of nerve fibers to muscle fibers and the presence of unique neuromuscular junctions. These features contribute to the specialized functions of EOMs, including rapid and precise eye movements. Understanding the mechanisms behind the resilience of EOMs to disease and aging may offer insights into potential therapeutic strategies for treating muscular dystrophies and myopathies affecting other skeletal muscles.

Keywords: Chronic Obstructive Pulmonary Disease (COPD), Long Non-Coding RNAs (lncRNAs), Molecular Pathogenesis, Inflammation, Lung Cancer, Diagnostic Biomarkers

Urbanization is a dynamic process. At different stages of urbanization, polices of managing car-bon emissions should be adjusted. In this paper, two types of nighttime light data and statistical data of 68 cities in China from 2002 to 2021 are used to establish an urban development evalua-tion system comprising population, economy, construction, and society subsystems. Then, cities were categorized into expanding, contracting, and stable types to understand the uncertainty of urbanization's impact on carbon emissions. The main conclusions are as follows: (1) Integrated nighttime light data is used to extract built-up area boundaries, achieving an overall accuracy ranging from 68.75% to 98.4%, with kappa coefficients ranging between 0.60 and 0.94. (2) Ex-panding cities were concentrated in the eastern coastal regions, while contracting cities were mainly located in inland cities with traditional industries. Urban agglomerations in the Beijing-Tianjin-Hebei region, Yangtze River Delta region, and Chengdu-Chongqing metropolitan demonstrate synchronized characteristic of urbanization development. (3)Economy and con-struction have a greater impact on carbon emissions than population and society. For expanding cities, the focus of carbon emission governance should prioritize rational land use planning. Conversely, for contracting cities, emphasis should be placed on adjusting economic structures.

Convolutional Neural Networks (CNNs) are often criticized for their lack of transparency, acting as 'black boxes' in decision-making, a challenge compounded by class imbalance in ECG datasets, which limits their clinical application. This study introduces a CNN-based ECG signal classification model that enhances interpretability and addresses class imbalance through the Synthetic Minority Over-sampling Technique (SMOTE). The model also integrates Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and SHAP value analysis, facilitating the visualization of decision boundaries and the assessment of feature contributions. Our evaluation using the MIT-BIH Arrhythmia Database highlights the model's high performance, with accuracy and precision nearing 1.00 for Normal ECG (NOR), Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB), and Ventricular Premature Beat (PVC) in the six-class task. In the ten-class task, the model demonstrated robustness, particularly with an accuracy of 0.9846, precision of 0.9783, recall of 0.9736, and F1 score of 0.9760 in Pacemaker Fusion Beat (PFHB), supported by an AUC of 0.9999 and AP of 0.9885. These results underscore the model's efficacy in cardiac rhythm recognition and resilience to class imbalance. Future research will explore sophisticated model architectures and feature extraction methods to enhance the model's generalization and clinical applicability for early heart disease diagnosis and personalized treatment.

This study introduces a data obfuscation technique, leveraging the exponential map associated with the generators of Lie groups. Originating from quantum machine learning frameworks, our method illustrates the practical application of quantum mechanics principles in data processing. Specifically, it employs the exponential map of a generator algebra to introduce controlled noise into the data, achieving obfuscated data while preserving its utility for machine learning tasks. This strategy is shown to safeguard privacy in sensitive datasets, such as discussed medical records, and to enhance dataset volume and diversity through augmentation. Our empirical analysis, benchmarked against standard machine learning approaches, demonstrates that our method can maintain or even improve the predictive accuracy of the original data. This research highlights the potential of Lie group theory for advancing data privacy in medicine, marking a significant contribution to machine learning methodologies by offering the dual benefits of data obfuscation and enrichment. Through this synthesis of algebraic structures and machine learning, we propose new pathways for the secure and effective use of data in sensitive areas.

Species distribution models (SDMs) are usually used to predict current species’ geographic distributions and to forecast the impact of climate change, with different aims, such as conservation, and biodiversity management. SDMs use has been increasing in the last decades, however, they are vulnerable to parametrization and data quality input. Thus, inappropriate input can lead to potential unreliability in results. In this context, the most used data and methodologies in SDM, and putative deviations from the consensual best practices, were identified, by analysing recent literature (2018 to 2022). Results show that the parameters presented more consistently are the chosen algorithm (MaxEnt was used in 98% of the studies), the accuracy measures, and the time windows. Many papers fail to specify other parameters, limiting the reproducibility of the studies. Some papers also fail to provide information about the target species: only a fraction of the species' range is considered, or no justification for including specific variables in the model is provided. These options can decrease reliability in predictions under future scenarios since data provided to the model is inaccurate from the start or there is insufficient information for outputs discussion.

Wheeled mobile robot dynamics and suitable controller design are challenging but rewarding fields of study. By understanding the dynamics of wheeled mobile robots, it could be possible to design suitable hybrid control schemes for wheeled mobile robots. Since hybrid control schemes involve combining individual control methods to create a more effective overall control strategy. This can be done in a variety of ways, such as using fuzzy linear quadratic Gaussian control. We were therefore inspired to create dynamic models and their controller designs for the wheeled mobile robot by examining the dynamics of the wheeled mobile robot. The novelty of the current paper is to hybridize the different control schemes for wheeled mobile robots in order to get better performance. Entire systems models were simulated in a MATLAB/SIMULINK environment. The results obtained for the settling time response by FLQG were 87.1% over LQG; this study compared the effectiveness of current and previous FLQG controllers in external disturbances and found peak amplitude improvements of 71.25%. Therefore, the proposed controller is suitable for use with the wheeled mobile robot.

The band gap research in graphene is still a very important topic for materials application. Here, we report a band gap opening and p-type semiconducting property of the graphene by using an electrochemical doping on graphene surface. The manganese-oxide nanopar-ticles adsorbed on the graphene were used as the dopants in an electrolyte, which induce the band gap opening and the change of electronic structure. In addition, the fabricated graphene FET shows the p-type semiconductor behaviors. The temperature dependent conductivity of the p-type doped graphene at applied potential of 1.5 V during electro-chemical doping shows the formation of band gap of 0.23 eV, which is obtained from the fitting of conductivity equation. The semiconducting properties of manganese-oxide doped graphene is attributed to the formation of manganese-oxide nanoparticle on the surface of graphene.

