Abstract Objective: To assess wound infiltration with ropivacaine plus magnesium sulfate for pain relief following thyroid surgery. Background: Analgesia with local anesthetics following surgery is a critical element of alleviating postoperative pain. However, such strategies in neck surgery has not been a well-established practice. Methods: This prospective double-blind randomized study enrolled 68 patients who underwent thyroid surgery. Concerning the solution used for surgical wound infiltration the study participants were randomly allocated into three groups: 1) 100 mg of ropivacaine (Group R), 2) 100mg of ropivacaine plus magnesium sulfate 10mg/kg (Group RMg), and 3) normal saline which served as placebo (Group P). Pain perception both at rest and at movement, was measured using the Visual Analogue Scale (VAS) at 30 minutes, as well as 1, 2, 4, 6, 12, and 24 hours postoperatively. The total consumption of analgesics in morphine equivalents was also recorded. Moreover, adverse effects and patient satisfaction were recorded. Cortisol, TNF-α, and IL-6 levels were measured 30 minutes before infiltration, 6 hours and 24 hours postoperatively. Results: Demographics and clinical characteristics were similar between the groups. The VAS scores at rest and during movement were significantly lower in the RMg group compared to saline or ropivacaine groups. Total analgesic consumption was also significantly lower in the RMg group. No operational, wound or infiltration-related adverse effects were recorded in the study groups. Better overall satisfaction was obtained for the group RMg. Conclusions: Ropivacaine plus magnesium sulfate wound infiltration provided better pain control and analgesic effect was more significant, contributing to effective postoperative analgesia in patients undergoing thyroid surgery.

Rabies remains a significant global threat, yet accurate estimations of its impact are hindered by the lack of confirmatory diagnoses. Postmortem confirmation of rabies traditionally involves invasive brain tissue testing, a process met with resistance from deceased patients' families, impeding consent. This paper presents and evaluates an innovative yet unpublished transnasal approach for postmortem brain tissue collection, offering a minimally invasive, easier, faster, and safer method. This method preserves the cadaver's integrity, potentially easing family reluctance towards autopsies. The limited testing of both human and animal rabies in Ghana highlights the challenges in diagnosing this fatal disease. Scarce diagnostic resources and the complexity of obtaining brain tissue samples exacerbate the issue. Cultural and religious beliefs surrounding autopsies contribute to familial hesitation, viewing these procedures as disruptive and disfiguring, further complicating consent. The transnasal technique involves approaching the brain tissue through the nostrils and cribriform plate without any superficial manipulation of the patient's head and face, thereby preserving aesthetics and natural features of the person. Technological advancements and seamless One Health collaboration among governmental, non-governmental, and research entities locally and globally culminated in Ghana's first confirmed rabies diagnosis using this method of brain tissue collection. This success emphasizes the efficiency and feasibility of transnasal brain collection approach and the invaluable role of the One Health approach and collaborative efforts in overcoming diagnostic challenges in rabies control.

Metabolic syndrome (MetS) refers to the group of several interconnected risk factors that collectively double the risk of cardiovascular disease. Epilepsy is linked to MetS across all age groups, though its prevalence differs across various studies. This can be understood from the perspective of seizure-related metabolic abnormalities, long-term antiepileptic drugs (AEDs) use, and a more sedentary lifestyle due to epilepsy. The factors that are considered in developing MetS for patients with epilepsy (PWE) are age, residence, level of physical activity, food intake status, epilepsy subtype, epilepsy duration, current (AEDs) use, drug responsiveness status, body-mass index (BMI), total cholesterol and LDL-cholesterol levels. A deeper understanding of the epilepsy-AED-MetS connection and the exploration of lifestyle interventions hold the promise of significantly improving the overall health and well-being of PWE. Clinicians managing PWE should closely monitor various risk factors for developing MetS and consider them when selecting AED treatment.

This work aimed to develop an anionic cellulose nanofiber (CNF) bio-adsorbent from palm date tree waste and to investigate its removal efficiency against cationic methylene blue dye from contaminated water. Palm date pulp was first prepared from palm date leaves through acid hydrolysis using H2SO4, followed by hydrolysis in a basic medium using KOH, in which the process completely removed the components of hemicellulose, lignin, and silica. To obtain anionic CNF, the resulting pulp was further treated with H2SO4, followed by centrifugation. Biogel formation of the CNF suspension was promoted by sonication, where its removal efficiency of methylene blue dye was studied as a function of dye concentration, temperature, contact time, and pH value. Two equilibrium models, the Langmuir and Freundlich models were employed, and the Langmuir model was found to be consistent with the experimental data. The highest removal efficiency was obtained at 60oC and was 5mg/gm. Furthermore, several kinetic models were used to gain insight into the adsorption mechanism. The pseudo-second-order model provided an accurate description of the adsorption process, while the Elovich equation suggested a chemical reaction between methylene blue dye and CNF. The study’s findings were in agreement with the pseudo-second-order model, indicating general chemical reactions. The study indicates that CNF adsorbents derived from renewable natural waste sources such as palm date leaves can be effective in removing cationic contaminants such as methylene blue dye.

In this paper, a modular wire-actuated robotic arm was designed to improve the safety and adaptability of service robots during human-robot interaction. To raise the stiffness adjustment range of the robotic arm, a symmetric variable-stiffness unit was designed based on flexure, which had compact and simple structure, and lowly nonlinear stiffness-force relationship. In this paper, we focused on the research of the symmetric 1-DOF joint module. Based on the kinematics and stiffness analysis, the pose of the joint module could be adjusted by controlling the length of the wires, and the stiffness of the joint module could be adjusted by controlling the tension of the wires. Because of the actuation redundancy, the pose and stiffness of the joint module could be controlled synchronously. Furthermore, a directly method was proposed for the stiffness-oriented wire tension distribution problem of the 1-DOF joint module. A simulation was carried out to verify the proposed method.

Myelolipoma is a benign, typically inert neoplasm of uncertain aetiology that is rarely reported in cats. Although commonly asymptomatic, in some cases, myelolipomas can cause abdominal discomfort or present with rupture and haemorrhage. Here, we describe a rare case of a splenic myelolipoma in a Domestic Long Hair cat in which, after extensive diagnostic investigations, clinical signs of hyporexia and weight loss were attributable to the presence of an intra-abdominal mass. The patient was treated by splenectomy and unexpectedly died during the post-operative period. Although splenectomy appears to be a sensible intervention in symptomatic patients, the optimal management of splenic myelolipomas in cats remains unknown. The risk-benefit ratio of surgical management needs to be carefully considered, and therapeutic intervention should be tailored individually to each patient.

This study assesses the predictive performance of six machine learning models in forecasting tumor dynamics within three months following Gamma Knife Radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before and after hyperparameter tuning, utilizing accuracy, AUC and other metrics derived from confusion matrices. Initial findings highlighted that XGBoost significantly outperformed other models with an accuracy of 0.95 and an AUC of 0.95 before tuning. Post-tuning, the Support Vector Machine (SVM) demonstrated the most substantial improvement, achieving an accuracy of 0.98 and an AUC of 0.98. Conversely, XGBoost showed a decline in performance after tuning, indicating potential overfitting. The study also explores feature importance across models, noting that features like “control at one year”, “age of the patient”, and “beam on time for volume V1 treated”, were consistently influential across various models, albeit their impacts were interpreted differently depending on the model’s underlying mechanics. This comprehensive evaluation not only underscores the importance of model selection and hyperparameter tuning but also highlights the practical implications in medical diagnostic scenarios, where the accuracy of positive predictions can be crucial.

Background: Low-level physical activity (PA) among Chronic Low Back Pain (cLBP) is associated with various biopsychosocial factors. This research aimed to study the predictors of PA behavior among cLBP patients. Methods: In the present study 300 eligible patients with cLBP who referred to comprehensive health service centers in the Shahid Beheshti University of Medical Sciences (SBUMS) in Tehran, Iran were random selected.To diagnose the predictors of PA behavior, all the Theory of Reasoned Action (TRA) constructs were examined as risk factors to see if they influence on the probability of PA behavior occurrence and were interpreted through odds ratio (OR). SPSS version 19 was used to analyze the data. Results: Totally 280 cLBP patients with mean age of 57.07 ±13.09 years old participated in the study. This study showed that motivation to comply significant predictor the cLBP patients for subjective norm OR (%95CI): 2.095(0.116-2.792), p-value<0.001), intention was significant predictor for perform the PA behavior OR (%95CI): 1.431(0.138-1.538), p-value <0.001), behavior beliefs could predictor for attitude OR (%95CI): 1.276(0.106-1.355), p-value= 0.002). attitude, normative beliefs, subjective norm ,and evaluation outcome behavior could predictors the cLBP patients for intention to perform the PA behavior OR (%95CI): 1.188(0.032-1.312), p-value<0.001)., OR (%95CI): 1.158(0.076-2.208), p-value=0.003) ., OR (%95CI): 1.104(0.076-1.128), p-value<0.001) ., OR (%95CI): 0.814(0.301-1.440), p-value=0.007). Conclusions: This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm).

A novel five-surface phosphor-in-ceramic (FS-PiC) for high illumination and excellent color uniformity in larger-scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680°C to form a phosphor wafer. A sophisticated laser engraving was employed on the phosphor wafer to form a saddle-shaped large-scale FS-PiC LEDs. The performance of the FS-PiC LEDs exhibited the illumination of 401lm, average color temperature (CCT) of 5488K±110K, and color coordinates (CIE) of (0.3179±0.003, 0.3352±0.003). In contrast to convention single-surface phosphor-in-ceramic (SS-PiC) LEDs, the performance exhibited the illumination of 380lm, average CCT of 5830K±758K, and CIE of (0.3083±0.07, 0.3172±0.07). These indicated that the performance of the FS-PiC LEDs was higher than the SS-PiC LEDs for illumination, CCT, and CIE of 1.1, 7, and 23 times, respectively. Furthermore, the FS-PiC LEDs demonstrate lower lumen loss of 2% and less chromaticity shift of 5.4x10-3 under accelerated aging at 350°C for 1008 hours, owing to the high ceramic melting temperature of up to 510°C. In this study, the proposed FS-PiC larger-scale LEDs having excellent optical performance and high reliability may be the promising candidates to replace the convention phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.

Aiming at the development of the application of massive and heterogeneous LEO constellations, the influence of typical perturbation forces on the orbit prediction of LEO satellites at different altitudes is analyzed. Firstly, the main perturbation force model of LEO satellites is introduced. Then experiments for analyzing the influence of orbit prediction on LEO satellites at different altitudes are designed. Finally, the influence of typical perturbation forces on the orbit prediction under different prediction durations by numerical analysis is assessed systematically, and the orbit prediction of LEO satellites with different non-spherical gravitational field orders, ocean tide orders and atmospheric density models were compared and calculated. The research results show that different orders of non-spherical gravitational fields should be considered when the altitude of satellites is different, the reasonable gravitational field orders for LEO satellites at 500km, 1000km, 1500km and 2000km under 1-hour forecast time are 140x140, 80x80, 60x60 and 40x40 orders, the reasonable orders of ocean tide perturbation for 1500km and 2000km satellites are 20x20 orders. Under the 24-hour forecast time, atmospheric resistance has a great influence on the precision of LEO satellites at orbit altitude below 1,000km. The forecast deviation of the LEO satellites orbit at 500km reaches 8751.576m. The difference of orbit precision between different atmospheric density models is in the meter level. The orbit deviation by the Standard Atmosphere 1976 and NRLMSISE 2000 atmospheric models respectively reaches 25.494m. Relevant conclusions provide support for the optimization and selection of dynamical models in high precision orbit determination and fast orbit prediction of LEO satellites.

