Sarcomas are a heterogenous group of tumours that commonly carry poor prognosis with limited therapeutic options. Adolescents and young adults (AYA) with sarcoma are a unique and under-studied patient population that have only achieved modest survival gains compared to other groups. We present our institutional experience of AYA with sarcoma who underwent comprehensive molecular profiling (CMP) using either large-panel targeted DNA sequencing or whole genome and transcriptome sequencing and evaluated the feasibility and clinical impact of this approach. Genomic variants detected were determined to be clinically relevant and actionable following the Molecular Tumour Board evaluation. Clinicians provided feedback regarding the utility of testing three months after reporting. Twenty-five patients who were recruited for CMP are included in this analysis. The median time from consent to final molecular report was 45 days (interquartile range 37-57). Potentially actionable variants were detected for 14 patients (56%) and new treatment recommendations were identified for 12 patients (48%). Pathogenic germline variants were identified in three patients (12%), and one patient had a change of diagnosis. Implementation for CMP for AYA with sarcoma is clinically valuable, feasible and should be increasingly integrated into routine clinical practice as technologies and turnaround times continue to improve.

Cancer-associated cachexia (CAC) is a debilitating condition marked by muscle and fat loss, unresponsive to nutritional support, and contributes significantly to morbidity and mortality in patients with cancer. Immune dysfunction, driven by cytokine imbalance, contributes to CAC progression. This review explores the potential relationship between CAC and anti-cancer immune response in pre-clinical and clinical studies. Pre-clinical studies showcase the involvement of cytokines like IL-1β, IL-6, IL-8, IFN-γ, TNF-α, and TGF-β, in CAC. IL-6 and TNF-α, interacting with muscle and adipose tissues, induce wasting through JAK/STAT and NF-κB pathways. Myeloid-derived suppressor cells (MDSCs) exacerbate CAC by promoting inflammation. Clinical studies confirm elevated pro-inflammatory cytokines (IL-6, IL-8, TNFα) and immune markers like neutrophil-to-lymphocyte ratio (NLR) in patients with CAC. Thus, immunomodulatory mechanisms involved in CAC may impact the anti-neoplastic immune response. Inhibiting CAC mechanisms could enhance anti-cancer therapies, notably immunotherapy. R-ketorolac, a new immunomodulator, reversed weight loss and increased survival in mice. Combining these agents with immunotherapy may benefit patients with cancer experiencing CAC. Further research is vital to understand the complex interplay between tumor-induced immune dysregulation and CAC during immunotherapy.

Synovial sarcomas are rare soft tissue tumors that infrequently occur in the ethmoid sinus, posing diagnostic challenges. Herein, we report a case of a 38-year-old male with a 7-month history of recurrent throbbing headaches, left eye pain, and facial nerve palsy, evolving into multiple stroke episodes. Radiological studies showed extension to the cavernous sinus, raising an initial suspicion of vasculitis. Histological findings of an endoscopic biopsy, however, confirmed a monophasic synovial sarcoma. Consequently, the patient was referred to a specialized center for comprehensive management. This case underscores the rarity of ethmoid sinus synovial sarcomas, their diverse clinical presentations, and the necessity of a multidisciplinary approach for accurate diagnosis and tailored therapeutic strategies.

Background/Objectives: Rehabilitation helps reduce disability in dementia. The Australian National Dementia Action Plan identifies a gap in clear treatment pathways post-diagnosis, affecting the quality of life for those with dementia. This study assessed the impact of a one-day dementia training course and follow-up on GPs' and practice nurses' knowledge, attitudes, and confidence regarding dementia rehabilitation. Methods: The training, led by two experienced GPs and an academic physiotherapist, covered dementia diagnosis, allied health roles, care planning, and referrals. The follow-up involved applying the learnt material and completing a reflective task. Three longitudinal surveys (Dementia Knowledge Assessment Scale - DKAS, General Practitioners’ Attitudes and Confidence towards Dementia Survey - GPACS-D, and Dementia Rehabilitation Scale) and Likert-scale statements were conducted pre-course, post-course, and at 4-month follow-up, alongside a focus group. Descriptive and regression analyses were applied to survey data, and content analysis was used for focus group data. Results: Seventeen participants (14 GPs, 3 nurses) completed the pre-post course survey, with eight (6 GPs, 2 nurses) participating in follow-up and focus group discussions. Post-course, DKAS scores increased by 12.1%, GPACS-D by 10.1%, and the dementia rehabilitation scale by 9.4%. Likert-scale statements improved by 8-79%. At the four-month follow-up, there was a slight, non-significant decline in most measures. Focus groups highlighted the training’s impacts, useful components, barriers, and suggestions for improvement. Conclusion: Training GPs and practice nurses in dementia rehabilitation enhances knowledge, awareness, and confidence. Ongoing efforts are needed to sustain benefits and address referral barriers for better access to dementia rehabilitation services.

The orexin/hypocretin neuropeptide family has emerged as a focal point of neuroscientific research following the discovery that this family plays a crucial role in a variety of physiological and behavioral processes. These neuropeptides serve as powerful neuromodulators, intricately shaping autonomic, endocrine, and behavioral responses across species. Notably, they serve as master regulators of vigilance and stress responses; however, their role in complex processes such as food intake, metabolism, and thermoregulation warrant further investigation. This narrative review provides a journey through the evolution of our understanding of the orexin system, from its initial discovery to the promising progress made in developing orexin derivatives. It goes beyond conventional boundaries, striving to synthesize the multifaceted activities of orexins. Special emphasis is placed on domains such as stress response, fear, anxiety, and learning, in which the authors contributed to the literature with original publications. This article demonstrates the orchestrating role of the orexins in several intricate and integrative physiological processes. It also overviews the advancement of orexin pharmacology, which has already yielded some promising successes, particularly in the treatment of sleep disorders. This interdisciplinary approach to studying neuropeptides unveils their significance as vital connectors between transient functional changes and lasting structural adaptations. Ultimately, it advances our understanding of the intricate physiological and behavioral contributions of the orexin/hypocretin neuropeptide family.

Bacterial infections and resistance to antibiotic drugs represent the highest challenges to public health. The search for new and promising compounds with anti-bacterial activity is a very urgent matter. In order to promote the development of platforms enabling to the discovery of compounds with anti-bacterial activity, Fourier Transformed Mid-Infrared (FT-MIR) spectroscopy associated with the machine learning algorithms were used to predict the impact of compounds extracted from Cynara cardunculus against Escherichia coli cells. According to the plant tissue (seeds, dry and fresh leaves, and flowers) and the solvents (ethanol, methanol, acetone, ethyl acetate, and water), compounds with different compositions concerning, phenol content, antioxidant, and antimicrobial activity were obtained. Principal component analysis of spectra, allowed to discriminate compounds that inhibit the E. coli growth, according to the conventional assay. The supervised classification models enabled the prediction of the compound's impact on the E. coli growth, with the accuracy for the test data: Partial least squares-discriminant analysis of 94%; Support vector machines of 89%; k-Nearest neighbor of 72%; and a Backpropagation network of 100%. According to the promising results, the integration of FT-MIR spectroscopy with machine learning presents a high potential to promote the discovery of new compounds with antibacterial activity, thereby streamlining the drug exploratory process.

Background: The increase in the prevalence of obesity in South Africa is a problem and weight management play an important role in the treatment of the high prevalence. For this purpose, a quantitative study was carried out using a structured questionnaire to assess predictors of attempt and failure to lose weight. Methods: One thousand and fifty adults were enrolled in the study and 54% (n=562) were overweight and obese (BMI >/25kg/m2). Descriptive statistics were analysed. Inferential statistical tests (chi-square tests, logistic regression, and Pearson’s correlation coefficients) were used to determine the relationship between variables. Results: The results revealed that age, sex, marital status, educational level, employment status, income level, area of residence, ethnic groups, and self-perceived BMI (normal weight, overweight, and obese) were predictors of attempt and failure to lose weight. There was a positive correlation between self-perceived BMI and the attempt and failure to lose weight. Conclusion: Weight management is important in the realm of public health and can be regarded as an investment in the population, as it leads people toward weight control strategies grounded in empirical evidence. Additionally, the findings can inform public health policies and interventions to improve weight management strategies at the population level.

For the first time, an attempt has been made to present in a systematized form chronologically the development of ornithological studies at the National Museum of Natural History in Sofia (Bulgaria) from its foundation in the last decades of the 19th century to the present day. This 135-year period (1889-2024) includes the work of 12 curators of the ornithological collections. Their major contributions and most-significant ornithological publications are also presented.

Limited research has been conducted on the metabolites present in the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (PR, syn. Lamiophlomis rotata (Benth.) Kudô), and their potential pharmacological activities, such as antioxidant properties, are often overlooked. We conducted a metabolomics-based screening to identify the characteristic metabolites (CMs) in the EOs extracted from PR. Meanwhile, we evaluated their in vitro antioxidant activities (AOAs). The EOs obtained through hydro-distillation are characterized by a light yellow color and a fresh, elegant fragrance. Cryoprecipitation was used to separate the crystals (Crs) from the EOs, resulting in the crystal-free EOs (CFs). A total of 121 components are identified and quantified in the EOs, Crs, and CFs. Among them, 84 were reported for the first time from such EOs. The major compounds include long-chain fatty acids (LCFAs) and their esters, such as palmitic acid (PA), myristic acid (MA), linoleic acid (LA), oleic acid (OA), stearic acid, and methyl palmitate (MP). Furthermore, 11 kinds of apocarotenoids (also called norisoprenoids) were first systematically investigated. Among them, eight C13-norisoprenoids, with trans-β-damascenone (DN) being particularly notable for its flavor, were identified. A sum of 11 CMs are screened , including PA, MA, LA, OA, MP, hexahydrofarnesyl acetone, phytol (PT), DN, stearic acid, linalool, and hexanal. These CMs are biosynthesized through FAs and 2-C-Methyl-D-erythritol 4-phosphate/1-Deoxy-D-xylulose 5-phosphate pathways. The in vitro AOAs of EOs, Crs, CFs, and seven selected CMs (PA, MA, LA, OA, MP, PT, and DN) were evaluated. Generally, PA and MA exhibited pro-oxidant activities (POAs) or weak AOAs. LA and OA demonstrated POAs or weak AOAs at lower concentrations, but at higher concentrations, they displayed medium to strong AOAs. Importantly, the CFs typically exhibited stronger AOAs compared to the corresponding EOs and Crs, potentially due to variations in their PA content. Overall, this study provides valuable insights into the potential utilization of EOs from PR.

Senna rugosa is a species found in the Cerrado and used in folk medicine as a vermifuge and in the treatment of poisonous snakebites accidents. In this work, we identified the main secondary metabolites present in ethanolic extracts of the leaves (ELSR) and roots (ERSR) of S. rugosa and evaluated the potential cytoprotective effect against cellular macromolecular damage, as well as the cytotoxic properties of the extracts on the K562 and Jurkat leukemic cell lines. The identification of metabolites was done by liquid chromatography coupled with mass spectrometry. The antioxidant activities were investigated by direct ABTS•+ and DPPH• radical scavenging methods, protection against oxidative damage in proteins and DNA. The cytotoxic properties were investigated against healthy cells, isolated from human peripheral blood (PBMC) and leukemic cell lines. The leaf extract contains catechin, rutin, epigallocatechin derivatives, kaempferol glycosides, luteolin, and dimeric and trimeric procyanidins, while the root extract profile shows obtusichromoneside derivatives, 2-methoxystypandrone, stilbene derivatives, naphthopyranones, and flavanone derivatives. The extracts showed antioxidant activity, with IC50 of 4.86 ± 0.51 µg/mL and 8.33 ± 0.90 µg/mL in the ABTS assay for ELSR and ERSR, respectively. And in the DPPH• assay, the IC50 was 19.98 ± 1.96 µg/mL for ELSR and 13.37 ± 1.05 µg/mL for ERSR. The extracts protected macromolecules against oxidative damage at concentrations of 5 µg/mL. The cytotoxicity test against leukemic strains was observed after 24 and 48 hours of treatment. After 48 h, results against the K562 cell line demonstrate IC50 of 242.54 ± 2.38 µg/mL and 223.00 ± 2.34 µg/mL for ELSR and ERSR , respectively. While against the Jurkat cell line, these extracts showed IC50 of 171.45 ± 2.25 µg/mL and 189.30 ± 2.27 µg/mL, respectively Results on PBMC viability, demonstrate that the extracts showed selectivity for the leukemic cell lines. Together, our results reveal that the leaves and roots of S. rugosa have completely distinct and complex chemical compositions. This study expands the repertoire of identified chemical compounds and underscores their significant pharmacological potential in conditions related to oxidative stress and leukemia.

