bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Attachment Anxiety and Avoidance in Predicting Proximal Minority Stressors among Gay and Lesbian People in Italy
Authors: Trombetta Tommaso , Paradiso Maria Noemi , Santoniccolo Fabrizio , Rollè Luca
Published: May 2024

As has been widely documented, minority stress affects the psychosocial well-being of gay and lesbian people. Recently, researchers have turned their attention to psychological factors that may influence the level of minority stress experienced, in order to explain individual differences in perceptions of proximal minority stressors. The present research aimed at assessing the effect of attachment avoidance and anxiety on levels of perceived stigma and internalized homonegativity. A total of 163 participants who self-identified as lesbian or gay (Mage = 32.56, SD = 10.87) were recruited and responded to the self-report questionnaires. Two multiple regression models were applied to assess the association between adult attachment and perceived stigma and internalized homonegativity. Results showed a positive association between attachment anxiety and avoidance and internalized homonegativity, as well as between attachment avoidance and perceived stigma. The emerging results demonstrate the impact of attachment anxiety and avoidance on proximal minority stressors and provide useful data for interventions addressing lesbian and gay people aimed at promoting security-based strategies of affect regulation and positive representations of self and others, which in turn may reduce the level of proximal minority stressors experienced and promote psychosocial well-being.
Community Perceptions of Blackfly Nuisance and Acceptability of the “Slash and Clear” Vector Control Approach in the Ntui Health District of Cameroon: A Qualitative Study
Authors: Siewe Fodjo Joseph Nelson , Ekome Serge Raoul Ekukole , Njamnshi Julius Ndi Taryunyu , Njamnshi Wepnyu Yembe , Njamnshi Kongnyu G. , Ngarka Leonard , Njamnshi Alfred K.
Published: May 2024

Besides being vectors of the onchocerciasis parasite, blackflies are a source of nuisance in onchocerciasis-endemic communities. We investigated the experience of residents in the Ntui Health District (Cameroon) regarding blackfly nuisance and assessed their perceptions of a novel “Slash and Clear” (S&C) intervention for blackfly control. Focus group discussions were conducted before and after S&C implementation (respectively, in February 2022 and December 2023). Blackflies were known to emerge from the river areas and cause disease. To prevent blackfly bites, the population often covered their body with protective clothing and applied various substances (kerosene, oil, or lemon) to their skin. Post-intervention data showed reduced blackfly nuisance, and the willingness to sustain blackfly control in the long-term was unanimous among community leaders and members, including the village volunteers who implemented the S&C intervention. In conclusion, blackfly nuisance is evident in the Ntui onchocerciasis focus of Cameroon and led to a panoply of coping practices, some of which could be detrimental to their health. Implementing S&C for blackfly control is well accepted and could sustainably alleviate the nuisance caused by blackflies while simultaneously breaking the onchocerciasis transmission cycle.
The Basic Requirement of Tight Junction Proteins in Blood-Brain Barrier Function and Their Role in Pathologies
Authors: Dithmer Sophie , Blasig Ingolf E. , Fraser Paul A. , Qin Zhihai , Haseloff Reiner F.
Published: May 2024

This review addresses the role of tight junction proteins at the blood-brain barrier (BBB). Their expression is described, and their role in physiological and pathological processes at the BBB is discussed. Based on this, new approaches are depicted for paracellular drug delivery and diagnostics in the treatment of cerebral diseases. Recent data provide convincing evidence that, in addition to its impairment in the course of diseases, the BBB could be involved in the aetiology of CNS disorders. Further progress will be expected based on new insights in tight junction protein structure and in their involvement in signalling pathways.
A Novel Minimally Invasive Surgically Induced Skeletal Muscle Injury Model in Sheep
Authors: Vidal Laura , Vila Ingrid , Venegas Vanesa , Sacristán Anabel , Contreras-Muñoz Paola , Lopez-Garzon Maria , Giné Carles , Rodas Gil , Marotta Mario
Published: May 2024

Sports-related muscle injuries account for 10–55% of all injuries, which is a growing concern, especially given the aging world population. To evaluate the process of skeletal muscle injury and compare it with muscle lesions observed in humans, we developed a novel in vivo model in sheep. In this model, muscle injury was induced by an ultrasound-guided transverse biopsy at the myotendinous junction of the medial gastrocnemius muscle. Twelve male sheep were examined at 3, 7, 14, and 28 days post-injury. Histological, immunofluorescence, and MRI analyses indicate that our sheep model could resemble key human clinicopathological features. Statistically significant differences (p < 0.05) were observed in collagen I, dMHC, α-SMA, and CD68 immunohistochemical detection when comparing injured and healthy muscles. The injured gastrocnemius muscle exhibited elevated levels of type I collagen, infiltration of CD68(+) macrophages, angiogenesis, and the emergence of newly regenerated dMHC(+) myofibers, which persisted for up to 4 weeks post-injury. Similarly, the progression of muscle injury in the sheep model was assessed using advanced clinical 3 T MRI and compared with MRI scans from human patients. The data indicate that the sheep muscle injury model presents features similar to those observed in human skeletal muscle injuries. This makes it a valuable large animal model for studying muscle injuries and developing novel therapeutic strategies.
Development of a Sampling and Storage Protocol of Extracellular Vesicles (EVs)—Establishment of the First EV Biobank for Polytraumatized Patients
Authors: Weber Birte , Ritter Aileen , Han Jiaoyan , Schaible Inna , Sturm Ramona , Relja Borna , Huber-Lang Markus , Hildebrand Frank , Pallas Christiane , Widera Marek , Henrich Dirk , Marzi Ingo , Leppik Liudmila
Published: May 2024