Patients with a psychotic disorder frequently report oral health problems, while mental health nurses (MHNs) seem not to be fully aware of these problems and the risk factors. Therefore, this study aims to develop supportive tools for MHNs regarding oral health to increase sensitization among MHNs and to provide MHNs with knowledge to recognize (potential) oral health problems in patients with a psychotic disorder. We used a human-centered design in which the user, MHNs as well as experts by experience, were placed in the centre of the research process. Problems and needs in MHNs working with patients with a psychotic disorder were addressed. To identify key issues of problem as well as the needs in terms of resources, we started with focus groups (n = 9). We analysed the data thematically based on context of patients and MHNs in practice regarding oral health, preferred oral health tools focused on MHN, and intended outcomes of tools. A Multi Criteria Decision Matrix was developed and analysed (n = 9) to identify the most optimal and viable solution based on established criteria and issues that are prevalent in the work of MHNs. Most promising result was the development of a brochure with an awareness screener. The brochure with awareness screener was developed as a low-fidelity prototype for MHNs regarding oral health in patients with a psychotic disorder, based on the latest scientific evidence. After testing it, the feasibility was tested through semi-structured interviews (n=19). MHNs and experts by experience were satisfied with the tool and provided recommendations for adjustments to the content. Significant augmentations to the brochure include a clinical lesson and a toothbrush with toothpaste for patients. We can conclude that a brochure with an awareness screener is feasible for MHNs. Future steps aiming to further refine and optimize care processes for oral health tools in MHNs, should take refining eligibility criteria for psychiatric populations and the language level of the target group of a tool into account.

The importance of frailty in older people is getting constant recognition as an important aspect both in terms of public health, as well in personal level for the appropriate management of an older person health condition. This is reflected by the continuously increasing number of research studies carried out in several settings across different countries. Sometimes this is very solid, but in other cases there is a considerable gap in terms of accurate and well grounded documentation of frailty status. This is the case in Greece, where we are missing clinically validated tools to approach frailty. We are missing frailty screening tools, such as for instance PRISMA 7, the gold standard tool of Fried criteria is somehow problematic since the question referring to physical activity originates from a questionnaire that has not been translated and validated, while Clinical Frailty Scale has been validated for the translation but not for the capacity to detect frailty. Aim of this study is to validate these tools for their accuracy to detect frailty by using a measurable index of frailty, previously proposed for use in clinical studies: the Short Physical Performance Battery (SPPB). 74 male and female participants have been evaluated for their frailty status using different tools. We observed that PRISMA 7 translation detects frailty only when one question is removed at a cut-off of ≥ 2 and indicated a sensitivity of 88.1%, and specificity of 99.9% with a good correlation with SPPB measurements (r = 0.858; p &lt; 0.001). When CFS was validated using SPPB it demonstrated a very good correlation (r = -0.838; p &lt; 0.001 respectively) as it was the case for the modified Fried Criteria (r = -0.725; p &lt; 0.001). All items demonstrated a good correlation between them. We can here propose that we can accurately assess frailty status in the community setting by using a modified version of Fried criteria, Clinical Frailty Scale translation in Greek and we can screen for frailty by using the Greek translation of PRISMA 7 only after removing the item 6 of the questionnaire.

Introduction: Anterior cervical discectomy and fusion (ACDF) for cervical disc herniation (CDH) is commonly performed. Specific postoperative complications include dysphagia, dysphonia, cervicalgia, adjacent segment disorder, cage subsidence, and infections. However, interscapular pain is commonly reported by these patients after surgery, although its mechanisms have been not clarified yet. Methods: This retrospective series of 31 patients undergoing ACDF for CDH at a single Academic Hospital. Baseline and postoperative clinical, radiological, and surgical data were analyzed. The linear regression analysis was conducted to identify any factor independently influencing the occurrence rate of postoperative interscapular pain. Results: The mean age was 57.6±10.8 years, and the M:F ratio was 2.1. The preoperative mean VAS-arm was 7.15±0.81 among the 20 patients reporting brachialgia, and the mean VAS-neck was 4.36±1.43 among those 9 patients reporting cervicalgia. At 1 month interscapular pain was still reported by 8 out of the 17 patients who experienced it postoperatively, and it was recovered in all patients after 2 months. The regression analysis showed how the interscapular pain was not directly associated to age(p=0,74), gender(p=0,46), smoking status(p=0,44), diabetes(0,42), preoperative brachialgia(p=0,21) or cervicalgia(p=0,48), symptoms duration(p=0,13), baseline VAS-arm(p=0,11), VAS-neck(p=0,93), or mJOA(p=0,63) scores, or disc height modification(p=0,90). However, the postoperative increase of the mean zygapophyseal joint rims distance was identified as an independent factor in determining interscapular pain (p=0,02). Conclusions: Our study revealed that the onset of interscapular pain following ACDF may be determined by over-distraction of the zygapophyseal joints rim. Then, proper sizing of prosthetic implants could reduce this painful complication.

Pregnancy at advanced maternal age (AMA) is a condition of potential risk for the development of maternal-fetal complications with possible repercussions even in the long-term. Here, we analyzed the changes of plasma redox balance and the effects of plasma on human umbilical cord mesenchymal cells (hUMSCs) in AMA pregnant women (patients) at various timing of pregnancy. One hundred patients and twenty pregnant women younger than 40 years (controls) were recruited, and evaluated at various timings during pregnancy until after delivery. Plasma samples were used to measure the thiobarbituric acid reactive substances (TBARS), glutathione and nitric oxide (NO). In addition, plasma was used to stimulate the hUMSCs, which were tested for cell viability, reactive oxygen species (ROS) and NO release. The obtained results showed that throughout pregnancy until after delivery in patients the levels of plasma glutathione and NO were lower than those of controls, while those of TBARS were higher. Moreover, plasma of patients reduced cell viability and NO release, and increased ROS release in hUMSCs. Our results highlighted alterations in the redox balance and the presence of potentially harmful circulating factors in plasma of patients They could have clinical relevance for the prevention of complications related to AMA pregnancy.

Background: Extracellular Vesicles are pivotal mediators in intercellular communication, facilitating the exchange of biological information among healthy, pathological and tumor cells. Between the diverse subtypes of extracellular vesicles, exosomes have unique properties, clinical and therapeutical applications, even towards cancer. Breast cancer ranks as one of the most prevalent malignancies across the globe. Both the tumor core and its surrounding microenvironment engage in a complex, orchestrated interaction that facilitates the cancer’s growth and spread. Methods: The most valuable and significant PubMed Literature about extracellular vesicles and adipose–derived stem cells exosomes was selected and analyzed in order to report their biological properties and potential applications, in particular on the Triple–Negative Breast Cancer. Results: Adipose–derived stem cells exosomes represent a potential tool to target the tumor core of the Triple–Negative Breast Cancer, its microenvironment and surrounding tissues including metastasis. The authors are developing a supportive Triple–Adipose–derived stem cells Exosomes [T.A.E.] Technology against breast cancer in order to perform a selective preconditioning of the cancer before or while the traditional oncological treatments are running. Conclusion: The possibility to exploit the impact of Adipose–derived stem cells exosomes within the T.A.E. Technology against the Triple–Negative breast cancer is real, highlighting a new era for supportive measures against breast cancer.Keywords: Extracellular vesicles; Exosomes; Adipose–derived stem cells, Tumor microenvironment, Triple–Negative Breast Cancer, T.A.E. Technology.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.

The current treatment for cervico-facial cancer involves radio and/or chemotherapy. Unfortunately, cancer therapies can lead to local and systemic complications such as mucositis, which is the most common dose-dependent complication in the oral cavity and gastrointestinal tract. Mucositis can cause a considerably reduced quality of life in cancer patients already suffering from physical and psychological exhaustion. However, melatonin, whose role in the treatment of mucositis has recently been investigated, offers an effective alternative therapy in the prevention and/or management of radio and/or chemotherapy-induced mucositis. This review focuses on the pathobiology and management of mucositis in order to improve the quality of cancer patients’ lives.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

Background: Exposure to chronic low levels of aflatoxin B1 (AFB1) contamination can lead to immune suppression and nutritional consequences that might greatly contributed in the increase of hepatocellular carcinoma (HCC). The toxicity of AFB1 is greatly vary between different population, affected by age, gender, and environmental factors. Material and subjects: Aflatoxin B1 (AFB1) was measured in 50 blood samples collected from non B, C hepatitis viruses and non CMV-Ab liver disease patients from different general hospitals and polyclinic in KSA during period 01-2013 to 06-2014. All Patients demonstrate elevation of ALT and AST with unknown etiology. Serum samples were obtained and kept at −20 °C for AFB1detection. Results: Out of the 50 blood samples, 38 demonstrate a detectable serum level of AFB1 while the remaining 12 patients were AFB1 negative and used as control participants. While AST was non-significantly different in AFB1 exposed patients, ALT was significantly higher in AFB1 positive samples compared to control AFB1-negative. AFB1 was positively correlated with AST and ALT as liver function enzymes and with age as a risk factor of long duration of AFB1 chronic exposure. Multiple linear regression analysis ascertained the association between AFB1 chronic exposure and ALT increase in liver dysfunction Saudi patients. Conclusion: Measurement of elevated ALT as marker of liver injury in AFB1 chronically exposed Saudi patients can help to avoid the future development of HCC. Moreover, early detection of AFB1 exposure, together with early vaccination against HBV and HCV can remove the synergistic effects of these two etiological factors and thus decrease the risk of developing liver cancer.

Combining modern thermodynamics theory branches, including finite time thermodynamics or entropy generation minimization, constructal theory and entransy theory, with metallurgical process engineering, this paper provides a new exploration on generalized thermodynamic optimization theory for iron and steel production processes. The theoretical core is to thermodynamically optimize performances of elemental packages, working procedure modules, functional subsystems, and whole process of iron and steel production processes with real finite-resource and/or finite-size constraints with various irreversibilities toward saving energy, decreasing consumption, reducing emission and increasing yield, and to achieve the comprehensive coordination among the material flow, energy flow and environment of the hierarchical process systems. A series of application cases of the theory are reviewed. It can provide a new angle of view for the iron and steel production processes from thermodynamics, and can also provide some guidelines for other process industries.

Background/Objectives: Periodic fever, aphthous stomatitis, pharyngitis and cervical adenitis syndrome, often referred to as PFAPA syndrome, may enigmatically recur for an undetermined time in the affected children: a potential reason to explain its recurring pattern for an unpredictable period and its self-limitation is currently unknown. We explored the relationship of PFAPA symptom evolution during a variable follow-up with PFAPA disease pictures and breastfeeding for less than 6 months during infancy. Methods: In the Outpatients Clinic of Pediatric Rheumatology of our Institution we have retrospectively screened 150 Italian children with history of PFAPA syndrome during the period 2014-2024, all without any recognized chronic diseases: 88 males, 62 females, mean age at onset of 2.5±1.7 years, age range of 0.3-9.4 years, and mean age at diagnosis of 4.5±2.0 years. Results and Conclusions: After dividing patients into two groups based on either the disappearance or persistence of PFAPA symptoms during a variable median follow-up we found that positive family history of recurring fevers, cervical lymphadenopathy, arthralgia, myalgia, and breastfeeding for less than 6 months were associated with the persistence of the disease over time. Inherited autoinflammatory disorders were excluded on a genetic basis in 16.3% of the cohort. Performing a multivariate analysis adjusted for sex and age we found that only breastfeeding for more than 6 months and a higher level of education in PFAPA patients’ mothers were independently associated with the resolution of the recurring PFAPA symptoms.

This study explored market actors’ perspectives on data sharing within Poland’s food passports pilot, which tested the feasibility of a digital system that provides reliable and comprehensive information on the origin, journey, and quality of agri-food products. Using thematic analysis, we identified factors influencing stakeholders’ willingness and motivations to share data. Our findings highlight the necessity of a clear value proposition for all actors within the production and distribution chain to invest resources and time in additional data exchange systems. For farmers, reducing burdensome reporting procedures and providing direct financial incentives were key motivators. Agri-food processing, transport and packaging companies viewed data collaboration as a practical tool to ensure high-quality raw materials and promote premium-priced food. Appropriate data management policies were critical for all stakeholders. While sustainability was recognized as important, opportunities for collaboration going beyond economic considerations were not widely explored. Additionally, concerns about data interpretation emerged as a significant issue. These findings suggest the need for data-sharing strategies that better align economic benefits with broader sustainability goals. Further research is also needed to examine how concerns about potential data misinterpretation limit stakeholders’ willingness to engage in data sharing initiatives.

