Diverse Conditions Research Articles

Effect of expressway exit deceleration markings on distracted drivers in China

Expressway exit areas experience traffic diversion and complex road conditions, making them accident-prone areas. In this study, transverse and fishbone visual illusion deceleration markings were selected to optimize the induction facilities at expressway exits. The research aims to investigate the impact of these markings on the driving behavior, cognitive load, and physiological characteristics of drivers in various distracted scenarios at expressway exit areas. Furthermore, a comprehensive evaluation of each experimental scheme is conducted using the Matter-Element Extension Model. The study found that the implementation of deceleration markings can effectively enhance driver alertness and lane change awareness, enabling drivers to reduce their speed to near the speed limit in exit areas without compromising driving comfort. Compared to the situation without markings, drivers begin to decelerate approximately 600 m earlier and exit the ramp when markings are present. Fishbone deceleration markings, in contrast to transverse markings, result in lower vehicle speeds, smoother deceleration, and more effectively stimulate drivers' intention to change lanes, guiding them to make the final lane change earlier. Based on the comprehensive evaluation results, it is recommended that transverse or fishbone deceleration markings be considered in engineering practice. These markings have not produced significant effects on driver visual fatigue and driving load, with fishbone markings demonstrating superior comprehensive evaluation outcomes. These research findings can provide valuable insights for future expressway exit area marking design schemes, further enhancing driver safety.

Social responsibility of nursing in policies of health humanization

Background: new conceptions of the world have focused on restructuring health policies and designing a new healthcare model.Objective: to reflect on the humanization policy as part of health promotion with emphasis on nursing care.Content: The article mentions paradigm changes and refers to the biomedical model and the new condition of diversity in models of care practices for health promotion and co-responsibility of nursing in generating and sustaining the humanization of nursing care. It rethinks strategies and commitment to co-responsibility by nursing staff in promoting population health. Participation of nurses in promoting humanization care has shown signs of development in its acceptance, bonding healthcare service professionals and its users. An interview-conversation as a strategy for collecting information is highlighted, whether to care or to research based on a humanization framework.Conclusions: Sensitive listening, modality of dialogue, and the conversational interview method are relationship techniques and means to acquire skills for policy development in humanizing care in health promotion.

HPLC method for the determination of thymoquinone in growth cell medium.

Preclinical drug testing requires in vitro and in vivo assessments that are vital for studying drug pharmacokinetics and toxicity. Distinct factors that play an important role in drug screening, such as hydrophobicity, solubility of the substance and serum protein binding can be challenging by inducing result inconsistencies. Hence, establishing accurate methods to quantify drug concentrations in cell cultures becomes pivotal for reliable and reproducible results important for in vivo dosing predictions. This research focuses on developing an optimized analytical approach via high-pressure liquid chromatography (HPLC) to determine thymoquinone (TQ) levels in monolayer cell cultures. The method's validation adheres to the International Council for Harmonisation (ICH) guideline M10, ensuring its acceptance and applicability. Using an HPLC system with a Diode Array Detector (DAD), the study fine-tuned various parameters to achieve an efficient separation of TQ. Validation covered specificity, sensitivity, matrix effects, linearity, precision, and accuracy, alongside assessing TQ stability in RPMI-1640 medium. The HPLC method exhibited remarkable TQ specificity, free from interfering peaks at the analyte retention. Sensitivity analysis at the lower limit of quantification (LLOQ) revealed 5.68% %CV and 98.37% % mean accuracy. Matrix effect evaluation showcased accuracy within 85-115%. Linearity spanned in the concentration range of 2-10 μM with a correlation coefficient (r2) of 0.9993. Precision and accuracy were aligned with acceptance criteria. The proposed method was found to be greener in terms of usage of persistent, bioaccumulative, and toxic chemicals and solvents, corrosive samples, and waste production. The developed HPLC-DAD method emerges as specific, accurate, sensitive, and reliable for TQ determination in cell cultures. It ensures robust TQ quantification, enhancing precise in vitro assessments and dependable dosing predictions for in vivo studies. Further research is advocated to investigate TQ's stability across diverse environmental conditions.