Viral pathogens pose a substantial threat to public health and necessitate the development of effective remediation and antiviral strategies. This short communication aimed to investigate the antiviral efficacy of disinfectants on the surface proteins of human pathogenic viruses. Using in silico modeling, ligand binding energies (LBEs) of selected disinfectants were predicted and combined with their environmental impacts and costs through eco-pharmaco-economic analysis (EPEA). Results revealed the binding affinities of chemical disinfectants to viral proteins varied significantly (p

Purpose: Post-pandemic management of COVID-19 infections and any emergent outbreaks is as an endemic disease remains a public health concern. Vaccine hesitancy may continue to hamper efforts to respond any new disease outbreaks and future epidemics. This qualitative study aimed to explore factors influencing covid-19 vaccine acceptance and hesitancy in Kenya too gain deeper insights on this issue. Methods: The study was implemented in Western Kenya using key informant interviews. Fourteen (14) key informants were purposively selected for the study. All interviews were transcribed and analyzed using thematic analysis. Interpretation of findings was done within the framework of the Health Belief Model. Key findings: Knowledge was a critical factor in combatting misinformation and fostering vaccine acceptance among participants in this study. Misinformation included rumors that the vaccine lowers immunity and was intended for population control. Cues to action included influence from political and opinion leaders and observing the loss of life among unvaccinated individuals. Perceived barriers to vaccine uptake included fear of vaccine safety, side effects, long waiting times at that time of our study, fear of contracting the COVID-19 at vaccination sites, family/spousal influence on vaccine uptake and fear of the unknown with the vaccine. Conclusion: Findings from this study provides insight into areas for targeted strategies for managing Covid-19 vaccinations and future pandemics. Within the framework of the Health Belief Model, this study identified salient barriers and facilitators of COVID-19 vaccine hesitancy that may be helpful to inform future pandemic response.

The present study analyzed the effect of temperature, pH, retention time, pretreatment and mixing ratio on the anerobic digestion process. The parameters during the anaerobic co digestion of cow manure and food waste were then optimized using the Taguchi experimental design method. ANOVA is carried out to find the significant parameters which influence the biogas production. Experimental tests were carried out at laboratory scale reactors kept at different temperatures (28 °C, 35 °C, and 50 °C). The specific methanogenic Performance (SMP) during anerobic digestion at higher temperatures was characterized with the analysis of acetate, propionate, butyrate, hydrogen, glucose, and formate. The improvement of biogas production with different pre-treatment i.e., ultrasonic, autoclave, and microwave techniques also analysed. The results showed that reactor that maintained at 35 °C showed the highest biogas production. While the reactor that maintained at lower temperature (28 °C) produced the lower volume of biogas. As the retention time increases, the amount of biogas produced increases. Methanogenic activities of microorganisms reduced at higher temperature conditions (65 °C). Biogas production increased by 28.1%, 20.23%, and 13.27 % when the of substrates treated with ultrasonic, autoclave, and microwave, respectively, compared to the untreated substrate. The optimized condition for the highest biogas production during anaerobic co digestion of food waste and cow manure is temperature of 35 °C, pH of 7 and mixing ratio (CM: FW=1.5:0.5). ANOVA showed that temperature is the most important input parameter affecting biogas production, followed by mixing ratio.

One of the most crucial elements in deeply understanding humans on a psychological level is manifested through facial expressions. The analysis of a human behavior can be informed by their facial expressions, making it essential to employ indicators such as expression (Expr), valence-arousal (VA), and action units (AU). In this paper, we introduce the method proposed in the Challenge of the 6th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW) at CVPR 2024. Our proposed method utilizes the multi-modal Aff-wild2 dataset, which is splitted into spatial and audio modalities. For the spatial data, we extract features using a SimMiM model that was pre-trained on a diverse set of facial expression data. For the audio data, we extract features using a WAV2VEC model. To fusion the extracted spatial and audio features, we employed the cascaded cross-attention mechanism of a transformer.

Existing implants used with Total Knee Arthroplasty (TKA), Total Hip Arthroplasty (THA), and other joint reconstruction treatments, have displayed premature failures and frequent needs for revision surgery in recent years, particularly with young active patients who represent more than 55% of all joint reconstruction patients. Bone cement and stress shielding have been identified as the major reasons for premature joint failures. A breakdown of the cement may happen, and revision surgery may be needed because of the aseptic loosening. The significant mismatch of stiffness properties of patient trabecular bones and metallic implant materials in joint reconstruction surgery results in the stress shielding phenomenon. This could lead to significant bone resorption and increased risk of bone fracture and the aseptic loosening of implants. The present project introduces an approach for development of customized cellular structures to match the mechanical properties and architecture of human trabecular bone. It consists of four modules:1- characterization of geometry, microarchitecture, and stiffness properties of patient’s bones; 2- developing customized lattice structures tailored to mimic properties established in module 1; 3 - integration of developed lattice structure into full scale implant design and manufacturing; 4- implementation of the developed technology for use in implants that would overcome most of the issues related to aseptic loosening phenomenon. The present work aims at fulfilling the objectives of module 2 by exploring new designs of customized lattice structures and texture tailored to mimic closely patients’ bone anisotropic properties and that can incorporate an engineered biological press-fit fixation technique. The effects of various lattice design variables on mechanical performance of the structure are examined through systematic experimental plan using statistical design of experiments technique and analysis of variance method. All tested lattice designs were explored under realistic geometrical, biological, and manufacturing constraints. Of the four design factors examined in this study, strut thickness was found to have the highest percent contribution (41%) regarding the structure stiffness, followed by unit cell type, and cell size. Srut shape was found to have the lowest effect with only 11% contribution. The introduced solution offers lattice structure designs that can be adjusted to match bone stiffness distribution and promote bone ingrowth and hence eliminating the phenomenon of stress shielding while incorporating biological press-fit fixation technique.

.(1) Background: Groundwater resources management in dry lands, characterized by climate var-iability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. The present study employed Analytic Hierarchy Process (AHP) and GIS to identify Ground-Water Potential (GWP) areas in a semi-arid region of Nigeria; (2) Methods: Land-use-land-cover, drainage density, slope, rainfall, static water level, soil media, vadose media and aquifer media were selected for GWP analysis. Parameters weights were de-termined using AHP and ranked based on their contribution to GWP by experts. The parameters were then integrated using weighted overlay tool in ArcGIS 10.5 to produce GWP map of the study area. Boreholes yield data from 245 wells were collected to determine the model accuracy and model validation; (3) Results: Results classified the study area into very high GWP (1.9%), high GWP (8.8%), moderate GWP (62%), low GWP (20.70%) and very low GWP (6.6%). Validation of the AHP model with boreholes yield data shows a correlation coefficient of 71.3% giving a good prediction; (4) Conclusions: AHP and GIS can be used to successfully map GWP areas which could serve as an exploration guide for sustainable management of groundwater resources in semi-arid areas.