This paper aims to describe and analyze a relativistic engine that uses a permanent magnet and an electrically charged device. According to Newton’s third law, every action is met with an equal and opposite reaction, meaning the total force in a system unaffected by external forces is zero. However, relativity principles state that signals cannot travel faster than the speed of light, so actions and reactions cannot occur simultaneously. As a result, the total force cannot be zero at any given moment. This implies that the system gains mechanical momentum and energy over a finite period. The question then arises about how to uphold the law of momentum and energy conservation. It has been shown that the momentum is balanced by an equal and opposite momentum in the field, while the energy gained by the engine is offset by a reduction in the field’s energy. Previous analyses assumed that the bodies involved were macroscopically neutral, meaning the number of electrons and ions was equal in every volume element. This paper relaxes that assumption and examines charged bodies interacting with magnetic currents from permanent magnetic materials, exploring the implications for a charged relativistic engine based on a permanent magnet.

Computer Vision using Deep Learning algorithms has served numerous human activity identification applications, particularly those linked to safety and security. However, despite the fact that autistic children are frequently exposed to danger as a result of their activities, many Computer Vision experts have shown little interest in their safety. High-grade autistic children frequently experience the Meltdown Crisis condition, characterized by hostile behaviors and loss of control. This study aims to introduce a monitoring system capable of predicting the Meltdown Crisis condition early and alerting the children’s parents or caregivers before entering more difficult settings. For this endeavor, the suggested system was constructed using a combination of a pre-trained Vision Transformer (ViT) model (Swin-3D-b) and a Residual Network (ResNet) architecture to extract robust features from video sequences in order to extract and learn the spatial and temporal features of the Stereotyped Motor Movements made by autistic children at the beginning of the Meltdown Crisis state, which is referred to as the Pre-Meltdown Crisis state. In order to attain a 92% recall and F1 Score, the final decisions made for data preparation, model construction, and training parameters were tweaked and established experimentally. The best loss value obtained was 0.08. The MeltdownCrisis dataset, which includes realistic scenarios of autistic children’s behaviors in the Pre-Meltdown Crisis state and Normal state the Normal state data being used as a negative class was utilized for evaluation.

This study looks at how basic research capabilities develop within enterprise clusters, focusing on the complex and adaptive nature of these systems. It builds a conceptual model using systems theory and applies information entropy to measure how much these capabilities have emerged. By using information entropy, the study creates a model to gauge how research abilities are forming in enterprise clusters. To dive deeper, the China Pingmei Shenma Group was used as a case study. Data came from interviews, surveys, and text analysis. This case—focused on a state-owned enterprise cluster in China’s coal-based energy and chemical industries—highlights the key factors that influence research capability growth. These factors include support from external systems, how internal resources are used, and their renewal over time. From 2017 to 2022, changes in entropy were tracked, revealing the process of research development driven by both internal and external forces. The study shows that when a system can bring in external resources while reducing internal disorder, its research capability is greatly improved. In real-world terms, the research proves that measuring entropy is a valuable way to evaluate and enhance research abilities within enterprise clusters, offering a clear method to manage innovation systems in tech-driven industries.

Test plants or laboratory prototypes are essential for the development of training activities in engineering. In the area of automation and control, in particular, equipment that model to a high degree those generally found in industrial processes is required, allowing engineers in training to be in permanent contact with the challenges of the context in which they work. This paper presents the design and simulation of a fly cutting plant for use in academic environments. In the design, a 3D model was built in SketchUp, considering features present in industrial plants. The simulation of the system was developed in MATLAB through a mathematical modeling of the plant. The main contribution of the work carried out was the design of a low-cost and small-dimension industrial prototype, which includes a conveyor belt and a continuous cutting mechanism through which large-scale industrial processes can be known and operated. As results, performance tests were performed in tools such as MATLAB, Simulink, and Code Composer Studio. After the operation, the operation and cutting tests were implemented using a classical control technique. Additionally, all the design features of a flying cutting plant, which can be easily implemented for the development of process control-oriented activities, are presented.

Extensive research has been conducted on the SARS-CoV-2 virus in association with various infectious diseases to understand the pathophysiology of the infection and potential co-infections. In tropical countries, exposure to local viruses may alter the course of SARS-CoV-2 infection and coinfection. Notably, only a portion of the antibodies produced against SARS-CoV-2 proteins demonstrate neutralizing properties, and the immune response following natural infection tends to be temporary. In contrast, long-lasting IgG antibodies are common after dengue virus infections. In cases where preexisting antibodies from an initial dengue virus infection bind to a different dengue serotype during a subsequent infection, there is a potential for antibody-dependent enhancement (ADE) and the formation of immune complexes associated with disease severity. Both SARS-CoV-2 and dengue infections can result in immunodeficiency. Viral proteins of both viruses interfere with the host’s IFN-I signaling. Additionally, a cytokine storm can occur after viral infection, impairing a proper response, and autoantibodies against a wide array of proteins can appear during convalescence. Most of the reported autoantibodies are typically short-lived. Vaccines against both viruses alter the immune response, affecting the course of viral infection and enhancing clearance. A comprehensive analysis of both viral infections and pathogenicity is revisited to prevent infection, severity, and mortality.

Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out Of Distribution (OOD) recognition. The term "Out of Model Scope" (OMS) detection provides a clearer perspective, although the original problem remains unsolved. The ability to detect OMS inputs is particularly beneficial in safety-critical applications such as autonomous driving or medicine. By detecting OMS situations, we not only enhance the system's robustness but also prevent it from operating in unknown and unsafe scenarios. In this paper, we introduce a novel approach for OMS detection that combines three sources of information: 1) the original input, 2) the latent feature space extracted by an encoder, and 3) the synthetic data generated from the encoder's latent feature space. We demonstrate the effectiveness of combining original images and synthetically generated images against adversary attacks in the computer vision domain. We achieve results comparable to other state-of-the-art methods and demonstrate that any Encoder can be integrated into our pipeline in a plug-and-train fashion. Our experiments further evaluate which combination of the Encoder's features works best in order to discover OMS samples and highlight the importance of a compact feature space for the training of the Generator.

In the dynamic arena of healthcare research, where the complexities of data often rival the intricacies of biological systems, the ability to model and analyze such multifaceted datasets is crucial. This comprehensive review delves into the evolution and application of Soft Sets and their extensions, including HyperSoft Sets, SuperHyperSoft Sets, IndetermSoft Sets, IndetermHyperSoft Sets, and TreeSoft Sets, in healthcare claims data analysis. These extensions address intricate challenges in data analysis, offering versatile frameworks for managing uncertainty and indeterminacy inherent in healthcare claims data. By exploring their definitions and applications, this review elucidates how these mathematical tools have evolved and their significance in advancing healthcare research and enhancing data analysis methodologies. Real-world examples underscore the implications of these tools, emphasizing their pivotal role in facilitating informed decision-making and knowledge discovery in healthcare. The review systematically examines various case studies and research findings to illustrate the practical utility of Soft Set extensions. Detailed analyses of real-world scenarios highlight advancements in processing complex healthcare data. The conclusions drawn from this analysis indicate that the adoption of Soft Sets and their extensions can significantly improve the accuracy and efficiency of healthcare data analysis, ultimately contributing to better healthcare outcomes and more informed policy-making. Future research directions are also discussed, suggesting further potential applications and developments in this field.

This paper reveals some properties of the cumulative entropy of consecutive k-out-of-n:F system's lifetime. First, we introduce a method for calculating the cumulative entropy of their lifetime and explore its preservation properties using established stochastic orders. Ad- ditionally, we obtain useful bounds that can used in situations where the distribution function of the system's component lifetimes are complicated or systems have large components. To support practical applications, we present two nonparametric estimators for the cumulative entropy of these systems. The efficiency and performance of these estimators are illustrated with simulated datasets and further validated with real data sets.

This study investigates the fatigue behavior of cold-finished mild steel subjected to electrochemical hydrogen charging under controlled conditions. Samples were hydrogenated at constant time in a fixed electrolyte pH after which they underwent fatigue testing under constant loading condition with fixed frequency. The primary objective was to assess the impact of varying hydrogen permeation levels on the number of cycles to failure. The experimental results revealed a complex relationship between hydrogen concentration and fatigue life. Initially, as hydrogen permeation increased, the number of cycles to failure substantially decreased, demonstrating a detrimental effect of diffused hydrogen on fatigue resistance of samples. This decline in fatigue life was attributed to hydrogen embrittlement (HE) and hydrogen-enhanced decohesion (HEDE) phenomena, which collectively facilitate crack initiation and propagation. However, at high hydrogen concentrations, an unexpected increase in number of cycles to failure was observed suggesting the existence of a threshold hydrogen concentration beyond which the fatigue mechanisms may be altered, potentially due to saturation of hydrogen-related defects and mechanisms such as Hydrogen Enhance Localized Plasticity (HELP). The insights gained from this research have significant implications for the material's application in hydrogen-rich environments, such as those encountered in the energy and transportation industries.

Pancreatic cancer is one of the most aggressive and lethal forms of cancer, with a five-year survival rate of less than 10%. Despite advances in treatment modalities, the prognosis for pancreatic cancer patients remains poor, highlighting the urgent need for innovative approaches for early diagnosis and targeted therapies. In recent years, there has been significant progress in understanding the molecular mechanisms underlying pancreatic cancer development and progression. This paper reviews the current knowledge of molecular targets for the diagnosis and treatment of pancreatic cancer.

In this study, the determination of static E50 and υ parameters of rock materials was investigated using P-S wave velocities and Shore hardness (SH), non-destructive measurement methods. We used multiple linear regression (MLR), multiple non-linear regression (MNLR) and artificial neural network (ANN) models to estimate and determine these parameters. When the models defined by MLR, MNLR, and ANN were compared to the R2 values, ANN models that estimate E50 and υ parameters of rock materials using non-destructive methods (Vp, Vs, Vp/Vs, d, and SH) could be determined with higher accuracy than MLR and MNLR models. The study’s originality is based on the fact that ores such as galena, chromite, and barite have been studied for the first time on rock mechanics, and in this respect, it offers an innovative perspective. In addition, the use of all non-destructive measurement methods, Vp, Vs, and Shore hardness tests, also increases the originality of the study.

Hydrogels have gained significant attention as vehicles for transdermal delivery systems. These polymeric-structured substances have been implemented in pharmaceutical and cosmetic applications. Many factors are employed in their preparation. Light, pH, temperature and specific molecules ligands are commonly used in the production of hydrogels. The Transdermal delivery system (TDD) is a widely used route, used to deliver actives/drugs via the skin. Hydrogels as a TDD have been shown to be efficient in enhancing the efficacy in delivering the actives and drugs. The aim of this review is to discuss the hydrogels application in both dermatological therapeutic and cosmetic applications, covering the types, and properties of hydrogel polymer networks. Furthermore, this review presents one of the most extensively used polymers (Hyaluronic acid HA) in this field and discusses the properties, preparation methods and applications of HA hydrogel patches as a delivery system, including methods of loading the actives and the releasing of these actives from them.

Larus michahellis increased its population throughout the 20th century in its worldwide distribution area. The increase in the Salinas de San Pedro del Pinatar has produced changes in the habitats due to the contribution of guano, predation on birds, incidents with workers, and the production of salt. The objective is to analyze the impacts of L. michahellis on the landscape, habitats, waterfowl, salt production, and workers, as well as to evaluate the effectiveness of control activities. Censuses of wintering L. michahellis have been carried out between 1990-2021, of nesting aquatic birds between 1994-2021, and nests and eggs of L. michahellis have been eliminated between 2000-2021. The result has been a decrease in pairs of L. michahellis, recovery of waterfowl populations, colonization of others, absence of incidents with workers, and reduction of damage to salt production. However, to reach a definitive solution, measures should be adopted to prevent L. michahellis from accessing the main sources of human food: urban solid waste dumps, aquaculture farms, and fish discards.

