With many Americans eager to resume travel after prolonged restrictions from the coronavirus pandemic, car rentals are on the rise. According to Auto Rental News, “2021 U.S. Car Rental Revenue Climbs 21% Year-Over-Year” (Brown, 2021). In conjunction with increased car rental, and associated travel, we can expect to see an increase in cyber security and data privacy attacks. In the digital age, enterprises have a responsibility to protect consumers’ personally identifiable information (PII). As it pertains to rental vehicles, when consumers connect their mobile devices to a rental vehicle’s Entertainment and Infotainment System or utilize the built-in navigation feature, they do so, unbeknownst to themselves that the information from their devices is transferring to the vehicle, where it will remain, unless properly expunged from the system. A large majority of consumers are blissfully unaware that their PII is being stored, and how easy it would be for an adversary to potentially breach their data security and privacy. To expand upon this hypothesis, I conducted a further investigation on the subject, by partaking in the rental of three different vehicles, each belonging to a different manufacturer (Nissan, Chrysler, and Maserati), from three different vehicle rental companies (Enterprise, Hertz and Turo). I then, as a consumer, tested my hypothesis to determine if, I was able to easily breach the prior consumers’ data security and privacy by viewing devices that had previously connected to the vehicle, as well as any of the previous consumers’ personal information. The results were undeniable; the PII of the previous consumers is not protected.

Background/Objectives: Energy availability (EA) is essential for maintaining physiological func-tions, significantly influencing athletes' health and performance. Nutritional behaviours, how-ever, vary across sports. This study aims to assess EA levels in athletes from different disciplines, focusing on the relationship between EA and body composition in endurance athletes compared to rugby players. Methods: The study involved 18 endurance athletes (15 men, 3 women) and 36 rugby players (all men). Data were gathered through interviews, questionnaires, and bioim-pedance analysis. Energy intake (EI) was measured with a 24-hour dietary recall, and exercise energy expenditure (EEE) was calculated using the IPAQ questionnaire. EA was calculated as EA = (EI - EEE) / fat-free mass (FFM), with results categorized into clinical, subclinical, and optimal ranges. Results: The endurance group had a lower average FFM (57.81 kg) compared to the rugby players (67.61 kg). EA was also significantly lower in endurance athletes (11.72 kcal/kg FFM) than in rugby players (35.44 kcal/kg FFM). Endurance athletes showed more restrictive nutritional behaviour with lower EI and higher EEE, but both groups maintained body composition within normal ranges. Conclusions: Endurance athletes exhibit greater nutritional restrictions compared to rugby players, though their body composition remains healthy. Further research is required to investigate the long-term effects of low EA on performance, injury risk, and potential impairment when EA falls below the optimal threshold of 45 kcal/kg FFM/day.

Background: Extensive-stage SCLC (ES-SCLC) treatment has recently been revolutionized by the advent of immune checkpoint inhibitors. This survey was conducted to evaluate the current pattern of care among Italian clinicians, in particular about the integration with radiation therapy (RT). Methods: In June 2023, 225 Italian cancer care professionals were invited to 21-question web-based survey about the ES-SCLC management through personal contacts and the Italian Association for Radiotherapy and Clinical Oncology (AIRO) network. Results: We received 90 responses, the majority were radiation oncologists (89%) with more than 10 years of experience (51%). Preferred management of ES-SCLC in patients with a good performance status was concomitant chemo-immunotherapy (84%). Almost all respondents recommended prophylactic cranial irradiation (PCI) (85%), taking into account age and thoracic response; PCI was performed mainly between the end of chemotherapy before starting immunotherapy (37%), with three-dimensional conformal technique (46%). Furthermore, 83% of respondents choose to deliver thoracic RT in case of both intrathoracic and extrathoracic response with a RT schedule of 30 Gy/10 fractions. Stereotactic RT is increasingly being used in oligoprogressions. Conclusions: Our analysis showed the variability of real-world management of ES-SCLC. Future clinical trials and developments are needed to improve the multidisciplinary treatment of these patients.

Thoracostomy and chest tube placement are key procedures in treating various pleural diseases involving the accumulation of fluids (e.g. malignant effusions, serous, pus, or blood) or air (pneumothorax) in the pleural cavity. Initially described by Hippocrates and refined through the centuries, chest drainage obtained historical milestones with the creation in the 19th century of closed drainage systems with methods to prevent the entry of air into the pleural space and to reduce infection risk. The introduction of plastic materials and the Heimlich valve further revolutionized chest tube design and function. Technological advancements led to the availability of various chest tube designs (straight, angled, pig-tail) and drainage systems, including polyvinyl chloride (PVC) and silicone tubes with radiopaque stripes for better radiological visualization. Modern chest drainage units (CDUs) can incorporate smart digital systems that monitor and graphically report pleural pressure and evacuated fluid/air, improving patient outcomes. The application of suction, whether via wall systems or portable digital devices, enhances the efficacy of pleural drainage, although careful regulation is needed to avoid complications such as reexpansion pulmonary edema or prolongation of air-leak. To prevent recurrent effusion, particularly due to malignancy, pleuroedsis agents can be applied through a chest tube into the pleural space. In other circumstances, such as non-expandable lung (NEL), maintaining a long-term chest drain may be the most appropriate approach and procedures such as placement of an indwelling pleural catheter (IPC) can significantly improve quality of life. Continued innovations and rigorous training ensure that chest tube insertion remains a cornerstone of effective pleural disease management.

Metabolic diseases are major diseases affecting animal welfare, health and production of small ruminants´ flocks for dairy and meat purposes. In breeding females, they mainly occur from six to eight weeks before and after parturition, respectively. The pregnancy toxemia and lactational ketosis are manifestations of hyperketonemia, primarily due to energetic deficit. Hypocalcemia and hypomagnesemia are related to the metabolic availably of calcium and magnesium, respectively. This review aimed to identify and discuss the current and most relevant aspects related to individual and herd heath management of these interrelated metabolic diseases with impact in the sheep and goats´ farm sustainability. These diseases are primarily due to nutritional deficit, but homeostatic and homeorhetic disruptions are responsible for clinical signs and forms. Currently, their clinical diagnosis and monitoring are mainly supported by biochemistry from animal fluids, and bromatological evaluation of the feed. Epidemiological studies, measuring risks factors, also contributes for their prevention. Nevertheless, research on specific biomarkers and composite indexes related to these diseases, in a context of herd health management and precision medicine, are new pathways driven to a suitable and efficient animal production.

Background/Objectives: The burden of hospital-acquired infections (HAIs) is particularly sub-stantial in low- and middle-income countries (LMICs). However, a comprehensive understanding of their prevalence in these regions is lacking. This systematic review aimed to evaluate the prevalence of HAIs in LMICs. Methods: Major databases, including Scopus, PubMed, and Web of Science, were thoroughly searched for published studies between January 1, 2000, and July 15, 2024. The PRISMA guidelines were followed for a comprehensive and systematic approach. The pooled prevalence of HAIs was estimated using a random-effects model and a 95% confidence interval (CI). Results: The literature search identified 87 studies reporting HAI prevalence in LMICs. The overall prevalence of HAIs across LMICs was 22% (95% CI: 17-28), with notable regional variations. The South-East Asian Region (SEAR) presented the highest prevalence at 37% (95% CI: 13-62), followed by the African Region at 25% (95% CI: 16-33). The European Region (EUR) had the lowest preva-lence, at 14% (95% CI: 5-23). In terms of income level, low-income countries had the highest prevalence at 37% (95% CI: 23-52), followed by lower-middle income at 22% (15-30) and up-per-middle income at 13% (95% CI: 6-20). Surgical site infections (SSIs) had the highest prevalence among infection types at 27% (95% CI: 23-31), followed by pneumonia at 23% (95% CI: 18-28) and urinary tract infections (UTIs) at 22% (95% CI: 19-26). Gastrointestinal infections (GIs) were less prevalent at 6% (95% CI: 3-9). Conclusions: This systematic review underscores the high prevalence of HAIs in most LMICs, with variations based on region and income level, emphasizing the need to facilitate the development of targeted prevention and control strategies to mitigate the impact of this critical public health issue, especially in resource-limited settings.

The article delves into the landscape of the plant-based food industry, exploring innovative market entry strategies and their interplay with the evolving food market and shifting consumer preferences and lifestyles. Adopting a multidimensional approach, the study reflects diverse perspectives at play. Through a comparative analysis of strategic promotion and growth strategies employed by both innovative startups and established industry giants in the plant-based alternatives sector in Germany, the study aims to capture the challenges faced by the 'newer' wave of plant-based alternatives. This examination is particularly relevant for navigating the complexities of entering a competitive market. Striving to penetrate evolving consumer lifestyles, the study draws insightful comparisons with their "older" counterparts. In addition, through in-depth interviews with selected companies, the study investigates the entry methods of startups venturing into the German market, aiming to identify parallels and contrasts in market strategies with established brands. This provides valuable insights into innovation within the alternative food market. Furthermore, the study explores the process of brand "platformization" by scrutinizing the websites of the selected companies and analyzing customers' online reviews of their brand experience. This comprehensive analysis unveils distinctive patterns in communication strategies, brand positioning, and consumer engagement, offering insights into plant-based innovation shaping new, caring lifestyles. Main findings include a strong correlation among dimensions related to food quality, use, and taste, indicating a holistic approach to food consumption facilitated by online platforms.

There is a strong global demand for sulfate- free personal cleansing products. The objective of sulfate-free personal cleansing technology should not be aimed at the absence of “sulfate” wording in the ingredient listing, but on the true benefits to both people and the planet, including but not limited to safety, mildness, and sensory for the people perspective and renewability, low carbon footprint, low water footprint, biodegradability & sustainability for the planet perspective. In addition, some surfactants or their precursors contain 1,4-dioxane as a by-product in their manufacturing, which is a major safety concern. In this paper, several commonly used sulfate-free surfactants are compared based on a variety of desirable criteria from both the people and the planet perspective. There is also an important trend promoting green manufacturing processes using natural, renewable, safe, biodegradable & sustainable feedstocks to mitigate the challenges presented by climate change. It is concluded that the best options for the sulfate-free personal cleansing products of the future are glutamates for skin cleansing and alaninates for hair cleansing.

The aim of this research work consisted of assessing the effects of the COVID-19 pandemic on the interurban public transport system in a rural region with a sparse population density, considering the number of tickets sold and passengers in each locality, as well as the different connecting lines. From a methodological point of view and with the intention of identifying patterns to explain the behaviour of both routes and passengers, a series of variables were selected, becoming determining factors that sought to offer a solution to the search for a common trend. Additionally, data processing by means of statistical analysis and the application of Geographic Information Systems (GIS) tools complemented the procedure. The results obtained in the investigation were provided both by municipality and by interurban route. An interesting finding of the research was the uneven recovery of the municipalities. The localities closest to the attractor nucleus have recovered more quickly to pre-pandemic mobility levels due to their geographical proximity, larger population, higher income per household and the need to access certain public services. In terms of routes, all lines showed significant decreases in ticket sales, although with variations. Although passenger numbers have shown a gradual recovery, the initial loss was considerable, and pre-pandemic normality has not been completely achieved. The authors consider that future research should include other alternative means of transport in these interurban areas, incorporating variables to characterise passengers, such as age, gender...etc.

The application of hydrogen flooding was recently shown to be a simple and effective approach towards improved layer differentiation and interface determination during SIMS depth profiling of thin films as well as an approach with a potential in the field of quantitative SIMS analyses. To further study the effects of hydrogen, the flooding of H₂ molecules was compared to the reactions of the atomic H on the samples of pure metals and their alloys. H₂ was introduced into the analytical chamber via a capillary which was, to achieve the dissociation, heated to approximately 2200 K. Dissociation of H₂ up to 30% resulted in a significant increase in the intensity of the metal hydride cluster secondary ions originating from the metallic samples. Comparison of time scales of possible processes provided an insight into the mechanism of the hydride cluster secondary ion formation. Cluster ions presumably form during the recombination of the atoms and molecules from the sample and adsorbed atoms and molecules from the gas. This process occurs on the surface or just above it during the sputtering process. These findings coincide with the previous mechanistic and computational studies.

Despite medical advances, sepsis and septic shock remain one of the leading causes of mortality worldwide, with a high inter-individual variability in prognosis, clinical manifestations and response to treatment. Given the heterogeneity of sepsis and recent technological progress amongst machine learning analysis technique, a new, personalized approach in sepsis is being intensively studied. Despite the difficulties when tailoring a targeted approach, with the use of artificial intelligence-based pattern recognition, more and more publications are becoming available, highlighting novel factors that may intervene in the high heterogenicity of sepsis. This has led to the devise of a phenotypical approach in sepsis, further dividing patients based on host and trigger-related factors, clinical manifestations and progression towards organ deficiencies, dynamic prognosis algorithms and patient trajectory in the Intensive Care Unit (ICU). Host and trigger-related factors refer to patients’ comorbidities, body-mass index, age, temperature, immune response, type of bacteria and infection site. The progression to organ deficiencies refers to individual particularities of sepsis-related multiorgan failure. Finally, the patient’s trajectory in the ICU points out the need of a better understanding of interindividual response to various supportive therapies. This review aims to identify the main sources of variability in clustering septic patients in various clinical phenotypes, as a useful clinical tool for precision-based approach in sepsis and septic shock.