In a dynamic production processes, mechanical degradation poses a significant challenge, impacting product quality and process efficiency. This paper explores a novel approach for monitoring degradation in the context of viscose fiber production, a highly dynamic manufacturing process. Using causal discovery techniques, our method allows domain experts to incorporate background knowledge into the creation of causal graphs. Further, it enhances the interpretability and increases the ability to identify potential problems via changes in causal relations over time. The case study employs a comprehensive analysis of the viscose fiber production process within a prominent textile industry, emphasizing the advantages of causal discovery for monitoring degradation. The results are compared with state-of-the-art methods, which are not considered to be interpretable, specifically LSTM-based autoencoders, showcasing the alignment and validation of our approach. This paper provides valuable information on degradation monitoring strategies, demonstrating the efficacy of causal discovery in dynamic manufacturing environments. The findings contribute to the evolving landscape of process optimization and quality control.

The exponential growth of the agricultural industry in the Amazon region has brought about notable economic advancements. However, this growth has substantially cost the region’s ecosystems, manifesting in increased deforestation and biodiversity degradation within the Amazon forest. This article is dedicated to assessing the eco-efficiency of agricultural production in Amazon biome municipalities. It places particular emphasis on identifying critical determinants through the utilization of the classic Data Envelopment Analysis (DEA) model for efficiency computation, super-efficiency models for distinctive characterization, bootstrap computational techniques for robust resampling, and the Malmquist index for calculating annual eco-efficiency indices of each Decision-Making Unit (DMU). An exploration of the correlation between efficiency and meteorological attributes of the municipalities is conducted. The findings of this study reveal several significant points: 1) Eco-efficient municipalities within the Amazon Biome can serve as benchmarks for other DMUs striving to attain optimal input-output levels. 2) Most municipalities in the Amazon Biome operate closely to the productive frontier due to the prevalent technology employed in their agricultural activities. 2) The nature of the technological frontier’s return suggests that small and large DMUs possess eco-efficiency potential. 4) The current dataset does not yield conclusive evidence regarding a direct correlation between the variables. Leveraging this information, strategic pathways can be formulated to drive economic development in tandem with the sustainability of Amazon Biome municipalities. These strategies promise to foster social, economic, and environmental benefits for the populace while providing valuable insights to inform future research within this thematic domain.

Laser machining by ultra-short (sub-ps) pulses at high intensity offers high precision, high throughput in terms of area or volume per unit time, and flexibility to adapt processing protocols to different materials on the same workpiece. Here we consider the challenge of optimization for high throughput: how to use the maximum available laser power and larger focal spots for larger ablation volumes by implementing a fast scan. This implies the use of high-intensity pulses approaching ∼PW/cm2 at the threshold where tunnelling ionization starts to contribute to overall ionization. A custom laser micromachining setup was developed and built to enable high speed, large area processing and easy system reconfiguration for different tasks. The main components include laser, stages, scanners, control system, and software. Machining of metals such as Cu, Al, or stainless steel, and fused silica surfaces at high-fluence and high-exposure doses at high scan speeds up to 3 m/s were tested for the fluence scaling of ablation volume, which was found to be linear. Modified surfaces are color-classified for their appearance, which is dependent on surface roughness and chemical modification. Such colour-coding can be used as a feedback parameter for industrial process control.

(1) Background: Hepatitis B virus (HBV) viral load (VL) is useful in determining treatment eligibility, however, due to high costs associated with the test, hepatitis B e antigen (HBeAg) is recommended as a proxy for HBV VL in resource-limited settings. (2) Methods: We used 299 archived plasma samples with hepatitis B surface antigen (HBsAg), HBeAg, and HBV VL (cut-off of 20,000 IU/mL and 200,000 IU/mL) results from people living with human immunodeficiency virus (PLWH). HBeAg and HBV VL results were analyzed to evaluate the use of HBeAg to determine CHB treatment eligibility and qualification of HBV prevention of mother-to-child transmission (PMTCT) prophylaxis for the first time in Botswana. (3) Results: Approximately 70.8% and 87.5% of participants with HBeAg-positive serology had HBV viral loads ≥20,000 IU/mL and 200,000 IU/mL respectively. Using logistic regression, the odds of having a qualifying HBV VL for CHB treatment and PMTCT prophylaxis were respectively 55.5 and 110.4 times higher in participants with positive HBeAg serology indicating a statistically significant association between HBeAg status and HBV VL. (4) Conclusions: HBeAg detection may not always correlate with high HBV VL, warranting further research focusing on this association, and other biomarkers that correlate better with HBV VL.

Alzheimer´s disease (AD) is characterized by the brain deposition of senile plaques composed by amyloid-β peptides (Aβ) that increase inflammation. An endogenous peptide derived from the insulin-like growth factor (IGF)-I, glycine-proline-glutamate (GPE) has IGF-I-sensitizing and neuroprotective actions. Here, we examined the effects of GPE on Aβ levels and hippocampal inflammation generated by the intracerebroventricular infusion of Aβ25-35 during 2 weeks (300 pmol/day) in ovariectomized rats and the signaling-related pathways and levels of Aβ-degrading enzymes associated with these GPE-related effects. GPE prevented the Aβ-induced increase in the phosphorylation of p38 mitogen-activated protein kinase and the reduction in activation of signal transducer and activator of transcription 3, insulin receptor substrate-1 and Akt, as well as on interleukin (IL)-2 and IL-13 levels in the hippocampus. The functionality of somatostatin, measured as the percentage of inhibition of adenylate cyclase activity and the levels of insulin-degrading enzyme were also preserved by GPE co-treatment. These findings indicate that GPE co-administration may protect from Aβ insult by changing hippocampal cytokine content and somatostatin functionality through regulation of leptin- and IGF-I-signaling pathways that could influence the reduction in Aβ levels through modulation of levels and/or activity of Aβ proteases.

