Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments and that there is a sudden transition from 3D vision to 2D vision. Regarding these transitions, the EEG signal analysis method was used for deep and comprehensive analysis of 2D and 3D brain signals. In this study, a single-stream anaglyph video of random 2D and 3D segments was prepared. After watching this single video, the obtained EEG recordings were considered for two different analyses: the part involving the critical transition (transition-state) and the state analysis of only the 2D versus 3D or 3D versus 2D parts (steady-state). The main objective of this study is to see the behavioral changes of brain signals in 2D and 3D transitions. To clarify the impacts of the human brain’s power spectral density (PSD) in 2D-to-3D (2D_3D) and 3D-to-2D (3D_2D) transitions of anaglyph video, 9 visual healthy individuals were prepared for testing in this pioneering study. Spectrogram graphs based on Short Time Fourier transform (STFT) were considered to evaluate the power spectrum analysis in each EEG channel of transition or steady-state. Thus, in 2D and 3D transition scenarios, important channels representing EEG frequency bands and brain lobes will be identified. To classify the 2D and 3D transitions, the dominant bands and time intervals representing the maximum difference of PSD were selected. Afterward, effective features were selected by applying statistical methods such as standard deviation (SD), maximum (max), and Hjorth parameters to epochs indicating transition intervals. Ultimately, k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms were applied to classify 2D_3D and 3D_2D transitions. The frontal, temporal, and partially parietal lobes show 2D_3D and 3D_2D transitions with a good classification success rate. Overall, it was found that Hjorth parameters and LDA algorithms have 71.11% and 77.78% classification success rates for transition and steady-state, respectively.

A growing number of households benefit from the government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefitting from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

Background: Alzheimer’s disease (AD), the most threatening neurodegenerative diseases, is characterized by the loss of memory and language function, an unbalanced perception of space and other cognitive and physical manifestations. Pathology of the AD is characterized by neuronal loss, and the extensive distribution of senile plaques and neurofibrillary tangles (NFTs). The role of environment and the diet in the AD is being studied actively, and nutrition is certainly one of the main factors playing a prominent role in the prevention of neurodegenerative diseases. In this context, the relationship between dementia and wine use/abuse has received increased research interest in recent times, with varying and often conflicting results. Scope and approach: This review aims to critically summarize the most recent studies conducted to clarify the relationship between wine drinking and AD, as well as whether effects are influenced by quantity and/or frequency of drinking. Key findings and Conclusion: Overall, based on the interpretation of various studies, it can be concluded that there is no indication that light to moderate alcohol drinking is detrimental to cognition and dementia, and it is not possible to define whether alcohol could be used as a means to reduce risk of developing AD.

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

We propose the traditional goal of cancer therapists to develop a single drug or drug combination that can, by itself, eliminate all cancer cells within a host has neglected potential treatments that may achieve curative outcomes by strategically combining agents that are individually effective but non-curative. We derive basic principles for such an approach from the eco-evolutionary dynamics of background extinctions in which a “first strike” reduces the size and heterogeneity of the initial population and is followed immediately by demographic and ecological “second strikes” that push the population below an extinction threshold. This proposed strategy appears identical to the empirically-derived curative therapy in childhood Acute Lymphocytic Leukemia.

Globally, public acceptance of waste-to-energy (WtE) incinerators is a crucial factor in implementing national waste-to-energy policies. This study adds to the literature on anti-incinerator sentiment by drawing upon an extended psychological-emotional model that integrates place-, trust-, and fairness-based pathways. A total of 338 residents in the Asuwei area in North Beijing completed a survey on a proposal to construct a WtE incinerator in the vicinity. Hierarchical regression analyses indicate that place attachment positively enhances anti-incinerator sentiment through direct effects, as well as through moderation and mediation effects between risk perception and opposing willingness. Further, institutional trust negatively moderates the impact of perceived risk on anti-incinerator sentiment, in addition to directly reducing perceived risk. Trust also influences anti-incinerator sentiment via risk perception, attesting to the effectiveness of a casual model of trust. Likewise, fairness perception acts as another determinant of opposing sentiment, similar to trust. We further reveal that procedural fairness plays a more significant role in predicting anti-incinerator sentiment than does distributional fairness. These findings demonstrate the importance of using a range of instrumental and more affective strategies to promote social acceptance of renewable energy infrastructure.

This paper deals with the techno-economic study of the hybrid renewable energy system based on energy storage aspect under the form of hydrogen and methane. Indeed, with the intermittency of the renewable energy sources such as photovoltaic and wind energy, several problems of produced energy injection to the power system network can be encountered due to the shortage or the excess of these sources. This situation appeals the use of systems that ensure the stability of network based on the storage of energy surplus into gas using electrolyzer systems, which will be used afterward to cover the eventual shortage. In the present paper, the study of performance of each pathway of methane and hydrogen storage has been performed by the treatment of multiple scenarios via different architecture case studies in an Algerian location. Whereas, the energy produced by the photovoltaic system, the wind energy and the gas micro turbine sources are considered similar in each case. The modeling and simulation of the studied system operation under optimization criteria has been performed in this work, where the main aim is to define the appropriate configuration taking into account the different with low costs of investment, maintenance operation and immediate reactivity with a big storage capacity.

Diffusion Models (DMs) are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech synthesis, and natural language processing due to their ability to produce high-quality samples. As DMs are being adopted in various domains, existing literature reviews that often focus on specific areas like computer vision or medical imaging may not serve a broader audience across multiple fields. Therefore, this review presents a comprehensive overview of DMs, covering their theoretical foundations and algorithmic innovations. We highlight their applications in diverse areas such as media quality, authenticity, synthesis, image transformation, healthcare, and more. By consolidating current knowledge and identifying emerging trends, this review aims to facilitate a deeper understanding and broader adoption of DMs and provide guidelines for future researchers and practitioners across diverse disciplines.

We study two fundamental linguistic channels ‒ the Sentences and the Interpunctions channels ‒ and show they can reveal deeper connections between texts. The theory applied does not follow the actual paradigm of linguistic studies. As study‒case, we consider the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in writing style (mathematically defined) of writers, and in reading skill required to their readers. The analysis is based on deep‒language parameters and communication/information theory. To set the New Testament texts in the larger Greek Classical Literature, we consider texts written by Aesop, Polybius, Flavius Josephus and Plutarch. The results largely confirm what scholars have found about the New Testament texts giving, therefore, credibility to the theory. The gospel according to John is very similar to Fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse, are each other “photocopy” in the two linguistic channels, and not linked to all other texts. These two texts deserve further study by historians of the early Christian Church Literature at the level of meaning, readers and possible Old Testament texts which might have influenced them. The theory can guide scholars to study any literary corpus.

Hubei, Hunan and Henan Provinces are located in Central China, a region with extensive transport networks and trade. Bursaphelenchus xylophilus, the causative agent of pine wilt disease, is spreads mainly through human activities. In order to further understand the genetic structure of PWN in Central China, we studied the genetic information of PWN populations in this region and compared the genetic relationship with strains from Guangdong and Jiangsu provinces. We found that the HB (Hubei) 15, HEN (Henan) 20, HN (Hunan) 07, HN08 and HN10 had significantly more SNPs and homozygotes than other strains from Central China, and their most frequent mutant genotypes also differed from other strains. The clustering results indicated that HB15, HEN 20, HN07, HN08 and HN10 were genetically distinct from other strains and closely related to Guangdong strains. We also observed significant genetic variation among strains in Henan province, suggesting that some of them might have different transmission sources than those from Hubei and Hunan provinces. The results provide a basis for tracing the origin and spread of PWD in China.

The salt marshes, lying at the land-sea temperate interface, furnish a plethora of ecosystems services such as biodiversity niche support, ocean-climate change regulation, ornithology recreo-tourism or plant gathering by hand. They undergo significant worldwide losses due to their conversion into crop fields and to their spatial compression between the rising sea-level and the armoring shoreline. Their monitoring however requires to use a suite of remote sensing sensors to embrace the regional scale while capturing the plant details. This research innovatively adopts a multiscale approach using a cascading spaceborne and airborne process, from the 10-m Sentinel-2, through the 3-m Dove, to the 0.03-m unmanned airborne vehicle (UAV) imageries. The high to very high temporal resolution of the Sentinel-2 and Dove enabled to cover twenties and tens of km2 over five and four years, respectively, in the form of normalized difference vegetation index (NDVI) classes, associated with microphytobenthos, low, medium and high salt marsh vegetation, including the opportunistic Elyma genus. The NDVI was then modelled at the UAV scale (a few km2) using a three-layered NN prediction, providing the final near-infrared (NIR), and the intermediate red, green and blue reflectance imageries, calibrated/validated/tested with the Dove reflectance imageries (R2NIR=0.98, R2red=0.88, R2green=0.84, and R2blue=0.90). The 100fold increase in pixel size allowed to detect the decimeter-scale objects of the tidal flats and salt marshes, to enlarge the NDVI class ranges, and hold great promise to model other spectral bands at the UAV scale for further deeply enhancing the salt marsh mapping.

Minimizing optical losses in resonant cavities is crucial for improving photonic device performance. This study focuses on the development of a simulation tool to analyze scattering losses in Fabry-Pérot interferometers (FPI), offering precise modeling of waveguide dynamics and contributing to accurate loss predictions across various platforms. Optical cavities often suffer from scattering losses due to surface roughness and material defects. Our approach integrates theoretical models and simulations to quantify these losses, utilizing the FPI as a model system. We identified upper and lower reflectivity thresholds, beyond which accurate measurement of losses becomes unreliable. For reflectivity below a certain threshold, measurement errors arise, while excessively high reflectivity can reduce fringe visibility and introduce detector sensitivity issues. Simulations were used to validate the model's ability to predict reflectivity and attenuation in waveguides with varying loss levels. The software’s flexibility to adjust transmission parameters for different cavity configurations enhances its utility for a broad range of photonic systems. Our study offers a novel methodology for optical loss analysis, with practical applications in optimizing photonic devices. By providing a reliable tool for precise loss measurement, this work supports advancements in optical technologies, enabling the design of more efficient, high-performance devices across various applications.

Poor therapeutic outcomes have been attributed to inter-individual and interethnic variability in cytochrome P450 (CYP450)-dependent metabolism and altered drug retention associated with P-glycoprotein (P-gp). An individualized pharmacotherapeutic approach would benefit the genetically diverse South African population. The study aim was to develop a validated, targeted, analytical method to quantify seven probe drugs and their metabolites in dried blood spots (DBS) using the Mitra™ volumetric absorptive micro-sampling device for blood collection. An Agilent liquid chromatography (LC) system coupled to a Sciex 4000 QTRAP tandem mass spectrometer (MS) was used for method optimization and validation. Targeted LC-MS/MS methods were validated according to ICH guidelines. The validated LC-MS/MS method met the required bioanalytical standards for specificity, sensitivity, linearity, accuracy, precision, carry-over, and stability. This study successfully validated the use of DBS, collected with the Mitra™ microsampling device, to measure expected probe drug and metabolite concentrations using the “Geneva phenotyping cocktail” for the purpose of simultaneous phenotyping of in vivo CYP450 metabolic activity of the CYP1A2, -2B6, -2C9, -2C19, -2D6, and -3A4 enzymes, and P-gp transport activity. However, statistical analysis using Bland-Altman plots showed that not all analytes exhibited linear distribution pharmacokinetics between DBS and plasma, which influenced the predicted vs real plasma concentrations based on measurements in a DBS matrix. These findings were attributed to the blood-to-plasma concentration ratio, the physicochemical properties and stability of the analytes, and the extraction efficiency of the Mitra™ sampler. More research is required before DBS sampling can be substituted for conventional plasma sampling

Starvation of photoreceptors induced by reduced dysregulated ocular blood flow is proposed as a common pathway for the pathogenesis of retinitis pigmentosa (RP). The current study evaluated the safety and efficacy of ophthalmic nerve stimulation (ONS) as an ocular blood flow neuromodulator, combined with ascorbic acid (AA) as a potent anti-oxidant in the treatment of RP. Additionally, the initial characteristics of rod responders were identified. Forty participants with simple, non-syndromic RP presented with a characteristic triad of RP (the bone spicule pigmentation, attenuation of retinal blood vessels, and waxy optic disc pallor), were en-rolled in a prospective open-label single-armed interventional study. The severity of the disease was clinically graded into six stages. Patients with an established diagnosis of RP; aged ≥ 4 years, with best corrected visual acuity (BCVA) ≥ 20/400 were included. All participants were daily treated with bilateral ONS sessions combined with intravenous administration of AA for two weeks. The primary efficiency endpoint was 6 months’ changes in scotopic vision as measured by a 10-item, 100-point, Low Luminance Questionnaire-10 (LLQ-10). The secondary efficiency points included best corrected visual acuity (BCVA) and contrast sensitivity. Rod responders were defined by ≥ 25 points increment of LLQ-10 score at 6 months after treatment. The results showed that ONS combined with AA treatment significantly improved low luminance vision, BCVA, and contrast sensitivity in patients with RP (p≤ 0.05). At 6-month visit, twenty-four (60%) patients were identified as rod responders and 16 (40%) patients were rod-non-responders. The mean change in LLQ-10 score was (46.35 ±16.81) in rod responders versus (4.9 ± 7.6) in non-responders (p < 0.0001). A clinically significant improvement of BCVA (≥0.2 logMAR) and contrast sensitivity (≥0.3 log unit) were demonstrated in 50% of the right eyes of rod responders. No serious adverse effects were reported and headache in 5 patients (12.5%) was the only en-countered side effect in this study. In conclusion, ocular neuromodulation is a safe therapeutic strategy for RP. It significantly improved night vision, BCVA, and contrast sensitivity. Determinants of rod responders include a shorter duration of night blindness, an earlier stage of the disease, and a relatively thicker ganglion cell layer at baseline. Additionally, two therapeutic scenarios were recognized; an early disease-modifying intervention that restores night vision and reverses the disease process and a late cone rescue intervention that improves/maintains central vision.

