Fly ash, a type of solid waste generated in power plants, can be utilized as a catalyst carrier to enhance its value-added potential. Common methods often involve using a large amount of alkali for preprocessing, resulting in stable quartz and mullite forming silicate dissolution. This leads to an increased specific surface area and pore structure. In this study, we produced a catalyst composed of MnO_x/NiOOH supported on fly ash by directly employing nickel hydroxide and potassium permanganate to generate metal active sites over the fly ash surface while simultaneously creating a larger specific surface area and pore structure. The ozone catalytic oxidation performance of this catalyst was evaluated using sodium acetate as the target organic matter. The experimental results demonstrated that an optimal removal efficiency of 57.5% for sodium acetate was achieved, surpassing even that of MnO_x/NiOOH supported catalyst by using γ-Al₂O₃. After loading of MnO_x/NiOOH, an oxygen vacancy is formed on the surface of fly ash, which plays an indirect oxidation effect on sodium acetate due to the transformation of ozone to •O₂⁻ and •OH over this oxygen vacancy. The reaction process parameters, including varying concentrations of ozone, sodium acetate, and catalyst dosage, as well as pH value and the quantitative analysis of formed free radicals, were examined in detail. This work demonstrated that fly ash could be used as a viable catalytic material for wastewater treatment and provided a new solution to the added value of fly ash. Full article

The direct hydrogenation of greenhouse gas CO₂ to higher alcohols (C₂₊OH) provides a new route for the production of high-value chemicals. Due to the difficulty of C-C coupling, the formation of higher alcohols is more difficult compared to that of other compounds. In this review, we summarize recent advances in the development of multifunctional catalysts, including noble metal catalysts, Co-based catalysts, Cu-based catalysts, Fe-based catalysts, and tandem catalysts for the direct hydrogenation of CO₂ to higher alcohols. Possible reaction mechanisms are discussed based on the structure–activity relationship of the catalysts. The reaction-coupling strategy holds great potential to regulate the reaction network. The effects of the reaction conditions on CO₂ hydrogenation are also analyzed. Finally, we discuss the challenges and potential opportunities for the further development of direct CO₂ hydrogenation to higher alcohols. Full article

In the cutting process, there are many parameters that affect the cutting effect, and the same parameter has different degrees of influence on different performance indicators, which makes it difficult to select key parameters for parameter optimization and parameter combination evaluation while considering multiple performance indicators at the same time. The process of titanium alloy milling with an integrated end mill is studied herein. The values of cutting tool flank face wear and material removal rates are obtained with experimental and analytical methods. Numerical characteristics and causes of the cutting tool flank face wear at different stages are also analyzed. The dynamic, comprehensive evaluation method based on the double incentives model is used to evaluate the dynamic, comprehensive importance of cutting parameters in view of the problem of considering multiple performance indicators and the characteristics of the dynamic change in performance indicators in the cutting process. According to the result of a dynamic, comprehensive evaluation, the cutting parameters with the highest comprehensive importance are selected. Finally, the radar map is used to plot the comprehensive importance of the cutting parameters. The overall comprehensive importance of each cutting parameter is intuitively displayed as well. As a result of the research, the dynamic, comprehensive evaluation method based on the double incentives model has a good application value in the evaluation of tool performance in the cutting process and can quickly select the best tool performance parameter combination; it is established that the most comprehensive parameter is the cutting speed, and the cutting width is the second most important. In turn, the comprehensive importance of the cutting depth is the lowest. Full article

In this paper, we present four categories of covering-based intuitionistic hesitant fuzzy rough set (CIHFRS) models using intuitionistic hesitant fuzzy $\beta$-neighborhoods (IHF $\beta$-neighborhoods) and intuitionistic hesitant fuzzy complementary $\beta$-neighborhoods (IHFC $\beta$-neighborhoods. Through theoretical analysis of covering-based IHFRS models, we propose the intuitionistic hesitant fuzzy TOPSIS (IHF-TOPSIS) technique for order of preference by similarity to an ideal solution, addressing multicriteria decision-making (MCDM) challenges concerning the assessment of IHF data. A compelling example aptly showcases the suggested approach. Furthermore, we address MCDM problems regarding the assessment of IHF information based on CIHFRS models. Through comparison and analysis, it is evident that addressing MCDM problems by assessing IHF data using CIHFRS models proves more effective than utilizing intuitionistic fuzzy data with CIFRS models or hesitant fuzzy information with CHFRS models. IHFS emerges as a unique and superior tool for addressing real-world challenges. Additionally, covering-based rough sets (CRSs) have been successfully applied to decision problems due to their robust capability in handling unclear data. In this study, by combining CRSs with IHFS, four classes of CIFRS versions are established using IHF $\beta$-neighborhoods and IHFC $\beta$-neighborhoods. A corresponding approximation axiomatic system is developed for each. The roughness and precision degrees of CBIHFRS models are specifically talked about. The relationship among these four types of IHFRS versions and existing related versions is presented based on theoretical investigations. A method for MCDM problems through IHF information, namely, IHF-TOPSIS, is introduced to further demonstrate its effectiveness and applicability. By conducting a comparative study, the effectiveness of the suggested approach is evaluated. Full article