In the last few years, several studies have emphasized the existence of injury-specific EV “barcodes” that could have significant importance for the precise diagnosis of different organ injuries in polytrauma patients. To expand the research potential of the NTF (network trauma research) biobank of polytraumatized patients, the NTF research group decided to further establish a biobank for EVs. However, until now, the protocols for the isolation, characterization, and storage of EVs for biobank purposes have not been conceptualized. Plasma and serum samples from healthy volunteers (n = 10) were used. Three EV isolation methods of high relevance for the work with patients’ samples (ultracentrifugation, size exclusion chromatography, and immune magnetic bead-based isolation) were compared. EVs were quantified using nanoparticle tracking analysis, EV proteins, and miRNAs. The effects of different isolation solutions; the long storage of samples (up to 3 years); and the sensibility of EVs to serial freezing–thawing cycles and different storage conditions (RT, 4/−20/−80 °C, dry ice) were evaluated. The SEC isolation method was considered the most suitable for EV biobanking. We did not find any difference in the quantity of EVs between serum and plasma-EVs. The importance of particle-free PBS as an isolation solution was confirmed. Plasma that has been frozen for a long time can also be used as a source of EVs. Serial freezing–thawing cycles were found to affect the mean size of EVs but not their amount. The storage of EV samples for 5 days on dry ice significantly reduced the EV protein concentration.
A Causal Regulation Modeling Algorithm for Temporal Events with Application to Escherichia coli’s Aerobic to Anaerobic Transition
Authors: Chen Yigang , Mao Runbo , Xu Jiatong , Huang Yixian , Xu Jingyi , Cui Shidong , Zhu Zihao , Ji Xiang , Huang Shenghan , Huang Yanzhe , Huang Hsi-Yuan , Yen Shih-Chung , Lin Yang-Chi-Duang , Huang Hsien-Da
Published: May 2024

Time-series experiments are crucial for understanding the transient and dynamic nature of biological phenomena. These experiments, leveraging advanced classification and clustering algorithms, allow for a deep dive into the cellular processes. However, while these approaches effectively identify patterns and trends within data, they often need to improve in elucidating the causal mechanisms behind these changes. Building on this foundation, our study introduces a novel algorithm for temporal causal signaling modeling, integrating established knowledge networks with sequential gene expression data to elucidate signal transduction pathways over time. Focusing on Escherichia coli’s (E. coli) aerobic to anaerobic transition (AAT), this research marks a significant leap in understanding the organism’s metabolic shifts. By applying our algorithm to a comprehensive E. coli regulatory network and a time-series microarray dataset, we constructed the cross-time point core signaling and regulatory processes of E. coli’s AAT. Through gene expression analysis, we validated the primary regulatory interactions governing this process. We identified a novel regulatory scheme wherein environmentally responsive genes, soxR and oxyR, activate fur, modulating the nitrogen metabolism regulators fnr and nac. This regulatory cascade controls the stress regulators ompR and lrhA, ultimately affecting the cell motility gene flhD, unveiling a novel regulatory axis that elucidates the complex regulatory dynamics during the AAT process. Our approach, merging empirical data with prior knowledge, represents a significant advance in modeling cellular signaling processes, offering a deeper understanding of microbial physiology and its applications in biotechnology.
Liriodenine and Its Probable Role as an Osmolyte during Water Stress in Annona lutescens (Annonaceae)
Authors: Cisneros-Andrés Alfredo , Cruz-Ortega Rocío , Castro-Moreno Marisol , González-Esquinca Alma Rosa
Published: May 2024

In tropical deciduous forests (TDFs), plants have developed various strategies to tolerate desiccation during the dry season. One strategy is osmotic adjustment, which includes the accumulation of secondary metabolites. Annona lutescens, a species that inhabits TDFs, increases and accumulates liriodenine alkaloid in its roots during the dry season. In this study, we evaluate the possible role of this molecule as an osmolyte and in pH homeostasis. We performed growth analyses and determined liriodenine concentrations during water stress in Annona lutescens seedlings grown under controlled temperature, water, and light conditions. We also calculated their osmotic adjustment based on pressure–volume curves and performed solubility tests along a pH gradient. Osmotic adjustment was compared between control plants (irrigated) and plants subjected to 15, 25, and 35 days of water stress. Osmotic adjustment was dramatically higher in plants subjected to 35 days of water stress compared to the control. The solubility of liriodenine was 54% at pH 4.5, and when liriodenine was in contact with malic acid solutions, the pH increased slightly. The highest concentration of liriodenine was in the roots, with a significant increase from 540.855 μg g−1 after 15 days of water stress to 1239.897 μg g−1 after 35 days. Our results suggest that liriodenine plays an important role in the response to water stress as an osmolyte and in pH homeostasis.
Enhancing Supercapacitor Performance with Zero-Dimensional Tin–Niobium Oxide Heterostructure Composite Spheres: Electrochemical Insights
Authors: Thirumal Vediyappan , Babu Bathula , Rajkumar Palanisamy , Kim Jin-Ho , Yoo Kisoo
Published: May 2024