Abstract: Pasteurella spp. is a gram-negative bacterium that is part of the oral and upper respira-tory tract microbiota of many animals such as canids and felines. In humans it can produce pa-thology primarily associated with animal bites or scratches. In addition, members of this genus, and especially Pasteurella multocida, may also be involved in systemic infections, mainly in im-munocompromised patients in close contact with pets. The aim of this study is to analyse the prevalence and clinical characteristics of infections caused by Pasteurella spp. as well as the sensitivity profile of these isolates obtained in the Microbiology laboratory of the Hospital Can Misses (Ibiza, Ibiza and Formentera Health Area, ASEF) in the period from January 2013 to December 2018. The group of islands of Ibiza and Formentera is known as the Pitiusas Islands. Retrospective descriptive study in which all Pasteurella spp. isolates were analysed in the Microbiology Laboratory of Hospital Can Misses from 1 January 2013 to 31 De-cember 2018. Bacterial identification was performed by Vitek 2 automated biochemical test panel (bioMérieux, Spain) and antimicrobial susceptibility by E-test or antibiotic discs in Mueller-Hinton blood agar, interpreted based on European Committee on An-timicrobial Susceptibility Testing (EUCAST) standards, 2022 version. Medical records were systematically reviewed by collecting demographic data of infected patients, comorbidities, epidemiological data and clinical features of the infection. A total of 22 isolates of Pasterurella spp. were obtained from 22 different patients, 62.8% female, from three different species: 18 P. multocida, 2 P. canis and 2 P. pneumo-tropica. Most isolates came from soft tissue infection samples: 7 wound exudates and 5 abscess material. The antibiotics tested with the highest sensitivity profile were gen-tamicin and cefepime (100% sensitivity). The species most commonly isolated in our environment is P. multocida. Close contact with companion animals, especially cats and dogs, is the main risk factor for Pasteurella spp. infections, although in many cases such contact cannot be established. So Pasteurella spp. infection should be considered a zoonosis in possible emergency, especially in rural areas such as Pitiusas Islands.

We introduce the notion of p-adic magic contraction on p-adic Hilbert space. We derive p-adic Halmos dilation, p-adic Egervary N-dilation, p-adic von Neumann inequality and p-adic Sz.-Nagy dilation for p-adic magic contraction.

Stabilized un-doped Zinc Telluride (ZnTe) thin films were grown on glass substrates under vacuum using closed space sublimation (CSS) technique. A dilute copper nitrate solution (0.1/100 ml) was prepared for copper doping known as ion exchange process in the matrix of ZnTe thin film. The reproducible polycrystalline cubic structure of undoped and Cu doped ZnTe thin films with preferred orientation (111) was confirmed by X-rays diffraction (XRD) technique. Lattice parameter analyses verified the expansion of unit cell volume after incorporation of Cu species into ZnTe thin films samples. The micrographs of scanning electron microscopy (SEM) were used to measure the variation in crystal sizes of samples. The energy dispersive X-rays was used to validate the elemental composition of undoped and Cu-doped ZnTe thin films. The bandgap energy 2.24 eV of ZnTe thin film decreased after doping Cu to 2.20 eV may be due to the introduction of acceptors states near to valance band. Optical studies showed that refractive index was measured from 2.18 to 3.24 whereas thicknesses varied between 220 nm to 320 nm for un-doped and Cu doped ZnTe thin film respectively using Swanepoel model. The oxidation states of Zn⁺², Te⁺² and Cu⁺¹ through high resolution X-ray photoelectron spectroscopy (XPS) analyses was observed. The resistivity of thin films changed from ~10⁷ Ω-cm for undoped ZnTe to ~1 Ω-cm for Cu-doped ZnTe thin film, whereas p-type carrier concentration increased from to respectively. These results predicted that Cu-doped ZnTe thin film can be used as an ideal, efficient and stable intermediate layer between metallic and absorber back contact for the heterojunction thin film solar cell technology.

Ischemia stroke is one of a clinically common cerebrovascular disease. And Inhibition of brain tissue ischemia and reperfusion-induced damage, especially apoptosis, has an irreplaceable protective effect on ischemic nerves, and has special significance for the treatment of patients after treatment. However, the development of neuroprotective drugs still has certain challenges. Radix scrophulariae as a valuable medicine, has been discovered to has neuroprotective effects. Our researches initially proved that Radix scrophulariae aqueous extract (RSAE) exerting a neuroprotective effects on cerebral ischemia and reperfusion (I/R) injury in oxygen glucose deprivation and reperfusion (OGD/R)-induced PC12 cells and middle cerebral artery occlusion/reperfusion (MCAO/R) model mice, were associated with attenuation of infarct volume, brain water content, nitric oxide (NO) and malondialdehyde (MDA), inhibiting I/R-induced damage by reducing the levels of LDH release, improving anti-oxidant capacity by upregulating the SOD, GSH-Px and CAT activity, stabilizing mitochondrial membrane potential, reducing neuronal apoptosis, necrosis and neuronal loss by regulating the expression of anti-apoptotic BCL-2and pro-apoptotic protein Bax, and elucidating downregulate the phosphorylation levels of MAPK pathways. Our findings may elaborate the neuroprotective effects and potential mechanisms of RSAE on focal cerebral I/R injury in mice. Since, Radix scrophulariae, as a potential neuroprotective natural plant, has originally been identified to, our results may offer directions and clues for discovering new active compounds or drugs for treatment of ischemic stroke, which allows us to discover many new natural active chemicals by chemical separation and identification, and provide new insights into therapeutic targets in stroke patients.

Acute high altitude illnesses are of great concern for physicians and people traveling to high altitude. High Altitude Pulmonary Edema (HAPE) can be better understood through the Oxygen Transport Triad which involves the Pneumo-Dynamic Pump (Ventilation), the Hemo-Dynamic Pump (Heart and circulation), and Hemoglobin. The two pumps are the first physiologic response upon initial exposure to hypobaric hypoxia. Hemoglobin is the balancing energy-saving time-evolving equilibrating factor. The increased hemoglobin at high altitude reduces the percentage of dissolved oxygen in the arterial oxygen content with respect to sea level. At high altitude, the acid-base balance must be adequately interpreted using the high altitude Van-Slyke correction factors. Pulse-oximetry measurements during breath-holding at high altitude allow for the evaluation of high altitude diseases. The Tolerance to Hypoxia Formula shows that, paradoxically, the higher the altitude the more tolerance to hypoxia. All organisms adapt physiologically and optimally to a high-altitude environment to survive. Reduction of pulmonary hypertension in HAPE through oxygen administration results in a favorable outcome.

Water treatment is one of the most research-challenging areas, and continuously requires the development of efficient sustainable materials for catalytic total mineralization of organic compounds. Herein, Moringa oleifera biomass was converted to "black gold" biochar loaded with ZnO nanoparticles (MOFB@ZnO) by slow pyrolysis, at 500 °C under an inert atmosphere, (MOFB@ZnO). This composite catalyst was used for the total degradation of Congo Red, a model organic pollutant. SEM confirmed the uniform distribution of ZnO nanoparticles, while XPS and XRD indicated the presence of ZnO, primarily in the wurtzite crystalline structure. Optimization was conducted using the central composite design (CCD) method and STATISTICA 12.0 software. The composite catalyst was applied in the electrochemical degradation of Congo Red dye, using a platinum anode and a carbon felt cathode to generate H2O2 from O2 reduction. The ZnO-decorated Moringa oleifera biochar catalyst permitted to achieve of 98% removal of total organic carbon in less than 6h. It is 10-fold more efficient than pristine biochar and can be recycled up to 4 times without any significant loss. The process is highly efficient producing sustainable low-cost catalysts for water purification from organics, and contributes to sustainable chemical processes therefore addressing SDGs 6, 9, and 13.

The purpose of this study was to investigate the effects of cognitive dual-tasking on gait initiation and sit-to-walk. Twenty-eight healthy young adults performed gait initiation and sit-to-walk under two conditions: while engaging in serial subtraction (dual-task) and without any additional task (single-task). Motion data were collected using a 10-camera optoelectronic motion capture system, synchronized with force plates and surface electromyography. We analyzed spatiotemporal parameters, center of mass displacement, center of pressure trajectory, and lower limb muscle activation patterns. We found that dual-task conditions significantly affected both gait initiation and sit-to-walk patterns, increasing the duration of transitions and mediolateral center of mass displacements, while reducing vertical center of mass displacements and forward propulsion. We also observed a more constrained and less efficient center of pressure path, with reduced posterior displacement during the weight shift phase. Muscle activation, particularly in the tibialis anterior and biceps femoris, decreased during dual-task conditions, indicating altered neuromuscular strategies. These findings suggest a shift in postural control demands and motor performance during dual-task transitions.

This paper presents a comprehensive study on the design and aerodynamic optimization of a hybrid surveillance drone, conducted within the academic framework of Abu Dhabi University. The research primarily focuses on the comparison between flying wing and conventional aircraft layouts, with an emphasis on reducing drag coefficients and enhancing stall behavior through integrated design strategies. Utilizing SST k-omega viscous model (CFD) simulations, the study evaluates the aerodynamic performance of the drone model, analyzing lift, drag, and pitching moment coefficients against existing models. The paper further explores winglet selection and propeller dynamics, aiming to optimize the lift-to-drag ratio and achieve desired lift-to-weight ratios through careful consideration of propeller-wing interactions. Findings from the study indicate a notable improvement in aerodynamic efficiency, with the new drone model achieving a maximum lift coefficient (Cl, max) of 0.746, a minimum drag coefficient (Cd, min) of 0.039, and a peak lift-to-drag ratio (Cl/Cd) of 8.507. The research contributes significantly to the fields of Aerospace Engineering and Mechanical Engineering, providing a foundation for future advancements in drone design and application.

Visual servoing technology has been well developed and applied in many automated manufacturing tasks, especially in tools’ pose alignment. To access a full global view of tools, most applications adopt eye-to-hand configuration or eye-to-hand/eye-in-hand cooperation configura-tion in an automated manufacturing environment. All research papers mainly put efforts into developing control and observation architectures in various scenarios, but none of them has dis-cussed the importance of the camera’s location in eye-to-hand configuration. In a manufacturing environment, the quality of camera estimations may vary significantly from one observation loca-tion to another, as the combined effects of environmental conditions result in different noise levels of a single image shot at different locations. In this paper, we propose an algorithm for the camera’s moving policy so that it explores the camera workspace and searches for the optimal location where the images’ noise level is minimized. Also, this algorithm ensures the camera ends up at a subop-timal (if the optimal one is unreachable) location among the locations already searched, with limited energy available for moving the camera. An automated manufacturing application has been sim-ulated and the results show the success of this algorithm’s improvement of observation precision with limited energy.

