bluuebunny/crossref_metadata_2025 huggingface dataset:
Linear Ensembles for WTI Oil Price Forecasting
Authors: Santos João Lucas Ferreira dos , Vaz Allefe Jardel Chagas , Kachba Yslene Rocha , Stevan Sergio Luiz , Antonini Alves Thiago , Siqueira Hugo Valadares
Published: August 2024

This paper investigated the use of linear models to forecast crude oil futures prices (WTI) on a monthly basis, emphasizing their importance for financial markets and the global economy. The main objective was to develop predictive models using time series analysis techniques, such as autoregressive (AR), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), as well as ARMA variants adjusted by genetic algorithms (ARMA-GA) and particle swarm optimization (ARMA-PSO). Exponential smoothing techniques, including SES, Holt, and Holt-Winters, in additive and multiplicative forms, were also covered. The models were integrated using ensemble techniques, by the mean, median, Moore-Penrose pseudo-inverse, and weighted averages with GA and PSO. The methodology adopted included pre-processing that applied techniques to ensure the stationarity of the data, which is essential for reliable modeling. The results indicated that for one-step-ahead forecasts, the weighted average ensemble with PSO outperformed traditional models in terms of error metrics. For multi-step forecasts (3, 6, 9 and 12), the ensemble with the Moore-Penrose pseudo-inverse showed better results. This study has shown the effectiveness of combining predictive models to forecast future values in WTI oil prices, offering a useful tool for analysis and applications. However, it is possible to expand the idea of applying linear models to non-linear models.
CFD Methodology to Capture the Combustion Behavior of a Conventional Diesel Engine Retrofitted to Operate in Gasoline Compression Ignition Mode
Authors: Viscione Davide , Ravaglioli Vittorio , Mariani Valerio , Silvagni Giacomo , Bianchi Gian Marco
Published: August 2024

The need for a cleaner and more efficient transportation sector emphasizes the development of new technologies aimed at the integrated reduction of pollutant emissions and increases in efficiency. Among these, promising technologies such as low-temperature combustion (LTC) systems operate in the field of the combustion physics, combining the attributes of both spark-ignited (SI) and compression-ignited (CI) engines. In particular, in a gasoline compression ignition (GCI) engine, gasoline is injected in closely spaced multiple pulses near the top dead center (TDC), creating a highly stratified charge which locally auto-ignites based on the thermodynamic conditions. In this work, a sectorial mesh of the combustion chamber was built. Initial and boundary conditions were set according to a one-dimensional model of the engine from a GT-suite platform. Then, a dedicated Matlab R2023b code was used to capture the effect of the pressure wave propagation on the shape of the fuel mass rate in closely spaced multiple injection events. Finally, a 3D-CFD code was validated comparing pressure trace, rate of heat release (RoHR) and emissions with experimental data provided by the test bench. The results highlight the robustness of the tabulated combustion model, which is able to capture the auto-ignition delay with a considerably low amount of computational time compared to common detailed kinetic solvers.
Study on the Dynamic Characteristics of a Wind Turbine Tower Based on Wind Tunnel Experiments
Authors: Yao Yong , Yu Chi , Rao Mumin , Wang Zhaowei , Hua Xugang , Chen Chao
Published: August 2024

This study aims to comprehensively investigate the dynamic characteristics of the tower of a scaled wind turbine model through wind tunnel tests. A model was scaled from the NREL 5 MW prototype wind turbine with a geometric scale ratio of 1/75, based on the similarity rules in thrust coefficient and dynamic characteristics. A series of wind tunnel tests were carried out on the scaled wind turbine model under different operating conditions and parked conditions with different yaw angles, and the modal parameters of the scaled model were identified by the stochastic subspace identification method and rotor stop tests. It was found that the vibration response of the tower in the fore–aft direction achieved its maximum value when the yaw angle was 90° with feathered blades, while the tower vibration response in the side–side direction was relatively severe with the yaw angle ranging from 10° to 50°. These observations are found to be well aligned with the aerodynamic characteristics of the airfoil. Moreover, the experimental results indicate that the scaled wind turbine model can reflect the vibration responses of its full-scale counterpart in the fore–aft direction. The natural frequencies and mode shapes of the scaled model can be accurately identified by different methods, but the identified damping ratios are relatively scattered.
Application of Multiple Linear Regression and Artificial Neural Networks in Analyses and Predictions of the Thermoelectric Performance of Solid Oxide Fuel Cell Systems
Authors: Lai Meilin , Zhang Daihui , Li Yu , Wu Xiaolong , Li Xi
Published: August 2024

Solid oxide fuel cells (SOFCs) are an efficient, reliable and clean source of energy. Predictive modeling and analysis of their performance is becoming increasingly important, especially with the growing emphasis on sustainable development’s requirements. However, mathematical modeling is difficult due to the complexity of its internal structure. In this study, the system’s electricity generating performance and operational characteristics were analyzed using recent on-site monitoring data first. Then, based on Pearson’s correlation coefficient, some of the variables were selected to build two prediction models: an artificial neural network (ANN) model and a multiple linear regression (MLR) model. The models were evaluated on the basis of the normalized mean square error (NRMSE), which was 1.89% for the MLR model and 0.66% for the ANN model, with no overall bias. They were also compared with other existing models, and it was found that the two models used in this study have the advantage of high accuracy and low difficulty. Therefore, the models developed in this study can more accurately and effectively assess the SOFC system’s state and can better support work to improve the thermoelectric performance of SOFC systems.
Abdominal Pain and Chronic Opiate Use in Patients with Gastroparesis
Authors: Ifrah Abraham , Ebeid John , Parkman Henry P.
Published: August 2024

