Worldwide, different strategies are elaborated in order to ensure optimum conditions for the development and growth of the economic competitiveness, but also for increasing the quality of life and environment protection. All these strategies are closely linked with the development and modernization of the systems for producing energy from clean and renewable sources. In this context, the present paper presents the results of the researches regarding the evaluation of the sustainability of the briquettes production, using the biomass resulted from vine winter pruning as raw material. An analysis of the scientific references indicates that nearly 8 Mt of biomass result from over 7.4 million hectares of vine plantations existent worldwide, biomass that could be valorized through densification in order to produce solid biofuels with a lower calorific value of more than 17 MJ·kg-1. When designing the scientific endeavor, the following aspects were considered: defining the aim and objectives of the research; design of the research algorithm; collection, preparation and conditioning of the biomass; chemical analysis of the briquettes; evaluation of the technological characteristics of the briquettes; evaluation of the energy consumption and energy efficiency for producing the briquettes, taking into account two drying methods (natural and artificial drying). In the meantime, some specific laboratory equipment was design and built for the artificial drying of biomass, evaluation of the mechanical durability, measurement of the energy consumption etc. The analysis of the experimental data has led to the conclusion that the agricultural waste from vine pruning can constitute an important and sustainable source of energy in the form of bri-quettes, which fulfill most of the requirements imposed by the international standards.

As previous study in many countries shown that stroke patient onsets are not distributed randomly, but associate with meteorological factors. However, the relationship between stroke occurence and meteorological factors remain unknown in mountain area in Guizhou China. This paper firstly introduces multi-source fusion data which is integrated by the mountain meteorological factor, geographic mapping elevation information data and stroke population monitoring of Guizhou province. Mainly elaborates from a few aspects, which concludes data collection, data sorting, data extraction, data cleaning and data production in detail. A completed and detailed meteorological stroke data set was successfully established and multi-source data fusion was realized by the use of Gbase and unified data service interface of Guizhou meteorological big data cloud platform. And we report the impact of meteorological variables in Guizhou mountain area climate on stroke. In this study, we performed a statistical fusion data between January 2017 and December 2020 about stroke incidence rate and meteorological factors respectively, for instance, concerning the mean (Mean), maximum (Max), minimum (Min), median (Median), standard deviation (Std) . We calculated stroke rates (date stroke occurence)/(year stroke occurence) and we investigated the distribution of days included in the label. Results: the distribution of the incidence rate basically conforms to the normal distribution with the label Max 0.007399, label Min 0.000204, label Mean 0.002738, label Median 0.002643, label Std 0.00076. We observed a positive significant correlation of stroke incidence rate directly proportional to the daily temperature difference (between 0 and 20 degrees Celsius), as the value of this factor exhibits variation larger, the incidence rate is gradually increasing. And we investigated from the Pearson correlation coefficients that stroke incidence increasing when meteorological factors at low humidity (less than 40% (RH 80%), temperature higher than 31℃); the 24-hour daily temperature difference varies between 6 and 10℃ (6

The rural population in the Dry Zone of Sri Lanka is largely affected by Chronic Kidney Disease of Unknown etiology (CKDu). According to the multidisciplinary research carried out so far, quality of groundwater was considered one of the possible causative factors for CKDu. Therefore, the assessment of water quality variations and evolution mechanism of water quality parameters of drinking water sources is important for identifying any relationships between CKDu and the drinking water quality. The current study aimed to perform a detailed hydrogeochemical investigation using isotopic and chemical methods on selected groundwater sources in the CKDu-endemic, non-endemic and control areas. TDS, hardness, Mg2+, Na+ and F- are the main parameters that cause water quality deterioration but, their derived mechanism in these three regions are completely different. The excess concentrations of F- and Mg2+ in the CKDu endemic area, low F- and high Mg2+in the CKDu non-endemic sedimentary formation, and either combinations of low F- and low Mg2+, high F- and low Mg2+ or low F- with high Mg2+ in the control area are the distinct features. The primary processes that regulate the evolution of groundwater types in CKDu endemic and control area is the weathering of silicates. Similarly, in the CKDu endemic area, carbonate dissolution and reverse ion exchange are prominent. Cation exchange and evaporite dissolution are more pronounced in the control area. Shallow groundwaters are evapo-concentrated hence it further deteriorates quality when compared to the deep groundwater with non-mixed, non-evaporated, and higher elevation recharge effect (from 100 m altitude) in the CKDu endemic area. Dilution decreases the ion content in the CKDu endemic area while evaporite dissolution further increase it in the control area after the rainy season. Evaporation, and seawater mixing affected the quality of groundwater in the non-endemic sedimentary formation. A statistically significant difference of F- ionic ratio with Na+, Mg2+, Ca2+ in the endemic and control areas. Intense rock weathering combined with the desorption added excess F- to the groundwater in the CKDu endemic area while the cation exchange and fluorite dissolution is contributing factor in CKDu control area. All the groundwater samples analyzed have exceeded the moderate hardness threshold. However, prominent Mg hardness proportion together with excess F- in the CKDu endemic area may produce nephrotoxic MgF2 complexes that may trigger renal damage. In contrast, produced NaF complexes in the CKDu control area leads to reduction of F- toxicity in the human body. Therefore, increased levels of magnesium, fluoride and TDS in the shallow groundwater, along with geochemical, hydrogeological and climatic factors, may contribute to the CKDu in the Dry Zone of Sri Lanka.

Lipid droplet (LD) accumulation in hepatocytes is one of the major symptoms associated with fatty liver disease. Mitochondria play a key role in catabolizing fatty acids for energy production through β-oxidation. The interplay between mitochondria and LD assumes a crucial role in lipid metabolism, while it is obscure how mitochondrial morphology affects systemic lipid metabolism in the liver. We previously reported that cilnidipine, an already existing anti-hypertensive drug, has potency to prevent pathological mitochondrial fission by inhibiting protein-protein interaction between dynamin-related protein 1 (Drp1) and filamin, an actin-binding protein. Here, we found that cilnidipine and its new dihydropyridine (DHP) derivative, 1,4-DHP, which lacks Ca2+ channel blocking action of cilnidipine, prevent the palmitic ac-id-induced Drp1-filamin interaction, LD accumulation and cytotoxicity of human hepatic HepG2 cells. Cilnidipine and 1,4-DHP also suppressed the LD accumulation accompanied by reducing mitochondrial contact with LD in obese model and high fat diet-fed mouse livers. These results propose that targeting Drp1-filimin interaction becomes a new strategy for the prevention or treatment of fatty liver disease.

Graph databases (GDBs) are becoming increasingly popular across scientific disciplines, being highly suitable to store and connect complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph (KG) databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available GDB technologies. Relevant publications are then categorised according to their domain and application. We detail different approaches and highlight advantages of outstanding resources, such as UniProtKB, Disease Ontology, and Reactome, which provide graph-based solutions. We discuss ongoing efforts of the systems biology community to standardise and harmonise KG creation and the maintenance of integrated resources. Outlining prospects, including the use of GDBs as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of GDBs will be key for knowledge generation in systems biology and other research fields with heterogeneous data.

Purpose: Inflammation and neutrophils play a central role in both Covid-19 disease and cancer. We aimed to assess the impact of pre-existing tumor-related inflammation on Covid-19 outcomes in patients with cancer and to elucidate the role of circulating neutrophil subpopulations. Methods: We conducted a multicenter retrospective analysis of 524 patients with cancer and SARS-CoV-2 infection, assessing the relationship between clinical outcomes and circulating inflammatory biomarkers collected before and during Covid-19 infection. Additionally, a unicenter prospective cohort provided data for an exploratory analysis, assessing the immunophenotype of circulating neutrophils and inflammatory cytokines. The primary endpoints were 30-day mortality and severity of Covid-19 disease. Results: Prior to Covid-19, 25% of patients with cancer exhibited elevated dNLR, which increase to 55% at the time of Covid-19 diagnosis. We developed the FLARE score, incorporating both tumor and infection-induced inflammation, which categorized patients into four prognostic groups. The poor prognostic group had a 30-day mortality rate of 68%, significantly higher than the 23% in the favorable group (p<0.0001). The score proved to be an independent predictor of early mortality. The prospective analysis revealed a shift towards immature forms of neutrophils and higher IL-6 levels in patients with cancer and severe Covid-19 infection. Conclusions: A pre-existing tumor-induced pro-inflammatory state significantly impacts Covid-19 outcomes in patients with cancer. The FLARE score serves as an easy-to-use and worldwide accessible effective tool to predict outcomes in this population, while circulating neutrophil subpopulations might provide additional information and could help refine outcome prediction.