The development of advanced tin and niobium bimetallic composite electrode materials is crucial for enhancing the performance of supercapacitors. In this paper, we present a novel bimetallic composite material consisting of zero-dimensional spherical-like SnNb2O6 nanocomposites synthesized through the reaction of tin oxide (SnO2) and niobium pentoxide (Nb2O5) precursors, alongside comparative materials. The morphology of the spherical agglomerates comprising Sn/Nb oxide particles that were nucleated on the SnNb2O6 surface was characterized using field emission scanning electron microscopy (FE-SEM) and high-resolution transmission electron microscopy (HR-TEM). The as-prepared heterostructures of the SnNb2O6 composites were analyzed for elemental composition, including Sn3d, Nb3d, and O1s; moreover, chemical oxidative state analysis was performed through X-ray photoelectron spectroscopy (XPS). Additionally, cyclic voltammetry curves exhibited pseudocapacitive redox behavior for the SnNb2O6 composites, while the galvanostatic charge-discharge (GCD) performance demonstrated a maximum specific capacitance of 294.8 F/g at 1 A/g. Moreover, SnNb2O6 composite electrodes demonstrated rapid charge–discharge kinetics and excellent cycling stability, with a capacitance retention of 95.7% over 10,000 cycles. This study elucidated the synthesis of tin–niobium oxide-based composites, demonstrating their potential for high-performance supercapacitors.
Polymer-Based Immobilized FePMo12O40@PVP Composite Materials for Photocatalytic RhB Degradation
Authors: Wang Zijing , Tang Yuze , Ai Limei , Liu Minghui , Wang Yurong
Published: May 2024

FePMo12O40@PVP composite materials were synthesized with the regulation of polyvinylpyrrolidone (PVP) to control the structure. The samples were characterized by FT-IR, XRD, XPS, SEM, TEM and UV-Vis DRS. The composite retains the Keggin-type polyoxometalates structure, exhibiting a high specific surface area that enhances photon capture efficiency. Analysis of UV-Vis DRS absorption band edge and band gap indicated that the composite was responsive to visible light. Photocatalytic degradation of Rhodamine B (RhB) by FePMo12O40@PVP was investigated under commonly used LED light source, demonstrating excellent photocatalytic performance as 2.5 g-FePMo12O40@PVP (0.015 g) can remove 83% of RhB (10 mg/L) in 40 min. The FePMo12O40@PVP composite material demonstrated sustained moderate degradation efficiency even after undergoing three cycles of repeated use. The non-covalent interaction and strong interfacial coupling between PVP and FePMo12O40 promoted the transfer of h+, and e−, ∙O2−, ·OH, and h+ served as the primary active species in this photocatalytic system. This environmentally friendly material has the potential to significantly reduce energy consumption and offers valuable insights for the future treatment of dye wastewater.
The Right Coronary Anatomy and Operative Topography of the Tricuspid Valve Annulus
Authors: Piotrowski Michał , Burysz Marian , Batko Jakub , Litwinowicz Radosław , Kowalewski Mariusz , Bartuś Krzysztof , Wróbel Krzysztof , Graczykowski Łukasz , Słomka Artur
Published: May 2024

Background: The region of the tricuspid valve is an important area for various cardiac interventions. In particular, the spatial relationships between the right coronary artery and the annulus of the tricuspid valve should be considered during surgical interventions. The aim of this study was to provide an accurate description of the clinical anatomy and topography of this region. Methods: We analyzed 107 computed tomography scans (44% female, age 62.1 ± 9.4 years) of the tricuspid valve region. The circumference of the free wall of the tricuspid valve annulus was divided into 13 annular points and measurements were taken at each point. The prevalence of danger zones (distance between artery and annulus less than 2 mm) was also investigated. Results: Danger zones were found in 20.56% of the cases studied. The highest prevalence of danger zones and the smallest distances were found at the annular points of the tricuspid valve located at the posterior insertion of the leaflets, without observed sex-specific differences. Conclusion: The highest risk of iatrogenic damage to the right coronary artery is in the posterior part of the tricuspid valve annulus.
Percutaneous Coronary Interventions with Sirolimus-Eluting Alex Plus Stents in Patients with or without Diabetes: 4-Year Results
Authors: Bil Jacek , Tyczynski Maciej , Kern Adam , Bojko Krystian , Gil Robert J.
Published: May 2024

