Key Factors Research Articles

Enhancing Procurement Integrity: Key Factors Influencing Internal Audit Effectiveness in Tanzania Public Procurement

This paper analyses the effects of internal audit competence, independence, and procedures on internal audit effectiveness in the procurement process in the public sector of Tanzania. The study is quantitative, and data were collected through questionnaires from accounting officers, senior management officers, audit committees, and internal audit units in public sectors. A total of 318 responses were collected. A Partial Least Structural Equation Modelling (PLS-SEM) technique was applied using R-studio to analyse the collected data, assess the model and test hypotheses. The findings revealed that internal audit characteristics procedures, independence and competence influence internal audit effectiveness in procurement. The study findings provide useful insights for policymakers, academics, and internal audit practitioners on the effect of the characteristics of internal audits in improving the effectiveness of internal audits in procurement in Tanzania.

Dynamics of Population and Land Use towards Sustainable Development in Patna Planning Area

Abstract: This study examines the impact of population growth on the land use pattern of Patna Planning Area, in the context of urban geography. Patna, the capital city of Bihar state in India, has experienced significant population growth over the past few decades, leading to changes in its land use pattern. The objectives of this research include analyzing the historical population growth trends in Patna, identifying the key factors that have contributed to this growth, and assessing its impact on land use. The study takes into account various factors such as residential, industrial, commercial, and agricultural land use, as well as the infrastructural developments associated with population growth. To achieve these objectives, both primary and secondary data sources are utilized. Primary data is collected through surveys, interviews, and observations, while secondary data is obtained from existing literature, government reports, and demographic databases. The findings of this study reveal that the population growth in Patna has led to a changing land use pattern. The expansion of residential areas and the conversion of agricultural land into residential and commercial zones are noted as significant transformations. Additionally, industrial growth has resulted in the emergence of new industrial zones and the conversion of agricultural land into industrial areas in the suburbs. Furthermore, it is observed that population growth has put pressure on infrastructure such as transportation, sewage and water supply systems, leading to the need for their expansion and development. This study highlights the need for urban planning and policies to accommodate the growing population while ensuring sustainable land use.

Energy and exergy analysis of the cryogenic system for HTS magnets based on an open-cycle G-M/J-T cryocooler

High-field magnets have been developed for a broad range of research applications. High-temperature superconducting magnets have received considerable attention due to their potential use in high-field applications. The High Magnetic Field Laboratory of the Chinese Academy of Sciences (CHMFL) is currently designing and constructing high-temperature superconducting (HTS) magnets which need the cooling capacity about 5 W to 10 W at 4.5 K in order to ensure the stability of the system. To meet their operational requirements, a miniature cryogenic system based on the Gifford-McMahon/Joule-Thomson (G-M/J-T) cryocooler has been designed and analyzed. In this research, the performance of the cryogenic system for HTS magnets is investigated systematically by employing both energy analysis and entropy analysis techniques. The results highlight the importance of several key factors, including high pressures, precooling temperature at cooling stages, and J-T exchanger efficiency, for improving the cooling capacity of the cryogenic system. Lowering the precooling temperature can enhance the system cooling capacity and also cause an increase in the precooling capacity. As the pressure increases, the cooling capacity of the system reaches its maximum point at 11.31 bar The J-T heat exchanger accounts for the largest exergy loss rate, 35.2–43.7%. The findings provide technical guidelines for the subsequent experiments and performance optimization of cryogenic system.

Prognostic nomogram for early-stage cervical cancer in the elderly: A SEER database analysis