Background: Posterior malleolar fractures (PMFs) account for 7-44% of all ankle fractures, and are crucial for ankle stability, associated with poorer functional outcomes and higher rates of traumatic arthritis. Despite the exact mechanism and treatment strategy of this kind of fractures still remain controversial, most orthopaedic surgeons tend to treat PMFs with open reduction internal fixation method. To achieve rigid fixation for the fragment, screws should be inserted across the fracture plane perpendicularly. However, the study on the spatial geometry of the fracture surface of PMFs, especially the trend surface, has not been reported before.Objective: This study aimed to construct the trend surface of PMFs and establish an algorithm to better understand the spatial geometry of the fracture surface, which could guide treatment strategies.Methods: A retrospective analysis of CT images of PMFs from January 2021 to January 2024 was conducted. Cases were grouped according to the Bartoníček classification system. The skeletal ankle models were reconstructed, which were then transformed into CAD models. Fracture surfaces were segmented, and point clouds were output to record coordinate values. The K-Dimensional Tree data structure was built for the efficient indexcality of the Depth-First-Search algorithm to find the matched points in the clouds. The average point was computed for matched points, and subsequently, the fracture trend surface and heat map were generated.Results: Twenty-four cases were included. The posterior malleolar fracture trend surface was composed of two surfaces, each approximated as a plane and intersect an angle about 130.5°. The posterolateral surface extended slightly curvingly from the posterior two-fifths of the fibular notch to the posteromedial one-third of the distal tibia, formed an angle of 10.1° with the tibia axis and 10.1° with the coronal plan of the lower leg. The posteromedial surface extended from the posteromedial one-third of the distal tibia towards the intercollicular groove, formed an angle of 5.2° with the tibia axis and 39.4° with the coronal plan of the lower leg. The heat map revealed that the high-frequency fracture regions presented at 16.0mm away from the posterior malleolar distal edge and 11.2mm medial to the posterior margin of the fibular notch.Conclusion: The study provides a novel perspective on PMFs by describing the spatial geometric morphology of the fracture surface. This can be useful for the treatment strategies. 1. The fracture lines on the bone surface help us generate a stereoscopic model of the fracture surface in our brain, but this model may not be the same as the true fracture surface. 2. In A-P fluoroscopic view, 16.0mm away from the posterior malleolar distal edge and 11.2mm medial to the posterior margin of the fibular notch were the high frequency regions where the fracture surfaces passed through. 3. To firmly hold the posterolateral PMF, 3 key screws should be parallelly inserted into the distal tibia through the fragment, oriented medially 10.4°, cephalad 10°. The insertion points of the screws, in back view, are individually identified at 8.3mm, 16.9mm, 8.3mm superior to the inferior margin of the posterior malleolus, and 6.0mm,10.5mm, 15.1mm posterior to the posterior margin of the fibular notch. The depth of the screws should be no more than 40mm to avoid irritating the anterior tendons, vessels and nerves.

Alzheimer’s disease (AD) is a neurodegenerative disease that is characterized as a progressive decline in cognitive functions that primarily affects older adults. Alzheimer’s is pathophysiologically characterized by the accumulation of amyloid-beta (Aβ) plaques, neuroinflammation, accumulation of tau proteins in neurofibrillary tangles (NFTs), and tissue loss. These three main characteristics are hallmarks of neurodegeneration. Statins are a class of medications that lower the cholesterol levels in the blood, and their anti-inflammatory effects have gained attention for their potential impact on influencing AD progression. This literature review explores the relationship between the use of statins and AD, examining the effect of statins on cholesterol metabolism, neuroinflammation, apolipoprotein E (ApoE), and Aβ production. This literature review was conducted using PubMed and Google Scholar to summarize the association between statins and AD. The neurodegenerative properties of Alzheimer’s disease have been imaged and documented in both rodent models and humans. Experiments using transgenic mice and knock-in mice have shown that specific human genes enhance neurodegeneration, and the overactivation of glial cells in the brain causes hallmark neuroinflammation. These rodents all subsequently suffered from neurodegeneration and AD symptoms. Humans showed promise of possible AD biomarkers in the blood and brain through the presence of excess isoprostanes and oxysterols, respectively, providing hope for future research into early detection/treatment. There has been evidence that statins exhibit neuroprotective pleiotropic effects in rodent models, showcasing reductions in cellular adhesion molecules (the main molecule in inflammation), oxidative stress, and inflammatory peptides. ApoE is a cholesterol transport protein in the brain and is critical to forming an effective synapse. Statin use has effectively altered the ApoE4 allele and reduced the Aβ production in the brain. However, the mechanism for which statins slow the progression of neurodegeneration in AD is still unclear and warrants further research before it can be officially called a treatment.

Radiation-induced lung injuries (RILI) are a notable complication of thoracic radiotherapy, significantly affecting the quality of life and prognosis for cancer patients. We present the case of a 68-year-old man with metastatic prostate cancer who underwent radiation therapy for a metastatic thoracic vertebral lesion identified with high uptake on a PET-PSMA scan. Four months later, a follow-up PET-PSMA scan indicated that the pathological uptake in the vertebra had resolved, but it also revealed a new lung consolidation with PSMA uptake. This case illustrates a potential pitfall in interpreting PSMA PET-CT findings, as the uptake in the lung lesion was due to RILI rather than malignancy, infection, or another form of pneumonia, highlighting the necessity for careful clinical correlation to avoid misdiagnosis and potentially inappropriate and unnecessary treatment.

Wind energy is one of the main drivers of the renewable energy market. The wind turbine gearbox, used as a multiplier - is one of the main components directly related to wind turbine efficiency and lifespan. Therefore, the strict control of the gearbox project and its manufacturing processes or even minor improvements in this component heavily and positively impact energy production/generation over time. This work diagnoses a 1.6 MW gearbox fracture mechanics to identify its main reason and how the chain of events took place, leading to the catastrophic failure. The diagnoses underwent numerical simulation (Finite Element Analysis - FEA) and further analysis of the lubrication system, bearings, planetary stage gears, helical stage gears, and high-speed shaft. In conclusion, although the numerical simulation showed high contact stresses between the teeth, the region with the crack nucleated was the top land (tip of the tooth). The most likely factors that led to the premature failure were the missed lubrication for the planetary bearings, lack of gear raw material cleanliness, and excessive case depth at the tip of the sun shaft gear teeth. With the sun gear, planet bearings, and planet gears broken in pieces, those small and large pieces dropped into the oil, between the gears, and into the tooth ring, ending up as a premature gearbox failure.

In recent years, the demand for solid, thin, and flexible energy storage devices has surged in modern consumer electronics, which require autonomy and long duration. In this context, hybrid supercapacitors have become strategic, leading to significant efforts to develop cells with an energy density close to that of batteries, while maintaining the power density of conventional supercapacitors. Motivated by these requirements, we report the development of a new high-performance dual-redox-mediator supercapacitor. In this study, cells were constructed using fully moldable buckypapers (BPs), composed of carbon nanotubes and cellulose nanofibers, as electrodes. We evaluated the compatibility of BPs with hydrogel polymer electrolytes, based on 1 mol L-1 H2SO4 and polyvinyl alcohol (PVA), supplemented with different redox species: methylene blue, indigo carmine, and hydroquinone. Solid cells were constructed containing two active redox species to maximize the specific capacity of each electrode. Considering the main results, the dual-redox-mediator supercapacitor exhibits a high energy density of 32.0 Wh kg-1 (at 0.8 kW kg-1) and is capable of delivering 25.9 Wh kg-1 at high power demands (4.0 kW kg-1). Stability studies conducted over 10,000 galvanostatic cycles revealed that the PVA polymer matrix benefits the system by inhibiting the crossover of redox species within the cell.

This paper proposes an omnidirectional conveyor as a novel alternative to existing omnidirectional conveyors. With symmetric and compact layout, this new structure ensures consistent kinematics and enhanced flexibility in trajectory planning. The kinematic model of the proposed omnidirectional conveyor is developed and verified through simulation in CoppeliaSim. Four typical classes of trajectories are generated and verified in the simulation environment. Using PID control, the actual trajectories of a package on the conveyor closely match the desired trajectories. In addition, this paper outlines the workspace and corresponding wheel patterns for the conveyor, demonstrating how different supported wheel patterns emerge when packages move across various areas of the conveyor. The discussion extends to fault tolerance and obstacle avoidance, examining the workspace and wheel patterns with one or two omni wheels failed. Furthermore, this paper provides a comprehensive analysis on the feasible desired movements for the packages on the conveyor under the constrained wheel speed. This provides insights and guidance on trajectory planning and design of the conveyor.

The effect of zirconium modified with silica dioxide in the conductivity of modified nanocomposite membrane in proton exchange membrane fuel cells (PEMFCs) application. In this study silica-zirconia nanoparticles were successful synthesized by precipitation method. The surface area and surface morphology of Si-ZrO2 nanoparticles were observed under BET analysis, X-ray diffraction (XRD), scanning electron microscope (SEM), and transmission electron microscope (HRTEM). SEM and XRD results show that silica was well incorporated into ZrO2 nanoparticles with the mixed shape of nanorods and nanosphere. HRTEM shows a crystallised small nanoparticle with average diameter about 5–8 nm. The element analysis (EDX) confirms the presence of silica and zirconia nanoparticles as well as oxygen on the surface. The addition of silica has impact on the surface area and pore size of Si-ZrO2 nanoparticles, with Si-ZrO2 nanoparticles having a higher surface area of 185 m2/g when calcinated at 600 °C. It was shown that the Si-ZrO2 can be used as an impregnating membrane to enhance the conductivity as observed by cyclic voltammetry (CV), with a rectangular shape that exhibiting the best capacitance behaviour.

AbstractThe global textile industry is undergoing a significant transformation fueled by digital advancements, shifts in consumer behavior, and evolving market dynamics. This study investigates how digital platforms, such as e-commerce and customer relationship management (CRM) systems, can enhance operational efficiency, customer engagement, and market positioning for textile companies. Through the integration of primary data from focus groups and surveys, as well as secondary data from industry reports, this research identifies key strategies for digital adoption and market competitiveness. Using Company A as a case study, this paper explores how digital tools can address current industry challenges and foster growth in a competitive landscape. The findings reveal that implementing CRM systems significantly improves customer retention and personalized services, while adopting e-commerce platforms reduces operational inefficiencies and expands market reach. These results contribute to understanding the role of digital transformation in traditional industries, particularly with respect to customer engagement, branding, and operational optimization.

Background: This study conducts a comparative historical analysis of two significant drug crises: the opium epidemic in 19th-century Qing Dynasty China and the ongoing opioid crisis in the United States, aiming to extract applicable lessons for current global drug policies. Methodology: A historical case study approach was employed, integrating examinations of historical records, policy documents, and contemporary data to compare the development, impact, and responses to these crises within their respective contexts. Results: The analysis reveals significant parallels in socioeconomic impacts and governmental challenges. Key differences include the evolution from predominantly prohibitionist approaches in Qing China to more comprehensive public health-oriented strategies in the U.S. The study highlights the critical role of national power, particularly military capability, in effectively addressing drug crises. Conclusions: The findings underscore four key lessons: (1) Purely prohibitionist approaches often lead to unintended consequences such as black markets and increased criminal activity; (2) Addressing underlying socioeconomic factors contributing to drug abuse is crucial; (3) Aggressive anti-drug policies can escalate into severe diplomatic tensions, necessitating careful consideration of international relations in policy formulation; (4) A nation's military and economic strength significantly influences its ability to implement effective drug policies and resist external pressures that may exacerbate the crisis. These insights suggest that effective management of drug crises requires a balance of strong domestic policies, international cooperation, and maintenance of national power to ensure policy autonomy.

Apart from headwind changes, crosswind changes may be hazardous to the aircraft operation. This paper presents two cases of recently observed crosswind changes from the range height indicator scans of ground-based remote-sensing meteorological equipment, namely, an X-band microwave radar and a short-range LIDAR. Rapidly evolving winds have been observed by the equipment in tropical cyclone situations, and they are found to have high level of turbulence and possibly to be associated with vertically propagating waves. In order to study the feasibility of predicting such disturbed airflow, mesoscale meteorological model and computational fluid dynamics model with high spatial resolution are used in this paper. It is found that the models could capture the rapidly evolving airflow features rather well, including the turbulence level, the waves, the rapidly changing wind speeds and the presence of reverse flow. This paper aims at providing a reference to the airports to consider the feasibility of performing high resolution numerical simulation of rapidly evolving airflow to alert the pilots in advance for airports in complex terrain and setup of buildings.

As Aotearoa-New Zealand faces increasing cyber threats, this paper comprehensively analyses the nation’s current cybersecurity landscape, revealing novel opportunities and challenges. Through an interdisciplinary approach, the study integrates social, cultural, and technological dimensions—providing a fresh perspective that has been underexplored in previous research. A key focus is integrating cultural values, particularly those of the indigenous Māori, into cybersecurity practices. This not only strengthens the effectiveness and trustworthiness of security measures but also fosters a more inclusive and resilient digital environment, demonstrating our deep respect for the unique contributions of Māori culture. Additionally, this paper introduces critical insights into the country's cybersecurity talent gap, with a special focus on the challenges of developing and retaining cybersecurity expertise in remote regions. Our study also uncovers underexplored opportunities for cross-sector collaboration between private enterprises, government agencies, and indigenous communities, promoting an inclusive and resilient approach to cybersecurity. By positioning Aotearoa-New Zealand as a potential leader in regional cybersecurity innovation, we provide forward-looking recommendations that leverage its distinctive cultural and technological strengths. This research contributes fresh insights to the global discourse on cybersecurity, offering practical strategies tailored to the specific needs of smaller nations.