The Kuznetsk Basin (Kuzbass) is one of the largest coal basins in Siberia and a reference area for the ancient Angaraland continent. The proximity of the Kuzbass and Siberian platform caused their biotic similarities in the Late Palaeozoic. However, due to biota endemism, the Kuzbass Upper Palaeozoic does not correlate directly with the International Chronostratigraphic Chart (ICC). This paper discusses radioisotopic (CA-ID-TIMS) dating of zircons from a volcanic tuff located in the Starokuznetsk Formation. This level matches the interval of the Balakhonka/Kolchugino (B/K) floral change in Kuzbass, i.e. the gradual replacement of cordaitoid-dominated wet forests (Balakhonka flora) by more arid fern-pteridosperm-cordaitoid assemblages (Kolchugino flora). New age (276.9 ± 0.4 Ma) directly correlates the Starokuznetsk Fm with the Upper Kungurian of the ICS. We compared the Kuzbass data with data of the Western Verkhoyanie, where Middle Permian ammonoids (Sverdrupites assemblage) occur in strata recording the B/K floral change. Available (ICC) and new datings indicate the lag between the B/K floral change in low (Kuzbass) and high (Verkhoyanie) latitudes of Angaraland. The B/K floral change in the Kuzbass began in the early Late Kungurian and was completed by the end of this age. In contrast, the B/K floral change in Verkhoyanie began at the end of the Late Kungurian and was completed in the Late Wordian. The delay in the floral changes at different latitudes of Angaraland suggests that existing interregional correlations need further improvement.

The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 20 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group’s insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.

Laminopathies are causally associated with mutations on Lamin A gene (LMNA). To date, more than 400 mutations in LMNA have been reported in patients. These mutations are widely distributed throughout the entire gene and are associated with a wide range of phenotypes. Unfortunately, little is known about the mechanisms underlying the effect of the majority of these mutations. This is the case of more than 40 mutations that are located at exon 4. Using CRISPR/Cas9 technology, we have generated a collection of Lmna exon 4 mutants in mouse C2C12 myoblasts. These cell models include different types of exon 4 deletions and the presence of R249W mutation, one of the human variants associated with a severe type of laminopathy (LMNA-associated congenital muscular dystrophy). We have characterized these clones by measuring their nuclear circularity, myogenic differentiation capacity in 2D and 3D conditions, DNA damage, and p-ERK and p-AKT levels. Our results indicate that Lmna exon 4 mutants show abnormal nuclear morphology. In addition, levels and/or subcellular localization of different members of the lamin and LINC complex are altered in all these mutants. Whereas no significant differences were observed for ERK and AKT activities, the accumulation of DNA damage was associated to the Lmna p.R249W mutant myoblasts. Finally, significant myogenic differentiation defects were detected in the Lmna exon 4 mutants. These results have key implications in the development of future therapeutic strategies for the treatment of laminopathies.

The connection between the mother and the child has been considered one of the strongest bonds in nature. Though there are numerous factors that can influence the establishment of pregnancy, in its essence three are considered major: a good quality embryo, a receptive endometrium and a successful cross-talk between them. The placenta, that derives from the trophoblast of the embryo, develops when a successful implantation occurs. It is an ephemeral organ through which the turnover of nutrient, gas and waste molecules is realized. It serves as barrier and can provide the embryo with immune factors. Placental disorders are observed in some rare but life-threatening obstetric conditions like: preeclampsia (PE), fetal growth restriction (FGR), gestational tropho-blastic diseases (GTD) and gestational diabetes mellitus (GDM). The etiology and pathogenesis of some are still partially enigmatic. Our attention in this review was driven by the participation of small RNA molecules: miRNAs and piRNAs, as potential epigenetic modulators of genes that play pivotal role in placental functioning. The molecular approach for understanding of placental disorders may help new diagnostic and therapeutic solutions to be found.

Choosing a career path is an important decision in a person’s life and forms the basis for their future direction. It impacts the future career and influences financial stability as well as the person’s well-being. Many people struggle to find out what they are interested in and talented in, making it difficult to choose a fitting career path. Therefore, the decision-making process requires careful consideration, self-reflection, and exploring numerous options. While virtual environments provide an effective way to explore different experiences, virtual reality (VR) offers users immersive interactions with simulated 3D environments. This allows the realistic exploration of different job fields in a virtual environment without being physically present. VR 360-degree videos have been shown to significantly increase job interest among students. The ability to review and refine performance makes VR an ideal tool for career skill development as well as career guidance. In this paper, we present a tool that offers young people virtual career guidance through an immersive VR experience. The study investigates the extent to which performing occupational tasks in a virtual environment influences the career perceptions of young adults and whether it enhances their understanding of professions. In total, 23 teenagers and 8 application experts were involved to assess the teenager’s expectations and the potential of the career guidance tool.

Decades of illegal hunting (poaching) have adversely affected wildlife populations and thereby limited sustainable wildlife conservation in the Luangwa Valley, Zambia. Despite intervention efforts to address the problem, illegal hunting of wildlife has persisted. Therefore, this study was conducted to understand the persistence of illegal hunting by investigating drivers of poaching and intervention measures using mixed-methods approach. Stratified random sampling was used to collect data from 346 respondents through structured questionnaires. Purposive sampling was used to collect data through nine (9) focus group discussions and three (3) in-depth interviews with experts. The study revealed that persistent illegal hunting was mainly driven by people’s critical needs for survival and sustaining livelihoods and not by inadequate law enforcement as presumed by resource managers. Although law enforcement was the most prevalent intervention measure, it did not deter local illegal hunters because the main motivations for poaching were not effectively addressed. The key implication of findings is that where illegal harvesting of natural resources in protected areas by local resource users is driven by people’s critical needs for survival and livelihoods which are ineffectively addressed, illegal harvesting may persist even with increased law enforcement. The study provides empirical evidence, novel conceptual knowledge and understanding on how prevalent drivers of poaching and other factors may have influenced persistent illegal hunting in the Luangwa Valley.

Endodontic treatments are performed to avoid extractions and maintain the natural dentition. Root canal treatments are undertaken to eliminate or prevent an infection within the root canal system. Chemical and mechanical root canal debridement are the main methods used in endo-dontics to remove necrotic tissue, microorganisms, and microbial byproducts from the canal. However, to date there is no objective method to clinically determine the proper root canal disin-fection level and thus proceed with the obturation. Clinicians just rely on their experience and habits or can trust in empirical methods such as the insertion of paper cones inside the channel and then check their appearance after the removal. Even in the in vitro and ex vivo scientific stud-ies there is no objective method to analyze and compare the efficacy of different endodontic chemo-mechanical techniques and materials. The most frequently used method is to visually an-alyze some areas with a scanning electron microscope (SEM), even if the resulting images are hardly quantifiable and could greatly vary according to the analyzed area. A new device to clin-ically test the cleanliness of a root canal and display the result in an objective score was recently developed. The device analyzes the luminescence generated by an enzyme cycling method that process the adenosine triphosphate (ATP), adenosine diphosphate (ADP) and adenosine mono-phosphate (AMP) present in organic residues. The aim of the present in vitro study was to test the efficacy and reliability of this novel device in a controlled in vitro environment, before using it in clinical practice.

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

In this contribution, the propylamine-functionalized cellulose (Cell-Pr-NH2) was employed as the catalyst in the three-component reaction between hydroxylamine hydrochloride, various type of aryl/heteroaryl aldehydes, ethyl acetoacetate/ethyl 4-chloroacetoacetate/ or ethyl 3-oxohexanoate. The results of these experiments were the formation of 3,4-disubstituted isoxazol-5(4H)-one heterocycles. The desired five-membered heterocyclic compounds were obtained in good to high yields at room temperature. The investigation of different solvents led us to the conclusion that water is the best solvent to perform the current one-pot, three-component reactions. Attempts to find the optimum catalyst loading clearly showed that 14 mg of Cell-Pr-NH2 seems to be sufficient to carry out the reactions. This method has highlighted some principles of green chemistry including less waste generation, atom economy, use of water as an environmentally friendly solvent, and energy saving. Purification without chromatographic methods, mild reaction conditions, simple work-up, low-cost reaction medium, saving time, and obtainable precursors are other notable features of this one-pot fashion.

Stormwater runoff from large roads is a major source of pollutants to receiving waters. Porous pavements have been shown to substantially reduce many of these pollutants, but studies are lacking on arterial roads. We sampled typical stormwater pollutants in runoff from sections of an arterial road 9-16 years after installation of three pavement types: control with conventional asphalt, porous asphalt overly, and full-depth porous asphalt. Both types of porous pavements substantially reduced most of the stormwater pollutants measured. Total suspended solids, turbidity, total lead, total copper, and 6PPD-quinone were all reduced by >75%. Total nitrogen, ammonia, total phosphorus, biochemical oxygen demand, total and dissolved copper, total mercury, total zinc, total polycyclic aromatic hydrocarbons, and di-2-ethylhexyl phthalate were all reduced by >50%. Reductions were lower or absent for nitrate, orthophosphate, E. coli, dissolved lead, and dissolved zinc. Most reductions were statistically significant. Many pollutants exceeded applicable water quality standards in the control samples but met them with both types of porous pavement. This study demonstrates that porous overlays and full-depth porous asphalt can provide substantial reductions of several priority stormwater pollutants on arterial roads for many years after installation.

Stress has various impacts on the health of human beings. Recent success in wearable sensor development, combined with advancements in deep learning to automatically detect features from raw data, opens several interesting applications related to detecting emotional states. Being able to accurately detect stress-related emotional arousal in an acute setting can positively impact the imminent health status of humans, i.e., through avoiding dangerous locations in an urban traffic setting. This work proposes an explainable deep learning methodology for the automatic detection of stress in physiological sensor data, recorded through a non-invasive wearable sensor device, the Empatica E4 wristband. We propose an Long-Short Term-Memory (LSTM) network, extended through a Deep Generative Ensemble of conditional GANs (LSTM DGE) , to deal with the low data regime of sparsely labeled sensor measurements. As explainability is often a main concern of deep learning models, we leverage Integrated Gradients (IG) to highlight the most essential features used by the model for prediction and to compare the results to state-of-the-art expert-based stress detection methodologies in terms of precision, recall and interpretability. Results show that our LSTM DGE outperforms the state-of-the-art algorithm by 3 percentage points in terms of recall, and 7.18 percentage points in terms of precision. More importantly, through the use of Integrated Gradients as a layer of explainability, we show that there is a strong overlap between model-derived stress features for electrodermal activity, and existing literature, which current state-of-the-art stress detection systems in medical research and psychology are based on.

In the ambitiously evolving construction industry of Kuwait, characterized by its vision 2035 and rapid technological integration, there exists a pressing need for advanced analytical frameworks. This research paper introduces a groundbreaking deep learning approach utilising an autoencoder neural network to analyse the complexities of the Kuwait Construction Market and identify data irregularities. The construction sector’s significant investment influx and project expansion make it an ideal candidate for deploying sophisticated analytical techniques to detect anomalous patterns indicating inefficiencies or unveiling potential opportunities. Our approach leverages the capabilities of autoencoder architectures to delve into and understand the prevalent patterns in market behaviours. This meticulous analysis allows for the detection of deviations that may lead to operational or financial consequences. We elucidate the mathematical foundations of autoencoders, highlighting their proficiency in managing the complex, multidimensional data typical of the construction industry. Through training on an extensive dataset—comprising variables like market sizes, investment distributions, and project completions—our model demonstrates its ability to pinpoint subtle yet significant anomalies. The outcomes of this study enhance our understanding of deep learning’s pivotal role in construction and building management. Additionally, our findings proactively sketch the future market trajectory and facilitate anomaly detection, thereby contributing substantially to the academic discussion on integrating machine learning into construction management. This research offers valuable insights for professionals within Kuwait, aiming to harness deep learning techniques to boost operational efficiency and strategic foresight in the construction sector.

This work examines the beneficial role of an unsteady stenosis, operating without the use of any external energy source, as a means for augmenting the flow rate of a valveless pump in a hydraulic loop, including an open tank. In contrast to our previous work that the loop was horizontal, here gravity was taken into account. The stenosis neck cross-sectional area was controlled by the fluid pressure and an opposing force applied externally by a spring of adjustable tension. The pincher compressed and decompressed periodically a part of a flexible tube with frequencies from 5 Hz to 11 Hz and compression ratios Ab from 24% to 65%. The presence of the stenosis increased the net flow rate 19 times for Ab = 24%, and 6.3 times for Ab = 38%, whereas for Ab = 65%, the flow rates were comparable. The volumetric efficiency varied from 30% to 40% under the presence of the stenosis, and from 2% to 20% without the stenosis. The role of the stenosis role was to cause a unidirectional flow, opening during tube compression and closing during decompression. The pressure amplitudes along the flexible tube increased towards the rigid-flexible tube junction (as a result of the wave reflections) which were found to be significantly attenuated by the presence of the stenosis.