BackgroundTo identify key clinical factors affecting the survival of elderly patients with early-stage cervical cancer and to construct a nomogram for predicting their prognosis. MethodsPatients (aged ≥ 65 years old) diagnosed with cervical cancer between 2004 and 2015 at clinical stages IA to IIA were included in this study. Diagnosis was confirmed via pathological examination, and the cases were randomly divided into a training or a validation group in a 7:3 ratio. Univariate and multivariable Cox regression analyses were performed to identify independent factors affecting the prognosis of elderly early-stage cervical cancer patients, based on which a nomogram was constructed to predict their 12-, 24- and 36-month overall survival (OS). The nomogram's performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) curves. ResultsA total of 686 patients were identified as eligible and assessed. Multivariable Cox proportional hazard regression analysis revealed that age, tumor diameter, marital status and surgical intervention were independent prognostic factors for elderly individuals with early-stage cervical cancer, which were then used to construct the nomogram. The calibration curves showed a strong correlation between predicted and observed survival rates, and Kaplan-Meier survival curves for different risk subgroups demonstrated significant survival differences (P < 0.001). DCA confirmed the nomogram's clinical utility in predicting the prognosis of elderly patients with early-stage cervical cancer. ConclusionThe prognostic model developed in this study can accurately predict the OS of elderly patients with early-stage cervical cancer, showing high concordance with actual clinical outcomes.

Prognostic value and potential function of a novel heme-related LncRNAs signature in gastric cancer

Heme is a coordination complex formed by the binding of iron ions and porphyrin rings. Its metabolic processes are associated with various cancers, including gastric cancer (GC). In recent years, long non-coding RNAs (LncRNAs) have been identified as key regulatory factors in GC. However, the role of LncRNAs associated with heme metabolism in GC and their relationship with prognosis have not been reported. In this study, we constructed a novel LncRNAs signature related to heme metabolism (HMlncSig) and validated its prognostic value for predicting the survival of GC patients through training, test, and entire cohorts. Kaplan-Meier analysis demonstrated that patients in the high-risk group had shorter survival times. Univariate and multivariate Cox regression analysis showed that HMlncSig was an independent prognostic indicator for GC patients, regardless of other clinical pathological features. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set variation analysis pathways showed that the activation of these markers may be involved in tumor progression, influencing the survival of GC patients. The nomogram, based on HMlncSig score and clinical features, demonstrated the strong predictive ability of this signature. Additionally, significant differences were observed between the high-risk and low-risk groups in terms of immune cell subtypes, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy. Through clinical validation, we found that the risk score and heme levels of GC patients were both significantly elevated and correlated with the degree of malignancy. Furthermore, we found that AP000692.1, a key gene in this signature, promoted the proliferation, migration, and invasion of GC cells. In conclusion, our HMlncSig model has significant predictive value for the prognosis of GC patients and can provide clinical guidance for personalized immunotherapy.

Applications of Autonomous Navigation Technologies for Unmanned Agricultural Tractors: A Review

The development of unmanned agricultural tractors (UAT) represents a significant step towards intelligent agricultural equipment. UAT technology is expected to lighten the workload of laborers and enhance the accuracy and efficiency of mechanized operations. Through the investigation of 123 relevant studies in the literature published in recent years, this article reviews three aspects of autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages and deficiencies of these technologies in the context of UATs are clarified by analyzing technical principles and the status of current research. We conduct summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of autonomous navigation technologies in UATs, it can be seen that fruitful research progress has been achieved. The review also summarizes the common problems seen in current UAT technologies. The application of research to the sharing and integrating of multi-source data for autonomous navigation has so far been relatively weak. There is an urgent need for high-precision and high-stability sensing equipment. The universality of path planning methods and the efficiency and precision of path tracking need to be improved, and it is also necessary to develop highly reliable electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

Understanding the correlates of construction safety of high-rise buildings: A Bayesian perspective

Safety in high-rise building construction is a critical concern, particularly in the densely populated urban areas of Vietnam. Understanding the complex interplay of factors influencing safety on construction sites is essential for reducing accidents and enhancing overall project outcomes. This study aims to identify and analyze key factors impacting safety in high-rise construction projects. Utilizing Bayesian Poisson Regression, the research investigates the relationship between various safety-related factors and the occurrence of non-fatal accidents. The study adopts a comprehensive approach, selecting potential safety factors from the existing literature and developing a rating system validated by site safety managers. Data were collected from 48 high-rise buildingprojects in Vietnam, constructed between 2019 and 2022. Bayesian Poisson Regression was employed to analyze the impact of 15 variables on safety outcomes, including management commitment, worker participation,training programs, emergency preparedness, and safety inspections. The findings underscore the multifacetednature of construction safety and the need for a holistic approach that involves strong safety training, engagedmanagement and workers, protective measures, and proactive safety audits. This research provides actionableinsights for practitioners and contributes to the academic discourse on construction safety, emphasizing theutility of Bayesian methods in unraveling complex safety dynamics in high-rise construction.

Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market.

The impact of inflammatory biomarkers on amputation rates in patients with diabetic foot ulcers.

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, often leading to amputation. Understanding the relationship between haematological inflammatory markers and the incidence of amputation in DFU patients with infectious complications is crucial for improving management and outcomes. This retrospective study, conducted from May 2020 to October 2022, involved 109 patients with DFUs, categorised into amputation (AM) and non-amputation (NAM) groups. Patients were evaluated for various factors, including demographic data, DFU duration, and blood parameters such as haemoglobin A1c (HbA1c), haemoglobin (Hb), albumin (ALB), white blood cell count (WBC), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Statistical analyses were performed using independent sample t-tests, Mann-Whitney U test and logistic regression. The univariate analysis showed no significant difference in BMI, DM duration or DFU duration between groups. However, significant differences were noted in PCT, Hb, ESR, ALB, HbA1c and WBC levels, and in inflammatory ratios (NLR, PLR and LMR). Multivariate logistic regression identified CRP, NLR and PLR as independent risk factors for amputation. The study highlights CRP, PLR and NLR as key independent risk factors for amputation in patients with DFUs. These easily obtainable markers from routine blood tests can effectively aid in predicting the risk of osteomyelitis and amputation, enhancing clinical decision making and patient care strategies.

Air Quality Index Prediction Using Machine Learning

Air pollution poses a significant threat to public health, particularly in rapidly developing countries like India, where urbanization and industrialization contribute to diverse sources of pollutants. This research employs machine learning techniques to comprehensively analyse and predict air quality levels across different regions of India. Extensive air quality data, encompassing various pollutants and temporal variations, is collected and compiled. State-ofthe-art machine learning models are developed to identify key influencing factors, including industrial emissions, vehicular traffic, agricultural practices, and meteorological conditions. The models are evaluated for accuracy and reliability in predicting air quality levels. The study aims to provide valuable insights into the complex dynamics of air pollution in the Indian context. By understanding the contributing factors and predicting future air quality levels, this research contributes to the development of targeted and effective air quality management strategies. Keywords: Machine Learning, Air Pollution, AQI.

In-depth analysis to develop a social marketing model to promote women's participation in waste segregation behaviour: A qualitative study

Waste separation is one of the key factors in managing solid waste and creating a healthy environment. Waste separation at source has always been associated with challenges. Therefore, this study was conducted to determine the perceptions of housewives and related parties regarding the factors that influence waste separation behaviour and to identify approaches to improve behaviour based on the social marketing framework. This study was conducted as a qualitative content analysis in Amol City in 2022. The data was collected through semi-structured individual interviews. A total of 25 housewives were selected as main participants and 5 stakeholders through purposive selection. The results of the study included lack of awareness of recyclable materials (product), personal, family and environmental barriers (price), lack of doorstep collection of dry waste (place), and lack of use of appropriate technology (promotion). The lack of financial resources, inappropriate political measures and the coronavirus pandemic were also the causes of this challenge. Most participants cited environmental and educational deficits as the main reason for not separating waste. It is possible to improve waste sorting behaviour at source through appropriate behavioural interventions at the individual, social and environmental levels. Researchers can use the results of this study to design, implement and evaluate waste segregation intervention programmes for housewives.