Inherited heart diseases (IHDs) are caused by genetic mutations that disrupt the physiological structure and function of the heart. Understanding the mechanisms behind these diseases is crucial for developing personalised interventions in cardiovascular medicine. Development of induced pluripotent stem cells, which can then be differentiated to any nucleated adult cell type, has enabled the creation of personalised single-cell and multicellular models, providing unprecedented insights into the pathophysiology of IHDs. This review provides a comprehensive overview of recent advancements in human iPSC models used to dissect the molecular and genetic underpinnings of common IHDs. We examine multicellular models and tissue engineering approaches, such as cardiac organoids, engineered heart tissue, and multicellular co-culture systems, which simulate complex intercellular interactions within heart tissue. Recent advancements in stem cell models offer a more physiologically relevant platform to study disease mechanisms, enabling researchers to observe cellular interactions, study disease progression, and identify therapeutic strategies. By leveraging these innovative models, we can gain deeper insights into the molecular and cellular mechanisms underlying IHDs, ultimately paving the way for more effective diagnostic and therapeutic strategies.

New allyl derivative of curcumin containing three allyl groups (1E,6E)-4-allyl-1,7-bis(4’-allyloxy-3’-methoxyphenyl)hepta-1,6-diene-3,5-dione was synthesized by the reaction of curcumin with the excess of allyl bromide in the presence of K2CO3 in acetone under reflux. The triple allylated curcumin was characterized by 1H and 13C NMR spectroscopy and single-crystal X-ray diffraction study.

Flexible humidity sensors (FHS) with fast response and durability to high-humidity environment are highly desirable for practical applications. Herein, an FHS based on crosslinked sodium alginate (SA) and MXene was fabricated, which exhibited high sensitivity (impedance varied from 107 to 105 Ω between 10% and 90% RH), good selectivity, prompt response (response/recover time of 4 s/11 s), high sensing linearity (R2 = 0.992) on a semi-logarithmic scale, relatively small hysteresis (~5% RH), good repeatability, and good resistance to high humid environment (negligible change in sensing properties after placed in 98% RH over 24 h). It is proposed that the formation of crosslinking structure of SA and introduction of MXene with good conductivity and high specific surface area contributed to the high performance of the composite FHS. Moreover, the FHS could promptly differentiate respiration status, recognize speech and measure fingertip movement, indicating potentials in breath monitoring and non-contact human-machine interactions. This work provides guidance for developing advanced flexible sensors with wide application scope in wearable electronics.

Codon bias analysis of SARS-CoV-2 reveals suboptimal adaptation for translation in human cells it infects. The detailed examination of the codons preferentially used by SARS-CoV-2 shows a strong preference for LysAAA, GlnCAA, GluGAA, and Arg AGA infrequently used in human genes. In the absence of an adapted tRNA pool, efficient decoding of these codons requires a 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2) modification at the U34 wobble position of the corresponding tRNAs (tLysUUU; tGlnUUG; tGluUUC; tArgUCU). The optimal translation of SARS-CoV-2 open reading frames (ORFs) may therefore require several adjustments to the host's translation machinery, enabling the highly biased viral genome to achieve a more favorable "Ready-to-Translate" state in human cells. Experimental approaches based on LC-MS/MS quantification of tRNA modifications and on alteration of enzymatic tRNA modification pathways provide strong evidence to support the hypothesis that SARS-CoV-2 induces U34 tRNA modifications and relies on these modifications for its lifecycle. The conclusions emphasize the need for future studies on the evolution of SARS-CoV-2 codon bias and its ability to alter the host tRNA pool through the manipulation of RNA modifications.

Traditional mining activities in Zaruma-Portovelo (SE Ecuador) have led to high concentrations of pollutants in the Puyango River due to acid mine drainage (AMD) from abandoned waste. Dispersed Alkaline Substrate (DAS) passive treatment systems have shown efficacy in neutralizing acidity and retaining metals and sulfates in acidic waters, achieving near 100% retention for Fe, Al, and Cu, over 70% for trace elements, and 25% for SO₄²⁻. However, significant solid residues are generated, requiring proper geochemical and mineralogical understanding for management. This study investigates the fractionation of elements in AMD precipitates. Results indicate that trivalent metals (Fe, Al) form low-crystallinity oxyhydroxysulfate minerals such as schwertmannite and jarosite, which retain elements like As, Cr, Cu, Pb, and Zn through adsorption-coprecipitation. Sulfate removal occurs via salts like coquimbite and gypsum. Divalent metals are primarily removed through carbonate and bicarbonate phases, with minerals such as azurite, malachite, rhodochrosite, and calcite. Despite the effectiveness of DAS, leachates from the precipitates exceed regulatory thresholds for aquatic life protection, classifying them as hazardous and posing environmental risks. However, these residues offer opportunities for the recovery of valuable metals.

Objective: This study aims to investigate the effects of acupuncture therapy on the quality of life, early recurrence rate, and heart rate variability in patients following radiofrequency ablation for atrial fibrillation, as well as to assess its safety. Methods: Seventy patients were enrolled in this study. Of these, 35 patients received acupuncture treatment post-radiofrequency ablation, forming the experimental group, while the remaining 35 patients received sham acupuncture treatment, constituting the control group. The acupuncture group targeted the Xinju (BL15), Neiguan (PC6), and Shenmen (HT07) points, whereas the sham acupuncture group received sham interventions at three non-meridian and non-acupoints. Both groups underwent acupuncture treatment twice weekly for a total of 24 consecutive sessions. After three months, the total scores on the Atrial Fibrillation Specific Quality of Life Scale (AFEQT)—including symptom scores, daily activity scores, treatment anxiety scores, atrial fibrillation control scores, and symptom improvement satisfaction scores—along with atrial fibrillation burden and satisfaction scores, were compared between the two patient groups. Additionally, the recurrence rate of atrial fibrillation, frequency of hospitalizations due to arrhythmia, and incidence of adverse events occurring three months post-catheter ablation were also assessed. No significant differences were observed in the general baseline characteristics between the two groups. Results: The total AFEQT scores—including symptom scores, daily activity scores, treatment anxiety scores, atrial fibrillation control scores, and symptom improvement satisfaction scores—were significantly higher in both groups post-treatment compared to pre-treatment. Notably, patients in the experimental group exhibited statistically significant improvements in daily activity scores, treatment anxiety scores, and symptom improvement satisfaction scores compared to those in the control group (P<0.05). There were no statistically significant differences between the two groups regarding other measured outcomes. Conclusion: Acupuncture-assisted treatment of atrial fibrillation can improve the clinical efficacy of drugs and catheter ablation, help maintain sinus rhythm, increase sinus rhythm conversion rate, reduce ventricular rate, and shorten conversion time, and is safe and reliable.

This study reveals that with similar valence of empathy, the tendency for humans to help humans in need is stronger than the animal in need. It also illustrates that a convincible advertisement for a charity should be a combination of various feelings, mainly empathic anger, in addition to compassion or empathy. To gain support from young individuals or donors regardless of their personal values, the egoistic values particularly, both the NPOs in humanitarian aid as well as in environmental protection or conservation should develop ads by which each individual or donor is aroused by either an empathic anger and empathic joy or both. This claim is more applicable for any ads developed to help people in need more than animals in need. Nevertheless, this study also found the role of an animal, generally known as innocent, as an actor in an ad is likely more crucial than human. Subjects with high-egoistic values appeared to get vulnerably aroused to a higher extent by being immersed in animal’s suffering than human’s suffering. The feeling of arousal seemed to motivate subjects with high-egoistic values to not decrease the amount of donation to a charity.

This review aimed to identify the risks of cosmetics during the sensitive period of pregnancy. Pregnancy causes many hormonal changes and skin issues, such as red stretch marks, cellulite, and more. These aesthetic concerns can impact both the appearance and health of the pregnant woman. Cosmetics and aesthetic treatments can help improve these problems and positively affect the mental well-being of these women. However, the lack of clinical trials regarding the safety of such treatments during pregnancy has led to the recommendation of only the mildest aesthetic applications. Additionally, professional aestheticians and dermatologists who provide cosmetics and other aesthetic treatments (e.g., laser, ultrasound, radiofrequency) during pregnancy face challenging and sometimes adverse working conditions. They should be treated with respect for their situation, with careful consideration of all the peculiarities associated with pregnancy. Further research and additional recorded data are crucial for better understanding the use of cosmetics and aesthetic treatments during pregnancy.

In this study, the structural behavior of a short threaded anchor with a 20 mm diameter and an embedment length of 50 mm (2.5Ø) in UHPFRC is investigated using non-linear Finite Element models. UHPFRC is assumed to exhibit tensile strain-hardening behavior, with tensile strengths of 7 MPa and 11 MPa, respectively. The modelled anchor was subjected to a continuously increasing uniaxial pull-out force. The results indicate that the fracture mechanism of threaded anchors in UHPFRC is primarily characterized by the formation of a tensile membrane within the UHPFRC, which acts as the main resisting element against the pull-out force. Additionally, the influence of UHPFRC's tensile properties on the pull-out behavior and ultimate resistance of the threaded anchors was determined.

Deuterium is a non-radioactive isotope of hydrogen, containing a neutron as well as a proton, which makes it twice as heavy as hydrogen. Deuterium is a natural element found at 156 parts per million in seawater. Human metabolism employs clever strategies to minimize the amount of deuterium in mitochondrial water, because it causes a stutter in ATPase pumps, introducing excess reactive oxygen species and inefficiencies in ATP production. Gut microbes produce hydrogen gas that is 80% depleted in deuterium (deupleted), and this gas is recycled into organic matter that supplies deupleted nutrients to the host, such as acetate, butyrate, formate, methionine, and choline. Mitochondrial dysfunction is associated with many chronic diseases, most notably, cancer. Dehydrogenases are flavoproteins that typically have a high deuterium kinetic isotope effect, and they supply deupleted protons to NAD⁺ to produce NADH, which supplies protons to the ATPase pumps. Here, we examine the unique metabolic policies of cancer cells in a new light, and we propose that a tumor may arise as a strategy to help repair the mitochondria of tumor-resident immune cells overburdened with deuterium. While lactate accumulation in the tumor microenvironment promotes tumor growth, it also provides a valuable deuterium depleted nutrient to the tumor-resident immune cells. We provide strong evidence that deuterium depleted water (DDW) is a promising treatment for cancer.

The accurate detection and assessment of stress play a pivotal role in enhancing individual well-being and healthcare outcomes. Traditional methods of stress detection often grapple with limitations in accuracy and scalability. With the advent of machine learning (ML), the potential to revolutionize stress detection has emerged. This paper presents a comprehensive study on the application of ML algorithms for stress detection, with a focus on physiological and behavioral data analysis. Central to our approach is the integration of SHapley Additive exPlanations (SHAP), an Explainable Artificial Intelligence (XAI) technique, to interpret ML models. SHAP provides a novel lens to understand the impact of individual features in the complex decision-making processes of ML models, thereby enhancing the transparency and reliability of stress predictions. We demonstrate how SHAP not only aids in elucidating model decisions but also contributes to refining the models for greater accuracy. Our results highlight the effectiveness of ML in detecting stress and the pivotal role of XAI in making these models more interpretable and trustworthy. This study underscores the synergy between advanced ML techniques and XAI, paving the way for more nuanced and reliable stress detection methodologies that are essential in diverse settings, from healthcare to workplace environments.

Human space exploration is evolving, with private and government organizations working to develop the new generation of astronauts and technology for future colonization of the Moon and other extreme locations. The coming decade is promising, which is reflected in a number of emerging habitats to simulate analog missions around the world. Analog missions have always been at the forefront of advancing knowledge and now this method is widely used by space enthusiasts and professionals. The Analog Astronaut Training Center is designed to simulate one of the major challenges of human space exploration, namely isolation with limited resources, and focuses on collecting data based on various parameters such as environment, physiology and psychology. The environmental monitoring of the habitat conditions is remotely controlled, allowing the Mission Control Center to receive the mission data in real time. The data obtained, together with physiological and psychological inputs, allow monitoring of human adaptations to limited resources and sustainable living in extreme conditions. This paper presents an overview of the sensors used and the data collected during organized analogue simulations, which help to optimize the design of future life-support systems.

Background/Objectives: Distance or urbanisation settings may affect active commuting to school (ACS). This study aimed to (i) detect home-school threshold distances of walking to school and (ii) predict walkable distances among adolescents in different urbanisation settings and both sexes, and (iii) to identify variables predicting adolescents’ ACS, in a central Spain region. Methods: The PACOyPACA (Spanish acronym for Pedal-and-Walk to School, Pedal-and-Walk Home) study evaluated adolescents attending urban, semi-urban and rural schools from Castilla-La Mancha region. The sample included 448 adolescents [48.9% females, mean age 14.80 (SD=0.60)] living closer than 5,100m from school. Distance was divided into deciles to detect which adolescents walked more. Most walkable distances within the whole sample, by sex and by urbanisation settings were predicted using Receiver Operating Characteristic (ROC) curves. Variables affecting ACS were found with binary logistic regression. Significance was set at p≤0.05. Results: Most adolescents walked to school (73.1%). Commuting modes differed significantly by urbanisation settings (p=0.001), but not by sex. Most walked when living around 1,400m from school or closer within the whole sample, in both sexes and in urban and semi-urban settings, and adolescents within rural settings did it until 750-900m. Walkable distances were 1,350m for the whole sample and both sexes, and 1,450, 1,350 and 800 within urban, semi-urban and rural settings, respectively. Distance was the only predictor of ACS (p&lt;0.001). Conclusions: Walkable home-school distances differed based on urbanisation settings, which may be due to the classification of urbanisation settings. This study addresses schools within scarcely populated areas.