Object detection is complex and involved diverse requirements for different applications. In critical application such as visual impaired navigation guide and real-time surveillance for instance, identifying a particular object of instance is required and this involved a complex approach for realization. Literatures were reviewed, starting with the application of deep learning techniques for object detection; their gaps were identified and addressed using real-time object detection models literature review. From the review gaps were also detected and addressed using literature review on occlusion detection techniques. Object of instance detection in clustered scene with similar object of interest was identified as an open gap not addressed in the existing literature; even through it is vital for many applications. This research recommended an Occlusion Based Object of Instance Detection (OBOID) technique which used the spatial information to identify instant object of interest in clustered scene with many similarly object of interest. Limitation of the recommended OBOID is that it requires only system where position and distance of object is necessary to inform other decision.

Conventional fertilization practices can lead to many ecological problems, such as nutrient imbalance, soil acidity, and reduced soil fertility in natural rubber plantations. To address these challenges, a field investigation was strategically carried out to substitute inorganic fertilizer with organic fertilizers consisted of six treatments, i.e., no fertilization (CK), inorganic fertilizer (NPK), 25 % replacement of inorganic through organic (25%M), 50 % replacement of inorganic through organic (50%M), 75 % replacement of inorganic through organic (75%M), and 100% organic fertilizer (100%M). The soil physicochemical properties (SOC, TN, AN, C:N, pH, NH4+-N, and NO3--N) and carbon and nitrogen converting enzymes (BG, NAG, and LAP) were all determined. The partial substitution of inorganic fertilizers with organic fertilizers (i.e., 75%M at surface soil layer) showed higher SOC (14.52 g.kg-1), TN (1.06 g.kg-1), AN (20.07 mg.kg-1), C:N (14.63), NH4+-N (10.63 mgkg-1), and NO3--N(11.06 mg.kg-1) than NPK and CK. Such increase in physicochemical properties in partial replacement of inorganic with organic fertilizers plots resulted from higher carbon and nitrogen enzymes activities (BG (143.17 nmol.g-1.h-1), NAG (153.96 nmol.g-1.h-1), and LAP (153.48 nmol.g-1.h-1)) compared to NPK and CK, and further the person correlation and RDA analysis confirmed a significant positive correlation between SOC, AN, and soil enzymes. This study presents a new strategy for assessing the impact of partially replacing inorganic fertilizers with organic fertilizers in rubber plantations, mainly by modifying the soil nutrient composition in tropical regions.

Fluoropyrimidines (FPs) are commonly prescribed in many cancer streams. The DPYD*2A (rs3918290), *13 (rs55886062), *HapB3 (rs56038477), alleles, and DPYD rs67376798, had shown the highest level of evidence about their association with FPs response. The EMA and FDA-approved drug labels for FPs, recommend genotyping these variants before treatment starts. We implemented the DPYD genotyping in our daily clinical routine, but we still find patients showing severe adverse drug events (ADEs) to FPs. We studied among these patients the association with the response to FPs of DPYD rs1801265, rs17376848, rs1801159, rs1801160, rs1801158, and rs2297595; as explanatory candidates of the interindividual differences for the FP-related toxicities. We also studied the impact of DPYD*2A, *13, *HapB3, and rs67376798 genotype for FP dose tailoring in our clinical practice and characterized the DPYD gene in our population. We found that FP dose lowering based on DPYD genotype does not affect the treatment efficacy. Also, the DPYD*4 (defined by rs1801158) allele was associated with a higher risk of ADEs (severity grade ≥ 3) in both the univariate (O.R.= 5.66; 95% C.I.= 1.35 – 23.67; p= 0.014) and multivariate analyses (O.R.= 5.73; 95% C.I.= 1.41 – 28.77; p= 0.019). This makes it a candidate variant for implementation in clinical practice.

The metabolome is the composition of all molecules present in an organism, metabolomics science allows us to qualitatively and quantitatively analyze metabolites and understand the biochemical state in response to genetic and environmental changes. The purpose of the study was to identify the metabolomic profile of biofluids (saliva and urine) of patients living with HIV/AIDS (PLHIV/AIDS), and establish a possible association of metabolites with periodontal disease (PD). It was an analytical and descriptive study composed of 65 patients seen at the Center for Studies and Care for Special Patients (CEAPE-UNIP), who were divided into 4 predetermined groups (G), G1-PLHIV/AIDS and without PD, G2- PLHIV/Aids and with PD, G3-people without HIV/Aids and without PD, G4-people without HIV/Aids and with PD. The results showed that in relation to urine, G2 has the highest mean area of concentration of metabolites. There are statistically significant differences between G1 and G2. The area of G2 is greater than G3, and greater than G4. There are no differences between G3 and G4, neither between G1 and G3, nor between G1 and G4. Regarding saliva, there are no statistically significant differences when comparing the groups for the mean areas of concentration of metabolites. We conclude that it was possible to distinguish the metabolic profile of PLHIV/Aids with periodontal disease and without periodontal disease, some metabolites are over expressed in PLHIV/Aids and with PD. Most of the metabolites of the carbohydrate group are under expressed in PLHIV/AIDS, even in systemic compensation situations these patients presented a different metabolic profile.

Maternal obesity and over/undernutrition can have a long-lasting impact on offspring health during critical periods in the first 1000 days of life. Children born to mothers with obesity have reduced immune responses to stimuli which increase susceptibility to infections. Recently, maternal western-style diets (WSD), high in fat and simple sugars, have been associated with skewing neonatal immune cell development, and recent evidence suggests that dysregulation of innate immunity in early life has long-term consequences on metabolic diseases and behavioral disorders in later life. Several factors contribute to abnormal innate immune tolerance or trained immunity, including changes in gut microbiota, metabolites, and epigenetic modifications. Critical knowledge gaps remain regarding the mechanisms whereby these factors impact fetal and postnatal immune cell development, especially in precursor stem cells in bone marrow and fetal liver. Components of the maternal microbiota that are transferred from mothers consuming a WSD to their offspring are understudied and identifying cause and effect on neonatal innate and adaptive immune development needs to be refined. Tools including single-cell RNA-sequencing, epigenetic analysis, and spatial location of specific immune cells in liver and bone marrow are critical for understanding immune system programming. Considering the vital role of immune function plays in offspring health, it will be important to understand how maternal diets can control developmental programming of innate and adaptive immunity.

The need to alleviate the difficulties of abstraction and improve students’ achievement in Physical Geography informed this research. This study investigated the Effects of Mastery Learning Strategy and Learning Retention on Senior Secondary School Students’ Achievement in Physical Geography. The study adopted the quasi experimental non-equivalent pre-test, post-test control group design. The Multi-stage sampling technique at four levels was used to select four co-educational secondary schools in Ganye Educational Zone in Nigeria. The sample for the study was 218 Senior Secondary School two (SS II) students offering Geography from four intact classes in the four selected secondary schools. The instrument used for data collection was “Physical Geography Achievement and Retention Test” (PGART). The reliability of the instrument was established using Kendall tau b statistic. This gave a reliability index of 0.74. Data collected were analyzed using Mann-Whitney U and t-Test. The results showed that Mastery Learning Strategy has the potentials to improve students’ learning outcomes, retention and achievement in all spheres of cognitive domain in Physical Geography better than the Conventional Method. Hence the need to incorporate this teaching strategy during instruction so that learners would be guided to learn meaningfully and be assisted to retain content learnt in Geography.

The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design of proteins with unprecedented precision and functionality. Computational methods now play a crucial role in enhancing the stability, activity, and specificity of proteins for diverse applications in bio-technology and medicine. Techniques such as deep learning, reinforcement learning, and transfer learning have dramatically improved protein structure prediction, optimization of binding affin-ities, and enzyme design. These innovations have streamlined the process of protein engineering by allowing the rapid generation of targeted libraries, reducing experimental sampling, and en-abling the rational design of proteins with tailored properties. Furthermore, the integration of computational approaches with high-throughput experimental techniques has facilitated the development of multifunctional proteins and novel therapeutics. However, challenges remain in bridging the gap between computational predictions and experimental validation, and in ad-dressing ethical concerns related to AI-driven protein design. This review provides a compre-hensive overview of the current state and future directions of computational methods in protein engineering, emphasizing their transformative potential in creating next-generation biologics and advancing synthetic biology.

As a major coal country, China faces the issue of significant gas emissions during the coal mining process. This study aims to improve the utilization efficiency of mine gas, reduce greenhouse gas emissions, and promote the low-carbon and green transformation of the coal industry. A 10kW gas regenerative thermal oxidation (RTO) experimental system was constructed. The effects of initial methane concentration, low-temperature flue gas proportion, and operating load on combustion temperature, methane oxidation rate, high-temperature flue gas energy, and system thermal efficiency were studied. The results show that when the combustion temperature is below 600°C, the CH4 combustion reaction cannot proceed effectively, and the system temperature continuously decreases and cannot be maintained stable. The experiment determines the stable operating methane concentration range of RTO. In this experimental system, the lower limit of the initial methane concentration is 0.28%, corresponding to an 86% methane oxidation rate. As the initial methane concentration decreases, the combustion temperature also decreases, and the methane oxidation rate follows suit. The higher the low-temperature flue gas proportion, the higher the combustion temperature, and the system thermal efficiency and output heat decrease with the increase of the low-temperature flue gas proportion. This experiment explores multiple factors affecting regenerative thermal oxidation, providing an basis for ensuring the safe and stable operation of the system and optimization. Improving the thermal insulation and heat exchange performance of the storage body can expand the lower limit of the initial methane concentration, thereby increasing the stability and thermal efficiency of the system.

The survival rate of extracorporeal life support (ECLS) remains overall at 60 %. Research and development is slow, partly due to the lack of sophisticated experimental models. This publication introduces a dedicated rodent oxygenator (“RatOx”) and shows preliminary in vitro classification tests. The RatOx has an adaptable fiber module size for various rodent models. Gas transfer performance over the fiber module for different blood flows and fiber module sizes were tested according to DIN EN ISO 7199.At the maximum possible amount of effective fiber surface and a blood flow of 100 ml/min, the oxygenator performance has been tested to a maximum of 6.27 ml O2/min and 8.2 ml CO2/min, respectively. The priming volume for this the largest fiber module is 5.4 ml, while the smallest possible configuration with a single fiber mat layer has 1.1 ml of priming volume. The novel RatOx ECLS system has been evaluated in-vitro to comply to a high degree with all predefined functionality criteria for rodent sized animal models. We intend for the RatOx to become a standard testing platform for scientific studies on ECLS therapy and technology.

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of the estimated wind energy in a desert city in northwestern Mexico. For the statistical modeling, 3 time series of wind speed data were used, corresponding to the years 2017, 2018, and 2019, recorded with a sonic anemometer at a sampling frequency of 10 Hz. From these, the analysis is performed with different stationarity periods (5, 30, 60, and 600 seconds). The estimation of the parameters characterizing the probability density functions was performed using different methods; the statistical models were evaluated by the coefficient of determination and the Nash-Sutcliffe efficiency coefficient, while their accuracy by the measured quadratic error, the mean square error, the mean absolute error, and the mean absolute percentage error. It was found that Weibull with the energy pattern factor method and Gamma using the method of moments were the probability density functions that best describe the statistical behavior of the wind speed and, therefore, better estimate the energy generated, so it is concluded that the proposed methodology will allow having greater confidence, both in the estimation of the wind speed and in the small wind energy available for its use.

Climate change presents an urgent and impending threat to virtually all global biological systems. In recent years, there has been a surge in research endeavors aimed at investigating the potential relationship between changes in climate patterns and the spread of infectious diseases. This scoping review included studies on global warming and infectious diseases from 2019 to 2023, The studies included in this research were obtained from reputable academic databases such as Web of Science and google scholar. A systematic keyword search was conducted to identify relevant studies, and a predefined set of inclusion criteria was applied to review and select the appropriate studies for analysis. This review found that climate change has a remarkable impact on the dissemination and incidence of many infectious diseases, it increases microbial resistance and may increase the prevalence the arthropods-borne diseases with mild effect on fungal infections, also, the low to middle income countries may be affected more than other countries from these virulent pathogens, this study concluded that a future research in the field of climate change and infectious diseases should involve a thorough examination of the transmission of diseases, considering both direct and indirect modes of transmission

Background The nematode Caenorhabditis elegans (C. elegans) possesses a sophisticated sense of smell and is used for a novel cancer screening test that utilizes the chemotaxis index. We designed a single-institution, prospective study to confirm the ability of Nematode Nose (N-NOSE) to determine preoperative chemotherapy's efficacy for esophageal cancer patients. Patients and Methods We investigated the predictability of N-NOSE screening for the clinical effects of preoperative chemotherapy for esophageal cancer patients receiving radical surgery. The index reduction score (IRS) was calculated by chemotaxis of C. elegans at three points: before treatment, before surgery, and after surgery, and its clinical relevance was examined. Result Thirty-nine patients with esophageal cancer were enrolled from August 2020 to December 2021 and 30 patients receiving radical surgery were examined. Complete response or partial response was achieved in 23 cases (76.7%). When the target of the treatment effect was complete response only, the prediction accuracies of the IRS calculated by area under the curve was 0.85 (95% Confidence interval: 0.62-1) in clinically achieving complete response group, and the sensitivity and specificity were 1 and 0.63, respectively. Conclusion Index reduction score using N-NOSE screening may reflect the efficacy of chemotherapy for esophageal cancer patients. A large-scale prospective study at multiple centers is desired in the future.