Chronic kidney disease (CKD) and cardiovascular disease (CVD) are highly prevalent conditions, each significantly contributing to the global burden of morbidity and mortality. CVD and CKD share a great number of common risk factor, such as hypertension, diabetes, obesity, and smoking among others. Their relationship extends beyond these factors, encompassing intricate interplay between the two systems. Within this complex network of pathophysiological processes, vitamin D has emerged as a potential linchpin, exerting influence over diverse physiological pathways implicated in both CKD and CVD. In recent years, scientific exploration has unveiled a close connection between these two prevalent conditions and vitamin D, a crucial hormone traditionally recognized for its role in bone health. This article aims to provide an extensive review of vitamin D's multifaceted and expanding actions concerning its involvement in CKD and CVD.

This study discusses the application of deep learning technology in network intrusion detection systems (IDS) and focuses on a new model named CNN-Focal. First, through the review of traditional IDS technology, it analyzes its limitations in dealing with complex network traffic. Then, the design principle of the CNN-Focal model is described in detail, which uses threshold convolution and SoftMax multi-class classification technology to effectively improve abnormal traffic detection's accuracy and efficiency. The experimental results show that CNN-Focal performs well on the open data set, demonstrating the potential and advantages of its application in the natural network environment and providing a new perspective and method for further research of deep learning in the field of network security in the future.

The proliferation of Internet of Things (IoT) devices on Linux platforms has heightened concerns regarding vulnerability to malware attacks. This paper introduces a novel approach to investigating the behavior of Linux IoT malware by examining syscalls and library syscall wrappers extracted through static analysis of binaries, as opposed to the conventional method of using dynamic analysis for syscall extraction. We rank and categorize Linux system calls based on their security significance, focusing on understanding malware intent without execution.Feature analysis of the assigned syscall categories and risk ranking is conducted with statistical tests to validate their effectiveness and reliability in differentiating between malware and benign binaries. Our findings demonstrate that potential threats can be reliably identified with an F1 score of 96.86%, solely by analyzing syscalls and library syscall wrappers. This method can augment traditional static analysis, providing an effective preemptive measure to enhance Linux malware analysis. This research highlights the importance of static analysis in strengthening IoT systems against emerging malware threats.

The rise in IoT (Internet of Things) devices poses a significant security challenge. Maintaining privacy and ensuring anonymity within the system is a sought-after feature with inevitable trade-offs, such as scalability and increased complexity, making it incredibly challenging to handle. To tackle this, we introduce our proposed work for managing IoT devices using Hyperledger fabric. We integrated our system on the blockchain with a closed-circuit television (CCTV) security camera fixed at a rental property. The CCTV security camera redirects its feed whenever a new renter walks in. We have introduced the web token for authentication from the renter to the owner. Our contributions include the proposition of efficient framework architecture, a novel chain code algorithm, and stealth addresses with modified ring signatures. We performed different analyses to show the system's throughput and latency through stress testing. We have shown the advantages of the proposed architectures by comparing similar existing schemes. Our proposed scheme enhances the security of blockchain-enabled IoT devices and mitigates the single point of failure issue. Our future work includes scaling it up to cater to the needs of the healthcare system.

This study investigated how different gamification elements in mobile apps influence users' basic psychological needs (autonomy, competence, relatedness) and subsequent engagement outcomes. Survey data was analyzed using PLS-SEM. Social gamification elements enhanced autonomy and competence needs, while immersive elements boosted autonomy and relatedness. Achievement/progression components increased competence and relatedness perceptions. Interestingly, personal traits did not significantly impact psychological needs. Crucially, satisfying autonomy and relatedness predicted higher user satisfaction and continued usage intentions, highlighting their importance for sustained engagement. Competence influenced satisfaction but not continuance intention. The findings demonstrate the motivational roles of distinct gamification features in fostering need-supportive experiences. Designers should incorporate varied social, immersive, and achievement components to address users' psychological requirements holistically. Prioritizing autonomy and relatedness support appears vital for achieving enjoyable, self-motivated, and persistent user engagement across gamified systems and domains. The study provides actionable insights for optimizing motivational affordances through psychologically-informed gamification implementations.

Abstract. Introduction: BMD study gives partial information on bone health in patients with TSH suppression therapy due to Differentiated Thyroid Cancer (DTC). TBS, a new parameter of bone microarchitecture is propose for bone quality study. This study analyze their long-term use in patients with DTC. Methods: BMD was measured by DXA and TBS with iNsigth software in 145 postmenopausal DTC patients. Vertebral Fractures (VFs) with a semi-quantitative x-ray method. Results: BMD at the end study was not different from initial. TBS decreased from 1.35±0.1 to 1.27±0.1 (p=0.002). PTH, Osteocalcin, and BAP were increased, suggesting increased bone remodeling. There was an increase in osteoporosis and osteopenia (40.6% and 16.5% to 46.6% and 18.6%); 31% had partially degraded and 15.1% degraded TBS changed to 48,9% and 24,8% at the end study. VFs in 30 patients, was not different in age, BMI, calcium and alcohol ingestion, smoking, radioiodine, or thyroid parameters vs. without VFs. Odds ratio for VFs increased with osteopenia (OR 2.63). Combination of TBS plus TBS did not improve discrimination. Conclusions: TBS was lowered while BMD did not differ. Percentage of osteoporosis and osteopenia and of partially degraded and degraded TBS was higher at the end study. Predominant discordance rate was found in partially degraded microarchitecture, in which the proportion of osteopenia was higher than normal or osteoporotic patients. AUC of TBS plus BMD did not improve discrimination. TBS, radioactive iodine, and sedentary lifestyle were the main differential data for patients with DTC and VFs.

The shikimate pathway is crucial for the biosynthesis of aromatic amino acids in plants and represents a promising target for developing new herbicides. This work aimed to identify inhibitors of shikimate dehydrogenase (SDH), a key enzyme of the shikimate pathway that catalyzes the conversion of 3-dehydroshikimate to shikimate. Virtual screening and molecular docking were performed on the SDH active site of Arabidopsis thaliana (AtSDH), and 6-nitroquinazoline-2,4-diol (NQD) was identified as a potential inhibitor. In vitro assays showed that NQD decreased the activity of AtSDH by reducing Vmax while keeping KM unchanged, indicating noncompetitive inhibition. In vivo, hydroponic experiments revealed that NQD reduced the root length of soybean and maize. Additionally, NQD increased the total protein content and certain amino acids. Soybean roots uptake NQD more efficiently than maize roots. Furthermore, NQD reduced shikimate accumulation in glyphosate-treated soybean roots, suggesting its potential to restrict the flow of metabolites along the shikimate pathway in soybean. Simultaneous treatment of maize seedlings with glyphosate and NQD accumulated gallic acid in the roots, indicating that NQD inhibits SDH in vivo. Overall, the data indicate that NQD inhibits SDH both in vitro and in vivo, providing valuable insights into the potential development of herbicides targeting SDH.