We characterized the performance, as well as the safety, of a second-generation thin-strut sirolimus-eluting stent with a biodegradable polymer, Alex Plus (Balton, Poland), implanted in patients with type 2 diabetes (DM) with a 4-year follow-up. We defined the primary endpoint as the 48-month rate of major cardiovascular adverse events (MACE), including cardiac death, myocardial infarction (MI), or target lesion revascularization (TLR). The secondary endpoints were all-cause death, cardiac death, MI, and TLR rates at 12, 24, 36, and 48 months. We enrolled 232 patients in whom 282 stents were implanted, including 97 DM and 135 non-DM patients. The mean age of the DM patients was 69.5 ± 10.1 years and females accounted for 30% of the patients. DM patients had higher rates of arterial hypertension (97% vs. 88%, p = 0.016), dyslipidemia (86% vs. 70%, p = 0.005), prior MI (61% vs. 40%, p = 0.002), prior PCI (65% vs. 50%, p = 0.020), and prior CABG (14% vs. 5.9%, p = 0.029). We recorded statistically significant differences for MACE (HR 1.85, 95% CI 1.01–3.41, p = 0.046), cardiac death (HR 4.46, 95% CI 1.44–13.8, p = 0.010), and MI (HR 3.17, 95% CI 1.10–9.12, p = 0.033), but not for TLR, between DM and non-DM patients in terms of the analyzed endpoints at 4 years. Our study showed that Alex Plus was efficient and safe in a contemporary cohort of real-world DM patients undergoing percutaneous revascularization.
Comparison of Greater Occipital Nerve Blockade and Sphenopalatine Ganglion Blockade in Patients with Episodic Migraine
Authors: Unal Hanzade Aybuke , Basarı Ahmet , Celiker Opal Sezgi , Cakar Turhan Keziban Sanem , Asik Ibrahim , Ozgencil Gungor Enver
Published: May 2024

Objectives: Compare the effects of greater occipital nerve (GON) and sphenopalatine ganglion (SPG) blocks on headache intensity and duration, number of headache days, and disability in patients with episodic migraine. Methods: In this prospective single-blind randomized study, patients with episodic migraine were randomly divided into two groups: GON and SPG block groups. Patients received blocks once a week for 4 weeks, and once a month for 2 months. The number of headache days, the headache duration, numeric rating scale (NRS) scores, and number of acute medical treatments were assessed before the procedures and 1 month, 2 months, and 3 months after the procedures. Disability was evaluated using the migraine disability assessment (MIDAS) questionnaire at baseline and 3 months after treatment. This study protocol is registered at ClinicalTrials.gov (NCT06243874.). Results: 19 patients in the GON block group and 18 patients in the SPG block group were evaluated. Significant improvements in pain severity, headache duration, number of headache days, and the need for acute medical treatment were observed in the 1st, 2nd, and 3rd months compared to baseline in the two groups (p < 0.001). There were significant improvements in the MIDAS scores in the third month (p < 0.001). The GON block group showed a greater reduction in headache intensity, duration, number of headache days, and MIDAS scores compared to the SPG block group in the 3rd month (p < 0.001). Conclusions: GON block reduces headache duration, intensity, the number of headache days, and the need for acute medical treatment much more than SPG block in patients with episodic migraine.
Good Manufacturing Practice-Compliant Cryopreserved and Thawed Native Adipose Tissue Ready for Fat Grafting
Authors: Rusconi Giulio , Cremona Martina , Gallazzi Matteo , Mariotta Luca , Gola Mauro , Gandolfi Eugenio , Malacco Matteo , Soldati Gianni
Published: May 2024

Background: As adipose tissue-derived mesenchymal stem cells are becoming the tool of choice for many clinical applications; standardized cryopreservation protocols are necessary to deliver high-quality samples. For this purpose, the cryopreservation and thawing of native adipose tissue under GMP conditions could represent an extremely useful and powerful tool for the direct reinfusion of the tissue, and consequently, of its stromal vascular fraction. Methods: In this study, 19 samples of adipose tissue were cryopreserved and characterized before and after storage in liquid nitrogen vapors. Of these 19 samples, 14 were processed in research and 5 in a GMP-compliant environment. Storage with and without cryopreservation medium was also evaluated. After one week to three months of storage, samples were thawed, washed, enzymatically digested, and characterized with flow cytometry. Results: The results show that there is a loss of nearly 50% of total nucleated cells during the cryopreservation/thawing process. Non-GMP and GMP samples are comparable for all parameters analyzed. This study also allowed us to exclude the cryopreservation of adipose tissue without any cryopreservation medium. Conclusions: The data shown in this work are consistent with the idea that native adipose tissue, if properly processed and controlled, could be a useful source of cells for regenerative medicine, keeping in mind that there is a clear difference in the quality between fresh and thawed samples.
Greater Risk of Periprosthetic Joint Infection Associated with Prolonged Operative Time in Primary Total Knee Arthroplasty: Meta-Analysis of 427,361 Patients
Authors: Shin Kyun-Ho , Kim Jin-Ho , Han Seung-Beom
Published: May 2024

Background/Objectives: Periprosthetic joint infection (PJI) is a severe complication in total knee arthroplasty (TKA) with catastrophic outcomes. The relationship between prolonged operative times and PJI remains debated. This meta-analysis investigated the link between prolonged operative times and the risk of PJI in primary TKA. Methods: A comprehensive search of the MEDLINE/PubMed, Cochrane Library, and EMBASE databases was conducted to identify studies comparing the incidence of PJI in TKAs with prolonged versus short operative times, as well as those comparing operative times in TKAs with and without PJI. Pooled standardized mean differences (SMD) in operative times between groups with and without PJI or surgical site infections (SSI), including superficial SSIs and PJIs, were analyzed. Additionally, the pooled odds ratios (OR) for PJI in TKAs with operative times exceeding 90 or 120 min were examined. Results: Seventeen studies involving 427,361 patients were included. Significant differences in pooled mean operative times between the infected and non-infected TKA groups were observed (PJI, pooled SMD = 0.38, p < 0.01; SSI, pooled SMD = 0.72, p < 0.01). A higher risk of PJI was noted in surgeries lasting over 90 or 120 min compared to those of shorter duration (90 min, pooled OR = 1.50, p < 0.01; 120 min, pooled OR = 1.56, p < 0.01). Conclusions: An association between prolonged operative time and increased risk of PJI in primary TKA has been established. Strategies for infection prevention should encompass thorough preoperative planning aimed at minimizing factors that contribute to prolonged operative times.
MResTNet: A Multi-Resolution Transformer Framework with CNN Extensions for Semantic Segmentation
Authors: Detsikas Nikolaos , Mitianoudis Nikolaos , Pratikakis Ioannis
Published: May 2024