Smart agriculture is a new way of farming that uses advanced technology. It makes a significant contribution to improving the efficiency and productivity of farming practices. Systems that use drones to monitor pests and spray pesticides greatly reduce the burden on farmers. In addition, remote sensing technology facilitates the monitoring of crop growth conditions and the early detection of diseases and pests. However, the high cost of equipment to communicate sensor data is preventing farmers from adopting sensing systems. As a result, many studies have been conducted to make the sensing system available at a low cost. Nevertheless, many farmers have not yet adopted them. Therefore, this paper proposes an agricultural sensor network system using drones and optical camera communication (OCC). The proposed system aims to achieve high-density farm sensing at low cost. The proposed system uses OCC as the communication method for sensor data. Low cost light sources such as LED panels can be used as transmitters. In addition, existing agricultural drones equipped with cameras can be used as receivers. We also propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. The proposed system is suitable for deploying sensor networks in areas with underdeveloped infrastructure and radio silence. In this paper, we conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama to demonstrate the effectiveness of the proposed system using a Mavic 2 Pro drone, launched by DJI Co., Ltd.

In this study, it was analyzed that the characteristics of ammonia and their effects on secondary particulate matter (PM) formation by region in Korea during 2020. The NH3 concentration was high in GJ (11.4 ppb) neighboring agricultural area followed by DJ (9.0 ppb) and SE (8.6 ppb) locating in the urban area. On the other hand, BI (2.6 ppb) and JI (4.5 ppb), which are background regions, were lower than other area. Seasonally, ammonia was high in spring and summer, and it generally increased when human activities are active. Therefore, it is believed that ammonia in the atmosphere changes depending on not only local emissions but also temperature-dependent phase distribution characteristics. For SE and GJ, regions with relatively high ammonia concentrations, the effect of ammonia on secondary PM formation was conducted. In both regions, the ammonium-to-sulfate mole ratio tended to increase with an ammonia or PM2.5 concentration increasing. It can be assumed that PM2.5 concentration increases as nitrates are formed under the ammonia sufficient condition. The adjusted gas ratio is generally greater than 4, indicating that there is a lot of free ammonia. Thus, it is estimated that reduction of ammonia would not effective to restrain the nitrate formation.

This paper explores the critical role of the banking sector in facilitating the ecological transition through the integration of ESG (Environmental, Social, and Governance) factors. By analyzing the intersection of ESG considerations and access to credit globally, the study highlights how banks can catalyze sustainable investments while balancing financial risks. Using a systematic literature review and k-Means clustering analysis, we assess the global landscape of credit access, emphasizing the implications of ESG adoption on financial stability and economic growth. The findings suggest that while ESG integration presents challenges, it offers significant opportunities for banks to enhance their competitiveness and foster resilient financial systems. The paper concludes by proposing policy recommendations aimed at improving the incorporation of ESG factors within credit risk management and promoting sustainable finance.

(1) Background: São Paulo, Brazil, exhibits high mortality rates from pediatric solid tumors. This study analyzed the survival trends of patients aged 0-19 diagnosed with the state's five most prevalent solid tumors between 2000-2022. (2) Methods: An epidemiological, descriptive study utilized data from the Oncocentro Foundation of São Paulo, classified according to the International Classification of Childhood Cancer. The time between the first consultation and diagnosis, between diagnosis and treatment initiation, and patient survival were assessed using the Pe-to-Peto test. (3) Results: Analysis involved 11,067 cases: 53.5% male, with 89.6% diagnosed via microscopic confirmation. Tumor distribution comprised 34.3% central nervous system, 21.1% bone, 18.6% soft tissue, 14.2% germ cell, and 11.9% retinoblastomas. Main treatments included surgery with chemotherapy (26.5%), surgery alone (20.5%), and chemotherapy alone (15.6%). The average time between consultation and diagnosis was 22.94 ± 69.93 days, significant for treatments and recurrences, except for germ cell tumors (p=0.0178). The time between diagnosis and treatment was 25.46 ± 39.71 days, not significant for germ cell tumor treatments (p=0.0793). (4) Conclusions: Survival curves varied among neoplasm groups, with patients experiencing delays beyond recommended times, despite advanced healthcare services in the state.

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

Parkinson’s disease (PD) is the second most common degenerative disease which may cause blood pressure abnormalities due to autonomic dysfunction. Early morning rise of blood pressure which is called morning surge is found to be related with some cardiovascular diseases when it is exaggerated. We wanted to search the relation of Morning blood pressure surge (MBPS) and inflammation in PD. Method: Ambulatory blood pressure monitoring for 24 hours, fibrinogen to albumin ratio, hs-CRP are used in this retrospective study. Fifty idiopathic PD patients and 50 age and sex matched control cases were included. MBPS, it has been defined as the difference between morning BP (measured 2 hours after awakening) and the lowest night-time BP. Body mass index (BMI) is used as an independent variable. Results: Median value of MBPS for PD group (21,63) was significantly different from the control group values (18,63) (p

Green and low-carbon development has become an important embodiment of China's path to becoming a strong agricultural country. How to enable agricultural enterprises to better adopt green technologies and conduct production and operation with the concept of sustainable development has become a key link. This article utilizes a structural equation model (SEM) to analyze the role paths and mediating effects of organizational learning ability and policy orientation in agricultural enterprises' market orientation and willingness to adopt green technologies[ The definition of green technology in this paper refers to Guo Kesha, Tian Xiaoxiao. Green technology and green transformation of industrial development mode [J]. Tianjin Social Sciences, 2024 (02) :99-107, including green manufacturing (production) technology and green service technology.]. The results show that market orientation, organizational learning ability, and policy effectiveness have significant direct positive impacts on the willingness to adopt; market orientation has a significant positive impact on agricultural enterprises' organizational learning ability, organizational learning ability has a significant positive impact on policy orientation, and market orientation has a significant positive impact on policy effectiveness; the results of mediation analysis also indicate that learning ability has a significant mediating effect between market orientation and willingness to adopt, and policy effectiveness has a significant mediating effect between market orientation and willingness to adopt. Through difference analysis, it is believed that the mediating effects of the three paths are equally important, and organizational learning ability and policy effectiveness play a partial mediating role in agricultural enterprises' willingness to adopt green technologies. Based on this, policy suggestions are proposed to improve enterprises' own organizational learning ability, increase the promotion of policies related to green technologies, improve relevant policies for the application of green technologies, and increase research and development efforts for green technologies.

To reduce the redundant counting of TDC in high-speed applications and thus reduce power consumption, a TDC architecture is proposed to quantify the difference between two adjacent rows of pixel signals. This structure can remove the identical part between two rows of pixel signals by adjusting the start and stop signal of the TDC, which will reduce the number of flipping of D flip-flops in the TDC. In the 110nm CMOS process, simulation results show that this design achieves an effective number of bits (ENOB) of 4.72 bits and a Figure of Merit (FoM) of 104.7 fJ/step - 162.3 fJ/step with a power consumption ranging from 60 µW to 93 µW. Compared with traditional counting methods, the proposed TDC can reduce counting power consumption by 30%.

The benefits of cycling as a sustainable transportation mode are widely recognized. Cycling to work offers numerous advantages for individuals, employers, the environment, and society, ranging from improved physical health, wellbeing, and productivity to enhanced public health and reduced carbon emissions. Many governments around the world have implemented various policy measures, interventions, and initiatives to promote cycling. Some cities and towns have encouraged workplaces to provide bike-friendly amenities, such as secure bike parking/storage and shower and changing facility (referred to as end-of-trip facilities), to accommodate cyclists and motivate more employees to embrace sustainable transportation options. However, the presence or absence of such amenities has been found to both positively influence cycling behavior or deter some individuals from cycling to work. Despite the desirability of these amenities, the number of office buildings equipped with bike storage and shower/changing facility remains small, and their economic value is not well understood. In this paper, we aim to investigate whether the presence of cycling-supportive facilities could add value to office buildings. Specifically, we conduct a study using data from office buildings across England as of the end of 2021. We employ hedonic techniques to examine whether office buildings with bike storage and/or shower facility command a rent premium and whether the existence of a rent premium for bike storage and/or shower facility vary by location and across regions in England, independently from any premium associated with BREEM certification. We find that the buildings with bike storage and shower facility secure rent premiums respectively. The level of rent premiums varies with location and regions. The variations of premium are driven by the shortage of the supply of these facilities.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.

Commercial buildings situated in hot and humid tropical climates rely significantly on cooling systems to maintain optimal occupant comfort. A well-accurate day-ahead load profile prediction plays a pivotal role in planning the energy requirements of cooling systems. Despite the pressing need for effective day-ahead cooling load predictions, current methodologies have not fully harnessed the potential of advanced deep-learning techniques. This research paper aims to address this gap by investigating the application of innovative deep learning models in day-ahead hourly cooling load prediction for commercial buildings situated in tropical climates. A range of deep learning techniques, including Deep Neural Network, Convolutional Neural Networks, Recurrent Neural Networks, and Long Short-Term Memory networks are employed to enhance prediction accuracy. Furthermore, these individual deep learning techniques are synergistically integrated to create hybrid models, such as CNN-LSTM and Sequence-to-Sequence models. An extensive comparative analysis is conducted to identify the most effective hybrid model. Sequence-to-sequence model provided better performance compared to the other single and hybrid models. Experiments are conducted to choose the time horizons from the past that can serve as input to the models. Further, the influence of various categories of input parameters on prediction performance has been assessed. Historical cooling load, calendar features and outdoor weather parameters are found in decreasing order of influence on prediction accuracy. This research focuses on buildings located in Singapore and presents a comprehensive case study to validate the proposed models and methodologies.

Pedestrians, bicyclists, scooterists are Vulnerable Road Users (VRU) in traffic accidents. The number of fatalities and injuries in traffic accidents involving vulnerable road users has been steadily increasing in the last two decades in the U.S. even though road vehicles now have perception sensors like camera to detect risk and issue collision warnings or apply emergency braking. Perception sensors like camera are highly affected by lighting and weather conditions. Camera, radar and lidar cannot detect vulnerable road users in partially occluded and occluded situations. This paper proposes the use of Vehicle-to-VRU communication to inform nearby vehicles of VRUs having trajectories with potential collision risk. An Android smartphone app with low energy Bluetooth (BLE) advertising is developed and used for this communication. The same app is also used to collect motion data of VRUs for training. VRU motion data is smoothed using a Kalman filter and an LSTM neural network is used for future motion prediction. This information is used in an algorithm comparing Time-To-collision-Zone (TTZ) for the vehicle and VRU and issue a driver warning with different severity levels. The warning severity level is based on analysis of real data from a smart intersection for close vehicle and VRU interactions. The resulting driver warning system is demonstrated using proof-of-concept experiments. The method can easily be extended to a VRU collision mitigation system.

A significant amount of data is available for bench-scale fire assessments. However, there is little surrounding large-scale tests and even less so for bench-to-large scale comparisons. Large-scale tests require more material, time and preparation, making them more expensive than bench-scale assessments. However, large-scale testing is an essential component to bench-scale fire testing. The bench-scale tests must be representative of both large-scale and real fire behaviour to provide an insight into how a material or product will behave in the event of a fire during its end use application. The few existing studies reviewed in this study show more guidance and data is needed, especially on a large-scale. Unfortunately, the data that is presented is done so in an inconsistent manner using various means of presentation, statistical analysis, and modelling that doesn’t show clear comparisons between bench and large scale. Currently, no bench-scale method shows good agreement with large-scale fire behaviour. Overall, there is a need for more large-scale testing and data for direct comparisons to be made.

The current study primarily aimed to simulate detonation initiation via turbulent jet flame acceleration in partial-premixed H2-air mixtures. Different vertical concentration gradients were generated by varying the duration of hydrogen injection (referred to as diffusion time) within an enclosed channel filled with air. H2-air mixtures with average hydrogen concentrations of 22.5% (lean mixture) and 30% (near stoichiometric mixture) were investigated at diffusion times of 3, 5, and 60 seconds. Numerical results show that the vertical concentration gradient has a major influence on the early-stage of flame acceleration (FA). In the stratified lean mixture, detonation began in all the diffusion times, and comparing the flame-speed graphs showed that a decrease in the diffusion time and an increase in the mixture inhomogeneity speeded up the flame propagation and the jet flame to detonation transition occurrence in the channel. In the stratified H2-air mixture with an average hydrogen concentration of 30%, transition from a turbulent jet flame to detonation occurred in all the cases, and the mixture inhomogeneity weakened the FA and delayed the detonation initiation.