This study presents PlanteSaine, a novel mobile application powered by Artificial Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina Faso. Agriculture in Burkina Faso, like many developing nations, faces substantial challenges from plant pests and diseases, posing threats to both food security and economic stability. PlanteSaine addresses these challenges by offering a comprehensive solution that provides farmers with real-time identification of pests and diseases. Farmers capture images of affected plants with their smartphones, and PlanteSaine's AI system analyzes these images to provide accurate diagnoses. The application's offline functionality ensures accessibility even in remote areas with limited internet connectivity, while its messaging feature facilitates communication with agricultural authorities for guidance and support. Additionally, PlanteSaine includes an emergency alert mechanism to notify farmers about pest and disease outbreaks, enhancing their preparedness to deal with these threats. An AI-driven framework, featuring an image feature extraction phase with EfficientNetB3 and an artificial neural network (ANN) classifier, was developed and integrated into PlanteSaine. The evaluation of PlanteSaine demonstrates its superior performance compared to baseline models, showcasing its effectiveness in accurately detecting diseases and pests across maize, tomato, and onion crops. Overall, this study highlights the potential of PlanteSaine to revolutionize agricultural technology in Burkina Faso and beyond. Leveraging AI and mobile computing, PlanteSaine provides farmers with accessible and reliable pest and disease management tools, ultimately contributing to sustainable farming practices and enhancing food security. The success of PlanteSaine underscores the importance of interdisciplinary approaches in addressing pressing challenges in global agriculture

Introduction: Type 1 diabetes mellitus is a chronic disease of autoimmune etiology that is highly prevalent in childhood. In the last decade, the possibility of using the Bacillus Calmette-Guérin vaccine for the treatment of this disease has been studied thanks to its immunomodulatory action . Objectives: The objective of this work is to carry out a systematic review of the available scientific evidence on the relationship between the tuberculosis vaccine and the treatment of diabetes in childhood. Secondarily, the aim is to study the incidence of Type 1 Diabetes Mellitus in a cohort of children from the Basque Country according to whether or not they have received the vaccine. Methods: An exhaustive bibliographic search has been carried out on the evidence available to date. For the epidemiological study in Euskadi, a comparison of accumulated incidences between vaccinated and unvaccinated population groups was made. Results: According to the literature analyzed, There is more and more evidence about the possible use of the tuberculosis vaccine in Type 1 Diabetes Mellitus. The results of our study were not conclusive, but we believe that it is necessary to continue with long-term studies to eliminate biases. Conclusions: The Bacillus Calmette-Guérin vaccine could be used for the treatment of autoimmune, allergic, infectious or oncological processes, although more studies are still necessary in this regard.

It is known that knockdown of the mitochondrial 18 kDa translocator protein (TSPO) as well as TSPO ligands modulate various functions, including functions related to cancer. To study the ability of TSPO to regulate gene expression regarding such functions, we applied microarray analysis of gene expression to U118MG glioblastoma cells. Within 15 minutes, the classical TSPO ligand PK 11195 induced changes in expression of immediate early genes and transcription factors. These changes also included gene products that are part of the canonical pathway serving to modulate general gene expression. These changes are in accord with reverse transcriptase (RT) real-time -PCR. At the time points of 15, 30, 45, and 60 minutes, as well as 3 and 24 hours of PK 11195 exposure, the functions associated with the changes in gene expression in these glioblastoma cells covered well known TSPO functions. These functions included cell viability, proliferation, differentiation, adhesion, migration, tumorigenesis, and angiogenesis. This was corroborated microscopically for cell migration, cell accumulation, adhesion, and neuronal differentiation. Changes in gene expression at 24 hours of PK 11195 exposure were related to downregulation of tumorigenesis and upregulation of programmed cell death. In the vehicle treated as well as PK 11195 exposed cell cultures, our triple labeling showed intense TSPO labeling in the mitochondria but no TSPO signal in the cell nuclei. Thus, mitochondrial TSPO appears to be part of the mitochondria-to-nucleus signaling pathway for modulation of nuclear gene expression. The novel TSPO ligand 2-Cl-MGV-1 appeared to be very specific regarding modulation of gene expression of immediate early genes and transcription factors.

Background: Systemic autoimmune rheumatic diseases (SARDs), including Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA), are characterized by chronic inflammation and autoimmunity. Identifying reliable biomarkers is crucial for enhancing diagnosis, monitoring disease progression, and evaluating therapeutic responses. This study explores the potential of serum Syndecan-1 (SDC-1) as a biomarker for these conditions and concurrently examines its relationship with free light chain (FLC) expression levels in the same patients. Methods: A retrospective analysis was performed on serum samples from 120 patients (60 RA, 60 SLE), alongside 50 healthy donors (HD). Serum levels of κ and λ FLCs were determined by turbidimetric assay, while SDC-1 levels were measured using ELISA. Statistical analyses, including the Kruskal-Wallis test, Wilcoxon-Mann-Whitney U test, multivariable linear regression and Spearman’s correlation, were employed to compare biomarker levels across groups and to explore correlations among them. Results: Significantly increased levels of SDC-1, κ-FLC, and λ-FLC were observed in patients diagnosed with RA and SLE compared to HD (p < 0.001), while no significant differences in the κ/λ ratio were noted among the groups (p = 0.4). A statistically significant difference in subject age was also identified. However, multivariate regression analysis indicated that RA and SLE statuses are significantly associated with the levels of these markers, with minimal confounding by age. A significant correlation was observed separately in all groups between the FLC markers. Conversely, no correlation was detected between SDC-1 and FLCs, nor between these markers and age. Conclusion: Elevated serum levels of FLCs and SDC-1 in RA and SLE patients compared to healthy controls underscore their potential as biomarkers for SARDs. The findings also suggest sustained plasma cells activation, supporting the SDC-1 role in the pathogenesis of these conditions.

Artificial Intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use ChatGPT holds a prom-inent position using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for gen-erating human-like responses to queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT in-tegration, with pilot studies and trials revealing each field's potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex data sets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs.