Background: The aim of this systematic review was to evaluate diagnostic accuracy of molecular-based LTPs serum IgE for the diagnosis of food allergies in patients with suspected allergy to one of the LTPs-containing food. Methods: cohort, prospective or retrospective cross- sectional studies were considered for inclusion in the review. Oral food challenge (both open and double-blind placebo-controlled) was the reference standard for the diagnosis. Pubmed (MEDLINE), Web of Science, Scopus, and ClinicalTrial.org were searched for relevant papers. Risk of bias was assigned by QUADAS-2 tool. Data were reported as sensitivity and specificity. Study protocol was registered in the PROSPERO database (CRD42022321985). Results: Fifteen articles, including 2395 individuals, were included. Sensitivity of Ara h 9 for peanut allergy diagnosis ranged from 6 to 61%; specificity ranged from 57 to 100%. Cor a 8 sensitivity ranged from 11 to 43%, with specificity ranging from 59 to 94%. Conclusions: Ara h9 and Cor a 8 serum IgE may be useful to confirm diagnosis of peanut and hazelnut allergy in symptomatic patients, although diagnostic accuracy is limited by low sensitivity. More investigation on other LTPs and in adult population may be important to define the clinical role of this test in food allergies diagnostics.

Chronic urticaria (CU) is a debilitating skin condition affecting up to 20% of the global popula-tion, characterized by erythematous, maculo-papular lesions and significant quality of life im-pairment. This study focused on the role of interleukin 33 (IL-33) and its polymorphisms, partic-ularly SNP rs1929992, in chronic spontaneous urticaria (CSU). Using demographic, clinical, and laboratory data from CU patients and controls, we aestimated allele and genotype frequencies, Hardy-Weinberg equilibrium condition, and serum IL-33 levels, using unconditional binomial logistic regression for association analysis. Results revealed that CU patients had significantly higher frequencies of the minor allele of IL33 rs1929992 compared to controls (31.25% vs. 17.35%, p = 0.024), and carriers of the AG genotype exhibited increased odds of CU (adjusted OR = 2.208, p ≤ 0.001). Additionally, serum IL-33 levels were markedly elevated in CU patients, par-ticularly those with the GA genotype. The findings suggest that the IL-33 SNP rs1929992 is asso-ciated with an increased susceptibility to CSU, emphasizing its potential as a diagnostic and therapeutic biomarker. This study underscores the genetic and immunological underpinnings of CSU, paving the way for personalized treatment approaches.

The precise localisation of epileptic foci with the help of EEG or ECoG signals is still a clinical challenge that is rarely successful, except in the case of foci that are very close to the surface and allow a clear assignment to a single electrode. On the research side, dipole reconstruction of instantaneous excitation fields via the lead-field matrix or the evaluation of time-dependent phase shifts in the measurements seem to be still possible and are under development. For the latter, we have investigated the necessary correlation of signals in the time range up to a few hundred milliseconds in an EEG of a healthy subject (self-experiment). We find periods of up to 190 msec in length in which a correlation over short latencies succeeds very well, alternating with periods in which long-range correlations occur while the short latencies come to a standstill. An automatic propagation time focus localisation to be developed therefore appears possible if an underlying state monitoring system independently recognises the suitable time periods and then successfully performs the comparatively shortest-range triangulation calculations over these.

The flow of mapping the development and direction of research on Socioeconomic Factors in the Education Ecosystem is known through published articles with the Scopus database index. Quantitative approach is used as the article research with bibliometric data analysis techniques to explore all publications indexed in the Scopus database on Socioeconomic Factors in the Education Ecosystem from 1990 to 2023. The data obtained were analyzed using Excel and R/R-Studio. VOSViewer is used to perform visual analysis of keyword occurrence and document citations stimulantly. Researchers found 772 publications that fit the function, subject, and criteria that had been set. The annual growth rate is seen in the data obtained. The papers are analyzed in terms of publications by field of science, the number of studies published annually. The bibliometric data analysis performed was limited to Scopus data. Other national and international databases were not taken into account in the study. The limitation of this study is only taking data sets or meta data in publications indexed by Scopus. This article presents a brief overview of the literature accessible to researchers working in the field of Socioeconomic Factors in the Education Ecosystem as well as provides recommendations for future research.

This paper addresses the capability to alter the hydrophilic wettability characteristics of poly(vinyl alcohol) (PVA) polymer films doped with glycerol. Films of PVA and glycerol-choline chloride (GCC) blends have been prepared using the solution casting method with different glycerol dopants ranging from 0% to 10% (wt %). The results show that as the GCC dopant content increases from 0% to 10%, the wettability increases, thus increasing the surface energy of the solid film. The wettability changes are observed by identifying the contact angle of 10 µL deionized water droplet which altered from 55^o to 28^o as dopant content changed from 0% to 10% per PVA solution weight. The results show that the roughness of film surfaces increases as the content of dopant (GCC) increases in the film indicating that roughness has a strong influence on the wettability of the casted films.

Machine unlearning, the process of selectively forgetting or removing the influence of specific data points from a machine learning model, is increasingly important for privacy and compliance with regulations like the GDPR. This paper explores the concept of exact unlearning, focusing on its implementation in models trained using convex and non-convex functions. Convex functions, due to their well-behaved optimization landscapes, lend themselves to efficient unlearning through methods such as inverse optimization, duality-based approaches, and incremental learning. In contrast, non-convex functions, common in deep learning models, present more complex challenges due to their multiple local minima and high-dimensional parameter spaces. Techniques like checkpoint-based retraining, gradient inversion, and meta-learning are discussed as viable, though computationally expensive, methods for non-convex exact unlearning. The paper also highlights real-world applications in fields such as finance and healthcare, where exact unlearning can enhance privacy and security without compromising model performance. Finally, it outlines key challenges and future research directions, particularly the need for more efficient unlearning algorithms in non-convex settings and the development of secure, adversarial-resistant methods for sensitive data removal.

Road safety is a critical public health concern in Nepal, especially in urban areas where inadequate infrastructure exacerbates traffic incidents. This study reviews and synthesizes 21 peer-reviewed papers to investigate how road infrastructure contributes to traffic accidents. Key factors include poor road conditions, reckless driving, and inadequate traffic management. Findings indicate that road traffic accidents (RTAs) significantly increase morbidity, mortality, and economic burdens in Nepal. To address these issues, the study recommends infrastructure improvements, stricter enforcement of traffic laws, and enhanced public education on road safety.

Generic text embeddings have demonstrated considerable success across a multitude of applications. However, these embeddings are typically derived by modeling the co-occurrence patterns within text-only corpora, which can limit their ability to generalize effectively across diverse contexts. In this study, we investigate methodologies that incorporate visual information into textual representations to overcome these limitations. Through extensive ablation studies, we introduce a novel and straightforward architecture named VisualText Fusion Network (VTFN). This architecture not only surpasses existing multimodal approaches on a range of well-established benchmark datasets but also achieves state-of-the-art performance on image-related textual datasets while utilizing significantly less training data. Our findings underscore the potential of integrating visual modalities to substantially enhance the robustness and applicability of text embeddings, paving the way for more nuanced and contextually rich semantic representations.

The study focused on utilizing post-process osmotic solution enriched with inulin or maltodextrin, evaluating its potential for spray drying. Parameters such as yield, energy consumption, and the physical properties of the dried solutions and powders—including moisture content (Mc), water activity (Aw), color, true and bulk density, porosity, and glass transition temperature—were analyzed. The effects of carrier type, concentration, and inlet temperature (Tin) were systematically examined. Samples dried with maltodextrin demonstrated over 50% higher yield than those with inulin, with the highest yield of 32.13±0.64% and the lowest yield of 2.75±0.48%. Higher Tin improved drying efficiency by reducing Mc but also caused darker powders. Energy consumption increased with rising Tin, peaking at 2295±51 kJ. The Spray Drying Energy Index (SDEI) was introduced to assess energy consumption relative to powder yield, with the most favorable SDEI values observed for processes with the highest total energy consumption. These same samples exhibited lower Mc and Aw values. The lowest bulk density was 0.455±0.004 g·cm-3, while porosity was 58.3±0.7%. The results highlight the potential of spray drying as a sustainable method for utilizing by-products from osmotic dehydration, aligning with the principles of sustainable food practices.

This study reports a 50-year-old patient presented with eczematous drug-eruption induced by selpercatinib after the treatment of non-small cell lung cancer (NSCLC). The patient has symmetric erythematous papules and plaques all over the body with dry, scaly skin accompanied by severe pruritus and visible scarring. After systemic treatment with glucocorticoids, the skin lesions of the patient were well reduced. Currently, the medical literature on the incidence of selpercatinib-induced cutaneous eczematous reactions and their clinical management is scarce. Therefore, this study provides novel evidence for the treatment of selpercatinib-induced cutaneous eczematous reactions.

By tonnage, corn (Zea mays L.) is the #1 crop produced globally, and recent research has suggested that no-till (NT) systems can lead to reduced yields of this important crop. Additionally, there is a lack of long-term data about the effects of tillage and N management on cropping systems. Corn is the most nitrogen (N)-fertilized crop in the USA, and N losses to the environment contribute to significant impacts on air and water quality. We conducted long-term studies on conventional tillage (CT), and conservation tillage systems such as strip tillage (ST) and NT, under different N rates. We found that immediately after conversion to NT, yields from NT were significantly lower than yields from CT (P<0.1), but after five years of NT, the NT yields were 1.5% higher than the CT yields (P<0.1). Initially, the NT yields were lower than the ST (P<0.01), but after seven years of NT, the NT yields were comparable to ST grain yields. Although the total aboveground N uptake with NT immediately after conversion to NT was lower than with CT and ST, these differences were not significant in the long run. The nitrogen use efficiency (NUE) with NT increased over time. The present work highlights the importance of long-term research for determining the cumulative impacts of best management practices such as NT. We found that NT becomes a more viable practice after five or seven years of implementation, demonstrating the high importance of long-term research.

Aβ1-42 (amyloid beta) oligomers, the major neurotoxic culprits in Alzheimer's disease, initiate early pathophysiological events, including neuronal hyperactivity, that underlie aberrant network activity and cognitive impairment. Although several synaptotoxic effects have been extensively studied, neuronal hyperexcitability which may also contribute to cognitive deficits is not fully understood. Here, we found several adverse effects of in vivo injection of Aβ1-42 oligomers on contextual memory and intrinsic properties of CA1 pyramidal neurons. Male rats underwent behavioral and electrophysiological studies 1 week after microinjections into the dorsal CA1 region, followed by histological analysis. After 1 week, Aβ1-42 oligomers impaired contextual learning without affecting basic physiological functions and triggered training-induced neuronal excitability. Furthermore, riluzole, a persistent sodium current (INaP) blocker, dose-dependently reduced Aβ1-42 oligomer-induced hyperexcitability. Congo red staining, which detects insoluble amyloid deposits, further identified labeling of CA1 pyramidal neurons while immunohistochemistry with lecanemab, which detects soluble Aβ oligomers, revealed immunoreactivity of both pyramidal and non-pyramidal cells in the target area. Therefore, our study suggests that a single injection of Aβ1-42 oligomers resulted in contextual memory deficits along with concomitant neuronal hyperexcitability and amyloid deposition in the CA1 region after 1 week.

Low-grade endotoxemia by lipopolysaccharide (LPS) has been detected in COVID-19 and could favour thrombosis via eliciting a pro-inflammatory and pro-coagulant state. The aim of the study was to analyse the mechanism accounting for low-grade endotoxemia and its relationship with oxidative stress and clotting activation thrombosis in COVID-19. We measured serum levels of sNOX2-dp, zonulin, LPS, D-dimer and albumin in 175 patients with COVID-19, classified as having or not acute respiratory distress syndrome (ARDS), and 50 healthy subjects. Baseline levels of sNOX2-dp, LPS, zonulin, D-dimer, albumin and hs-CRP were significantly higher in COVID-19 compared to controls. In COVID-19 patients with ARDS, sNOX2-dp, LPS, zonulin, D-dimer and hs-CRP were significantly higher compared to COVID-19 patients without ARDS. Conversely, concentration of albumin was lower in patients with compared with those without ARDS and inversely associated with LPS. In COVID-19 cohort, the number of patients with ARDS progressively increased according to sNOX2-dp and LPS quartiles; a significant correlation between LPS and sNOX2-dp, and LPS and D-Dimer was detected in COVID-19. In a multivariable logistic regression model, LPS/Albumin levels and D-dimer predicted thrombotic events. In COVID-19 patients, LPS is significantly associated with a hypercoagulation state and disease severity. In vitro, LPS can increase endothelial oxidative stress and coagulation biomarkers, that were reduced by the treatment with albumin. In conclusion, impaired gut barrier permeability, increased NOX2 activation and low serum albumin may account for low-grade endotoxemia, and they may be implicated in thrombotic events in COVID-19.

Background: Adverse pregnancy outcomes correlate with blood glucose levels in women with type 1 diabetes. There is a gap between glycaemic targets and blood glucose control achieved in pregnancy. Aims: To investigate the impact of an intensive weekly service on glycaemic control compared with our previous care model in pregnancies affected by type 1 diabetes. Materials and Methods: This is a retrospective cross-sectional pre / post study comparing measures of glycaemic control in women with type 1 diabetes at each trimester of pregnancy, in the 12 months before and the 8 months after the commencement of an intensive weekly insulin stabilisation service (ISS). Results: The study utilised data from Dexcom continuous glucose monitoring (CGM) reports for analysis of pregnancy-specific glycaemic data (incorporating time in range 3.5-7.8 mmol/L). 16 women provided data for 35 trimesters pre ISS and 17 women provided data for 38 trimesters post ISS. There was an improvement in pregnancy-specific time-in-range for trimester 3 following the commencement of an intensive weekly insulin stabilization service (mean pre 49.6%, post 61.4%, p=0.042). Similar results were seen when women using hybrid closed loop technology were excluded, albeit not then reaching statistical significance. It was not possible to assess the effect of the intervention on the first trimester. There were no statistically significant changes in glycaemia for trimester 2. Conclusions: In a small group of pregnant women with type 1 diabetes, improvement in pregnancy specific time-in-range occurred in trimester 3, but not in trimester 1 or 2, following the introduction of intensive weekly clinical support.