The Holistic Advantage: Unified Quantitative Modeling for Less-Biased, In-Depth Insights into (Socio)Linguistic Variation

What happens when recognized and diverse conditioning factors of linguistic variation are omitted from analysis and/or are not analyzed under a single analytical procedure? This paper explores the consequences of such a choice on data interpretation and, consequently, (socio)linguistic theorization. Utilizing Twitter-style English in the Philippines (EngPH) as a case study, I employ the Twitter Corpus of Philippine Englishes (TCOPE) primarily to investigate and elucidate variations in three morphosyntactic variables that have been previously examined using a piecemeal approach. I propose a holistic quantitative approach that incorporates documented linguistic, social, diachronic, and stylistic factors in a unified analysis. The paper illustrates the impacts of adopting this holistic approach through two statistical procedures: Bayesian regression modeling and Boruta feature selection with random forest modeling. In contrast to earlier research findings, my overall results reveal biases in non-unified quantitative analyses, where the confidence in the effects of certain factors diminishes in light of others during analysis. The adoption of a unified analysis or modeling also enhances the resolution at which variations have been examined in EngPH. For instance, it highlights that presumed ‘universals’, such as the hierarchy of linguistic > stylistic > diachronic > social factors in explaining variation in some domains, is contingent on the specific variable under examination. Overall, I argue that unified analyses reduce data distortion and introduce more nuanced interpretations and insights that are critical for establishing a well-grounded empirical theory of EngPH variation and language variation as a whole.

Left atrial strain analysis in the realm of pediatric cardiology: Advantages and implications.

Left atrial (LA) strain analysis has emerged as a noninvasive technique for assessing LA function and early detection of myocardial deformation. Recently, its application has also shown promise in the pediatric population, spanning diverse cardiac conditions that demand accurate and sensitive diagnostic measures. This research article endeavors to explore the role of LA strain parameters and contribute to the growing body of knowledge in pediatric cardiology, paving the way for more effective and tailored approaches to patient care. A comprehensive literature review was conducted to gather evidence from studies using echocardiographic strain imaging techniques across pediatric populations. LA strain parameters exhibited greater sensitivity than conventional atrial function indicators, with early detection of diastolic dysfunction and LA remodeling in pediatric cardiomyopathy, children with multisystem inflammatory syndrome, rheumatic heart disease, as well as childhood renal insufficiency and obesity offering prognostic relevance as potential markers in these pediatric subpopulations. However, there remains a paucity of evidence concerning pediatric mitral valve pathology, justifying further exploration. LA strain analysis carries crucial clinical and prognostic implications in pediatric cardiac conditions, with reliable accuracy and sensitivity to early functional changes.

Simulation analysis of low back forces in Snatch and Clean & Jerk movements via digital human modelling.

Weightlifting is an Olympic sport for dynamic strength and power, and requires the execution of different lifting techniques It is important to analyze the forces subjected to the lower back during weightlifting movements to prevent injuries. Digital Human Modeling (DHM) is a powerful tool that can be used to analyze and optimize the performance of humans while doing their work or activities. The purpose of this study is to present a simulation analysis of the lower back forces during the execution of two weightlifting techniques: Snatch (SN) and Clean & Jerk (CJ), with different loads and for both genders. Digital Human modelling through JACK simulation package was used analyze the forces exerted on the lumbosacral area (L5-S1) of the lower back in order to determine the risk for low back injuries. The level of compression and shear forces recommended by the literature have been set as thresholds. The simulaitons were performed in male and female models, with loads from 20-100kg. The results show that any weight higher than 60 kg in both movements poses risk for the weightlifters in terms of compression and shear forces. It has been observed that weightlifters can lift greater loads in the CJ technique compared to the SN technique. Furthermore, females are able to lift higher loads with lower risk of injuries. Weightlifting is a high-risk activity due to the high levels of shear and compression forces that the body is exposed to during the lifting techniques. Digital Human Modeling holds significant value due to their ability to facilitate the exploration of diverse conditions within a safe environment, devoid of any potential harm to human subjects.

