A living wall, when integrated with a mechanical ventilation system, can effectively improve the indoor thermal environment and reduce indoor CO₂ concentration during the transition season. In this study, a control experiment was conducted to analyze the effect of a living wall integrated with mechanical ventilation (LW-V) on indoor air quality. During the experiment, indoor air temperature, relative humidity, indoor air speed, and CO₂ concentration were measured, while the skin temperature was monitored and subjective questionnaires were administered to 60 subjects. The results show that the indoor environment was effectively improved by employing the LW-V system, with the average indoor temperature decreasing by 1.45 °C, while relative humidity increased by 19.1%. Due to the plant photosynthesis, CO₂ concentrations were reduced by 13.83 ppm. Meanwhile, the mean skin temperature was reduced by 0.18 °C and was closer to the neutral mean skin temperature. Questionnaire analysis reveals the LW-V system improved overall air freshness sensation and thermal comfort level by 1.09 and 0.53, respectively. The LW-V system improved the indoor thermal environment as well as air quality during the transition season significantly. Full article

This paper is the first to examine the operation of the HawkEye satellite in the presence of dust aerosol. The study region is the Black Sea. Dust transport dates were identified using visual inspection of satellite imagery, back-kinematic HYSPLIT trajectory analysis, CALIPSO aerosol stratification and typing maps, and the global forecasting model SILAM. In a comparative analysis of in-situ and satellite measurements of the remote sensing reflectance, an error in the atmospheric correction of HawkEye measurements was found both for a clean atmosphere and in the presence of an absorbing aerosol. It is shown that, on average, the dependence of the atmospheric correction error on wavelength has the form of a power function of the form from λ⁻³ to λ⁻⁹. The largest errors are in the short-wavelength region of the spectrum (412–443 nm) for the dust and dusty marine aerosol domination dates. A comparative analysis of satellite and in situ measurements of the optical characteristics of the atmosphere, namely the AOD and the Ångström parameter, was carried out. It is shown that the aerosol model used by HawkEye underestimates the Angström parameter and, most likely, large errors and outliers in satellite measurements are associated with this. Full article

The present study concerns the preparation of hybrid nanostructures composed of carbon dots (CDs) synthesized in our lab and a double-hydrophilic poly(2-dimethylaminoethyl methacrylate-co-oligo(ethylene glycol) methyl ether methacrylate) (P(DMAEMA-co-OEGMA)) random copolymer through electrostatic interactions between the negatively charged CDs and the positively charged DMAEMA segments of the copolymer. The synthesis of P(DMAEMA-co-OEGMA) copolymer was conducted through RAFT polymerization. Furthermore, the copolymer was converted into a strong cationic random polyelectrolyte through quaternization of the amine groups of DMAEMA segments with methyl iodide (CH₃I), and it was subsequently utilized for the complexation with the carbon dots. The molecular, physicochemical, and photophysical characterization of the aqueous solution of the copolymers and their hybrid nanoparticles was conducted using dynamic and electrophoretic light scattering (DLS, ELS) and spectroscopic techniques, such as UV-Vis, fluorescence (FS), and FT-IR spectroscopy. In addition, studies of their aqueous solution using DLS and ELS showed their responsiveness to external stimuli (pH, temperature, ionic strength). Finally, the interaction of selected hybrid nanoparticles with iron (III) ions was confirmed through FS spectroscopy, demonstrating their potential application for heavy metal ions sensing. Full article

This study deals with the prediction of recurring failures in water supply networks, a complex and costly task, but essential for the effective maintenance of these vital infrastructures. Using historical failure data provided by Companhia de Água e Esgotos da Paraíba (CAGEPA), the research focuses on predicting the time until the next failure at specific points in the network. The authors divided the failures into two categories: Occurrences of New Faults (ONFs) and Recurrences of Faults (RFs). To perform the predictions, they used predictive models based on machine learning, more specifically on MLP (Multi-Layer Perceptron) neural networks. The investigation unveiled that through the analysis of historical failure data and the consideration of variables including altitude, number of failures on the same street, and days between failures, it is possible to achieve an accuracy greater than 80% in predicting failures within a 90-day interval. This demonstrates the feasibility of using fault history to predict future water supply outages with significant accuracy. These forecasts allow water utilities to plan and optimize their maintenance, minimizing inconvenience and losses. The article contributes significantly to the field of water infrastructure management by proposing the applicability of a data-driven approach in diverse urban settings and across various types of infrastructure networks, including those pertaining to energy or communication. These conclusions underscore the paramount importance of systematic data collection and analysis in both averting failures and optimizing the allocation of resources within water utilities. Full article