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS. Full article

The discharge of lead and cadmium wastewater, along with the pollution caused by phosphogypsum, represents a particularly urgent environmental issue. This study employed a straightforward hydrothermal method to convert phosphogypsum into porous calcium silicate hydrate (P-CSH), which was then used to remove and recover Pb(II) and Cd(II) from wastewater. The adsorption capacities of P-CSH for Pb(II) and Cd(II) were notably high at 989.3 mg/g and 290.3 mg/g, respectively. The adsorption processes adhered to the pseudo-second-order kinetics model and the Langmuir isotherm model. Due to identical adsorption sites on P-CSH for both Pb(II) and Cd(II), competitive interaction occurred when both ions were present simultaneously. Additionally, the adsorption efficacy was minimally impacted by the presence of common coexisting cations in wastewater. The dominant mechanisms for removing Pb(II) and Cd(II) via P-CSH were chemical precipitation and surface complexation. Moreover, the adsorbed heavy metals were efficiently separated and reclaimed from the wastewater through a stepwise desorption process. The primary components of the residue from stepwise desorption were quartz and amorphous SiO₂. Following dissolution via pressurized alkaline leaching, this residue could be recycled for synthesizing P-CSH. This research offered a new strategy for the resourceful use of phosphogypsum and heavy metal wastewater. Full article

For manufacturing components with thick plates, such as in the heavy equipment and shipbuilding industries, the gas metal arc welding (GMAW) process is applied. Among the components that apply the thick plate GMAW process, there are groove butt joints, which are fabricated through multi-pass welding. Various welding qualities are managed in multi-pass welding, and the root-pass weld is controlled to ensure complete joint penetration (CJP). Currently, the state of complete joint penetration during root-pass welding is managed visually, making it difficult to confirm the penetration condition in real time. Therefore, there is a need to predict the penetration condition in real time. In this study, we propose a convolutional neural network (CNN)-based prediction model that can classify penetration conditions using welding current and voltage data from the root pass of V-groove butt joints. The root gap of the joints was varied between 1.0 and 2.0 mm, and the wire feed rate was adjusted. During welding, the current and voltage were measured. The welding current and voltage are transformed into a short-time Fourier transform (STFT) representation depicting the arc and wire extension lengths. The transformed dynamic resistance STFT information serves as the input variable for the CNN model. Preprocessing steps, including thresholding, are applied to optimize the input variables. The CNN architecture comprises three convolutional layers and two pooling layers. The model classifies penetration conditions as partial joint penetration (PJP), CJP, and burn-through, achieving a high accuracy of 97.8%. The proposed method facilitates the non-destructive evaluation of the root-pass welding quality without expensive monitoring equipment, such as vision cameras. It is expected to be immediately applied to the thick plate welding process using readily available welding data. Full article

The purpose of this study was to use principal component analysis to determine the effect of meteorological elements on the concentration of PM_2.5 particulate matter in Krakow, the capital of the Lesser Poland Voivodeship in southern Poland. Daily values for selected meteorological elements measured in spring, summer, autumn, and winter over a 10-year period, obtained from the Institute of Meteorology and Water Management—National Research Institute, were adopted as variables explaining PM_2.5 concentrations. Data on particulate air pollution were obtained from the air monitoring station in Krakow. In spring, autumn, and winter, the first factor significantly influencing the PM_2.5 concentration was the maximum, minimum, and average temperature. In summer, the average and maximum temperatures were significant. The second factor in spring was precipitation and wind speed, and the third was relative humidity. In summer, the second factor was atmospheric pressure, and the third was relative humidity. The second factor in autumn was atmospheric pressure and precipitation, and the third was relative humidity. In winter, the second factor was wind speed, and the third was precipitation and relative humidity. Throughout the study, the annual mean PM_2.5 concentrations exceeded acceptable and target levels defined by the Regulation of the Minister of the Environment, and even further exceeded the level recommended by the WHO. Full article