Detailed Design of Special-Shaped Steel Structures Based on DfMA: The BIM-FEM Model Conversion Method

(1) This paper, based on the characteristics of complex steel structures as well as difficult points in the process of their detailed design, introduces the product design concept of DfMA (Design for Manufacturing and Assembly) from the manufacturing industry and studies the detailed design method of BIM-FEM model conversion. The BIM software Revit (2020) is used as the basis for the BIM detailed design of the project, which achieves the purpose of rapid modeling and provides a detailed design model basis for finite element analysis. (2) Utilizing the Revit API and C# for secondary development as the technical means, this approach involves converting the geometric entity model described by CSG-Brep into an APDL stream. This creates an interface with the finite element analysis software ANSYS (12.0) to implement the detailed design of BIM-FEM model conversion, optimizing the algorithm for converting complex analysis models that require high precision for special-shaped steel structures. (3) This research addresses issues such as the disconnection between the design, manufacturing, and construction of special-shaped steel structures, providing support for design decisions. Moreover, it enhances the detailed design method by improving the standardization of special-shaped components under the condition of design diversity. (4) These studies provide sustainability for engineering design, manufacturing, and construction projects, enabling the maximization of benefits and product lifecycle management (PLM) through these projects. (5) Finally, a case study analysis was conducted on the Wuhan City New Generation Weather Radar Construction Project, designed by the Central South Architectural Design Institute (CSADI), to verify the detailed design of BIM-FEM model conversion. This proved the scientific validity, practicality, and necessity of this research.

Bayesian conditional diffusion models for versatile spatiotemporal turbulence generation

Turbulent flows, characterized by their chaotic and stochastic nature, have historically presented formidable challenges to predictive computational modeling. Traditional eddy-resolved numerical simulations often require vast computational resources, making them impractical or infeasible for numerous engineering applications. As an alternative, deep learning-based surrogate models have emerged, offering data-drive solutions. However, these are typically constructed within deterministic settings, leading to shortfall in capturing the innate chaotic and stochastic behaviors of turbulent dynamics. In this study, we introduce a novel generative framework grounded in probabilistic diffusion models for versatile generation of spatiotemporal turbulence under various conditions. Our method unifies both unconditional and conditional sampling strategies within a Bayesian framework, which can accommodate diverse conditioning scenarios, including those with a direct differentiable link between specified conditions and generated unsteady flow outcomes, as well as scenarios lacking such explicit correlations. A notable feature of our approach is the method proposed for long-span flow sequence generation, which is based on autoregressive gradient-based conditional sampling, eliminating the need for cumbersome retraining processes. We evaluate and showcase the versatile turbulence generation capability of our framework through a suite of numerical experiments, including: (1) the synthesis of Large Eddy Simulations (LES) simulated instantaneous flow sequences from unsteady Reynolds-Averaged Navier–Stokes (URANS) inputs; (2) holistic generation of inhomogeneous, anisotropic wall-bounded turbulence, whether from given initial conditions, prescribed turbulence statistics, or entirely from scratch; (3) super-resolved generation of high-speed turbulent boundary layer flows from low-resolution data across a range of input resolutions. Collectively, our numerical experiments highlight the merit and transformative potential of the proposed methods, making a significant advance in the field of turbulence generation.

Robust Representation Learning for Power System Short-Term Voltage Stability Assessment Under Diverse Data Loss Conditions.