Bearing capacity analysis and mechanism study of shared caisson under multidirectional loading

Shared anchor foundations experience loads from various directions throughout their operational lifespan. As a result of environmental loads or the possibility of anchor chain failures, the loading direction of the shared foundation may alter, affecting its normal functionality. This study investigates the bearing capacity of the shared caisson in sand using an advanced model and numerical methods under multidirectional loading. Moreover, the research investigates soil responses to clarify the mechanisms governing bearing capacity. The study delves into factors such as load angles, sand density, and previous load magnitudes to comprehend their impact on the bearing capacity of shared caissons. The findings suggest that subsequent loading on dense soil enhances bearing capacity, whereas loading on loose soil reduces it. Key factors influencing the shared caisson's bearing capacity include plastic deformation of the surrounding soil and density changes resulting from previous loads. A coefficient was proposed for designing the shared caisson, taking into account multidirectional loads, thereby providing insights for future shared anchor foundation designs.

Linkages of soil and microbial stoichiometry to crop nitrogen use efficiency: Evidence from a long-term nitrogen addition experiment

Increasing crop nitrogen use efficiency (NUE) has important implications for food security and agricultural sustainability. Changes in nutrient availability due to stoichiometric imbalances in soil under long-term application of nitrogen (N) can limit crop NUE and yield. However, little is known about the linkages across stoichiometric balance, N fertilizer application, and N uptake. We investigated the changes in soil stoichiometry, microbial community, and crop NUE relative to N fertilizer application in a 16-year field experiment in which five levels (0, 70, 140, 210 and 280 kg N ha−1) of mineral N fertilizer treatment were applied to wheat and maize cropland. The results showed that the P storage decreased from 4.3 Mg P ha–1 under the fertilizer dose of 0 kg N ha−1 to 3.5 Mg P ha–1 under the fertilizer dose of 280 kg N ha−1. Thus, long-term N application increased soil C/P and N/P ratios, in a marked decrease in the content of soil available P. The microbial community based on phospholipid fatty acids (PLFAs) increased with increasing N addition rates, from 0 to 140 kg N ha−1, but significantly decreased at application rates above 210 kg N ha−1. Thus, applying N at a rate of 140 kg ha−1 resulted in the N threshold rate for microorganism survival being reached or exceeded. The crop NUE peak occurred at the urea application rate of 140 kg N ha−1 (60.4 %), after which NUE declined. The soil elementary and enzymatic stoichiometric ratios under long-term N addition directly affected crop NUE in the topsoil. Soil elementary stoichiometric ratios affected crop NUE by indirectly altering microbial biomass of the subsoil. Overall, soil stoichiometric imbalances under long-term N addition were the key factors driving NUE across N gradients.

Abstract 1697: Phase separation of BHLHE40 up-regulates SREBF1 and inhibits ferroptosis in pancreatic cancer cells

Abstract Pancreatic cancer (PCa) is one of the most lethal malignancies in human cancers. The enhanced infiltration of stromal tissue of PCa tumor microenvironment limits the identification of key tumor-specific transcription factors and epigenomic abnormalities in malignant epithelial cells. Integrated transcriptome and epigenetic multi-omics analysis of paired PCa organoids indicated that the basic helix-loop-helix transcription factor 40 (BHLHE40) was significantly upregulated in tumor samples. Increased chromatin accessibility at promoter region and enhanced mTOR pathway activity contribute to the elevated expression of BHLHE40. Integrated analysis of chromatin immunoprecipitation (ChIP)-seq, RNA-seq and high-through chromosome conformation capture (Hi-C) data together with chromosome conformation capture (3C) assay indicate that BHLHE40 not only regulates the sterol regulatory element-binding factor 1 (SREBF1) transcription as a classic transcription factor, but also links the enhancer and promoter regions of SREBF1 via forming liquid-liquid phase-separated droplets. Then, we find the BHLHE40-SREBF1-stearoyl-CoA desaturase (SCD1) axis protects PCa cells from ferroptosis, leading to the reduced accumulation of lipid peroxidation in cells. Moreover, SREBF1 inhibitor, Fatostatin, significantly suppresses the cell growth of PCa tumors with higher expression of BHLHE40. This study highlights the important roles of BHLHE40 mediated lipid peroxidation in inducing ferroptosis of PCa cells and provides a novel mechanism underlying the SREBF1 overexpression in PCa. Citation Format: Yizhi Cao, Xuelong Wang, Yang Liu, Pengyi Liu, Jiejie Qin, Youwei Zhu, Shuyu Zhai, Minmin Shi, Weishen Wang, Xiaxing Deng, Chenghong Peng, Hao Chen, Ruibao Ren, Lingxi Jiang, Baiyong Shen. Phase separation of BHLHE40 up-regulates SREBF1 and inhibits ferroptosis in pancreatic cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1697.