A fundamental task in computer vision is the process of differentiation and identification of different objects or entities in a visual scene using semantic segmentation methods. The advancement of transformer networks has surpassed traditional convolutional neural network (CNN) architectures in terms of segmentation performance. The continuous pursuit of optimal performance, with respect to the popular evaluation metric results, has led to very large architectures that require a significant amount of computational power to operate, making them prohibitive for real-time applications, including autonomous driving. In this paper, we propose a model that leverages a visual transformer encoder with a parallel twin decoder, consisting of a visual transformer decoder and a CNN decoder with multi-resolution connections working in parallel. The two decoders are merged with the aid of two trainable CNN blocks, the fuser that combined the information from the two decoders and the scaler that scales the contribution of each decoder. The proposed model achieves state-of-the-art performance on the Cityscapes and ADE20K datasets, maintaining a low-complexity network that can be used in real-time applications.
A Shape-Aware Network for Arctic Lead Detection from Sentinel-1 SAR Images
Authors: Song Wei , Zhu Min , Ge Mengying , Liu Bin
Published: May 2024

Accurate detection of sea ice leads is essential for safe navigation in polar regions. In this paper, a shape-aware (SA) network, SA-DeepLabv3+, is proposed for automatic lead detection from synthetic aperture radar (SAR) images. Considering the fact that training data are limited in the task of lead detection, we construct a dataset fusing dual-polarized (HH, HV) SAR images from the C-band Sentinel-1 satellite. Taking the DeepLabv3+ as the baseline network, we introduce a shape-aware module (SAM) to combine multi-scale semantic features and shape information and, therefore, better capture the shape characteristics of leads. A squeeze-and-excitation channel-position attention module (SECPAM) is designed to enhance lead feature extraction. Segmentation loss generated by the segmentation network and shape loss generated by the shape-aware stream are combined to optimize the network during training. Postprocessing is performed to filter out segmentation errors based on the aspect ratio of leads. Experimental results show that the proposed method outperforms the existing benchmarking deep learning methods, reaching 96.82% for overall accuracy, 93.01% for F1-score, and 91.48% for mIoU. It is also found that the fusion of dual-polarimetric SAR channels as the input could effectively improve the accuracy of sea ice lead detection.
Research on the Ignition Strategy of Diesel Direct Injection Combined with Jet Flame on the Combustion Character of Natural Gas in a Dual-Fuel Marine Engine
Authors: Liu Long , Liu Shihai , Liu Dai
Published: May 2024

In large-bore two-stroke diesel/nature gas dual-fuel marine engines, a certain quantity of diesel is injected into the cylinder to satisfy the full-power output engine rated power of the gas mixture. However, the ignition and flame propagation process based on the injection strategy of diesel direct injection combined with diesel jet flame on the ignition and combustion of natural gas is unclear, which directly affects the power and the thermal efficiency of engine and emissions. Therefore, this work numerically investigates the flame propagation characteristic under the strategy of the main and pilot diesel modes. The influence of the injection timing and proportion of diesel on combustion and emission performance are further analyzed. The results show that the influence of the injection timing of main diesel (MDIT) on the combustion process and emission performance is more obvious than that of the injection timing of pilot diesel (PDIT). The results indicate that the MDIT increased from −2°CA to −8°CA, the power increased by 316 kW, and the thermal efficiency improved by 1.5%. However, the CO2 emissions increased by 10.5 g/kWh, and the NOx emissions increased by 0.7 g/kWh. Additionally, an early PDIT is not conducive to the rapid organization of combustion, resulting in decreased engine power and thermal efficiency. Furthermore, it was found that the power improved by 50 kW and the thermal efficiency improved by 0.6%, with a decrease in the main diesel ratio (MDR) from 100% to 90%. Meanwhile, the CO2 emissions decreased by 4 g/kWh, although there was no obvious change in NOx emissions with the advance of MDR.
A Computation Model for Coast Wave Motions with Multiple Breakings
Authors: Bian Hongwei , Zou Zhili , Yan Sheng
Published: May 2024

This paper presents a computational model for coast wave motions with multiple wave breakings. In the Boussinesq model, the wave breaking judgment method is combined with the wave recovery judgment condition, which stops the wave breaking process when triggered. The energy dissipation of wave breaking is corrected, and the dissipation of wave energy is maintained at about 10% during the wave recovery stage, so that the dissipation caused by the residual turbulent motion of wave breaking and the increase in wave height caused by the shallowing of waves due to the water bottom slope are offset. By comparing the calculation results with the experimental results, it is proved that this model can be used to calculate multiple wave breakings. This model is applied to discuss the influence of wave incident angle and wave period on wave height and longshore current and gives the distribution characteristics of wave height and longshore current under multiple wave breakings.
Improvement of Container Dynamic Allocation for Automated Container Terminals in the Post-Epidemic Era
Authors: Wang Yu , He Junliang , Zhang Leijie , Yan Wei
Published: May 2024