Introduction: Although opiate narcotics may worsen gastroparesis(GP), patients can take these for abdominal pain (AP) or other chronic pain syndromes. This study aims to evaluate medications patients with gastroparesis use for AP and compare patients who use opiate analgesics for AP to those using opiate analgesics for non-abdominal pain. Methods: Patients at a tertiary academic center gastroenterology clinic completed the Patient Assessment of Gastrointestinal Disorders–Symptom Severity Index (PAGI-SYM) and Quality of Life Short-Form 8 (QOL SF-8) surveys between 10/2021 and 03/2023. Patients recorded gastroparesis treatments, pain treatments and indication, and any hospitalizations/emergency department (ED) visits within 3 months of a clinic visit. Results: A total of 53 patients were enrolled: 72% reported having AP. Patients were using the following medications for AP: 25% heating pad, ice or hot showers, 20.8% acetaminophen, 14.6% hyoscyamine, 13% opiate use, 13% marijuana use, 10.4% dicyclomine, 8.3% Nonsteroidal anti-inflammatory drugs (NSAIDs), 4% benzodiazepine, and 2.1% gabapentin. The reported reasons for using opiates were 58% AP, 16.6% chronic back pain, 16.6% Reflex Sympathetic Dystrophy (RSD) and fibromyalgia, and 8.3% osteoarthritis. All opiate users reported daily scheduled use. AP severity scores (4.1 vs. 2.8; p = 0.041), morphine equivalent usage (77 ± 44 vs. 32 ± 28; p = 0.037), and the number of ER visits (1.0 vs. 0 over 3 months) were higher in patients using opiates for AP than those using opiates for non-abdominal pain. Conclusions: In this series, 72% of patients with gastroparesis had abdominal pain, and 13% of patients were taking opiates. Patients who used opiate analgesics for abdominal pain had a higher average abdominal pain severity score and used a higher amount of opiate analgesia than patients using opiates for musculoskeletal pain. Abdominal pain in patients with gastroparesis can be harder to control with opiate analgesia compared to non-abdominal pain, supporting the concept of avoiding chronic opiate usage for abdominal pain in gastroparesis.
Which Variables Are Associated with the Magnitude of the Physical Fitness Response in Older Adults? An Analysis of Their Development and Influence
Authors: da Silva Sobrinho Andressa Crystine , Finzeto Larissa Chacon , de Almeida Mariana Luciano , da Silva Rodrigues Guilherme , Ribeiro de Lima João Gabriel , Pereira Rodrigues Karine , Alexandre Trapé Átila , Prado Lais , Bueno Júnior Carlos Roberto
Published: August 2024

Regular physical exercise has proven to be an effective strategy for enhancing the health and well-being of older adults. However, there are still gaps in our understanding of the impacts of exercise on older adults with different health conditions, as well as in the customization of training programs according to individual capabilities. This study aimed to analyze the variables that influence the response of physical capabilities in older adults, considering their development over the aging process, with the goal of assisting professionals in creating personalized training programs. To achieve this, we conducted a cohort study involving 562 previously inactive adults and older adults who underwent anthropometric assessments, blood pressure measurements, and comprehensive physical tests. These assessments were conducted before and after a 14-week training program. Results indicated no significant variations in variables such as waist circumference (p = 0.0455, effect size = 0.10), body mass index (p = 0.0215, effect size = 0.15), systolic (p < 0.0001, effect size = 0.35) and diastolic blood pressure (p < 0.0001, effect size = 0.25) pre- and post-intervention. Strength tests, agility, the 6 min walk test (6MWT), and the back scratch test (BS) showed significant improvements post-intervention, with p-values all below 0.0001 and effect sizes ranging from 0.30 to 0.50. Multiple linear regression analyses revealed that lower initial values in physical capabilities were associated with more significant improvements during training (R2 = 0.73, p < 0.001). These results underscore that individualized guidance in training can lead to clinically meaningful improvements in physical performance and health among older adults, with effect sizes indicating moderate-to-large benefits (effect size range = 0.30 to 0.50). Therefore, personalized training programs are essential to maximize health benefits in this population.
Synthesis and Anti-Cancer Activity of the Novel Selective Glucocorticoid Receptor Agonists of the Phenylethanolamine Series
Authors: Zhidkova Ekaterina M. , Tilova Leyla R. , Fetisov Timur I. , Kirsanov Kirill I. , Kulikov Evgeny P. , Enikeev Adel D. , Budunova Irina V. , Badun Gennadii A. , Chernysheva Maria G. , Shirinian Valerii Z. , Yakubovskaya Marianna G. , Lesovaya Ekaterina A.
Published: August 2024