Background: Although the link between environmental lead exposure and several patterns of cardiovascular disease (CVD) has been reported, its association with silent myocardial infarc-tion (SMI) has not been explored. We aimed to assess the association between blood lead levels (BLL) and risk of SMI. Methods: This analysis included 7283 (mean age 56.1±2.52 years, 52.5% women) participants from the Third National Health and Nutrition Examination Survey who were free of clinical CVD. Ascertainment of BLL done using graphite furnace atomic absorption spectrophotometry. SMI defined as ECG evidence of MI without history of MI. Multivariable lo-gistic regression analysis was used to examine the association between SMI and BLL. Results: SMI was detected in 120 participants corresponding to an unweighted prevalence of 1.65%. Par-ticipants with higher levels of BLL had higher prevalence of SMI (0.4%, 0.9%, and 2.4% across BLL tertiles; p-value

To achieve low-cost and on-demand launches of micro satellites, the authors have been researching and developing a micro hybrid rocket since 2014. In 2018, a ballistic launch experiment was performed using the developed hybrid rocket, where it reached an altitude of about 6.2 km. The rocket engine had a 3D-printed solid fuel grain made of acrylonitrile butadiene styrene (ABS) resin in combination with a nitrous-oxide oxidizer. The fuel grain port had a star-fractal swirl geometry in order to increase the surface area of the port, to promote the laminar-turbulent transition by increasing the friction resistance, and to give a swirling velocity component to the oxidizer flow. This overcame the hybrid rocket’s drawback of low fuel regression rate; i.e., it achieved a higher fuel-gas generation rate compared with a classical port geometry. In 2021, the hybrid rocket engine was scaled up and its total impulse was increased to over 50 kNs for reaching an altitude of 15 km. In addition to the engine, other components were also improved, such as through incorporation of lightweight structures, low-shock separation devices, a high-reliability telemetry device and data logger, while keeping costs low. The rocket was launched and reached an altitude of about 10.1 km, which broke the previous Japanese altitude record of 8.3 km for hybrid rockets. The presentation will report on the developed components from the viewpoint of system design and the results of the ballistic launch experiments.

Recommender systems in education are becoming more widespread, typically focusing on recommending courses or study materials. This study proposes a machine learning approach to recommend a university degree based on high school and university standardised test results, incorporating students' socioeconomic information as input variables. The objective is to develop a tool for students’ decision-making, supporting the sustainable development goal of Quality Education by providing a data schema to maximise the likelihood of a successful match between the student's profile and the academic program. With its focus on equity in education, this study provides a data-driven approach to assist students in selecting suitable university degrees, aiming to improve educational outcomes and inspire a more equitable education system.

The article covers the Surveyor Institute's historical context and its role in the legal order of land rights registration. It highlights the importance of GPS technologies in ensuring the accuracy of registering rights to real estate. The article reviews the role of systematic registrations in clarifying overlapping cadastral data and preventing neighborhood disputes. Additionally, it underscores the challenges related to surveying activities in Georgia and emphasizes the importance of establishing a legal framework for this profession.

The increasing importance of hydropower generation has led to the development of new smart technologies and the need for reliable and efficient equipment in this field. As long as hydropower power plants are more complex to build up than other power plants, the operation regimes and maintenance activities become essential for the hydropower companies to optimize their performance, such that including the data-driven approaches in the decision-making process represents a challenge. In the paper, a comprehensive and multi-task framework integrated into a Knowledge Discovery module based on Data Mining to support the decisions of the operators from the control rooms and facilitate the transition from the classical to smart Supervisory Control and Data Acquisition (SCADA) system in hydropower plants has been designed, developed, and tested. It integrates tasks related to detecting the outliers through advanced statistical procedures, identifying the operating regimes through the patterns associated with typical operating profiles, and developing strategies for loading the generation units that consider the number of operating hours and minimize the water amount used to satisfy the power required by the system. The proposed framework has been tested using the SCADA system's database of a hydropower plant belonging to the Romanian HydroPower Company. The framework can offer the operators from the control room comparative information for a time horizon longer than one year. The tests demonstrated the utility of a Knowledge Discovery module to ensure the transition toward smart SCADA systems that will help the decision-makers improve the management of the hydropower plants.

Fungi play important roles in the process of material cycling and energy transfers in aquatic ecosystems. Yet little is known about the fungal community in lake sediment. In this study, sediment samples from five habitat types in Baiyangdian Lake (BYD Lake) were collected across three seasons. High-throughput sequencing techniques were used to determine the compositions of fungal communities. Fungi are highly diverse in the sediment of BYD Lake, although some important fungi have not been accurately identified. The fungal diversity was highest in winter and lowest in summer, while the variations of species richness among sampling sites were not significant. The compositions of fungal community differed among seasons and habitats. Physicochemical properties of sediments were measured and the influence of the environmental factors on fungal communities were analyzed. Temperature, P, N, and heavy metals explained 48.98% of the variations of fungal communities across three seasons. Human activities have affected the species and biomass of fungi to some extent. Temperature is the most influential factor and is negative to fungal diversity. Nutrient element in different forms have different effects on shaping the fungal community. The effect of heavy metals is not clear.

This paper explores the properties of projective vector fields on semi-Riemannian manifolds. The main result establishes that if a projective vector field η on such a manifold is also a conformal vector field with potential function ψ, then η must either be homothetic, or the vector field ζ, which is dual to dψ, is a light-like vector field. Additionally, it is shown that a complete Riemannian manifold admits a projective vector field that is also conformal and non-Killing if and only if it is locally Euclidean. The paper also presents other results related to the characterization of Killing and parallel vector fields using the Ricci curvature and the Hessian of the function given by the inner product of the vector field.

In Brain-Computer Interface Motor Imagery (BCI-MI) systems, Convolutional Neural Networks (CNNs) have traditionally dominated as the deep learning method of choice, demonstrating significant advancements in state-of-the-art studies. Recently, Transformer models with attention mechanisms have emerged as a sophisticated technique, enhancing the capture of long-term dependencies and intricate feature relationships in BCI-MI. This research investigates the performance of EEG-TCNet and EEG-Conformer models, which are trained and validated using various hyperparameters and bandpass filters during preprocessing to assess improvements in model accuracy. Additionally, this study introduces the EEG-TCNTransformer, a novel model that integrates the convolutional architecture of EEG-TCNet with a series of self-attention blocks employing a multi-head structure. The EEG-TCNTransformer achieves an accuracy of 82.97% without the application of bandpass filtering. The source code of EEG-TCNTransformer is available on GitHub.

Target detection technology plays a crucial role in fishery ecological monitoring, fishery diversity research, and intelligent aquaculture. Deep learning, with its distinct advantages, provides significant convenience to the fishery industry. However, it still faces various challenges in practical applications, such as significant differences in image species and image blurring. To address these issues, this study proposes a multi-scale, multi-level, and multi-stage cross-domain feature fusion model. In order to train the model more effectively, a new dataset called Fish52 (Multi-scene Fish dataset) was constructed, on which the model achieved an mAP of 82.57%. Furthermore, we compared prevalent one-stage and two-stage detection methods on the Lahatan (single-scene fish dataset) and Fish30 dataset and tested them on the F4k and FishNet dataset. The mAP of our proposed model on the Fish30, Lahatan, F4k, and FishNet datasets reaches 91.72%, 98.7%, 88.6%,and 81.5% respectively, outperforming existing mainstream models. Comprehensive empirical analysis indicates that our model possesses high generalization ability and has reached advanced performance levels. In this study, the depth of the model backbone is deepened, a novel neck structure is proposed, and anew module is embedded therein. To enhance the fusion ability of the model, a new attention mechanism module is introduced. In addition, in the adaptive decoupling detection header module, introducing classes with independent parameter sand regression adapters reduces interaction between different tasks. The proposed model can better monitor fishery resources and enhance aquaculture efficiency. It not only provides an effective approach for fish detection but also has certain reference significance for the identification of similar target sin other environments, and offers assistance for the construction of smart fisheries and digital fisheries.

The real implementation of biogas reforming at industrial scale to obtain interesting products, like hydrogen or syngas, is a developing research field where multidisciplinary teams are continuously adding improvements and innovative technologies. Thus, these works can contribute to the proliferation of green technologies where circular economy and sustainability are present. To assess the sustainability of these processes, there are different tools like life cycle assessment (LCA), which implies a complete procedure where even small details count to consider a certain technology sustainable or not. The aim of this work was to review works where LCA is applied to different aspects of biogas reforming, especially focusing on the role of catalysts, which are essential to improve the efficiency of a certain process, but also present a strong influence on its environmental impact. As a conclusion, catalysts have an influence on LCA through the improvement on the catalytic performance and the impact of their production, whereas other aspects related to biogas or methane reforming could equally influence on their durability or reusability, with the subsequent effect on LCA. Further research about this subject is required in a continuously changing technology with plenty of possibilities.

Runway Safety Assistant Foreseeing Excursions (RUN.S.A.F.E.) is a complete embedded system solution that predicts a potential runway overrun of a civil aviation aircraft, during the Take off and Landing. This work examines the feasibility of such a system, through the algorithms and computations that predict the overruns. The system executes both static and dynamic calculations, the former being dependent, while the latter independent to the user’s inputs. Both outcomes and the runway’s length continuously estimate in real time if the process will end up in an overrun. All inputs are specifically selected, to either be available to the pilots, or to be retrieved from the existing avionics systems of the cockpit. A performance evaluation is conducted on both static and dynamic calculations, and metrics unveil the accuracy of the predictions and the time needed to converge to a reliable result. The solution is adapted for a Boeing 737-800 aircraft, with CFM56-7B engines, yet the calculations also apply for similar aicrafts, equipped with a tricycle Landing gear and turbofan engines, namely the whole Boeing 737 family, the Airbus A320 family etc.. The system is aligned with current standards and certification specifications, where applicable.

Acousto-Optical Tunable Filters (AOTFs) are a promising technology, exceptionally suited for advanced applications in spectroscopy and imaging across various scientific fields, including space exploration. This is due to their flexibility and high-speed functionality for precise wavelength selection via periodic modulation of the crystal’s refractive index using sound waves. These AOTFs are in turn driven by Radio Frequency (RF) signals through a transducer creating sound waves inside the crystal. This work presents a detailed comparison of three distinct topologies of Radio Frequency Power Amplifiers (RFPAs) for driving these AOTFs within the 30 to 300 MHz frequency range. The analysis focuses on three critical parameters: efficiency, bandwidth, and linearity, which are essential for optimizing the performance of AOTFs. By evaluating the trade-offs among these parameters, this research aims to identify the most effective design approach for RFPAs in this application context.

Mobile devices (MD) are used by mobile cloud computing (MCC) customers users because of their 11 portability and robust connectivity and the ability to house and operate third-party applications 12 (apps). However, the apps installed on a MD may pose data security risks to the MD owner and to 13 other MCC users, especially when the requested permissions include access to sensitive data (e.g., 14 user’s location and contacts). Calculating the risk score of an app or quantifying its potential 15 harmfulness based on user input or on data gathered while the app is actually running may not 16 provide reliable and sufficiently accurate results to avoid harmful consequences. This study 17 develops and evaluates a risk assessment framework for Android-based MDs that does not depend 18 on user input or on actual app behaviour. Rather, an app risk evaluator assigns a risk category to 19 reach resident app based on the app’s classification (benign or malicious) and the app’s risk score. 20 The app classifier (a trained machine learning model) considers the permissions and the intents 21 requested by the app. The apps risk score is calculated by a probabilistic function based on the 22 app’s use of a set of selected dangerous permissions. The results from the testing of an instance of 23 the framework on a MD with real-life resident apps indicated that the proposed security solution 24 was effective and feasible.

