bluuebunny/crossref_metadata_2025 huggingface dataset:
The Atomistic Understanding of the Ice Recrystallization Inhibition Activity of Antifreeze Glycoproteins
Authors: Yang Wentao , Liao Yucong , Shi Qi , Sun Zhaoru
Published: February 2023

As the most potent ice recrystallization inhibitors, antifreeze glycoproteins (AFGPs) have been extensively studied since their discovery. However, the molecular mechanism of how they inhibit ice growth remains controversial—notably, which group directly contributes to the binding of AFGPs to ice is hotly debated. Here, we use molecular dynamics simulations to investigate the atomistic details of the binding of AFGP8 to ice. We show that the binding of AFGP8 to ice can be divided into three cases: backbone dominant binding (BDB), disaccharide dominant binding (DDB) and weak binding (WB). Hydrogen-bonding and hydrophobic groups contribute equally to the binding of AFGP8 to ice and synergistically promote the binding. The –CH3 groups promote the contacting of AFGP8 to ice via hydrophobic effect, and the hydrogen-bonding groups anchor AFGP8 to ice surfaces through direct hydrogen bonding with ice. Specially, we verify that the -CONH- groups anchor the backbone of AFGP8 to ice by forming hydrogen bonds with ice surfaces while the –OH groups not only anchor the disaccharide to ice but also slow down the dynamics of the surrounding water. In addition, we reveal that both the backbone and the disaccharide can bind to ice surfaces while the latter is more flexible, which also perturbs the hydrogen bond network of potential ice-like water molecules by swaying in the solution to further enhance its antifreeze activity. This work provides the atomistic details of the ice growth inhibition mechanism of AFGP8, which is helpful for the design of high-efficacy cryoprotectants.
Trapped Carrier Recombination in Sb2Se3 Polycrystalline Film
Authors: Tao Tingting , Shu Jingting , Guo Yingnan , Wang Kai , Zhao Xiaohui , Liang Baolai , Li Zhiqiang , Dang Wei
Published: February 2023

Sb2Se3 has recently emerged as a promising material for optic-electronic applications. In this work, trapped carrier recombination in Sb2Se3 was investigated by joint use of time-resolved microwave conductivity (TRMC) and photoluminescence (PL) spectroscopy. trapped carrier thermal excitation into the continuous band was observed in TRMC kinetics. Based on the exponential band tail model, the depth of the trap state, where trapped carriers are released into a continuous band, was estimated to range from 33.0 meV to 110.0 meV at room temperature. Temperature-varying TRMC and PL were further employed to study the influence of temperature on the trapped carrier recombination. Negative thermal quenchings of PL intensity and quantity of thermal emission carriers were observed and can be well explained by the thermal excitation of deep trapped carriers into shallow trap states and the continuous band. Two thermal activation energies of 12.5 meV and 304.0 meV were also revealed. This work is helpful for understanding the trapped carrier recombination process in polycrystalline Sb2Se3 film.
Temperature Modeling of AZ31B Alloy Plate during open-Roller Conveying Process Considering Air-Cooling Characteristics
Authors: Xu Shuang , Wang Zebin , Jia Weitao , Chen Xingrui , Dong Yunyun
Published: February 2023

In the process of open-roller conveying, magnesium alloy plates easily produce temperature drops and uneven temperatures. Ignoring the heat dissipation caused by the contact between the plate and the roller table, the process can be described as a process of air cooling. The present study aimed to investigate the temperature distribution and evolution of a magnesium alloy plate during the process. The air-cooling process of the AZ31B magnesium alloy plate was investigated and analyzed in detail under different initial temperatures and plate thicknesses, with a specific focus on the temperature distribution along both the width and thickness directions. The results show that the temperature-difference curves between the end face and the center under different air-cooling conditions appeared to have four stages: rapid increase, slow increase, basic stable and slow decline. To facilitate the establishment of the temperature model, the whole air-cooling process was approximately divided into two independent one-dimensional heat-conduction processes in the thickness direction and the width direction. Subsequently, one-dimensional steady-state heat-conduction models were developed in various directions, based on the fundamental principles of heat transfer and assuming that the adjacent temperature-drop layer satisfied the quadratic function distribution. Through the superposition of cooling with time in two directions, the temperature evolution at different positions in the process of air cooling can be solved accurately.
A Clinical Study to Assess Diffuse Reflectance Spectroscopy with an Auto-Calibrated, Pressure-Sensing Optical Probe in Head and Neck Cancer
Authors: Rickard Ashlyn G. , Mikati Husam , Mansourati Antoine , Stevenson Daniel , Krieger Marlee , Rocke Daniel , Esclamado Ramon , Dewhirst Mark W. , Ramanujam Nirmala , Lee Walter T. , Palmer Gregory M.
Published: February 2023