Through a thematic analysis of firsthand posts from 258 abuse survivors in online forums from 2016 to 2023, this research examines the barriers that Chinese children encounter when disclosing sexual abuse. The anonymous narratives shed light on the motives behind survivors’ reluctance to reveal abuse, the outcomes following disclosure, and the wider implications for survivors and their families under culture. The findings underscore the need for early intervention upon disclosure, aiming to safeguard children from further harm and foster the development of an effective child protection framework. Full article

Protocell models play a pivotal role in the exploration of the origin of life. Vesicles are one type of protocell model that have attracted much attention. Simple single-chain amphiphiles (SACs) and organic small molecules (OSMs) possess primitive relevance and were most likely the building blocks of protocells on the early Earth. OSM@SAC vesicles have been considered to be plausible protocell models. Pyrite (FeS₂), a mineral with primitive relevance, is ubiquitous in nature and plays a crucial role in the exploration of the origin of life in the mineral–water interface scenario. “How do protocell models based on OSM@SAC vesicles interact with a mineral–water interface scenario that simulates a primitive Earth environment” remains an unresolved question. Hence, we select primitive relevant sodium monododecyl phosphate (SDP), isopentenol (IPN) and pyrite (FeS₂) mineral particles to build a protocell model. The model investigates the basic physical and chemical properties of FeS₂ particles and reveals the effects of the size, content and duration of interaction of FeS₂ particles on IPN@SDP vesicles. This deepens the understanding of protocell growth mechanisms in scenarios of mineral–water interfaces in primitive Earth environments and provides new information for the exploration of the origin of life. Full article

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parallel processing capabilities of modern central processing units (CPUs), namely the availability of multiple cores and multithreading. The proposed multi-threaded implementations for computing DKraP coefficients divide the computations into multiple independent tasks, which are executed concurrently by different threads distributed among the independent cores. This multi-threaded approach has been evaluated across a range of DKraP sizes and various values of polynomial parameters. The results show that the proposed method achieves a significant reduction in computation time. In addition, the proposed method has the added benefit of applying to larger polynomial sizes and a wider range of Krawtchouk polynomial parameters. Furthermore, an accurate and appropriate selection scheme of the recurrence algorithm is introduced. The proposed approach introduced in this paper makes the DKraP coefficient computation an attractive solution for a variety of applications. Full article

(1) Receiving an oncological diagnosis involves countless physical and mental challenges for those who become ill. In addition to this, developmental activities are put on hold when a parent becomes ill, significantly impairing children’s normal growth and development. The purpose of this review is to highlight the psychological impact of cancer on children, with particular attention to differences based on the age of the child and the stage of the parent’s disease. (2) Articles published on PubMed up until October 2023 were searched. Qualitative and quantitative studies were included in this review after an evaluation of the full text. The study selection process was undertaken by two researchers, and articles for which there was unanimous agreement between researchers were included in the review. (3) Children’s psycho-emotional responses differ based on their age and the disease stage. In general, good communication and a supportive family environment that understands everyone’s needs seem to constitute important protective factors that favor the adaptation of the entire family to the disease. (4) The family, as an evolutionary system, finds itself facing phases typical of development. Knowing the variables that intervene in the process of adaptation to the disease will allow us to design specific and differentiated clinical interventions based on the needs of not only the patient but also the entire family. Full article

Objective: The study aimed to investigate the effects of castration on performance, carcass characteristics, and meat quality in sheep, as well as explore the expression of key genes related to metabolic pathways and muscle growth following castration. Methods: A meta-analysis approach was utilized to analyze data from multiple studies to compare the performance, carcass characteristics, and meat quality of castrated sheep (wethers) with intact rams. Additionally, protein–protein interaction (PPI) networks, differential gene expression (DEG) interactions, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were examined to identify molecular mechanisms associated with fat metabolism and muscle development in sheep tails. Results: The analysis revealed that castrated sheep (wethers) exhibited improved average daily gain, increased tenderness, lower backfat thickness, and a tendency for greater loin muscle area compared to intact rams. This suggests that castration promotes faster growth and results in leaner carcasses with potentially higher muscle content. Furthermore, the identification of downregulated DEGs like ACLY, SLC27A2, and COL1A1 and upregulated DEGs such as HOXA9, PGM2L1, and ABAT provides insights into the molecular mechanisms underlying fat deposition and muscle development in sheep. Conclusions: The findings support the practice of castration in sheep production as it enhances growth performance, leads to leaner carcasses with higher muscle content, and improves meat tenderness. The identified changes in gene expression offer valuable insights for further research into understanding the impact of castration on muscle development and fat metabolism in sheep. This meta-analysis contributes to the knowledge of molecular mechanisms involved in fat deposition in sheep, opening avenues for future investigations in livestock fat metabolism research. Full article