Obesity is one of the world's major public health challenges. Its pathogenesis and comorbid metabolic disorders share common mechanisms, such as mitochondrial or endoplasmic reticulum dysfunction or oxidative stress, gut dysbiosis, chronic in-flammation and altered autophagy. Numerous pro-autophagy dietary interventions are being investigated for their potential obesity-preventing or therapeutic effects. In this review, we summarize current data on the relationship between autophagy and obesity and discuss various non-pharmacological dietary interventions as regu-lators of autophagy-related genes in the prevention and ultimately treatment of obe-sity in humans, available in scientific databases and published through July 2024. Lifestyle modification (such as calorie restriction, intermittent fasting, physical exer-cise), a diet rich in flavonoids, antioxidants, specific fatty acids, specific amino acids and others have shown a beneficial role in the induction of this process. Induction of autophagy by heterogeneous interventions elicits a relatively homogeneous response characterized by activation of specific kinases (AMPK, IKK, JNK1, TAK1, ULK1, VPS34), inhibition of others (such as mTORC1), protein deacetylation reactions (at least in part providing SIRT1 activation and/or EP300 inhibition), and reversal of in-hibitory interactions such as those between BECN1 and members of the Bcl-2 family.

The female pelvis is often evolutionarily described as a compromise to accommodate the birthing process and bipedalism. This compromise puts a mother and baby at risk for fetopelvic disproportion, the mismatch between the size of the fetus and the mother's pelvis, impacting the ease at which the vaginal birthing process occurs. Obstructed labor, commonly caused by fetopelvic disproportion, is a leading cause of maternal mortality and morbidity and has serious medical sequelae for the fetus. In this review, this evolutionary aspect of fetopelvic disproportion is being reconsidered within a broader sociocultural and environmental approach related to a change of paradigm from a more reductionist Neo-Darwinist to a more encompassing Extended Evolutionary Synthesis view. The review explores a more comprehensive understanding of several factors related to fetopelvic disproportion, including socioeconomic factors and ethnic disparities amongst individuals that might lead to a higher likelihood of obstructed labor and maternal and fetal morbidity and mortality.

This study, based on proactive motivation theory, explores the relationship between perceived overqualification, digital leadership, and constructive deviant behavior, as well as generational differences. Using data collected in two waves from 596 employees, the results show that perceived overqualification positively influences constructive deviant behavior, and digital leadership enhances this effect. Employees born in the 1980s are most influenced by both factors, followed by those born in the 1990s, where the effect of digital leadership is less significant. The study suggests that effectively utilizing digital leadership and recognizing generational differences in perceived overqualification can help organizations better manage overqualified talent, improving employee satisfaction and productivity.

Background: Depression is a common disorder in older people. It affects their physical recovery and general well-being, leading to longer hospital stays and higher healthcare costs. Under-standing the prevalence of depression and its impact on functional outcomes in the population is crucial for improving strategies and patient care. This study aims to determine the prevalence of depression in elderly patients in geriatric rehabilitation and assess its impact on their functional abilities during the rehabilitation process; Methods: A retrospective cohort study was conducted at the Lucerne Cantonal Hospital Wolhusen, Switzerland, between 2015 and 2020, involving 1,159 patients aged 65 years and older. Depression was assessed using the Geriatric Depression Scale (GDS) Short Form, while functional abilities were measured using the Functional Independence Measure (FIM) and the Tinetti test. The data was analyzed using TIBCO Statistica 13.3, with sta-tistical significance set at p < 0.05; Results: The study found that 25.4% of participants had depressive symptoms, with higher rates in women (27.8%) than in men (21.2%). Based on FIM and Tinetti scores, these patients had lower functional abilities at admission and discharge. However, all patients, regardless of depression status, showed significant improvements in functional scores during rehabilitation; Conclusions: Depression is proving to be a problem in older people par-ticipating in geriatric rehabilitation that significantly impairs their functional progress. These findings underline the importance of recognizing and treating depressive symptoms to increase the effectiveness of rehabilitation and improve the well-being of older patients. Integrating mental health support into geriatric rehabilitation programs is critical to optimizing patient outcomes.

Interleukin-12 (IL-12) is considered to be a promising cytokine for enhancing anti-tumor immune response. However, recombinant IL-12 had significant toxicity and limited efficacy in early clinical trials. Recently, many strategies for delivering IL-12 to tumor tissues have been developed, such as modifying IL-12, utilizing viral vectors, non-viral vectors and cellular vectors. Previous studies have found that IL-12 fusion with extracellular matrix proteins, collagen and immune factors is a way to enhance its therapeutic potential. In addition, studies have demonstrated that viral vectors are a good platform, and a variety of viruses such as oncolytic viruses, adenoviruses and poxviruses have been used to deliver IL-12, and testing has been conducted in various cancer models. Local expression of IL-12 in tumors based on viral delivery avoids systemic toxicity while inducing effective anti-tumor immunity and acting synergistically with other therapies without compromising safety. Also, lipid nanoparticles are currently considered to be the most mature drug delivery system. Moreover, cells are also considered to be drug carriers because they can effectively deliver therapeutic substances to tumors. In this article, we will systematically discuss the antitumor effects of IL-12 on its own or in combination with other therapies based on different delivery strategies.

(1) Polycyclic aromatic hydrocarbons (PAHs) are hazardous organic compounds with known carcinogenic and toxic properties. Exposure to PAHs occurs through various sources, including diet, inhalation, and skin contact, and they can transfer into breast milk following maternal exposure, potentially endangering breastfeeding infants. (2) This study aimed to determine the PAH content in breast milk samples from 50 Hungarian mothers using high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The carcinogenic risk to infants was estimated using the Incremental Life Risk Calculation (IRCL) model. (3) Total PAH concentrations ranged from 0 to 78 ng/mL, with fluorene (5.3 ng/mL), phenanthrene (3.2 ng/mL), and pyrene (2.5 ng/mL) being the most abundant. PAHs were detected in 48 of the 50 samples, with phenanthrene present in 92% of samples. Dibenzo (a,h)anthracene was not detected. (4) Based on IRCL calculations, 10% of the samples were classified as safe, while 88% presented an acceptable carcinogenic risk for infants. Statistical analysis of questionnaires completed by the mothers indicated that factors such as diet, residence, and education may influence PAH levels in breast milk.

Post-transplant lymphoproliferative disorders (PTLD) pose significant risks following organ transplantation, characterized by potential aggressiveness. This report aims to discuss a case of PTLD presenting as B-cell large cell lymphoma (DLBCL) post-kidney and pancreas transplantation. A 44-year-old female with type 1 diabetes underwent kidney and pancreas transplantation. She presented with fever, night sweats, and weakness, revealing multiple lesions on CT, including in transplanted and native kidneys, pancreas and lung. Biopsy of transplant kidney confirmed PTLD, DLBCL subtype, with complex immunohistochemical findings. Chemotherapy (R-CHOP) was initiated but complicated by infusion reactions and bowel perforation necessitating surgery and antibiotics. Despite the complications, the normal function of the transplanted kidney is maintained, which made it possible to implement the standard chemotherapy protocol. This case underscores the diagnostic challenges and therapeutic complexities of PTLD, specifically DLBCL, in transplant recipients. Comprehensive evaluation and vigilant management are crucial for successful outcomes in such cases.

Basic education is a foundational component of the national education system and human resource development, providing crucial support for the sustainable development of various aspects of human society, including economy, social welfare, and technology. The advancement of basic education is intrinsically linked to national innovation, the well-being of the populace, and the sustainable high-quality development of society. Enhancing the ecological carrying capacity of basic education at the provincial level is critical and pragmatically significant for the coordinated, sustainable, and high-quality development of the region's socioeconomic landscape.Based on panel data from the Guangxi Zhuang Autonomous Region (hereinafter referred to as Guangxi) from 2013 to 2022, and utilizing the DPSIR theoretical model, a comprehensive evaluation index system has been established. Through statistical analysis and spatial analysis methods, this study explores the temporal and spatial evolution characteristics of the ecological carrying capacity of basic education in various regions under Guangxi's jurisdiction. A multiple linear regression model is employed to analyze the differential impacts of changes in economic structure on the ecological carrying capacity of basic education.The findings reveal a steady upward trend in the ecological carrying capacity of basic education across the municipal districts of Guangxi. The development of five subsystems—Pressure, Driving-force, and others—has also become increasingly balanced; however, the impact of each subsystem on the overall carrying capacity varies. From a formation mechanism perspective, the ecological carrying capacity of basic education in Guangxi is the result of the complex interactions of multiple factors, with notable differences in influencing factors at various stages of development.Therefore, to bridge the regional disparities in the ecological carrying capacity of basic education across the different areas of Guangxi, it is essential to adopt a range of measures that promote coordinated, balanced, and high-quality educational development among regions, effectively ensuring the long-term sustainable development of Guangxi's economy and society.

The utilization of sustainable biomaterials in pharmaceutical and medical applications has garnered significant attention in recent years due to their potential to address environmental concerns while meeting the demands of modern healthcare. This review provides a comprehensive overview of the latest advancements and applications of sustainable biomaterials in the pharmaceutical and medical fields. Beginning with an exploration of sustainable sourcing methods and production techniques, the review highlights the importance of eco-friendly practices in biomaterial development. Subsequently, it delves into the diverse range of sustainable biomaterials, including biopolymers, natural extracts, and bio-based nanoparticles, elucidating their properties and biomedical applications. Moreover, the chapter discusses the role of sustainable biomaterials in drug delivery systems, tissue engineering, wound healing, and medical device fabrication, emphasizing their biocompatibility, biodegradability, and therapeutic efficacy. Along with discussions on regulatory issues and commercialization prospects, the potential and challenges related to the integration of sustainable biomaterials into pharmaceutical and medical practices are also critically reviewed. By elucidating the advancements and potential of sustainable biomaterials, this article aims to inspire further research and innovation in the pursuit of environmentally friendly and effective solutions for healthcare applications.

The issue of managing waste bread is a global concern, with significant environmental and the economic implications. The utilisation of waste bread for bioethanol production, employing energy-saving tech-nology, could prevent these consequences and reduce the consumption of traditionally used fossil fuels. The objective of this study was to evaluate the influence of the type of waste bread (wheat and wheat-rye sourdough) and the mash preparation method on the results of alcoholic fermentation and the concen-tration of selected congeners in the distillates. The highest fermentation efficiency (96% of theoretical) was achieved for both types of bread through the utilisation of the pressureless starch liberation method combined with simultaneous saccharification and fermentation. The separate saccharification of starch did not result in an enhanced efficiency of the process. Despite a slight reduction in efficiency of the process, the hydrolysis of native starch was regarded as a promising solution for the processing of waste bread to ethanol. All of the obtained distillates exhibited a low concentration of methanol. The elevated acidity and aldehydes levels, in relation to the national recommendations, indicate the potential necessity for the separation of the volatile congeners depending on the intended use of the obtained spirit distillates.

There is a global demand for alternative energy sources away from unsustainable fossil fuels. COP26 agreed that fossil fuels should be phased down; at COP27, anxiety about the cost and availability of energy was raised, and COP28 reiterated the phasedown of coal power. Solar technology in the form of Perovskite solar cells is one such alternative energy source. This article considers the fabrication of the Perovskite layer in a solar cell and postulates the extent to which Material Flow Cost Accounting (MFCA) could be used as a feasible costing method, among other things, to address byproduct and waste generation. Through MFCA, the monetary and physical flows of materials are identified and can be applied throughout the supply chain to facilitate affordability, from the extraction of the ore, transportation, fabrication of the chemicals, manufacturing and distribution of the solar cell and panels, and finally, the recycling of the panel. Informed by these observations, a conceptual framework for applying MFCA in fabricating the Perovskite layer in the supply chain is developed based on sets of qualitative propositions. Future work will be researching the processes of manufacturing solar cells, costing raw materials, energy flows, and solar cell manufacturing emissions.

Statins are the main cholesterol-lowering treatments, but often they are stopped because of statin myopathy. Expensive second-line treatments are then prescribed, causing a burden on the health system. Creatine supplementation may be a safe, effective and cheap alternative this shift. We investigated tolerability and possible effectiveness of creatine supplementation in statin myopathy. Our data confirmed previous findings showing that creatine supplementation is safe and well tolerated even in this elder population. In fact, 11 of the 13 enrolled patients completed the study, and only one patient interrupted the study because of a creatine-related issue (elevation of serum creatinine). Creatine supplementation significantly reduced the Shewmon and Craig’s “myopathy score”, while it did not reduce serum creatine kinase (CK), a marker of muscle structural damage. Notably, creatine supplementation was effective at the dose of 1g. t.i.d., lower that usually prescribed in international literature and within the recommendations of health agencies like the Italian Ministry of Health. Thus, creatine supplementation may improve statin myopathy in its milder and/or earlier form, when serum CK is not elevated. Moreover, creatine supplementation may prevent or delay switching from statins to the very expensive second-line anti-cholesterol treatments.