Liver transplantation is currently the only curative therapy for patients with liver cirrhosis. Not all patients in the natural course of the disease will undergo transplantation, but the majority of them will experience portal hypertension and its complications. In addition to medical and endoscopic therapy, a key role in managing these complications is played by the placement of a transjugular intrahepatic portosystemic shunt (TIPS). Some indications for TIPS placement are well-established and they are expanding and broadening over time. This review aims to describe the role of TIPS in managing patients with liver cirrhosis, considering them as potential candidates for liver transplantation. As far as is known TIPS placement seems not to affect the surgical aspects of liver transplantation, in terms of intra operative bleeding rates, postoperative complications or length of stay in the Intensive Care Unit. However, the placement of a TIPS “towards transplant" can offer advantages in terms of enhancing the patient's clinical condition at the time of transplantation and improving patient survival. Additionally, the TIPS procedure can help preserve the technical feasibility of the transplant itself. In this context, indications for TIPS placement may be expanded and considered at an earlier stage. TIPS insertion can also lead to serious adverse events and there are no evidence-based recommendations on this topic to date. For these reasons further studies are needed to make reliable recommendations for TIPS in the pre-transplant setting.

Molnupiravir, a prodrug known for its broad antiviral activity, demonstrated efficacy in animal models of Covid-19, prompting clinical trials where initial results indicated a significant effect against the disease. However, subsequent clinical studies did not confirm these findings, leading to the rejection of molnupiravir for permanent market authorization in many countries. This report critically assessed 19 studies published in 17 reports that investigated the efficacy of molnupiravir in animal models of Covid-19 with the purpose of determining how well the design of these models informed human studies. We found that the administered doses of molnupiravir in most studies involving animal Covid-19 models were disproportionately higher than the dose rec-ommended for human use. Specifically, when adjusted for body surface area, half of the doses of molnupiravir used in the animal studies were more than twice as high as the human dose. Addi-tionally, the drug was frequently given prophylactically or shortly after SARS-CoV-2 inoculation in these models, in contrast to clinical trials where such timing is not consistently achieved. Furthermore, the recommended five-day treatment duration for humans was exceeded in several animal studies. Collectively, we suggest that these design elements in the reported animal studies contributed to a bias favoring molnupiravir, and thus inflated expectations for its efficacy against Covid-19. Addressing these elements may offer avenues to enhance the clinical efficacy of mol-nupiravir for treatment of Covid-19 that include dose increment, early treatment, and admin-istration by inhalation along with use of molnupiravir in antiviral combination therapy.

This paper introduces an advanced method that integrates contingent valuation and machine learning (CVML) to estimate residents’ demand for reducing or mitigating environmental pollutions and climate change. To be precise, CVML is an innovative hybrid machine-learning model, and it can leverage a limited amount of survey data for prediction and data enrichment purposes. The model comprises of two interconnected modules: Module I, an unsupervised learning algorithm, and Module II, a supervised learning algorithm. Module I is responsible for grouping the data into groups based on common characteristics, thereby grouping the corresponding dependent variable, whereas Module II is in charge of demonstrating the ability to predict and the capacity to appropriately assign new samples to their respective category based on input attributes. Take a survey on the topic of air pollution in Hanoi in 2019 as an example, we found that CVML can predict households’ willingness– to– pay for polluted air mitigation at a high degree of accuracy (i.e., 98%). We found that CVML can help users reduce costs or save resources because it makes use of secondary data that is available on many open data sources. These findings suggest that CVML is a sound and practical method that could be widely applied in a wide range of fields, particularly environmental economics and sustainability science. In practice, CVML could be used to support decision-makers in improving the financial resources to maintain and/or further support many environmental programs in years to come.

Environmental concerns, among other causes, are leading to meat replacement in the diet by healthy, nutritious and tasty foods. Alternative protein sources of plant origin can be an alternative to meat, but their low biological value proteins can be a problem. Novel foods, such as insect meals, can meet currently consumer demands. Therefore, this research has developed innovative prototypes of analogue burgers with animal and vegetable proteins. Concerned about health and allergies, a prototype incorporating soya to satisfy coeliacs was developed. An iterative and heuristic process was carried out to test the product development feasibility. The main raw materials used were insect flour (Tenebrio molitor), seitan and soya. In addition, oat and sodium alginate were used as binders. Shelf-life of the new product was evaluated by physicochemical (pH, aw, moisture, colour, acidity and peroxide index) and sensory analysis (quantitative analysis -QDA-). The production of the burger analogues was feasible. Product characterisation showed significant differences (p < 0.05) among samples for organoleptic properties, highlighting texture changes. Using a multivariate model, it was established “The best before date” at 7 days for all developed prototypes, conditioned by microbial growth. Finally, the spoilage model indicated an important contribution to bacterial growth with a notable modification in the pastiness and hardness of the burger analogues developed.

It is known from ancient Egyptian mathematical papyri that the Egyptians were able to calculate the area of a circle with great accuracy. How they found the formula for this calculation was still unknown. Here it is shown how the unknown ancient Egyptian mathematician found a method for calculating the area of a circle and the ratio of a circle’s circumference to diameter.

Waste-to-Hydrogen (Wahh) is a process of converting waste into hydrogen gas through various methods such as thermal conversion, biological conversion, and chemical conversion. This process not only helps in managing waste but also provides a clean source of energy as hydrogen is a renewable energy source that produces zero greenhouse gas emissions during combustion. Wahh has the potential to provide a sustainable solution for energy generation and waste management in the current scenario of globally increasing energy demands. This study aims to examine the properties and energy efficiencies of various renewable fuels including fuelwood, biogas, biomethane, and biohydrogen with a specific focus on differentiating the characteristics of biohydrogen. The paper explores the emerging concepts of waste-to-hydrogen microgrids, biohydrogen refineries, biohydrogen prosumer networks, and a biohydrogen circular economy, as well as Public-Private-People Partnerships (4Ps) and the hydrogen-centric renewable energy revolution, which are taking shape in industrialized countries. The study presents a comprehensive feasibility analysis of these concepts in the context of Nepal. The results of this research will provide valuable insights into the potential for adopting these innovative technologies in Nepal and will contribute to the development of a sustainable and efficient energy system.

Within this paper, a machine learning algorithm is used to investigate the importance of certain setpoints and parameters in the filtration processes of a large-scale water treatment facility. Previously, a model for the filtration process based on Run-to-Run Control was proposed and tested against sample data from the treatment plant, but it was quickly found that such a model was incompatible for successfully computing setpoints of operation which minimize the energy cost of running the filtration systems. The machine learning model described herein is an attempt to elucidate the importance of the available data on the filtration systems and to identify the most important variables that influence the filtration run time.

This research aims to contribute to the growing body of knowledge of Collaborative Consumption (CC) by exploring the motivations that influence the use of Peer-to-Peer (P2P) accommodation platforms from the demand side. There has been a significant increase in interest in sustainable choices regarding P2P accommodation in recent years. To address this gap and contribute to the collaborative consumption and P2P accommodation theory a quantitative study was conducted through a survey yielding 235 responses from both users and non-users of P2P platforms. The findings of this study suggest that P2P accommodation platform usage is influenced by multiple motivations, including sustainability, belonging, economic benefits, and convenience. Interestingly, the study also found that individuals with higher levels of academic qualifications are more likely to adopt this mode of consumption. Moreover, the study is the first of its kind to quantitatively address this topic and, therefore, contributes significantly to the field of collaborative consumption and P2P accommodation theory. By understanding the motivations of P2P platform users, policymakers and practitioners can develop targeted strategies to promote sustainable choices in this sector. Overall, this study provides a useful framework for future research on collaborative consumption and sustainable P2P accommodation.

The combination of non-steroidal anti-inflammatory drugs (NSAIDs) with non-opioid analgesics is common in clinical practice for the treatment of acute pain conditions like post-operative and post-traumatic pain. Besides that, and despite the very satisfactory results achieved by oral analgesics, parenteral analgesia is a key tool in the treatment of painful conditions when the enteral routes are not convenient. The parenteral ready-to-use fixed-dose combinations of NSAIDs with non-opioid analgesics like paracetamol or metamizole could play a central role in the treatment of painful conditions since they are able to gather into only one formulation the advantages of multimodal and parenteral analgesia. Surprisingly, only very recently a parenteral ready-to-use fixed-dose combination of Ibuprofen/Paracetamol was launched to the market. This review aims to review the current availability of NSAID-based Parenteral Fixed-dose combinations with paracetamol and metamizole in the European and American markets, and how the combination of such drugs could play a central role in a multimodal analgesia strategy. Also, it is explored how the parenteral formulations of NSAIDs, paracetamol, and metamizole could serve as starting elements for the development of new parenteral ready-to-use fixed-dose combinations. With this review, we concluded that, despite the well-recognized utility of combining NSAIDs with non-opioid analgesics, there are in the literature several randomized clinical trial studies unable to demonstrate clear advantages concerning their efficacy and safety. In the future, it is deemed necessary to perform clinical trials specifically designed to assess the efficacy and safety of these fixed-dose formulations to generate solid evidence of their clinical advantages.

In this paper, inspired by quantum field theory, or more specifically QED, we propose a dynamical model for relativity. By adopting the approach provided by this dynamical model, we provide a dynamical explanation for relativistic phenomena such as length contraction, time dilation and clock desynchronization. The result of the dynamical approach for clock desynchronization is especially interesting. Our dynamical approach exhausts the freedom for different clock synchronizations on frames accelerated from an initial reference frame, which is allowed by Einstein’s principle approach. Furthermore, our dynamical approach arrives at the interesting conclusion that Einstein’s equivalence principle and gravitational redshift are necessary to explain special relativistic clock desynchronization. This result shows that special relativity by itself is an incomplete theory. If our dynamical model assumptions are assumed to be valid at a fundamental level, it implies some modifications to quantum field theory and general relativity via the equivalence principle. These modifications have been discussed.

The manuscript presents a unified methodology for the engineering design of resonant inverters used for power sources to power various technologies based on induction heating. The methodology is compiled using the generalized consideration of electromagnetic processes in a series RLC circuit and the quasi-boundary method for the analysis of resonant inverters with and without reverse diodes operating in soft and hard commutation modes. On this basis, the transmission functions of the inverters are derived, and the matching between the parameters of the inverter and the load through complicated output circuits is also considered. The basic ratios for determining the circuit elements and their current and voltage loading are presented. The methodologies are verified using several computational examples, simulations and measurements from induction heating devices. The simplified design approach presented is useful for its application in power electronics training and also in the design of various devices using the principle of induction heating. Another important result is the achievement of formalization and algorithmization of the design process, which is a consequence of the application of a unified approach both in the analysis and in the design of a whole class of power electronic devices.

An out-of-hospital cardiac arrest (OHCA) is one of the leading causes of death in the world. The survival rate can be influenced by the Chain of Survival. The school is the institution that has the opportunity to promote the education of citizens in Basic Life Support (BLS), increasing the number of trained bystanders. This study aimed to identify the theoretical and practical knowledge and self-reported skills in BLS, in order to characterise the motivation to intervene in an emergency situation. A quantitative, descriptive, cross-sectional, and analytical study of the survey type was developed with a sample of 1215 students enrolled in 10th grade of secondary education in 2019-2020 in Portugal. The results point to a fragile appropriation of theoretical and practical knowledge in the field of BLS. Self-declared competences tend to rank below the theoretical knowledge manifested. Motivation to intervene is high: students are sensitive to the topic, willing to learn and highlight the importance and social relevance of the topic. We conclude that students do not feel nor are able to intervene in an OHCA episode. It seems necessary to develop didactic proposals that align the teaching of BLS with the Essential Learning at the end of compulsory education in Portugal.