The increase in population and the challenges caused by it are always among the concerns of decision-makers and policymakers in large countries. One of the most serious concerns is in the field of energy consumption. Optimizing energy use is one of the most effective ways to manage limited resources and energy. Energy consumption in residential houses constitutes a significant percentage of the total energy consumption worldwide; therefore, current research focusing on mathematical models aims to provide a predictive multi-objective linear mathematical model for residential house consumption. For this purpose, the consumption of water, electricity, and gas for 80 residential houses, including 10 household appliances and equipment on a weekly basis, has been considered. The results showed that the mixed-integer multi-objective predictor model is able to optimize household consumption plans compared to the actual state of household energy consumption. Since the goals of household satisfaction and energy consumption costs in the model conflict with each other, the influence coefficient was calculated to demonstrate the simultaneous achievement of these goals. The optimal value achievable with the default model for the model's purposes is 69%.

Here, using the theory of electrical-quantum modelling of the neutron and proton as a three-phase alternating current electrical generator, we will analyse the proton decay and the inverse neutron decay and determine the following subatomic particles, Dproton, Protoniu, Dneutron and Neutroniumd.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

This paper presents a study to accurately evaluate defects in reinforced concrete decks using ultrasonic pulse-echo signals. Two validation specimens were designed and tested where reinforced concrete deck slab specimens included planned voids and defects. A commercial Ultrasonic Pulse-Echo (UPE) device obtains 2-D images of the void/defect locations of the reinforced concrete deck. The UPE is based on the ultrasonic shear-wave test method using dry-point-contact transmitting and receiving transducers and employing a synthetic aperture focusing technique. The authors analyzed the recorded UPE A-scan data to enhance the accuracy of estimating the defects' locations using the synthetic aperture focusing technique imaging method. The analysis benefitted from an advanced denoising approach and defect echo peak extraction based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. While output from conventional UPC devices can only provide qualitative results, the new method provides quantitative information on the anomalies inside the reinforced concrete deck. The developed approach accurately assists with assessing the location and depth of the voids/defects in the reinforced concrete deck slabs.

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.

A hallmark of Alzheimer’s disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ soluble protofibrils was approved by US FDA for AD therapy thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms are widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7- Aβ) and the α4β2 nicotinic acetylcholine receptor.

The practice of teaching and scientific research on cadaveric material remains crucial for medical education, especially in surgical disciplines. However, in Italy, this practice has been neglected due to legislative insufficiency and financial constraints. Although innovative methods and tools like simulators and e-learning have been adopted, direct hands-on experience with human cadavers remains irreplaceable for medical and surgical education. The absence of clear legislation governing cadaveric dissection has limited availability for teaching and research, resulting in economic burdens for universities and individuals seeking proper surgical training. To address this issue, the Law No. 10/2020 and the recent implementing decree were introduced in Italy, providing detailed legislation on the donation of bodies for educational and research purposes. The law emphasizes the importance of respecting the donor's specific choices and aligns with constitutional principles promoting culture, research, and health protection. However, some critical issues related to consent procedures, duration of body availability, and preservation of anatomical parts remain. Additionally, the law's dissemination among the population needs improvement. Future optimization could include allowing donors to choose the timing of body donation and considering different timeframes for body availability. Furthermore, the implementation of consent procedures could be simplified to increase donations. The law should also address the need for appropriate reception centers and allocate resources for effective dissemination. Despite these challenges, Law No. 10/2020 represents a significant step forward in enhancing medical-surgical training, scientific research, and the overall quality of patient care in Italy.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

Viruses can induce the fusion of infected and neighboring cells, leading to the formation of syncytia. Cell-cell fusion is mediated by viral fusion proteins on the plasma membrane of infected cells that interact with cellular receptors on neighboring cells. Viruses use this mechanism to spread rapidly to adjacent cells or escape host immunity. For some viruses, syncytium formation is a hallmark of infection and a known pathogenicity factor. For others, the role of syncytium formation in viral dissemination and pathogenicity remains poorly understood. Human cytomegalovirus (HCMV) is an important cause of morbidity and mortality in transplant patients and the leading cause of congenital infections. Clinical HCMV isolates have broad cell tropism but differ in their ability to induce cell-cell fusions, and little is known about the molecular determinants. We developed a system to analyze HCMV glycoprotein B (gB) variants in a defined genetic background. HCMV strains TB40/E and TR were used as vectors to compare the fusogenicity of six gB variants from congenitally infected fetuses with those from three laboratory strains. Five of them conferred the ability to induce fusion of MRC-5 human embryonic lung fibroblasts to one or both backbone strains, as determined by a split GFP-luciferase reporter system. The same gB variants were not sufficient to induce syncytia in infected ARPE-19 epithelial cells, suggesting that additional factors are involved. The system described here allows a systematic comparison of the fusogenicity of viral envelope glycoproteins and may help to clarify whether fusion-promoting variants are associated with increased pathogenicity.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Leishmaniasis is the third most common vector-borne disease and a very important protozoan infection. Cutaneous leishmaniasis is one of the most common types of leishmaniasis infectious diseases with up to 2 million occurrences of new cases each year worldwide. A dynamic transmission multivariate time series model was applied to the data to account for overdispersion and evaluate the effects of three environmental layers as well as seasonality in the data. Furthermore, ecological niche modeling was used to investigate the geographical suitable conditions for cutaneous leishmaniasis using temperature, precipitation and altitude as environmental layers, together with the leishmaniasis presence data. A retrospective analysis of the cutaneous leishmaniasis spatial data in Afghanistan between 2003 and 2009 indicates a steady increase from 2003 to 2007, a small decrease in 2008, then another increase in 2009. An upward trend and regularly repeating patterns of highs and lows was observed related to the months of the year which suggests seasonality effect in the data. Two peaks were observed in the disease occurrence-- January to March and September to December -- which coincide with the cold period. Ecological niche modelling indicates that precipitation has the greatest contribution to the potential distribution of leishmaniasis.

Mediterranean diet, featuring sourdough bread, shows promise in managing metabolic syndrome. This study explored the effects of two sourdough breads with differing fermentation times but similar nutritional profiles on inflammation, satiety, and gut microbiota composition in adults with metabolic syndrome. The double-blind clinical trial randomized participants to consume over two-months Elias Boulanger® long fermentation (48h) sourdough bread (EBLong) or Elias Boulanger® short fermentation (2h) sourdough bread (EBShort). We assessed clinical parameters, inflammatory- and satiety-related biomarkers; and richness and abundance of gut microbiota at baseline and follow-up. 31 individuals (mean age: 67, 55.7% female) participated. EBShort was associated with reduced soluble intercellular adhesion molecule (sICAM) levels, and irrespective of the adjudicated intervention, all participants had a decrease in sICAM and diastolic pressure relative to baseline (p&lt;0.017). At follow-up, plasminogen activator inhibitor-1 (PAI-1) levels were lower in EBShort (-744 pg/mL; 95%CI: -282 to -1210 pg/mL) compared to EBLong. High-quality sourdough bread may offer mild benefits in blood pressure and inflammation for those with metabolic syndrome, however, only EBLong was associated to reduced Enterobacteriaceae abundance. Further research is needed to understand potential benefits and mechanisms of sourdough bread in managing metabolic syndrome and improving cardiovascular health.

Background and Objectives: The purpose of the study was to analyze the relationships between several clinical and biological factors, but also the tumor topography and surgical strategies used in patients with colorectal cancer. Materials and Methods: We designed an analytical, observational, retrospective study that included patients admitted to our emergency surgical department and diagnosed with colorectal cancer. The study group inclusion criteria were: patients admitted during 2020-2022; patients diagnosed with colorectal cancer (including the ileocecal valve); patients who benefited from a surgical procedure, either in emergency or elective. Results: In our study group, consisting of 153 patients, we accounted for 56.9% male patients and 43.1% female patients. The most common clinical manifestations were pain (73.2% of the study group), followed by abdominal distension (69.3% of the study group) and absence of intestinal transit (38.6% of the study group). A number of 69 patients were operated in emergency (45.1%), while 84 patients (54.9%) benefited from elective surgery. The most frequent topography of the tumor was the sigmoid colon, with 19.60% of the patients, followed by the colorectal junction, with 15.68% of the patients and superior rectum and inferior rectum, with 11.11% of the patients in each subcategory. The most frequent type of procedure was right hemicolectomy (21.6% of the study group), followed by rectosigmoid resection (20.9% of the study group). The surgical procedure was finished by performing an anastomosis in 49% of the patients, an ostomy in 43.1% of the patients, while for 7.8% of the patients, a tumoral biopsy was performed. Conclusions: Colorectal cancer remains one of the most frequent cancers in the world, with a heavy burden that involves high mortality, alterations in the quality of life of the patients and their families, and also the financial costs of the medical systems.

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

Protecting sensitive data, such as data collected from sensors, is crucial for ensuring the accurate assessment of sensing devices and preventing unauthorized access. In this regard, Internet of Things (IoT) devices offer a promising alternative for in-situ monitoring. However, IoT sensing devices are often constrained by limited processing power and memory. Therefore, lightweight and efficient security algorithms are essential. This review paper assesses the implementation of lightweight cryptographic algorithms for power-constrained microcontrollers in IoT systems using symmetric cryptography. The implemented algorithms analyze the resource constraints of the IoT devices and compare their performance for efficient implementation of secure monitoring systems. Experimental results demonstrate the performance of various lightweight encryption algorithms on low-power microcontrollers. The analysis reveals the comparative performance of these algorithms in terms of average power and energy consumption, memory usage, latency, and throughput.

The application of deep learning convolutional neural networks (CNNs) for rock image characterization has become a prominent method in petroleum geology both nationally and internationally. Precise and automated segmentation of rock sheet images is essential for effective analytical studies. This research addresses the limitations of traditional image segmentation methods, which suffer from low accuracy and high costs in analyzing reservoir rock flakes. We propose an advanced model based on the U-Net architecture, incorporating both attention mechanisms and residual networks. The inclusion of residual modules enhances the network's depth, while the Convolutional Block Attention Module (CBAM) improves feature representation by adjusting the weighting of learned information. Extensive experimental results demonstrate that this approach delivers superior segmentation performance, marking a significant advancement in the field of reservoir rock image analysis.

We show that analyzing archived and future multibeam backscatter and bathymetry data, in tandem with regional environmental parameters, can help identify polymetallic nodule fields in the world’s oceans. Extensive archived multibeam transit data through remote areas of the world’s oceans are available for data mining. New multibeam data will be made available through the Seabed 2030 Project. Uniformity of along and across track backscatter, backscatter intensity, angular response, water depth, nearby ground-truth data, and local slope, sedimentation rate, and seafloor age provide thresholds for discriminating areas permissive for nodule presence. A case study of this methodology is presented using archived multibeam data from a remote section of the South Pacific along the Foundation Seamounts between the Selkirk paleomicroplate and East Pacific Rise that were collected in 1997 during the Hotline cruise. The 12 kHz Simrad EM12 DUAL multibeam and the forementioned data strongly suggest a previously unknown nodule occurrence exists. Methods include comparing analyses using three different backscatter products to further determine if scanned backscatter products, rather than primary digital multibeam files can be used for analysis, and comparing results from using digitized 8-bit images, or 8-bit and decibel-value surfaces derived from the MB-SystemTM software. We show this expeditious analysis of broad areas of multibeam data could characterize benthic habitat types efficiently in remote deep ocean areas prior to more time consuming and expensive video and sample acquisition surveys. Additionally, utilizing software other than specialty sonar processing programs during this research explores how multibeam data products could be interrogated by a broader range of scientists and data users. Future mapping, video, and sampling cruises in this area would test our prediction and investigate how far it might extend to the north and south.