With the help of neural network-based representation learning, significant progress has been recently made in data-driven online dynamic stability assessment (DSA) of complex electric power systems. However, without sufficient attention to diverse data loss conditions in practice, the existing data-driven DSA solutions' performance could be largely degraded due to practical defective input data. To address this problem, this work develops a robust representation learning approach to enhance DSA performance against multiple input data loss conditions in practice. Specifically, focusing on the short-term voltage stability (SVS) issue, an ensemble representation learning scheme (ERLS) is carefully designed to achieve data loss-tolerant online SVS assessment: 1) based on an efficient data masking technique, various missing data conditions are handled and augmented in a unified manner for lossy learning dataset preparation; 2) the emerging spatial-temporal graph convolutional network (STGCN) is leveraged to derive multiple diversified base learners with strong capability in SVS feature learning and representation; and 3) with massive SVS scenarios deeply grouped into a number of clusters, these STGCN-enabled base learners are distinctly assembled for each cluster via multilinear regression (MLR) to realize ensemble SVS assessment. Such a divide-and-conquer ensemble strategy results in highly robust SVS assessment performance when faced with various severe data loss conditions. Numerical tests on the benchmark Nordic test system illustrate the efficacy of the proposed approach.

Cyclotron line formation in the radiative shock of an accreting magnetized neutron star

Context. Magnetic neutron stars (NSs) often exhibit a cyclotron resonant scattering feature (CRSF) in their X-ray spectra. Accretion onto their magnetic poles is responsible for the emergence of X-rays, but the site of the CRSF formation is still a puzzle. A promising candidate for high-luminosity sources has always been the radiative shock in the accretion column. Nevertheless, no quantitative calculations of spectral formation at the radiative shock have been performed so far. Aims. It is well accepted that, in the accretion column of a high-luminosity, accreting magnetic NS, a radiative shock is formed. Here, we aim to explore the scenario where the shock is the site of the cyclotron-line formation. We studied spectral formation at the radiative shock and the emergent spectral shape across a wide range of the parameter space and determined which parameters hold an important role in shaping a prominent CRSF. Methods. We developed a Monte Carlo (MC) code based on the forced first collision numerical scheme to conduct radiation transfer simulations at the radiative shock. The seed photons were due to bremsstrahlung and were emitted in the post-shock region. We properly treated bulk-motion Comptonization in the pre-shock region, thermal Comptonization in the post-shock region, and resonant Compton scattering in both regions. We adopted a fully relativistic scheme for the interaction between radiation and electrons, employing an appropriate polarization-averaged differential cross-section. As a result, we calculated the angle- and energy-dependent emergent X-ray spectrum from the radiative shock, focusing on both the CRSF and the X-ray continuum, under diverse conditions. The accretion column was characterized by cylindrical symmetry, and the radiative shock was treated as a mathematical discontinuity. Results. We find that a power law, hard X-ray continuum, and a CRSF are naturally produced by the first-order Fermi energization as the photons criss-cross the shock. The depth and the width of the CRSF depend mainly on the transverse optical depth and the post-shock temperature. We show that the cyclotron-line energy centroid is shifted by ∼(20 − 30)% to lower energies compared to the classical cyclotron energy; this is due to the Doppler boosting between the shock reference frame and the bulk-motion frame. We demonstrate that a “bump” feature arises in the right wing of the CRSF due to the up-scattering of photons by the accreting plasma and extends to higher energies for larger optical depths and post-shock temperatures. Conclusions. We conclude that resonant Compton scattering of photons by electrons in a radiative shock is efficient in producing a power-law X-ray continuum with a high-energy cutoff accompanied by a prominent CRSF. The implications of the Doppler effect on the centroid of the emergent absorption feature must be considered if an accurate determination of the magnetic field strength is desired.