Cyclic peptides have higher stability and better properties as therapeutic agents than their linear peptide analogues. Consequently, intramolecular click chemistry is becoming an increasingly popular method for the synthesis of cyclic peptides from their isomeric linear peptides. However, assessing the purity of these cyclic peptides by mass spectrometry is a significant challenge, as the linear and cyclic peptides have identical masses. In this paper, we have evaluated the analytical capabilities of energy-resolved mass spectrometry (ER MS) and mid-infrared microscopy (IR) to address this challenge. On the one hand, mixtures of both peptides were subjected to Collision Induced Dissociation tandem mass spectrometry (CID MS/MS) experiments in an ion trap mass spectrometer at several excitation energies. Two different calibration models were used: a univariate model (at a single excitation voltage) and a multivariate model (using multiple excitation voltages). The multivariate model demonstrated slightly enhanced analytical performance, which can be attributed to more effective signal averaging when multiple excitation voltages are considered. On the other hand, IR microscopy was used for the quantification of the relative amount of linear peptide. This was achieved through univariate calibration, based on the absorbance of an alkyne band specific to the linear peptide, and through Partial Least Squares (PLS) multivariate calibration. The PLS calibration model demonstrated superior performance in comparison to univariate calibration, indicating that consideration of the full IR spectrum is preferable to focusing on the specific peak of the linear peptide. The advantage of IR microscopy is that it is linear across the entire working interval, from linear peptide molar ratios of 0 (equivalent to pure cyclic peptide) up to 1 (pure linear peptide). In contrast, the ER MS calibration models exhibited linearity only up to 0.3 linear peptide molar ratio. However, ER MS showed better performances in terms of limit of detection, intermediate precision and root-mean-square-error of calibration. Therefore, ER MS is the optimal choice for the detection and quantification of the lowest relative amounts of linear peptide.

This study investigates user behavior in urban green spaces (UGS) in downtown Shanghai prior to the COVID-19 pandemic. UGS are essential public infrastructure, contributing to urban sustainability, quality of life, and social cohesion. Although widely studied, there remains a gap in urban studies and environmental behavior research regarding UGS use from the perspective of space appropriation. This study addresses this by analyzing user demographics, frequency, and spatial activity patterns to assess how different forms of space use can be evaluated across varying levels of appropriation. Using a mixed-methods design, non-participant observation and behavior mapping were conducted across three comprehensive parks in Shanghai, divided into nine observation zones. Data were analyzed using the Pandas library in Python 3.6, descriptive statistics, and qualitative coding. Findings revealed sixty distinct activity types, predominance of elderly male users, absence of teenagers, and activity peaks in the early morning and late after-noon. Structured patterns of engagement suggest a soft to moderate level of appropriation. This research underscores the effectiveness of observational methods, validates appropriation as an analytical category, and emphasizes the importance of structured classification systems for improving understanding of UGS use and its societal role.

This paper investigates the integration of Graph Neural Networks (GNNs) and incremental learning for blockchain applications, with a focus on fraud detection, anomaly detection, and smart contract verification. By leveraging graph structure exploitation, GNNs can propagate information across nodes, reducing label dependency. Incremental learning enhances the model's adaptability to evolving blockchain networks, allowing continual learning without full retraining. Together, these technologies provide a scalable, efficient solution for improving security, performance, and adaptability in decentralized financial systems and smart contract environments.

Background/Objectives: Thyroid cancer, particularly well-differentiated thyroid cancer, is one of the most prevalent endocrine malignancies, with a rising incidence. Although it generally has a favorable prognosis, recurrence is common. Accurate prediction of recurrence is crucial for optimizing treatment plans and improving patient outcomes. This study aimed to advance the state-of-the-art in thyroid cancer recurrence prediction by refining feature engineering techniques and exploring a diverse ensemble of machine learning algorithms and an artificial neural network, using the differentiated thyroid cancer dataset from the UCI Machine Learning Repository; Methods: Various unsupervised data engineering methods, such as dimensionality reduction and clustering, were employed to enhance feature quality and mitigate noise, using stratified 10-fold cross-validation. The best-performing dimensionality reduction techniques were used to build classification model pipelines employing each of several machine learning models and an artificial neural network. The performance of these classification pipelines were assessed using metrics sensitive to class imbalance; Results: Principal Component Analysis and Truncated Singular Value Decomposition achieved superior clustering performance and moderate variances in their first principal components. Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, and Feedforward Neural Network models all achieved high performance, with Logistic Regression pipelines demonstrating balanced accuracy, F1 score, AUC, sensitivity, specificity, and precision—all greater than 0.93 on the test set and slightly lower in 10-fold cross-validation. Gradient Boosting classification pipelines performed the lowest, though still with respectable metrics; Conclusions: This study shows that employing feature engineering techniques like Principal Component Analysis or Truncated Singular Value Decomposition in Logistic Regression, Random Forest, Feedforward Neural Networks, Support Vector Machine, and K-Nearest Neighbors classification pipelines can improve thyroid cancer recurrence prediction accuracy and reliability, supporting more personalized treatment strategies in post-treatment patients.

In this paper, we conduct a comprehensive analysis of the RounD dataset to enhance the understanding of motion forecasting for autonomous vehicles in complex roundabout environments. We implement a trajectory prediction framework that combines Long Short-Term Memory (LSTM) networks with graph-based modules to model vehicle interactions. Our primary objective is to assess the generalizability of a standard trajectory prediction model across diverse training and testing datasets. Through extensive experiments, we analyze how varying data distributions, including different road configurations and recording times, influence the model’s prediction accuracy and robustness. This study provides key insights into the challenges of domain generalization in autonomous vehicle trajectory prediction.

Companies operating in the PayTech and online e-commerce sectors play a crucial role in critical infrastructure, functioning within the dynamic digital landscape. This study focuses on the recovery process after cyber-attacks and examines the contrasting perspectives of internal and external professionals. The research reveals notable differences in the perceptions of recovery strategies between internal stakeholders such as investor relations, reputation management, and Chief Information Security Officers, representing companies belonging to critical infrastructure and external auditors, who provide just and emergency support and perform specific tasks. Importantly, the study underscores the current attitudes towards future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company's internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors.

There is a pressing need for tools that can rapidly predict PM2.5 concentrations and assess health impacts under various emission scenarios, aiding in the selection of optimal mitigation strategies. Traditional chemical transport models (CTMs) like CMAQ are accurate but computationally intensive, limiting practical scenario analysis. To address this, we propose a novel method integrating a conditional U-Net surrogate model with health impact assessments, enabling swift estimation of PM2.5 concentrations and related health effects. The U-Net model was trained with 2019 South Korean PM2.5 data, including precursor emissions and boundary conditions. Our model showed high accuracy and significant efficiency, reducing processing times while maintaining reliability. By combining this surrogate model with the EPA’s BenMAP-CE tool, we estimated potential premature deaths under various emission reduction scenarios in South Korea, extending projections to 2050 to account for demographic changes. Additionally, we assessed the required PM2.5 emission reductions needed to counteract the increase in premature deaths due to an aging population. This integrated framework offers an efficient, user-friendly tool that bridges complex air quality modeling with practical policy evaluation, supporting the development of effective strategies to reduce PM2.5-related health risks and estimate economic benefits.

Interactive device design traditionally prioritizes delaying or preventing degradation during the functional phase, as it is generally perceived as a disadvantage. However, the concept of intentionally designing controlled material breakdown can unlock new properties and functions that enhance both the system and its environment. This approach, termed "Degrade to Upgrade", challenges the conventional view of degradation as merely an end-of-life process. Instead, it encourages Human-Computer Interaction (HCI) researchers and designers to see it as an active phase, one that can be leveraged for innovative device design.

Evaluating altered mental status and suspected meningeal disorders in children often begins with imaging, typically before a lumbar puncture. The challenge is that meningeal enhancement is a common finding across a range of pathologies, making diagnosis complex. This review proposes a categorization of meningeal diseases based on their predominant imaging characteristics. It includes a detailed description of the clinical and imaging features of various conditions that lead to leptomeningeal or pachymeningeal enhancement in children and adolescents. These conditions encompass infectious meningitis (viral, bacterial, tuberculous, algal, and fungal), autoimmune diseases (such as anti-MOG demyelination, neurosarcoidosis, Guillain-Barré syndrome, idiopathic hypertrophic pachymeningitis, and NMDA-related encephalitis), primary and secondary tumors (including diffuse glioneuronal tumor of childhood, primary CNS rhabdomyosarcoma, primary CNS tumoral metastasis, extracranial tumor metastasis, and lymphoma), tumor-like diseases (Langerhans cell histiocytosis and ALK-positive histiocytosis), vascular causes (such as pial angiomatosis, ANCA-related vasculitis, and Moyamoya disease), and other disorders like spontaneous intracranial hypotension and posterior reversible encephalopathy syndrome. Despite the nonspecific nature of imaging findings associated with meningeal lesions, narrowing down the differential diagnoses is crucial, as each condition requires a tailored and specific treatment approach.

Introduction: Intraductal papillary mucinous neoplasms (IPMN) are commonly-detected pancreatic cysts that may transform into pancreatic ductal adenocarcinoma (PDAC). Predicting which IPMNs will progress to PDAC remains a clinical challenge. Moreover, identifying those clinically evident IPMNs for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of a IPMN to identify novel molecular pathways related to IPMN-derived PDAC that could help guide biomarker development. Methods: Data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project was utilized to analyze 66 PDAC cases from Moffitt Cancer Center and The Ohio State University Wexner Medical Center for which tumor whole transcriptome sequencing datasets were generated. Cases were classified based on whether a tumor had originated from an IPMN (n=16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway (n=50). We then performed differential expression and pathway analysis using Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Downweighted Genes (PADOG) algorithms. We also analyzed immune profiles using the Tumor-immune Microenvironment Deconvolution Web-portal for Bulk Transcriptomics (TIMEx). Results: Both GSEA and TIMEx indicate that PanIN-derived PDAC tumors enrich inflammatory pathways (complement, hedgehog signaling, coagulation, inflammatory response, apical surface, IL-2/STAT5, IL-6/STAT3, EMT, KRAS signaling, apical junction, IFN-gamma, allograft rejection) and are comparatively richer in almost all immune cell types than those from IPMN-derived PDAC upon deconvolution. IPMN-derived tumors were enriched in metabolic and energy generating pathways (oxidative phosphorylation, unfolded protein response, pancreas beta cells, adipogenesis, fatty acid metabolism, protein secretion). Further, the metabolic-linked gene signature enriched in the IPMNderived samples is associated with a cluster of early stage and long survival (top 4th quartile) PDAC cases from the Cancer Genome Atlas (TCGA) expression database. Intriguingly, the gene most significantly upregulated for both the improved survival group and IPMN-derived PDAC was gastrokine-2 (GKN2, padj<0.001), a gene upregulated in PDAC precursor lesions (compared to PDAC). Conclusions: Our data suggest that IPMN-derived and PanIN-derived PDACs differ in the expression of immune profiles and metabolic pathways. These initial findings support future studies to assess the accuracy of identifying PDACs arising from IPMN lesions based on either GKN2 expression or their metabolic or immune profiles and explore mechanisms to explain these findings.

The relationship between Portugal and England spans centuries, encompassing political alliances, economic cooperation, cultural exchanges, and significant periods of tension and exploitation. This article provides a comprehensive and critical overview of the historical relations between Portugal and England from medieval times to the present, highlighting both the cooperation and the conflicts that have shaped this complex alliance. It explores key events, treaties, and figures that have influenced the trajectory of the relationship, including the heavy indebtedness Portugal accumulated with England and how this debt was transferred to Brazil in exchange for its independence—a factor that perpetuated social distortions such as slavery and inequality in Brazil. The article also discusses the contemporary context of Portugal-England relations, emphasizing the continued importance and challenges of this partnership in the modern world.

Physical inactivity is a leading risk factor for non-communicable diseases. Climate change is now regarded as the biggest threat to global public health. Electric micromobility (e-micromobility, including e-bikes e-cargo bikes and e-scooters) has the potential to simultaneously increase people’s overall physical activity while decreasing greenhouse gas emissions where it substitutes for motorised transport. The ELEVATE study aims to understand the impacts of e-micromobility, including identifying the people, places and circumstances where they will be most beneficial in terms of improving people’s health while also reducing mobility-related energy demand and carbon emissions. A complex mixed methods design collected detailed quantitative and qualitative data from multiple UK cities. First, a nationally representative (n=2000), city-wide (n = 1200) and targeted study area surveys have collected data on travel behaviour, levels of physical activity, vehicle ownership and use as well as attitudes towards e-micromobility. Then, to provide insights on an understudied type of e-micromobility, 49 households have been recruited to take part in e-cargo bike one-month trials. Self-reported data from participants are validated with objective data using methods such as GPS trackers and smartwatches recording of routes and activities. CO₂ impacts of e-micromobility use are also calculated. Participant interviews provided detailed information on preferences, expectations, experiences, barriers and enablers of e-micromobility.

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

You Only Look One (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. However, because of the diverse characteristics of YOLO models, choosing selecting the optimal model according to various applications and environments in smart transportation is critical. In this article, we conduct an empirical evaluation and analysis study for most YOLO versions to assess their performance in smart transportation. To achieve this, we first measure the average precision of YOLO models across multiple datasets (e.g., COCO, PASCAL VOC). Second, we analyze the performance of YOLO models on multiple object categories within each dataset, focusing on classes relevant to road transportation such as those commonly used in smart transportation applications. Third, multiple intersection-over-union (IoU) thresholds are considered in our performance measurement and analysis. By examining the performance of various YOLO models across datasets, IoU thresholds, and object classes, we make six observations on these three aspects while aiming to identify optimal models for road transportation scenarios. Thus, YOLOv5 and YOLOv8 outperform other models in all three aspects due to their novel performance features. For instance, YOLOv5 achieves stable performance thanks to its cross-stage partial darknet-53 (CSPDarknet53) backbone, auto-anchor mechanism, and efficient loss functions including IoU loss, complete IoU loss, focal loss, gradient harmonizing mechanism loss. Similarly, YOLOv8 outperforms others with its upgraded CSPDarknet53 backbone, anchor-free mechanism, and efficient loss functions like complete IoU loss and distribution focal loss.