The digital revolution has significantly impacted many Chinese Time-Honored businesses, particularly those slow to adapt to environmental changes, resulting in challenges related to long-term marketing capabilities and declining performance. This study explores the relationship between ambidextrous marketing capabilities and corporate performance. Utilizing a survey involving 91.8% of middle and upper-level managers across 47 Chinese time-honored firms, we construct a research model that demonstrates how the application of ambidextrous marketing capabilities can foster the development of Sustainable marketing capability, which in turn positively influence corporate performance. Sustainable marketing capability mediate the effect of ambidextrous marketing capabilities on corporate performance. Additionally, enhancements in market conditions or legislation may further amplify the impact of Sustainable marketing capability on business performance. In the context of Chinese time-honored firms, these findings offer managerial insights into building Sustainable marketing capability, enhancing performance, and achieving competitive advantages.

Two methods for Pd nanoparticle synthesis were explored with three different carbide-derived carbon (CDC) support materials of which one was nitrogen-doped. These materials were studied for oxygen reduction reaction (ORR) in 0.1 M KOH solution. The prepared CDC/Pd catalysts were characterized using TEM, XRD and XPS. Using these methods, we can observe the influence of support materials for one-pot synthesis methods as we use the standard citrate method and polyol method with polyvinylpyrrolidone (PVP) as a capping agent. Comparing the two methods N-doping of carbon material resulted in smaller nanoparticles only in the case of citrate synthesis, suggesting that the influence of support is weaker using polyol method. Citrate method on CDC1, which was predominantly microporous led to a higher degree of agglomeration and larger particle formation in comparison to CDC2 and CDC3 supports, which possessed higher degree of mesoporosity. Smaller Pd particle sizes were achieved using citrate and NaBH4 in comparison to the ethylene glycol-PVP method. CDC2 and CDC3 did not show significant difference suggesting that the N-doping did not have much of an influence on the ORR. Highest SA value was observed on CDC1/Pd_Cit, which could be attributed to formation of larger particles and agglomerates.

Rasagiline (Azilect®) is a selective monoamine oxidase B (MAO-B) inhibitor that provides symp-tomatic benefit in Parkinson’s disease (PD) treatment and found to exert preclinical neuroprotec-tive effects. Here, we investigated the neuroprotective signaling pathways of rasagiline in the PC12 neuronal cultures exposed to an ischemic-like insult. Exposure of neurons to oxy-gen-glucose deprivation for 4 h followed by 18 h of reoxygenation caused 40% aponecrotic cell death. Rasagiline induced dose-dependent neuroprotection by decreasing cell death and produc-tion of the neurotoxic reactive oxygen species, and reducing the nuclear translocation of glycer-aldehyde-3-phosphate dehydrogenase (GAPDH). Rasagiline increased protein kinase B (Akt) phosphorylation and decreased protein expression of the ischemia-induced α-synuclein protein, in correlation to the neuroprotective effect. Treatment with rasagiline induced nuclear shuttling of transcription factor Nrf2 and increased the mRNA levels of the antioxidant enzymes heme oxy-genase-1, (NAD (P) H- quinone dehydrogenase, and catalase. These results indicate that rasagiline provides neuroprotection in the ischemic neuronal cultures with inhibition of α-synuclein and GAPDH-mediated aponecrotic cell death, and via mitochondrial protection, as by increasing mi-tochondria-specific antioxidant enzymes by a mechanism involving the Akt/Nrf2 redox-signaling pathway. These findings may be exploited for neuroprotective drug development in PD and stroke therapy.

Dreams and positive symptoms of schizophrenia are similar in many aspects, such as bizarre-ness, impairment of reality testing, intense emotional participation. Hallucinations, delusions, and disorganized thoughts have been proposed to be an intrusion of the dreaming state in wake-fulness: conversely, psychotic patients’ abnormal cognitive and behavioral features could over-flow into sleep, transferring peculiar features to their dreams which would differ, in quantity and quality, from those of healthy people. Here we assess this latter hypothesis by analyzing the dreams of 46 patients, hosted in a residential facility or in a day-treatment center, affected by disorders of the schizophrenic spectrum with psychotic symptoms, versus those of 28 healthy controls, in terms of several quantitative and qualitative characteristics. In patients, we also in-vestigated whether dream variables correlated with the severity of symptoms assessed via the Brief Psychiatric Rating Scale. Overall, patients reported fewer and shorter dreams than controls, with a reduction of many ele-ments like characters and settings. The greatest differences regarded emotions, which were less frequent in patients and inversely correlated with symptoms’ severity. This evidence supports the hypothesis that dreams are crucial for emotion regulation during wakefulness and that this func-tion could be totally or partially ineffective in psychoses.

Snow crab replaced groundfish fisheries as the primary focus of the Newfoundland and Labrador (NL) fishing industry in the mid-1990s. Over the past three decades, management philosophies in this male-only fishery have shifted from promoting industry expansion to promoting industry rationalization to implementing Precautionary Approach (PA) management. Until the mid-2010s, there were regionalized management strategies characterized by higher exploitation rates in northern than southern sub-stock units along the NL marine shelves. However, in the late 2010s, exploitation rates were permitted to elevate to high levels across the entire stock range in association with a large resource decline and evidence of biological harm through fishing emerged in chronically depleted areas. In 2019, when stock and fishery productivity were near historic lows, a multi-indicator PA system was informally introduced into management of the resource. This event coincided with anticipated improvements in stock and fishery performance. This paper examines the extent to which the multi-indicator PA management system, focused on promotion of both biological protection and maximization of fishing efficiency, may have contributed to recent improvements in stock and fishery status. A suite of indicators from areas implementing PA guidance into management in 2019 prior to formal adoption of the PA system in 2023 suggest the system has been highly beneficial in promoting rapid recovery, improving stock and fishery performance metrics to levels matching or exceeding historic levels under similar conditions. We discuss capacity of the system to better safeguard biological aspects of resource and fisheries productivity moving forward under a scenario of an expectant resource decline.

This study focuses on examining the determinants of capital structure and the influence of taxes within Iran Khodro Company in the automobile industry from 2016 to 2023. The research analyzes the relationship between debt, taxes, and various company-specific factors. Findings indicate a direct relationship between taxes and debt, with financial leverage being the most significant element related to taxes. The study aims to provide valuable insights for managers and decision-makers in enhancing financial decision-making and shareholder wealth. Various studies have also been conducted on the impact of taxes and different factors on the capital structure of companies listed on the Tehran Stock Exchange, highlighting the importance of tax implications in financial decisions.