In this research, we utilize density functional theory (DFT) to study and investigate the adsorption process of methanol on three unique two-dimensional nanomaterials, namely BN, Graphene, and AlN. Eight sites for BN, AlN, and six sites for graphene were considered to reach full structural optimization. By conducting comprehensive simulations and analyses, we discovered diverse adsorption configurations and energy levels, which indicate different interaction strengths between methanol and the three 2D nanomaterials. Remarkably, AlN exhibits superior adsorption capabilities when compared to Graphene and BN which can be explained by attributable to the nature of charge transfer between the adsorbate and the adsorbent. For methanol adsorption on AlN, the strongest adsorption energy was (-0.5532 eV), and the amount of charge transferred from methanol to AlN was found to be (+0.075). For BN, the strongest adsorption energy was (-0.1351 eV), and the amount of charge transferred from methanol to BN was (+0.022). The density of states results indicated that the bandgap decreased, with a shift to the right. In contrast, for methanol adsorption on graphene, the strongest adsorption energy was found to be (-0.073 eV), and the amount of charge transferred from methanol to graphene was (+0.004). The density of states results showed no change in the bandgap. Our findings underscore the superiority of AlN’s potential over BN and Graphene for applications requiring efficient methanol adsorption, such as gas separation and storage technologies. This study emphasizes the superiority of AlN over Graphene and BN for tasks that necessitate effective methanol adsorption.

Accurate calculation of non-covalent interaction energies in nucleotides is crucial for understanding the driving forces governing nucleic acid structures and functions, as well as developing advanced molecular mechanics forcefields or machine learning potentials tailored to nucleic acids. Here, we dissect the nucleotides’ structure into three main constituents: nucleobases (A, G, C, T, and U), sugar moieties (ribose and deoxyribose), and phosphate group. The interactions among these fragments and between fragment and water were analyzed. Different quantum mechanical methods were compared for their accuracy in captuing the interaction energy. The non-covalent interaction energy was decomposed into electrostatics, exchange-repulsion, dispersion, and induction using two ab-initio methods: Symmetry-Adapted Perturbation Theory (SAPT) and Absolutely Localized Molecular Orbitals (ALMO). These caculations provide the benchmark for different QM methods while providing valuable understanding of the roles of various interamolecular forces in hydrogen bonding and aromatic stacking.

The hyperactivation of the sympathetic nervous system (SNS) is linked to obesity, hypertension, and type 2 diabetes, with elevated norepinephrine (NE) levels being a key feature. Previous research has shown increased sodium-glucose cotransporter 1 (SGLT1) protein in kidneys of hypertensive rodents, prompting investigation into SGLT1 expression in other tissues such as skeletal muscle. This study aimed to assess: i) whether skeletal muscle cells and tissue express SGLT1 and SGLT2 protein; ii) if NE increases SGLT1 in skeletal muscle cells and iii) whether skeletal muscle of neurogenically hypertensive mice exhibits increased SGLT1 expression. We found that i) skeletal muscle cells and tissue are a novel source of SGLT2 protein and ii) NE significantly elevated SGLT1 in skeletal muscle cells. As SGLT2 inhibition (SGLT2i) with Empagliflozin increased SGLT1, in vivo studies with the dual SGLT1/2i, Sotagliflozin were warranted. Treatment of neurogenically hypertensive mice with Sotagliflozin significantly reduced blood pressure. Our findings suggest that SNS activity upregulates the therapeutic target, SGLT1 in skeletal muscle, potentially worsening cardiometabolic control. As clinical trial data suggests cardiorenal benefits with SGLT2i, future studies should aim to utilize sole SGLT1i which may offer a therapeutic strategy for conditions with heightened SNS activity, such as hypertension, diabetes and obesity.

In this work, we introduce the design a 16-channel in-pixel neural analog front-end which employs a current-based summing approach to establish a common-mode feedback loop. The primary aim of this novel structure is to enhance both the system common-mode rejection ratio (SCMRR) and the common-mode interference (CMI) range. Compared to more conventional designs, the hereby proposed front-end utilizes DC-coupled inverter-based main amplifiers, which significantly reduce the occupied on-chip area. Additionally, the current-based implementation of the CMFB loop obviates the need for voltage buffers, replacing them with simple common-gate transistors and in turn decreasing both area occupancy and power consumption. The proposed architecture is further examined from an analytical standpoint, providing a comprehensive evaluation through design equations of its performance in terms of gain, common-mode rejection and noise power. A 50μm×65μm compact layout of the pixel amplifiers that make up the recording channels of the front-end was designd in a 180 nm CMOS process. Simulations conducted in Cadence Virtuoso reveal an SCMRR of 80.5 dB and a PSRR of 72.58 dB, with a differential gain of 44 dB and a bandwidth that fully encompasses the frequency range of the bio-signals that can be theoretically captured by the neural probe. The noise integrated in the range between 1 Hz and 7.5 kHz results in an IRN of 4.04 μVrms. Power consumption is also tested, with a measured value of 3.77 μW per channel, corresponding to an overall consumpution of about 60 μW. To test its robustness with respect to PVT and mismatch variations, the front-end is evaluated by means of extensive parametric simulations and Monte Carlo simulations, revealing favorable results.

The Julia-Kocienski olefination reaction has become over past 30 years since its discovery one of the key C-C connective methods that is used in the late-stage natural product synthesis. The reaction proceeds under mild reaction conditions, with wide substrate scope and functional group tolerance, and with high (E) selectivity. In this review, we discuss the reaction from a mechanistic point of view and disclose key features that play an important role in reaction selectivity. Finally, the mechanistic aspects of the newly developed modification of the Julia-Kocienski reaction, which allows the formation of both (E) and (Z) olefins, from the same reaction partners, are discussed.

Background and Objectives: Peripheral vertigo is one of the most common symptoms for which patients are seen by a neurologist in the emergency room. Symptoms of peripheral vertigo can range from lightheadedness to an illusion of spinning. On average, vertigo is diagnosed for older patients as its predicting factors from medical history are yet to be determined. The objective of the study was to predict peripheral vertigo based on medical history and risk factors. Materials and Methods: A prospective case-control study at the Neurology Department of Lithuanian University Hospital was conducted. 71 patients diagnosed with vertigo and 43 controls was included. They completed questionnaires and underwent evaluation by neurologists or otolaryngologists, with statistical analysis performed using IBM SPSS Statistics. Results: 58% of vertigo patients were diagnosed with peripheral vertigo, with significant predictors including age (>60), motion sickness, height intolerance, gastroesophageal reflux disease and dyslipidemia, leading to the development of a risk assessment table for the peripheral vertigo prediction. Conclusions: This study suggest that early identification of these predictors could enhance peripheral vertigo management, while further research with larger cohorts is needed to validate and expand upon these findings, emphasizing the importance of considering medical history and risk factors for predicting peripheral vertigo and improving patient care.

Hip fractures are the most frequently treated fractures in the world. Of these, intertrochanteric fractures (ITFs) account for almost 50%. After surgical fixation of ITFs, nonunion is rare. Nonunions are commonly produced from mal-reduction (in varus) and/or inadequate stability of the bone-implant construct and/or fatigue failure of the implants. Other causes of nonunion include posteromedial comminution and osteoporosis. The published incidence of ITF nonunion is 1%-2%. Mechanical complications of ITFs include cut-out, excessive shortening of the proximal femur, delayed union, nonunion, early implant fracture, nail toggle and cut through/medial migration. That is why a fundamental goal in the treatment of ITFs is to achieve stable fixation in osteoporotic bone, allowing early weight bearing. Intraoperative determination of fracture stability is essential. The American Academy of Orthopedic Surgeons (AAOS) clinical practice guidelines for the management of intertrochanteric fractures (ITF) in patients older than 55 years are the following: 1) In patients with stable ITF, the use of either a sliding hip screw (SHS) or a cephalomedullary nail (CMN) is advised (strong strength of evidence). 2) In patients with reverse obliquity fractures, a CMN is recommended (strong strength of evidence). 3) Patients with unstable ITF should be treated with a CMN (strong strength of evidence). 4) In patients with ITF, a short or long CMN may be considered (limited strength of evidence).

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses metabolic dysfunction-associated fatty liver (MASL) and metabolic dysfunction-associated steatohepatitis (MASH), with MASH posing a risk of progression to cirrhosis and hepatocellular carcinoma (HCC). The global prevalence of MASLD is estimated at approximately a quarter of the population, with significant healthcare costs and implications for liver transplantation. The pathogenesis of MASLD involves intrahepatic liver cells, extrahepatic components, and immunological aspects, particularly the involvement of macrophages. Hepatic macrophages are a crucial cellular component of the liver and play vital roles in liver function, contributing significantly to tissue homeostasis and swift responses during pathophysiological conditions. Recent advancements in technology have revealed the remarkable heterogeneity and plasticity of hepatic macrophage populations and their activation states in MASLD, challenging traditional classification methods like the M1/M2 paradigm and highlighting the coexistence of harmful and beneficial macrophage phenotypes that are dynamically regulated during MASLD progression. This complexity underscores the importance of considering macrophage heterogeneity in therapeutic targeting strategies, including their distinct ontogeny and functional phenotypes. This review provides an overview of macrophage involvement in MASLD progression, combining traditional paradigms with recent insights from single-cell analysis and spatial dynamics. It also addresses unresolved questions and potential therapeutic targets in this area.

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant scattering information of objects. Utilizing this information for PolSAR image classification can improve accuracy and enhance object monitoring. Although significant progress has been achieved in related research, there are still issues such as insufficient utilization of polarimetric information and features. In this paper, a deep learning classification method based on polarimetric channel power features for PolSAR is proposed. The distinctive characteristic of this method is that the polarimetric features inputted into the deep learning network are the power values of polarimetric channels, where these channels are treated equivalently and contain complete polarimetric information. In terms of experimental comparative study, besides polarimetric power combinations, three different data input schemes were employed as data for the input end of the convolutional neural network (CNN), taking into account existing research. The neural networks utilizes the extracted polarimetric features to classify images, and the classification accuracy analysis is employed to compare the strengths and weaknesses of different input schemes. It is worth mentioning that the polarized characteristics of the data input scheme mentioned in this article have been derived through rigorous mathematical deduction, and each polarimetric feature has clear physical meaning. By testing different data input schemes on the Gaofen-3 (GF-3) PolSAR image, the experimental results show that the method proposed in this article outperforms existing methods and can improve the accuracy of classification to a certain extent, validating the effectiveness of this method in large-scale area classification.

The research paper investigates the synthesis of metal matrix composites (MMCs) through the amalgamation of aluminum and silicon carbide particles, employing a two-step mixing methodology called the stir casting method. Metal matrix composites are materials that enhance the capabilities of a metallic matrix by incorporating another material. This leads to better characteristics such as tensile and shear moduli, fatigue and fracture properties, thermal expansion coefficient, and more. Aluminum-matrix composites are a class of materials that possess distinct characteristics that may be modified by altering factors such as the type of reinforcing material, the amount of reinforcement, and the fabrication technique employed to produce the composite. The concept aims to combine the desirable properties of metals and ceramics by incorporating durable refractory particles into a malleable metal structure. The fabrication process employs the stir casting technique, where reinforcing phases are mechanically stirred into a molten matrix to create cast composites with reinforcement volume percentages of up to 30%. The study utilizes Response Surface Methodology to enhance the mechanical properties of the composites through the optimization of manufacturing parameters, including stirring temperature, time, and speed. The study entails analyzing the correlation between different casting conditions and the resulting changes in hardness and tensile strength.

Aims: To study the effects of pyridoxal phosphate (PLP) on oxidative stress in isolated pancreatic acinar cells. We have previously shown that PLP has cytoprotective and insulinotropic effects on mice islet cells in vivo and in vitro studies. Main methods: Acinar cells were isolated from three months old WNIN male rats and were cultured in vitro for a period of 24 h in CO₂ incubator. Later the cells were divided into four groups as untreated (group 1), H₂O₂ treatment (group 2)_, PLP treatment (group 3) and PLP followed by H₂O₂ treatment (group 4). Cell viability was confirmed using MTT assays, oxidative stress levels were measured with ROS assay, change in different protein levels were recorded by flow cytometry. The acinar cells insulin secretion assay was performed with ELISA. The amylase protein expression was assessed using confocal microscopy. Key findings: The cell viability of acinar cell in group 1 was considered as 100%, while in group 2 it was reduced to 82% due to H₂O₂ effect, and in group 3 (99.8%) and group 4 (99.5%) were near to group 1 due to the cytoprotective effect of PLP. The ROS levels were increased by 1.47 folds in group 2, while PLP decreased to 1.02 fold in group 4, which was comparable with the changes in group 1. Beneficial effects of PLP were also observed from the increased expression levels of acinar cells are amylase -2.01, neurogenin-3-9.51, PDX-1- 23.6 and insulin-13.5 in group 3 compared to group 1. The specificity of PLP’s response was confirmed by amino oxy acetic acid (AOAA), a specific PLP inhibitor. The increased amylase protein localization with PLP was confirmed by confocal microscopy. Insulin secretion efficiency of acinar cells was observed to be 6.13 folds higher at basal and 24.63 fold higher at stimulated levels in group3 compared to group1. Significance: Our results advocate the antioxidant and cytoprotective effects of PLP on the pancreatic acinar cell along with increased pancreatic marker expressions of amylase,PDX-1, neurogenin-3 and insulin proteins.