Glucocorticoids (GCs) are widely used for treating hematological malignancies despite their multiple adverse effects. The biological response to GCs relies on glucocorticoid receptor (GR) transrepression (TR) that mediates the anticancer effects and transactivation (TA) associated with the side effects. Selective GR agonists (SEGRAs) preferentially activating GR TR could offer greater benefits in cancer treatment. One of the well-characterized SEGRAs, 2-(4-acetoxyphenyl)-2-chloro-N-methylethylammonium-chloride (CpdA), exhibited anticancer activity; however, its translational potential is limited due to chemical instability. To overcome this limitation, we obtained CpdA derivatives, CpdA-01–CpdA-08, employing two synthetic strategies and studied their anti-tumor activity: 4-(1-hydroxy-2-(piperidin-1-yl)ethyl)phenol or CpdA-03 demonstrated superior GR affinity and stability compared to CpdA. In lymphoma Granta and leukemia CEM cell lines, CpdA-03 ligand exhibited typical SEGRA properties, inducing GR TR without triggering GR TA. CpdA-03 effects on cell viability, growth, and apoptosis were similar to the reference GR ligand, dexamethasone (Dex), and the source compound CpdA. In vivo testing of CpdA-03 activity against lymphoma on the transplantable P388 murine lymphoma model showed that CpdA-03 reduced tumor volume threefold, outperforming Dex and CpdA. In conclusion, in this work, we introduce a novel SEGRA CpdA-03 as a promising agent for lymphoma treatment with fewer side effects.
The Effects of Caffeine on Blood Platelets and the Cardiovascular System through Adenosine Receptors
Authors: Marcinek Kinga , Luzak Boguslawa , Rozalski Marcin
Published: August 2024

Caffeine is the most popular and widely consumed behaviourally active substance in the world. This review describes the influence of caffeine on the cardiovascular system, with a special focus on blood platelets. For many years, caffeine was thought to have a negative effect on the cardiovascular system mainly due to increasing blood pressure. However, more recent data suggest that habitual caffeine consumption may reduce the risk of cardiovascular disease and hypertension. This could be a significant finding as cardiovascular disease is the leading cause of death worldwide. Caffeine is known to inhibit A1 adenosine receptors, through which it is believed to modulate inter alia coronary blood flow, total peripheral resistance, diuresis, and heart rate. It has been shown that coffee possesses antiplatelet activity, but depending on the dose and the term of its use, caffeine may stimulate or inhibit platelet reactivity. Also, chronic exposure to caffeine may sensitize or upregulate the adenosine receptors in platelets causing increased cAMP accumulation and anti-aggregatory effects and decrease calcium levels elicited by AR agonists. The search for new, selective, and safe AR agonists is one of the new strategies for improving antiplatelet therapy involving targeting multiple pathways of platelet activation. Therefore, this review examines the AR-dependent impact of caffeine on blood platelets in the presence of adenosine receptor agonists.
Inhibiting CD44-ICD Attenuates LPS-Induced Initiation of Hepatic Inflammation in Septic Mice
Authors: Li Li-Hsuan , Hsu Dur-Zong , Chandrasekaran Victor Raj Mohan , Liu Ming-Yie
Published: August 2024

Sepsis is a severe condition induced by microbial infection. It elicits a systemic inflammatory response, leading to multi-organ failure, and the liver, as a scavenger, plays a significant role in this process. Controlling hepatic inflammation and maintaining liver function is crucial in managing sepsis. CD44-ICD, as a CD44 signal transductor, is involved in multiple inflammatory responses. However, the role of CD44-ICD in lipopolysaccharide (LPS)-induced hepatic inflammation has not been investigated. Therefore, we aimed to examine whether CD44-ICD initiates hepatic inflammation in septic mice. We induced hepatic inflammation in mice by administering LPS. DAPT, a CD44-ICD inhibitor, was given to mice or Chang cells 30 min or 1 h before LPS administration (10 mg/kg, i.p., or 100 ng/mL, respectively). Inhibition of CD44-ICD decreased the level of aspartate aminotransferase (AST), alanine aminotransferase (ALT), hepatic necrosis, inflammatory cell infiltration, interleukin (IL)-1β, inducible NO synthase (iNOS), nitric oxide (NO) production, nuclear factor (NF)κB signaling pathway proteins, and CD44 expression in mice. CD44-ICD inhibition also decreased IL-1β and CD44 expression levels in Chang cells. CD44-ICD may be a primary regulatory function in CD44-associated LPS-induced initiation of hepatic inflammation in mice.
Chikungunya and Mayaro Viruses Induce Chronic Skeletal Muscle Atrophy Triggered by Pro-Inflammatory and Oxidative Response
Authors: da Silva Mariana Oliveira Lopes , Figueiredo Camila Menezes , Neris Rômulo Leão Silva , Guimarães-Andrade Iris Paula , Gavino-Leopoldino Daniel , Miler-da-Silva Leonardo Linhares , Valença Helber da Maia , Ladislau Leandro , de Lima Caroline Victorino Felix , Coccarelli Fernanda Meireles , Benjamim Claudia Farias , Assunção-Miranda Iranaia
Published: August 2024