The Katerini-Kolindros aquifer system (KKas) is a critical freshwater resource, essential for the local and regional economy. To understand contamination sources, groundwater flow paths, and assess the aquifer's health, an extensive dataset of 751 samples from 113 wells collected between 2010 and 2020 was analyzed using multivariate statistical analysis (MVSA) and hydrogeochemical diagrams. The prevailing water types identified were Ca-HCO₃ and Mg-HCO₃, with mixed water types resulting from various factors affecting groundwater quality. The chemistry of groundwater in the KKas is shown to be affected by ion exchange processes and to a lesser extent by reverse ion exchange processes. No indications of sea-water intrusion have been identified in the water wells monitored. On the other hand, nitrate contamination has been detected in specific water wells spatially associated with urban-type land uses and activities. It is considered that nitrate contamination originates primarily from septic tanks and urban sewage networks or secondarily from fertilization of football pitches, cemeteries or urban waste management practices.

In February 2004, the Food and Drug Administration (FDA) was the first to approve the combination of cisplatin (CDDP) and pemetrexed (PEM) as standard first-line chemotherapy for untreated, unresectable malignant pleural mesothelioma (MPM). However, after that approval, no progress was made in the standard first-line treatment of MPM for almost 15 years. Positive results from a phase 3 study (Mesothelioma Avastin Cisplatin Pemetrexed Study: MAPS) verifying the effect of bevacizumab, an anti-angiogenesis agent added to CDDP/PEM for unresectable MPM, were published in The Lancet in December 2015; however, this did not lead to approval by national drug regulatory agencies. Furthermore, no second-line treatment was established for cases refractory to CDDP/PEM. In August 2018, the Pharmaceuticals and Medical Devices Agency of Japan was the first in the world to approve monotherapy with nivolumab, an immune checkpoint inhibitor (ICI), for previously unresectable, advanced, or recurrent MPM. Following Japan, in October 2020, the FDA approved the combination of nivolumab and ipilimumab for the treatment of previously untreated, unresectable MPM. In this article, we review the transition of drug treatment for MPM, in light of the historical background, focusing on the benefits of ICIs.

This article aims to carry out experiments on water absorption by husked red rice, at constant temperatures of 28, 40 and 50 °C. The description of the absorption kinetics, as well as the analyses of water distribution and volumetric expansion of each grain, at a given instant, was done using a diffusion model. In order for the model to be as close as possible to the real physical situation, the mesh necessary to numerically solve the diffusion equation was generated from the photograph of a grain. Thus, the diffusion equation was written in Boundary-Fitted Coordinates (BFC). The solution of the diffusion equation written in generalized coordinates was then discretized in space and time, using the Finite Volume method, with a fully implicit formulation, considering variable volume and also variable mass diffusivity as a function of local moisture content. Optimizations based on Levenberg-Marquardt algorithm make it possible to determine the parameters of an exponential function relating mass diffusivity and the local moisture content for each temperature. Statistical indicators (chi-square, determination coefficient and Student’s t-test) allowed concluding that the model proposed was very satisfactory for all temperatures, making it possible to simulate water absorption, water distribution and volumetric expansion of the grain over time.

The comparison of three types of ionosonde data from Europe during an Interplanetary Coronal Mass Ejection (ICME) and a Stream Interaction Regions (SIRs) / Corotating Interaction Regions (CIRs) -driven geomagnetic storm event is detailed in this study. The selected events are 16-20 March 2015 for the ICME-driven and 30 May to 04 June 2013 for the SIR/CIR-driven one. Ionospheric data from three European ionosonde stations, namely Pruhonice (PQ), Sopron (SO) and Rome (RO), are investigated. The ionospheric F2-layer responses to these geomagnetic events are analyzed with the ionospheric foF2 and h’F2 parameter, the calculated deltafoF2 and deltahF2 values, ratio of Total Electron Content (rTEC) and Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) satellite Global Ultraviolet Imager (GUVI) thermospheric [O]/[N2] measurement data. The storm-time and the quiet day mean values are also compared, and it can be concluded that the quiet day curves are similar at all stations while the storm-time ones showed the latitudinal dependence during the development of the storm. As a result of the electron density comparison, during the two events it can be concluded that SSC that characterized the ICME induced a Travelling Atmospheric Disturbance (TAD) seen in the European stations, while this is not in the SIR/CIR-driven ionospheric storm, which showed a stronger and more prolonged negative effect in all stations probably due to the season.

The precise regulation of hinge moment and pitch angle driven by the pitch regulated mechanism is crucial for modulating thrust requirements and ensuring stable attitude control in Martian coaxial rotorcraft. Nonetheless, the aerodynamic hinge moment in rotorcraft presents time-dependent dynamic properties, posing significant challenges for accurate measurement and assessment for such characteristics. In this study, we delve into the detailed aerodynamic hinge moment characteristics associated with the pitch regulated mechanism of Mars rotorcraft under a spectrum of control strategies. A robust computational fluid dynamics model has been developed to simulate rotor’s aerodynamic loads, accompanied by a quantitative hinge moment characterization that takes into account the effects of varying rotor speeds and pitch angles. Our investigation has yielded a thorough understanding of the interplay between aerodynamic load behavior and rotor surface pressure distributions, leading to the creation of an empirical mapping model for hinge moments. To validate our findings, we engineered a specialized test apparatus capable of measuring the hinge moments of the pitch regulated mechanism, facilitating empirical assessments under replicated atmospheric conditions of both Earth and Mars. The result indicates aerodynamic hinge moments depend non-linearly on rotational speed, peaking at a 0° pitch angle and showing minimal sensitivity to pitch under 0°. Above 0°, hinge moments decrease, reaching a minimum at 15° before rising again. Simulation and experimental comparisons demonstrate that under Earth conditions, the aerodynamic performance and hinge moment errors are within 8.54% and 24.90%, respectively. For Mars conditions, errors remain below 11.62%, proving the CFD model’s reliability. This supports its application in the design and optimization of Mars rotorcraft systems, enhancing their flight control through accurate prediction of aerodynamic hinge moments across various pitch angles and speeds.