The significant congestion during the COVID-19 epidemic has prompted terminal managers to prioritize efforts to enhance daily operational efficiency in the post-epidemic era. In direct response to these priorities, this study develops a dynamic stack-based yard space allocation model tailored to optimize daily yard space allocation in automated container terminals. The model is based on a predeveloped yard template and considers the influence of shipping schedule fluctuations. Its primary objectives are to minimize truck movements and achieve a balanced block distribution, thereby providing theoretical support for real-time container drop-off during terminal shipping schedule fluctuations and dynamic variations in container operation flow. Through extensive experimentation, this study analyzes multiple scenarios in real automated terminal yard space management. The findings indicate that, because of bay space expansion and operational process changes, the allocation of automated terminal yard space is better suited to the stack-based processing mode. In the stack-based mode, the higher operational efficiency of automated rail-mounted gantries can help terminals achieve better dynamic allocation balances with lower energy consumption.
Effects of Orange Peel Extract on Laccase Activity and Gene Expression in Trametes versicolor
Authors: Vandelook Simon , Bassleer Berend , Elsacker Elise , Peeters Eveline
Published: May 2024

The genome of Trametes versicolor encodes multiple laccase isozymes, the expression of which is responsive to various conditions. Here, we set out to investigate the potential of orange peel extract as an inducer of laccase production in this white-rot fungus, in comparison to the previously identified inducing chemical compound, veratryl alcohol. For four geographically distinct T. versicolor strains, a positive correlation has been observed between their oxidative activity and incubation time in liquid cultures. The addition of 20% orange peel extract or 5 mM veratryl alcohol caused a rapid increase in the oxidative potential of T. versicolor M99 after 24 h, with a more pronounced effect observed for the orange peel extract. To elucidate the underlying molecular mechanisms of the induced laccase activity, a transcriptional gene expression analysis was performed for the seven individual laccase genes in T. versicolor, revealing the upregulation of several laccase genes in response to the addition of each inducer. Notably, the gene encoding TvLac5 demonstrated a substantial upregulation in response to the addition of 20% orange peel extract, likely contributing to the observed increase in its oxidative potential. In conclusion, our results demonstrate that orange peels are a promising agro-industrial side stream for implementation as inducing agents in large-scale laccase production with T. versicolor.
Effects of Light on the Fruiting Body Color and Differentially Expressed Genes in Flammulina velutipes
Authors: Im Ji-Hoon , Park Che-Hwon , Shin Ju-Hyeon , Oh Youn-Lee , Oh Minji , Paek Nam-Chon , Park Young-Jin
Published: May 2024

Light plays vital roles in fungal growth, development, reproduction, and pigmentation. In Flammulina velutipes, the color of the fruiting body exhibits distinct changes in response to light; however, the underlying molecular mechanisms remain unknown. Therefore, in this study, we aimed to analyze the F. velutipes transcriptome under red, green, and blue light-emitting diode (LED) lights to identify the key genes affecting the light response and fruiting body color in this fungus. Additionally, we conducted protein–protein interaction (PPI) network analysis of the previously reported fruiting body color-related gene, Fvpal1, to identify the hub genes. Phenotypic analysis revealed that fruiting bodies exposed to green and blue lights were darker than those untreated or exposed to red light, with the color intensifying more after 48 h of exposure to blue light compared to that after 24 h of exposure. Differentially expressed gene (DEG) analyses of all light treatments for 24 h revealed that the numbers of DEGs were 17, 74, and 257 under red, green, and blue lights, respectively. Subsequently, functional enrichment analysis was conducted of the DEGs identified under green and blue lights, which influenced the color of F. velutipes. In total, 103 of 168 downregulated DEGs under blue and green lights were included in the enrichment analysis. Among the DEGs enriched under both green and blue light treatments, four genes were related to monooxygenases, with three genes annotated as cytochrome P450s that are crucial for various metabolic processes in fungi. PPI network analysis of Fvpal1 revealed associations with 11 genes, among which the expression of one gene, pyridoxal-dependent decarboxylase, was upregulated in F. velutipes exposed to blue light. These findings contribute to our understanding of the molecular mechanisms involved in the fruiting body color changes in response to light and offer potential molecular markers for further exploration of light-mediated regulatory pathways.
Empowering Self-Help Groups: The Impact of Financial Inclusion on Social Well-Being
Authors: Survase Madan , Gohil Atmajitsinh
Published: May 2024

Financial inclusion (FI) relates to the access and availability of financial services to society, especially in low-income groups. FI is pivotal in achieving 7 of the 17 Sustainable Development Goals (SDGs). This paper explores the level of FI in the rural areas of Maharashtra and measures the impact of FI on the social conditions of Self-Help Groups (SHGs) prevalent in these areas. The study is based on a 424 SHGs survey conducted in the Pune, Thane, and Palghar districts of Maharashtra, India. The impact of FI on SHGs is evaluated using a Structural Equation Model (SEM). The results of the study show that physical banking services, Business Facilitators (BFs), and Business Correspondents (BCs) improve the social conditions of rural SHGs. Additionally, BCs and BFs mediate the relationship between physical banking services and social conditions. The study also reveals an insignificant association between BCs and BFs and insurance services. The present study highlights the importance of increasing the awareness of insurance policies through financial literacy programs and making timely availability and accessibility of BCs and BFs to enhance financial inclusion in rural areas.
Effect of Steel Slag on the Properties of Alkali-Activated Slag Material: A Comparative Study with Fly Ash
Authors: Han Fanghui , Zhu Ziqin , Zhang Hongbo , Li Yuchen , Fu Ting
Published: May 2024

