bluuebunny/crossref_metadata_2025 huggingface dataset:
Exposing Data Leakage in Wi-Fi CSI-Based Human Action Recognition: A Critical Analysis
Authors: Varga Domonkos
Published: August 2024

Wi-Fi channel state information (CSI)-based human action recognition systems have garnered significant interest for their non-intrusive monitoring capabilities. However, the integrity of these systems can be compromised by data leakage, particularly when improper dataset partitioning strategies are employed. This paper investigates the presence and impact of data leakage in three published Wi-Fi CSI-based human action recognition methods that utilize deep learning techniques. The original studies achieve precision rates of 95% or higher, attributed to the lack of human-based dataset splitting. By re-evaluating these systems with proper subject-based partitioning, our analysis reveals a substantial decline in performance, underscoring the prevalence of data leakage. This study highlights the critical need for rigorous dataset management and evaluation protocols to ensure the development of robust and reliable human action recognition systems. Our findings advocate for standardized practices in dataset partitioning to mitigate data leakage and enhance the generalizability of Wi-Fi CSI-based models.
The Trends in Atrial Fibrillation-Related Mortality before, during, and after the COVID-19 Pandemic Peak in the United States
Authors: Dimri Inon , Roguin Ariel , Hamuda Nashed , Abu Fanne Rami , Barel Maguli , Leshem Eran , Kobo Ofer , Margolis Gilad
Published: August 2024

Background: During the first months of the COVID-19 outbreak, an increase was observed in atrial fibrillation (AF)-related mortality in the United States (U.S). We aimed to investigate AF-related mortality trends in the U.S. before, during, and after the COVID-19 pandemic peak, stratified by sociodemographic factors. Methods: using the Wide-Ranging Online Data for Epidemiologic Research database of the Centers for Disease Control and Prevention, we compared the AF-related age-adjusted mortality rate (AAMR) among different subgroups in the two years preceding, during, and following the pandemic peak (2018–2019, 2020–2021, 2022–2023). Result: By analyzing a total of 1,267,758 AF-related death cases, a significant increase of 24.8% was observed in AF-related mortality during the pandemic outbreak, followed by a modest significant decrease of 1.4% during the decline phase of the pandemic. The most prominent increase in AF-related mortality was observed among males, among individuals younger than 65 years, and among individuals of African American and Hispanic descent, while males, African American individuals, and multiracial individuals experienced a non-statistically significant decrease in AF-related mortality during the pandemic decline period. Conclusions: Our findings suggest that in future healthcare crises, targeted healthcare policies and interventions to identify AF, given its impact on patients’ outcomes, should be developed while addressing disparities among different patient populations.
Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios as Predictors of Dysphagia Severity and Quality of Life in Nasopharyngeal Cancer Patients after Intensity Modulated Radiotherapy (IMRT)
Authors: Cocuzza Salvatore , Parisi Federica Maria , Spatola Corrado , La Mantia Ignazio , Lechien Jerome Rene , Chiesa-Estomba Carlos , Ferlito Salvatore , Albanese Gianluca , Lentini Mario , Mayo-Yanez Miguel , Fakhry Nicolas , La Rocca Madalina , Maniaci Antonino
Published: August 2024

Background: Patients treated with definitive radiotherapy for nasopharyngeal carcinoma (NPC) develop severe dysphagia, affecting their quality of life. Traditional prognosis biomarkers are insufficient, leading to a search for new predictors like neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). Methods: We retrospectively enrolled 44 NPC patients who underwent definitive radiotherapy between 2010 and 2018. EQUATOR and STROBE network guidelines were adopted. Pre-treatment evaluations were conducted, and post-treatment oropharyngeal dysphagia was assessed using the Sydney Swallow Questionnaire (SSQ) and FEES, then assigning a Dysphagia Outcome and Severity Scale (DOSS) level. Patients were divided based on NLR and PLR cut-offs, comparing subjective dysphagia (SSQ) scores and DOSS results at baseline and after a 5-year follow-up. Multiple linear regression was used for analysis. Results: At baseline, the mean NLR was 2.52 ± 1.10, and the PLR was 208.40 ± 94.35. Multivariate analysis indicated NLR and PLR as significant predictors of DOSS outcomes (p < 0.001). Conclusions: Baseline inflammation markers, such as NLR and PLR, may be used to predict dysphagia severity in NPC patients undergoing definitive radiotherapy. These markers could help identify patients at higher risk for severe dysphagia and implement tailored therapeutic and rehabilitative strategies to improve their quality of life. Further studies with larger cohorts are needed to confirm these findings and explore additional prognostic factors for dysphagia outcomes in NPC patients.
Physical Activity and Urinary Sodium Excretion Circadian Rhythm: A Population-Based Cross-Sectional Pilot Study
Authors: Zandonà Martina , Novotny Jakub , Garo Maria Luisa , Sgro Ettore , Del Giorno Rosaria , Gabutti Luca
Published: August 2024

