Assessing indoor environmental quality (IEQ) is fundamental to ensuring health, well-being, and safety. A particular type of indoor compartment, land transport cabins (LTCs), specifically those of trains and buses, was surveyed. The global rise in commute and in-cabin exposure time gives relevance to the current study. This study discusses indoor climate (IC) in LTCs to emphasize the risk to the well-being and comfort of exposed occupants linked to poor IEQ, using objective assessment and a communication method following recommendations of the CEN-EN16798-1 standard. The measurement campaign was carried out on 36 trips of real-time travel on 15 buses and 21 trains, mainly in the EU region. Although the measured operative temperature, relative humidity, CO₂, and VOC levels followed EN16798-1 requirements in most cabins, compliance gaps were found in the indoor climate of these LTCs as per ventilation requirements. Also, the PMV-PPD index evaluated in two indoor velocity ranges of 0.1 and 0.3 m/s showed that 39% and 56% of the cabins, respectively, were thermally inadequate. Also, ventilation parameters showed that indoor air quality (IAQ) was defective in 83% of the studied LTCs. Therefore, gaps exist concerning the IC of the studied LTCs, suggesting potential risks to well-being and comfort and the need for improved compliance with the IEQ and ventilation criteria of EN16798-1. Full article

Failure mode and effects analysis (FMEA) helps to identify the weak points in the processing, manufacturing, and assembly of products and plays an important role in improving product reliability. To address the shortcomings of the existing FMEA methods in terms of the uncertainty treatment of information and not considering the weights and correlations between risk factors, we propose a new FMEA method. In this paper, the Fermatean fuzzy Z-number (FFZN) is proposed by fusing the Fermatean fuzzy number and Z-number. Extending it to the Bonferroni mean (BM) operator, the Fermatean fuzzy Z-number-weighted Bonferroni mean (FFZWBM) operator is proposed. A new FMEA method is proposed based on this operator. In order to overcome the factors not considered in the FMEA method, two new risk factors are proposed and added. The ability of experts to express fuzzy information is enhanced by introducing the FFS. The weights and correlations between the influencing factors can be handled by aggregating the evaluation information using the FFZWBM operator. Finally, the proposed method is applied to an arithmetic example and the accuracy of the proposed method is proved by teaming it with other methods. Full article

Despite the large number of existing varieties of Vitis vinifera L., only few occupy a large niche in today’s highly globalized wine market. The increasing consumer demand for diversified products, as well as the changing climatic conditions, make establishing a process of varietal diversification essential to achieve both challenges. It is for this reason that the study of minority varieties, which have a higher level of adaptation to each area of origin, is of particular interest. With the main objective of achieving an in-depth knowledge of minority varieties in Spain, the national research project ‘Valorization of Minority Grapevine Varieties for their Potential for Wine Diversification and Resilience to Climate Change’ (MINORVIN), has been proposed. Within this extensive project, the present study describes the aroma profiles of 60 single-variety wines, corresponding with 44 different varieties, with 12 of these varieties being studied at the same time in several Spanish regions. Volatile compounds were determined through three consecutive vintages using gas chromatography-mass spectrometry (GC-MS) and gas chromatography–flame ionization detector (GC-FID). Compounds were grouped into major compounds, including alcohols, C₆ compounds, esters, acetates, acids, carbonyl compounds, and other type of compounds, and minor compounds, including lactones, terpenes, and C₁₃-norisoprenoids, according to their concentration in the wines being analyzed. Among this last group of compounds, lactones were quantitatively the most abundant, followed by terpenes. This study reflects that minority variety wines show distinctive aromatic profiles, supporting the importance of valuing and promoting the autochthonous minority grapevine varieties for the Spanish winemaking industry. Full article