Slag and fly ash (FA) are mostly used as precursors for the production of alkali-activated materials (AAMs). FA is the waste discharged by power plants, while slag and steel slag (SS) both belong to the iron and steel industry. The effects of SS and FA on the strength, microstructure, and volume stability of alkali-activated slag (AAS) materials with different water glass modulus (Ms) values were comparatively investigated. The results show that adding SS or FA decreases the compressive strength of AAS mortar, and the reduction effect of SS is more obvious at high Ms. SS or FA reduce the non-evaporable water content (Wn) of AAS paste. However, SS increases the long-term Wn of AAS paste at low Ms. The cumulative pore volume and porosity increase after adding SS or FA, especially after adding FA. The hydration products are mainly reticular C-(A)-S-H gels. Adding SS increases the Ca/Si ratio of C-(A)-S-H gel but decreases the Al/Si ratio. However, by mixing FA, the Ca/Si ratio is reduced and the Al/Si ratio is almost unchanged. The incorporation of SS or FA reduces the drying shrinkage of AAS mortar, especially when SS is added. Increasing Ms increases the compressive strength and improves the pore structure, and it significantly increases the drying shrinkage of all samples. This study provides theoretical guidance for the application of steel slag in the alkali-activated slag material.
Predicting Machine Failures from Multivariate Time Series: An Industrial Case Study
Authors: Pinciroli Vago Nicolò Oreste , Forbicini Francesca , Fraternali Piero
Published: May 2024

Non-neural machine learning (ML) and deep learning (DL) are used to predict system failures in industrial maintenance. However, only a few studies have assessed the effect of varying the amount of past data used to make a prediction and the extension in the future of the forecast. This study evaluates the impact of the size of the reading window and of the prediction window on the performances of models trained to forecast failures in three datasets of (1) an industrial wrapping machine working in discrete sessions, (2) an industrial blood refrigerator working continuously, and (3) a nitrogen generator working continuously. A binary classification task assigns the positive label to the prediction window based on the probability of a failure to occur in such an interval. Six algorithms (logistic regression, random forest, support vector machine, LSTM, ConvLSTM, and Transformers) are compared on multivariate time series. The dimension of the prediction windows plays a crucial role and the results highlight the effectiveness of DL approaches in classifying data with diverse time-dependent patterns preceding a failure and the effectiveness of ML approaches in classifying similar and repetitive patterns preceding a failure.
RBF-Assisted Hybrid Neural Network for Solving Partial Differential Equations
Authors: Li Ying , Gao Wei , Ying Shihui
Published: May 2024

In scientific computing, neural networks have been widely used to solve partial differential equations (PDEs). In this paper, we propose a novel RBF-assisted hybrid neural network for approximating solutions to PDEs. Inspired by the tendency of physics-informed neural networks (PINNs) to become local approximations after training, the proposed method utilizes a radial basis function (RBF) to provide the normalization and localization properties to the input data. The objective of this strategy is to assist the network in solving PDEs more effectively. During the RBF-assisted processing part, the method selects the center points and collocation points separately to effectively manage data size and computational complexity. Subsequently, the RBF processed data are put into the network for predicting the solutions to PDEs. Finally, a series of experiments are conducted to evaluate the novel method. The numerical results confirm that the proposed method can accelerate the convergence speed of the loss function and improve predictive accuracy.
R-DDQN: Optimizing Algorithmic Trading Strategies Using a Reward Network in a Double DQN
Authors: Zhou Chujin , Huang Yuling , Cui Kai , Lu Xiaoping
Published: May 2024

Algorithmic trading is playing an increasingly important role in the financial market, achieving more efficient trading strategies by replacing human decision-making. Among numerous trading algorithms, deep reinforcement learning is gradually replacing traditional high-frequency trading strategies and has become a mainstream research direction in the field of algorithmic trading. This paper introduces a novel approach that leverages reinforcement learning with human feedback (RLHF) within the double DQN algorithm. Traditional reward functions in algorithmic trading heavily rely on expert knowledge, posing challenges in their design and implementation. To tackle this, the reward-driven double DQN (R-DDQN) algorithm is proposed, integrating human feedback via a reward function network trained on expert demonstrations. Additionally, a classification-based training method is employed for optimizing the reward function network. The experiments, conducted on datasets including HSI, IXIC, SP500, GOOGL, MSFT, and INTC, show that the proposed method outperforms all baselines across six datasets and achieves a maximum cumulative return of 1502% within 24 months.
Optimizing Subtalar Arthrodesis: A Human Cadaveric Evaluation of a Novel Partially-Threaded Screw Combination in the Delta Configuration
Authors: Raykov Georgi , Ivanov Stoyan , Gueorguiev Boyko , Pastor Tatjana , Berk Till , Pastor Torsten , Zderic Ivan
Published: May 2024