Background/Objectives: Blood pressure (BP) is characterized by a circadian rhythm (Circr) with lower nighttime values, called dipping. Non-dipping is associated with higher CVD risk. The Circr of urinary sodium excretion (NaCle), peaking during the day, is linked to BP patterns. Physical activity (PA) is known to improve BP control and enhance the dipping phenomenon, but its possible effect on NaCle remains unclarified. This study aimed to investigate the correlation between PA and the Circr of NaCle and to determine if the relationship is independent of age, sex, BP values, dipping pattern, and salt intake. Methods: A pilot cross-sectional analysis was conducted using data from the Ticino Epidemiological Stiffness Study, involving 953 participants in Switzerland. Data collection included standardized questionnaires, blood samples, 24 h urine collections, and ambulatory BP monitoring. Participants were categorized into sedentary, partially active, and active. The effect of PA, NaCl intake, and dipping on the day/night NaCle ratio was assessed with multivariable linear regressions. Results: Participants’ median age was 49 years, with 78% having normal BP values and 47% exhibiting a dipping pattern; 51% were classified as sedentary and 22% as partially active. The median NaCl intake was 7.9 g/day. The youngest subjects had a higher hourly NaCle ratio compared to older subjects. Higher NaCl intake correlated with increased BP, a phenomenon more pronounced in men and younger subjects. The hourly day/night NaCle ratio positively correlates with dipping; however, PA did not show a significant correlation with the NaCle ratio. Conclusions: This study indicates that while the day/night NaCle ratio correlates with the dipping pattern, PA is unrelated to the circadian rhythm of renal sodium handling. The beneficial effects of PA on BP and cardiovascular health thus appear to be mediated through mechanisms other than NaCle. These are explorative findings only but relativize the need for further investigations on the topic.
Congenital Absence of Pericardium: The Swinging Heart
Authors: Marzullo Raffaella , Capestro Alessandro , Cosimo Renato , Fogante Marco , Aprile Alessandro , Balardi Liliana , Giordano Mario , Gaio Gianpiero , Gauderi Gabriella , Russo Maria Giovanna , Schicchi Nicolò
Published: August 2024

Congenital absence of the pericardium (CAP) is an unusual condition discovered, in most cases, incidentally but can potentially lead to fatal complications, including severe arrhythmias and sudden death. Recently, the use of modern imaging technologies has increased the diagnosis of CAP, providing important findings for risk stratification. Nevertheless, there is not yet consensus regarding therapeutic decisions, and the management of patients with CAP remains challenging. In this paper, we discuss the pathophysiological implication of CAP, review the current literature and explain the role of multimodality imaging tools for its diagnosis, management and treatment.
Design and Thermodynamic Analysis of Waste Heat-Driven Liquid Metal–Water Binary Vapor Power Plant Onboard Ship
Authors: Kepekci Haydar , Ezgi Cuneyt
Published: August 2024

Day after day, stricter environmental regulations and rising operating costs and fuel prices are forcing the shipping industry to find more effective ways of designing and operating energy-efficient ships. One of the ways to produce electricity efficiently is to create a waste heat-driven liquid metal–water binary vapor power plant. The liquid metal Rankine cycle systems could be considered topping cycles. Liquid metal binary cycles share characteristics like those of the steam Rankine power plants. They have the potential for high conversion efficiency, they will likely produce lower-cost power in plants of large capacity rather than small, and they will operate more efficiently at design capacity rather than at partial load. As a result, liquid metal topping cycles may find application primarily as base-load plants onboard ships. In this study, a waste heat-driven liquid metal–water binary vapor power plant onboard a ship is designed and thermodynamically analyzed. The waste heat onboard the vessel is the exhaust gas of the LM2500 marine gas turbine. Mercury and Cesium are selected as liquid metals in the topping cycle, while water is used in the bottoming cycle in binary power plants. Engineering Equation Solver (EES) software (V11.898) is used to perform analyses. For the turbine inlet temperature of 550 °C, while the total net work output of the binary cycle system is calculated to be 104.84 kJ/kg liquid metal and 1740.29 kJ/kg liquid metal for mercury and cesium, respectively, the efficiency of the binary cycle system is calculated to be 31.9% and 26.3% for mercury and cesium as liquid metal, respectively. This study shows that the binary cycle has a thermal efficiency of 26.32% and 31.91% for cesium and mercury, respectively, depending on liquid metal condensing pressure, and a binary cycle thermal efficiency of 25.9% and 30.9% for cesium and mercury, respectively, depending on liquid metal turbine inlet temperature, and these are possible with marine engine waste heat-driven liquid metal–water binary vapor cycles.
Characterization of Nile Red-Stained Microplastics through Fluorescence Spectroscopy
Authors: Prasad Suparnamaaya , Bennett Andrew , Triantafyllou Michael
Published: August 2024