Underwater gliders have emerged as effective tools for long-term ocean exploration. Employing aircraft for launching underwater gliders could significantly expand their application. Compared to slender underwater vehicles, the distinctive wing structure of underwater gliders may endure huge impact forces when entering water, leading to more intricate impact load characteristics and potential wing damage. This paper employs a computational fluid dynamics approach to analyze the water entry event of an airdropped underwater glider and its impact load behavior. The results indicate that the glider impact load is enhanced prominently by the wing, and that the extent of enhancement is influenced by the entry attitude. At an entry angle of 80°, the glider exhibits the maximum impact load during different water entry angles. In addition, a larger attack angle indicates a higher glider impact load. Our present study holds significant importance for both the hydrodynamic shape design and water entry strategy control of airdropped underwater gliders. Full article

To investigate the dissolution mechanism of Ti metal, ab initio calculations were conducted to observe the impact of Ti vacancy defects on the O-adsorbed Ti(0001) surface, focusing on the formation energies of Ti vacancy, geometric structures, and electronic structures. The surface structures subsequent to Ti dissolution were simulated by introducing a Ti cavity on both clean and O-adsorbed Ti(0001) surfaces. Our findings indicated that Ti vacancy formation energies and electrochemical dissolution potential on the O-adsorbed Ti(0001) surface surpassed those on the clean surface, and they increased with increasing O coverage. This suggested that O adsorption inhibited Ti dissolution and enhanced O atom interaction with the Ti surface as O coverage increased. Furthermore, at higher O coverage, Ti vacancies contributed to the strengthening of Ti-O bonds on the O-adsorbed Ti(0001) surface, indicating that Ti dissolution aided in stabilizing the Ti surface. The formation of Ti vacancies brought the atomic ratio of Ti to O on the Ti surface closer to that of TiO₂, potentially explaining the increased stability of the structure with Ti vacancies. Full article

It is a common view that Popper’s defense of the open society has been a defense of Western, liberal democracies. This seems to imply that by fostering democratic institutions we are ipso facto fostering open societies. I criticize this view by arguing that in-built incentives in democratic mechanisms move us away from (or hamper) the open society. Democracy promotes voters’ ignorance, indulges voters’ irrationality, and allows voters to externalize costs. This is contrary to well-informed, rational decisions and personal responsibility that lie at the fundamentals of the open society. I suggest that it has been free-market capitalism, or free-market societies, which has moved us closer to the ideal of the open society and which best realizes open society’s values. Full article

Cultivated land plays a crucial role as the basis of grain production, and it is essential to effectively manage the unregulated expansion of non-grain production (NGP) on cultivated land in order to safeguard food security. The study of NGP has garnered significant attention from scholars, but the prediction of NGP trends is relatively uncommon. Therefore, we focused on Jiangsu Province, a significant grain production region in China, as the study area. We extracted data on cultivated land for non-grain production (NGPCL) in 2000, 2005, 2010, 2015, and 2019, and calculated the ratio of non-grain production (NGPR) for each county unit in the province. On this basis, Kernel Density Estimation (KDE) and spatial autocorrelation analysis tools were utilized to uncover the spatio-temporal evolution of NGP in Jiangsu Province. Finally, the Patch-Generating Land Use Simulation (PLUS) model was utilized to predict the trend of NGP in Jiangsu Province in 2038 under the three development scenarios of natural development (NDS), cultivated land protection (CPS), and food security (FSS). After analyzing the results, we came to the following conclusions:(1) During the period of 2000–2019, the NGPCL area and NGPR in Jiangsu Province exhibited a general decreasing trend. (2) The level of NGP displayed a spatial distribution pattern of being “higher in the south and central and lower in the north”. (3) The results of multi-scenario simulation show that under the NDS, the area of NGPCL and cultivated land for grain production (GPCL) decreases significantly; under the CPS, the decrease in NGPCL and GPCL is smaller than that of the NDS. Under the FSS, NGPCL decreases, while GPCL increases. These results can provide reference for the implementation of land use planning, the delineation of the cultivated land protection bottom line, and the implementation of thee cultivated land use control system in the study area. Full article