The External Occipital Protuberance (EOP) is a notable anatomical landmark connected to neck musculature. With the rise of tech neck syndrome due to prolonged smartphone use, concerns have emerged regarding its influence on EOP morphology. This study compares EEOP characteristics in contemporary individuals (aged 18-30 years) from Abruzzo with ancient skulls from the Opi necropolis (VII-Vth century BC) Methods: Four null hypotheses were tested concerning EEOP prevalence and severity: (1) no gender differences, (2) no differences between modern and ancient populations, (3) no gender-based variations in severity, and (4) no temporal differences in severity. Statistical analyses were conducted to assess the significance of these hypotheses. Results: The study found a higher prevalence of EEOP in modern individuals compared to ancient populations, with no significant gender differences in prevalence. However, severity of EEOP showed significant variation by gender and historical period, with modern individuals exhibiting greater severity. Conclusions: The observed increase in EEOP prevalence and severity in modern populations suggests a potential influence of tech neck posture associated with increased screen time. These findings underscore the need for further research into the effects of contemporary lifestyle factors on cranial morphology.

Thioethers are critical in the fields of pharmaceuticals and organic synthesis, but most of the methods for synthesizing alkyl thioethers employ foul-smelling thiols as starting materials or generate them as by-products. Additionally, most thiols are air-sensitive and are easily oxidized to produce disulfides under atmospheric conditions; thus, a novel method for synthesizing thioethers is necessary. This paper reports a simple, effective, green method for synthesizing dialkyl or alkyl aryl thioether derivatives using odorless, stable, low-cost ROCS2K as a thiol surrogate. This transformation offers a broad substrate scope and good functional group tolerance with excellent selectivity. The reaction likely proceeds via xanthate intermediates, which can be readily generated via the nucleophilic substitution of alkyl halides or aryl halides with ROCS2K under transition-metal-free and base-free conditions.

Keywords: Urban Heritage, Resilience, Urban Planning, Climate change, Urban Development, Sustainable Urban Development

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.

Background: The advantage of a robotic assisted (RARP) over a laparoscopic (LRP) approach in radical prostatectomy (RP) remains to be demonstrated. Aim of the study is to use a homogeneous population in real life and single surgeon surgery, to analyze the oncological and functional results based on the type of the surgical approach. Methods: This is a prospective trial on non-metastatic prostate cancers (PC) patients considered after multidisciplinary decision to RP, using RARP or LRP. A real-life setting was analyzed at our Urological Departments, using homogeneous criteria for the management of PC cases and a one surgeon experience on 444 cases (284 LRP and 160 RARP) .Results: Mean operative time was significantly lower in RARP (173.33±44.3 min) than in LRP (153.21±25.1 min) (p<0.001). In cases submitted to an extended lymph node dissection (eLND), the mean number of lymph nodes removed was 15.16±7.83 and 19.83±4.78 respectively in LRP and RARP procedures (p<0.001), but positive lymph nodes (pN1) were similarly found in 15.8% of LRP patients and 13.6% of RARP patients (p=0.430). Surgical margins (SM) positivity was not significantly higher in RARP group (20.0%) when compared to LRP group (15.9%) (p=0.145). During the postoperative follow-up, a biochemical recurrence (BCR) was detected in 14.4% and 7.5% of cases in the LRP and RARP group respectively (p=0.014). Better results of PAD test at 3-month interval using RARP approach (mean pad weight 75.57±122 grams and 14±42 grams respectively in LRP and RARP (p<0.01)) were described. Conclusions: In the comparison between RARP and LRP approach, a clear advantage of the robotic approach is a significant reduction in operating times, days of hospitalization and postoperative catheterization compared to laparoscopic surgery. It is not possible to describe any certain oncological advantage both in terms of surgical margins and pathological lymph nodes removed. In RARP cases a reduction to the limit of significance is described in terms of biochemical recurrence. RARP produces a more rapid recovery of urinary continence at 3 months postoperatively without significant advantages in terms of erective potency recovery.

Abstract: Background: MAb114, REGN-EB3, Remdesivir, and ZMapp, which are monoclonal antibody-based treatments, have been compared and shown to be promising therapies against the Ebola Virus Disease (EVD). There has been no comparison between these med-ications and standard treatment (without antiviral). Our study aimed to examine the con-tribution of each regimen compared to standard treatment on the survival of EVD patients and assess whether this association was modified by EVD vaccination (rVSV-ZEBOV Ebola vaccine) status. Methodology: We performed a secondary analysis of data obtained from four EVD treatment centers located in Katwa, Mangina, Butembo, and Beni in the North Kivu region. The main outcome measure was mortality within a 28-day period. A Cox model was used to identify predictors of survival in hospitalized EVD patients. Results: Vaccinated EVD patients were 1.7 times less likely to die compared to unvac-cinated patients (3.70 days vs. 5.00 days; p=0.0002). Delaying care and treatment at EVD treatment centres increased mortality risk by 5% for each day following symptom onset. Compared to the standard treatment group, adjusted mortality rates were significantly re-duced in the groups receiving MAb114 (0.29, p

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.

Ultrasound (US) scans of the inferior vena cava (IVC) provide useful information on the volume status of a patient. However, their investigation is user-dependent and prone to measurement errors. An important technical problem is the objective difficulty in studying a very compliant blood vessel like IVC, which makes large respirophasic movements and shows a complicated three dimensional geometry. Using bi-dimensional (2D) B-mode views either in long or short axis has improved the characterization of IVC dynamics compared to a measurement along a single direction (M-mode). However, specific movements of the IVC can challenge also the information provided by these 2D sections. Thus, these two orthogonal views, provided by an US system in X-plane, are here integrated by an innovative method. It is tested on simulated videos of the IVC performing complicated movements, that are compensated by the new method, overcoming the biased measurements provided by 2D scans. The method is then applied on example experimental data.

Cutaneous Squamous Cell Carcinoma (cSCC) is an increasingly common malignancy of the skin and the leading cause of death from skin cancer in adults over the age of 85. Fibroblast Growth Factor Receptor 2 (FGFR2) has been identified as an important effector of signaling pathways that lead to the growth and development of cSCC. In recent years, there have been numerous studies evaluating the role FGFR2 plays in multiple cancers, its contribution to resistance to anti-cancer therapy, and new drugs that may be used to inhibit FGFR2. This review will provide an overview of our current understanding of FGFR2 and potential mechanisms in which we can target FGFR2 in cSCC. The goals of this review are the following: 1) to highlight our current knowledge on the role of FGFR2 in healthy skin and contrast this with its role in the development of cancer; 2) to further explain the specific molecular mechanisms that FGFR2 uses to promote tumorigenesis; 3) to describe how FGFR2 contributes to more invasive disease, 4) to describe its immunosuppressive effects in skin, and 5) to evaluate its effect on current anticancer therapy and discuss therapies on the horizon to target FGFR2 related malignancy.