High diversity of macrophytes in the »green river« Krka (Slovenia)

AbstractThe presence, abundance, and distribution of aquatic macrophytes and their growth forms in the river Krka in Slovenia were studied. The studied slow‐flowing lowland River Krka is also called a »green river« since it is overgrown with macrophytes from its source to its outflow to the river Sava. The environmental parameters of the river ecosystem were also assessed using the modified version of the RCE (Riparian, Channel, and Environmental Inventory) method. Within 24 sections reaching from 100 to 250 m, 23 taxa of macrophytes were found. Sections were distributed noncontinuously from the source to the outflow more or less equally along the river course. The invasive alien species Elodea canadensis reached the highest relative abundance, followed by Ranunculus trichophyllus, Potamogeton crispus, Myriophyllum spicatum, Ceratophyllum demersum, and Potamogeton nodosus. Potamogeton crispus was present in most of the studied sections followed by Nasturtium officinale and M. spicatum. The river offers suitable conditions for the high diversity of macrophytes regarding the type of substrate, low flow velocity, heterogeneity of habitats, and relatively high concentrations of nutrients. In comparison to the survey performed in 2003, when the river Krka was surveyed continuously from the source to the outflow, we found that seven of the submerged and natant macrophytes were not detected in 2020. Macrophytes, growing in the river Krka, indicated meso‐ to eutrophic conditions. Five species recorded in the river Krka are listed on the Red list of endangered species in Slovenia, indicating the need to conserve the river ecosystem.

Adopting photovoice to explore teachers’ experiences in online teaching

<span lang="EN-US">The coronavirus disease 2019 (COVID-19) outbreak has caused a rapid and massive change in the education sector across the world and left no choice to teachers to maintain their status quo. As a country with very diverse geographical and technological conditions, Indonesia has felt the severe impact of this pandemic. This study explores how Indonesian English as foreign language (EFL) teachers struggle to adapt to the online teaching process, identifies the challenges they encountered during the online teaching and learning process, and investigates their strategies in coping with the associated challenges to ensure the learning objectives were achieved. This study employed photovoice as a visual research methodology to capture the new phenomena and answer the research objectives by inviting four English teachers from three different islands, Java, Sumatra, and Sulawesi to share their experiences and strategies for survival. The results indicated that Indonesian EFL teachers suffered from challenging experiences, including the trial and error of learning management system (LMS) choice, and were confronted with unpleasant feedback from the students. This study also identified poor internet connection and low online student participation as the main issues. To deal with such problems, especially with low student participation, they viewed disadvantaged situations as a trigger to improve their creativity.</span>

First Record and Geographic Expansion of the Sebastes schlegelii in the Sea of Marmara

This study reports the first-recorded presence of the Korean rockfish (Sebastes schlegelii) in the Sea of Marmara, signifying a notable geographical expansion beyond its natural range. The sampled male specimen, with a total length of 27.5 cm and a weight of 459.20 g, aligns with known size patterns observed in the Black Sea, suggesting a consistent trend. The unexpected presence of the species in the Sea of Marmara raises intriguing questions about its potential spread in the broader Mediterranean Sea basin. The adaptability of the Sebastes schlegelii to diverse environmental conditions underscores its ecological resilience. The study emphasizes the need for careful monitoring and management due to potential threats posed by invasive species, especially considering the vulnerabilities of the Sea of Marmara to climate change

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Optimal Treatment Strategies for Critical Patients with Deep Reinforcement Learning

Personalized clinical decision support systems are increasingly being adopted due to the emergence of data-driven technologies, with this approach now gaining recognition in critical care. The task of incorporating diverse patient conditions and treatment procedures into critical care decision-making can be challenging due to the heterogeneous nature of medical data. Advances in Artificial Intelligence (AI), particularly Reinforcement Learning (RL) techniques, enables the development of personalized treatment strategies for severe illnesses by using a learning agent to recommend optimal policies. In this study, we propose a Deep Reinforcement Learning (DRL) model with a tailored reward function and an LSTM-GRU-derived state representation to formulate optimal treatment policies for vasopressor administration in stabilizing patient physiological states in critical care settings. Using an ICU dataset and the Medical Information Mart for Intensive Care (MIMIC-III) dataset, we focus on patients with Acute Respiratory Distress Syndrome (ARDS) that has led to Sepsis, to derive optimal policies that can prioritize patient recovery over patient survival. Both the DDQN ( RepDRL-DDQN ) and Dueling DDQN ( RepDRL-DDDQN ) versions of the DRL model surpass the baseline performance, with the proposed model’s learning agent achieving an optimal learning process across our performance measuring schemes. The robust state representation served as the foundation for enhancing the model’s performance, ultimately providing an optimal treatment policy focused on rapid patient recovery.