Generating synthetic data is a complex task that necessitates accurately replicating the statistical and mathematical properties of the original data elements. In sectors such as finance, utilizing and disseminating real data for research or model development can pose substantial privacy risks owing to the inclusion of sensitive information. Additionally, authentic data may be scarce, particularly in specialized domains where acquiring ample, varied, and high-quality data is difficult or costly. This scarcity or limited data availability can limit the training and testing of machine-learning models. In this paper, we address this challenge. In particular, our task is to synthesize a dataset with similar properties to an input dataset about the stock market. The input dataset is anonymized and consists of very few columns and rows, contains many inconsistencies, such as missing rows and duplicates, and its values are not normalized, scaled, or balanced. We explore the utilization of generative adversarial networks, a deep-learning technique, to generate synthetic data and evaluate its quality compared to the input stock dataset. Our innovation involves generating artificial datasets that mimic the statistical properties of the input elements without revealing complete information. For example, synthetic datasets can capture the distribution of stock prices, trading volumes, and market trends observed in the original dataset. The generated datasets cover a wider range of scenarios and variations, enabling researchers and practitioners to explore different market conditions and investment strategies. This diversity can enhance the robustness and generalization of machine-learning models. We evaluate our synthetic data in terms of the mean, similarities, and correlations. Full article

Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches. Full article

In this work, Ce-doped Ti₆Cr₁₄V₈₀ BCC hydrogen-storage alloys have been synthesized as catalysts to enhance the hydrogen-storage performance of MgH₂ based on its room-temperature activation features and excellent durability. The Ti₆Cr₁₄V₈₀Ce₁ alloy was pre-ball milled under a hydrogen atmosphere into a Ti₆Cr₁₄V₈₀Ce₁H_x hydride. Different amounts of the Ti₆Cr₁₄V₈₀Ce₁H_x hydride were incorporated into MgH₂ by ball milling to obtain the MgH₂ + y wt%Ti₆Cr₁₄V₈₀Ce₁H_x (y = 0, 3, 5, 10, 15) nano-composites. With an optimization doping of 10 wt%Ti₆Cr₁₄V₈₀Ce₁H_x, the initial dehydrogenated temperature was decreased to 160 °C. Moreover, the composite can rapidly release 6.73 wt% H₂ within 8 min at 230 °C. Also, it can absorb 2.0 wt% H₂ within 1 h even at room temperature and uptake 4.86 wt% H₂ within 10 s at 125 °C. In addition, the apparent dehydrogenated activation energy of the MgH₂ + 10 wt%Ti₆Cr₁₄V₈₀Ce₁H_x composite was calculated to be 62.62 kJ mol⁻¹ fitted by the JMAK model. The capacity retention was kept as 84% after 100 cycles at 300 °C. The ball milled Ti₆Cr₁₄V₈₀Ce₁H_x transformed from the initial FCC phase structure into a BCC phase after complete dehydrogenation and back into an FCC phase when fullly hydrogenated. A catalyst mechanism analysis revealed that the ‘autocatalytic effect’ originating in Ti₆Cr₁₄V₈₀Ce₁H_x plays a crucial role in boosting the de-/hydrogenation properties of MgH₂. This work provides meaningful insights into rational designs of nano-compositing with different hydrogen-storage alloy catalyzed MgH₂. Full article

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, they focus on quantitative analysis and do not give sufficient consideration to the relationship between HSFC and CEALU. Therefore, in this study, by relying on provincial panel data of China for the period 2005–2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: (1) China’s CEALU per unit area presented a fluctuating upward change, but the growth rate slowed down during the period 2005–2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%; (2) the high-standard farmland construction (HSFC) policy led a significant carbon emission reduction effect in agricultural land use and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing change; (3) the carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China. Full article