Abstract 6207: Exploring colorectal cancer with ARIA: Biomedical insights

Abstract Gaining the promised benefits from the population-scale datasets, both clinical and genomic, is often hindered by the inability to easily access, explore and manipulate such complex data - a difficulty that ARIA was designed to overcome. In the field of biomedicine, organizations harness extensive datasets, gaining profound insights into patients and participants, thereby unleashing possibilities for accelerating research, especially in the realms of drug development and precision medicine. To facilitate navigation through the intricate landscape of biomedical data, Velsera has innovated ARIA to catalyse efficient and insightful analysis, with a keen emphasis on user-friendliness to ensure accessibility across a diverse professional audience. To demonstrate the practical application of ARIA, we explore genomic and clinical datasets to identify key differences in colorectal cancer progression. CRC, the third most common cancer globally, has unique characteristics in origination and progression from benign to pathogenic. Here we investigate differences between patients with polyps that do and do not progress to CRC, including key environmental factors such as smoking history, inactive lifestyle and obesity in conjunction with their known clinical and genetic risk factors. This exploration into the abilities of ARIA demonstrate the ability to analyse complex datasets combining both clinical and genomics data at a large scale. For the purpose of this demonstration, a Synthea Dataset, encompassing synthetic clinical and genomic data for 122,011 patients across various age groups, was utilized. This dataset was generated by Velsera specifically for testing ARIA functionalities. In conclusion, ARIA empowers efficient analysis of complex biomedical datasets, providing a comprehensive understanding of disease mechanisms and facilitating valuable insights. Citation Format: Nevena Nikolic, Sarah Kleinstein, Jelena Radenkovic, Milan Kovacevic. Exploring colorectal cancer with ARIA: Biomedical insights [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6207.

Abstract 5448: Malignant RNA editing by inflammation-responsive RNA editase ADAR1 drives T-cell leukemia relapse via attenuating dsRNA sensing

Abstract Leukemia-initiating cells (LICs) play a crucial role in leukemia research and treatment, being considered the source of relapse and resistance, posing a substantial challenge for successful management of the disease. It's crucial to identify the key factors that drive LIC self-renewal to develop targeted methods for eliminating LICs and preventing relapse. In this study, we demonstrate that the RNA editing enzyme ADAR1 plays a vital role as a determinant of stemness, promoting LIC self-renewal by reducing the detection of abnormal double-stranded RNA (dsRNA). As a result, ADAR1-knockdown significantly impairs the ability of LICs to self-renew and extends survival in T-ALL PDX models. We performed RNA-seq studies on enriched T-ALL LICs (CD34+Lin-). The lentivirus-to-cell ratio was optimized to achieve a 50% reduction in ADAR1, resulting in differential expression of 661 genes, with downregulation of critical self-renewal genes in ADAR1-deficient leukemia-initiating cells. Importantly, additional data indicated that ADAR1 likely influences self-renewal gene expression independently of A-to-I RNA editing, revealing novel regulatory mechanisms in leukemia. Knockdown of MDA5 and ADAR1 in patient-derived xenograft (PDX) T-ALL leukemia-initiating cells (LICs) revealed diverse rescue effects on self-renewal in different PDX models. The differential response was associated with variations in gene expression patterns in Rig-I-Like signaling and cytosolic sensing pathways, suggesting intrinsic differences in IFN signaling properties among patients. Moreover, the study proposes a patient-specific reliance on the ADAR1 p150-MDA5 axis for promoting self-renewal, as evidenced by differential rescue effects and varying expression levels of ADAR1 isoforms and MDA5 in T-ALL patient samples and cell lines. ADAR1, beyond its role in RNA editing, acts as a dsRNA binding protein, exerting RNA editing-independent functions to suppress aberrant IFN signaling and promote cancer progression. Using Jurkat cells with high intrinsic MDA5 levels, an ADAR1 knockout (KO) was generated, revealing that ADAR1 is upregulated by IFN treatment, predominantly the p150 isoform. We explored the dual roles of ADAR1—RNA editing-dependent and -independent—in suppressing IFN-induced apoptosis, demonstrating the necessity of both for optimal function. Additionally, ADAR1 was found to suppress cytoplasmic dsRNA sensing pathways, such as RIG-I and PKR, and its RNA editing-independent activity contributes significantly to the suppression of interferon-stimulated gene (ISG) expression in T-ALL. In summary, our findings reveal that ADAR1 acts as a factor that promotes self-renewal while limiting the recognition of naturally occurring dsRNA. Therefore, targeting ADAR1 emerges as a safe and effective therapeutic approach for eradicating LICs in T-ALL. Citation Format: Maria Dolores Rivera, Haoran Zhang, Qingchen Zhou, Jessica Pham, Jane Isquith, Roman Sasik, Adam Mark, Sabina Enlund, Frida Holm, Ma Wenxue, Kathleen Fisch, Dennis Kuo, Catriona Jamieson, Qingfei Jiang. Malignant RNA editing by inflammation-responsive RNA editase ADAR1 drives T-cell leukemia relapse via attenuating dsRNA sensing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5448.