Human and animal waste, including waste products originating from human or animal digestive systems such as urine, feces, and animal manure, have constituted a nuisance to the environment. Inappropriate disposal and poor sanitation of human and animal waste often cause negative impacts on human health through contamination of the terrestrial environment, soil, and water bodies. Therefore, it is necessary to convert these wastes into useful resources to mitigate their adverse environmental effect. The present study provides an overview and research progress of different thermochemical and biological conversion pathways for the transformation of human- and animal-derived waste into valuable resources. The physicochemical properties of human and animal waste are meticulously discussed as well as nutrient recovery strategies. In addition, a bibliometric analysis is provided to identify the trends in research and knowledge gaps. The results reveal that the U.S.A, China and England are the dominant countries in the research areas related to resource recovery from human or animal waste. In addition, researchers from the University of Illinois, the University of California Davis, the Chinese Academy of Science and Zhejiang University are front runners in research related to these areas. Future research should be centred on developing technologies for the on-site recovery of resources, exploring integrated resource recovery pathways, and exploring different safe waste processing methods.

The aim of this study was to estimate the association between fear of COVID-19 and risk perception with preventive behavior in health professionals from three Latin American countries. An analytical cross-sectional study was conducted. Health professionals with on-site care in Colombia, Ecuador, Guatemala, and Peru were surveyed. Information was collected through an online self-report questionnaire. The main variables were preventive behavior as the dependent variable and fear of COVID-19 and risk perception as independent variables. Linear regression was used, and Beta coefficients and p-values were calculated. 435 health professionals were included, the majority were aged 42 years or older (45.29%, 95%CI: 40.65%-50.01%) and female (67.82%, 95%CI: 63.27%-72.05%). It was shown that the greater the fear of COVID-19, the greater the preventive behavior of COVID-19 infection (B=2.21, p=0.002 for total behavior; B=1.12, p=0.037 for additional protection at work; B=1.11, p<0.010 for hand washing). The risk perception of COVID-19 infection had a slight direct relationship with preventive behaviors (B=0.28, p=0.021 for total behavior; B=0.13, p=0.015 for hand washing), with the exception of the preventive behavior of using additional protection at work (p=0.339). We found that fear and risk perception are associated with increased practice of hand washing and use of additional protection at work. Further studies are required on the influence of working conditions, job performance and the occurrence of mental health problems in frontline personnel with regard to COVID-19.

This article mainly proposes the point of view that financial literacy curriculum aims to make kinds of people, to make people with financial creativity of resource integration thinking and continuous ‘to conscience’ of morality, which is cultivate a way of thinking that can maximize benefits through the use of resource integration and constantly ‘to conscience’ to achieve goals for participants in financial structures with balanced interests. In this sense, this article argues that financial literacy is to make kinds of people with a financial mindset and constantly strengthen ‘to conscience’ through uniting of knowledge and action to achieve human well-being and benign operation of society. In this sense, this article attempts to determine what is really taught in financial literacy education in terms of curriculum theory. That is to improve creativity by cultivating financial thinking with constant ‘to conscience’. The views of this paper provide a new way of thinking about financial literacy education assessment. This changes the evaluation criteria of financial literacy education from the result-oriented of wealth growth to the process-oriented of financial creativity growth, trying to move the criticism of financial literacy education curriculum and evaluation from controversy to unity.

In previous studies regarding the osseointegration of zirconia (ZrO2) implants, a lack of consistency was observed in the surface topographies of the ZrO2 and Ti samples because of the difficult processability of ZrO2 surfaces. To resolve this problem, we used the molecular precursor method (wet process), which is a surface-modifying technique that can easily change the surface chemistry without changing the surface topography. A roughened Ti surface was prepared using sandblasting (large-grit) and acid treatment. We were able to create ZrO2-coated Ti implants with the same topography as that of roughened Ti substrates using the molecular precursor method, which solution contained a Zr complex. The uniform presence of tetragonal Zr was confirmed, and the apparent zeta potential of the surface of the ZrO2-coated Ti implant was higher than that of Ti. In animal experiments, ZrO2-coated Ti implants showed an equivalent or higher bone-to-implant contact ratio compared to that of the non-coated implants inserted into the femur bone defects of the rats. ZrO2 with the same surface topography as that of roughened Ti exhibits a promotion of osteogenesis equivalent to or better than that of Ti in the early stages of bone formation.

Modularity and organizational hierarchy are important concepts in understanding the structure and evolution of interactions in complex biological systems. In this work, we introduce and use a spectral characterization measure (Spectral Entropy) to quantify modularity in protein-to-protein interaction (PPI) networks in species across the tree of life. We evaluated the relation between the size of a PPI network and its (Spectral Entropy-based) modularity, and found a sigmoidal response between the two. We also found significant differences in the distribution of Spectral Entropy values among the three domains of life (Bacteria, Archaea, Eukaryotes). To explore further correlations with biological traits, we focused solely on bacterial PPI networks, which are the most numerous among the three domains and had associated trait metadata, and investigated how modularity impacts or is impacted by growth, aerobicity, selection and location on the tree of life. We found no relation between maximal growth rate and Spectral Entropy, but a strong dependence between G-C content (a proxy for selection) and Spectral Entropy. We also discovered that Spectral Entropy is negatively affected by phylogenetic placement (evolutionary distance from the last universal common ancestor). The general nature of the Spectral Entropy measure of hierarchical modularity in networks suggests that it will be useful in other settings where structural properties of real-world networks are being compared.

Molecular mechanisms for N2 fixation (solar NH3) and CO2 conversion to C2+ products in enzymatic conversion (Nitrogenase), electrocatalysis, metal-complexes and plasma-catalysis are analysed and compared. It is evidenced that differently from what present in thermal and plasma-catalysis, the electrocatalysis path requires not only the direct coordination and hydrogenation of undissociated N2 molecule, but to realize a series of features present in the Nitrogenase mechanism. There is the need of i) a multi-electron and -proton simultaneous transfer, not as sequential steps, ii) forming bridging metal hydride species, iii) generate intermediates stabilized by bridging multiple metal atoms, iv) have the capability of the same sites to be effective both in N2 fixation and in COx reduction to C2+ products. Only iron oxide/hydroxide stabilized at defective sites of nanocarbons was found to have these features. This comparison of the molecular mechanisms in solar NH3 production and relations with CO2 reduction is proposed to be a source of inspiration to develop the next generation electrocatalysts to address the challenging transition to a future sustainable energy and chemistry beyond fossil fuels.

In light of the latest trends in global installed capacities, the importance of variable renewable energy sources (VRES) to future energy supply systems is evident. Despite this, the inherent intermittency of VRES remains an obstacle to their widespread adoption. Green hydrogen is often suggested as an energy carrier that can account for this in a sustainable manner. In the analysis, a robust European energy system in the context of 2050 and with 100% VRES energy supply is designed through an iterative minimal cost-optimization approach that ensures robust security of supply over 38 weather-year scenarios (1980-2017). The impact of spatial VRES variability is factored in by defining exclusive VRES groups within each optimization region and, from this, it can be seen that higher numbers of groups in each region offer cheap electricity generation locations to the optimizer and thus decrease the total annual cost of the system. Beyond this, the robust system design and impact of inter-annual variability is identified by iteratively combining the installed capacities of different system designs obtained by applying 38 historical weather years. The robust system design outlined here has significantly lower capacities in comparison to the maximum regional capacities obtained in the first round of optimization.

Biogas contains more than 40% CO2 that can be removed to produce high quality CH4. Recently, CH4 production from CO2 methanation has been reported in several studies. In this study, CO2 methanation of biogas was performed over a 20 wt% Ni-Mg-Al catalyst, and the effects of CO2 conversion rate and CH4 selectivity were investigated as a function of CH4, O2, H2O, and N2 compositions of the biogas. At a gas hourly space velocity (GHSV) of 30,000/h, the CO2 conversion rate was ~79.3% with a CH4 selectivity of 95%. In addition, the effects of the reaction temperature (200–450 °C), GHSV (21,000–50,000/h), and H2/CO2 molar ratio (3–5) on the CO2 conversion rate and CH4 selectivity over the 20 wt% Ni-Mg-Al catalyst were evaluated. The characteristics of the catalyst were analyzed using Brunauer-Emmett-Teller (BET) surface area analysis, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The catalyst was stable for approximately 200 h at a GHSV of 30,000/h and a reaction temperature of 350 °C. CO2 conversion and CH4 selectivity were maintained at 75% and 93%, respectively, and the catalyst was therefore concluded to exhibit stable activity.

General wisdom thinks that the central of blackholes are singular and featured by mass, charge and spin exclusively; the microstate reflected in the Bekenstein-Hawking entropy can be accounted for only in some quantum gravity. We challenge this wisdom with two exact solution families to the sourceful Einstein equation which describe dust ball with oscillatory inner structure and variety of mass profiles. We attribute the matter content's oscillation across the central point of the system to the forward scattering domination in high energy collisions induced by inter-gravitating acceleration and provide their Penrose-Carter diagram representation and quantum description briefly. Our solution family provides a very simple semi-classic picture for the micorstate definition of black holes.

Purpose: To explore the influence of education and other factors on an athlete’s decision to return to sport post-concussion injury, and whether general risk-taking tendencies are related to return to sport post-concussion decisions in these athletes. Participants and Methods: A self-administered electronic survey was designed to examine their decision-making process when faced with scenario-based questions regarding returning to sport post-concussion injury. Students from the Health Sciences and Medicine Faculty at Bond University were invited to participate. Participants were allocated to a concussion education or non-education group prior to commencement of questionnaire via the random generator on Qualtrics software function. The risk propensity scale was used to assess the risk aversion of each participant. Results: Sixteen respondents were randomized evenly to education and non-education groups. Seven (43.8%) had previously received concussion education training prior to completing the questionnaire, with one (14%) choosing to return to sport in the scenario-based questions. The education group reported two (25%) respondents return to sport, while three (75%) respondents out of four returned to sport with no education or previous concussion training. Influential factors that impacted the decision whether to return to sport or not included: game importance, concussion severity and symptoms, and various internal and external factors. Finally, there was a divergence in results from the risk propensity scale when deciding to return to sport and general risk-taking propensities. Conclusion: This study identified several influential factors including game importance, concussion severity and symptoms which play a significant role in the return to sport decisions post-concussion injury.

It has been a long time since the world has experienced a pandemic with such a rapid devastating impact as the current COVID-19 pandemic. The causative agent, the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is further unusual in that it appears capable of infecting many different mammal species. As a significant proportion of people worldwide are infected with SARS-CoV-2 and may spread the infection unknowingly before symptoms occur or without any symptoms ever occurring, there is a non-negligible risk of humans spreading SARS-CoV-2 to wildlife, in particular mammals. Because of SARS-CoV-2’s evolutionary origins in bats and reports of humans transmitting the virus to pets and zoo animals, regulations for prevention of human-to-animal transmission have so far focused mostly on these animal groups. Here, we summarize recent studies and reports that show that a wide range of distantly related mammals are likely susceptible to SARS-CoV-2 and that susceptibility or resistance to the virus is in general not predictable, or only to some extent, by phylogenetic proximity to known susceptible or resistant hosts. In the absence of solid evidence on the SARS-CoV-2 susceptibility/resistance for each of the >5,500 mammal species, we argue that sanitary precautions should be taken when interacting with any mammal species in the wild. Preventing human-to-wildlife SARS-CoV-2 transmission is important for protecting these (sometimes endangered) animals from disease, but also to avoid establishment of novel SARS-CoV-2 reservoirs in wild animals. The risk of repeated re-infection of humans from such a wildlife reservoir could severely hamper SARS-CoV-2 control efforts. For wildlife fieldworkers interacting directly or indirectly with mammals, we recommend sanitary precautions such as physical distancing, wearing face masks and gloves, and frequent decontamination, which are very similar to regulations currently imposed to prevent transmission among humans.