As one of the emerging nanomaterials, boron nitride nanotubes (BNNTs) provide promising opportunities for diverse applications due to their unique properties, such as high thermal conductivity, immense inertness, and high-temperature durability, while the instability of BNNTs due to their high surface induces agglomerates susceptible to the loss of their advantages. Therefore, the proper functionalization of BNNTs is crucial to highlight their fundamental characteristics. Herein, a simplistic low-cost approach of BNNT surface modification through catechol-polyamine (CAPA) interfacial polymerization is postulated to improve its dispersibility on the polymeric matrix. The modified BNNT was assimilated as a filler additive with AlN/Al₂O₃ filling materials in a PDMS polymeric matrix to prepare a thermal interface material (TIM). The resulting composite exhibits a heightened isotropic thermal conductivity of 8.10 W/mK, which is a ~47.27% increase compared to pristine composite 5.50 W/mK, and this can be ascribed to the improved BNNT dispersion forming interconnected phonon pathways and the thermal interface resistance reduction due to its augmented compatibility with the polymeric matrix. Moreover, the fabricated composite manifests a fire resistance improvement of ~10% in LOI relative to the neat composite sample, which can be correlated to the thermal stability shift in the TGA and DTA data. An enhancement in thermal permanence is stipulated due to a melting point (Tm) shift of ∼38.5 °C upon the integration of BNNT-CAPA. This improvement can be associated with the good distribution and adhesion of BNNT-CAPA in the polymeric matrix, integrated with its inherent thermal stability, good charring capability, and free radical scavenging effect due to the presence of CAPA on its surface. This study offers new insights into BNNT utilization and its corresponding incorporation into the polymeric matrix, which provides a prospective direction in the preparation of multifunctional materials for electric devices. Full article

Access to mental healthcare is undoubtedly of major importance for LGBT+ people worldwide, given the high prevalence of mental health difficulties due to minority stress exposures. This study drew mixed-method survey data from the community-based KAMI Survey (n = 696) to examine the enablers, barriers, and unmet needs experiences of LGBT+ individuals in accessing mental healthcare services in Malaysia. First, we present findings from a series of descriptive analyses for sociodemographic differences in unmet needs for mental healthcare, barriers, and satisfaction levels with different types of mental healthcare. Next, we conducted an inductive thematic analysis of open-text comments (n = 273), with relevance drawn to Andersen’s Behavioural Model of Healthcare. More than a quarter (29.5%) reported an unmet need for mental healthcare, and some groups (younger, asexual or queer, or participants living in non-major cities) reported higher unmet needs. More than three-fifths (60.5%) reported not knowing where to find culturally safe mental health professionals. The thematic analysis uncovered key contextual (e.g., mental health practitioners’ stance, stigma, collaborative client-care) and individual (e.g., positive expectation of mental health services and anticipated stigma) attributes that influence healthcare experiences. Participants also identified resources that facilitate healthcare utilisation, such as affordability, availability of suitable professionals, and geographical considerations. The implications of our findings for the mental healthcare practices in Malaysia were outlined. Full article

Background and objectives: This review aims to delve into the role of artificial intelligence in medicine. Ulcerative colitis (UC) is a chronic, inflammatory bowel disease (IBD) characterized by superficial mucosal inflammation, rectal bleeding, diarrhoea and abdominal pain. By identifying the challenges inherent in UC diagnosis, we seek to highlight the potential impact of artificial intelligence on enhancing both diagnosis and treatment methodologies for this condition. Method: A targeted, non-systematic review of literature relating to ulcerative colitis was undertaken. The PubMed and Scopus databases were searched to categorize a well-rounded understanding of the field of artificial intelligence and its developing role in the diagnosis and treatment of ulcerative colitis. Articles that were thought to be relevant were included. This paper only included articles published in English. Results: Artificial intelligence (AI) refers to computer algorithms capable of learning, problem solving and decision-making. Throughout our review, we highlighted the role and importance of artificial intelligence in modern medicine, emphasizing its role in diagnosis through AI-assisted endoscopies and histology analysis and its enhancements in the treatment of ulcerative colitis. Despite these advances, AI is still hindered due to its current lack of adaptability to real-world scenarios and its difficulty in widespread data availability, which hinders the growth of AI-led data analysis. Conclusions: When considering the potential of artificial intelligence, its ability to enhance patient care from a diagnostic and therapeutic perspective shows signs of promise. For the true utilization of artificial intelligence, some roadblocks must be addressed. The datasets available to AI may not truly reflect the real-world, which would prevent its impact in all clinical scenarios when dealing with a spectrum of patients with different backgrounds and presenting factors. Considering this, the shift in medical diagnostics and therapeutics is coinciding with evolving technology. With a continuous advancement in artificial intelligence programming and a perpetual surge in patient datasets, these networks can be further enhanced and supplemented with a greater cohort, enabling better outcomes and prediction models for the future of modern medicine. Full article