Indications of the passage of time are indirect reminders of our mortality. Humans have often responded to this discomforting thought by attempting, temporally at least, to escape its relentless march through the notion of a timeless present. This essay explores how architecture can assist us in that objective. It suggests that there are at least three different ways that buildings can offer us temporary psychological refuge from the progress of time. They can include the fascination of seemingly timeless natural movement patterns. They can recall archetypal environments, and they can isolate us from the external world of perpetual temporal progress.

The clothing industry is a hotbed for exploitative working conditions and environmental damages, of which affluent global North countries remain a substantial driver. The circular economy is a potential solution to these issues, but its social implications remain unclear. Using the UK as a case study, this article analyses the global social impacts of a transition to circular clothing economies in the global North, finding these to be (almost) entirely dependent upon the intentions and design of the associated politics. Some aspects of a transition will be unambiguously good for some people; others will only be beneficial with careful governance. Moreover, entrenched global economic inequalities leave trade-offs borne largely by the global South, highlighting the need for circular economy research – its drive for localisation notwithstanding – to look globally to consider how a fair transition can be achieved.

These findings have several policy implications, emphasizing the need for enhanced data collection, climate-resilient agricultural policies, and continued investment in research. The study contributes to the understanding of climate-smart agriculture, providing insights for informed decision-making towards resilient and productive agricultural systems in the face of climate change challenges.

The relations between the kinetic energy spectrum and the second order longitudinal structure function in two dimensions are derived, and several examples are considered. The forward conversion (from spectrum to structure function) is illustrated first with idealized power law spectra, representing turbulent inertial ranges. The forward conversion is also applied to the zonal kinetic energy spectrum of Nastrom and Gage (1985) and the result agrees well with the longitudinal structure function of Lindborg (1999). The inverse conversion (from structure function to spectrum) is tested with data from 2D turbulence simulations. When applied to the theoretical structure function (derived from the forward conversion of the spectrum), the result closely resembles the original spectrum, except at the largest wavenumbers. However the inverse conversion is much less successful when applied to the structure function obtained from pairs of particles in the flow. This is because the inverse conversion favors large pair separations, which are typically noisy with particle data. Fitting the structure function to a polynomial improves the result, but not sufficiently to distinguish the correct inertial range dependencies. Furthermore the inversion of non-local spectra is largely unsuccessful. Thus it appears that focusing on structure functions with Lagrangian data is preferable to estimating spectra.

This work focuses on short-term forecasting of PV output power. The multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with good success. Their performances in forecasting PV power have been compared with other algorithms but not with themselves. The study aims to compare performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions. The performance of MLPNN, CNN and kNN are being compared using solar PV (hourly) energy yield data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in south Africa that may be prone to extreme weather conditions. The kNN algorithm was found to have RMSE value of 4.95% and MAE value of 2.74% at its worst performance, and RMSE value of 1.49% and MAE value of 0.85% at its best performance. It outperformed the others by a good margin and kNN could serve as a fast, easy, and accurate tool to forecast solar PV output power.

Cassava (Manihot esculenta Crantz), domesticated in the Amazonian region of South America, presents an important diversity in Ecuador, where it is a main staple food; however, only few Ecuadorian cassava accessions have been included in international molecular assessments. The purpose of this study was to apply suitable cassava mi-crosatellites to characterize the genetic variability of the Ecuadorian cassava collection composed mainly of local landraces from the Coast, Andes and Amazonia regions. The use of microsatellite markers allowed the determination of the genetic diversity of the collection. Seven selected SSR primers, permitted to identify homozygous and hetero-zygous materials within the cassava collection of 133 accessions. The loci presented an average genetic diversity value of 0.7 and an average PIC value of 0.67, which is con-sidered high. Low number of duplicates (8.8%) were identified in the Ecuadorian col-lection which is not fully duplicated at CIAT. Currently, a wide range of cassava diver-sity is still cultivated in multi-crop agro-ecosystem, mainly in the Coast and Amazo-nian regions. Especially in the Amazonian region, due to important cultural uses of cassava by local ethnic communities, more in depth studies in the region could unveil the genetic diversity present in situ today.

A problem of efficacy of crystal growth methods for crystallization from solution or melt has been investigated. Axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds – Ge, NaNO3, CdTe.

The ACEtabular rim eXtension (ACE-X) implant is a custom-made 3-dimensional-printed titanium device designed for the treatment of canine hip dysplasia. Thirty-four dogs (61 hips) underwent ACE-X implantation, and assessments were conducted using computed tomography, force plate analysis, Ortolani’s test, and Helsinki Chronic Pain Index (HCPI) questionnaires at five intervals: pre-operative day, surgery day, 1.5-month, 3-month, and 12-month follow-up. Statistically significant increases in femoral head coverage with negative Ortolani subluxation test were observed immediately after surgery and persisted throughout the study. Osteoarthritis (OA) scores remained stable, but osteophyte size significantly increased between the surgery day and the 12-month follow-up, especially in hips with a baseline OA score of 2 compared to those with a score of 1. Force plate data showed no significant changes during the study. The HCPI demonstrated a significant decrease in pain score from pre-operative value to 6-week follow-up and gradually decreased over time. Major complications were identified in 6 hips (9.8%) of 4 dogs. In conclusion, the ACE-X implant effectively increased femoral head coverage, eliminated subluxation, and provided long-term pain relief with minimal complications, benefiting over 90% of the study population. The study supports the ACE-X implant as a secure and valuable treatment for canine hip dysplasia.

Salvia miltiorrhiza (SM) contains the tanshinones, a compound with various pharmacological effects, and has been extensively studied as a pharmaceutical material. However, conventional methods for extracting tanshinones face challenges such as environmental hazards and high cost. In this study, we aimed to effectively extract tanshinones from SM using cloud point extraction (CPE) with lecithin, a natural surfactant. By optimizing various extraction conditions including the solid-to-liquid ratio, lecithin concentration, NaCl concentration, pH, and equilibrium temperature, the optimal extraction efficiency was achieved using 20 mL of solvent per 1 g of sample, 3% lecithin (w/v), 2% NaCl (w/v), pH 6, and room temperature (25 ± 2°C). The CPE method, which minimizes the use of organic solvent and is eco-friendly demonstrated improvements in extraction efficiency, with a 4.55% increased for dihydrotanshinone I, 8.32% for cryptotanshinone, 15.77% for tanshinone I, and 6.81% for tanshinone IIA compared to the conventional water extraction method. These results suggest that CPE is promising, environmentally friendly, and efficient approach for extracting hydrophobic components from pharmacologically active materials such as SM, with potential applications across various fields of natural product extraction.

Language barriers exacerbate health disparities among minorities. This study highlights the efficacy of simple interventions in mitigating language barriers, optimizing clinic efficiency, and enhancing preparedness for surgical procedures in Spanish-speaking (SS) females diagnosed with breast cancer in a safety net community hospital. A bilingual questionnaire was given to English and SS patients during their initial clinic visit. Additionally, a bilingual handout on surgical options and postoperative care was provided to selected surgical patients. Among the 41 patients studied, those who completed the questionnaire had an average encounter time of 27.06 minutes, compared to 45.26 minutes for those who did not. For SS patients, the average encounter time with the questionnaire was 34.07 minutes versus 46.54 minutes without it. The average cost of a medical interpreter was $17.04 with the questionnaire, versus $23.27 without. All SS patients who received the educational handout expressed greater satisfaction and understanding of their treatment plans and were less likely to require additional pre-surgery visits. This study demonstrated how the simple implementation of a translated questionnaire can reduce interpretation cost, encounter time, and improve clinic flow. Furthermore, utilizing a bilingual surgical educational handout enhances patient understanding, surgery readiness and reduces unnecessary additional visits.

Thoracic aortic and arterial aneurysms are cardiovascular conditions associated with life-threatening endpoints including dissection and rupture. The genetic basis underlying the development these disease states is an evolving field, and the reporting of variants associated with aneurysms in patients are essential for advancing screening and diagnostic tools. Among all patients in our program who underwent clinical genetic screening (N=145) for arterial aneurysm and dissection disorders, we identified three patients with single nucleotide variants in the TNXB gene. This gene has known roles in collagen fibrillogenesis and classic Ehlers Danlos Syndrome. This is one of the first reports to associate this gene with aortopathy/arteriopathy and advances the literature relating extracellular matrix genes to arterial aneurysm development.

Anthrax is a severe acute zoonotic disease of herbivores caused by Gram-positive, anaerobic, spore-forming bacteria. It is transmitted via direct contact with sick farm animals or those who have died of Anthrax. This study intends to present a cutaneous form of Anthrax in a 36-year-old woman suffered from a painless ulcer on her thumb five days after handling a head of sheep. The lesion started as a small papule that developed as a painless vesicular blister on the dorsal exterior surface of the right thumb. However, upon clinical investigation, the patient showed an absence of fever, lethargy, and pain. Swabs were collected and examined according to conventional microbiological tests. Direct smear revealed a Gram-positive bacilli that showed spore formation resembling B. anthracis. Nutrient agar, 5% sheep blood agar, and PLET agar were streaked by the swab. Other swabs were inoculated into the peptone water. All cultured media were inoculated at 37 oC for 24 hours. The morphology of growing colonies was examined, while the biochemical tests were done to identify the isolated bacteria, including a motility test and antibiotic sensitivity. The results of this study approved the existence of Bacillus anthracis by microbiological analyses. Accordingly, cutaneous form of anthrax was diagnosed, and specific systematic and local treatments were provided for the patient. In conclusion, this study confirmed the diagnosis of cutaneous Anthrax, a highly contagious disease that needed early detection and more attention and awareness should be taken when handling animal products.

β-hydroxybutyrate (BHB) is generated as one of the ketone bodies in the liver under fasted and hypoglycemic conditions. While BHB is utilized as an alternative energy substrate in extrahe-patic tissues/organs, this ketone body has been reported to exert anti-inflammatory effects via modulating inflammatory signaling cascades. Several bacterial pathogens that originated in hy-gienic litter conditions consecutively threaten chickens, and its harmful constituent, lipopoly-saccharide (LPS), induces intestinal and systemic inflammation. Therefore, the management of inflammation is a significant concern in poultry production. However, the therapeutic effects of BHB on inflammation have yet to be investigated in chickens. This study demonstrated that BHB administration can alleviate LPS-induced inflammation in broiler chickens, and the effects could be dependent on gene expression levels of ketolytic enzymes, BHB dehydrogenase-1 and suc-cinyl-CoA:3-ketoacid CoA transferase, in extrahepatic tissues/organs. This study is the first to show the therapeutic effects of BHB on LPS-induced inflammation in chickens, possibly via an involvement of BHB utilization.

Daylighting design is not only a stage of dimensioning glazed surfaces to provide sufficient natural light to an occupied space, but also a method of analysing how this matter can be achieved without unwanted effects, such as: gains and losses of heat, glare, and variations of the daylighting intensity, at various indoor distances and levels. According to the international regulations in force, glazed surfaces must be designed with a careful balance between the admission of natural light and thermal performance, such as heat loss in winter and heat gain in summer. In a novel project, it is essential to determine the optimal ratio of window-to-wall surface area. This necessity arises because the materials constituting the glazed surfaces of windows typically exhibit lower insulation properties compared to those of the building's walls. This methodology could be applied to building renovations when envelope modifications are possible and suitable. The case study presented in the paper highlights the energy consumed due to a group of windows with a large glazed area in an existing building, located in a temperate continental climate area. The energy consumption results from supplementary artificial lighting required to maintain adequate illumination for indoor activities and that to counterbalance heat loss during colder periods are evaluated. The analysis performed by modifying the glazed surface led to the identification of an optimum value of windows dimensions for an energy consumed minimum.