Chikungunya (CHIKV) and Mayaro (MAYV) viruses are arthritogenic alphaviruses that promote an incapacitating and long-lasting inflammatory muscle–articular disease. Despite studies pointing out the importance of skeletal muscle (SkM) in viral pathogenesis, the long-term consequences on its physiology and the mechanism of persistence of symptoms are still poorly understood. Combining molecular, morphological, nuclear magnetic resonance imaging, and histological analysis, we conduct a temporal investigation of CHIKV and MAYV replication in a wild-type mice model, focusing on the impact on SkM composition, structure, and repair in the acute and late phases of infection. We found that viral replication and induced inflammation promote a rapid loss of muscle mass and reduction in fiber cross-sectional area by upregulation of muscle-specific E3 ubiquitin ligases MuRF1 and Atrogin-1 expression, both key regulators of SkM fibers atrophy. Despite a reduction in inflammation and clearance of infectious viral particles, SkM atrophy persists until 30 days post-infection. The genomic CHIKV and MAYV RNAs were still detected in SkM in the late phase, along with the upregulation of chemokines and anti-inflammatory cytokine expression. In agreement with the involvement of inflammatory mediators on induced atrophy, the neutralization of TNF and a reduction in oxidative stress using monomethyl fumarate, an agonist of Nrf2, decreases atrogen expression and atrophic fibers while increasing weight gain in treated mice. These data indicate that arthritogenic alphavirus infection could chronically impact body SkM composition and also harm repair machinery, contributing to a better understanding of mechanisms of arthritogenic alphavirus pathogenesis and with a description of potentially new targets of therapeutic intervention.
Nanoparticles-Delivered Circular RNA Strategy as a Novel Antitumor Approach
Authors: Racca Luisa , Liuzzi Elisabetta , Comparato Simona , Giordano Giorgia , Pignochino Ymera
Published: August 2024

Anticancer therapy urgently needs the development of novel strategies. An innovative molecular target is represented by circular RNAs (circRNAs), single-strand RNA molecules with the 5′ and 3′ ends joined, characterized by a high stability. Although circRNA properties and biological functions have only been partially elucidated, their relationship and involvement in the onset and progression of cancer have emerged. Specific targeting of circRNAs may be obtained with antisense oligonucleotides and silencing RNAs. Nanotechnology is at the forefront of research for perfecting their delivery. Continuous efforts have been made to develop novel nanoparticles (NPs) and improve their performance, materials, and properties regarding biocompatibility and targeting capabilities. Applications in various fields, from imaging to gene therapy, have been explored. This review sums up the smart strategies developed to directly target circRNAs with the fruitful application of NPs in this context.
Arabidopsis Histone Variant H2A.X Functions in the DNA Damage-Coupling Abscisic Acid Signaling Pathway
Authors: Guo Peng , Wang Tian-Jing , Wang Shuang , Peng Xiaoyuan , Kim Dae Heon , Liu Yutong
Published: August 2024

Environmental variations initiate chromatin modifications, leading to the exchange of histone subunits or the repositioning of nucleosomes. The phosphorylated histone variant H2A.X (γH2A.X) is recognized for the formation of foci that serve as established markers of DNA double-strand breaks (DSBs). Nevertheless, the precise roles of H2A.X in the cellular response to genotoxic stress and the impact of the plant hormone abscisic acid (ABA) remain incompletely understood. In this investigation, we implemented CRISPR/Cas9 technology to produce loss-of-function mutants of AtHTA3 and AtHTA5 in Arabidopsis. The phenotypes of the athta3 and athta5 single mutants were nearly identical to those of the wild-type Col-0. Nevertheless, the athta3 athta5 double mutants exhibited aberrant embryonic development, increased sensitivity to DNA damage, and higher sensitivity to ABA. The RT-qPCR analysis indicates that AtHTA3 and AtHTA5 negatively regulate the expression of AtABI3, a fundamental regulator in the ABA signaling pathway. Subsequent investigation demonstrated that AtABI3 participates in the genotoxic stress response by influencing the expression of DNA damage response genes, such as AtBRCA1, AtRAD51, and AtWEE1. Our research offers new insights into the role of H2A.X in the genotoxic and ABA responses of Arabidopsis.
Dynamic Response and Mooring Fracture Performance Analysis of a Semi-Submersible Floating Offshore Wind Turbine under Freak Waves
Authors: Liu Baolong , Yu Jianxing
Published: August 2024

Among the extreme sea scenarios, freak waves pose a serious threat to offshore structures, potentially leading to structural failure, such as mooring line failure, floater capsizing, or structural damage. In this study, we conducted a numerical investigation on the transient performance of a semi-submersible floating offshore wind turbine (FOWT) equipped with a redundant mooring system under the influence of freak waves and mooring failure. Firstly, we analyzed the dynamic responses of an intact-mooring-system FOWT under a freak wave. Next, we examined the effect of mooring failure on the transient responses. The results indicate that floater motions exhibit significant differences in the interval of freak wave crests. The impact of freak waves increases the blade tip deformation and tower root bending moment, while also affecting the tension of the mooring line and the aerodynamic performance of the wind turbine. Consecutive fracture with an interval of 20 s significantly increases surge motion and reduces output power. When mooring lines break separately with an interval of 400 s, the amplification in the responses is noticeably lower compared to consecutive fracture cases.
Stress Suppression Design for Radiofrequency Microelectromechanical System Switch Based on a Flexible Substrate
Authors: Wang Kang , Chai Zhaoer , Pan Yutang , Gao Chuyuan , Xu Yaxin , Ren Jiawei , Wang Jie , Zhao Fei , Qin Ming , Han Lei
Published: August 2024