Uncontrolled abnormal cell growth, known as cancer, may lead to tumors, immune system deterioration, and other fatal disability. Early cancer identification makes cancer treatment easier and increases the recovery rate, resulting in less mortality. Gene expression data play a crucial role in cancer classification at an early stage. Accurate cancer classification is a complex and challenging task due to the high-dimensional nature of the gene expression data relative to the small sample size. This research proposes using a dimensionality-reduction technique to address this limitation. Specifically, the mutual information (MI) technique is first utilized to select influential biomarker genes. Next, an ensemble learning model is applied to the reduced dataset using only the most influential features (genes) to develop an effective cancer classification model. The bagging method, where the base classifiers are Multilayer Perceptrons (MLPs), is chosen as an ensemble technique. The proposed cancer classification model, the MI-Bagging method, is applied to several benchmark gene expression datasets containing distinctive cancer classes. The cancer classification accuracy of the proposed model is compared with the relevant existing methods. The experimental results indicate that the proposed model outperforms the existing methods, and it is effective and competent for cancer classification despite the limited size of gene expression data with high dimensionality. The highest accuracy achieved by the proposed method demonstrates that the proposed emerging gene-expression-based cancer classifier has the potential to help in cancer treatment and lead to a higher cancer survival rate in the future. Full article

The fall webworm (FWW), H. cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), is an extremely high-risk globally invasive pest. Understanding the invasion dynamics of invasive pests and identifying the critical factors that promote their spread is essential for devising practical and efficient strategies for their control and management. The invasion dynamics of the FWW and its influencing factors were analyzed using standard deviation ellipse and spatial autocorrelation methods. The analysis was based on statistical data on the occurrence of the FWW in China. The dissemination pattern of the FWW between 1979 and 2022 followed a sequence of “invasion-occurrence-transmission-outbreak”, spreading progressively from coastal to inland regions. Furthermore, areas with high nighttime light values, abundant ports, and non-forested areas with low vegetation cover at altitudes below 500 m were more likely to be inhabited by the black-headed FWW. The dynamic invasion pattern and the driving factors associated with the fall webworm (FWW) provide critical insights for future FWW management strategies. These strategies serve not only to regulate the dissemination of insects and diminish migratory tendencies but also to guarantee the implementation of efficient early detection systems and prompt response measures. Full article

Spodoptera exempta, known as the black armyworm, has been extensively documented as an invasive agricultural pest prevalent across various crop planting regions globally. However, the potential geographical distribution and the threat it poses to host crops of remains unknown at present. Therefore, we used an optimized MaxEnt model based on 841 occurrence records and 19 bioclimatic variables to predict the potential suitable areas of S. exempta under current and future climatic conditions, and the overlap with wheat, rice, and maize planting areas was assessed. The optimized model was highly reliable in predicting potential suitable areas for this pest. The results showed that high-risk distribution areas for S. exempta were mainly in developing countries, including Latin America, central South America, central Africa, and southern Asia. Moreover, for the three major global food crops, S. exempta posed the greatest risk to maize planting areas (510.78 × 10⁴ km²), followed by rice and wheat planting areas. Under future climate scenarios, global warming will limit the distribution of S. exempta. Overall, S. exempta had the strongest effect on global maize production areas and the least on global wheat planting areas. Our study offers a scientific basis for global prevention of S. exempta and protection of agricultural crops. Full article