This review examines respiratory complications in autoimmune rheumatic diseases within intensive care units (ICUs). The respiratory system, primarily affected in diseases like rheumatoid arthritis, systemic lupus erythematosus, and scleroderma, often leads to respiratory failure. Common manifestations include alveolar hemorrhage, interstitial fibrosis, and acute respiratory distress syndrome. Early recognition and treatment of non-malignant conditions are crucial to prevent rapid disease progression, with ICU mortality rates ranging from 30% to 60%. Delayed immunosuppressive or antimicrobial therapy may result in organ system failure. Collaboration with rheumatic specialists is vital for accurate diagnosis and immediate intervention. Mortality rates for rheumatic diseases in the ICU surpass those of other conditions, underscoring the need for specialized care and proactive management. The review emphasizes comprehensive assessments, distinguishing disease-related complications from underlying issues, and the importance of vigilant monitoring to enhance patient outcomes. Full article

This paper is devoted to studying a type of elliptic equation that contains a varying nonlocal term. We provide a detailed analysis of the existence, non-existence, and blow-up behavior of $L^2$-norm solutions for the related equation when the potential function $V\left(x\right)$ fulfills an appropriate choice. Full article

To explore the causes of mine tremors in coal mines with sandstone roofs, a three-point bending loading experiment was designed for composite sandstone layers, and the fracture and interlayer shear slip characteristics of the composite sandstone layers were studied using optical measurement and acoustic emission techniques. The results show that the bending of the rock layers led to interlayer sliding deformation, while the fracturing greatly promoted interlayer sliding. The maximum interlayer slip accelerations during bending deformation and fracturing were 0.6 mm/s² and 3.8 mm/s², respectively. During the fracturing of the rock layers, the proportion of acoustic emission shear fracture events increased with the continuous occurrence of long-lasting and high-amplitude acoustic emission events. The mechanism of mine tremors in thick sandstone roofs is as follows: the increase in the area of the goaf causes rock bending deformation and fracturing, accompanied by interlayer shear slip, fracturing of the sandstone layer, and friction dislocation at the cementation surface of the adjacent sandstone layers, which jointly cause vibration of the roof. Full article

In the first part of this article, the role of intestinal epithelial tight junctions (TJs), together with gastrointestinal dopaminergic and renin–angiotensin systems, are narratively reviewed to provide sufficient background. In the second part, the current experimental data on the interplay between gastrointestinal (GI) dopaminergic and renin–angiotensin systems in the regulation of intestinal epithelial permeability are reviewed in a systematic manner using the PRISMA methodology. Experimental data confirmed the copresence of DOPA decarboxylase (DDC) and angiotensin converting enzyme 2 (ACE2) in human and rodent enterocytes. The intestinal barrier structure and integrity can be altered by angiotensin (1-7) and dopamine (DA). Both renin–angiotensin and dopaminergic systems influence intestinal Na⁺/K⁺-ATPase activity, thus maintaining electrolyte and nutritional homeostasis. The colocalization of B⁰AT1 and ACE2 indicates the direct role of the renin–angiotensin system in amino acid absorption. Yet, more studies are needed to thoroughly define the structural and functional interaction between TJ-associated proteins and GI renin–angiotensin and dopaminergic systems. Full article

Background: Andrographolide (ADG) has poor aqueous solubility and low bioavailability. This study systematically reviews the use of solid dispersion (SD) techniques to enhance the solubility and absorption of ADG, with a focus on the methods and polymers utilized. Methodology: We searched electronic databases including PubMed, Web of Science, Scopus^®, Embase and ScienceDirect Elsevier^® up to November 2023 for studies on the solubility or absorption of ADG in SD formulations. Two reviewers independently reviewed the retrieved articles and extracted data using a standardized form and synthesized the data qualitatively. Results: SD significantly improved ADG solubility with up to a 4.7-fold increase and resulted in a decrease in 50% release time (T_1/2) to less than 5 min. SD could also improve ADG absorption, as evidenced by higher C_max and AUC and reduced T_max. Notably, Soluplus-based SDs showed marked solubility and absorption enhancements. Among the five SD techniques (rotary evaporation, spray drying, hot-melt extrusion, freeze drying and vacuum drying) examined, spray drying emerged as the most effective, enabling a one-step process without the need for post-milling. Conclusions: SD techniques, particularly using Soluplus and spray drying, effectively enhance the solubility and absorption of ADG. This insight is vital for the future development of ADG-SD matrices. Full article