Astragaloside IV attenuates renal tubule injury in DKD rats via suppression of CD36-mediated NLRP3 inflammasome activation.

In recent years, diabetic kidney disease (DKD) has emerged as a prominent factor contributing to end-stage renal disease. Tubulointerstitial inflammation and lipid accumulation have been identified as key factors in the development of DKD. Earlier research indicated that Astragaloside IV (AS-IV) reduces inflammation and oxidative stress, controls lipid accumulation, and provides protection to the kidneys. Nevertheless, the mechanisms responsible for its protective effects against DKD have not yet been completely elucidated. The primary objective of this research was to examine the protective properties of AS-IV against DKD and investigate the underlying mechanism, which involves CD36, reactive oxygen species (ROS), NLR family pyrin domain containing 3 (NLRP3), and interleukin-1β (IL-1β). The DKD rat model was created by administering streptozotocin along with a high-fat diet. Subsequently, the DKD rats and palmitic acid (PA)-induced HK-2 cells were treated with AS-IV. Atorvastatin was used as the positive control. To assess the therapeutic effects of AS-IV on DKD, various tests including blood sugar levels, the lipid profile, renal function, and histopathological examinations were conducted. The levels of CD36, ROS, NLRP3, Caspase-1, and IL-1β were detected using western blot analysis, PCR, and flow cytometry. Furthermore, adenovirus-mediated CD36 overexpression was applied to explore the underlying mechanisms through in vitro experiments. In vivo experiments demonstrated that AS-IV significantly reduced hyperglycemia, dyslipidemia, urinary albumin excretion, and serum creatinine levels in DKD rats. Additionally, it improved renal structural abnormalities and suppressed the expression of CD36, NLRP3, IL-1β, TNF-α, and MCP-1. In vitro experiments showed that AS-IV decreased CD36 expression, lipid accumulation, and lipid ROS production while inhibiting NLRP3 activation and IL-1β secretion in PA-induced HK-2 cells. AS-IV alleviated renal tubule interstitial inflammation and tubule epithelial cell apoptosis in DKD rats by inhibiting CD36-mediated lipid accumulation and NLRP3 inflammasome activation.