Solanesol is a noncyclic terpene alcohol composed of nine isoprene units and it mainly accumulates in solanaceous plants, especially tobacco (Nicotiana tabacum L.). Here, RNA-seq analyses of tobacco leaves, stems, and roots were used to identify solanesol biosynthesis genes. Six 1-deoxy-d-xylulose 5-phosphate synthase, two 1-deoxy-d-xylulose 5-phosphate reductoisomerase, two 2-C-methyl-d-erythritol 4-phosphate cytidylyltransferase, four 4-diphosphocytidyl-2-C-methyl-d-erythritol kinase, two 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase, four 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, two 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase, six isopentenyl diphosphate isomerase, and two solanesyl diphosphate synthase (SPS) genes were identified to be involved in solanesol biosynthesis. Furthermore, the two N. tabacum SPS (NtSPS1 and NtSPS2), which had two conserved aspartate-rich DDxxD domains, were highly homologous with SPS enzymes from other solanaceous plant species. In addition, the solanesol contents of three organs, and leaves from four growing stages, corresponded with the distribution of chlorophyll. Our findings provide a comprehensive evaluation of the correlation between the expression of different biosynthetic genes and the accumulation of solanesol in tobacco.

Rectal cancer presents a significant burden globally, often requiring multimodal therapy for locally advanced cases. Long-course chemoradiotherapy (LCRT) and short-course radiotherapy (SCRT) followed by surgery have been conventional neoadjuvant approaches. Recent trials favor LCRT due to improved local control. However, tumor distant recurrence remains a concern, prompting exploration of Total Neoadjuvant Therapy (TNT) as a comprehensive treatment strat-egy. Immune checkpoint inhibitors (ICIs) show promise, particularly in mismatch repair-deficient (dMMR) or microsatellite instability-high (MSI-H) tumors, potentially revolutionizing neoadjuvant regimens. Non-operative management (NOM) represents a viable alternative post-neoadjuvant therapy for selected patients achieving clinical complete response (cCR). Additionally, monitoring minimal residual disease (MRD) using circulating tumor DNA (ctDNA) emerges as a non-invasive method for treatment response assessment. This review synthesizes current evidence on TNT, ICIs, NOM and ctDNA, elucidating their implications for rectal cancer management and highlighting avenues for future research and clinical application.

The effects of exogenous inorganic [i.e., nitrate (NO3-)/ammonium (NH4+)] and organic [i.e., glutamate (Glu)/argine (Arg)] N alone and in combination on the accumulation of proline (Pro) in rice plant under trivalent chromium [Cr(III)] stress were studied through the mass balance matrix model (MBMM). ‘NH4+’ application showed the largest contribution to the Pro content in rice shoots under different concentrations of Cr(III), followed by ‘NO3-’, ‘Arg’, and ‘Glu’ application respectively. While, ‘Arg’ application displayed the largest contribution to the Pro content in roots under Cr(III) stress, followed by ‘NH4+’, ‘Glu’, and ‘NO3-’ application. Among the combination cases of N sources used, the application of ‘NH4++Arg’ showed the greatest contribution to the Pro content in both roots and shoots of Cr(III)-treated rice seedlings, while the application of ‘NO3-+Glu’ showed the least contribution to the Pro content in rice seedlings under Cr(III) stress. Results from this study indicated that the level of indigenous Pro in rice seedlings is quite sensitive to Cr(III) stress under different N sources, and mathematical modeling showed a reliable result to estimate the relationship between Pro content and N source application in rice plants in response to Cr(III) exposure .

Hearing loss (HL) is a major clinical, population and public health leading to serious disorders and often early mortality. However, there is a significant paucity in high quality data. Saudi Arabia has a genetically uniform and young population; however factors and estimates on prevalence of HL remains unknown. Background/Objectives: we aimed to determine the frequency, factors, and patterns of HL in different regions. Methods: this study was a descriptive cross-sectional design using a web-based online public questionnaire sent out simultaneously to different regions of Saudi Arabia; namely Eastern, Western, Northen, and Southern as self-administered non-probability sample of social media users mainly WhatsApp, Twitter, and others. Results: Among 789 responses, 6.6 % reported HL, 62.4% were from the Eastern province of which 41.2% were employed and 31.7% were students. Many (36.5%) reported HL &gt; 5-years while 21.2% had programmed and fitted with hearing aids or cochlear implants implying negligence. 19.2% reported diabetes and 51.9% had family history. Ages (11– 50 years) were examined with a slight female predominance (females 59.1%, males 41%). Age was significantly associated with HL (P &lt;0.001) irrespective of gender (males 6.8%, females 6.4%, P value =0.838) reaching peaks at 17.2% in age groups 51-60 years and 25% in 71-80 indicating a risk for HL (OR = 1.43, 95% CI: 0.78-2.81, p = 0.032). Genetic diseases reported as leading cause in 34.6% (OR = 2.23, 95% CI: 1.34-3.58, p = 0.432) followed by noise (26.9%), while other factors including infections, stroke, and fevers made 19.2%. Work involving air or sea travels reported (7.7%) with no significant association (P = 0.628) while history of head injury or trauma (11.5%), or relocation between low- and high-altitudes showed 21.2%. However, frequent noise pollution (OR = 1.54, 95% CI: 0.83-3.01, p = 0.048), regular use of medications (OR = 2.15, 95% CI: 1.03-3.32, p = 0.017), and history of inflammatory disorders (OR = 0.72, 95% CI: 0.32-1.87, p = 0.229) were also associated with higher odds of HL. Conclusion: thus, these findings have significant clinical implications in early diagnosis and management of HL in genetic disorders, diabetes, geriatrics, as well as awareness on family history and occupational health and safety. The study was limited in size and use of online questionnaires. Future large cohort multicenter study would gain more insights.

Commercial protein supplements are the main sources for the sports nutrition. Nowadays, those protein supplements mainly differ in the ingredients and formulations, possibly affecting the digestion behavior and protein absorption during gastrointestinal digestion. Herein, this work aimed to investigate the gastric digestion behavior and protein hydrolysis of commercial protein supplements by using an in vitro dynamic digestion model. Five commercial protein supplements were selected, including three protein powders and two liquid protein beverages. The results indicated that liquid protein beverages had smaller particle size than protein powder dispersions, and one of the protein powders existed as the microcapsules. During gastric digestion, all samples tended to form aggregates as the pH decreased, and the degree of aggregation was more pronounced in liquid protein beverages than in protein powders, where the intact structure of the microcapsules was gradually disrupted. Protein hydrolysis degree in liquid protein beverages was higher than that in protein powders. One of the liquid products (M20) had the highest protein hydrolysis degree of around 35.74% after 120 min gastric digestion and a half-empty time of 37.82 min. These findings suggest that the formulation and ingredients of commercial protein supplements will affect their digestion behavior, resulting in varying degree of protein hydrolysis. Hence, sports supplements should be carefully designed to provide precise nutrition for the athletes and exercisers.