Text CAPTCHAs are crucial security measures employed on global websites to deter unauthorized intrusions. The presence of anti-attack features incorporated into text CAPTCHAs limits the effectiveness of breaking them, despite CAPTCHA recognition being an effective method for assessing their security. This study introduces a novel color augmentation technique called Variational Color Shift (VCS) to boost the recognition accuracy of different networks. VCS generates a color shift range of every input image and then resamples the image within that range to generate a new image, thus expanding the number of samples of the original dataset to improve training effectiveness. In contrast to Random Color Shift (RCS) which treats the color offsets as hyperparameters, VCS uses the estimated offsets to reparametrize the points sampling from the unit uniform distribution to reconstruct new image pixels, which makes the offsets learnable. To reduce the computational effort of VCS, we also propose two variants of VCS: Sim-VCS and Dilated-VCS. In addition, to solve the overfitting problem caused by many disturbances in CAPTCHAs, we propose an Auto Encoder (AE) based on a Large Separable Kernel Attention (AE-LSKA) to replace the convolutional module in the text CAPTCHA recognizer. This new module employs an AE) to compress the interference while expanding the receptive field using Large Separable Kernel Attention (LSKA), which reduces the impact of local interference on the model training and improves the overall perception of characters. The experimental results show that the recognition rate of the model after integrating the AE-LSKA module is improved by at least 15 percentage points on both M-CAPTCHA and P-CAPTCHA datasets. In addition, experimental results demonstrate that color augmentation using VCS is more effective in enhancing recognition.

Thorium is a weak radioactive element, but the control of its concentration in natural aqueous systems is of great interest for health, because it is a toxic heavy metal. The present paper presents the recovery of thorium from diluted synthetic aqueous systems by nanofiltration. The membranes used for nanofiltration of systems containing thorium species are composites containing 4′-Aminobenzo-15-crown-5 ether (ABCE) and sulfonated poly–ether–ether–ketone (sPEEK). The composite membranes (ABCE–sPEEK) were characterized by scanning electron microscopy (SEM), energy dispersive X–ray spectroscopy EDAX, thermal analysis (TG and DSC) and from the perspective of thorium removal performance. To determine the process performances, the variables were: the nature of the composite membrane, the concentration of thorium in the aqueous systems, the rotation speed of the stirrer, the pressure and the pH of the thorium aqueous system. When using pure water, a permeate flux value of 12 L·m⁻2 h⁻1 was obtained for sPEEK membrane, and up to 15 L·m⁻2 h⁻1 for the ABCE–sPEEK composite membrane. The use of mechanical stirring, with a propeller stirrer, leads to an increase in the permeate flux of pure water by about 20 % for each of the studied membrane. Depending on the concentration of thorium and the pH of the feed solution, retentions between 84.9 % and 98.4 % were obtained. An important observation is the retention jump at pH 2 for the ABCE–sPEEK composite membrane. In the paper, a thorium ion retention mechanism is proposed for the sPEEK membrane and the ABCE–sPEEK composite membrane.

This study examines the transformative potential of Artificial Intelligence (AI) in international trade, highlighting its significant roles in optimizing trade operations, enhancing trade finance, and improving market access. In trade optimization, through advanced machine learning and predictive analytics, AI helps in demand forecasting, route optimization, and customs processes, ensuring efficient logistics and inventory management. In trade finance, AI automates document processing and risk assessment, democratizing access to finance and enhancing transactional transparency through integration with blockchain technology. In improving market access, AI-driven analytics identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. The study includes case studies of leading companies such as Alibaba, DHL, and Maersk, showcasing how they leverage AI to enhance their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI's practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include data quality, ethical considerations, technological complexity, and public perception. Ensuring high-quality, accessible data, fostering ethical AI usage, and overcoming technological and regulatory barriers are crucial for successful AI integration. Policy recommendations emphasize the need for robust data infrastructure, ethical AI guidelines, and international cooperation to harmonize data protection regulations. These measures aim to create an environment conducive to AI-driven sustainable economic growth and innovation in global trade.

As interest in renewable fuels grows, biomass has gained increasing attention for its potential applications. Understanding the kinetic and thermodynamic parameters of biomass pyrolysis and combustion are crucial for optimizing its valorization. In this study, TGA was employed to examine bamboo powder's pyrolysis and combustion behaviors under different temperature ramps in nitrogen and air environments. The TG and DTG curves reveal that bamboo pyrolysis occurs in three distinct stages: drying, devolatilization, and carbonization. Similarly, combustion also proceeds through three stages: drying, devolatilization, and char combustion. Notable differences in the temperature ranges of the key stages were observed between pyrolysis and combustion. Moreover, kinetic parameters were evaluated using the KAS, FWO, and STR model-free approaches. The findings indicate that, the activation energy during the oxidative devolatilization stage of combustion are notably lower compared to those during pyrolysis devolatilization. The disparity in activation energy is even more pronounced in the third stage. Thermodynamic analysis shows that the pyrolysis and combustion of bamboo are endothermic and non-spontaneous. It can be stably converted into value-added energy through pyrolysis or combustion process. This study provides essential data to aid in designing and scaling up the thermochemical conversion processes for bamboo.

Abstract—Traditional automatic modulation classificationmethods operate under the closed-set assumption, which provesto be impractical in real-world scenarios due to the diversenature of wireless technologies and the dynamic characteristicsof wireless propagation environments. Open-set environments introduce substantial technical challenges, particularly in terms ofdetection effectiveness and computational complexity. To addressthe limitations of modulation classification and recognition inopen-set scenarios, this paper proposes a semi-supervised openset recognition approach, termed SOAMC (Semi-SupervisedOpen-Set Automatic Modulation Classification). The primaryobjective of SOAMC is to accurately classify unknown modulation types, even when only a limited subset of samples ismanually labeled. The proposed method consists of three keystages: (1) A signal recognition pre-training model is constructedusing data augmentation and adaptive techniques to enhancerobustness. (2) Feature extraction and embedding are performedvia a specialized extraction network. (3) Label propagation isexecuted using a graph convolutional neural network (GCN) toefficiently annotate the unlabeled signal samples. Experimentalresults demonstrate that SOAMC significantly improves classification accuracy, particularly in challenging scenarios with limitedlabeled data and high signal similarity. These findings are criticalfor the practical identification of complex and diverse modulationsignals in real-world wireless communication systems.

BackgroundContextualising the narrative on energy efficiency as the first fuel in the clean energy transition, the energy efficiency first principle (EE1) was introduced in EU energy and climate policy with the Energy Union communication in 2015 and made nonbinding with the EU Governance Regulation in 2018. In 2023, the EU legislators made EE1 legally binding to apply in policy, planning and investment decisions exceeding 100 million euros each and 175 million euros in the transport sector across all sectors that affect the energy system. Understanding the process through which new legislation is developed and adopted is important for understanding the policy itself, why it was designed in the way it was. Understanding the contextualisation of EE1 is particularly important since it introduced a paradigm shift in EU energy and climate policy. Better knowledge of the process of transformative policy change is important for policy and governance towards a clean energy transition for climate neutrality.ResultsApplying the multiple streams framework as a theoretical lens for analysing policy processes, this paper determines the policy process and the agency of policy entrepreneurs to make EE1 legally binding, from problem formulation to final adoption. Based on qualitative text analysis of policy documents, position papers and reports from EU negotiations, combined with interviews of key actors, the study shows how non-profit and non-governmental organisations such as the Regulatory Assistance Project (RAP), the European Climate Foundation (ECF) and the Energy Efficiency Financial Institutions Group (EEFIG), as well as the European Commission and the rotating Council Presidency, were critical policy entrepreneurs for coupling the problem, policy and politics streams. RAP together with ECF and EEFIG considered the unequal treatment of energy supply and energy demand in energy policy to hamper efficient use of the energy system and suggested the EE1 principle to overcome this problem. Using a broad set of strategies related to cultural-institutional entrepreneurship, such as attention- and support seeking strategies, linking strategies, relational management strategies, and arena strategies, they persuaded the European Commission to propose legislation on EE1. But the initial framing was too technical. for decision-makers to understand. The coupling of the problem–policy package to politics was performed once a policy window was opened by external and internal events such as the Paris Agreement on climate change, the entering office of the Ursula von der Leyen European Commission in late 2019, and the energy crisis in Europe following Russia’s second war on Ukraine. Climate change and security of supply were problems that decision-makers could understand. ConclusionsIt is concluded that coalition-building is important for policy entrepreneurs to gain broad acceptance for their policy proposals. In addition, timing is of great importance for policy entrepreneurs being able to couple a package of problems and policy solutions to the political stream. Political decision-makers must be receptive to the problem and its policy solution. This happens when a policy window of opportunity is opened. In this case, the policy entrepreneurs proposed a solution to what they perceived of as a problem almost seven years before the politics stream was mature and receptive. This led policy entrepreneurs to use ‘salami tactics’ to sequentially introduce policy change whit bits and pieces of the proposed policy instrument being implemented over a long period. It also highlights the need for endurance of policy entrepreneurs.But the study also raises ethical issues that policy entrepreneurship may not only be positive to democratic governance for the clean and just energy transition. The agency of policy entrepreneurs is often technocratic and non-transparent, and they take the role of political decision-makers but with no formal decision-making power, reducing possibilities to claim accountability, legitimacy and justice.

The dynamics of society is enabled, in large part, through an efficient matching between people who have money to lend and people who have a need to borrow. Fair loans serve both the lender and the borrower. This task is handled today mostly via traditional banks. They offer various plans to depositors from whence they serve borrowers. Proposing to replace such rigidity with cyberspace-rooted dynamic ad-hoc global matching of lenders and borrowers. Uniquely here we build a chain of lenders to support a single borrower. Lenders will post a proposition to lend a given amount of money for a stated duration for a set interest rate. Borrowers will post a request to borrow a desired amount of money, for a specified duration, and for which they are ready to pay a stated interest. A virtual digital bank (VDB) will match all the posts, negotiate terms as necessary, and move the money -- everyone benefits. Distributed Digital Lending, DDL, applies to macro, long terms loans, as well as to micro. very short terms loans. DDL efficiency will ensure that all money at rest will be money in growth, and the full global lending capacity will be put to good service through the exact loans borrowers want. DDL is hinged in digital transactions which are immediate, irrevocable, and private, per regulatory allowance. The matching is optimized with AI tools. BitMint*LeVeL is the design standard coin for DDL, but other digital money options will do too.

This study examines the current functioning of Health Care Bioethics Committees (HBCs) in Chile, with the objective of providing recommendations for improving public health care management. Through a comprehensive literature review and a case analysis of the ‘Hospital Clínico de la Universidad de Chile’, the structure, functions and challenges of the CEA are explored. The research reveals the importance of the multidisciplinary composition of the committees, the need for continuing education in bioethics, and the relevance of the consultative role in ethical decision making. The results suggest that the effectiveness of CABs does not necessarily depend on the number of members or the length of their terms of office, but on the quality of their training and experience. It is concluded that for adequate health care management, it is essential to strengthen the role of the CEA in the ethical education of health care personnel and in the development of institutional regulations, as well as to improve their visibility and accessibility within the Chilean health care system.

Recent advances in the research area of 3D magnetic topological solitons (hopfions) in restricted geometries are reviewed. The description of the magnetic solitons is based on macroscopic micromagnetic approach and the Landau-Lifshitz equation of the magnetization motion. The concepts of the gauge emergent vector potential and emergent magnetic field are widely used to calculate 3D topological charge (the Hopf index) of magnetic textures. The relation of the magnetic hopfions with classical field theory is demonstrated and a special role of the curvilinear toroidal coordinates in description of the hopfions is underlined. The hopfion stability and dynamics in ferromagnetic films and dots are considered. Some critical discussion of calculations of the magnetization emergent magnetic field and the Hopf index of the toroidal magnetic hopfions in restricted geometries is presented.

With consumers increasingly aware of the effects of human activity on the environment, tourism products and destinations are increasingly marketed as sustainable and socially responsible. As most sustainable practices lead to additional costs, and tourists’ decisions tend to be price sensitive, achieving sustainability goals necessarily involves understanding how much tourists are willing to pay extra for sustainable practices, as well as the antecedents of such Willingness to Pay (WTP). The present study aims to advance knowledge on the antecedents of WTP for Sustainable Destinations (WTP-4-SD), for which it builds on previous studies employing the Theory of Planned Behavior (TPB) and the New Environmental Paradigm (NEP). In this context, a theoretical model involving Ecotourism Attitudes, Environmental Beliefs, Climate Change-Related Risk Perceptions (CC-RRP), Environmental Concern During trip (ECDT), and Sustainable Consumption Behavior (SCB) as antecedents of WTP-4-SD is proposed. The model was tested based on data collected through an online survey, form a sample of 1,545 Spanish and Portuguese tourists, and analyzed through Structural Equations Modelling (SEM). The findings suggest that a cohesive set of attitudes and beliefs regarding the man-nature relationship, the risks of climate change and the role of tourism – which have been labelled “No Planet-B Attitudes” – is the main driver of WTP-4-SD.