Renewable energy sources (RES) will play a crucial role in future sustainable energy systems. In scenarios analyzing future energy system designs, a detailed spatial and temporal representation of renewable-based electricity generation is essential. For this, sufficiently representative weather data are required. Most analyses performed in this context use the historical data of either one specific reference year or an aggregation of multiple years. In contrast, this study analyzes the impact of different weather years based on historical weather data from 1980 through 2015 in accordance with the design of an exemplary future energy system. This exemplary energy system consists of on- and offshore wind energy for power-to-hydrogen via electrolysis, including hydrogen pipeline transport for most southwestern European countries. The assumed hydrogen demand for transportation needs represents a hypothetical future market penetration for fuel cell-electric vehicles of 75%. An optimization framework is used in order to evaluate the resulting system design with the objective function of minimizing the total annual cost (TAC) of the system. For each historical weather year, the applied optimization model determines the required capacities and operation of wind power plants, electrolyzers, storage technologies and hydrogen pipelines to meet the assumed future hydrogen demand in a highly spatially- and temporally-detailed manner, as well as the TAC of the system. Following that, the results of every individual year are compared in terms of installed capacities, overall electricity generation and connection to the transmission network, as well as the cost of these components within each region. The results reveal how sensitive the final design of the exemplary system is to the choice of the weather year. For example, the TAC of the system changes by up to 20% across two consecutive weather years. Furthermore, significant variation in the optimization results regarding installed capacities per region with respect to the choice of weather years can be observed.

By combing continuum topology optimization (TO) method and lattice structure technique, a sandwich aircraft spoiler with a high stiffness-to-weight is designed. TO method is served to produce the shell of the aircraft spoiler and the lattice structure, used as cores, is employed to support the shell. TO problem is established as maximizing the stiffness of the structure with limited material volume. Density-based method is utilized to achieve a 0/1 solution. We then empirically replace the core of the aircraft spoiler by using 3D kagome lattice structure. Two different materials, i.e., aluminum alloy and titanium alloy, are synthetically applied to further reduce the weight and simultaneously improve the strength of the aircraft spoiler. Numerical simulations are conducted to show that the designed aircraft spoiler can meet the service environment with a reduction of its weight by approximately 80% when compared with that of the initial design model. Finally, we have fabricated the designed model with photosensitive resin by using 3D printing technique.

Drug delivery to the brain represents a challenge especially in the therapy of central nervous system malignancies. Simvastatin (SVT), as other statins, has shown potential anticancer properties that are difficult to exploit in the CNS. In the present work the physico-chemical, mucoadhesive and permeability enhancing properties of simvastatin-loaded poly-ε-caprolactone nanocapsules coated with chitosan for nose-to-brain administration were investigated. Lipid-core nanocapsules coated with different molecular weight (MW) chitosans (LNCchit) prepared by a novel one-pot technique were characterized for particle size, surface charge, particle number density, morphology, drug encapsulation efficiency, interaction between surface nanocapsules with mucin, drug release and permeability across two nasal mucosa models. Results show that all formulations present adequate particle size (below 220 nm), positive surface charge, narrow droplet size distribution (PDI<0.2) and high encapsulation efficiency. Nanocapsules presented controlled drug release and mucoadhesive properties dependent on the MW of the coating chitosan. The results of permeation across RPMI 2650 human nasal cell line evidenced that LNCchit increased the permeation of SVT. In particular, the amount of SVT permeated after 4h for nanocapsules coated with low MW chitosan, high MW chitosan and control SVT was 13.91 ± 0.78 µg, 9.15 ± 1.23 µg and 1.42 ± 0.21 µg respectively. These results were confirmed by the SVT ex vivo permeation across rabbit nasal mucosa. This study highlighted the suitability of LNCchit as promising strategy for the administration of simvastatin for a nose-to-brain approach for the therapy of brain tumors.

Location-Based Services (LBS) have been widely deployed for the connected vehicle (CV) applications such as vehicle navigation,vehicle tracking and location-based augmented reality. The current LBS deployments have limitations in supporting time-critical CV use cases, including vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle-to-people (V2P) safety applications. The paper presents the new LBS framework based on the publish-subscribe communication paradigm, to enable device-to-device (D2D) connections through use of selected application protocols in the application layer of the TCP/IP layered protocol model. Two publish-subscribe application protocols, Distributed Data Service (DDS) real-time publish and subscribe (DDS-RTPS) and Message Queue Telemetry Transport (MQTT), are introduced to support the LBS D2D applications. A number of test scenarios with Mosquitto MQTT and OpenDDS under 4G-mobile broadband (MBB) services are designed to assess the transmit/receive round-trip time (RTT) and packet-loss rate (PLR) with settings of a publisher to multiple subscribers, to simulate the connections to multiple vehicles. The transmission frequency is set for 10 Hz and the message sizes vary from 100 to 2000 Bytes. The PLRs are defined as the percentages of the delayed messages beyond a delay limit. Static test results with OpenDDS show that for the RTT delay beyond the limit of 100 ms, the total PLRs range between 5.25% and 8.76% for the message size of 50 to 2000 Bytes. Vehicle testing results with Mosquitto show that PLRs for the RTT delays between 200 ms and 1000 ms are 0.63%, 3.58% and 5.77%, for connections with 1, 4 and 10 vehicles, respectively. The results demonstrate the potential of the D2D LBS framework for medium-demanding CV safety applications such as V2P and V2I use cases, taking advantages of the 4G-MBB services and 5G extreme mobile broadband (eMBB) services and mobile devices generally available with all road users.

The seasonally adjusted civilian labor force participation rate, the sum of employed and unemployed persons as a percentage of the civilian non-institutional population, is analysed in the general to specific modelling framework with a saturating set of step indicators from January 1977 through June 2018. The results indicate that, ceteris paribus, the rise in the ratio of women to men in the labor force in addition to positive demographic movements can largely account for the rise in the labor force participation rate up to January 2000. Subsequently, the aging population helps to explain the decline. Recessions play a transitory role.

The speech-to-song illusion is a type of auditory illusion that the repetition of a part of a sentence would change people’s perception tendency from speech-like to song-like. The study aims to examine how pace, emotion, and language tonality affect people’s experience of the speech-to-song illusion. It uses a between-subject (Pace: fast, normal, vs. slow) and within-subject (Emotion: positive, negative, vs. neutral; language tonality: tonal language vs. non-tonal language) design. Sixty Hong Kong college students were randomly assigned to one of the three conditions characterized by pace. They listened to 12 audio stimuli, each with repetitions of a short excerpt, and rated their subjective perception of the presented phrase, whether it sounded like a speech or a song, on a five-point Likert-scale. Paired-sample t-tests and repeated measures ANOVAs were used to analyze the data. The findings reveal that a faster speech pace could strengthen the tendency of the speech-to-song illusion. Neither emotion nor language tonality show a statistically significant influence on the speech-to-song illusion. This study suggests that the perception of sound should be in a continuum and facilitates the understanding of song production in which speech can turn into music by having repetitive phrases and to be played in a relatively fast pace.

The impact of an unlicensed low-cost taxi in Bangladesh is very severe, especially in municipal cities. Day by day the numbers of unlicensed low-cost taxi are increasing by jumping up and creating pressure on traffic and transportation system. The aim of this study is to find out the causes of increasing illegal taxi and the extent of this vehicle in the municipalities of Bangladesh. Pabna municipality is used as a case study due to the more activeness of illegal taxi then the other municipalities. To achieve the objectives, the researcher used a qualitative approach to acquire more depth about the problems. Besides a direct observation of the study area, an open-ended questionnaire survey and HIS survey were conducted. The illegal low-cost taxi is very active it was analyzed through the field survey. A statistical model was developed to understand the actual causes of increasing illegal low-cost taxi, where ten predicted hypotheses (age, education level, marital status and family member support of illegal drivers, and the variable of commuter satisfaction e.g. safety, comfort, continuous service, affordability of service, reliability of service and driver behavior) were tested. The model was run through the multiple regression analyses technique in SPSS and the result proved that education level of illegal low-cost taxi drivers, and the commuter satisfaction variable (safety and comfort) had a positive and significant effect of increasing illegal low-cost taxi in the study area. However other variable had no significant effect in case of increasing illegal low-cost taxi. Besides the safety and comfort, steady job for the operators, provision of continuous, individual and door to door service system are the main reasons for increasing the illegal low-cost taxi in the study area. Finally, the researcher concludes with the requirement of some necessary action from the responsible authority on vehicular regulation for the improvement of the local public transport system in Bangladesh.

In 1990 the Malaysian Government launched Vision 2020 with the goal of Malaysia becoming a ‘fully developed country’ by the year 2020. In this drive for development the country has been examining many of its key natural assets, exploring how to both preserve them whilst ensuring that they make the maximum possible contribution to national development goals. Endau Rompin is one of these assets, being the second largest National Park in Peninsula Malaysia. The rich tropical rainforest flora and fauna of the Park and its hinterland, however, are threatened by various anthropogenic forces, most notably deforestation and poaching; both of which have taken the Park’s flagship species - the Tiger Panthera tigris jacksoni – towards the brink of local extinction. Malaysia’s statutory East Coast Economic Region Development Council commissioned a study to consider ways of increasing tourism revenues from the Park while at the same time reversing these threats. The key conclusion drawn is that a more holistic, landscape-scale approach should be adopted, with Endau Rompin forming part of a wider strategic economic zone based around sustainable tourism and land management. The proposed expanded zone extends eastwards beyond the confines of the Park, across the coastal plain to the South China Sea, and onwards to the neighbouring Mersing Islands. This expanded zone is referred to as Malaysia’s new ‘Rainforest to Reef Region’.

The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

Whole genome duplication (WGD) or polyploidization can occur at the cellular, tissue, and organismal levels. At the cellular level, tetraploidization has been proposed as a driver of aneuploidy and genome instability, and correlates strongly with cancer progression, metastasis, and development of drugs resistance[1–6]. WGD is also a key developmental strategy for regulating cell size, metabolism, and cellular function[1,7–10]. In specific tissues, WGD is involved in normal development (e.g. organogenesis), tissue homeostasis, wound healing, and regeneration[10–17]. At the organismal level, WGD propels evolutionary processes such as adaptation[18], speciation[19], and crop domestication[20]. An essential strategy to further our understanding of the mechanisms promoting WGD and its effects is to compare isogenic strains that differ only in their ploidy. Caenorhabditis elegans (C. elegans) is emerging as an animal model for these comparisons, in part because relatively stable and fertile tetraploid strains can be produced rapidly from nearly any diploid strain[7]. Here we review the use of Caenorhabditis polyploids as tools to understand important developmental processes (e.g. sex determination, dosage compensation, and allometric relationships)[21–27] and cellular processes (e.g. cell cycle regulation, chromosome dynamics during meiosis)[28–32]. We also discuss how the unique characteristics of the C. elegans WGD model will enable significant advances in our understanding of mechanisms of polyploidization and its role in development and disease.

The present paper discusses an elliptic equation with Steklov boundary conditions and $(p(x),q(x))$-Laplacian. Using mountain pass theorem together with Ekeland's variational principle, we prove, under appropriate conditions on the functions involved, that the problem admits at least two solutions.

Finding sustainable renewable energy sources for energy conversion and management is still an obscure topic. This paper presents a model-based simulation for an energy conversion system using piezoelectric energy harvester (PEH) technology. A dynamic mathematical model of a PEH device consists of a piezoelectric transducer, a controlled PWM rectifier, and a closed-loop buck boost converter is developed. A piezoelectric transducer converts mechanical vibrations from a wind force into an oscillating train of electrical charges. The sinewave peak-to-peak level relationship describes the changeable values of these charges, which depend on the severity of the wind vibration. The controlled PWM rectifier, in conjunction with a closed-loop buck-boost converter, converts this train of sinewave cycles into DC voltages. The control blocks of the closed-loop buck-boost converter use the perturbation and observation (P&amp;O) algorithm based on maximum power point tracking (MPPT), which adapts the operational voltage of the piezoelectric source to deliver the maximum power to load and improves the PEHS output voltage stability. A simulation program is employed to perform mathematical analysis on various wind vibration scenarios, piezoelectric sources without PWM converters, and piezoelectric vibration sources connected to a closed-loop P&amp;O converter. The crucial results of this paper demonstrate that the proposed dynamic PEHS model effectively feeds low-power electronic loads by directly adjusting the output voltage level to the set voltage, even under different vibration severity levels. As a result, the proposed PEHS dynamic model serves as a guideline for researchers in the development of self-powered sensors, which contributes to understanding sustainable energy alternatives.