Microplastics (MPs), typically defined as plastic fragments smaller than 5 mm, are pervasive in terrestrial and marine ecosystems. There is a need for rapid, portable, low-cost detection systems to assess health and environmental risks. Fluorescent tagging with Nile Red (NR) has emerged as a popular detection method, but variations in fluorescent emissions based on NR solvent, plastic polymer, excitation wavelength, and additives complicate standardization. In this study, seven plastic samples stained with acetone-based NR were analyzed using a fluorescent spectrometer to identify optimal emission peaks across UV-Vis excitation wavelengths. These findings aid in selecting appropriate excitation wavelengths and optical filters for future detection systems. Additionally, a straightforward polymer identification scheme was validated against field-collected plastic samples, whose material composition was confirmed via Fourier Transform Infrared Spectroscopy. This work contributes towards developing accessible microplastic detection technologies by characterizing the fluorescent properties of NR-stained plastics and enhancing the capability for effective environmental monitoring. Future research will expand the dataset to include diverse plastics with varying additives and weathering, and incorporate computer-vision tools for automated data processing and polymer identification.
Streptomyces pratensis S10 Promotes Wheat Plant Growth and Induces Resistance in Wheat Seedlings against Fusarium graminearum
Authors: Tian Xiaoman , Hu Lifang , Jia Ruimin , Cao Shang , Sun Yan , Dong Xiaomin , Wang Yang
Published: August 2024

Fusarium graminearum, a devastating fungal pathogen, causes great economic losses to crop yields worldwide. The present study investigated the potential of Streptomyces pratensis S10 to alleviate F. graminearum stress in wheat seedlings based on plant growth-promoting and resistance-inducing assays. The bioassays revealed that S10 exhibited multiple plant growth-promoting properties, including the production of siderophores, 1-aminocyclopropane-1-carboxylic acid deaminase (ACC), and indole-3-acetic acid (IAA), phosphate solubilization, and nitrogen fixation. Meanwhile, the pot experiment demonstrated that S10 improved wheat plant development, substantially enhancing wheat height, weight, root activity, and chlorophyll content. Consistently, genome mining identified abundant genes associated with plant growth promotion. S10 induced resistance against F. graminearum in wheat seedlings. The disease incidence and disease index reduced by nearly 52% and 65% in S10 pretreated wheat seedlings, respectively, compared with those infected with F. graminearum only in the non-contact inoculation assay. Moreover, S10 enhanced callose deposition and reactive oxygen species (ROS) accumulation and induced the activities of CAT, SOD, POD, PAL, and PPO. Furthermore, the quantitative real-time PCR (qRT-PCR) results indicated that S10 pretreatment increased the expression of SA- (PR1.1, PR2, PR5, and PAL1) and JA/ET-related genes (PR3, PR4a, PR9, and PDF1.2) in wheat seedlings upon F. graminearum infection. In summary, S. pratensis S10 could be an integrated biological agent and biofertilizer in wheat seedling blight management and plant productivity enhancement.
The Impact of Food Delivery Riders’ Perception of Fairness on Organizational Identification in the Digital Economy: Based on the Intermediary Perspective of Organizational Trust in the Context of Digital Technology
Authors: Tong Lei , Sutunyarak Chonlavit
Published: August 2024

With the rapid rise in the gig economy driven by advancements in digital technology and financial technology, this study focuses on the work experiences and psychological perceptions of food delivery riders in platform-based employment. This study used a sample of food delivery riders from 19 cities in China (such as Shanghai, Beijing, Guangzhou, etc.) and multiple delivery platforms (such as Meituan, Ele.me) to collect data through a combination of online and offline questionnaires. The impact relationship between perceived fairness, organizational trust, and organizational identity of food delivery riders was examined through factor analysis, structural equation modeling, and mediation effect modeling. The results of the survey and statistical analysis indicate that fairness perception and its dimensions (distributive fairness, procedural fairness, and interactional fairness) significantly influence riders’ organizational identification, with organizational trust serving as a critical mediating factor. The integration of digital technology has substantially enhanced the operational efficiency of platform-based employment by enabling real-time tracking, transparent communication, and data-driven decision-making. Innovations in financial technology, such as digital payment systems and financial management tools, offer riders safer and more convenient compensation methods, thereby contributing to their financial stability and fostering trust in the platform. The establishment of trust alleviates the riders’ concerns regarding compensation stability and bolsters their optimistic attitudes toward accessing platform resources and meeting their needs. This study provides significant insights and recommendations for leveraging digital technology and financial technology to improve the relationship and operational efficiency between riders and platform enterprises.
Diversity and Influencing Factors of Public Service Facilities in Urban (Suburban) Railway Life Circle—Evidence from Beijing Subway Line S1, China
Authors: Xun Jiayue , Zhang Min , Xu Gaofeng , Guo Xinyue
Published: August 2024