This study mapped the bioenergy production from sugarcane vinasse according to the mesoregions of the State of São Paulo (SP), Brazil, assessing the magnitude of biogas-derived electricity and biomethane production and estimating the greenhouse gas (GHG) emissions. SP holds 45% of the Brazilian ethanol-producing plants, in which 1.4 million m³ of carbon-rich vinasse are generated daily. The electricity generated from vinasse has the potential to fully supply the residential consumption (ca. 6.5 million inhabitants) in the main sugarcane-producing mesoregions of the state (Ribeirão Preto, São José do Rio Preto, Bauru, Araçatuba and Presidente Prudente). In another approach, biomethane could displace almost 3.5 billion liters of diesel, which represents a 26% abatement in the annual state diesel consumption. Energetically exploiting biogas is mandatory to prevent GHG-related drawbacks, as the eventual emission of methane produced under controlled conditions (261.2 × 10⁶ kg-CO₂eq d⁻¹) is ca. 7-fold higher than the total emissions estimated for the entire ethanol production chain. Meanwhile, replacing diesel with biomethane can avoid the emission of 45.4 × 10⁶ kg-CO₂eq d⁻¹. Implementing an efficient model of energy recovery from vinasse in SP has great potential to serve as a basis for expanding the utilization of this wastewater in Brazil. Full article

In the last few years, increasing interest from researchers and companies has been shown in the development of photocatalytic coatings for air purification and self-cleaning applications. In order to maintain the photocatalyst’s concentration as low as possible, highly active materials and/or combinations of them are required. In this work, novel photocatalytic formulations containing g-C₃N₄/TiO₂ composites were prepared and deposited in the form of coatings on a-block substrates. The obtained photocatalytic surfaces were tested for NOx and acetaldehyde removal from model air. It was found that the addition of only 0.5 wt% g-C₃N₄ towards TiO₂ content results in over 50% increase in the photocatalytic activity under visible light irradiation in comparison to pure TiO₂ coating, while the activity under UV light was not affected. The result was related to the creation of a g-C₃N₄/TiO₂ heterojunction that improves the light absorption and the separation of photogenerated electron-hole pairs, as well as to the inhibition of TiO₂ particles’ agglomeration due to the presence of g-C₃N₄ sheets. Full article

Bioethanol production offers promise in mitigating environmental impacts from ethanol consumption despite water scarcity. This study endeavors to evaluate the nuanced influence of different deheading times (45 days before harvest, 21 days before harvest, and no deheading) along with varying water regimes on select sweet sorghum cultivars (Honey, Willy, MN1500, and Atlas), focusing on yield traits, theoretical ethanol production, and water productivity. Findings underscore the substantial impact of cultivation practices on bioethanol yield. A water deficit ranging from 30% to 70% resulted in a discernible reduction in stalk yields of 17.86% to 18.54% and in sugar yields of 0.2 to 0.31 Mg ha⁻¹, accompanied by a corresponding decline in theoretical ethanol yield of 120.9 to 180.9 L ha⁻¹. Additionally, notable enhancements in Brix and sugar content of 16.32% to 18.42% and 16.81% to 19.03%, respectively, were observed across both seasons. Of particular significance, the Honey variety, subjected to a 30% water deficit and deheading at 21 days before harvest, demonstrated exceptional growth and yield characteristics. These empirical insights furnish valuable guidance for optimizing sweet sorghum cultivation practices, thereby augmenting sustainable bioethanol production and propelling forward the frontier of renewable energy technologies towards a more environmentally sustainable future. Full article