Investigating the multifaceted dynamics of cybersecurity practices and their impact on the quality of e-government services: evidence from the KSA

PurposeThe Kingdom of Saudi Arabia (KSA) is embracing digital transformation and e-government services, aiming to improve efficiency, accessibility and citizen-centricity. Nonetheless, the country faces challenges such as evolving cyber threats. The purpose of this study is to investigate the factors influencing cybersecurity practices to ensure the reliability and security of e-government services.Design/methodology/approachThis paper investigates the multifaceted dynamics of cybersecurity practices and their impact on the quality and effectiveness of e-government services. Five key factors explored include organizational culture, technology infrastructure, adherence to standards and regulations, employee training and awareness and financial investment in cybersecurity. This study used a quantitative method to gather data from 320 participants. The researcher collected 285 completed questionnaires, excluding unusable or incomplete responses, and analyzed the final data set using partial least squares structural equation modeling.FindingsThe findings show that financial investment in cybersecurity, employee training and awareness and adherence to cybersecurity regulations significantly influence the adoption of robust cybersecurity practices. However, the relationship between organizational culture and cybersecurity practices is less straightforward. The research establishes a strong positive correlation between cybersecurity practices and e-government service quality, highlighting the role of security in fostering public trust and user satisfaction and meeting the evolving needs of citizens and businesses.Originality/valueThis research contributes valuable empirical evidence to the fields of e-government and cybersecurity, offering insights that can inform evidence-based policy decisions and resource allocation. By understanding the nuanced dynamics at play, Saudi Arabia is better poised to fortify its digital governance infrastructure and provide secure, high-quality e-government services to its constituents.

Analysis of influencing factors for housing construction technology in Desakota Village and town communities in China

Rapid urbanization has reformed the peripheries of China’s main cities during the last four decades. The rural areas have been constantly developed through infrastructure development in recent days which introduces a newly semi-urban region referred to as Desakota. The purpose of this research is to discover potential influencing factors of housing construction technology in desakotas of China which needs to be assessed for the implementation of Desakotas forming globally. In this study, a total of six key primary factors and twenty key secondary factors have been shortlisted, which were surveyed by 120 respondents. After the statistical analysis, it is seen that one primary factor, “Architectural and engineering mechanical factors” has been ranked top. Moreover, “Cost, financial and economic evaluation and Analysis of the impact of the natural environment on buildings” both ranked top among twenty secondary factors. This study adds to the body of knowledge by revealing the primary contributing elements for the first time that need to be taken into consideration in the rural and town communities of desakotas in China. The study results could help stakeholders, construction firms, academicians, researchers, and the government to focus their efforts and resources on the significant changes in the Desakotas in preparation for rapid urban development.

Simulation of CO2 dissolution reactions in saline aquifers using lattice Boltzmann method

CO2 dissolution reactions in saline aquifers during geologic carbon sequestration (GCS) involve multiple physicochemical processes and pose a challenge for both experimental and numerical techniques to capture reactive transport features and complex porous structures. Benefited from advanced models in the lattice Boltzmann (LB) community, namely, multiphase flow LB model and multicomponent transport LB model with chemical reactions, dynamics of CO2-water interfaces, concentration evolution of ions, and heterogeneous and homogeneous reactions could be readily captured by the proposed LB model to characterize CO2 dissolution reactions applicable to far-field applications. This LB model can not only emphasize CO2 dissolution processes at the scale of a few pores but also elaborate on the corresponding controlling mechanisms in porous media during GCS in saline aquifers. LB simulations herein indicate that both diffusion coefficient and reactive interfacial length may change the total concentration gradient at the CO2-water interface to further affect CO2 dissolution reactions. It is also confirmed that CO2 dissolution is a non-equilibrium process, which could not be neglected in reservoir-scale simulations. The effect of reactive interfacial length on CO2 dissolution is negligible due to a narrower range of contact angles in saline aquifers. Influenced by the structural complexity of porous media, the dissolution of CO2 clusters shows a strong heterogeneous characteristic evaluated by the pore size distribution. The evolution of pH in homogeneous reactions is estimated via mass action equations. Besides, the effects of partial pressure, formation temperature, and salinity, as three key factors in the practical application, are thoroughly probed. The high pressure is conducive for sequestration because of its greater sequestration efficiency, but the temperature has both positive and negative impacts on CO2 dissolution trapping and should be carefully evaluated in a certain saline aquifer before the operation. High ion strength would decrease the efficiency of dissolution trapping to some extent.