The urban (suburban) railway is a fast and convenient rail transit system connecting urban and suburban areas, and a refined analysis of the diversity of public service facilities around its stations can help to promote the intensive use of land around rail stations. However, the differences in the diversity of public service facilities in the railway life circle between urban and suburban railway stations and the factors affecting them are not clear. This paper takes the Beijing Suburban Railway Line Sub-center (Line S1) as a case study, uses the Shannon-Wiener index to measure the spatial diversity characteristics of public service facilities, and utilizes a multi-scale geographically weighted regression model to explore the influencing factors. The findings indicate that: (1) Centered on the stations, all six stations show a “less-more-less” ring or half-ring to the left distribution structure of the comprehensive diversity index of public service facilities within their study areas, with an increase followed by a decrease. (2) The influence of each influencing factor on the diversity of market-featured facilities exhibits significant differences. The most substantial spatial heterogeneity is observed in the distances to the nearest subway stations and bus stops. Distances to subway and urban (suburban) railway stations exhibit different spatial distribution characteristics within urban and suburban areas on Line S1. In urban areas, the closer the distance to the subway station or the further the distance to the railway station, the greater the diversity of public service facilities. Conversely, in suburban areas, the opposite is true. The conclusions of this research provide a scientific methodology and improvement measures to facilitate the construction of railway life circles in suburban regions of megacities.
Identifying Optimal Zones for Avocado (Persea americana Mill) Cultivation in Iberian Peninsula: A Climate Suitability Analysis
Authors: Domínguez Antonio , García-Martín Abelardo , Moreno Eduardo , González Encarnación , Paniagua Luis L. , Allendes Gonzalo
Published: August 2024

In recent decades, the cultivation of avocados (Persea americana Mill) has expanded throughout the Iberian Peninsula, with most of the production occurring on the Southern Atlantic and Mediterranean Coast, as well as in the Canary Islands. This expansion is due to high demand and high prices, which have made the crop very attractive. However, climatic suitability criteria have not always been followed, putting sustainability at risk. Avocados originate from tropical and subtropical areas and have very specific climatic requirements that must be met to ensure good production. This study analyzed the key climatic variables, including winter cold damage, pollen viability and flowering and fruit set temperatures. Using daily climate data from 1975 to 2022, advanced spatial analysis techniques were applied to produce suitability maps. The results indicate that the expansion of the crop is possible in certain areas of Southern Andalusia but not in the rest of the peninsula. Variables associated with low temperatures, such as cold damage (temperatures below 0 °C in winter) and conditions unfavorable for fruit set (minimum daily temperatures below 10 °C in spring), have been identified as the most restrictive factors. Specifically, the number of days with minimum temperatures above 10 °C in March and April appears to be the most limiting climatic factor for avocado cultivation in the Iberian Peninsula and the Balearic Islands. Andalusia and the Valencian Community have been identified as the most climatically suitable regions for avocado cultivation, with approximately 1,500,000 hectares recognized as potentially suitable for avocado production. This work provides valuable insights into the potential for sustainable agricultural intensification, the sustainability of agricultural decision-making and resilience to climate change.
Ecological Protection Redlines’ Positive Impact on Terrestrial Carbon Storage in Hainan Island, China
Authors: Zhang Zhouyao , Zhu Yuxin , Jia Peihong
Published: August 2024

The establishment of the ecological protection redline (EPR) in China plays a crucial role in safeguarding key ecological functional areas and sustaining biodiversity. Besides their significance, the impact of these redlines on regional carbon sequestration remains unclear due to current inconsistencies in their implementation and adjustment. This paper conducts a thorough analysis of the evolution of two EPR versions on Hainan Island and employs the InVEST model to assess the effects of two EPR areas on regional carbon storage between 2000 and 2020. Additionally, a spatial autoregressive model is integrated to explore the socioeconomic and environmental driving mechanisms behind changes in regional carbon storage, thereby revealing complex interactions between ecological protection policy adjustments and ecosystem services of carbon storage. Key findings include: (1) The 2022 EPR area has improved the management of ecological protection boundaries, permanent cultivated land, and urban development boundaries, outperforming the 2016 version, particularly in control of construction land and water resource management. (2) The EPR2022 exhibits higher carbon storage per area, indicating a more effective zoning system. The increase in carbon storage is primarily observed in transitions from cultivated land to forest, grassland to forest, and water bodies to grassland. (3) Elevation exhibits a relatively strong positive correlation with carbon storage within the EPRs, with high-altitude areas typically encompassing the core zones of tropical rainforest national parks that possess diverse vegetation and stable ecosystems, conducive to maintaining or increasing carbon storage. Evaluating the efficacy of the EPR in enhancing regional carbon storage is critical for refining management strategies and achieving carbon neutrality goals. Future strategies should incorporate a comprehensive analysis of ecosystem services of carbon storage into the EPR framework to enhance multiple ecosystem functions, thereby establishing a resilient and functionally stable ecological landscape. This research introduces an insightful estimation method crucial for developing more effective ecological protection policies and provides valuable insights for managing ecological protection areas globally.
Investigating Returns Management across E-Commerce Sectors and Countries: Trends, Perspectives, and Future Research
Authors: Stevenson Anthony Boyd , Rieck Julia
Published: August 2024