One way that bacteria develop antibiotic resistance is by reducing intracellular antibiotic concentrations through efflux pumps. Therefore, enhancing the efficacy of antibiotics using efflux pump inhibitors provides a way to overcome this type of resistance. Notably, an increasing number of pathogenic Staphylococcus aureus strains have efflux pump genes. In this study, the extract from Corydalis ternata Nakai tuber (Corydalis Tuber) at 512 mg/L was demonstrated to have an antibiotic synergistic effect with ciprofloxacin at 2 mg/L and tobramycin at 1024 mg/L against methicillin-resistant S. aureus (MRSA). Berberine, an isoquinoline alkaloid identified in Corydalis Tuber, was identified as contributing to this effect. Ethidium bromide efflux pump activity assays showed that Corydalis Tuber extract and berberine inhibited efflux, suggesting that they are efflux pump inhibitors. Molecular docking simulations suggested that berberine binds to S. aureus efflux pump proteins MepA, NorA, NorB, and SdrM. Additionally, berberine and Corydalis Tuber extract inhibit biofilm formation, which can confer antibiotic resistance. This study’s findings suggest that Corydalis Tuber, a traditional herbal medicine, and berberine, a medicinal supplement, act as S. aureus efflux pump inhibitors, synergistically increasing the efficacy of ciprofloxacin and tobramycin and showing promise as a treatment for antibiotic-resistant S. aureus infections, including MRSA. Full article

Short-term (with a lead time of about one week) earthquake (EQ) prediction is one of the most challenging subjects in geoscience and applied science; however, it is highly required by society because it is of essential importance in mitigating the human and economic losses associated with EQs. Electromagnetic precursors have recently been agreed to be the most powerful candidate for short-term prediction, because a lot of evidence has been accumulated on the presence of electromagnetic precursors (not only from the lithosphere, but also from the atmosphere and ionosphere) prior to EQs during the last three decades. On the other hand, unusual animal behavior associated with EQs, which is the main topic of this review, has been investigated as a macroscopic phenomenon for many years, with a much longer history than the study of seismo-electromagnetics. So, in this paper, we first summarize the previous research work on this general unusual animal behavior with reference to its relationship with EQs, and then we pay the greatest attention to our own previous work on dairy cows’ milk yield changes. We recommend this unusual animal behavior as an additional potential tool for short-term EQ prediction, which may be a supplement to the above seismo-electromagnetic effects. Finally, we will present our latest case study (as an example) on unusual changes of cows’ milk yields for a particular recent Tokyo EQ on 7 October 2021, and further propose that electromagnetic effects might be a possible sensory mechanism of unusual animal behavior, suggesting a close link between electromagnetic effects and unusual animal behavior. Full article

Every economic sector is susceptible to the direct or indirect effects of weather variability, and the tourism sector is no exception. In fact, the tourism industry is considered to be more vulnerable to the effects of weather variability than the general economy, with changes in weather patterns, extreme events, and environmental degradation offering substantial obstacles. Ethiopia’s tourism industry, like many others, faces challenges from weather variability. This study investigates the short- and long-term effects of weather variability on Ethiopia’s international tourism receipts. Utilizing data from 1995 to 2019, the research employs a vector error correction model to analyze the relationships between weather variables (temperature, rainfall), economic factors (GDP growth, inflation), political stability, and tourist arrivals. The findings reveal that in the long run, higher temperatures, rainfall, and inflation have negative impacts on tourism receipts, while political stability and past tourist arrivals have positive effects. Short-term trends mirror these, with the addition of GDP growth not showing a significant impact. To ensure the sustainability of tourism in Ethiopia, the study emphasizes the importance of understanding weather’s influence, developing adaptation strategies, and promoting sustainable tourism practices. Full article

With the widespread adoption of smart farms and continuous advancements in IoT (Internet of Things) technology, acquiring diverse additional data has become increasingly convenient. Consequently, studies relevant to deep learning models that leverage multimodal data for crop disease diagnosis and associated data augmentation methods are significantly growing. We propose a comprehensive deep learning model that predicts crop type, detects disease presence, and assesses disease severity at the same time. We utilize multimodal data comprising crop images and environmental variables such as temperature, humidity, and dew points. We confirmed that the results of diagnosing crop diseases using multimodal data improved 2.58%p performance compared to using crop images only. We also propose a multimodal-based mixup augmentation method capable of utilizing both image and environmental data. In this study, multimodal data refer to data from multiple sources, and multimodal mixup is a data augmentation technique that combines multimodal data for training. This expands the conventional mixup technique that was originally applied solely to image data. Our multimodal mixup augmentation method showcases a performance improvement of 1.33%p compared to the original mixup method. Full article