As global food demand continues to grow, enhancing rice seed setting rate and yield has emerged as a crucial research topic. The stigma exsertion rate in rice, a pivotal determinant of the outcrossing seed setting rate in sterility lines, is essential for facilitating the propagation and efficient seed production of hybrid rice varieties. This article reviews the research progress on stigma exertion rate in rice, systematically analyzing the latest molecular biology and genetics findings to uncover the key genes and molecular mechanisms regulating stigma exertion. Furthermore, it explores the application of molecular marker-assisted selection technology in rice breeding, aiming to optimize stigma exertion traits to enhance the stigma exertion rate and outcrossing habit of rice sterility lines. By integrating existing research outcomes, this article not only provides researchers with a theoretical foundation for a deeper understanding of the regulatory mechanisms of stigma exertion but also offers practical strategies for rice breeding practices.

This study aimed to determine the correlation between inter-limb asymmetries and physical per-formance metrics in adolescent female tennis players. Methods: Twenty-five female tennis players (age: 13.29 ± 0.98 years; weight: 52.52 ± 7.31 kg; height: 162.91 ± 6.02 cm) consented to participate in the study. Performance was evaluated using various variables, including bilateral and unilat-eral countermovement jump (CMJ), bilateral and unilateral horizontal jump (HJ), 180º change of direction (180COD) conducted with both the right and left legs, and a 20-m sprint. The systematic bias was evaluated by one-way repeated measures analysis of variance, Pearson’s correlation test for relationships between variables, and the kappa coefficient for consistency in the asymmetry direction. Results Significant relationships were found between CMJ Asymmetry and the varia-bles HJR (r=-0.47) and HJL (r=-0.44). In addition, significant relationships were found between HJ Asymmetry and the variables CMJR (r=-0.60) and CMJL (r=-0.54), HJR (r=-0.64), HJL (r=-0.67), CMJ (r=-0.55) and HJ (r=-0.52). Conclusion Jumping tests are important indicators of performance loss in female tennis players. In addition, no significant correlation was found be-tween the 180COD and performance tests, suggesting that asymmetries in COD do not affect jump performance or speed. Based on these results, it is recommended to integrate individualized pro-grams for each athlete to reduce asymmetries.

Adventitious root (AR) formation in plants origins from non-root organs such as leaves and hy-pocotyls. Auxin signaling is essential for AR formation, but the role of other phytohormones is less clear. In Arabidopsis, at least two distinct mechanisms can produce ARs either from hypocotyls as part of the general root architecture, or from wounded organs during de novo root regeneration (DNRR). In previous reports, gibberellin acid (GA) seems to play reverse roles in both types of AR formation, since GA treatment blocks AR formation from hypocotyls, whereas depletion of GA signaling results in reduced DNRR from detached leaves. Here, we report the positive effects of GA biosynthesis inhibitor paclobutrazol (PBZ/PAC) treatment on both types of AR formation in Arabidopsis. Consistently, loss of GA synthesis and signaling promoted DNRR in our conditions. Furthermore, PBZ treatment can rescue declined AR formation from leaf explants in erecta recep-tor mutants. Transcriptional profiling revealed that PBZ treatment altered GA, brassinosteroids and auxin responses, which included up-regulation of LBD16 that plays a pivotal role in AR initi-ation. This study reveals that depletion of GA biosynthesis promotes DNRR in Arabidopsis, and thus will contribute to further clarification of the role of GA during AR formation in plants.

Background: Cardiovascular comparisons between glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and Sodium-glucose co-transporter-2 (SGLT-2) inhibitors in type 2 diabetes(T2D) remain an area of interest. Thus, the purpose of this meta-analysis is to compare the impact of these two drug classes on major CV outcomes, such as heart failure hospitalization(HHF), major adverse cardiovascular events (MACE), CV mortality, myocardial infarction, stroke, and all-cause mortality, with an emphasis on heart failure hospitalizations. Methods: PubMed (including MEDLINE), Google Scholar, Cochrane Central Library, PLOSONE, and Science Direct databases were searched for studies that compared GLP-1 RAs and SGLT-2 inhibitors in patients with type 2 diabetes. Six cohort studies were selected for the analysis. Odds ratios (OR) with 95% CI were calculated and a random-effects model was used to estimate the hazard ratios (HR) of the studies. The quality of the studies was evaluated using the Newcastle-Ottawa Scale (NOS), and publication bias was assessed using funnel plots and Egger’s test. Results: Pooled analysis demonstrated a significant reduction in heart failure hospitalizations with SGLT-2 inhibitors compared to GLP-1 RAs (HR: 0.78 [0.62–0.98], I² = 87%, p < 0.01). Cardiovascular mortality was also significantly reduced by SGLT-2 inhibitors (HR: 0.74 [0.31–1.67], I² = 87%, p < 0.01), and a modest reduction was observed for all-cause mortality (HR: 0.85 [0.44–1.64], I² = 17%, p = 0.27). While SGLT-2 inhibitors appeared to slightly reduce the risk of myocardial infarction (HR: 0.83 [0.74–0.92], I² = 0%, p = 0.85), no significant difference was observed for MACE (HR: 0.91 [0.82–1.01], I² = 0%, p = 0.70) or stroke (HR: 0.88 [0.77–1.00], I² = 0%, p = 0.85). Conclusions: Compared to GLP-1 receptor agonists, SGLT-2 inhibitors were more effective in lowering heart failure hospitalizations and cardiovascular mortality in patients with type 2 diabetes. It was also found that all-cause mortality and myocardial infarction were moderately reduced using oral agents. However, the differences were not significant for MACE or stroke. These results imply that SGLT-2 inhibitors may potentially provide better cardiovascular benefits, especially with respect to heart failure and cardiovascular mortality, than GLP-1 RA. Further research should be conducted to determine the effects of the long-term use of these therapies on stroke and other cardiovascular events.

Background: Avaram Amrit, derived from a traditional medicinal plant, has shown potential in diabetes management. This study aimed to evaluate its clinical efficacy in glycemic control. Methods: A 12-week, open-label clinical trial was conducted with 9 type 2 diabetes patients. Participants received Avaram Amrit extract daily. Fasting and postprandial glucose levels were measured bi-weekly, with HbA1c assessed at baseline and week 12. Results: Fasting glucose levels decreased significantly from 252.54 ± 71.99 mg/dL at baseline to 195.50 ± 55.01 mg/dL at week 12 (p<0.001), representing a 22.6% reduction. Mean HbA1c decreased by 1.25 percentage points. Postprandial glucose levels showed consistent improvement across the study period. A strong positive correlation was observed between initial HbA1c and fasting glucose (r=0.89). Conclusion: Avaram Amrit demonstrated significant improvement in glycemic control over 12 weeks. The consistent decrease in both short-term (glucose levels) and long-term (HbA1c) measures indicates a positive response to the intervention. While promising, larger randomized controlled trials are necessary to confirm these findings and establish Avaram Amrit's role in diabetes management.

Modern organizations have migrated from localized physical offices to work-from-home environments. This surge in remote work culture has exponentially increased the demand and usage of Virtual Private Network (VPN), which permits remote employees to access corporate offices effectively. However, the technology raise concerns including security threats, latency, throughput, and scalability, among others. These Newer generation threats are more complex and frequent, which makes the legacy approach to security ineffective. The research paper gives an overview of contemporary technologies used across enterprises including VPN and Zero Trust Network Access (ZTNA), Proxy Servers, Secure Shell (SSH) Tunnels, Software-defined wide area network (SD-WAN), and Secure Access Service Edge (SASE). This paper also presents a comprehensive cybersecurity framework named Zero Trust VPN (ZTVPN), which is a VPN solution based on Zero Trust principles. The proposed framework is aimed to enhance IT security and privacy for modern enterprises in remote work environments and addresses concerns of latency, throughput, scalability, and security. Finally, the paper demonstrates the effectiveness of the proposed framework in various enterprise scenarios, highlighting its ability to prevent data leaks, manage access permissions, and provide seamless security transitions. The findings underscore the importance of adopting ZTVPN to fortify cybersecurity frameworks, offering an effective protection tool against contemporary cyber threats. This research serves as a valuable reference for organizations aiming to enhance their security posture in an increasingly hostile threat landscape.

Water scarcity presents one of the greatest challenges of our time. Especially in naturally water scarce regions, the need of additional water resources is rising, requiring innovative and site-adapted technologies. In this review, selected non-conventional water technologies for sustainable water management are strategically evaluated. Focused on a matrix-based assessment incorporating key indicators, the study discusses the availability, applicability, environmental impact, scalability, and economic viability of the selected technologies. Based on a comprehensive literature review, the methodology involves a systematic comparison of technologies for desalination, water reuse, groundwater utilization, agricultural reuse, and unconventional approaches like cloud seeding, dew water, and fog water harvesting. The indicators covering the respective categories are presented in the results. On this basis, the different technologies are analyzed by matrix-based evaluation, highlighting various strengths and weaknesses and providing insights into technology selection based on regional needs. The discussion interprets the findings, deriving implications for dry environments, acknowledging limitations and suggesting pathways for future research. Through a rigorous analytical framework, this study contributes to the discourse on sustainable water solutions, offering valuable insights for policymakers, researchers and industries during a decision-making progress.

This study presents a systematic review to evaluate the effectiveness of virtual patients in enhancing clinical reasoning skills in medical education, utilizing a hybrid methodology that combines human reviewers and ChatGPT. By analyzing various studies involving conversational virtual patients, the review examines the impact of these digital tools on student learning outcomes and satisfaction. Consistent with previous systematic reviews, our findings suggest that conversational virtual patients can improve clinical competencies, particularly in history-taking and clinical reasoning. Regarding student feedback, satisfaction tends to be higher when virtual patients’ interactions are more realistic, often due to the use of artificial intelligence (AI) and natural language processing (NLP) in the simulators. Furthermore, the study compares the accuracy of AI-driven reviews with human assessments, revealing comparable results. This research highlights AI’s potential to complement human expertise in academic evaluations, contributing to more efficient and consistent systematic reviews in rapidly evolving educational fields.

The COVID-19 pandemic has highlighted the critical need for telehealth and remote patient monitoring in healthcare delivery. Despite the growing use of on-body wearable sensors for continuous monitoring and predicting adverse events, such as hospitalizations or falls, their widespread adoption within the healthcare ecosystem remains a significant challenge. While the pandemic has accelerated the acceptance of these technologies, achieving widespread integration requires their sustained incorporation into routine healthcare practices beyond emergency situations. In this study, we extend the application of our previously developed remote patient monitoring system, originally designed for the geriatric frail population, to COVID-19 patients. Our objective is to assess whether the metrics obtained from this system, which includes physical activity and indoor localization sensors, along with vital sign monitoring, can provide additional insights into the recovery trajectory of individuals affected by COVID-19.

Human papillomavirus (HPV) is the most sexually transmitted infection associated with the development of cervical cancer. This study investigated cervical HPV prevalence, characteristics and distribution according to age and human immunodeficiency virus (HIV) among women attending public community health facility in the Eastern Cape Province of South Africa. A total of 325 participants (aged 18 to 60) visiting a community health facility for any reason were recruited. Cervical HPV infection was detected using the Seegene Anyplex™ II HPV28 assay. Overall HPV prevalence was 65.2% (95% CI: 59.9–70.2%), with the highest prevalence of 80.9% (95% CI: 67.2–89.8%) observed in the 18–25 years age group and lowest prevalence of 46.3% (95% CI: 35.8–57.1%) in 46–60 years of age. HR-HPV infection was found to decrease with increasing age among women who were HPV infected by any type (p=0.02), but not when stratified according to HIV status. A proportion of 12.9% (42/325) were infected with one or more HPV types covered by the Cervarix® HPV vaccine (HPV-16 and/or -18), 18.8% (61/325) by those covered by Gardasil®4 (HPV-6, -11, -16 and/or -18) and 42.2% (137/325) by those covered by Gardasil®9 (HPV-6, -11, -16, -18, -31, -33, -45, -52 and/or -58). Alpha-9 HPV species were the most dominant species (40.6%, 132/325), followed by alpha-7 species (29.8%, 97/325). In the overall population, alpha-9 HPV species were always part of the most dominant HPV alpha species co-infection, which were alpha-9 and -7 species (17.5%, 57/325), alpha-9 and -5 species (9.8%, 32/325), and alpha-9 and -6 species (9.5%, 31/325). High overall HPV, HR-HPV, and alpha-9 species prevalence were observed among women attending the public health facility. These findings contribute to the limited HPV distribution data among Eastern Cape women, which could be used to improve HPV-related policy and assess the effectiveness of the HPV vaccination.