Background: The systematic literature review with additional descriptive analysis at hand focuses on analysing returns management in e-commerce, which is an increasingly critical issue as the volume of online shopping is rising. Methods: Drawing from a comprehensive search of academic databases and a manual review of Google Scholar, 54 articles dating from 2007 onwards were collected and fully read. Results: The review reveals a main research effort emerging mainly from Germany and other countries, with a notable focus on fashion retail. The bulk of these studies aim to understand and reduce the frequency of customer returns, addressing a substantial operational challenge for online retailers. The findings provide multiple research streams extracted from the collected literature and combined to an overview. Conclusions: Through this, there are tendencies which can be interpreted to derive the evolution of the research field. The illustrated results in this review paint a detailed picture of the existing research landscape. This highlights the importance of ongoing research, which, e.g., holds potential benefits for customer satisfaction and environmental sustainability. The review also lists future research directions, recommending the continued investigation of areas such as predictive analytics and customer behaviour to further refine returns management practices.
DSU-LSTM-Based Trend Prediction Method for Lubricating Oil
Authors: Du Ying , Zhang Yue , Shao Tao , Zhang Yanchao , Cui Yahui , Wang Shuo
Published: August 2024

Oil monitoring plays an important role in early maintenance of mechanical equipment on account of the fact that lubricating oil contains a large amount of wear information. However, due to extreme industrial environment and long-term service, the data history and the sample size of lubricating oil are very limited. Therefore, to address problems due to a lack of oil samples, this paper proposes a new prediction strategy that fuses the domain shifts with uncertainty (DSU) method and long short-term memory (LSTM) method. The proposed DSU-LSTM model combines the advantages of the DSU model, such as increasing data diversity and uncertainty, reducing the impact of independent or identical domains on neural network training, and mitigating domain changes between different oil data histories, with the advantages of LSTM in predicting time series, thereby improving prediction capability. To validate the proposed method, a case study with real lubricating oil data is conducted, and comparisons are given by calculating the root-mean-square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) with LSTM, support vector machine (SVM), and DSU-SVM models. The results illustrate the effectiveness of the proposed DSU-LSTM method for lubricating oil, and the robustness of the prediction model can be improved as well.
Machine-Learning-Based Wear Prediction in Journal Bearings under Start–Stop Conditions
Authors: König Florian , Wirsing Florian , Singh Ankit , Jacobs Georg
Published: August 2024

The present study aims to efficiently predict the wear volume of a journal bearing under start–stop operating conditions. For this purpose, the wear data generated with coupled mixed-elasto-hydrodynamic lubrication (mixed-EHL) and a wear simulation model of a journal bearing are used to develop a neural network (NN)-based surrogate model that is able to predict the wear volume based on the operational parameters. The suitability of different time series forecasting NN architectures, such as Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Nonlinear Autoregressive with Exogenous Inputs (NARX), is studied. The highest accuracy is achieved using the NARX network architectures.
KCS-YOLO: An Improved Algorithm for Traffic Light Detection under Low Visibility Conditions
Authors: Zhou Qinghui , Zhang Diyi , Liu Haoshi , He Yuping
Published: August 2024

Autonomous vehicles face challenges in small-target detection and, in particular, in accurately identifying traffic lights under low visibility conditions, e.g., fog, rain, and blurred night-time lighting. To address these issues, this paper proposes an improved algorithm, namely KCS-YOLO (you only look once), to increase the accuracy of detecting and recognizing traffic lights under low visibility conditions. First, a comparison was made to assess different YOLO algorithms. The benchmark indicates that the YOLOv5n algorithm achieves the highest mean average precision (mAP) with fewer parameters. To enhance the capability for detecting small targets, the algorithm built upon YOLOv5n, namely KCS-YOLO, was developed using the K-means++ algorithm for clustering marked multi-dimensional target frames, embedding the convolutional block attention module (CBAM) attention mechanism, and constructing a small-target detection layer. Second, an image dataset of traffic lights was generated, which was preprocessed using the dark channel prior dehazing algorithm to enhance the proposed algorithm’s recognition capability and robustness. Finally, KCS-YOLO was evaluated through comparison and ablation experiments. The experimental results showed that the mAP of KCS-YOLO reaches 98.87%, an increase of 5.03% over its counterpart of YOLOv5n. This indicates that KCS-YOLO features high accuracy in object detection and recognition, thereby enhancing the capability of traffic light detection and recognition for autonomous vehicles in low visibility conditions.
Chatter Detection in Thin-Wall Milling Based on Multi-Sensor Fusion and Dual-Stream Residual Attention CNN
Authors: Zhan Danian , Lu Dawei , Gao Wenxiang , Wei Haojie , Sun Yuwen
Published: August 2024