The present study describes the enhancement of the nutritional values of gluten-free rice crackers by adding whole black rice grain flour. The crackers were prepared by combining whole brown rice flour (WRF) and whole black rice flour (BRF) in ratios of 0% (WRC), 25% (25-BRC), 50% (50-BRC), 75% (75-BRC), and 100% (BRC). The resulting samples underwent in-vivo effects on postprandial blood glucose levels as well as physicochemical and sensory analysis. In comparison to WRC, the samples containing 100% added black rice flour presented higher nutritional qualities in terms of protein, by 16.61%, 8.64% for lipids, 5.61% for ash, 36.94% for crude fiber, 58.04% for total polyphenols, 95.49% for proanthocyanidins, and 88.07% for flavonoids. The addition of BRF had a suppressing effect on lightness (L*) and yellowness (b*), while redness (a*) increased. The results of the glycemic measurements confirmed that consumption of crackers made from brown or black whole-grain rice grain flour does not generate glycemic peaks above the limit of 30 mg/dL in baseline blood glucose levels. The results of developing rice crackers from black and brown flour blends showed promising physicochemical and nutritional properties and could provide a good alternative to wheat flour as a gluten-free product. Full article

Current decision-making regarding urban design, architecture, and spatial planning often
emphasizes existing power balances, which historically have excluded other humans, such as
indigenous people, and nature from conversations and decision-making. The purpose of this study
is to explore if and how an empathic experience could give insights into how nature can be given
a voice, and, more concretely, how a group of trees on the TEC campus in Monterrey would feel
about a sudden change in their direct environment. The methodology is divided into three parts.
The first is the explanation of the case study and immersion of the (human) participants in the site.
The second stage consists of deep listening and reproducing the imagined expressions of the trees.
In the third stage, the participants return from the site, evaluate, and formulate a manifesto. The
experience suggests that it is possible to inspire human beings to imagine what trees would have to
say if we only imagined their language. It also shows that it is possible to gain access to a formerly
hidden environment. The conclusion is that the empathic access to these formerly muted worlds,
such as those of nature or socially marginalized peoples, can strengthen our understanding of, and
our ability to resolve, the current environmental crisis. Full article

The vision of a unified European HTA is by no means a new endeavor. At its core are the publicly declared ambitions to harmonize assessments of clinical data within the EU and avoid the duplication of efforts. Not surprisingly, these ambitions are publicly announced to be motivating the new 2022 EU HTA regulation. However, industry experts typically see more of a risk for additional bureaucracy resulting in delays, further scrutiny, and one additional EU (clinical) dossier to submit on top of all national HTA dossiers, which could be considered a duplication of effort and therefore counterproductive. Regardless of how the details of the process will be defined and how the entire process will work in practice, we can be sure that EU officials will refer to the EU HTA and Joint Clinical Assessment (JCA) in particular as a learning system. The purpose of this article is to take a closer look at the new EU HTA regulation and analyze threats and opportunities for manufacturers and what the resulting opportunities and threats will be at the affiliate level throughout the EU. Full article

Autophagy is an evolutionarily conserved lysosome-dependent degradation of cytoplasmic constituents. The system operates as a critical cellular pro-survival mechanism in response to nutrient deprivation and a variety of stress conditions. On top of that, autophagy is involved in maintaining cellular homeostasis through selective elimination of worn-out or damaged proteins and organelles. The autophagic pathway is largely responsible for the delivery of cytosolic glycogen to the lysosome where it is degraded to glucose via acid α-glucosidase. Although the physiological role of lysosomal glycogenolysis is not fully understood, its significance is highlighted by the manifestations of Pompe disease, which is caused by a deficiency of this lysosomal enzyme. Pompe disease is a severe lysosomal glycogen storage disorder that affects skeletal and cardiac muscles most. In this review, we discuss the basics of autophagy and describe its involvement in the pathogenesis of muscle damage in Pompe disease. Finally, we outline how autophagic pathology in the diseased muscles can be used as a tool to fast track the efficacy of therapeutic interventions. Full article

This article describes the development of current sensors used in DCU-type high-speed circuit breakers. DCU-type circuit breakers use the principle of turning off a constant short-circuit current by means of countercurrent. The article presents a new current sensor design called PIKh, which uses Hall sensors to measure current and determine its direction. PIKh sensors allow parallel operation of high-speed circuit breakers during the “parking” operation. The article includes the algorithm and principle of operation of the PIKh sensor. The proposed solution was verified on an electric traction vehicle. Full article