A novel stress suppression design for flexible RF MEMS switches has been presented and demonstrated through theoretical and experimental research to isolate the stress caused by substrate bending. An RF MEMS switch with an S-shaped microspring structure was fabricated by the two-step etching process as a developmental step toward miniaturization and high reliability. The RF MEMS switches with an S-shaped microspring exhibited superior microwave performance and stable driving voltage under different substrate curvatures compared to the conventional non-microspring switches, demonstrating that the bending stress is successfully suppressed by the S-shaped microspring and the island structure. Furthermore, this innovative design could be easily extended to other flexible devices.
Selected Physical and Mechanical Properties of Particleboards Manufactured from Plantation Willow and Poplar Wood
Authors: Żabowski Bartłomiej , Wronka Anita , Kowaluk Grzegorz
Published: August 2024

This research focuses on producing particleboards from the biomass of plantation willow (Salix viminalis L.) and poplar (Populus spp.), aiming to explore their feasibility as sustainable materials for various applications. Fast-growing willow and poplar are known for their rapid growth and suitability for energy production. They present an intriguing alternative as raw materials with added value for particleboard manufacturing. This study investigates the selected mechanical and physical properties of the produced particleboards, considering parameters such as density profile, bending strength, modulus of elasticity, internal bond, water absorption, thickness swelling, and screw withdrawal resistance. The research results were also compared between different mass shares of willow and poplar particles in the particleboards. The results show that the panels produced entirely from the tested alternative raw materials had a modulus of rupture of 21.7 N mm−2 compared to 14.6 N mm−2 for the reference panels, with an internal bond of about 2.02 N mm−2 compared to 0.65 N mm−2 for the reference panels. The thickness swelling after 24 h of soaking was about 24.2% compared to 42.2% for reference panels. The findings underscore the promising potential of willow and poplar-based particleboards as eco-friendly alternatives in the construction and furniture industries, contributing to resource efficiency and carbon emission reduction efforts.
Ionic Twin Nanostructural Comparison: Propylammonium Butanoate vs. Butylammonium Propanoate and Their Interactions with Water
Authors: Salma Umme , Plechkova Natalia V. , Gontrani Lorenzo , Carbone Marilena
Published: August 2024

This study investigates the nanostructure of two protic ionic liquids (PILs), [N0 0 0 3][C3CO2] and [N0 0 0 4][C2CO2], with similar polar head groups but varying alkyl chain lengths. An X-ray scattering technique and molecular dynamics simulations have been utilized to characterize the bulk and interfacial properties of these PILs. The findings suggest that the nanostructure of the PILs is primarily determined by the electrostatic forces between charged functional groups playing a dominant role. Despite differences in the alkyl chain lengths, the PILs possess remarkably similar nanostructures. Extending our investigation, we report the impact of water on the nanostructure. Our findings reveal that the addition of water disrupts interactions between cations and anions, weakening Coulombic forces. The disruptive behavior is attributed to the establishment of hydrogen bonds between water and ions. This comprehensive approach provides valuable insights into the nuanced factors shaping the nanostructure of these PILs, which are crucial for tailoring their applications in synthetic chemistry, catalysis, and beyond.
Modified Chevrel Technique: A Lifesaver for Surgeons
Authors: Dere Özcan , Yazkan Cenk , Şahin Samet , Nazlı Okay , Özcan Önder
Published: August 2024

Background and Objectives: Ventral hernias (VH) pose significant challenges for surgeons due to the risk of recurrence, complexities in aligning abdominal muscles, and selecting the most suitable layer for mesh augmentation. This study aims to evaluate the effectiveness of utilizing the anterior rectus fascia as a turnover flap in conjunction with onlay mesh reinforcement, a procedure known as the modified Chevrel technique (MCT). Materials and Methods: We conducted a retrospective analysis of patients who were operated on using MCT for abdominal hernias between January 2013 and December 2019. Data were extracted from our hospital’s electronic database. Recurrence rates, as well as the rates of surgical site occurrences (SSO), surgical site infections (SSI), and surgical site occurrences requiring procedural intervention (SSOPI), were analyzed based on patients’ comorbidities and demographic characteristics. Results: The median follow-up period was 42.9 months (range: 14–96), and the recurrence rate was 4% (n = 3). Among the recurrent cases, three patients had chronic obstructive pulmonary disease, representing a statistically significant association (p = 0.02). Although all patients with recurrence were obese, this association did not reach statistical significance (p > 0.05). The mean hospitalization duration was 17.6 days (range: 6–29). SSO, SSI, and SSOPI rates were 39 (52%), 12 (16%), and 32 (42%), respectively. Conclusions: Managing VH remains a surgical challenge, emphasizing the importance of achieving effective abdominal closure for both functional and cosmetic outcomes. MCT presents a relatively simple approach compared to techniques like transversus abdominis release (TAR) and anterior component separation (ACS), with acceptable rates of SSO, SSOPI, SSI, and recurrence.
Metabolic Dysfunction-Associated Steatotic Liver Disease in Japan: Prevalence Trends and Clinical Background in the 10 Years before the Coronavirus Disease 2019 Pandemic
Authors: Sato Akira , Oomori Yumiko , Nakano Rika , Matsuura Tomokazu
Published: August 2024