In this study, we obtained results for the computation of eigen-pairs, singular value decomposition, pseudo-inverse, and the least square problem for elliptic quaternion matrices. Moreover, we established algorithms based on these results and provided illustrative numerical experiments to substantiate the accuracy of our conclusions. In the experiments, it was observed that the p-value in the algebra of elliptic quaternions and elliptic numbers directly affects the performance of the problem under consideration. Selecting the optimal p-value for problem-solving and the elliptic behavior of many physical systems make this number system advantageous in applied sciences.

Using assembly theory, we investigate the assembly pathways of binary strings of length N formed by joining bits present in the assembly pool and the strings that entered the pool as a result of previous joining operations. We show that the string assembly index is bounded from below by the shortest addition chain for N, and we conjecture about the form of the upper bound. We define the degree of causation for the minimum assembly index and show that for certain N it features regularities that can be used to determine a shortest addition chain. We show that a string with the smallest assembly index for N can be assembled by a binary program of length equal to this index if the length of this string is expressible as a product of Fibonacci numbers. We conjecture that there is no binary program that has a length shorter than the length of the string having the largest assembly index for N that could assemble this string. The results confirm that four Planck areas provide a minimum information capacity that corresponds to a minimum thermodynamic (Bekenstein-Hawking) entropy. Knowing that the problem of determining the assembly index is at least NP-complete, we conjecture that this problem is NP-complete, while the problem of creating the string so that it would have a predetermined largest assembly index is NP-hard. The proof of this conjecture would imply P ≠ NP, since every computable problem and every computable solution can be encoded as a finite binary string.

The effect of neutron irradiation of Si-Ge/Si film structures obtained by gas-phase epitaxy on the processes of charge carrier generation and the magnitude of the dark short-circuit current and open-circuit voltage caused by it is studied, it is shown that their magnitude practically does not change with time. The results obtained indicate that all types of structural defects, both associated with dopant impurities and radiation exposure, contribute to the generation of charge carriers in heated silicon structures with the participation of deep energy levels, which indicates the applicability of neutron processing of silicon materials to create thermal energy converters, operating at high temperatures.

Inhibition of quorum sensing (QS)-dependent biofilm formation and virulence is extensively investigated as a novel approach to combat bacterial pathogens by impeding their ability to cause antibiotic-tolerant diseases. Such strategies are considered a promising alternative to conventional antibacterial therapy since interrupting the central cell-to-cell communication system imposes less selective pressure on the target pathogen. In this study, novel hybrid compounds composed of anthranilic acids substituted with halogens at different positions of the phenyl ring, and 4-(2-aminoethyl/4-aminobuthyl)amino-7-chloroquinoline linked via 1,3,4-oxadiazole were synthesized using standard procedures. Their anti-QS activities were evaluated using Chromobacterium violaceum ATCC31532 (anti-biofilm and bactericidal activities) and Pseudomonas aeruginosa PAO1 (anti-biofilm/-virulence activities). The results showed that compounds 15–19 and 23 inhibited the production of violacein, the QS-inducible pigment, in C. violaceum to a similar extent as the model QS inhibitor - quercetin (83.5–90%). Compound 15 exhibited the strongest effect on P. aeruginosa in the anti-biofilm screening, reducing its ability to form biofilm by almost 50%, while compounds 16 and 19 were able to reduce the biofilm formation by approximately 30%. However, compound 23 did not demonstrate significant anti-biofilm activity and only inhibited pyocyanin production in P. aeruginosa. In conclusion, this study suggests that 1,3,4-oxadiazoles 15, 16, and 19 are the most promising compounds for future research as novel QS inhibitors against Gram-negative bacteria equipped with different QS signaling pathways.

A simple and sensitive liquid chromatography-tandem mass spectrometry (LC– MS/MS) method has been developed for the simultaneous determination of atorvastatin (ATOR), ezetimibe (EZM) and their three metabolites including o-hydroxyl atorvastatin (o-OH ATOR), p-hydroxyl atorvastatin (p-OH ATOR), and ezetimibe-glucuronide (EZM-G) in human plasma using benzyl paraben (BP) as internal standard (IS). The analytes and IS were ionized using ESI positive ion mode (ATOR, o-OH ATOR, and p-OH ATOR), ESI negative ion mode (EZM, EZM-G, and BP), and operated in multiple reaction monitoring (MRM) mode. They were next extracted by salting-out assisted liquid–liquid extraction with acetonitrile, and then analyzed by liquid chromatography on a reversed-phase chromatographic column (50 mm × 4.6 mm; 3.5 µm), using a mixture of ac-etonitrile and an acetic acid solution (0.5%) as the mobile phase, showing high extraction effi-ciency (>70%), and a minimized matrix effect. The method was satisfactorily validated, and showed excellent linearity over wide concentration ranges of 0.06–15 ng/mL, 0.6–150 ng/mL, 0.4–100 ng/mL, 0.12–30 ng/mL, and 0.05–3 ng/mL for EZM, EZM-G, ATOR, o-OH ATOR, and p-OH ATOR, respectively.

BackgroundIt is unclear what underpins the large global variations in the prevalence of fluoroquinolone resistance in gram-negative bacteria. We tested the hypothesis that different intensities in the use of quinolones for food-animals plays a role. MethodsWe used Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in human infections with Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa was correlated with the use of quinolones for food producing animals. Linear regression was used to assess the relative contributions of country-level quinolone consumption for food-animals and humans on fluoroquinolone resistance in these 4 species. ResultsThe prevalence of fluoroquinolone resistance in each species was positively associated with quinolone use for food-producing animals (E. coli [ρ=0.55; P<0.001], K. pneumoniae [ρ=0.58; P<0.001]; A. baumanii [ρ=0.54; P=0.004]; P. aeruginosa [ρ=0.48; P=0.008]). Linear regression revealed that both quinolone consumption in humans and food animals were independently associated with fluoroquinolone resistance in E. coli and A. baumanii. ConclusionsReducing quinolone use in food-producing animals may help retard the spread of fluoroquinolone resistance in various gram negative bacterial species.

In this paper, the notion of θ∗-weak contraction is introduced, which is utilized to prove some fixed point results. These results are helpful to give a positive response to certain open question raised by Kannan [Amer. Math. Monthly 76:1969] and Rhoades [Contemp. Math. 72:1988] on the existence of contractive definition which does not force the mapping to be continuous at the fixed point. Some illustrative examples are also given to support our results. As applications of our result, we investigate the existence and uniqueness of a solution of non-linear matrix equations and integral equations of Volterra type as well.

Different contact materials along with optimization of the deposition techniques expand the possibilities to obtain high performance room temperature CdTe-based X/γ-ray detectors. The heterostructures with ohmic (MoOx) and Schottky (MoOx, TiOx, TiN, and In) contacts, created by DC reactive magnetron sputtering and vacuum thermal evaporation, as well as In/CdTe/Au diodes with a p-n junction, formed by laser-induced doping, were developed and investigated. Depending on the pre-treatment of the surface of semi-insulating p-CdTe crystals, deposition of a MoOx film formed an ohmic or Schottky contact. Based on the calculations and IV characteristics of the fabricated Mo-MoOx/р-CdTe/MoOx-Mo, In/CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo Schottky-diode detectors, the current transport processes were described in the models of the carrier generation-recombination within the space-charge region (SCR) at low bias voltages, and space-charge limited current at higher voltages, respectively. The energies of generation–recombination centers, density of trapping centers, and carrier lifetimes were determined. A sharp increase in the reverse current in the Mo-MoOx/р-CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo heterostructures at high bias was discussed in frames of the Poole–Frenkel emission model. Nanosecond laser irradiation of the In electrode, pre-deposited on the p-CdTe crystals, resulted in an increase in the voltage range, corresponding to the carrier generation-recombination in the SCR, in the IV characteristics of the In/CdTe/Au diodes. Such In/CdTe/Au p-n junction diodes demonstrated high energy resolutions (7%@59.5 keV, 4%@122 keV, and 1.6%@662 keV).

Arabidopsis contains eight different h-type thioredoxins (Trx) being distributed in different cell organelles. Although Trx h2 is deemed to be localized in mitochondria, its subcellular localization and function remains a matter of debate. Here, Trx h2 localization and function were investigated using cell fractionation studies and reverse genetics. Differential centrifugation and immunodetection showed the Trx h2 protein to be distributed to the microsomal fraction rather than to mitochondrial preparations. To analyze whether Trx h2 has different roles than mitochondrial Trxs, Arabidopsis mutants lacking Trx h2 were compared with mutants deficient in mitochondrial Trx o1 and double mutants with joint deficiencies in both Trxs. Under constant medium light, trxh2 grew as the wild type, while trxo1 and trxo1h2 mutants showed impaired growth. This was accompanied by differences in the metabolite profiles. The trxo1 and trxo1h2 mutants clustered differently from the wild type during the night, revealing a decrease in ascorbate and glutathione redox states. In fluctuating light intensities, genotypic differences in growth rates were attenuated. Compared to the wild type, the fluctuating-light induced decrease in the NADPH/NADP ratio was diminished in the mutants, with the trxo1h2 double mutant showing the strongest effect. This was accompanied by an increase in the photosynthetic efficiency of the trxo1h2 mutant, specifically in the high light phases of fluctuating light. Conclusively, these results support the view that Trxs o1 and h2 are localized in different subcellular compartments, and have different effects on ascorbate and glutathione redox states and growth in medium light, but cooperatively affect NADP(H) redox state and photosynthetic efficiency in fluctuating light.

Transforming growth factor beta (TGF-β) is a determinant for inflammation and fibrosis in cardiac and skeletal muscle in Chagas disease. To determine its regulatory mechanisms, we investigated the response of T. cruzi-infected cardiomyocytes (CM), cardiac fibroblasts (CF) and L6E9 skeletal myoblasts to TGF-β. Cultures of CM, CF and L6E9 were infected with T. cruzi (Y strain) and treated with TGF-β (1–10 ng/mL, 1h or 48 h). Fibronectin (FN) distribution was analyzed by immunofluorescence and Western blot (WB). Phosphorylated SMAD2 (PS2), phospho-p38 (p-p38), and phospho-c-Jun (p-c-Jun) signaling were evaluated by WB. CF and L6E9 showed an increase in FN from 1 ng/mL of TGF-β, while CM displayed FN modulation only after 10 ng/mL treatment. CF and L6E9 showed higher PS2 levels than CM, while p38 is less stimulated in CF than CM and L6E9. After T. cruzi infection, localized FN disorganization was observed in infected CF and L6E9. T. cruzi induced an increase in FN in CF cultures, mainly in uninfected cells. Infected CF cultures treated with TGF-β showed a reduction in PS2 and an increase in p-p38 and p-c-Jun levels. Our data suggest that p38 and c-Jun pathways may be participating in the fibrosis regulatory process mediated by TGF-β after T. cruzi infection.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we study the p-adic integral representation on Z_p of q-Bernoulli numbers arising from two variable q-Bernstein polynomials and investigate some properties for the q-Bernoulli numbers. In addition, we give some new identities of q-Bernoulli numbers.

In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

Piezoelectric nanotransducers may offer key advantages in comparison with conventional piezoelectrics, including more choices for types of mechanical input, positions of the contacts, dimensionalities and shapes. However, since piezo-semiconductive nanostructures are generally much easier to fabricate and integrate into functional systems than insulating materials, modeling becomes significantly more intricate and the effects of free charges have been considered only in a few studies. The available reports are complicated by the absence of proper nomenclature and figures of merit. Besides, some analyses are incomplete. For instance, the local piezopotential and free charges within axially strained conical piezo-semiconductive nanowires have only been systematically investigated for very low doping (1016 cm-3) and under compression. Here we give the definitions for the enhancement, depletion, base and tip piezopotentials, their characteristic lengths and both the tip-to-base and the depletion-to-enhancement piezopotential-ratios. As an example, we use these definitions for analyzing the local piezopotential and free charges in n-type ZnO truncated conical nanostructures with different doping levels (intrinsic, 1016 cm-3, 1017 cm-3) for both axial compression and traction. The definitions and concepts presented here may offer insight for designing high performance piezosemiconductive nanotransducers.