EyeMo: A Solution for Individuals with Disabilities to Use a Computer Through Eye Movements

The maintenance of an upright posture and the execution of desired movements by individuals necessitate the seamless and harmonious functioning of the muscular and skeletal systems. Neuromuscular diseases, spinal cord injuries, and related conditions can adversely impact individuals' motor functions, leading to a loss of muscle strength and, in severe cases, paralysis. Such health challenges may result in social isolation and detachment from one's social life. This study is focused on the development of a computer control application utilizing eye movements to aid users in navigating and interacting with computers. The system utilizes a lightweight eyeglass frame and a mini-USB camera to accurately capture images of the user's pupil. Pupil detection is achieved through a combination of traditional image processing and deep learning techniques, ensuring high accuracy under diverse conditions. Users have the ability to interactively calibrate the application to accommodate varying screen sizes, thereby enhancing system responsiveness. The user interface incorporates functionalities such as left-click, right-click, double-click, and scrolling, empowering users to perform tasks ranging from internet browsing to video watching. 
 After the development of the application, a request for research permission was submitted to the local institution to allow volunteers to test the application, adhering to ethical standards. Following the approval of ethical clearance, the application was made available for use by volunteers, and feedback was systematically collected. Volunteers generally reported that the application was beneficial, indicating its potential use by disadvantaged individuals. The upcoming versions of the application have the potential for integration with smart home systems. Additionally, the developed application can be used in games and for educational purposes.

Durability and micromechanical properties of biochar in biochar-cement composites under marine environment

Integrating biochar into traditional construction materials presents a promising avenue to reduce carbon emissions from the construction industry. While recent research has focused on the performance of biochar-cement materials, limited attention is given to the durability of biochar in cementitious materials. This study investigated the alterations in the structural, chemical, and mechanical properties of biochar in the cementitious system and marine environment. The results showed an increased pore size in the biochar and a potential collapse of its structure after long-term exposure of biochar to an alkaline cement environment. The decline of the aromaticity, 23.8% increase in matrix defectiveness, and formation of organometallic complexes between Ca2+ and oxygen-containing functional groups of biochar indicated that its interactions with hydrated cement would lead to the changes in its chemical properties. The exposure of biochar to the simulated cement solution reduced its Young’s modulus from 3.81 GPa to 1.55 GPa and hardness from 0.70 GPa to 0.13 GPa possibly due to the collapse of the pore structure. The saponification reaction might disrupt the cross-linking network structure constructed by COOC and C–O–C in the biochar and release the fulvic-acid organics, causing a decrease in the short- and long-term rebound ratios by 5.6–25.6% and 5–17%, respectively. Biochar exposed to the simulated harsh environment (seawater) exhibited an increase in Young’s modulus and hardness by ∼40% compared to virgin biochar. The long-term rebound ratio reached 96.6–99.2% due to brucite, NaCl, and KCl deposition and filling, implying the potential advantage of biochar-cement composites for long-term durability in the marine environment. These findings contribute new insights to the assessment of mechanical performance and durability of biochar-cement composites in diverse environmental conditions.