Background and Objectives: The trends in metabolic dysfunction-associated steatotic liver disease (MASLD) and related metabolic dysfunctions in Japan are unknown. Thus, we aimed to clarify these trends before the novel coronavirus disease 2019 pandemic in Japan. Materials and Methods: We included Japanese individuals aged 25–79 years who underwent health examinations at our center. We analyzed anthropometry, lifestyle-related disease, and nutritional intake in relation to MASLD trends from 2010–2019. Results: The prevalence of MASLD increased in all ages and body mass index (BMI) classes, reaching 30.3% in males and 16.1% in females, with MASLD accounting for 75% of steatotic liver cases and more than half of all type 2 diabetes mellitus (T2DM) and high waist circumference (HWC) cases. The increase in the prevalence of MASLD was thought to be largely attributable to an increase in that of the incidence of steatotic liver itself, and there was no increase in the prevalence of other factors, such as overweight, T2DM, hypertension, and dyslipidemia. The prevalence of glucose metabolic disorders (GMDs) and hypertension decreased. National nutritional data showed an increase in energy intake, total fat, saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids, which correlated with a decrease in GMDs. Salt intake also decreased, which correlated with hypertension. The MASLD group had a higher prevalence of all related metabolic factors than the non-MASLD group, especially HWC, T2DM, and hyperlipidemia. Conclusions: The prevalence of MASLD increased with that of steatotic liver, regardless of age or BMI. A relationship between increased dietary fat, increased steatotic liver, and decreased GMDs was suggested.
The Interaction of Continental and Analytical Philosophy in the Development of the Philosophy of Dialogue
Authors: Dvorkin Ilya
Published: August 2024

In continental and analytical philosophy, which developed in parallel in the 20th century, there was a turn to language, which in particular was marked by the creation of a philosophy of dialogue in continental philosophy and dialogical logic in analytical. Despite their significant differences, these two directions have much in common and can significantly complement each other. The philosophy of dialogue considers reality as the subject of dialogue between persons—I, Thou, He/She, We. World, activity and culture are dialogic and interpersonal in nature. Languages and texts are the basis for understanding reality and activity. Dialogical logic describes reality as an object of a dialogical game. This allows us to consider rationality, activity and communication from a unified perspective. The article compares these two directions of dialogical thought with each other and examines the aspects in which they can complement each other.
Liturgical Narrative and the Imagination
Authors: Whitlock Michelle L.
Published: August 2024

Paul Ricœur’s narrative hermeneutic provides a unique lens for interpreting liturgy as narrative. Liturgy begins with the collective, prefigured knowledge of the assembly and configures symbols, music, prayers, scriptures, and actions into an interpretive narrative. This process engages the liturgical assembly’s imagination to synthesize its unique narrative of God’s divine story. This paper explores the function of imagination in the formative process of liturgical narrative arguing that imagination shapes human knowing and being through liturgical narrative.
“The Voice of the Universe”: Cosmic Immanence in John Elof Boodin’s Process Thought, What It Is and Why It Matters
Authors: Flannery Michael A.
Published: August 2024

For most, the way to process thought has been through mathematician-turned-philosopher Alfred North Whitehead (1861–1947). However, his contemporary, Swedish–American philosopher John Elof Boodin (1869–1950), offers another path. While both clearly exposit a process-based philosophy/theology, there are important differences. The main purpose of this essay is to delineate those differences and highlight Boodin’s concept of cosmic immanence (CI) as a key feature separating him from Whitehead’s metaphysic. It is argued that CI can provide the heavy lifting for developing a coherent and satisfying process theology without the baggage attached to Whitehead’s difficult intricate interconnections and enigmatic neologisms. In other words, Boodin’s criticisms of Whitehead (of which there were several) do not amount to an abandonment of process-based thinking or even Whitehead’s larger project of developing a coherent process theology. However, the addition of a new synthesis—merging Boodin’s CI with Joseph A. Bracken’s trinitarian God/world thesis and Ludwig von Bertalanffy’s general systems theory (GST)—is necessary for completion. This new CI synthesis suggests that the same process-based destination can be arrived at by an easier and clearer route.
Semantic Segmentation Network Based on Adaptive Attention and Deep Fusion Utilizing a Multi-Scale Dilated Convolutional Pyramid
Authors: Zhao Shan , Wang Zihao , Huo Zhanqiang , Zhang Fukai
Published: August 2024