This study explores the potential of piloting desalination plants in a systematic way to evaluate energy improvements in water desalination processes. Pilot tests with the latest generation of reverse osmosis membranes in large desalination plants are becoming increasingly common, as small-scale experiments are carried out on the operation of new generation membranes with better salt rejection and lower energy consumption. This approach aims to achieve optimal water quality standard at the lowest possible cost. In this way, pilot tests are being carried out before the decision is made whether to change the reverse osmosis membranes, as this represents a significant investment. By carrying out these tests, we hope to minimize the risk of making a mistake to ensure the best results in terms of energy consumption, operating costs and reducing the environmental impact while complying with the required water quality. In this case, the Pareto analysis is used to identify the two or three most significant causes whose treatment affects more than 80% of the possible energy improvement to be implemented. This article introduces a novel approach to studying a total of 180 desalination plants at the territorial level in the Canary Islands. The global scarcity of freshwater resources has greatly contributed to the development of desalination technologies, in which reverse osmosis is one of the most widely used and highly regarded methods.

Diffuse midline gliomas are among the deadliest human cancers and have had little progress in treatment in the last 50 years. Cell cultures of these tumors have been developed recently, but it is unknown the degree to which such cultures retain the characteristics of the source tumors. DNA methylation profiling offers a powerful tool to look at genome-wide epigenetic changes that are biologically meaningful and can help assess the similarity of cultured tumor cells to their in vivo progenitors. Paraffinized diagnostic tissue from three diffuse intrinsic pontine gliomas with H3 K27M mutations was compared with subsequent passages of neurosphere cell cultures from those tumors. Each cell line was passaged 3-4 times and analyzed with DNA methylation arrays and standard algorithms that provided comparison of diagnostic classification and cluster analysis. All samples tested maintained high classifier scores and clustered within the reference group of H3 K27M-mutant diffuse midline gliomas. There was a gain of 1q in all cell lines, with two cell lines initially manifesting the gain of 1q only during culture. In vitro cell cultures of H3 K27M-mutant gliomas maintain high degrees of similarity in DNA methylation profiles to their source tumor, confirming their fidelity even with some chromosomal changes.

Antimicrobial Peptides (AMPs), as immune effectors synthesized by a variety of organisms, not only constitute a robust defense mechanism against a broad spectrum of pathogens in the host, but also show promising applications as effective antimicrobial agents. Notably, insects are significant reservoirs of natural AMPs. However, the complex array of variations in types, quantities, antimicrobial activities, production pathways of AMPs, and evolution of AMPs across insect species presents a significant challenge for immunity system understanding and AMP applications. This review covers insect AMP discoveries, classification, common properties, and mechanisms of action. Additionally, we summarize the types, quantities, and activities of im-mune-related AMPs in each model insect. We also conducted the first comprehensive investigation into the diversity, distribution, and evolution of 20 types of AMPs in model insects, employing phylogenetic analysis to describe their evolutionary relationships and shed light on conserved and distinctive AMP families. Furthermore, we summarize the regulatory pathways of AMP production through classical signaling pathways and additional pathways associated with Nitric Oxide, insulin-like signaling, and hormones. This review advances our understanding of AMP as guardians in insect immunity system and also unlocks a gateway to insect AMP resources, facilitating the use of AMPs to address food safety concerns.

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.

In the context of Covid-19 virus containment, there is a lack of acceptance of preventive measures in the population. The present work investigated which factors influence the belief in of scientific propositions compared belief in conspiracy theories. The focus here was on the determinants of conspiracy beliefs in the context of Covid-19 related media content. Using an online questionnaire (N = 175), results indicate that scientific compared to conspiracy theoretical media content led to higher acceptance. Furthermore, Need for Cognition (NFC-K), a conspiracy theoretical worldview (CMQ), and openness to experience (NEO-FFI) were positively associated with conspiracy beliefs derived from Facebook postings. In addition, a conspiracy theoretical worldview was negatively associated with belief in scientific media content. Furthermore, agreeableness was unrelated to conspiracy beliefs, although it was positively associated with conspiracy theoretical worldview. The results imply promising persuasion strategies for reducing conspiracy theoretical beliefs and to increase the acceptance of preventive measures.

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

To realize high response and selectivity gas sensor in detecting dissolved gases in transformer oil, in this study, the adsorption of four kinds of gases (H2, CO, C2H2 and CH4) on Pd-graphyne as well as the gas sensing properties evaluation were investigated. The energetically favorable structure of Pd doped γ-Graphyne was first studied, including the comparison of different adsorption sites and discussion of electronic properties. Then, the adsorption of these four molecules on Pd-graphyne was explored. The adsorption structure, adsorption energy, electron transfer and electron distribution, the band structure and density of states were calculated and analyzed. The results show that the Pd atom prefers to be adsorbed on the middle of three C≡C bonds and the band gap is smaller. The CO adsorption exhibits the largest adsorption energy and electron transfer and brings obvious change to the structure and electron properties to Pd-graphyne. Because of the conductance decrease after adsorption CO and acceptable recovery time at high temperature, the Pd-graphyne can be promising gas sensing materials to detect CO with high selectivity. This work offers theoretical support for the design of nanomaterials based gas sensor using novel structure for industrial application.

We propose a new theory beyond the standard model of elementary-particle physics. Employing the concept of a quantized spacetime, our theory demonstrates that the zero-point energy of the vacuum alone is sufficient to create all the fields, including gravity, the static electromagnetic field, and the weak and strong interactions. No serious undetermined parameters are assumed. Furthermore, the relations between the forces at the quantum-mechanics level is made clear. Using these relations, we quantize Einstein’s gravitational equation: Beginning with the zero-point energy of the vacuum, and after quantizing Newtonian gravity equation, we combine the energies of a static electromagnetic field and gravity in a quantum spacetime. Applying these results to the Einstein gravity equation, we substitute the energy density derived from the zero-point energy in addition to redefining differentials in a quantized spacetime. This is how we derive the quantized Einstein gravitational equation without assuming the existence of macroscopic masses. For the weak interaction, by considering plane-wave electron and the zero-point energy, we obtain a wavefunction that represents a β collapse. In this process, from a different point of view than Weinberg-Salam theory, we derive the masses of the W and Z bosons and the neutrino, and we calculate the radius and lifetime of the neutron. For the strong interaction, we previously reported an analytical theory for calculating the mass of a proton by providing a specific linear attractive potential obtained from the zero-point energy, which agrees well with the measurements. In the present study, we further calculate the strong interaction between two nucleons, i.e., the mass of the pi-meson. The resulting calculated quantities agree with the measurements, which verifies our proposed theory.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

Obesity is one of the most prevalent and damaging metabolic conditions and is a risk factor for the development of other disorders that define the metabolic syndrome. Recent studies have identified a significant role of AGE accumulation and RAGE signaling pathways in the underlying mechanisms that cause the chronic inflammatory response present in obesity which, ultimately, leads to adipose tissue dysfunction. Given the current interest and increasing evidence on possible therapeutic opportunities in the AGE-RAGE axis, the purpose of this work is to review the key findings on new small molecules and bioactive compounds that act as AGE or RAGE inhibitors and their effects on metabolic parameters of people with obesity. The search queries were defined according to the following PICO question: “What are the effects of AGE-RAGE antagonism on adipose tissue metabolism and other metabolic parameters of people with obesity? “. Article search was performed in three online databases: PubMed, Scopus, and Web of Science. In the end, 20 studies were selected for this review. Overall, the reviewed molecules showed beneficial effects on body weight, glucose tolerance, insulin resistance, inflammatory profile, and adipose tissue metabolism in mice models with obesity. There are still very few studies on human application of these molecules, but the ones that were reviewed revealed controversial data when compared to animal studies. Therefore, further human clinical trials should be performed to retrieve more conclusive data.

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.