A proteomics analysis of purified rabies virus (RABV) revealed 47 entrapped host proteins within the viral particles. Out of these, 11 proteins were highly disordered. Our study was particularly focused on five of the RABV-entrapped mouse proteins with the highest levels of disorder: Neuromodulin, Chmp4b, DnaJB6, Vps37B, and Wasl. We extensively utilized bioinformatics tools, such as FuzDrop, D²P², UniProt, RIDAO, STRING, AlphaFold, and ELM, for a comprehensive analysis of the intrinsic disorder propensity of these proteins. Our analysis suggested that these disordered host proteins might play a significant role in facilitating the rabies virus pathogenicity, immune system evasion, and the development of antiviral drug resistance. Our study highlighted the complex interaction of the virus with its host, with a focus on how the intrinsic disorder can play a crucial role in virus pathogenic processes, and suggested that these intrinsically disordered proteins (IDPs) and disorder-related host interactions can also be a potential target for therapeutic strategies. Full article

Residential energy retrofitting projects in the hot summer and cold winter (HSCW) zone of China face various risks related to project activities, which incur transaction costs (TCs), such as search, negotiation, and monitoring costs. As the leader in project implementation, the Chinese government is responsible for project planning, organisation, and coordination. However, TCs impede the government’s ability to execute risk-related project activities effectively, subsequently increasing the probability of the occurrence of risk. Drawing on transaction cost economics (TCE), this study proposes a theoretical framework to understand the barriers—such as asset specificity, uncertainty, and frequency—that prevent the government from performing project activities and mitigating risks effectively. An artificial neural network (ANN) is applied to verify the hypotheses. The results underscore experience and operational maturity in project activities, cost and time constraints, and the immature retrofitting market as significant impediments to the government’s execution of risk-related activities. Considering the varying roles of the government in reducing different risks, this study concludes by offering policy recommendations to alleviate these activity barriers and mitigate risks. By employing a TCs perspective, this study not only identifies key barriers but also deepens our understanding of risk mitigation mechanisms, providing robust policy insights tailored to the specific regional context of China, thereby enhancing both the execution and the framework of government-led retrofitting projects. Full article

Background: Abdominoperineal resection (APR)—the standard surgical procedure for low-lying rectal cancer (LRC)—leads to significant perineal defects, posing considerable reconstruction challenges that, in selected cases, necessitate the use of plastic surgery techniques (flaps). Purpose: To develop valuable decision algorithms for choosing the appropriate surgical plan for the reconstruction of perineal defects. Methods: Our study included 245 LRC cases treated using APR. Guided by the few available publications in the field, we have designed several personalized decisional algorithms for managing perineal defects considering the following factors: preoperative radiotherapy, intraoperative position, surgical technique, perineal defect volume, and quality of tissues and perforators. The algorithms have been improved continuously during the entire period of our study based on the immediate and remote outcomes. Results: In 239 patients following APR, the direct closing procedure was performed versus 6 cases in which we used various types of flaps for perineal reconstruction. Perineal incisional hernia occurred in 12 patients (5.02%) with direct perineal wound closure versus in none of those reconstructed using flaps. Conclusion: The reduced rate of postoperative complications suggests the efficiency of the proposed decisional algorithms; however, more extended studies are required to categorize them as evidence-based management guide tools. Full article

This study investigates the impacts of the Big Five personality traits and propensity to trust on the use and writing of online reviews. Additionally, this study examines how gender moderates these impacts. Results of a survey (n = 840) show that openness to experience and conscientiousness positively influence online review use, while openness to experience and extraversion positively influence online review writing. Moreover, gender moderates the impacts of extraversion, openness to experience, and agreeableness on online review writing, with no moderating effect observed for online review use. Our findings contribute to the electronic word-of-mouth (eWOM) literature and offer important practical insights for eWOM platforms. Full article

In Romania, the pandemic and post-pandemic effects, coupled with the nearly 80% increase in internet service penetration, have led to an extraordinary acceleration of e-commerce activity. Rising rents and operational costs, heightened financial challenges, and the improved quality and accessibility of internet connectivity have prompted some Romanian SMEs to sell their products and services online or through other online communication networks. In this context, it becomes essential to conduct marketing research to identify factors that could stimulate business performance. The purpose of this study is to assess the impact of e-marketing orientation, sustainability orientation, and technology orientation on the performance of online SMEs in Romania. Hypothesis testing and validation of the proposed construct model were conducted using structural equation modeling with partial least squares (SEM-PLS) and multi-group analysis (PLS-MGA). The research results have indicated that all three independent variables have positive and significant effects on online SMEs’ business performance. Finally, the study suggests that SME managers should focus on integrating these three variables and on selling products and services both nationally and internationally through the internet if they aim for long-term business performance growth. Full article