The large-scale introduction of renewable energy, replacing fossil fuels, is presented as an essential part of the energy transition; this substitution is being observed in electrical systems, but it will also be necessary to introduce them in other sectors, such as transportation, either by incorporating renewable energy sources in the sector's facilities, including automotive service centers, or by electrifying transportation technology. The introduction of electromobility in a country is associated with a group of technologies that are required to make this introduction feasible. In Cuba, the introduction of electric vehicles, electric charging stations and charging points, including residential charging points, could increase the current demand by about 330 MW, based on the prospects for the introduction of electrification in the country's transportation system. Taking all of the above as a point of reference, this article addresses the basic elements of an energy transition proposal in the transportation sector, arriving at a proposed Roadmap to achieve the required synergy between energy transition and electromobility.

Artificial intelligence has garnered significant attention in recent years as a rapidly advancing field of computer technology. With the continual advancement of computer hardware, deep learning has made breakthrough developments within the realm of artificial intelligence. Over the past few years, applying deep learning architecture in medicine and Industrial anomaly inspection has significantly contributed to solving numerous challenges related to efficiency and accuracy. Despite excellent results in radiological, pathological, endoscopic, ultrasonic, and biochemical examinations, this paper utilizes deep learning combined with image processing to identify spinal canal and vertebral foramen dimensions. In existing research, technologies such as corrosion and expansion in magnetic resonance image (MRI) processing have also strengthening the accuracy of results. Indicators such as area and Intersection over Union (IoU)are also provided for assessment. Among them, the mean average precision (mAP), for identifying intervertebral foramen (IVF) and intervertebral disc (IVD) through YOLOv4 is 95.6%. Resnet50 mixing U-Net was employed to identify the spinal canal and intervertebral foramen and achieved IoU scores of 79.11% and 80.89%.

In this paper, we consider the synchronization of chaotic oscillators interconnected via a second order dynamic coupling. The design of the proposed coupling is inspired in the ancient synchronization experiment of synchronized pendulum clocks, as described by the Dutch scientist Christiaan Huygens more than three centuries ago. It is demonstrated that the coupled chaotic systems may exhibit not only complete synchronization, but also mixed synchronization—some states synchronize in anti-phase whereas other states synchronize in-phase. In fact, a transition from complete synchronization to mixed synchronization or viceversa can be induced by just changing a single parameter in the coupling. Additionally, the stability of the synchronous solution is investigated by using the Master Stability Function approach and the largest transverse Lyapunov exponent. The Lorenz system is considered as particular application example. Finally, the performance of the proposed synchronization scheme is illustrated with computer simulations and validated by means of experiments using electronic circuits.

In two laboratory trials natural products, including freshly-picked leaves from spearmint, rosemary, and tansy plants; a water extract from soybean plants; peels from a common cucumber; and 1% peppermint oil in hexane were placed in a moist harborage preferred by Argentine ants, Linepithema humile, and the number of ants entering the harborage after two and four hours was counted. None of the recommended home remedies (tansy, cucumber, or soybean extract) deterred ants from an attractive, moist harborage in either trial even when the quantity of these treatments was increased 4- to 10-fold. Freshly picked leaves from rosemary and spearmint plants deterred ants from harboring, and the 1% peppermint oil was the most deterrent of all treatments.

The Akosombo Nile tilapia is the only approved local strain for aquaculture production in Ghana. In this study, an exotic red tilapia sample suspected to be cultured in a fish farm within the Lower Volta River Basin of the Lake Volta was collected for species identification. A molecular screening using DNA barcoding sequencing was performed on the samples targeting the cytochrome C oxidase subunit 1 mitochondrial gene (COX1). We confirmed the identity of the red tilapia fish to be a non-native Oreochromis sp. recently introduced into the country. The data obtained clearly demonstrates a breach of biosecurity that potentially threatens Ghana’s native tilapia genetic resources and aquaculture development.

Abstract: Conventional antibiotic and multidrug treatments become less and less effective and a discovery of new effective and safe antibacterial agents got a global priority. The returning to the natural antibacterial product is relatively new current trend. Terrestrial biota is a rich source of biologically active substances whose antibacterial potential was not fully utilized. Aim of this review is to present the current state-of-the art of terrestrial biota-derived antibacterial agents and inspired by nature treatments. It is a summary of the most important sources and new identified or modified antibacterial agents and treatments during the last 5 years. It focuses on the significance of plants- animals- and bacteria-derived biologically active agents as powerful alternatives to antibiotics as well as on the advantages of utilizing natural antibacterial molecules alone or in combinations with antibiotics. The main conclusion is that the terrestrial biota derived antibacterial products and substances open variety of new ways to modern improved therapeutic strategies. New terrestrial sources of known antibacterial agents and new antibacterial agents from terrestrial biota were discovered during the last 5 years, which are under investigation together with some long ago known but now surviving their renaissance for the development of new medical treatments. Use of natural antibacterial peptides as well as combinational therapy by commercial antibiotics and natural products outlines as the most promising for treating of bacterial infections. In vivo testing and clinical trials are necessary to reach clinical application.

The advancements in social networking have empowered open expression on micro blogging platforms like Twitter. Traditional Twitter Sentiment Analysis (TSA) faced challenges due to rule-based or dictionary algorithms, dealing with feature selection, ambiguity, sparse data, and language variations. This study proposed a classification framework for Twitter sentiment data using word count vectorization and machine learning techniques to reduce the difficulties addressed on annotated sentiment-labelled tweets. Various classifiers (Naive Bayes, Decision Tree, K Nearest Neighbours, Logistic Regression, and Random Forest) were evaluated based on Accuracy, Precision, Recall, F1-score, and Specificity. Random Forest outperformed others with an Area under Curve (AUC) value of 0.96, and an Average Precision (AP) score of 0.96 in sentiment classification, especially effective with minimal Twitter-specific features.

Recent studies have shown the potential of Transformer-based neural networks in increasing prediction capacity. However, classical transformers present several problems such as computational time complexity and high memory requirements, which make Long Sequence Time-Series Forecasting (LSTF) challenging. The contribution to the prediction of time series of flood events using deep learning techniques is examined, with a particular focus on evaluating the performance of the Informer model (a particular implementation of transformer architecture), which attempts to address the previous issues. This study explores the predictive capabilities of the Informer model compared to statistical methods, stochastic models and traditional deep neural networks. The accuracy, efficiency as well as the limits of the approaches are demonstrated via numerical benchmarks relating to real river streamflow applications. Using daily flow data from the River Test in England as the main case study, we conduct a rigorous evaluation of the Informer efficacy in capturing the complex temporal dependencies inherent in flood time series. Among other things, the present work extends its analysis to encompass diverse time series datasets from various locations (>100) in the United Kingdom, providing insights into the generalizability of the Informer. The results highlight the significant superiority of the Informer model over established forecasting methods, especially regarding the LSTF problem. Furthermore, it is observed that the structure of time series, as expressed by climacogram, affects the performance of the Informer network.

Climate disruption has serious impact on the entire agricultural production system at global scale. Research and development efforts as well as innovations may be necessary to offset the negative impact of climate change. Adaptation to climate change has remained a major socio-ecological issue in the Northern Region of Cameroon for three decades. Several agricultural innovations have been promoted in this region by international organizations and NGO, within the framework of different projects and programs, with a strong potential for adaptation to climate change. However, little is still known about agricultural innovations that have evolved over time in response to climatic factors. Therefore, research aiming at identifying adaptation strategies and practices at the local level is still limited. Also, rural communities and households do not always have access to these agricultural innovations because of lack of efficient innovation support service for agriculture. Through surveys and focus group discussions carried out in several villages in the Northern Cameroon Region, this study provides empirical data on emerging agricultural innovations in contrasting socio-economic, agricultural and ecological contexts. The study demonstrated that the process of adaptation at the village level using agricultural innovations is the result of various forms of support provided by a diversity of actors. However, heads of household (83%) are more involved in innovative initiatives to the detriment of other social strata, resulting in an imbalance in access and proximity to agricultural innovations. Also, support for agricultural innovations is segmented over time and weakens the sustainable transformation of adaptation due to the lack of coordination and the very low visibility of permanent structures dedicated to supporting agricultural innovations.

The study of localized surface plasmons (LSPs) in nanoscale structures is an essential step towards identifying optimal plasmonic modes that can facilitate robust optomechanical coupling and deepen our understanding of light-matter interactions at the nanoscale. This paper investigates numerically, using the finite element method, LSPs modes in a design comprising two coupled nano-ridges deposited on a gold layer, with an interposing polymer spacer layer. Such a structure, usually referred to as particles-on-mirror, shows exquisite optical properties at the nanoscale. We first examine the LSPs modes of a single nano-ridge through the analysis of its scattering cross-section in the visible and infrared range. To enhance the plasmonic response, a thin polymer layer is placed at the middle of the ridge, which introduces additional LSPs modes confined within the former. Then, we extend the analysis to the dimer configuration, which exhibits more complex and enhanced plasmonic behavior compared to a single nano-ridge. In particular, the dimer configuration yields LSPs resonances with a quality factor enhancement of approximately threefold relative to single nano-ridge. Furthermore, the presence of the polymer layer within the ridges significantly improves plasmon field localization and quality factor. These findings underscore the potential of nano-ridge-based structures in advancing optomechanical coupling and plasmon-phonon interaction studies, offering valuable insights for the development of high-performance acousto-plasmonic devices. In particular, the proposed device could help significantly improve the design of nano-acousto-optic modulators operating in the visible or in the near infrared, that require enhanced light-photon coupling rate.

There is currently no effective treatment strategy for the recurrent/metastatic adenoid cystic carcinoma (R/M ACC). Furthermore, recent single-agent and combination immunotherapy trials have failed in unselected ACC cohorts unlike non-ACC salivary gland cancers. Genomic profiling revealed no actionable targets but NOTCH1 and KDM6A frameshift and CTCF splice site mutations (no MYB/L fusion) with a low TMB, MSS and negative PD-L1. We recommended anti-PD-1 plus anti-CTLA-4 combination based on TMB 2-fold greater than median TMB in ACC, tumor harboring multiple immunogenic frameshift or splice site mutations, and PD-L1 negativity. Accordingly, we achieved a complete response in a radiotherapy and chemotherapy-refractory patient with locally recurrent lacrimal gland ACC and lung metastasis following personalized immunotherapy in combination with integrative therapeutics. Therefore, it is crucial to assess not only conventional immune biomarkers but also patient-specific parameters.

Lessons learned and risk-based outcomes from modernising the Australian Standard for post-mortem inspection and disposition judgement of beef, sheep, goat and pig carcases are described. Initial Risk Profiles identified priorities for quantitative assessments. The main difficulty encountered was the paucity of quantified performance of current inspection. Resolving this involved acquiring gross abnormality data representing regional production/proportional abattoir volumes, the range of gross abnormalities appearing nationally, proportional occurrence at carcase sites, and seasonality to enable comparisons. Evidence and discussion are provided for associated challenges experienced including preventing contamination, use of food chain information to support amendment, inspection as a part of industry Quality Assurance and opportunities to improve inspector training. Criteria considered by the Competent Authority for determination of equivalence of alternative post-mortem inspection techniques included comparisons of public health risk, non-detection rates for gross abnormalities, and microbial contamination resulting from inspection activities, as appropriate. Most gross abnormalities detected arose from animal health and welfare conditions affecting wholesomeness and did not present as food safety hazards. Non-detection rates between current and alternative inspection (observation) were negligible. A Quantitative Risk Assessment for Cysticercus bovis was conducted. Carcases with multiple gross abnormalities predominantly reflected historic infections (prior septicaemia) where trimming achieved wholesomeness unless cachexic.