The objective was to evaluate the effect of 3-nitrooxypropanol (3-NOP) in combination with dif-ferent feed additives on growth performance, carcass traits, meat quality, enteric methane (CH4) emissions, nutrient intake and digestibility, and blood parameters in feedlot beef cattle. In ex-periment (Exp.) 1, one hundred sixty-eight Nellore bulls (initial bodyweight (BW) 410 ± 8 kg) were allocated to 24 pens in a completely randomized block design. In Exp. 2, thirty Nellore bulls (Initial BW 410 ± 3 kg) were allocated to a collective pen in a completely randomized design. Three treatments were applied: Control (CTL): Sodium monensin (26 mg/kg of dry matter, DM), M3NOP: CTL with 3-NOP (100 mg/kg DM) and Combo: 3-NOP (100 mg/kg DM) with essential oils (100 mg/kg DM), 25-Hydroxy-Vit-D3 (0.10 mg/kg DM), organic chromium (4 mg/kg DM), and zinc (60 mg/kg DM). In Exp 1, bulls in Combo had greater (P

We present a study of the radio variability of bright, $S_{1.4}\geq100$ mJy, high-redshift quasars at $z\geq3$ on timescales up to 30--40 years. The study involved simultaneous RATAN-600 measurements at frequencies of 2.3, 4.7, 8.2, 11.2, and 22.3 GHz in 2017--2020. In addition, data from the literature were used. We have found that the variability index $V_S$ of the quasars ranges from 0.02 to 0.96, with about half of the objects in the sample showing a variability index in the range of 0.25--0.50, which is comparable to that of the blazars at lower redshifts. The distribution of $V_S$ at 22.3 GHz is significantly different from that at 2.3--11.2 GHz, which may be attributed to the fact that a compact AGN core dominates at the source's rest frame frequencies greater than 45 GHz, leading to higher variability indices obtained at 22.3 GHz (the $V_S$ distribution peaks around 0.4) compared to the lower frequencies (the $V_S$ distribution peaks around 0.1--0.2). Several source groups with distinctive variability characteristics were found using cluster analysis of quasars. We propose 7 new candidates for gigahertz peaked-spectrum (GPS) sources and 5 new megahertz peaked-spectrum (MPS) sources based on their spectrum shape and variability features. Only 6 out of 23 sources previously reported as GPS demonstrate a low variability level typical of classical GPS sources ($V_{S} < 0.25$) at 4.7--22.3~GHz. When excluding the highly variable peaked-spectrum blazars, we expect no more than 20\% of the sources in the sample to be GPS candidates and no more than 10\% to be MPS candidates.

Patient symptoms play a critical role in disease progression and diagnosis, yet they are most often captured in unstructured clinical notes. This study explores use of large language models (LLMs) for extracting patient symptoms from clinical notes, comparing their performance against rule-based information extraction (IE) systems, like BioMedICUS. By fine-tuning an LLM on diverse corpora from multiple healthcare institutions, we aimed to improve symptom extraction accuracy and efficiency with symptoms related to acute and post-acute sequelae of SARS-CoV-2. We also conducted prevalence analysis to highlight significant differences in symptom prevalence across corpora and performed fairness analysis to assess the model's equity across race and gender. Our findings indicate that while LLMs can match the effectiveness of rule-based IE methods, they face significant challenges related to demographic bias and generalizability due to variability in training corpora. This evaluation revealed overfitting and insufficient generalization, especially when models were trained predominantly on limited datasets with single annotator bias. This study also revealed that LLMs offer substantial advantages in efficiency, adaptability, and scalability for biomedical IE, marking a transformative shift in clinical data extraction processes. These results provide real-world evidence of the necessity for diverse, high-quality training datasets and robust annotation processes to enhance LLM’s performance and reliability in clinical applications.

Polyetheretherketone is a promising material for implants due to its good mechanical properties and excellent biocompatibility. Its accessibility to a wide range of applications is facilitated by the ability to process it with an easy-to-use manufacturing process such as Fused Filament Fabrication. The elimination of disadvantages associated with the manufacturing process, such as a poor surface quality, is a main challenge to deal with. As part of the mass finishing process, centrifugal disc finishing has demonstrated good results in surface optimization, making it a promising candidate for post-processing of additively manufactured parts. The objective of this study is to identify the key parameters of the centrifugal disc finishing process on the waviness of additively manufactured PEEK specimen, which has not been investigated yet. Waviness of the specimen was investigated by means of confocal laser scanning microscopy (CLSM), while weight loss was additionally tracked. Six parameters were investigated: type, amount and speed of media, use of compound, amount of water and time. Type of media, time and speed were found to significantly influence waviness reduction and weight loss. Surface electron microscopy images demonstrated the additional effects of deburring and corner rounding. Results on previous studies with specimens made of metal showed similar results. Further investigation is required to optimise waviness reduction and polish parts in a second post-processing step.

The inclusion of exogenous phytase in broiler P and Ca deficient diets in response to heightened concerns over excessive P excretion into the environment over the years has remarkably been documented. However, responses among these studies have been inconsistent because of the several factors affecting P utilization. For this reason, a systematic review with meta-analysis of results from forty-one studies published from 2000 to February 2024 was evaluated to: 1) quantitatively summarize the size of phytase effect on growth performance, bone strength, and mineralization in broilers fed P and Ca deficient basal diets and 2) estimate and explore the heterogeneity of the effect sizes of outcomes using sub-group and meta-regression analyses. The quality of the included studies was assessed using the Cochrane Collaboration’s SYRCLE Risk of Bias checklists for animal studies. Additionally, applying the random-effects models, Hedges’ g effect size of supplementation with phytase was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (P_SMD ≤ 0.05, I² > 50%, n ≥ 10). The meta-analysis showed that supplemental phytase increases ADFI and BWG and reduces FCR at each time point of growth (< 0.0001). Additionally, phytase supplementation consistently increased tibia ash, P and Ca, and bone strength (< 0.0001) of broilers fed P and Ca deficient diets. Results of the subgroup and meta-regression analyses showed that age and strain of broiler, dietary P source, and duration of phytase exposure significantly influence the effect size of phytase on growth and bone parameters. In conclusion, phytase can attenuate the effect of reducing dietary available phosphorus and calcium and improve ADFI, BWG, and reduced FCR, especially when added to starter diets. It further enhances bone ash, bone mineralization, and bone-breaking strength of broilers, even though the effects of bone ash and strength can be maximized in the starter phase of growth. However, the effect sizes of phytase were related to the age and strain of the broiler, dietary P source, and duration of phytase exposure rather than the dosage.

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.

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.

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

Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America, and to enhance the utility of drought monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impacts information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and the colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and the warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and indicators are changing over time as the climate warms, and by recommending ways to strengthen the use of indices and indicators in drought decision-making.

Baijiu is popular with its long history and balanced flavor, and flavor type was the most widely used classification mode for Baijiu. However, the evolution relationship of Baijiu flavor types and the differential markers between flavor types are still unclear, which has greatly affected the development of Baijiu industry. In this study, a total of 319 trace components were identified by gas chromatography-olfactometry-mass spectrometry and gas chromatography-mass spectrometry. Among them, 91 trace components with high odor active values or taste active values were recognized as flavor components. Then random forests were conducted to screen differential markers between derived and basic flavor types, and principal component analysis was carried out to evaluate their effectiveness in distinguishing the flavor types of Baijiu. Finally, 19 differential markers were screened and proved to effectively reveal the evolution Baijiu flavor types, and were further verified as key differential markers by addition test and correlation analysis.

The surprisingly high catalytic activity of gold has been known to the heterogeneous catalysis community since the mid-1980s. Significant effort has been directed towards improving the reactivity of these surfaces towards important industrial reactions. One such strategy is the introduction of small amounts of other metals to create Au-based surface alloys. In this work, we investigate the synergistic effect of Pt doping of the Au(111) surface towards decreasing the activation barrier of the methanol dehydrogenation elementary step, within first-principles density functional theory. To this aim we construct several models of \ce{Pt}-doped Au(111) surfaces, including a full \ce{Pt} overlayer and monolayer. The effect of \ce{Pt} surface doping is then investigated via the computation of adsorption energies of the various chemical species involved in the catalytic step, and the estimation of activation barriers of methanol dehydrogenation. Both electronic and strain effects induced by \ce{Pt} surface doping concur in substantially lowering the activation energy barrier of this important reaction elementary step. Morever, in the presence of preadsorbed atomic oxygen, \ce{Pt} surface doping can be used to reduce the activation energy for methanol dehydrogenation to as low as 0.1 eV.