Broad-spectrum hydrocarbon-degrading microbes in the global ocean metagenomes

Understanding the diversity and functions of hydrocarbon-degrading microorganisms in marine environments is crucial for both advancing knowledge of biogeochemical processes and improving bioremediation methods. In this study, we leveraged nearly 20,000 metagenome-assembled genomes (MAGs), recovered from a wide array of marine samples across the global oceans, to map the diversity of aerobic hydrocarbon-degrading microorganisms. A broad bacterial diversity was uncovered, with a notable preference for degrading aliphatic hydrocarbons over aromatic ones, primarily within Proteobacteria and Actinobacteriota. Three types of broad-spectrum hydrocarbon-degrading bacteria were identified for their ability to degrade various hydrocarbons and possession of multiple copies of hydrocarbon biodegradation genes. These bacteria demonstrate extensive metabolic versatility, aiding their survival and adaptability in diverse environmental conditions. Evidence of gene duplication and horizontal gene transfer in these microbes suggested a potential enhancement in the diversity of hydrocarbon-degrading bacteria. Positive correlations were observed between the abundances of hydrocarbon-degrading genes and environmental parameters such as temperature (−5 to 35 °C) and salinity (20 to 42 PSU). Overall, our findings offer valuable insights into marine hydrocarbon-degrading microorganisms and suggest considerations for selecting microbial strains for oil pollution remediation.

Rational Design of a Necklace-like ZIF-67/Poly(vinylidene fluoride) Electrospun Nanofiber Hybrid Membrane for Simultaneous Removal of PM0.3 and SO2.

Growing concerns over poor air quality, especially in urban and industrial regions, have led to increased global demands for advanced air-purification technologies. However, the stability and airborne pollutant control abilities of the available air-purification materials under diverse environmental conditions are limited. Thus, the advanced development of filtration materials that can effectively control different types of pollutants, such as particulate matter (PM) and gaseous pollutants, simultaneously has attracted attention. The zeolitic imidazolate framework (ZIF), a type of porous metal-organic framework (MOF), is a promising material for capturing weakly acidic toxic gases such as SO2 owing to its excellent adsorption performance and high thermal and chemical stability. In this study, we successfully developed an ultrastable necklace-like multifunctional hybrid membrane via the cetyltrimethylammonium bromide-assisted in situ growth of zeolitic imidazolate framework (ZIF)-67 crystals on electrospun Co2+-doped poly(vinylidene fluoride) nanofibers (70 nm) that can be used in different moisture environments to achieve sustainable air-filtration performance. The hybrid nanocomposite membrane demonstrated excellent performance for the simultaneous control of intractable fine PM0.3 (filtration efficiency, 99.461%) and SO2 (adsorption capacity, 1476.5 mg g-1) under different humidity conditions. This study contributes to the optimal synergistic integration of the advanced metal-organic framework (MOF)-nanofiber nanocomposite membranes and can guide the rational design and conceptualization of a facile and novel membrane for various applications in the environmental science and energy fields.

Thermodynamic Performance Assessment of Air Conditioner Combining Evaporative and Passive Cooling

Abstract The global increase in refrigeration and air conditioning applications poses a severe problem as regards the environmental degradation caused by greenhouse gas emissions. This study introduces a novel approach wherein both evaporative cooling and passive cooling are integrated to unveil notable enhancements in energy and exergy compared to conventional air conditioning systems. Therefore, this work aims to enhance the thermal performance of a 1.5-ton split air conditioner (SAC) employing outdoor (condenser) evaporative and indoor passive cooling (EPC). The heat removal capacity of a condenser and SAC performance are greatly affected by the air temperature at the condenser inlet. Evaporative cooling serves to lower outdoor air temperature, while passive cooling minimizes the indoor cooling load. Design parameters encompass outdoor temperature (Ta = 30–44 °C), relative humidity (RH = 20–80%), and temperature reduction due to passive cooling (ΔTR = 0.5–5 °C). A model is developed to calculate the temperature reductions of outdoor air through evaporative cooling in diverse climatic conditions, while the range of passive cooling degrees is obtained from previous experiments. Results indicate a substantial enhancement in the thermodynamic performance of the proposed system. The maximum coefficient of performance (COP) improvement of 68.66% is achieved at 44 °C outside temperature and 20% relative humidity. Annual energy savings, under extreme operating conditions, range from 358.4 kWh to 2116.8 kWh. The EPC SAC is identified as more sustainable than the conventional split air conditioner (CSAC). Moreover, the projected system is anticipated to recoup its costs within a relatively short period of 1.42 years.