Thin-walled parts exhibit high flexibility, rendering them susceptible to chatter during milling, which can significantly impact machining accuracy, surface quality, and productivity. Therefore, chatter detection plays a crucial role in thin-wall milling. In this study, a chatter detection method based on multi-sensor fusion and a dual-stream convolutional neural network (CNN) is proposed, which can effectively identify the machining status in thin-wall milling. Specifically, the acceleration signals and cutting force signals are first collected during the milling process and transformed into the frequency domain using fast Fourier transform (FFT). Secondly, a dual-stream CNN is designed to extract the hidden features from the spectrum of multi-sensor signals, thereby avoiding confusion when learning the features of each sensor signal. Then, considering that the characteristics of each sensor are of different importance for chatter detection, a joint attention mechanism based on residual connection is designed, and the feature weight coefficients are adaptively assigned to obtain the joint features. Finally, the joint features feed into a machining status classifier to identify chatter occurrences. To validate the feasibility and effectiveness of the proposed method, a series of milling tests are conducted. The results demonstrate that the proposed method can accurately distinguish between stable and chatter under various milling scenarios, achieving a detection accuracy of up to 98.68%.
Paramagnetic Solid-State NMR Study of Solid Solutions of Cobaltocene with Ferrocene and Nickelocene
Authors: Harmon-Welch Gabrielle E. , Bakhmutov Vladimir I. , Blümel Janet
Published: August 2024

The metallocenes ferrocene (Cp2Fe, 1), nickelocene (Cp2Ni, 2), and cobaltocene (Cp2Co, 3) crystallize in the same space group (P21/a) and they have the same shape and similar size. Therefore, they form solid solutions with random distribution of the different molecules when crystallized from solution. Alternatively, the solid metallocenes can be ground together manually, and the solid solutions form at any molar ratio within minutes. The metallocenes 2 and 3 are paramagnetic. Solid solutions of 1/3 and 2/3 have been studied by paramagnetic solution and solid-state NMR spectroscopy. The effect of the paramagnetic species on the other components in the solid solutions has been investigated. The impact on the chemical shifts is limited. However, the halfwidths and the signal shapes, as defined by the rotational sideband intensities, change with increasing amounts of paramagnetic components. The 1H T1 relaxation times are shortened for diamagnetic protons in the presence of paramagnetic metallocenes in the solid solutions. It has been demonstrated that all metallocenes mix at the molecular level within the polycrystalline samples. The EPR spectra of the solid solutions are dominated by the most intensive signal of any paramagnetic metallocene in the solid samples.
Work Faster, Work in Parallel, or Work Overtime? An Assessment of Short-Term Capacity Adjustments by Simulation
Authors: Fernandes Nuno O. , Thürer Matthias , Costa Federica
Published: August 2024

Many firms use short-term capacity adjustments to deal with demand changes over time, and a broad literature assesses when and where to adjust capacity. This study highlights that this may be dependent on the type of capacity flexibility used to actually realize the adjustment. By comparing for the first-time capacity adjustments by speeding up processing rates, working in parallel, or using overtime, significant differences in the operational performance are identified, with the latter resulting in the best percentage tardy performance. This provides important insights for the interpretation of the existing literature, guides the future literature, and helps managers to make better decisions.
The Connection between Der(Uq+(g)) and Der(Ur,s+(g))
Authors: Zhong Yongyue , Tang Xiaomin
Published: August 2024

To facilitate the parallel development of the structures and properties of two-parameter quantum groups with those of one-parameter quantum groups, this paper primarily elucidates the interrelations and distinctions between the derivation algebras of these two types of quantum groups. Additionally, we also proposed a method for deriving the derivation algebra of one-parameter quantum groups from known two-parameter quantum group derivations, and vice versa.
Contrastive Machine Learning with Gamma Spectroscopy Data Augmentations for Detecting Shielded Radiological Material Transfers
Authors: Stomps Jordan R. , Wilson Paul P. H. , Dayman Kenneth J.
Published: August 2024

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.
Single-Machine Scheduling with Simultaneous Learning Effects and Delivery Times
Authors: Liu Zheng , Wang Ji-Bo
Published: August 2024

This paper studies the single-machine scheduling problem with truncated learning effect, time-dependent processing time, and past-sequence-dependent delivery time. The delivery time is the time that the job is delivered to the customer after processing is complete. The goal is to determine an optimal job schedule to minimize the total weighted completion time and maximum tardiness. In order to solve the general situation of the problem, we propose a branch-and-bound algorithm and other heuristic algorithms. Computational experiments also prove the effectiveness of the given algorithms.
Dapsone as a Current Option for the Treatment of Autoimmune Bullous Diseases with Autoimmunity to Non-Enzymes: A Retrospective Study from a Single Central European Referral Center
Authors: Spałek Maciej Marek , Jałowska Magdalena , Welc Natalia , Bowszyc-Dmochowska Monika , Dmochowski Marian
Published: August 2024