Cross-lingual sentiment analysis is crucial for understanding and interpreting emotions expressed in text across diverse linguistic contexts. However, cross-lingual sentiment analysis faces challenges such as differences in emotional lexicons, data imbalance, and the need for multi-language sentiment normalization. In this study, we propose a novel approach to address these challenges by leveraging low-resource language training techniques to enhance cross-lingual sentiment analysis. Our method aims to bridge the gap in emotional lexicons by adapting sentiment analysis models to diverse linguistic contexts. Additionally, we tackle issues of data imbalance through innovative data augmentation strategies tailored to each language, and we introduce a multi-language sentiment normalization technique to ensure consistent sentiment interpretation across different languages. Our method achieved state-of-the-art results in twelve languages across four domains, demonstrating superior performance in both text-level and sentence-level sentiment analysis tasks. By conducting comprehensive evaluations across diverse linguistic contexts and domains, we showcase the versatility and effectiveness of our approach in achieving top-tier results in cross-lingual sentiment analysis.

As it turns out, both isotope scaling and density limits are phenomena closely linked to fluid closure. The necessity to include ion viscosity arises for both phenomena. Thus, we have added ion viscosity to our model. The experimental isotope scaling has been successfully recovered in our fluid model through parameter scans. Although ion viscosity typically exerts a small effect, the density limit is manifested by increasing the density by approximately tenfold from the typical experimental density. In our case, this increase originates from the density in the Cyclone base case. Notably, these phenomena would not manifest with a gyro-Landau fluid closure. The isotope scaling is nullified by the addition of a gyro-Landau term, while the density limit results from permitting ion viscosity to become comparable to the gyro-Landau term. The mechanism of zonal flows, demonstrated analytically for the Dimits upshift, yields insights into the isotope scaling observed in experiments. In our approach, ion viscosity is introduced in place of the Landau fluid resonances found in some fluid models. This implies that the mechanism of isotope scaling operates at the level of fluid closure in connection with the generation of zonal flows. The strength of zonal flows in our model has been verified, particularly in connection with the successful simulation of the nonlinear Dimits shift. Consequently, a role is played by our approach in the temperature perturbation part of the Reynolds stress.

In order to achieve the dual carbon goal and simplify the decarbonization process, a CO2 recovery process of the fire-flooding exhaust was designed. The process adopted the two-stage membrane separation method to recover CO2 and obtain high purity CO2 rich flow, and then through the mixed refrigerant liquefaction and rectification column, food grade liquid CO2 was obtained. HYSYS process simulation shows that for the fire-flooding exhaust with a flow rate of 1000 kg/h and a given composition, the process can achieve a CO2 recovery of 69.02%, total product sales S=2086.8 yuan/h, and specific power consumption of 2.818 kW∙h/kg. On this basis, a hybrid simulation platform of HYSYS & Matlab was established. Taking the specific power consumption of the product as the objective function, sequential quadratic programming (SQP) algorithm was adopted to optimize the process, and the optimized specific power consumption was reduced by 18.8%. Finally, by adjusting N2/CO2 components, the adaptability of the optimization condition was analyzed.

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.

Background/Objectives: Bovine babesiosis is a vector-borne disease transmitted by ticks that causes important losses in livestock worldwide. Recent research performed on the drugs currently used to control bovine babesiosis reported several issues including drug resistance, toxicity impact, and residues in edible tissue, suggesting the need for developing novel effective therapies. The endochin-like quinolones ELQ-316 and buparvaquone (BPQ) act as cytochrome bc1 inhibitors and have been proven to be safe and efficacious against related apicomplexans, such as Plasmodium spp. and Babesia microti, without showing toxicity in mammals. The objectives of this study are investigating whether ELQ-316, BPQ and their combination treatment could be effective against Babesia bovis in an in vitro culture model, and comparing with imidocarb (ID), the routinely used drug. Methods: In vitro cultured parasites at starting 2% percentage of parasitemia (PPE) were treated with BPQ, ELQ-316, ID, and the combinations of BPQ+ ELQ-316 and ID+ ELQ-316 at drug concentrations that ranged from 25 to 1200 nM, during four consecutive days. Parasitemia levels were evaluated daily using microscopic examination. Data was compared using the independent Student's t-test and ANOVA test. Results: All drugs tested, whether used alone or in combination, significantly decreased the survival (p<0.05) of B. bovis in in vitro cultures. The combination of BPQ+ ELQ-316 had the lowest calculated inhibitory concentration 50 (IC50) 31.21 nM (IC95%: 15.06 - 68.48) values, followed by BPQ, 77.06 nM (IC95%: 70.16- 86.01), ID+ELQ316 197 nM (IC95%:129.0 - 311.2), ID 635.1 nM (IC95%: 280.9 – 2119) and ELQ316 654.9 nM (IC95%: 362.3 – 1411). Conclusion: The results reinforce the higher efficacy of BPQ at affecting B. bovis survival, and the potential synergistic effects of its combination with ELQ-316, providing a promising treatment option against B. bovis.

The conservation of the main protease in viral genomes, combined with the absence of a homologous protease in humans, makes this enzyme family an ideal target for developing broad-spectrum antiviral drugs with minimal host toxicity. GC-376, a peptidomimetic 3CL protease inhibitor, has shown significant efficacy against coronaviruses. Recently, a GC-376-based PROTAC was developed to target and induce the proteosome-mediated degradation of the dimeric SARS-CoV-2 3CLPro protein. Extending this approach, the current study investigates the application of the GC-376 PROTAC to the 3CPro protease of Enteroviruses, specifically characterizing its interaction with CVB3 3CPro through X-ray crystallography, NMR and biophysical techniques. The present structural data show that there are some changes between the binding of CVB3 3CPro and SARS-CoV-2 3CLPro, but the overall similarity is strong. The most notable variation is the orientation of the phenylmethyl ester of GC-376 with the S4 subsite of the proteases. This is linked to the flexibility of the protein structure around the region of the catalytic triad shown by our NMR data. Other structural variations include distinct ligand interactions in subsites S1 and S2, influenced by the presence of Glu71 in CVB3 3CPro. Despite these differences, the GC-376 PROTAC fits well within the binding sites of both proteases, demonstrating its potential as a broad-spectrum antiviral agent.

This study evaluated the effect of newly introduced calcium silicate-based temporary intracanal medicament Bio-C Temp and calcium hydroxide-based material UltraCal XS on the release of transforming growth factor β1 (TGF-β1) from root canal dentin. Twenty-two intact and fully developed human premolars from patients aged 15 – 18 were shaped and irrigated according to the current clinical recommendations. The teeth were then gently split in half, and the root canal dentin of paired samples was covered with Bio-C Temp or UltraCal XS. After 3 weeks of incubation, the specimens were conditioned with 17% EDTA and the collected solution was subjected to quantification of released TGF-β1 by performing ELISA. One-way analysis of variance (ANOVA), followed by Tukey’s test, was selected to determine the statistically significant differences between the groups at the 0.95 confidence level. The highest mean value of released TGF-β1 (1993.1 pg/ml) was detected in the control group, where root canal dentin was conditioned with 17% EDTA alone. Regarding experimental groups, Bio-C Temp released a statistically significant higher amount of TGF-β1 (282.14 pg/ml) compared to UltraCal XS (114.28 pg/ml; p = 0.0158). Bio-C Temp affected the release of growth factors from root canal dentin less than UltraCal XS and may therefore serve as an intracanal medicament for regenerative endodontic procedures.