Volunteering has many social, emotional and health benefits and could be an option for people with younger/early onset dementia to engage in stage and age-appropriate, personally meaningful activities within their local communities. This study explored how people with young onset dementia volunteer in the UK, the benefits and barriers, and how we can improve access to volunteering opportunities. Audio data of people with young onset dementia discussing their experiences of volunteering were taken from the Dementia Diaries audio and video diary project (https://dementiadiaries.org/). The data were co-analysed by a co-production team, (X), made up of six researchers living with young onset dementia and two facilitators. The findings suggest that stigma is the overarching concept (or net) which influences people’s experiences of volunteering with dementia. Within the stigma net, three themes were developed that employed a lifespan approach to challenging said stigma: 1) Valuing the past, 2) Valuing the present and 3) Valuing the future, each with additional subthemes. This research contributes to the limited pool of literature that highlights the clear benefits of volunteering for people with young onset dementia, while also considering how dementia stigma can create practical and institutional barriers to accessing volunteering. Guidance is provided for how to deliver meaningful and accessible volunteering opportunities.

This article is aimed at studying new finite difference methods for one-dimensional (1D) and two-dimensional (2D) space Riesz variable-order (VO) nonlinear fractional diffusion equations (SRVONFDEs). In the presented model, fractional derivatives are defined in the Riemann-Liouville type. Based on 4-point weighted-shifted-Gr\"unwald-difference (4WSGD) operators for Riemann-Liouville constant-order (CO) fractional derivatives, which have a free parameter and have at least third order accuracy, we derive 4WSGD operators for space Riesz VO fractional derivatives. In order that the fully discrete schemes have good stability and can handle the nonlinear term efficiently, we apply the implicit Euler (IE) method to discretize the time derivative, which leads to IE-4WSGD schemes for SRVONFDEs. The stability and convergence of the IE-4WSGD schemes are analysed theoretically. In addiction, a parameter selection strategy is derived for 4WSGD schemes and banded preconditioners are put forward to accelerate the GMRES methods for solving the discretization linear systems. Numerical resutls demonstrate the effectiveness of the proposed schemes and preconditioners.

Biobutanol is becoming more relevant as a promising alternative biofuel, primarily due to its advantageous characteristics. These include a higher energy content and density compared to traditional biofuels, as well as its ability to mix effectively with gasoline, further enhancing its viability as a potential replacement. A viable strategy for attaining carbon neutrality, reducing reliance on fossil fuels, and utilizing sustainable and renewable resources is the use of biomass to produce biobutanol. Lignocellulosic materials have gained widespread recognition as highly suitable feedstocks for the synthesis of butanol, together with various value-added byproducts. The successful generation of biobutanol hinges on three crucial factors: effective feedstock pretreatment, the choice of fermentation techniques, and the subsequent enhancement of the produced butanol. While biobutanol holds promise as an alternative biofuel, it is important to acknowledge certain drawbacks associated with its production and utilization. One significant limitation is the relatively high cost of production compared to other biofuels, additionally, the current reliance on lignocellulosic feedstocks necessitates significant advancements in pretreatment and bioconversion technologies to enhance overall process efficiency. Furthermore, the limited availability of biobutanol-compatible infrastructure, such as distribution and storage systems, poses a barrier to its widespread adoption. Addressing these drawbacks is crucial for maximizing the potential benefits of biobutanol as a sustainable fuel source. This document presents an extensive review encompassing the historical development of biobutanol production and explores emerging trends in the field.

The study provides a comprehensive and detailed analysis of the existing key policies and considerations in Taiwan's Other Effective Area-Based Conservation Measures (OECMs), with the objective of providing useful evidence-based insights for formulating new effective environmental-friendly policies and promoting the existing policies. The study adopts a mixed research methodology that entails the combination of qualitative and quantitative research methodological frameworks. The primary source of the quantitative data for the study is the World Database on Protected Areas (WDPA) which provides variable data on OECMs and a component of databases of the Protected Planet Initiative (PPI) which is the joint product of UNEP and IUCN, managed by UNEP-WCMC and the IUCN working with governments, communities and collaborating partners. The qualitative methodological framework for the research adopted a technical systematic review approach based on the three-step framework for systematic reviews that involved planning, conducting and reporting the review. The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The sources that were included in the review included scientific research materials that focused on the policies related to OECMs. Taiwan has a total of 92 individual areas that are designated as national protected areas (PAs) and OECMs and formally recognized by the World Database on Protected Areas (WDPA). Out of the 92 designated areas, only seven are managed by the Construction and Planning Agency while the remaining 85 areas are managed by the Forestry Bureau. In terms of designation, 37 areas are designated as major wildlife habitats, 21 areas are designated as nature reserves, 20 areas are designated as wildlife refuges, eight areas are designated as national parks and six areas are designated as forest reserves. The primary themes that were identified were associated with marine spatial planning, environmental impact assessment (EIA) and marine scientific research and included biodiversity, protected area consideration, geographically defined areas, coastal resources and marine ecosystems. Other Effective Area-Based Conservation Measures (OECMs) have not been widely implemented yet, but most countries, including Taiwan, are increasingly aligning their existing policies with the strategies outlined in the OECMs policies to achieve large area-based conservation targets and reduce biodiversity loss.

Impulsive buying is a growing problem of modern society with significant financial and psychological consequences, and it is necessary to examine the mechanisms underlying it. Understanding the mechanisms driving this behaviour is crucial. Impulsive buying consists of two key aspects: a cognitive aspect, characterised by a lack of planning and reflection, and an affective aspect, involving emotional responses that can occur before, during, or after a purchase. This study aimed to explore the relationship between personality traits, as measured by the HEXACO model, and tendencies toward impulsive buying. Specifically, it examined how the HEXACO traits differentially predict the cognitive and affective components of impulsive buying tendencies.

In order to study the influence factors of vertical bearing capacity of pile foundation under the special address condition of multi-layer karst cave, the finite element model of foundation pile in double-layer karst area was established by using a commercial general finite element software Ansys, the bearing capacity of concrete pile foundation with different rock height, different ec-centricity and different elastic modulus under the gradually increasing load was studied. The results show that: (1) Under the condition of constant external load, the maximum displacement of pile foundation increases with the increase of eccentricity; (2) With the increase of concrete strength, the maximum displacement decreases gradually, but the corresponding maximum stress is roughly the same; (3) The height of the rock cave has a great influence on the bearing capacity of the pile foundation. In the construction process, it is necessary to minimize or avoid passing through the area with higher karst caves.

Around 1637, Pierre de Fermat famously wrote in the margin of a book that he had a proof for the equation $a^n + b^n = c^n$ having no positive integer solutions for exponents $n$ greater than 2. This statement, now known as Fermat's Last Theorem, remained unproven for centuries, despite the efforts of countless mathematicians. Andrew Wiles' work in 1994 finally provided a rigorous proof of Fermat's Last Theorem. However, Wiles' proof relied on advanced mathematical techniques that were far beyond the scope of Fermat's time, raising questions about whether Fermat could have truly possessed a proof using the methods available to him. Wiles's achievement was widely celebrated, and he was awarded the Abel Prize in 2016 in recognition of his groundbreaking work. The citation for the award described his proof as a "stunning advance" in mathematics. The present work offers a potential solution to Fermat's Last Theorem that may be more aligned with the original approach that Fermat claimed to have used.

Metabolic syndrome, obesity, and type 2 diabetes are closely related. They are characterized by chronic inflammation and oxidative stress. Obesity is the most important risk factor for metabolic syndrome and type 2 diabetes. Metabolic syndrome is characterized by insulin resistance and elevated blood glucose levels, among other conditions. These disorders contribute to the development of type 2 diabetes, which can exacerbate other metabolic disorders. Numerous studies indicate that diet and nutrients can have a major impact on preventing and treating these conditions. One such ingredient is lycopene. It exhibits antioxidant and anti-inflammatory effects and can affect metabolic processes in the body. According to the research presented, lycopene supplementation may have significant potential in the prevention and treatment of metabolic syndrome, obesity, and type 2 diabetes.

Neurotensin (NT) is a peptide involved in digestion, neuromodulation, and cancer progression. NT and its receptors (NTR1 and SORT1 mainly) have been widely studied in oncology. Data show NT expression is under the control of sex steroid hormones, in particular estradiol. We focused on its involvement in three main female hormone-sensitive cancers: breast, ovarian, and endometrial cancer in a narrative review. NT, NTR1 and SORT1 are mostly expressed in these three cancers and their involvement in oncologic processes such as proliferation and invasion seems to match, as does their impact on prognosis for most. The development of NT receptor-targeted therapies, including theranostics and radioligand treatments, presents a promising avenue for personalized cancer treatment.

Hybrid Power Switches (HPS) combine the advantages of SiC unipolar and Si bipolar devices and therefore can bridge the gap between these technologies. In this paper, the performance of a hybrid power switch configuration based on the latest SiC MOSFET and Si IGBT technologies is presented. The device is evaluated through experimental measurements of its characteristics under various conditions. The results show the HPS can achieve switching losses as low as a SiC MOSFET while offering the high current capability of the IGBT without significant increase in costs.

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

Background: Stroke is the third leading cause of disability, primarily due to motor, sensory, and cognitive impairments. Virtual reality (VR) has shown promising results in post-stroke rehabilita-tion, particularly for upper limb recovery. The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), aligned with the International Classification of Functioning, Disa-bility, and Health (ICF) principles, is a valid tool for measuring disability regardless of its cause. This study aimed to investigate the feasibility of VR TRAVEE system in upper limb rehabilitation for stroke patients. Methods: 14 stroke patients with residual hemiparesis were enrolled in the study. They underwent a 10-day program combining conventional therapy (CnvT) with VR rehabilitation. At baseline (T0), upper limb was assessed using the Modified Ashworth Scale (MAS), Active Range of Motion (AROM), and the Numeric Rating Scale (NRS) for pain. These assessments were repeated after the 10-day rehabilitation program (T1). Additionally, disability was measured using WHODAS 2.0 at T0 and again 30 days after completing the program. Results: Significant im-provements were observed in AROM, MAS scores for the shoulder, elbow, wrist, and metacar-pophalangeal joints as well as in the reduction of shoulder pain (p˂0.001). WHODAS scores de-creased across all six domains, with a statistically significant improvement in the cognition domain (p=0.011). Conclusions: Combining CnvT with VR as a rehabilitation approach enhances motor function in the upper limb. This method has the potential to reduce disability scores and promote neuroplasticity.

Excess sedentary behaviour (SB) and insufficient physical activity (PA) have been identified as risk factors for cardiometabolic diseases in adolescents, some factors may affect how much time they spent on these activities. This study sought to compare the SB and PA patterns as well as the compliance with PA recommendations by sex, geographical location, and time of the week in Mexican adolescents. In a cross-sectional design, we objectively assessed SB and PA in 106 adolescents (15 to 18 y) through waist-worn accelerometers for one week. The time spent in SB and in PA at different intensities was compared by sex, geographical location and time of the week with two-way and three-way repeated measures MANOVAs, while the compliance with physical activity recommendations (i.e. ≥60 min/day) was compared using chi-squared and McNemar tests. Male participants spent more time in moderate, vigorous, and moderate to vigorous PA than females both in the whole week and in weekdays (all p < 0.05). There was no significant difference in SB nor PA by geographical location (i.e., metropolitan vs non-metropolitan areas). Moreover, all participants spent more time on moderate, vigorous, and moderate to vigorous PA on weekdays than on weekends (p < 0.05). Compliance with international PA recommendations also showed a sex difference (males > females) and change between weekdays and weekends with no difference by geographical location. While geographical location does not seem to be a relevant factor, sex and time of the week appear to influence the SB and PA patterns in Mexican adolescents.

Chaos theory is widely used in the design of Pseudorandom Number Generators (PRNG), which produce number sequences with statistically uniform distributions and random appearance. However, certain methods for implementing chaotic maps can lead to dynamic degradation of the generated number sequences. To solve such problem, we develop a method for generating pseudo-random number sequences based on multiple one-dimensional chaotic maps. In particular, we introduce a Bernoulli chaotic map that utilizes function transformations and constraints on its control parameter, covering complementary regions of the phase space. This approach enables the generation of chaotic number sequences with a wide coverage of phase space, increasing uncertainty in the number sequence generation process. Moreover, by incorporating a scaling factor and a sinusoidal function, we develop a robust chaotic map, referred to as the Sine-Multiple Modified Bernoulli Chaotic Map (SM-MBCM), which ensures a high level of randomness, validated through statistical mechanics analysis tools. Using the SM-MBCM, we propose a Chaotic PRNG (CPRNG) and evaluate its quality through correlation coefficient analysis, key sensitivity tests, statistical and entropy analysis, key space evaluation, linear complexity analysis, and performance tests. Furthermore, we present an FPGA-based implementation scheme that leverages equivalent MBCM variants to optimize the electronic implementation process. Finally, we compare the proposed system with existing designs in terms of throughput and key space.

Reiner Gamma is a potential target for low-orbiting spacecraft or even surface-landed missions in the near future. Unfortunately, thus far no comprehensive low altitude (below 20 km) or surface measurements of the magnetic field, magnetic source and plasma environment have been made post-Apollo to complement and complete our understanding of the solar wind interaction with lunar magnetic anomalies and swirl formation. Acquiring the detailed geological knowledge of the Reiner Gamma region is significant for the above scientific targets. In this study, the following research work in the lunar Reiner Gamma magnetic anomaly region was carried out for the regional geological investigation: (1) the topographic and geomorphologic analysis; (2) elements, minerals and sequence analysis; (3) 1:10,000 regional geological map analysis. Our work helps define measurement requirements for possible future low-orbiting or surface-landed missions to the Reiner Gamma area or similarly magnetized regions of the lunar surface.