Background and Objectives: Dapsone (DP) is employed in the management of various skin conditions, including autoimmune bullous diseases to non-enzymes (n-eAIBDs). This study aimed to assess the advantages and safety profile of DP treatment in n-eAIBDs patients. The evaluation focused on clinical remission, reduction in glucocorticosteroid (GCS) usage, and adverse incidents during a 12-month observation in a dermatology department at a Central European university. Materials and Methods: Our retrospective study included forty-one patients who met the inclusion criteria, comprising nineteen with pemphigus vulgaris, nine with pemphigus foliaceus, four with bullous pemphigoid, and nine with mucous membrane pemphigoid, including one patient with Brunsting–Perry pemphigoid. Patients received 25–50 mg/day of DP along with oral GCSs for a year, with a subsequent dose reduction where feasible. Results: The mean decreases in prednisone-equivalent dosages across all groups after 2, 6, and 12 months of DP treatment were 45.66%, 65.77%, and 63.03%, respectively. Throughout the 12-month observation period, 21.62% of patients experienced a relapse, while the remaining patients attained either complete or partial remission with minimal therapy. Adverse incidents were observed in 29.27% of patients; these were mild or moderate, and no severe negative effects were observed. Conclusions: DP is an effective and affordable choice to support the treatment of n-eAIBDs, but it may not be sufficient for long-term management in certain patients with severe n-eAIBDs.
Postural Orthostatic Tachycardia Syndrome Associated with COVID-19: A Narrative Review
Authors: Park Jung-Hyun , Park Somin , Kim Na-Hye , Lee Yoonjin , Chang Yoonkyung , Song Tae-Jin
Published: August 2024

Postural orthostatic tachycardia syndrome (POTS) is a complex condition marked by an atypical autonomic response to standing, leading to orthostatic intolerance and significant tachycardia without accompanying hypotension. In recent studies, a considerable number of individuals recovering from COVID-19 have been reported to experience POTS within 6 to 8 months post-infection. Key symptoms of POTS include fatigue, difficulty with orthostatic tolerance, tachycardia, and cognitive challenges. The underlying causes of POTS following COVID-19 remain unknown, with various theories proposed such as renin–angiotensin–aldosterone system (RAAS) dysregulation, hyperadrenergic reaction, and direct viral infection. Healthcare professionals should be vigilant for POTS in patients who have recovered from COVID-19 and are experiencing signs of autonomic dysfunction and use diagnostic procedures such as the tilt-up table test for confirmation. COVID-19-related POTS should be approached with a holistic strategy. Although many patients show improvement with initial non-drug treatments, for subjects who do not respond and exhibit more severe symptoms, medication-based therapies may be necessary. The current understanding of COVID-19-related POTS is limited, underscoring the need for more research to increase knowledge and enhance treatment approaches.
Successes and Challenges in Clinical Trial Recruitment: The Experience of a New Study Team
Authors: Hung Man , Mohajeri Amir , Almpani Konstantinia , Carberry Gabriel , Wisniewski John F. , Janes Kade , Janes Brooklyn , Hardy Chase , Zakeri Golnoush , Raymond Ben , Trinh Heather , Bretner Jordan , Cheever Val J. , Garibyan Rafael , Bachstein Perry , Licari Frank W.
Published: August 2024

Participant recruitment is one of the most challenging aspects of a clinical trial, directly impacting both the study’s duration and the quality of its results. Therefore, reporting successful recruitment strategies is crucial. This study aimed to document the recruitment tactics and experiences of a research team during a university-based randomized clinical trial, conducted as part of a clinical research immersion program. Recruitment took place from October 2021 to October 2022. Before the study commenced, study team members received formal training in clinical trial participant recruitment from the Principal Investigator. The recruitment strategies were integrated into initial study design, which was approved by the Institutional Review Board. A multimodal approach was employed, incorporating both direct and indirect recruitment methods. These strategies successfully met the enrollment target within the twelve-month period. Throughout the process, team members acquired valuable knowledge in recruitment design and implementation, along with transferable interpersonal and networking skills. In-person recruitment was the most efficient and cost-effective strategy, followed by personal referrals. The primary challenge was accommodating participants’ availability. Other study teams should consider these recruitment strategies during their study designs. Additionally, the knowledge and skills gained by this study team underscore the value of experiential learning in research education.
Effect of Saccharomyces boulardii on Liver Diseases: A Systematic Review
Authors: Maslennikov Roman , Benuni Nona , Levshina Anna , Adzhieva Farida , Demina Tatyana , Kucher Alina , Pervushova Ekaterina , Yuryeva Evgeniya , Poluektova Elena , Zolnikova Oxana , Kozlov Evgenii , Sigidaev Alexey , Ivashkin Vladimir
Published: August 2024