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnajökull and Langjökull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangajökull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

Reference evapotranspiration (ET0) plays an irreplaceable role in regional dry/wet conditions under the background of climate change. Based on the FAO Penman-Monteith method and daily climate variables, ET0 was calculated for 22 stations in and around Songnen Grassland, northeast China, during 1960-2014. The temporal and spatial variations of ET0 and precipitation (P) were comprehensively analyzed at different time scales by using the Mann-Kendall test, Sen’s slope estimator, and linear regression coupling with break trend analysis. Sensitivity analysis was used to detect the key climate parameter attributed to ET0 change. Then, the role of ET0 in regional dry/wet conditions was discussed by analyzing the relationship between ET0, P and aridity index (AI). Results shown a higher ET0 in the southwest and a lower in the northeast, but P was opposite to that of ET0. Evidently decreasing trend of ET0 at different time scales was detected in almost the entire region, and the significant trend mainly distributed in the eastern, northeastern and central. For the whole region, sensitivity analysis indicated decreasing trend of ET0 was primarily attributed to relative humidity and maximum air temperature. The positive contribution of increasing temperature rising to ET0 was offset by the effect of significantly decreasing relative humidity, wind speed and sunshine duration. In addition, the value of ET0 shown higher in drought years and lower in wet years.

Indian tobacco farm laborers are primarily women and children working for very low wages. The aim of this study was to explore occupational and reproductive health challenges faced by women tobacco farm labors in Mysore District, India. We conducted interview and six focus group discussions among 41 women tobacco farm laborers. Codes and themes were generated based on deductive and inductive approaches using the socio-ecological model. Participants reported symptoms of green tobacco sickness including headaches, back pain, gastric problems, weakness, and allergies during menstruation, pre-natal, and post-natal periods. Participants had poor awareness about the health effects of tobacco farming and there were gender inequalities in wages and use of personal protective equipment. Participants received support from family and commu-nity health workers during their pregnancy and post-natal period. Women reported wanting ma-ternity benefits from the tobacco board, monetary support, and nutritional supplements. There is a need for health education about the environmental dangers of tobacco among farm laborers, and more supportive policies for women farmworkers during pregnancy and post-natal periods.

Background/Objectives: Resources to cope for maternity and women’s participation are essential modulators of maternal well-being. Therefore, it is relevant that the psychosocial factors of woman will be monitored during maternity to promote adequately healthcare. This study consisted in the design and the validation of two new tools that identify women's knowledge of obstetric healthcare rights (MatCODE) and perception of resource scarcity (MatER) during pregnancy, labor and early postpartum; Methods: The content validity was carried out using the Aiken's V coefficient and the content validity index (CVI-i) based on 5 experts. In addition, for the face validity of the pilot cohort was considered the INFLESZ scale. Finally, the questionnaires were applied to 185 women, which allowed to assess the construct validation by factorial and Rasch analysis. The divergent validity was also studied with validated psychological questionnaires; Results: MatCODE and MatER questionnaires received CVI-i and Aiken's V&gt;0.80 values, also the INFLESZ demonstrates acceptable semantic understanding. The analysis confirms the unidimensional of the questionnaires with fit values for MatCODE of RMSEA=0.113 [0.105; 0.122] and MatER of RMSEA=0.067 [0.063; 0.072]. The divergent validity showed significative and consistent correlations with the constructs assessed. In MatCODE was =0.95 and =0.94 and in MatER was =0.79 and =0.78; Conclusions: MatCODE and MatER are new useful tools monitoring maternal healthcare, with adequate psychometric characteristics in Spanish context.

In the United States, the Federal Aviation Administration has officially classified flight crew (FC) consisting of commercial pilots, cabin crew or flight attendants as “radiation workers” since 1994 due to the potential for cosmic ionizing radiation (CIR) exposure at cruising altitudes originating from solar activity and galactic sources. Several epidemiological studies have documented elevated incidence and mortality for several cancers in FC, but it has not yet been possible to establish whether this is attributable to CIR. CIR and its constituents are known to cause a myriad of DNA lesions, which can lead to carcinogenesis unless DNA repair mechanisms remove them. But critical knowledge gaps exist with regard to CIR dosimetry, the role of other genotoxic exposures among FC, and possible biological mechanisms underlying higher cancer rates observed in FC exist. This review summarizes our understanding of the role of DNA damage and repair responses relevant to CIR exposure in FC. We aim to stimulate new research directions and provide information that will be useful for guiding regulatory, public health, and medical decision-making to protect and mitigate risks for those who travel by air.

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 purposes of this study are based upon the theory of planned behavior (TPB) to examine the impact of past experiences of contract farming on selecting a specific type of contract farming in the future and then compare different psychological factors in the TPB for different potential contract farmer statuses. These statuses include homesteaders, farmers from cooperative farms, farmers from production and sales teams, professional farmers, and brokers. The impact of factors in the TPB for a particular contract type on potential contract farmers is further to compute. To this end, data are collected in three major sweet potato production areas in Taiwan. The results show that the farmers’ past contract farming experience does not influence the selection of the contract in the future. As for the selection of contract type, strengthening the perception and motivating the behavioral intention of contract farming for cooperative farms will increase the probability of selecting an unclassified sweet potato size contract. On the other hand, enhancing perceived behavioral control factors and behavioral intention factors for professional farmers and brokers is apt to have a relatively high probability of selecting those types involving the highest amount or the best price to obtain the best deal.

This review article explores the innovative application of software sensors for monitoring and controlling biosystems, emphasizing their advantage in managing the complexities of various biological processes. Biosystems—from cellular interactions to ecological dynamics—are characterized by intrinsic nonlinearity, temporal variability, and uncertainty, posing significant challenges for traditional monitoring approaches. A critical challenge highlighted is that what is typically measurable may not align with what needs to be monitored. Software sensors bridge this gap by combining hardware sensor data with advanced computational modelling techniques to indirectly infer hard-to-measure target variables, such as stress level, animal and human health indicators, and chemical soil properties. The article outlines advancements in sensor technologies and their integration into model-based monitoring and control systems, leveraging the capabilities of Internet of Things (IoT) devices, wearables, remote sensing, and smart sensors. It provides an overview of common methodologies for designing software sensors, focusing on the modelling process. The discussion contrasts hypothetico-deductive (mechanistic) models with inductive (data-driven) models, illustrating the trade-offs between model accuracy and interpretability. Specific case studies are presented, showcasing software sensor applications such as the use of Kalman filter in greenhouse control, remote detection of soil organic matter, and sound recognition algorithms for early detection of respiratory infections in animals. Key challenges in designing software sensors, including the complexity of biological systems, inherent temporal and individual variabilities, and the trade-offs between model simplicity and predictive performance, are also discussed. This article positions software sensor as remarkable tool for advancing biosystem management, driving forward the potential for sustainable practices in various sectors such as agriculture, healthcare, and environmental monitoring.

Background: In our recent publications pertaining to 4G model of final unification and based on strong and electroweak interactions, we have proposed the existence of a weak fermion of rest energy 585 GeV. Objective: To confirm the physical existence of the proposed 585 GeV weak fermion by analyzing weak and strong interactions in a unified approach via 4G model of final unification, super symmetry and string theory. Method: Considering the proposed nuclear charge of 2.95e, proton, electron mass ratio, specific charge ratios of proton and electron, Fermi’s weak coupling constant, Reduced Planck’s constant, nucleon magnetic moments, nuclear stability, nuclear binding energy, nuclear mass and neutron lifetime, it is planned to confirm the physical existence of the proposed 585 GeV weak fermion. Results: All proposed logics and formulae clearly establish the physical existence of 585 GeV weak fermion directly and indirectly. Conclusion: Believing in the physical existence of the proposed 585 GeV weak fermion, there is a scope for observing galactic TeV radiation coming by virtue of annihilation of 585 GeV fermions and radiation associated with various astrophysical acceleration mechanisms of 585 GeV fermions. Appeal: As we are beginners of astrophysics domain, we appeal the science community to see the possibility of considering the proposed 585 GeV weak fermion with a charge of $\pm\left(e\right)$ in place of electron and proton.

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.

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.

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.