Solid tumor cells have an altered metabolism that can protect them from cytotoxic lymphocytes. The antidiabetic drug metformin modifies tumor cell metabolism and several clinical trials are testing its effectiveness for the treatment of solid cancers. The use of metformin in hematologic cancers has received much less attention, although allogeneic cytotoxic lymphocytes are very effective against these tumors. We show here that metformin induces expression of Natural Killer G2-D (NKG2D) ligands (NKG2DL) and intercellular adhesion molecule-1 (ICAM-1), a ligand of the lymphocyte function-associated antigen 1 (LFA-1). This leads to enhance sensitivity to cytotoxic lymphocytes. Overexpression of antiapoptotic Bcl-2 family members decrease both metformin effects. The sensitization to activated cytotoxic lymphocytes is mainly mediated by the increase on ICAM-1 levels, which favors cytotoxic lymphocytes binding to tumor cells. Finally, metformin decreases the growth of human hematological tumor cells in xenograft models, mainly in presence of monoclonal antibodies that recognize tumor antigens. Our results suggest that metformin could improve cytotoxic lymphocyte-mediated therapy.

Studies on integrating Spiking Neural Networks (SNNs) with the Transformer architecture holds promise for enabling models to achieve ultra-low energy consumption while possessing the performance of the Transformer architecture. Currently, studies on ANN-to-SNN conversion of integrating Spiking Neural Networks (SNNs) with the Transformer architecture mainly focuses on simple activation functions in MLPs, and has not yet addressed the mismatch between the Softmax activation function in the self-attention mechanism and the computation rules of SNNs. Consequently, the ANN-to-SNN conversion efforts have consistently failed to make the Transformer architecture directly applicable to SNNs. To address this challenge, we propose the Spiking-Softmax method, which integrates Spiking Exponential Neuron (SI-exp) and Spiking Collaboration Normalized Neuron (SI-norm). The Spiking-Softmax method accurately simulates the Softmax activation function with only 12 time steps. Building upon this, we propose the Spike Integrated Transformer conversion (SIT-conversion) method, which enables the conversion of the Transformer architecture to SNNs. The SNNs generated by the SIT-conversion of Transformer models of various sizes achieve accuracy nearly identical to their ANNs counterparts, achieving nearly lossless and ultra-low-latency ANN-to-SNN conversion. This work represents the first implementation of simulating the Softmax activation function and fully converting the Transformer architecture into SNNs through spike firing.

The incorporation of electric vehicles (EVs) with vehicle-to-grid (V2G) offers the development of multi-energy microgrid (MMOs) models. However, MMOs have among their goals to decrease electricity costs by coordinating with vehicle-to-grid (V2G) scheduling. Controlling V2G models poses uncertainties about the voltages developed and creates the need for power generation disruptions. In this work, a Feed-Forward-Back-Propagation Network (FFBPN) is developed with Matlab software, based on the Levenberg-Marquardt algorithm by varying the number of hidden neurons to realize better performance thanks to the value of the Maximum Coefficient of De-termination (R2) and the Minimum Mean Squared Error (MSE). In this article, the dataset from NASA PCoE has been used to make proper consideration of the model that best calculates the life cycle of the battery, demonstrating relevant implications for future development of this type of system based on FFBPN for the integration of EV into V2G. The proposed FFBPN demonstrates better performance than other methods taken from the literature. In conclusion, the comparison between the phases of training, validation and test are used to completely represent the validity of the proposed model and precisely to identify the characteristics curves of FFBPN for future ap-plications highlighting its performance to create profitability, efficiency, production, energy saving and minimum environmental impact.

While various studies have explored the integration of sustainability in the construction sector of Tanzania, particularly in areas like energy efficiency and green building practices, there remains a significant gap in understanding the specific barriers to the selection of sustainable building materials (SBMs) in residential projects. This research intends to bridge this gap by identifying and analyzing the critical barriers that hinder the effective selection of SBMs in Tanzania's residential building projects. By employing qualitative interviews with experts from regulatory bodies, public developers, and academic researchers, the study provides a comprehensive overview of the barriers. To ensure the collection of relevant and insightful data, the study involved the selection of participants based on specific criteria tailored to each category of experts. To be able to analyze qualitatively the data collected, this study employed Atlas.ti and MS Excel software. The findings revealed six categories of critical barriers affecting the selection of SBMs for residential building projects in Tanzania were identified and analyzed: (1) Regulatory and Policy Barriers (2) Financial Barriers (3) Knowledge and Awareness Barriers (4) Technical Barriers (5) Market and Supply Chain Issues (6) Cultural and Social Barriers. Moreover, the lack of awareness and limited knowledge issue were as equally importantly voiced as regulatory and policy barriers to affect the effective selection of sustainable materials in Tanzania. This study underscores the need for targeted policy interventions that address the lack of awareness, financial difficulties, and the absence of comprehensive regulatory frameworks to promote the selection of sustainable materials.

This narrative review synthesizes findings from empirical studies to explore the factors influencing the adoption of ChatGPT in higher education. The review highlights several critical determinants, both confirmed and debatable, of ChatGPT acceptance among students and educators. Previous studies have predominantly utilized theories such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Diffusion of Innovations (DoI) theory. Confirmed factors include performance expectancy, effort expectancy, social influence, facilitating conditions, and trust, which significantly predict user attitudes and intentions toward adopting ChatGPT. Perceived usefulness and ease of use are core components influencing adoption positively. However, some factors have shown inconsistent impacts. While generally critical, effort expectancy and facilitating conditions vary based on context. Social influence, demographic characteristics (age, gender), extrinsic motivation, and technology readiness exhibit inconsistent effects, suggesting that intrinsic motivations may be more critical. Data collection primarily used online surveys with structured questionnaires, varying widely in sample sizes from small pilot studies to large-scale surveys and covering diverse academic disciplines. Practical implications suggest enhancing perceived usefulness and ease of use through training and technical support, building trust by addressing privacy concerns, and leveraging social influence to drive adoption. The review underscores the need to refine technology acceptance models to incorporate broader psychological and contextual factors, integrate intrinsic motivation theories, and adopt a systems thinking approach. Addressing limitations such as potential selection bias and the quality and scope of existing studies, future research can develop robust models and provide deeper insights into ChatGPT adoption dynamics in higher education, supporting its effective integration to enhance learning outcomes and foster educational innovation.

Heart failure is a major global health concern, especially in Ethiopia. Numerous studies have analyzed heart failure data to inform decision-making, but these often struggle with limitations to accurately capture death dynamics and account for within-cluster dependence and heterogeneity. Addressing these limitations, this study is then to incorporate the dependence and to analyze heart failure data to estimate survival time and identify risk factors affecting patient survival. The data, obtained from 497 patients at Jimma University Medical Center in Ethiopia, were collected between July 2015 and January 2019. Residence was considered as the clustering factor in the analysis. We employed the Bayesian accelerated failure time (AFT), and Bayesian AFT shared gamma frailty models, comparing their performance using the Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). The Bayesian log-normal AFT shared gamma frailty model had the lowest DIC andWAIC, with well capturing cluster dependency that attributed to unobserved heterogeneity between patient residences. Unlike other methods that use Markov-Chain Monte-Carlo (MCMC), we applied the Integrated Nested Laplace Approximation (INLA) to reduce computational load. The study found that 39.44% of patients died, while 60.56% were censored, with a median survival time of 34 months. Another interesting finding of this study is by adding frailty into the Bayesian AFT models has boosted the performance in fitting the heart failure dataset. Significant factors reducing survival time included age, chronic kidney disease, heart failure history, diabetes, heart failure etiology, hypertension, anemia, smoking, and heart failure stage. The Bayesian model also showed lower standard errors for parameters compared to other methods, highlighting the importance of frailty models in accurately assessing survival time in heart failure patients.

Previous literature has linked working for pay while attending university with negative academic and health outcomes, yet working students are often resilient when experiencing such adverse circumstances. This makes it crucial to explore potential psychological mechanisms which transform adverse experiences into sources of motivation and persistence for working students. We explore one mechanism – social identification – and its different foci – identifying as a student, employee, working student, or as a student of one’s discipline of study – as potential predictors of important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes in three cross-sectional studies. In Study 1, part-time working hours (but not identification processes) were associated with academic self-efficacy. In Study 2, discipline identification and part-time working hours were associated with using deep approaches to learning. In Study 3, student identification was associated with increased status in society. Overall, discipline identification may be solely linked to academic outcomes, yet student identification should be explored further as a potential enhancer of social and graduate outcomes. We discuss additional mechanisms which can help to transform working students’ experiences through their social identities and suggest boundary conditions which can affect the link between these identities and important outcomes.

The study aims at evaluating the demand of forest bathing in the Northern Italy’s regions underlining the willingness to pay and the potential tourists’ habits and flows on attending alpine contexts. Through the submission of a questionnaire, the sample’s answers have been analyzed employing a stratified sampling methodology considering three different macro areas (Northwest regions, Northeast regions, and Friuli Venezia Giulia region). After analyzing the sample attitudes, the research approached the estimation section by calculating the flow as the number of potential forest bathing hikes per year and the willingness to pay trough the Contingent Valuation Method. The main results indicate that Forest Bathing activity in Northern Italy have a considerable monetary value and it is generally compared with positive feelings, particularly concerning well-being, and fascination factors.

Introduction: Rural Americans face significant health disparities due to limited access to healthcare services. Telehealth has emerged as a promising solution to mitigate these disparities by facilitating remote access to medical care. This paper comprehensively reviews the advantages, challenges, and implementation strategies of telehealth in rural areas.Method: A narrative review methodology was employed to synthesize existing literature and case studies on telehealth in rural settings. Databases such as PubMed, Google Scholar, and JSTOR were searched for relevant studies published in the last three decades. Keywords such as "telehealth," "rural health," and "healthcare disparities" guided the search process. The review focused on studies assessing the impact of telehealth on healthcare access, cost-effectiveness, and quality of care in rural areas.Results: The review findings indicate that telehealth significantly enhances healthcare access by reducing travel distances, increasing availability of specialist consultations, and promoting patient engagement. It improves chronic disease management and patient satisfaction by enabling convenient access to healthcare services at home. Despite initial setup costs and challenges such as broadband access and regulatory issues, telehealth demonstrates long-term cost savings through reduced travel expenses and improved healthcare efficiency. Quality of care is enhanced through improved communication between healthcare providers and patients, leading to better treatment adherence and health outcomes.Conclusion: Telehealth represents a transformative approach to address healthcare disparities in rural areas. It offers a cost-effective solution to improve access to healthcare services, enhance patient outcomes, and reduce healthcare costs in the long run. However, successful implementation requires addressing infrastructure challenges, refining reimbursement policies, and ensuring regulatory support. Future efforts should focus on expanding broadband infrastructure, refining policy frameworks, and conducting further research to optimize telehealth's impact on rural healthcare delivery.

Computational neuroscience has undergone a significant transformation in recent years, driven by the exponential growth of neural data and advancements in data science and machine learning. While traditional theoretical models remain valuable, there is a growing emphasis on integrating data-driven approaches to develop more accurate, biologically plausible, and predictive models of neural function. This shift has led to a new equilibrium in the field, where data-driven model development, machine learning techniques, and hybrid approaches that combine data and theory are increasingly prevalent. In this article, we discuss the evolving landscape of computational neuroscience, highlighting the importance of data-driven methods and the emergence of a more integrative approach that leverages both data and theory to unlock the mysteries of the brain. We also explore the implications of this shift for future research and clinical applications, emphasizing the potential for data-driven computational neuroscience to revolutionize our understanding of neural function and pave the way for new treatments for neurological disorders.

This research presents a novel algorithmic implementation to improve the analysis of visually controlled interception and accompanying motor action through the computational application of harmonic ratios and stimulation invariants. Unlike traditional models that focus mainly on psychological aspects, our approach integrates the relevant constructs into a practical mathematical framework. This allows for dynamic prediction of interception points with improved accuracy and real-time perception-action capabilities, essential for applications in neurorehabilitation and virtual reality. Our methodology uses stimulation invariants as key parameters within a mathematical model to quantitatively predict and improve interception outcomes. The results demonstrate the superior performance of our algorithms over conventional methods, confirming their potential for ad-vancing robotic vision systems and adaptive virtual environments. By translating complex theo-ries of visual perception into algorithmic solutions, this study provides innovative ways to im-prove motion perception and interactive systems. This study aims to articulate the complex inter-play of geometry, perception, and technology in understanding and utilizing cross-ratios at infin-ity, emphasizing their practical applications in virtual and augmented reality settings.