Deep learning has recently made significant progress in semantic segmentation. However, the current methods face critical challenges. The segmentation process often lacks sufficient contextual information and attention mechanisms, low-level features lack semantic richness, and high-level features suffer from poor resolution. These limitations reduce the model’s ability to accurately understand and process scene details, particularly in complex scenarios, leading to segmentation outputs that may have inaccuracies in boundary delineation, misclassification of regions, and poor handling of small or overlapping objects. To address these challenges, this paper proposes a Semantic Segmentation Network Based on Adaptive Attention and Deep Fusion with the Multi-Scale Dilated Convolutional Pyramid (SDAMNet). Specifically, the Dilated Convolutional Atrous Spatial Pyramid Pooling (DCASPP) module is developed to enhance contextual information in semantic segmentation. Additionally, a Semantic Channel Space Details Module (SCSDM) is devised to improve the extraction of significant features through multi-scale feature fusion and adaptive feature selection, enhancing the model’s perceptual capability for key regions and optimizing semantic understanding and segmentation performance. Furthermore, a Semantic Features Fusion Module (SFFM) is constructed to address the semantic deficiency in low-level features and the low resolution in high-level features. The effectiveness of SDAMNet is demonstrated on two datasets, revealing significant improvements in Mean Intersection over Union (MIOU) by 2.89% and 2.13%, respectively, compared to the Deeplabv3+ network.
An End-to-End Deep Learning Framework for Fault Detection in Marine Machinery
Authors: Rigas Spyros , Tzouveli Paraskevi , Kollias Stefanos
Published: August 2024

The Industrial Internet of Things has enabled the integration and analysis of vast volumes of data across various industries, with the maritime sector being no exception. Advances in cloud computing and deep learning (DL) are continuously reshaping the industry, particularly in optimizing maritime operations such as Predictive Maintenance (PdM). In this study, we propose a novel DL-based framework focusing on the fault detection task of PdM in marine operations, leveraging time-series data from sensors installed on shipboard machinery. The framework is designed as a scalable and cost-efficient software solution, encompassing all stages from data collection and pre-processing at the edge to the deployment and lifecycle management of DL models. The proposed DL architecture utilizes Graph Attention Networks (GATs) to extract spatio-temporal information from the time-series data and provides explainable predictions through a feature-wise scoring mechanism. Additionally, a custom evaluation metric with real-world applicability is employed, prioritizing both prediction accuracy and the timeliness of fault identification. To demonstrate the effectiveness of our framework, we conduct experiments on three types of open-source datasets relevant to PdM: electrical data, bearing datasets, and data from water circulation experiments.
Multi-Channel Multi-Scale Convolution Attention Variational Autoencoder (MCA-VAE): An Interpretable Anomaly Detection Algorithm Based on Variational Autoencoder
Authors: Liu Jingwen , Huang Yuchen , Wu Dizhi , Yang Yuchen , Chen Yanru , Chen Liangyin , Zhang Yuanyuan
Published: August 2024

With the rapid development of industry, the risks factories face are increasing. Therefore, the anomaly detection algorithms deployed in factories need to have high accuracy, and they need to be able to promptly discover and locate the specific equipment causing the anomaly to restore the regular operation of the abnormal equipment. However, the neural network models currently deployed in factories cannot effectively capture both temporal features within dimensions and relationship features between dimensions; some algorithms that consider both types of features lack interpretability. Therefore, we propose a high-precision, interpretable anomaly detection algorithm based on variational autoencoder (VAE). We use a multi-scale local weight-sharing convolutional neural network structure to fully extract the temporal features within each dimension of the multi-dimensional time series. Then, we model the features from various aspects through multiple attention heads, extracting the relationship features between dimensions. We map the attention output results to the latent space distribution of the VAE and propose an optimization method to improve the reconstruction performance of the VAE, detecting anomalies through reconstruction errors. Regarding anomaly interpretability, we utilize the VAE probability distribution characteristics, decompose the obtained joint probability density into conditional probabilities on each dimension, and calculate the anomaly score, which provides helpful value for technicians. Experimental results show that our algorithm performed best in terms of F1 score and AUC value. The AUC value for anomaly detection is 0.982, and the F1 score is 0.905, which is 4% higher than the best-performing baseline algorithm, Transformer with a Discriminator for Anomaly Detection (TDAD). It also provides accurate anomaly interpretation capability.
Intrahepatic Duct Incision and Closure for the Treatment of Multiple Cholelithiasis in a Dog
Authors: Kang Ji-Hoon , Noh Mi-Young , Yoon Hun-Young
Published: August 2024

This report describes the successful intrahepatic duct incision and closure for the treatment of multiple cholelithiasis in a dog with untreated hypothyroidism. A 12-year-old spayed female Spitz dog weighing 11.3 kg was diagnosed with multiple cholelithiasis, and a quadrate liver lobectomy and cholecystectomy were performed. Large gallstones were located in the left liver lobe’s intrahepatic duct distal to the anastomosis of the intrahepatic ducts of the left medial and lateral lobes. The dilated intrahepatic duct was packed off with wet gauze, and incision and closure were performed on the most dilated section, which was proximal to the largest gallstone. After surgery, the patient showed normal liver function and was discharged with normal total bilirubin and C-reactive protein levels. On postoperative day 83, no stones were observed in the dilated common bile duct (CBD), and the degree of dilatation of the CBD had decreased from 9 mm to 4 mm, with no obstructions. Right intrahepatic gallstones were confirmed without dilatation. Hypothyroidism was managed medically. Hepatic duct incision and closure can be performed in dogs with multiple cholelithiasis. Although not the first option, intrahepatic bile duct incision proves to be a new alternative for the successful treatment of cholelithiasis in dogs.
Rendezvous of Nonholonomic Unmanned Ground Vehicles with Ultra-Wide-Angle Cameras
Authors: Li Lijun , Wang Yuanda , Xiong Chao , Shang Wei
Published: August 2024