Polycystic ovary syndrome (PCOS) is a common condition in reproductive-age women. Women with PCOS are at higher risk of pregnancy complications including gestational diabetes (GDM). The prevalence of PCOS and GDM varies according to the diagnostic criteria used. The mechanism for the occurrence of GDM in women with PCOS is still unclear. Materials &amp; Methods- A systematic search of the electronic database was done using keywords like PCOS, and GDM to include studies between April 2008 and March 2023 where uniform diagnostic criteria were used. Studies were excluded with high-risk of bias after the assessment of bias, and meta-analysis was done with relative risks and confidence intervals. Results &amp; Discussion-Out of 1896 search results, 95 were selected for full-text. The quality of the studies was scrutinized and a total of 28 studies were included as they fulfilled the inclusion criteria. The incidence of GDM in women with PCOS was found to be 10.55 % (2.9- 54.9%) from pooled data involving 1,280,245. The prevalence of PCOS in women diagnosed with GDM was found from pooled data of 36,351 women in retrospective studies to be 2.47% (1.5- 50.1%). Selection predominantly included cohort studies, most commonly from China. The meta-analysis reported the risk of GDM is higher in women with PCOS than in those without PCOS (HR: 1.59, 95% CI: 1.27–1.91, p &lt; 0.001). Family history of diabetes, ethnicity, pre-pregnancy BMI, insulin resistance, gestational weight gain, use of assisted reproductive techniques, and multifetal gestation were the risk factors for GDM in women with PCOS. Conclusion- The prevalence of GDM in patients with PCOS is high, but the causality is complex. The newer predictive models are promising in clarifying the causative relationships, yet use various parameters at different cut-offs. There is a need for the development of universally acceptable parameters for the early prediction of GDM in women with PCOS.

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.

Recent clinical trials using synthetic incretin hormones, glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists have demonstrated that these treatments ameliorated many complications related to obesity, emphasizing the significant impact of body weight on overall health. Incretins are enteroendocrine hormones secreted by gut endothelial cells triggered by nutrient ingestion. The phenomenon that oral ingestion of glucose elicited much higher insulin secretion than intra-venous injection of equimolar glucose is known as incretin effect. This also alludes to the thesis that food intake is the root cause of insulin resistance. Amylin is co-expressed with insulin from the pancreas β-cells but does not have insulinotropic function. Amylin suppresses glucagon secretion, slowing gastric emptying, and suppressing the central nervous system (CNS) reward center leading to weight loss. However, amylin can self-aggregate and cause serious cytotoxicity and may cause β-cell apoptosis. Glucagon is secreted by the pancreatic α-cells and participates in glucose homeostasis in glucose-dependent manner. In hypoglycemia, glucagon increases blood glucose level by glycogenolysis and gluconeogenesis and inhibits glycogenesis in the liver. Some triple agonists in combination with glucagon and dual incretins are already being developed. These advances bring to the question “Are the benefits of these anti-obesity treatments sustainable?” Chronic agonism may decrease the number of receptors. Also, long-term stimulation may cause β-cell exhaustion and failure. Additionally, instead of endogenous control of the appetite, exogenous control of satiety and food intake may hinder the long-term sustainability of these treatments. We will discuss the incretins’ mechanism of action, challenges, and future directions.

Background: Narcolepsy is characterized by excessive daytime sleepiness (EDS) and episodes of cataplexy, frequently triggered by psychological stress, significant disturbances in sleep-wake cycles, pregnancy, or trauma. Modafinil is widely used as the preferred treatment due to its effectiveness in alleviating EDS, improving disease outcomes, and enhancing overall quality of life. Nonetheless, long-term safety and efficacy data are still lacking, underscoring the importance of future research to advance treatment options for narcolepsy. Aim: In our systematic review and meta-analysis, we aim to assess the effectiveness of Modafinil in the treatment of Narcolepsy. Methods: We searched in electronic databases (PubMed, Embase, Google Scholar, Scopus, Science Direct, Web of Science) was performed to identify cohort studies and randomized controlled trials (RCTs) up to 8th July 2024. Data extraction focused on baseline characteristics of the included studies and efficacy outcomes, including scores on the Maintenance of Wakefulness Test (MWT) and Epworth Sleepiness Scale (ESS) . We performed the meta-analysis utilizing the Review Manager software, version 5.4. To assess the outcomes, we compared the Modafinil-treated group with the placebo group, employing the mean difference (MD) and a 95% confidence interval (CI) for statistical analysis. Result: In total, 3833 articles were identified for screening, with nine studies included in the systematic review and five in the meta-analysis. These studies involved 997 adult patients with Narcolepsy treated with Modafinil. MWT revealed a significant increase in total scores (MD= 3.56, 95% CI [2.25 to 4.86], p < 0.00001) and ESS revealed a significant decrease in scores (MD= -3.34, 95% CI [-4.13 to -2.56], p < 0.00001). Conclusion: The research emphasizes the potential of Modafinil in alleviating EDS associated with Narcolepsy. While the results are promising, they are based on short term scale studies. It is crucial to undertake larger-scale, extended-duration, placebo-controlled studies that include a broad range of demographic populations. These trials are essential to confirm the efficacy, verify the safety profile, and fine-tune dosing strategies to maximize the long-term therapeutic benefits.

Human Papillomavirus (HPV) related cancers account for a large percentage of cancers. The tumor microenvironment (TME) is a complex structure and contributes significantly to tumor development, progression, and invasion. The TME is particularly pronounced in HPV-related cancers and HPV is known to influence the TME. In cancer research, there is an urgent need for new models to deepen our understanding of the pathophysiology of the disease and to facilitate the development of innovative therapies. In this context, 3D cell culture has emerged as a promising method in cancer research, that offers significant potential compared to conventional approaches. 3D modelling can produce results that are more consistent with clinical outcomes without the ethical concerns and problems of animal models. In this review, our aim is to discuss the tumor microenvironment in HPV-related cancers and demonstrate the importance of advancing 3D cell culture models for this purpose.

This research focuses on optimization of coupled solar production and battery storage system to achieve Nearly Zero-Energy Building (nZEBs) based on building load behavior patterns. Moni-toring data from an office building with 120kW peak and 40kW average load consumption equipped with a 160kW solar photovoltaic (PV) system and a 50kW-45kWh energy storage system (ESS). The primary objective is to the primary objective is to analyze collected data from existing system and setup guideline to optimize ESS capacity to maximize clean energy consumption and thus minimize excess production losses, progressing the building toward Nearly ZEB Level 1 status (87.5%-100% energy usage). The study outcome has identified parameter impacts and demonstrates additional optimized cases with various PV and ESS installed capacity. Further analysis is performed based on working day load profile and appliance patterns. This ap-proach aims to learn the usage HVAC, lighting, and electronics, enabling the optimization scheme to be applied to buildings with different load patterns. Additionally, the analysis predicts other building behavior patterns and optimized clean energy system. The findings are then validated against actual data and the results demonstrate good model accuracy, especially daytime predic-tion. These insights also provide guidelines and strategies for further interventions on HVAC operations and adjusting concerned schedules to achieve desired ZEB level.

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.

Background: Inflammatory Bowel disease (IBD) is one of the worldwide health issues with increasing incidence. Recent data point out that those patients can have a defective immune system, rendering response to vaccinations suboptimal. Since 1990, Hepatitis B Virus (HBV) vaccination has been introduced among the compulsory childhood vaccinations in Oman. Given the questionable immunogenicity of vaccinations in IBD patients, we designed this study to quantify the immune response to scheduled HBV vaccine in IBD patients and compare it with that in a matching control cohort of healthy blood donors at Sultan Qaboos University Hospital (SQUH). Methods: This is a retrospective case-control study that was conducted between the 1st of July 2023 and the 31st of May 2024 at SQUH. Using the hospital information System (HIS), a total of 252 participants were enrolled in our study and divided into two groups. Group (1) included 126 IBD patients and group (2) included 126 healthy controls. Baseline demographics, medical comorbidities and viral serologies before and after vaccination were collected. The primary outcome of the study was to compare the long term immune response to HBV vaccine between the two groups. The secondary outcomes included identifying possible risk factors for suboptimal vaccine response. Results: One hundred and twenty-six participants were included in each group. Durable protective immune response to HBV vaccine was attained in 29 patients (23%) of the IBD group compared to 109 participants (86.5%) of the control group. There was a statistically significant association (p = 0.0156) between prednisolone treatment and low immune response to HBV vaccine. Moreover, esomeprazole usage exhibited a statistically significant association (p < 0.0001) with suboptimal response to HBV vaccine. Meanwhile, there was no statistically significant correlation between low immunogenicity to HBV vaccine and age, sex, type of IBD, comorbidities, and BMI. Conclusions: IBD patients are less immunogenic to HBV vaccination compared to healthy controls. Factors like esomeprazole and/or corticosteroid therapy might be associated with poor immune response. These findings highlight the importance of reassessing the immunogenicity of HBV vaccination and probably other protective vaccinations in all IBD patients as part of their standard of care.