We aimed to systematize the results of published studies on the use of Saccharomyces boulardii (SB) for the treatment of various liver disorders (CRD42022378050). Searches were conducted using PubMed and Scopus on 1 August 2022. The PubMed search was updated on 15 June 2024. The review included sixteen studies: ten experimental animal studies (EASs) and six randomized controlled trials (RCTs). The CNCM I-745 strain was used in 68.8% of the included studies. SB reduced the severity of many manifestations of cirrhosis, and lowered the Child–Pugh scores in RCT. SB reduced the serum concentrations of TNF-α, IL-1β, IL-6, and IL-4 in animals with metabolic dysfunction-associated steatotic liver disease (MASLD); lowered the serum TNF-α and IL-6 levels in experimental cirrhosis in rats; and reduced the CRP levels in decompensated cirrhosis. The EAS of MASLD revealed that SB reduced liver steatosis and inflammation and lowered the liver expression of genes of TNF-α, IL-1β, interferon-γ, and IL-10. In studies on experimental cirrhosis and MASLD, SB reduced the liver expression of genes of TGF-β, α-SMA, and collagen as well as liver fibrosis. SB reduced the abundance of Escherichia (Proteobacteria), increased the abundance of Bacteroidetes in the gut microbiota, prevented an increase in intestinal barrier permeability, and reduced bacterial translocation and endotoxemia.
Investigation of Mutations in the crt-o and mdr1 Genes of Plasmodium vivax for the Molecular Surveillance of Chloroquine Resistance in Parasites from Gold Mining Areas in Roraima, Brazil
Authors: de Aguiar Barros Jacqueline , Granja Fabiana , Abreu-Fernandes Rebecca de , de Queiroz Lucas Tavares , e Silva Daniel da Silva , Citó Arthur Camurça , Mocelin Natália Ketrin Almeida-de-Oliveira , Daniel-Ribeiro Cláudio Tadeu , Ferreira-da-Cruz Maria de Fátima
Published: August 2024

Plasmodium vivax causes the largest malaria burden in Brazil, and chloroquine resistance poses a challenge to eliminating malaria by 2035. Illegal mining in the Roraima Yanomami Indigenous territory can lead to the introduction of resistant parasites. This study aimed to investigate mutations in the pvcrt-o and pvmdr-1 genes to determine their potential as predictors of P. vivax chloroquine-resistant phenotypes. Samples were collected in two health centers of Boa Vista. A questionnaire was completed, and blood was drawn from each patient. Then, DNA extraction, PCR, amplicon purification, and DNA sequencing were performed. After alignment with the Sal-1, the amplified fragment was analyzed. Patients infected with the mutant parasites were queried in the Surveillance Information System. Among the patients, 98% (157/164) of participants were from illegal mining areas. The pvcrt-o was sequenced in 151 samples, and the K10 insertion was identified in 13% of them. The pvmdr1 was sequenced in 80 samples, and the MYF haplotype (958M) was detected in 92% of them and the TYF was detected in 8%, while the MYL was absent. No cases of recrudescence, hospitalization, or death were found. Mutations in the pvcrt-o and pvmdr-1 genes have no potential to predict chloroquine resistance in P. vivax.
A Critical Review on the Flotation Reagents for Phosphate Ore Beneficiation
Authors: Yu Liangmou , Yu Pan , Bai Shaojun
Published: August 2024

Phosphate ore is the dominating natural resource for the production of fertilizers and phosphorous chemical products. Flotation is the most widely employed technique to enrich apatite and remove the impurities for the separation of the phosphate ore. The flotation reagents play an important role in this efficient separation of phosphate ores. In the last few decades, great progress has been achieved in the flotation reagents for phosphate ores. However, a critical review on this theme has rarely been reported in recent years. Thus, the goal of this paper is to critically analyze the published literature on the flotation reagents for phosphate ores, mainly ranging from 2010 to 2024, including the regulators, depressors, collectors, and frothers. Additionally, the interaction mechanisms between the reagents and mineral surfaces were analyzed. It is concluded that sulfuric acids and its derivatives play a leading role in the depression of phosphate minerals. Highly selective biobased depressants have become potential carbonate inhibitors. Additionally, the derivatization and synthesis of multi-functional compounds and identifying the biobased frothers are the main development trends of collectors and frothers. Overall, a high-quality concentrate with a 31.05% grade and 98.21% recovery at pH 5 was achieved using lecithin as an ecofriendly amphoteric collector and sulfuric acid as the depressor when the feed contained 24.49% P2O5, which was superior to other flotation indexes of similar phosphate ores. This review will help researchers to document knowledge gaps and provide a reference for the efficient and green beneficiation of phosphate ores in the future.
Enhancing Highway Driving: High Automated Vehicle Decision Making in a Complex Multi-Body Simulation Environment
Authors: Rizehvandi Ali , Azadi Shahram , Eichberger Arno
Published: August 2024

Automated driving is a promising development in reducing driving accidents and improving the efficiency of driving. This study focuses on developing a decision-making strategy for autonomous vehicles, specifically addressing maneuvers such as lane change, double lane change, and lane keeping on highways, using deep reinforcement learning (DRL). To achieve this, a highway driving environment in the commercial multi-body simulation software IPG Carmaker 11 version is established, wherein the ego vehicle navigates through surrounding vehicles safely and efficiently. A hierarchical control framework is introduced to manage these vehicles, with upper-level control handling driving decisions. The DDPG (deep deterministic policy gradient) algorithm, a specific DRL method, is employed to formulate the highway decision-making strategy, simulated in MATLAB software. Also, the computational procedures of both DDPG and deep Q-network algorithms are outlined and compared. A set of simulation tests is carried out to evaluate the effectiveness of the suggested decision-making policy. The research underscores the advantages of the proposed framework concerning its convergence rate and control performance. The results demonstrate that the DDPG-based overtaking strategy enables efficient and safe completion of highway driving tasks.