Lysine plays a crucial role in promoting development, enhancing immune function, and improving the function of central nervous system tissues. The two configurational isomers of amino acids have significantly different effects. Currently, methods for chiral recognition of lysine all have drawbacks such as expensive equipment and complicated detection processes, whereas fluorescence analysis boasts high sensitivity, strong selectivity, and simple operation. In this study, we synthesized four novel Binaphthyl-Amine (BINAM)-based fluorescent probes capable of specifically identifying the L-configuration of lysine among the twenty amino acids constituting human proteins. The enantiomeric fluorescence enhancement ratio (ef or ΔIL/ΔID) reached up to 15.29, demonstrating high enantioselectivity. We also evaluated the probe's recognition ability under different pH, reaction times, and metal ion conditions, as well as the Limit of Detection of the probe. Our findings indicate that this probe is a highly stable tool for detecting chiral lysine.

Gold nanostructures (AuNSs) were used to fabricate surface-enhanced Raman spectroscopy (SERS) substrates. These AuNSs were produced by the solid-state dewetting method from thin films. The fragmentation process was studied at 300 °C, considering the duration of the thermal treatment for 1, 3, 6, and 12 hours. These SERS substrates were then employed to detect Rhodamine B (RhB) as a model analyte, simulating a contaminant in water at a concentration of 5 ppm. The morphology of the AuNSs was examined using SEM, which revealed a spheroidal shape beginning to coalesce after 12 hours. The size of the AuNSs was estimated to range from 22 ± 7 to 24 ± 6 nm, depending on the annealing time. The surface plasmon resonance of the AuNSs was determined using absorption spectroscopy, showing a shift as the annealing time increased. The SERS signals of RhB adsorbed on the AuNS substrates were studied, and a comparative analysis showed no significant differences in the positions of the bands; however, variations in intensity enhancement ranged from 20 to 90 times for 6 and 3 hours, respectively. Three new vibrational modes, observed at 1683, 1720, and 1789 cm–1, have been identified and reported.

Despite their relatively low incidence globally, CNS tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes..

This report demonstrates the first-time asymmetric synthesis of enantiopure structured triacylglycerols (TAGs) of the ABC type presenting three non-identical fatty acids, two of which unsaturated. The unsaturated fatty acids included the monounsaturated oleic acid (C18:1 n-9) and the polyunsaturated linoleic acid (C18:2 n-6). This was accomplished by a six-step chemoenzymatic approach starting from (R)- and (S)-solketals. The highly regioselective immobilized Candida antarctica lipase (CAL-B) played a crucial role in the regiocontrol of the synthesis. The synthesis also benefited from the use of the p-methoxybenzyl (PMB) ether protective group that enabled incorporation of two different unsaturated fatty acids to the glycerol skeleton. The total of six such TAGs were prepared, four constituting the unsaturated fatty acids in the sn-1 and sn-2 positions with a saturated fatty acid in the remaining sn-3 position of the glycerol backbone. In the two remaining TAGs the different unsaturated fatty acids accommodated the sn-1 and sn-3 end positions with the saturated fatty acid present in the sn-2 position. Enantiopure TAGs are urgently demanded as standards for enantiospecific analysis of intact TAGs in fats and oils.

The paper presents modelling of relationships between wind velocity distributions observed in Poland and technical requirements for wind power stations design. The wind velocities distributions for various locations in Poland are determined, and expressed in Weibull distribution parameters. Theoretical computations concerning the dependence of wind power station as function of wind speed and aire physical properties are presented. Conclusions important for design of power stations fitted to atmospheric conditions in Poland are given. Wind power plants have been an important source of electricity generation for many years.Wind power modelling with the use of wind speed is used to improve the accuracy of forecasts and analyses of the power production of wind farms.

Previous studies showed that some lamellarin-resembling annelated azaheterocyclic carbaldehydes and related imino adducts, sharing the 1-phenyl-5,6-dihydropyrrolo[2,1-a]isoquinoline (1-Ph-DHPIQ) scaffold, are cytotoxic in tumor cells and may reverse multidrug resistance (MDR) mediated by P-glycoprotein (P-gp). Herein, we synthesized and evaluated for their antiproliferative activity in four tumor cell lines (RD, HCT116, HeLa, A549) and ability of inhibiting P-gp-mediated MDR some ten diversely substituted 1-Ph-DHPIQ derivatives bearing at position 2 carboxylate groups (COOH, COOEt), nitriles (CN) and Mannich bases (e.g., morpholinomethyl derivatives). Lipophilicity parametrization and molecular docking calculations improved the understanding of the structure-activity relationships in cytotoxicity and P-gp inhibition of the investigated 1-Ph-DHPIQs, which led us to disclose a novel Mannich base HCl salt (8b’), which proved to be cytotoxic to all the tested tumor cell lines in the low micromolar range (IC50 < 20 M) and to inhibit in-vitro the efflux pumps P-gp and MRP1 responsible for MDR, with IC50s of 0.45 and 12.1 M, respectively.

The Galápagos archipelago is a vast reservoir of terrestrial and marine biodiversity, owing in large part to its relatively recent volcanic genesis and colonization by humans. This unique ecological system is particularly susceptible to human, animal, and environmental impacts. Climate change, globalization, and the blurring of human-domestic animal-wildlife interfaces are poised to bring new threats and challenges to the region. A One Health perspective that simultaneously considers human, animal, and environmental health is imperative in assessing and mitigating the challenges facing the Galápagos Islands.In Part I of this review, we provide the historical context for biodiversity in the archipelago; discuss the role of invasive species in habitat destruction, fragmentation, and competition with endemic species; and summarize the established and emerging infectious disease threats. We also discuss the imperative to implement research, surveillance, and preventative measures to identify and manage future threats from a One Health perspective, with a specific emphasis on implications for wildlife health. In Part II, we outline the socioeconomic context of life in the Galápagos Islands, evaluate the current and predicted effects of climate change, and discuss direct anthropogenic factors affecting Galápagos biodiversity, such as tourism, fishing, pollution, and the illegal wildlife trade. We also examine the impact of the COVID-19 pandemic in the region. Throughout this two-part review, we build a cohesive picture of One Health in the Galápagos Islands by integrating past work, current needs, and emerging threats. We also consider overarching goals for conservation, ecosystem management, and socioeconomic sustainability that have been previously defined by both governmental and non-governmental stakeholders, and we identify discrete, implementable, and interdisciplinary recommendations that will facilitate achievement of those goals.

Most crops are fertilized with high amounts of nitrogen, and have an alarmingly low utiliza-tion efficiency. For this reason, the coordination between the fertilizer contribution and the ni-trogen requirements of the crop is very important. Therefore, the objective of this study was to determine the nitrogen use efficiency, and create new NUE indices that can determine and calculate the final destination of the assimilated nitrogen, for the formation and development of green bean plant organs, fertilized with molybdenum nanofertilizer applied foliarly and combined with soil fertilization of ammonium nitrate. The plants were grown in a greenhouse covered with anti-aphid mesh and irrigated with nutrient solution. Three sources of foliar Molybdenum (Nano fertilizer, Molybdenum Chelate and Sodium Molybdate) were applied in four doses of 0, 5, 10 and 20 ppm Mo, complemented with edaphic fertilization of NH4NO3 (0, 3, 6 and 12 mM of N). As results, the NUE indices showed that with the application of the nanofertilizer, the total biomass production increased 41.65% more than with the application of the chelate, and 36.84% more than with the application of molybdate. Finally, it is con-cluded that the use of NUE indices is an important approach that evaluates the fate of nitro-gen and accurately estimates plant yield.

In solving the Collatz conjecture, it turns out that if we let all integers k be 6n, 6n+1, 6n+2, 6n+3, 6n+4, 6n+5, then we can solve the Collatz conjecture periodically. The Collatz conjecture states that for any positive integer P (initial value), if n is even, divide n by 2; if n is odd, repeat the rule of multiplying n by 3 and adding 1, which always converges to 1. One open problem has been proved by this paper. The authors hope to contribute to the mathematical community by presenting simple proofs of conjectures in the history of mathematics such as the Collatz conjecture.

Background:Fontan completion is the last stage of univentricular repair, which drains the inferior vena cava against gravity to a higher-pressure pulmonary arterial circulation. The passivity and anti-gravity nature of this circulation render a failing Fontan, not an uncommon encounter, twenty years ago, Rodefeld and colleagues, decided to explore the feasibility of vascular pumps to support the passive nature of Fontan circulation, and since then, trials are still ongoing, and we aimed through this review to wrap up the results of these trials. Methods:A literature review has been conducted, to identify any in vivo or in vitro trial of a Fontan assist device. Several outcome parameters determined whether the trial will be included or not in this review, including, the flow rate of a pump if applicable, the number of compressions per minute if a compression device has been used, the resultant flow rate, the inferior and superior vena cava pressures, associated with each setting of the respective device, and any evidence of hemolysis or clotting within the circuit. Results:A total of ten trials have been included, with 23 different settings. Three designs have been identified, out of which two fall within the pump design, namely the connecting chamber and the intravascular pump designs; only one trial explored the possible use of a compression device. The commonest design encountered in in-vivo trials was the intravascular pump (67%). No reports of significant hemolysis or thrombosis were found. An increasing flow rate beyond 5L/min was associated with a negative outcome in the connecting chamber design, increasing upstream pressure in the SVC, while intravascular pumps did not display this limitation. Conclusion:Univentricular heart patients are a relatively small population, with very extensive needs, despite twenty years of trials, no study has yet concluded the optimal design or settings for a Fontan assist device. In this review, we identified that the intravascular pump remains the most practical design, due to its easy mode of insertion, and that it is not faced with the limitation or risk of increasing upstream resistance. There is still a long way to conclude its use as other designs such as compression devices have not yet been fully studied.

Matrix metalloproteinases have been implicated in muscular dystrophy progression and recent studies described the role of MMP-10 in skeletal muscle pathology of young dystrophic mice. Nevertheless, its implication in dystrophin deficient hearts is still missing. Here, we aimed at investigating MMP-10 implication in severe muscular dystrophic progression and characterize MMP-10 loss in skeletal and cardiac muscles of aged dystrophic mice. We examined the histopathological effect of MMP-10 ablation in aged mdx mice, both in the hind limb muscles and heart tissues. We have found that MMP-10 loss compromises survival rates of aged mdx mice, with skeletal and cardiac muscles developing a chronic inflammatory response. Our findings indicate that MMP-10 is implicated in severe muscular dystrophy progression, identifying a new area of investigation that could lead to future therapies for dystrophic muscles.

The technological revolution has contributed significantly to environmental and social issues worldwide. In higher education institutions, there is a theoretical gap in systematic reviews on the integration of digital transformation into sustainability. This systematic review of the literature aims to address this gap by exploring how digital transformation improves sustainability in higher education institutions, identifying emerging trends and best practices for effective strategies. Using the PRISMA guidelines, the study conducted a comprehensive search in the Scopus database, producing 1,686 publications from 2019 to 2024. The findings reveal a widespread awareness of digital technology integration but highlight a lack of consensus on sustainable integration strategies. Furthermore, the results demonstrate that educational achievements can be enhanced through tools and methodologies that align with the Sustainable Development Goals of the United Nations. The analysis identifies three primary domains: sustainability capabilities enabled by digital transformation, innovative sustainable approaches, and the conceptualisation of sustainability in higher education. The incorporation of digital tools, such as AI chatbots, institutions foster innovation and achieves sustainability objectives, thus transforming teaching and learning approaches. This review contributes significantly to understanding the role of digital transformation in promoting a sustainable and digitally enabled future in higher education.

Is it possible that educating women could be the key to reducing birth rates and protecting the environment? Women's education in 3rd countries is far more than just access to basic education. It is a pathway to economic growth, social stability and self-awareness. This essay reflects on the ethical challenges and benefits of educating women in areas such as interpersonal relationships, changing the traditional role of women and sustainability. In exploring this key issue, it is possible to discover that education can transform society and bring about real change, provided humanity accepts its responsibility for the state and sustainability of a quality environment for future generations.

Charge-dipole interactions are very common interactions among atoms and molecules, especially materials that can emit light or contain free charges. The second-order charge-dipole interactions, proportional to $\frac{1}{R^4}$, are stronger than the second-order dipole-dipole interactions or van der Waals interactions, proportional to $\frac{1}{R^6}$, at longer distances. In reality, there is more than one atom or charge; therefore, we focus on few-body charge-dipole interactions, such as charge-dipole-dipole interactions. Laser cooling and trapping allow us to study such interactions with much higher precision. In this article, charge-dipole interactions will be investigated in ultracold gases. To increase the interaction strength, we excite the ultracold atoms to highly excited states, Rydberg states. Here, we treat one Rydberg atom as a dipole, the excited electron and the ion core are the two poles of an electric dipole. Specifically, we study charge-atom interactions in ultracold Rydberg gases.