This study explores the progress of chatbot technology, focusing on the aspect of error correction to enhance these smart conversational tools. Chatbots, powered by artificial intelligence (AI), are increasingly prevalent across industries such as customer service, healthcare, e-commerce, and education. Despite their use and increasing complexity, chatbots are prone to errors like misunderstandings, inappropriate responses, and factual inaccuracies. These issues can have an impact on user satisfaction and trust. This research provides an overview of chatbots, conducts an analysis of errors they encounter, and examines different approaches to rectifying these errors. These approaches include using data-driven feedback loops, involving humans in the learning process, and adjusting through learning methods like reinforcement learning, supervised learning, unsupervised learning, semi-supervised learning, and meta-learning. Through real life examples and case studies in different fields, we explore how these strategies are implemented. Looking ahead, we explore the different challenges faced by AI-powered chatbots, including ethical considerations and biases during implementation. Furthermore, we explore the transformative potential of new technological advancements, such as explainable AI models, autonomous content generation algorithms (e.g., generative adversarial networks), and quantum computing to enhance chatbot training. Our research provides information for developers and researchers looking to improve chatbot capabilities, which can be applied in service and support industries to effectively address user requirements. Full article

The soil response under the inherent cyclic loading conditions when dealing with offshore foundations can be considered by using contour plots. These plots are derived from several cyclic laboratory tests and characterize the general cyclic soil behaviour. In the design process with explicit numerical methods, such plots are needed in order to assess the soil behaviour under arbitrary loading conditions and hence estimate the cyclic foundation response. In the paper, excess pore pressure contour plots for a poorly graded medium sand are derived from numerous constant volume (CV) cyclic direct simple shear (DSS) tests and a new approach for parametrization of the plots is presented. Subsequently, the data are assessed regarding scaling for other sand soils, i.e., construction of contour plots with only a small number of test results by using the general trends observed. Full article

Background: Pneumonia is a ubiquitous health condition with severe outcomes. The advancement of ultrasonography techniques allows its application in evaluating pulmonary diseases, providing safer and accessible bedside therapeutic decisions compared to chest X-ray and chest computed tomography (CT) scan. Because of its aforementioned benefits, we aimed to confirm the diagnostic accuracy of lung ultrasound (LUS) for pneumonia in adults. Methods: A systematic literature search was performed of Medline, Cochrane and Crossref, independently by two authors. The selection of studies proceeded based on specific inclusion and exclusion criteria without restrictions to particular study designs, language or publication dates and was followed by data extraction. The gold standard reference in the included studies was chest X-ray/CT scan or both. Results: Twenty-nine (29) studies containing 6702 participants were included in our meta-analysis. Pooled sensitivity, specificity and PPV were 92% (95% CI: 91–93%), 94% (95% CI: 94 to 95%) and 93% (95% CI: 89 to 96%), respectively. Pooled positive and negative likelihood ratios were 16 (95% CI: 14 to 19) and 0.08 (95% CI: 0.07 to 0.09). The area under the ROC curve of LUS was 0. 9712. Conclusions: LUS has high diagnostic accuracy in adult pneumonia. Its contribution could form an optimistic clue in future updates considering this condition. Full article

The purpose of this research paper is to present a framework for selecting a biogas plant for the Indian rural community, considering performability factors such as reliability, quality, maintainability, safety, and sustainability. This will ensure that the plant operates reliably, efficiently, and safely over its entire life cycle and can play a significant role as a decision-support tool for decision-makers (e.g., managers, engineers, stakeholders). The proposed framework integrates the Analytic Hierarchy Process (AHP), and the Weighted Aggregated Sum Product Assessment (WASPAS) to optimally evaluate and prioritize the best alternative based on performability factors. The findings show that the suitable biogas plant in the context of the Indian rural population is a fixed-dome-type plant. The decision-making process in selecting the best biogas plant can be effectively aided by using this suggested tool. Currently, there are no proper tools or methods for selecting biogas plants for rural areas due to a lack of data or relevant literature on operational issues. The proposed method uses performability factors for the selection, which has not been researched so far. Moreover, the AHP–WASPAS approach offers a robust method for selecting biogas plants, ensuring efficient and sustainable energy production. The proposed method will help policymakers and stakeholders to choose the best biogas plant in the context of Indian rural application. Full article