With the development of agriculture, the complexity and dynamism of orchard environments pose challenges to the perception and positioning of inter row environments for agricultural machinery. The paper proposes a method for extracting navigation lines and measuring pedestrian obstacles. The improved YOLOv5 algorithm is used to detect tree trunks between left and right rows in orchards. The experimental results show that the average angle deviation of the extracted navigation lines is less than 5 degrees, verifying its accuracy. Due to the variable posture of pedestrians and ineffective camera depth, a distance measurement algorithm based on four zone depth comparison is proposed for pedestrian obstacle distance measurement. Experimental results show that within a range of 6m, the average relative error of distance measurement does not exceed 1%, and within a range of 9m, the maximum relative error is 2.03%. The average distance measurement time is 30 milliseconds, which can accurately and quickly achieve pedestrian distance measurement in orchard environments. On the publicly available TUM RGB-D dynamic dataset, YOLOD-SLAM2 significantly reduces the RMSE index of absolute trajectory error compared to ORB-SLAM2 algorithm, which is less than 0.05 m/s. In actual orchard environments, YOLOD-SLAM2 has a higher degree of agreement between the estimated trajectory and the true trajectory when the car is traveling in straight and circular directions. The RMSE index of the absolute trajectory error is less than 0.03m/s, and the average tracking time is 47ms, indicating that the YOLOD-SLAM2 algorithm proposed in this paper can meet the accuracy and real-time requirements of agricultural machinery positioning in orchard environments.

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 paper is dedicated to studying the influence of annealing temperature on the chemical, structural and electrophysical properties of low-k films made from porous organosilicate glasses containing terminal methyl groups. The films were deposited using centrifugation, followed by drying at 200 °C and annealing at temperatures ranging from 350 °C to 900 °C. Changes in refractive index, porosity, pore size, chemical composition, and electrical properties as a function of annealing temperature are evaluated. The results of JV measurements indicate that the methyl-modified film, which was annealed at 450 °С, demonstrates minimal leakage currents. This phenomenon can be explained by the almost complete removal of surfactant residues and non-condensed silanols, as well as the minimal thermal degradation of methyl groups. The results of the study on leakage current models in methyl-modified films, obtained at various annealing temperatures, lead us to conclude that the predominant mechanism of charge carrier transfer is Poole–Frenkel emission.

Pregnant women (PW) are at a higher risk of diseases and hospitalization from viral respiratory infections, specially influenza, due to cardiopulmonary and immunological changes. This study assessed the impact of viral respiratory infections on PW hospitalized with severe acute respiratory infection (SARI). It´s a cross-sectional study with 42 PW and 85 non-pregnant women (NPW) admitted with SARI to two tertiary hospital between January 2015 and December 2019. The rate of virus prevalence, SARI hospitalization, length of hospital stay, oxygen supplementation, intensive care unit (ICU) admission, and death were comparable between PW and NPW. Multivariate analysis showed that PW had a higher rate of viral SARI hospitalizations (OR = 2.37; 95% CI =1.02 - 5.48) compared to NPW, with influenza virus being the most prevalent (aOR =7.58; 95% CI =1.53 - 37.66). Length of hospital stay (aOR = 0.83; 95% CI = 0.73 – 0.95) and admission to the ICU (aOR=0.028; 95% CI=0.004 - 0.25) were lower in PW compared to hospitalized NPW. Respiratory viruses had a greater impact on the frequency of SARI in the group of PW. Although PW had a higher rate of influenza SARI, they had a better outcome than NPW due to the treatment they received.

Ciliated microeukaryotes are insufficiently integratively investigated despite their ubiquity and ecological significance. The morphology and ontogenesis of a new Stichotrichida species, Pseudosincirra binaria sp. nov., and the known Perisincirra paucicirrata Foissner et al., 2002, are here studied using live observations and protargol staining methods. The new species is characterized by having one buccal, one parabuccal and three frontal cirri, one frontoventral row extending to the posterior half of the cell, three left and two right marginal rows, three dorsal kineties with the left kinety conspicuously bipartite, along with one caudal cirrus at the rear end of each kinety. During morphogenesis, there exist five frontal-ventral cirral anlagen with anlagen IV and V forming frontoventral row in the proter, and four anlagen with anlage IV generating frontoventral row in the opisthe. The anlagen for marginal rows and dorsal kineties develop intrakinetally. The new population of Perisincirra paucicirrata corresponds well with other isolates regarding morphology and cell development. Phylogenetic analyses based on the small subunit ribosomal gene sequence data revealed that both Perisincirra and Pseudosincirra are deeply clustered in the clade consisting of species from the genera Deviata and Heterodeviata, supporting the placement of both genera into the family Deviatidae Foissner, 2016.

Dispersion of antibiotic in livestock farming represents a health concern worldwide, contributing to the spread of antimicrobial resistant bacteria through animals, the environment, and humans. Phenolic compounds could be alternatives to antibiotics, once drawbacks such as low water solubility, bioavailability, and reduced stability are overcome. Although nano- or microsized formulations could respond to these shortcomings they do not represent cost-effective options. Here, three phenolic compounds, obtained from wood processing manufacturers, were characterized, revealing suitable features such as antioxidant activity, size, and chemical and colloidal stability for in-field applications. The Minimum Inhibitory Concentration (MIC) of these colloidal suspensions was measured against six bacterial strains isolated from livestock. These particles showed different inhibition behaviors: Colloidal chestnut was effective against one of the most threatening antibiotic resistant pathogens such as S. aureus but was ineffective toward E. coli. On the other hand, colloidal pine showed a weak effect on S. aureus but specificity toward E. coli. The present proof-of-concept points at colloidal polyphenols as valuable alternatives for antimicrobial substitutes in the livestock context.

Introduction: Lower respiratory tract infections, including pneumonia, are one of the leading causes of child mortality, especially in low-resource settings. Current guidelines rely on clinical signs for diagnosis, leading to over-prescription of antibiotics, which in turn contribute to antimicrobial resistance. Lung point of care ultrasound (L-POCUS) offers potential to improve diagnostic accuracy and reduce unnecessary antibiotic use, but lacks standardized guidelines for diagnosis and management of paediatric pneumonia. Methods and Analysis: This study utilizes a modified Delphi process to develop expert consensus guidelines for L-POCUS interpretation in paediatric pneumonia that would constitute a framework for effective guidelines for judicious antibiotic prescribing. The 5-stage iterative process includes: i) creation of a literature summary and conceptual framework, ii) first round of online surveys for expert feedback, iii) virtual meetings to discuss survey results and refine guidelines, iv) second round of online surveys, v) final analysis and development of consensus guidelines. A panel of 12-15 experts, chosen for their paediatric POCUS experience, geographic diversity, and gender balance, will participate. Consensus will be defined as ≥75% agreement. Ethics and Dissemination: Participation is voluntary, with consent obtained at the start and the option to withdraw at any time. The protocol was approved by the Ethics Commission of Bern, Switzerland. Findings will be disseminated through open access publication.

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.