This study delves into the geomechanical responses of different sedimentary hydrodynamic cycles in deep tight sandstone formations. Employing core observation and thin section analysis, we quantitatively identified and characterized bedding planes, sedimentary microfacies, and tectonic fractures. Then, the intricate relationships between various architectural interfaces and geomechanical parameters were elucidated. Subsequently, utilizing finite element numerical simulation software, in situ stress and fracture parameters were derived. By identifying a fracture facies zone correlated with the sedimentary hydrodynamic cycle and production data, our findings unveil several key insights: (1) Geomechanical parameters (Young’s modulus, Poisson’s ratio, brittleness index) exhibited noteworthy variations within the T₃x²⁻⁵ sand group, indicative of weak elasticity and robust plasticity. (2) The effective distance, influenced by diverse reservoir architecture interfaces, displayed variability, with each transition between peak-valley-peak or valley-peak-valley pinpointed as a distinct sedimentary hydrodynamic cycle. (3) In environments characterized by strong sedimentary hydrodynamics (between two level 3 architecture interfaces), fractures with larger strike angles and lower dip angles were observed to be more prevalent. (4) Three significant fracture faces—level I, level II, and level III—were discerned within the study area. Notably, reservoirs associated with level III exhibited characteristics suggestive of medium porosity and permeability, indicative of a gas layer. By thoroughly understanding the geomechanical response characteristics of formations such as the Xujiahe Formation, it is possible to guide the exploration and development of energy resources such as oil and natural gas. This helps to improve the efficiency and safety of resource extraction, promoting the sustainable utilization of energy. Full article

Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities. Full article

The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4’s responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4’s responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements. Full article

China’s northern Hulun Lake is a significant body of water internationally. The issue of eutrophication has gained prominence in recent years. The achievement of precise chlorophyll-a (Chl-a) monitoring is crucial for safeguarding Hulun Lake’s ecosystem. The machine learning-based remote sensing inversion method has been shown to be effective in capturing the intricate relationship between independent and dependent variables; however, it lacks a priori knowledge and is limited by the quality of remote sensing data sources. The relationship between independent and dependent variables can be more accurately simulated with the use of suitable auxiliary variables. Therefore, three machine learning models—random forest (RF), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost)—were established in this study using meteorological observation parameters as auxiliary variables combined with Sentinel-2 satellite image remote sensing band combinations as independent variables and measured Chl-a data as dependent variables. The estimation effects before and after the fusion of meteorological ground observation data were compared, and the best model was used to estimate the spatial–temporal variation trend of Chl-a in the regional water body. The results show that (1) the addition of meteorological parameters as auxiliary variables improved the precision of the three machine models; the decision coefficient (R2) rose by 7.25%, 5.71%, and 7.20%, respectively, to 0.76, 0.66, and 0.73. (2) The concentration of Chl-a in the lake region was projected from June to October 2019 to October 2021 using the RF optimal estimating model of meteorological fusion. The northeast, southwest, and south of the lake were where the comparatively high concentration values of Chl-a were located, whereas the lake’s center had a generally low concentration of the substance. Chromatically, Chl-a typically peaked in August after initially increasing and then declining. (3) The three rivers that feed into the river have varying levels of water pollution, with chemical oxygen demand (COD) and total nitrogen (TN) pollution being the most severe. This is what primarily caused the higher levels of Chl-a in the northeast, southwest, and south. This study is crucial for the preservation and restoration of Hulun Lake’s natural ecosystem and offers some technical support for the monitoring of the lake’s concentration of Chl-a. Full article

This article presents a non-linear deterministic mathematical model that captures the evolving dynamics of HIV disease spread, considering three levels of infection in a population. The model integrates fractal-fractional order derivatives using the Caputo operator and undergoes qualitative analysis to establish the existence and uniqueness of solutions via fixed-point theory. Ulam-Hyer stability is confirmed through nonlinear functional analysis, accounting for small perturbations. Numerical solutions are obtained using the fractional Adam-Bashforth iterative scheme and corroborated through MATLAB simulations. The results, plotted across various fractional orders and fractal dimensions, are compared with integer orders, revealing trends towards HIV disease-free equilibrium points for infective and recovered populations. Meanwhile, susceptible individuals decrease towards this equilibrium state, indicating stability in HIV exposure. The study emphasizes the critical role of controlling transmission rates to mitigate fatalities, curb HIV transmission, and enhance recovery rates. This proposed strategy offers a competitive advantage, enhancing comprehension of the model’s intricate dynamics. Full article