Background and Objectives: Despite the established role of subtalar joint arthrodesis (SJA) for treatment of subtalar osteoarthritis, achieving bone union remains challenging, with up to 46% non-union rates. Adequate compression and stable fixation are crucial for successful outcomes, with internal screw fixation being the gold standard for SJA. The delta configuration, featuring highly divergent screws, offers stability, however, it can result in hardware irritation in 20–30% of patients. Solutions to solve this complication include cannulated compression screw (CCS) countersinking or cannulated compression headless screw (CCHS) application. The aim of this biomechanical study was to investigate the stability of a delta configuration for SJA utilizing either a combination of a posterior CCHS and an anterior CCS or a standard two-CCS combination. Materials and Methods: Twelve paired human cadaveric lower legs were assigned pairwise to two groups for SJA using either two CCSs (Group 1) or one posterior CCHS and one anterior CCS (Group 2). All specimens were tested under progressively increasing cyclic loading to failure, with monitoring of the talocalcaneal movements via motion tracking. Results: Initial stiffness did not differ significantly between the groups, p = 0.949. Talocalcaneal movements in terms of varus–valgus deformation and internal–external rotation were significantly bigger in Group 1 versus Group 2, p ≤ 0.026. Number of cycles until reaching 5° varus–valgus deformation was significantly higher in Group 2 versus Group 1, p = 0.029. Conclusions: A delta-configuration SJA utilizing a posterior CCHS and an anterior CCS is biomechanically superior versus a standard configuration with two CCSs. Clinically, the use of a posterior CCHS could prevent protrusion of the hardware in the heel, while an anterior CCS could facilitate less surgical time and thus less complication rates.
Prospects and Challenges in Developing mRNA Vaccines for Infectious Diseases and Oncogenic Viruses
Authors: Kutikuppala Lakshmi Venkata Simhachalam , Kourampi Islam , Kanagala Ramya S. D. , Bhattacharjee Priyadarshini , Boppana Sri Harsha
Published: May 2024

mRNA vaccines have emerged as an optimistic technological platform for vaccine innovation in this new scientific era. mRNA vaccines have dramatically altered the domain of vaccinology by offering a versatile and rapid approach to combating infectious diseases and virus-induced cancers. Clinical trials have demonstrated efficacy rates of 94–95% in preventing COVID-19, and mRNA vaccines have been increasingly recognized as a powerful vaccine platform. Although mRNA vaccines have played an essential role in the COVID-19 pandemic, they still have several limitations; their instability and degradation affect their storage, delivery, and over-all efficiency. mRNA is typically enclosed in a transport mechanism to facilitate its entry into the target cell because it is an unstable and negatively charged molecule. For instance, mRNA that is given using lipid-nanoparticle-based vaccine delivery systems (LNPs) solely enters cells through endocytosis, establishing an endosome without damaging the cell membrane. The COVID-19 pandemic has accelerated the development of mRNA vaccine platforms used to treat and prevent several infectious diseases. This technology has the potential to change the future course of the disease by providing a safe and effective way to combat infectious diseases and cancer. A single-stranded genetic sequence found in mRNA vaccines instructs host cells to produce proteins inside ribosomes to elicit immunological responses and prepare the immune system to fight infections or cancer cells. The potential applications of mRNA vaccine technology are vast and can lead to the development of a preferred vaccine pattern. As a result, a new generation of vaccinations has gradually gained popularity and access to the general population. To adapt the design of an antigen, and even combine sequences from different variations in response to new changes in the viral genome, mRNA vaccines may be used. Current mRNA vaccines provide adequate safety and protection, but the duration of that protection can only be determined if further clinical research is conducted.
Metabolomics Profiling of Stages of Coronary Artery Disease Progression
Authors: Anlar Gulsen Guliz , Anwardeen Najeha , Al Ashmar Sarah , Pedersen Shona , Elrayess Mohamed A. , Zeidan Asad
Published: May 2024

Coronary artery disease (CAD) and atherosclerosis pose significant global health challenges, with intricate molecular changes influencing disease progression. Hypercholesterolemia (HC), hypertension (HT), and diabetes are key contributors to CAD development. Metabolomics, with its comprehensive analysis of metabolites, offers a unique perspective on cardiovascular diseases. This study leveraged metabolomics profiling to investigate the progression of CAD, focusing on the interplay of hypercholesterolemia, hypertension, and diabetes. We performed a metabolomic analysis on 221 participants from four different groups: (I) healthy individuals, (II) individuals with hypercholesterolemia (HC), (III) individuals with both HC and hypertension (HT) or diabetes, and (IV) patients with self-reported coronary artery disease (CAD). Utilizing data from the Qatar Biobank, we combined clinical information, metabolomic profiling, and statistical analyses to identify key metabolites associated with CAD risk. Our data identified distinct metabolite profiles across the study groups, indicating changes in carbohydrate and lipid metabolism linked to CAD risk. Specifically, levels of mannitol/sorbitol, mannose, glucose, and ribitol increased, while pregnenediol sulfate, oleoylcarnitine, and quinolinate decreased with higher CAD risk. These findings suggest a significant role of sugar, steroid, and fatty acid metabolism in CAD progression and point to the need for further research on the correlation between quinolinate levels and CAD risk, potentially guiding targeted treatments for atherosclerosis. This study provides novel insights into the metabolomic changes associated with CAD progression, emphasizing the potential of metabolites as predictive biomarkers.