In this work, a method for measuring tow angles in carbon fiber components, based on the use of a polarized camera, is analyzed from a metrological point of view. Carbon fibers alter the direction of the reflected light electrical field, so that in each point of the surface of a composite piece the angle of polarization of reflected light matches the fiber orientation. A statistical analysis of the angle of linear polarization (AoLP) in each pixel of each examined area allows to evaluate the average winding angle. An evaluation of the measurement uncertainty of the method on a cylinder obtained by a filament winding process is carried out, and the result appears adequate for the study of the distribution of angles along the surface of the piece, in order to optimize the process.

Microplastics (MPs), typically defined as plastic fragments smaller than 5mm, are pervasive in terrestrial and marine ecosystems. There is a need for rapid, portable, low-cost detection systems to assess health and environmental risks. Fluorescent tagging with Nile Red (NR) has emerged as a popular detection method, but variations in fluorescent emissions based on NR solvent, plastic polymer, excitation wavelength, and additives complicate standardization. In this study, seven plastic samples stained with acetone-based NR were analyzed using a fluorescent spectrometer to identify optimal emission peaks across UV-Vis excitation wavelengths. These findings aid in selecting appropriate excitation wavelengths and optical filters for future detection systems. Additionally, a straightforward polymer identification scheme was validated against field-collected plastic samples, whose material composition was confirmed via Fourier Transform Infrared Spectroscopy. This work contributes towards developing accessible microplastic detection technologies by characterizing the fluorescent properties of NR-stained plastics and enhancing the capability for effective environmental monitoring. Future research will expand the dataset to include diverse plastics with varying additives and weathering, and incorporate computer-vision tools for automated data processing and polymer identification.

The objective of this study is to develop a predictive model for low-carbon bainitic steel utilising the P and λ parameters. The tempering activation energy of the steel was calculated through statistical methods. Kinetic curves for the hardness equivalents and a nomograph for tempering process parameters were plotted. The error analysis indicates that the predicted values based on the λ and P parameters had errors within 15% and 10%, respectively. The model can be effectively utilised to predict mechanical properties and optimise parameters during the tempering process.

Background: The goal of the study was to analyze variations in central, perifoveal, and peripheral retinal thickness (RT) and choroidal thickness (CT) in patients with diabetic macular edema (DME) measured with ultra-wide-field optical coherence tomography (UWF-OCT). Additionally, correlations between RT and CT in the central, perifoveal, and peripheral sectors and the presence of selected systemic factors were evaluated. Methods: A total of 74 consecutive adult diabetic patients with DME and 75 healthy controls were included. Study participants were divided into three groups: DME patients without panretinal photocoagulation (PRP; 84 eyes), DME patients after PRP (56 eyes), and healthy controls (125 eyes). RT and CT were analyzed in three zones: a central circle of 3 mm diameter (Central), a ring contained between a centered 9 mm circle and the central 3 mm circle (Perifoveal), and a second, more peripheral ring between centered 18 mm and 9 mm circles (Peripheral). Additionally, DME subgroups were analyzed according to the correlation of RT and CT with age, axial length, best corrected visual acuity (BCVA), diabetes duration, insulin therapy duration, body mass index (BMI), glycosylated hemoglobin (HbA1c) values, intravitreal injection (IVI) count, and the advancement of retinopathy assessed by the simplified diabetic retinopathy severity scale (DRSS). Results The increase in RT in the far peripheral sectors in DME patients was not significant. The increase in central and perifoveal RT and CT in PRP-naïve DME patients was strongly associated with poorer BCVA. Patients with DME after PRP presented with BCVA improvements significantly related to the number of IVIs. The amount of DME and RT in peripheral sectors were both independent of systemic factors such as BMI, duration of diabetes, duration of insulin intake, retinopathy severity, and HbA1c levels. Conclusion Peripheral retinal sectors in DME patients are less affected in terms of increase in their thickness compared to central ones. UWF-OCT provides valuable information on retinal and choroidal involvement in diabetic retinopathy complicated by DME.

This study investigates the environmental parameters contributing to the Urban Heat Island (UHI) effect in historically built environments, focusing on Matera's Street Canyon. The primary objective is to enhance understanding of heritage centers' ecological sustainability and management frameworks. The study involves two main phases: the initial research and development phase, including a comprehensive literature review and methodology development, followed by the empirical data gathering and analysis phase, utilizing advanced techniques such as 3D laser scanning, satellite imagery, and meteorological data integration. Key findings reveal significant correlations between urban morphology, material properties, and UHI intensity, suggesting stra-tegic urban planning interventions to mitigate UHI effects. This research provides actionable in-sights for urban planners and policymakers, emphasizing the importance of balancing heritage preservation with modern sustainability needs.

Compared to traditional multi-robot path planning problems, multi-chain robot path planning (MCRPP) is more challenging because it must account for collisions between robot units and between the bodies of a chain and the leading unit during towing. To address MCRPP more efficiently, we propose a novel algorithm called Multi-Train Safe Interval Path Planning (MT-SIPP). Based on safe interval path planning principles, we categorize conflicts in the multi-train planning process into three types: travel conflicts, waiting conflicts, and station conflicts. To handle travel conflicts, we use an improved k-robust method to ensure trains avoid collisions with other trains during movement. To resolve waiting conflicts, we apply a time correction method to ensure the safety of positions occupied by trains during waiting periods. To address station conflicts, we introduce node constraints to prevent other trains from occupying the station positions of trains that have reached their target stations and are stopped. Experimental results on three benchmark maps show that the MT-SIPP algorithm achieves about a 30% improvement in solution success rate and nearly a 50% increase in the maximum number of solvable instances compared to existing methods. These results confirm the effectiveness of MT-SIPP in addressing the challenges of MCRPP.

This research assesses the effectiveness of the Socio-Technical Assistance (STA) program combined with Owner-Driven Housing Reconstruction for rural private housing recovery after Nepal’s 2015 earthquake, particularly targeting vulnerable households. Through a quantitative 304-questionnaire survey, the study reveals that 96% of households credited STA activities for accelerating reconstruction, with 95% acknowledging its significance and 78% emphasizing its necessity. Notably,89% expressed dependency on STA for reconstruction, and 85% believed it heightened disaster risk reduction awareness. In conclusion, the study establishes that STA activities significantly contributed to the successful reconstruction of vulnerable households, addressing critical aspects such as financial support, technical assistance, housing accessibility, earthquake-resilient construction, improved livelihoods, and safety enhancements. The field study presents crucial recommendations to enhance the effectiveness of Socio-Technical Assistance (STA) activities in post-earthquake rural private housing reconstruction. Emphasizing the need for tailored, demand-driven interventions, the study cautions against relying solely on an Owner-driven Reconstruction model, challenging the one-size-fits-all strategy. The study proposes integrating tailored interventions into overarching recovery strategies, advocating for coordinated efforts to enhance Disaster Risk Reduction (DRR) awareness and cultivate resilient communities in particularly vulnerable households. Aligned with United Nations Sustainable Development Goal 11, which focuses on sustainable cities and communities. This research aims to enhance the literature on post-disaster humanitarian shelter and settlement by emphasizing the significance of inclusive and comprehensive approaches to recovery and reconstruction.

The Wnt/β-catenin signaling deregulation is associated with the pathogenesis of many human diseases, including hypertension and heart disease. The aim of the study was to immunohisto-chemically evaluate and compare the expression of Fzd8, WNT1, GSK-3ß and β-catenin genes in the hearts of rats with spontaneous hypertension (SHR) and DOCA-salt- induced hypertension. The myocardial expression Fzd8, WNT1, GSK-3ß and β-catenin was detected by immunohisto-chemistry and the gene expression was assessed with real-time PCR method. In SHR immunore-activity of Fzd8, WNT1, GSK-3β and β-catenin was attenuated in comparison to normotensive animals. In DOCA-salt immunoreactivity of Fzd8, WNT1, GSK-3β and β-catenin was enhanced. In SHR, decrease in the expression of genes encoding Fzd8, WNT1, GSK-3ß and β-catenin was observed compared to the control group. Increased expression of genes encoding Fzd8, WNT1, GSK-3ß and β-catenin was demonstrated in the hearts of rats DOCA-salt. Wnt signaling may play an essential role in the pathogenesis of arterial hypertension and the accompanying heart damage. Obtained results may constitute the basis for further research aimed at better under-standing the role of the Wnt/β-catenin pathway in the functioning of the heart.

Heart failure is associated with a significant mortality rate, and an elevated prevalence of this condition has been noted among hypertensive patients. The identification of predictive factors for heart failure progression in hypertensive individuals is crucial for early intervention and improved patient outcomes. In this study, we aimed to identify these predictive factors utilizing medical history data for hypertension patients. Specifically, we focused solely on utilizing medical data preceding the diagnosis of hypertension to enable patients to anticipate the onset of potential heart failure at the time of hypertension diagnosis. Age-specific and ICD system-specific predictive factors were identified utilizing the MIMIC-IV database through the application of two analytical approaches: chi-square tests and XGBoost modeling. Our findings reveal 21 overall predictive factors, encompassing conditions such as atrial fibrillation, the use of anticoagulants, kidney failure, obstructive pulmonary disease, and anemia. These factors were assessed through a comprehensive review of the existing literature. We anticipate that the results will offer valuable insights for the risk assessment of heart failure in hypertensive patients.

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. The article presents both the theoretical consideration of the proposed solution and its experimental verification, along with the concept of the in-plane displacement/strain sensor using the described head.

The growing impact of Artificial Intelligence (AI) on Humanity is unavoidable, and therefore, “AI literacy” is extremely important. In the field of education – AI in education (AIED) – this technology is having a huge impact on the educational community and on the education system itself. The present study seeks to assess the level of AI literacy of teachers at Portalegre Polytechnic University (PPU), aiming to identify gaps, find the main opportunities for innovation and development and seek the degree of relationship between the dimensions of AI literacy, as well as identifying the predictive variables in this matter. As a measuring instrument, a validated questionnaire based on three dimensions (AI Literacy, AI Self-Efficacy and AI Self-Management) was applied to a sample of 75 teachers in the various schools of PPU. This revealed an average level of AI literacy (3.28), highlighting that 62.4% of responses are at levels 3 and 4 (based on a Likert scale from 1 to 5). The results also demonstrate that the first dimension is highly significant for the total dimensions, i.e., for AI Literacy, and no factor characterizing the sample is a predictor, but finding a below-average result in the Learning factor indicates a pressing need to focus on developing these skills.

In recent years, online review system attracts attention to assess seller-customer relations in the world of e-commerce. To address the quality concern of online review, especially incentivized ones, this study evaluates credibility and consistency based on reviews’ volume, length, and content to distinguish the impact of incentives on customer review behavior, improving review quality, and purchase decision-making. Software product reviews collected from software review websites, including Capterra, Software Advice, and GetApp undergo Exploratory Data Analysis (EDA) to reveal critical features such as cost, support, usability, and product features. The indirect impact of companies’ size, direct impact of users’ experience, and different impacts of changing situations during years on the incentive reviews’ volume are major findings of sentiment analysis. A/B testing results show a minimal to no impact of such reviews on purchasing decisions, highlighting discrepancies in credibility and consistency in volume, length, and content. Employing advanced techniques like Sentence-BERT (SBERT) and TF-IDF, the study explores semantic differences in reviews to improve recommendation systems for a more customized shopping experience. This approach seeks to establish a framework that discerns between review types and their effect on customer behavior. The findings contribute to developing more sophisticated and consistent e-commerce solutions, emphasizing the importance of authentic and reliable online reviews in influencing consumer choices.

Background Main treatment modality for spinal meningiomas (SM) is gross total resection (GTR). However, optimal timing of surgery, especially in cases with absent or mild neurological symptoms remains unclear. The aim of this study is to assess the impact of early-stage resection on neurological outcome, quality of life (QoL) and quality of care. The primary objective was a favorable neurological outcome (McCormick scale 1); Methods: We retrospectively analyzed data from patients operated on SM between 2011 and 2021. Patients with mild neurological symptoms preoperatively (McCormick scale 1 and 2) were compared to those with more severe neurological symptoms (McCormick scale 3-5). Disabilities and QoL were assessed according to validated questionnaires (SF36, ODI, NDI). Results: Age, spinal cord edema, thoracic localization, and spinal canal occupancy ratio were associated with more severe neurological symptoms (all p<.05). Patients presented with mild symptoms were associated with favorable neurological outcome (OR: 14.778 (95%CI 3.918-55.746, p<.001), which is associated with shorter hospitalization, better QoL and less disabilities (p<.05). Quality of care was comparable in both cohorts; Conclusions: Early surgical intervention of SM, before the development of severe neurological deficits, should be considered as it is associated with a favorable neurological outcome and quality of life.