The purpose of this research is to understand the relationship between green business ethics, green finance, and sustainable business performance, and to evaluate the role of corporate social responsibility (CSR) in this relationship. The impact of the damage inflicted on nature's functioning order is being felt much more strongly today. In light of these realities, companies are required to place greater emphasis on sustainability principles not just out of financial concerns but as a result of corporate social responsibility. In this context, focusing on the role of corporate social responsibility in sustainable business performance is the main goal of this research. Quantitative research methods, specifically the cross-sectional survey method, were employed for data collection and analysis. For this purpose, a convenience sampling method was used to select 427 white-collar employees working in industries operating in Türkiye as the sample for this study. The data collected through surveys were analyzed using the AMOS 24 statistical program. The findings underscore that green business ethics and green finance have a significant impact on corporate social responsibility and sustainable business performance. Additionally, it was determined that corporate social responsibility plays an intermediary role in shaping sustainable business performance. These findings are expected to provide an important foundation that can guide both employees and managers in developing awareness about green policies and sustainability, emphasizing the importance of green policies in the working life.

Fractional cointegration in time series data has been explored by several authors, but panel data applications have been largely neglected. A previous study of ours discovered that the Chen and Hurvich fractional cointegration test for time series was fairly robust to a moderate degree of heterogeneity across sections, out of the six tests considered. Therefore, this paper advances a customized version of the Chen and Hurvich methodology to detect cointegrating connections in panels with unobserved fixed effects. Specifically, we develop a test statistic that accommodates variation in the long-term cointegrating vectors and fractional cointegration parameters across observational units. The behaviour of our proposed test is examined through extensive Monte Carlo experiments under various data generating processes and circumstances. The findings reveal that our modified test performs quite well comparatively and can successfully identify fractional cointegrating relationships in panels even in the presence of idiosyncratic disturbances unique to each cross-sectional unit. Furthermore, the proposed modified test procedure established the presence of long-run equilibrium between the exchange rate and labour wage of 36 countries agricultural markets.

Fluoride (iF) is important inorganic pollutant in groundwater in central México. The aim of this study was estimated environmental risk exposure of iF in residents of Jerez Zacatecas México. Fifty-five tap water samples were collected from households to determine iF concentrations using the ion-selective electrode method. Based on these environmental values, the Hazard Quotient (HQ) was estimated following the methodology of the Pan American Health Organization (PAHO). Subsequently, risk maps were generated from these values to visualize the spatial distribution of high-risk areas within the city. iF in tap water ranger in concentration from 1.3 – 7.3 mg/L (ppm). We estimated HQ in a range of 0.63 to 3.73. iF ex-posure in tap water is a health problem that must be addressed, carrying out risk communication actions that allow the population to take care of their health through simple actions, avoiding future health costs.

Camouflage is a natural or artificially process to prevent an object from being detected while camouflage breaking is a countering process for the identification of the concealed object. We report that a perfectly camouflaged object in a two-dimensional scene can be retrieved and detected with stereo-vision assisted three-dimensional (3D) imaging perceived with stereopsis. The analysis is based on binocular energy model applied to general 3D settings. We show that a perfectly concealed object with random noise background can be retrieved with vision’s stereoacuity to resolve the hidden structures. The theoretical analysis is further tested and demonstrated with distant natural images taken by a drone-camera, processed with a computer and displayed in an autostereoscopy. The recovered imaging is presented with removal of the background interference to demonstrate the general applicability for camouflage breaking with stereo imaging and sensing.

Preeclampsia is a complex pregnancy-related hypertensive disorder which poses significant risks for both maternal and fetal health. Preeclampsia affects 5-8% of the pregnancies in the United States, causing a significant public health and economic burden. Despite extensive research, the etiology and pathogenesis of preeclampsia remain elusive, but have been correlated with maternal conditions such as obesity. In the past decades, the incidence of preeclampsia increased along with the prevalence of obesity among women of reproductive age. Maternal obesity has been shown to negatively affect pregnancy in almost all aspects. However, the precise mechanisms by which obesity influences preeclampsia are unclear. Ankyrin repeat and SOCS Box Containing protein 4 (ASB4) is an E3 ubiquitin ligase that can promote the degradation of a wide range of target proteins. ASB4-null mice display a full spectrum of preeclampsia-like phenotypes during pregnancy including hypertension, proteinuria, and decreased litter size. Furthermore, maternal obesity induced by a high fat diet aggravates preeclampsia-like phenotypes in pregnant mice lacking ASB4. Variants in the ASB4 gene have been associated with obesity in humans, and a functional connection between the ASB4 gene and obesity has been established in mice. This review discusses the connections between preeclampsia, obesity, and ASB4.

This study addresses the critical need for standardizing Building Information Modeling (BIM) Execution Plans (BEPs) in the Architecture, Engineering, Construction, and Operations (AECO) sector. By analyzing 36 BEP documents from international organizations, we identify key elements and propose a comprehensive framework aimed at enhancing digital transformation and collaboration in complex construction projects. This research employs scientometric analysis to map the evolution of BEP standards and integrates empirical data from industry surveys to validate the proposed framework. Our findings highlight the benefits of standardized BEPs in reducing inefficiencies and improving project outcomes, thereby providing a significant contribution to the field of BIM implementation.

Market crises pose significant challenges for businesses, emphasizing the importance of effective crisis management strategies. Central to these strategies is the ability to identify and retain loyal customers, who often serve as the bedrock of stability during tumultuous times. This paper investigates the application of deep meta-learning analysis to predict loyal customers as a cornerstone of market crisis management. Drawing upon an extensive literature review, the study explores previous research on market crises, customer loyalty, and the evolution of deep learning and meta-learning in crisis management contexts. Methodologically, the paper outlines data collection, model development, and evaluation procedures tailored for deep meta-learning-based customer prediction. In results, the overall accuracy of model 85%, a precision 0.88, recall 0.82, and F1-score 0.85 were obtained. The analysis demonstrates the effectiveness of deep meta-learning models in accurately identifying loyal customers during market crises, offering insights into their performance and applicability compared to traditional methods. Practical implications include potential applications in crisis management for businesses and considerations for real-world implementation.

Due to the optical properties of the Electron Transport Layer (ETL) and Hole Transport Layer (HTL), inverted perovskite solar cells can perform better than traditional perovskite solar cells. It is essential to compare both types to understand their efficiencies. In this article, we studied inverted perovskite solar cells with NiOx/CH3NH3Pb3/ETL (ETL = MoO3, TiO2, ZnO) structures. Our results showed that the optimal thickness of NiOx is 80 nm for all structures. The optimal perovskite thickness is 600 nm for solar cells with ZnO and MoO3, and 800 nm for those with TiO2. For the ETLs, the best thicknesses are 100 nm for ZnO, 80 nm for MoO3, and 60 nm for TiO2. We found that the efficiencies of inverted perovskite solar cells with ZnO, MoO3, and TiO2 as ETLs, and with optimal layer thicknesses, are 30.16%, 18.69%, and 35.21%, respectively. These efficiencies are 1.5%, 5.7%, and 1.5% higher than those of traditional perovskite solar cells. Our study highlights the potential of optimizing layer thicknesses in inverted perovskite solar cells to achieve higher efficiencies than traditional structures.

Oral candidiasis is a common problem among immunocompetent patients. The frequent resistance of Candida strains to popular antimycotics makes it necessary to look for alternative methods of treatment. The authors conducted a systematic review following the PRISMA 2020 guidelines. The objective of this review was to determine whether curcumin-mediated aPDT and blue light could be considered as an alternative treatment for oral candidiasis. PubMed, Google Scholar and Cochrane Library databases were searched using a combination of the following keywords: (Candida OR candidiasis oral OR candidosis oral OR denture stomatitis) AND (curcumin OR photodynamic therapy OR aPDT OR photodynamic antimicrobial chemotherapy OR PACT OR photodynamic inactivation OR PDI). The review included in vitro laboratory studies with Candida spp., in vivo animal studies, and randomized control trials (RCTs) involving patients with oral candidiasis or prosthetic stomatitis, published only in English. The method of elimination of Candida species in the studies was curcumin-mediated aPDT. 757 studies were identified. Following the analysis of the titles and abstracts of the studies, only 42 studies were selected for in-depth screening, after which 26 were included in this study. All studies evaluated the antifungal efficacy of curcumin-mediated aPDT against C. albicans and non-albicans Candida. In studies conducted with planktonic cells solutions, seven studies demonstrated complete elimination of Candida spp. cells. The remaining studies demonstrated only partial elimination. In all cases, experiments on single-species yeast biofilms demonstrated partial, statistically significant inhibition of cell growth and reduction of biofilm mass. In vivo, curcumin-mediated aPDT has shown good antifungal activity against oral candidiasis also in an animal model. However, its clinical efficacy as a potent therapeutic strategy for oral candidiasis requires further RCTs.

Internships can foster educational alliances between industry (business environment) and academic institutions, which can facilitate both flexibility and accelerated innovation. The purpose of this research is to search for the factors that determine HRD through the implementation of the Internship program among the students of Democritus University of Thrace and reveal the correlation between the factors. Also, this paper investigated the impact of the COVID-19 Eras on Human Resource Development (HRD) Factors and finally, investigated the correlation between the two variables "Recruitment in the specialization" and "Covid Eras". The sample of the research consisted of 1398 students of DUTh who implemented Internships during the academic years 2015-2016 to 2021-2022. A questionnaire with 60 variables was created for data collection. A random sampling method was applied to collect the sample. From the results of the survey, ten factors were extracted for human resource training that explained 75.512% of the total variance and for each one, Cronbach's Alpha reliability was tested, which was high. In detail, the factors revealed were Learning Outcomes, Efficacy, Emotional Commitment, Satisfaction, Participation, Empowerment, Role Ambiguity, Role Conflict, Supervisor and Collaboration. From the results of the study, it was evident that HR development - training is a multi-dimensional concept and is a necessary condition for the competitiveness of the firms. Training can help to improve the flexibility of the firm, but also to motivate the staff by implementing multidisciplinary training programs. In general, internship programs are valuable ways for students to acquire broad competences, where the practical knowledge gained supports and complements the theoretical studies acquired in educational institutions.

Solid polymer electrolytes and composite polymer electrolytes serve as crucial components in all-solid-state energy storage devices. Structural batteries and supercapacitors present a promising alternative for electric vehicles, integrating structural functionality with energy storage capability. However, despite their potential, these applications are hampered by various challenges, particularly in the realm of developing new solid polymer electrolytes that require more investigations. In this study, novel solid polymer electrolytes and composite polymer electrolytes were synthesized using epoxy resin blends, ionic liquid, lithium salt, and alumina nanoparticles, and subsequently characterized. Among the formulations tested, the optimal system, designated as L70P30ILE40Li1MAl2 and containing 40 wt.% of ionic liquid and 5.7 wt.% of lithium salt, exhibited exceptional mechanical properties. It displayed a remarkable storage modulus of 1.2 GPa and reached ionic conductivities of 0.085 mS/cm at 60°C. Furthermore, a proof-of-concept supercapacitor was fabricated, demonstrating the practical application of the developed electrolyte system.