In this paper, a time-varying delay output feedback control method based on the potential barrier function is proposed, which can solve the communication delay and field-of-view (FOV) constraints of Unmanned Ground Vehicle (UGV) clusters when communicating with ultra-wide-angle cameras. First, a second-order oscillator and an output feedback controller are utilized to feed back the position and direction of neighboring vehicles by exchanging control quantities and to solve the time-varying delay in the position computation of the ultra-wide-angle camera. Due to the limited target radiation range perceived by the camera, an FOV-constrained potential function is adopted to optimize the design of the sliding mode surface. The stability of the closed-loop control system is analyzed by applying the Lyapunov method. Finally, simulation experiments are conducted to verify the effectiveness of the consensus scheme in addressing the communication delay and FOV constraint problem under two different initial conditions.
The Influence of Operational and Financial Risk Mitigation Strate-gies in Enhancing The Survival of Small and Medium-Sized Entities in Zimbabwe’s Volatile Business Environment
Authors: Chingwaro Lloyd , Muchowe Regis Misheal
Published: August 2024

The business environment in Zimbabwe is highly volatile as witnessed by soaring inflation, exchange rate volatility and shortage of foreign currency. This study therefore, scrutinizes the effectiveness of the operational and financial risk mitigation strategies employed by small and medium-sized enter-prises in Zimbabwe given the current unstable business environment. A survey of small and medi-um-sized enterprises in the Harare Central Business District was undertaken for data collection and quantitative data analysis was done, 162 responses from a sample of 260 were obtained and analyzed. Results of the study show a range of operational and financial mitigation strategies adopted by small and medium-sized enterprises in Harare, Zimbabwe. It is evident from the results that there is a sig-nificant correlation between effective risk management and survival of small and medium-sized en-terprises in Harare, this is because small and medium-sized enterprises that make efforts to implement robust risk mitigation measures show a higher likelihood of survival as compared to those that are reluctant to implement effective risk mitigation strategies. Based on the research findings, several rec-ommendations are drawn which can be insightful to small and medium-sized enterprises as follows: small and medium-sized enterprises should strive to develop a holistic approach to risk management in order to curb the negative effects of operational and financial risks, this can be done through regular risk assessments, implementation of suitable risk mitigation measures, as well as designing robust and ongoing monitoring mechanisms; Small and medium-sized enterprises can also consider collabora-tions with industry associations, financial institutions and academia who have access to expertise and resources for effective risk management. This study is of significance to policy makers who may con-sider formulating and providing support and incentives to enable small and medium-sized enterprises implement effective risk mitigation measures that can enhance their sustained survival.
Data-Driven Workforce Planning: Exploring People Analytics in Delhi SME Startups
Authors: Minz Nitish Kumar , Prakash Dr. Anshika , Yadav Dr. Monika , Kalra Hitika
Published: August 2024

This research explores the adoption, implementation, and impact of data-driven workforce planning and people analytics within small and medium-sized enterprise (SME) startups situated in Delhi, India. Through an in-depth analysis of existing literature and empirical studies, the paper investigates factors influencing adoption, challenges faced by startups, and strategies for successful implementation of people analytics. Additionally, the potential impact on organizational performance and employee outcomes, along with key benefits of data driven HRM practices, are examined. Ethical and legal considerations, including compliance with data privacy regulations and ensuring fairness and transparency, are also addressed. The paper concludes by discussing emerging trends, future research directions, and the significance of embracing data-driven approaches for driving innovation and sustainable growth in Delhi’s dynamic entrepreneurial landscape.
Sparking Inclusive Growth: SME Exchanges as Drivers of a Developed India (Vikasit Bharat)
Authors: Mathur Divya , Kumar Dr. A. Senthil
Published: August 2024

SMEs (Small and Medium Enterprises) are considered the backbone of a "Viksit Bharat" (Developed India). often cater to niche markets and are known for their agility and adaptability. This fosters a culture of entrepreneurship and innovation, driving the development of new products and services that cater to the specific needs of a growing Vikasit Bharat. To equip them accessibility of finance via various sources is the need of time. The Initial Public Offering also provides the opportunity for SMEs to bring in sufficient funds into the business. After listing the stock of the company trade on secondary market through stock exchanges like BSE SME and NSE Emerge are the dedicated exchanges for listing SMEs. The present study critically examines the performance of 377 IPOs in SME stock market issued during the period 2020 to December 2023 on the basis of two performance indicators (i) over-subscription ratio and (ii) listing day gains. This study aims at comparing the performance of the IPOs for two periods January 2020- December 2021 and January 2022- December 2023. The results of the study shows that the performance of the IPO’s launched during the period January 2022- December 2023 significantly differs from the performance of the IPO’s which were launched between January 2020- December 2021. It was also examined that the number of IPO’s and the fund raised through them also differ significantly for the two periods.