In this study, the team employed full-scale crash tests to investigate the impact of post-densification technology on the safety performance of separated central median W-beam barriers under low compaction conditions. By precisely simulating the design and construction environment of the central median, the study comprehensively evaluated the barrier's containment, redirection, buffering, and anti-intrusion performances, as well as the deformation of both the barrier and vehicles under various collision scenarios. The results indicate that under low compaction soil conditions, the A-level separated central median barriers reinforced with post-densification technology effectively meet the specified protection requirements. By comparing the influence of soil strength variations on barrier performance under simulated rainfall conditions, it was confirmed that enhancing soil compaction significantly improves soil stability, effectively increases the overall strength and stability of the barriers, reduces deformation, and significantly enhances safety performance. This study not only validates the effectiveness of the reinforcement scheme but also provides new perspectives for the scientific research of safety barriers and offers crucial technical support for the optimal design of road safety protection facilities.

Robotic-assisted hip and knee arthroplasty represents significant advancements in orthopedic surgery. Artificial intelligence (AI) - driven chatbots, such ChatGP, plays a significant role in healthcare education. This study aims to evaluate the quality of responses provided by ChatGPT to the top 20 questions concerning robotic-assisted hip and knee arthroplasty.We have asked ChatGPT to select the top 20 questions on Google concerning robotic hip and knee arthroplasty and to provide a detailed answer to each of them. The accuracy of the information provided were examined by three orthopedic surgeons with scientific and clinical experience in hip and knee replacement surgery. The accuracy was assessed through a 5-point Likert scale (from 1 – completely incorrect to 5 – correct); the completeness through a 4-point Likert scale (from 0 – comprehensiveness not assessable for completely incorrect answers to 3 – exhaustive information) on two different occasions to ensure the consistency of the assessment. Our analysis reveals that ChatGPT provides a relatively high degree of accuracy, moreover the explanations can be considered satisfy, especially for factual questions. The findings suggest that ChatGPT can serve as a valuable initial resource for general information on robotic hip and knee arthroplasty but the integration with human expertise remains essential.

The COVID-19 pandemics has had an unprecedented global impact, and the COVID-19 mass vaccination campaign has been commonly regarded as crucial to overcome the pandemics. Since all-cause mortality is the best way to measure the consequences of a health intervention, the present study was devised to analyze the all-cause mortality data of the United Kingdom (UK), which are made publicly available broken down by vaccination status. Data from April 2021 to May 2023 were retrospectively collected and analyzed according to age groups and vaccination status and the Standardized Mortality Ratio (SMR) for all-cause mortality and for non-COVID-19 were calculated in comparison to the corresponding unvaccinated groups. Results show that, since an age group dependent date, the all-cause mortality SMRs were increasing in any of the age groups considered. Initially, the all-causes death SMRs were less than 1 for all age groups, but due to their growth, for the age groups 18-39, 80-89 and 90+ years by a certain date they exceeded the reference value. For the other age groups, as long as the trend is maintained, it is possible to predict the date in which the SMR would reach the value 1. Non-COVID-19 SMR values show a very similar trend. Their initial values much lower than 1 suggest the presence of significant biases in the ONS dataset which lead to an underestimation of the risks for those vaccinated, as it is not plausible that the vaccine protects from causes other than COVID-19. The finding that all-cause mortality SMRs in vaccinated in comparison to unvaccinated people increases over time requires careful examination to understand the underlying factors. Meanwhile, the other major countries should undertake a systematic collection of all-causes mortality broken down by vaccination status, and should be implemented a moratorium of the promotion of mass vaccination campaigns.

Considerable amounts of agro-industrial by-products are discarded or burnt as fuel every year. However, they can be utilized as a valuable source of fiber, phenolics and other useful compounds such as antioxidants. The profile of beneficial compounds can be affected by genotype, locality, orchard management and productive season, adding or decreasing the bioactive potential of by-products. In this study, hazelnut (Corylus avellana L.) and walnut (Juglans regia L.) nutshells were investigated for their fiber content and antioxidant capacity as valorized by-products for the industry. Determinations (ORAC, TPC and color asses) were performed in hazelnut and walnut orchards located in Southern Chile during three consecutive seasons (2020/21; 2021/22 and 2022/23). Analyses of oxygen radical absorbance capacity (ORAC) in nutshells showed the highest ORAC from both species in the season 2020/21 (3217 µmol TE g1DW for hazelnut shells and 4663 µmol TE g DW1 for walnut shells), while variability in the consecutive seasons was lower for hazelnut than in walnut. Total phenolic content in hazelnut shells was positively correlated with L* (R: 0.883) and E (R: 0.924) during 2020/21 season, also with L* for 2022/23 (R: 0.907). While ORAC was negatively correlated with L* (R: 0.922) in 2021/22. In addition, morphological and structural features of both nutshells examined by Scavenging Electron Microscopy (VP-SEM) and Confocal Scavenging Laser Microscopy (CSLM) revealed differential tissue distribution and accumulation patterns of both cellulose and lignin. On the other hand, photo-colorimetric values were determined for both shells and corresponding seasons, and non-significative differences were found both shells and among seasons Finally, these results provide insight into the physicochemical characteristics of two shell types which should be considered together with antioxidant capacity in their valorization as a residual material.

This study introduces a robust methodology utilizing Multi-Criteria Decision Analysis (MCDA) combined with the Analytic Hierarchy Process (AHP) to repurpose abandoned hydrocarbon fields for energy storage, supporting the transition to renewable energy sources. We use a geostatistical approach integrated with Python scripting to analyze reservoir parameters—including porosity, permeability, thickness, lithology, temperature, heat capacity, and thermal conductivity—from a decommissioned hydrocarbon field in Southeast Hungary. Our workflow leverages stochastic simulation data to identify potential zones for energy storage, categorizing them into high, moderate, and low suitability scenarios. This innovative approach provides rapid and precise analysis, enabling effective decision-making for energy storage implementation in depleted fields.

NSCLC is a very aggressive solid tumor, with a poor prognosis due to post-surgical recurrence. Analysis of the specific tumor and immune signatures of NSCLC samples is a critical step in prognostic evaluation and management decisions for patients after surgery. Routine histological assay has some limitations. Therefore, new diagnostic tools with the capability to quickly recognize NSCLC subtypes and correctly identify various markers are needed. We developed a technique for ex vivo expansion of cancer and immune cells from surgical tumor and lung tissue samples of patients with NSCLC (adenocarcinomas and squamous cell carcinomas) and their examination on ex vivo cell preparations and, parallelly, on histological sections after Romanovsky–Giemsa and immunofluorescent/immunochemical staining for cancer-specific and immune-related markers. As a result, PD-L1 expression was detected for some patients only by ex vivo analysis. Immune cell profiling in the tumor microenvironment revealed significant differences in the immunological landscapes between the patients’ tumors, with smokers’ macrophages with simultaneous expression of pro- and anti-inflammatory cytokines, neutrophils, and eosinophils being the dominant populations. The proposed ex vivo analysis may be used as an additional diagnostic tool for quick examining cancer and immune cells in whole tumor samples and avoiding false negatives in histological assays.

The healthcare sector has undergone a profound transformation, owing to the influential role played by IoMT (Internet of Medical Things) technology. However, there are substantial concerns over these devices' security and privacy-preserving nature. Current literature on IoMT tends to focus on specific security features like data confidentiality or data integrity or data availability or access control and most solutions are simulated and not tested in a real-world live network. This paper proposes a smart secure by design solution that safeguards user’s data during health and wellbeing monitoring of patients locally (home, care-home, and hospital) and remotely. The proposed innovative solution is known as Secure by Design Real Time IoMT Architecture for e-Health Population Monitoring (RTPM) for smart hospitals and any healthcare monitoring management. In this system, keys can also be generated by the patient monitoring system independent to maintain high privacy standard and trust during the monitoring process and to enable the IoMT devices run independently even if the server is compromised and are made safe from external exploits to the client nodes. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices overheads and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system: confidentiality, integrity, availability, conducts authentication, protect from DoS attacks and prevent from non-repudiation attack of patient medical data and the devices in a real time, sensory data communication environment for live e-health monitoring. A secure communication is tested by capturing the live network traffic and the system’s performance analysis of RTPM using different security algorithms with different key sizes of RSA, AES, and SHA shows that resource constraint low powered system can also successfully integrate with high-end state-of-the-art secure parameters and features and have the potential to support real time secure interaction. A stress test is also conducted to ensure that the system can withstand huge key sizes and different data types including multi-media information.

A number of chemical modifications were carried out in order to synthesize new compounds based on the triterpenoid betulonic acid. Triazolation reactions were carried out for the synthesis of new 1,2,3-triazole derivatives based on betulonic acid. Chemical changes were made on the carbonyl group at the C-3 position of the initial molecule and on the carboxyl and hydroxyl groups at the C-28 position. Chromatographic methods were used to separate and purify the formed products. Spectroscopic (NMR-, mass-) methods were used to establish the structure of synthesized compounds. As a result of the chemical transformations carried out, a number of new derivatives of betulonic acid were obtained. All synthesized compounds were tested for antimicrobial and cytotoxic activity. As a result, compounds with pronounced antimicrobial activity were identified.

Total hip arthroplasty (THA) is a preferred treatment for primary osteoarthritis (OA) or secondary due to developmental hip dysplasia (DDH). Gait analysis is considered a golden standard for evaluating post-arthroplasty walking patterns. This study compared post-THA spatiotemporal gait parameters (SGPs) between OA and DDH patients and explored correlations with demographic and clinical variables. Thirty patients (15 per group) were recorded during gait, and their SGPs were analyzed. Functionality was evaluated with the Oxford Hip Score (OHS). The OA patients were significantly older than DDH (pr< 0.51, all p< 0.05). The preoperative gait alterations associated with OA or DDH were improved to similar levels in both groups after THA. Post-arthroplasty SGPs and OHS correlations indicate limitations in certain activities. These find-ings must be correlated with kinetic gait analysis data to fully evaluate gait and functionality dif-ferences among patient groups.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley Value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley Value are impractical as they necessitate additional model training, leading to increased communication overhead. Moreover, participants’ data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data weakens the marginal effects of participants, which in turn affects model accuracy and leads to underestimated contribution measurements. Current works often overlook the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a noval aggregation weight, it enhances the accuracy of contribution measurement. Experiments on the MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

Background: Snus consumption is increasingly popular, mainly among the youth, due to the promotion of the tobacco industry and the lack of knowledge regarding its adverse effects. Even though some of its systemic complications are common knowledge, the oral consequences are rarely known. Aim: Therefore, the objective of this study is to evaluate the oral health effects of snus consumption among a highly exposed group of adolescent athletes. Design: Participants received an interactive presentation, followed by interviews and dental screenings by young doctors to establish trust. They were categorized into groups based on the frequency of snus usage. The oral hygiene habits and status, snus consumption habits and awareness about its adverse effects were evaluated. Results: Statistically significantly (p

Mississippi youth are demographically unique compared to that of the nation. The purpose of this study was to determine the trend of drug use among adolescents of the United States and Mississippi, and to estimate the differences of drug use prevalence as a whole, and by gender and by race. National and Mississippi YRBSS data from 2001 to 2021 were obtained for analysis. Summary statistics, prevalence ratio, and survey Chi-squared tests of independence statistics were generated for the comparison for all students, and by gender and race separately. Trend analysis was conducted using logistic regression combined with joinpoint regression. Six survey questions being studied were: have you ever used marijuana, inhalant, heroin, methamphetamines, injected drugs, and were you offered, sold, or given an illegal drug on school property during the last 12 months. Survey packages in R were used to account for the complex sampling design of YRBSS data. On the national level, all six drug related risk behaviors being studied showed significant decrease from 2001 to 2021. In Mississippi however, only “ever used marijuana” showed a trend of decrease, while three remain unchanged, and two increased. 2021 YRBSS data shows that Mississippi adolescents exhibited significantly higher prevalence of drug use, and are more likely to be offered, sold or given an illegal drug on school property. Our study suggests an urgent need for drug use intervention among Mississippi adolescents. More concerted actions at the community, school and government level are needed for reducing youth drug use and controlling the drug traffic on school property.

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.