Diffuse reflectance spectroscopy (DRS) is a powerful tool for quantifying optical and physiological tissue properties such as hemoglobin oxygen saturation and vascularity. DRS is increasingly used clinically for distinguishing cancerous lesions from normal tissue. However, its widespread clinical acceptance is still limited due to uncontrolled probe–tissue interface pressure that influences reproducibility and introduces operator-dependent results. In this clinical study, we assessed and validated a pressure-sensing and automatic self-calibration DRS in patients with suspected head and neck squamous cell carcinoma (HNSCC). The clinical study enrolled nineteen patients undergoing HNSCC surgical biopsy procedures. Patients consented to evaluation of this improved DRS system during surgery. For each patient, we obtained 10 repeated measurements on one tumor site and one distant normal location. Using a Monte Carlo-based model, we extracted the hemoglobin saturation data along with total hemoglobin content and scattering properties. A total of twelve cancer tissue samples from HNSCC patients and fourteen normal tissues were analyzed. A linear mixed effects model tested for significance between repeated measurements and compared tumor versus normal tissue. These results demonstrate that cancerous tissues have a significantly lower hemoglobin saturation compared to normal controls (p < 0.001), which may be reflective of tumor hypoxia. In addition, there were minimal changes over time upon probe placement and repeated measurement, indicating that the pressure-induced changes were minimal and repeated measurements did not differ significantly from the initial value. This study demonstrates the feasibility of conducting optical spectroscopy measurements on intact lesions prior to removal during HNSCC procedures, and established that this probe provides diagnostically-relevant physiologic information that may impact further treatment.
Management of Recurrent Retroperitoneal Sarcoma
Authors: Jolissaint Joshua S. , Raut Chandrajit P. , Fairweather Mark
Published: February 2023

Recurrence after resection of retroperitoneal sarcoma is common and varies by histological subtype. Pattern of recurrence is similarly affected by histology (e.g., well-differentiated liposarcoma is more likely to recur locoregionally, whereas leiomyosarcoma is more likely to develop distant metastases). Radiotherapy may provide effective locoregional control in limited circumstances and the data on the impact of chemotherapy are scant. Surgery for locally recurrent disease is associated with the greatest survival benefit; however, data are retrospective and from a highly selected subgroup of patients. Limited retrospective data have also suggested a survival association with the resection of limited distant metastases. Given the complexity of these patients, multidisciplinary evaluation at a high-volume sarcoma center is critical.
Factors Influencing Lymph Node Positivity in HER2/neu+ Breast Cancer Patients
Authors: Englander Katherine , Chintapally Neha , Gallagher Julia , Elleson Kelly , Sun Weihong , Whiting Junmin , Laronga Christine , Lee Marie Catherine
Published: February 2023

Axillary lymph node metastases are a key prognostic factor in breast cancer treatment. Our aim was to evaluate how tumor size, tumor location, and imaging results correlate to axillary lymph node diseases for patients with stage I-III HER2/neu+ breast cancer. This is a single-institution retrospective chart review of female breast cancer patients diagnosed with primary invasive Her2/neu+ breast cancer who were treated with upfront surgical resection from 2000–2021. Of 75 cases, 44/75 (58.7%) had nodal metastasis, and there was a significant association of larger tumor size to nodal metastases (p ≤ 0.001). Patients with negative nodes had a smaller mean tumor size (n = 30; 15.10 mm) than patients with positive nodes (n = 45; 23.9 mm) (p = 0.002). Preoperative imaging detected suspicious nodes in 36 patients, and ultrasound detected the most positive nodes (14/18; p = 0.027). Our data confirms that tumor size at diagnosis is correlated with a higher likelihood of axillary involvement in patients with Her2/neu+ breast cancer; notably, a large proportion of Her2/neu+ breast cancers have metastatic involvement of axillary lymph nodes even with small primary lesions.
Molecular Characterization and Prognosis of Lactate-Related Genes in Lung Adenocarcinoma
Authors: Guo Zixin , Hu Liwen , Wang Qingwen , Wang Yujin , Liu Xiao-Ping , Chen Chen , Li Sheng , Hu Weidong
Published: February 2023

Objective: To explore the lactate-related genes (LRGs) in lung adenocarcinoma (LUAD) by various methods, construct a prognostic model, and explore the relationship between lactate subtypes and the immune tumor microenvironment (TME). Methods: 24 LRGs were collected. The mutation landscape and the prognosis value of LRGs were explored by using The Cancer Genome Atlas (TCGA) data. Consensus clustering analysis was used for different lactate subtype identification. Based on the lactate subtypes, we explore the landscape of TME cell infiltration. A risk-score was calculated by using the LASSO-Cox analysis. A quantitative real-time PCR assay was utilized to validate the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients. Results: Comparing the normal samples, 18 LRGs were differentially expressed in tumor samples, which revealed that the differential expression of LRGs may be related to Copy Number Variation (CNV) alterations. The two distinct lactate subtypes were defined. Compared to patients in the LRGcluster A group, LUAD patients in the LRGcluster B group achieved better survival. The prognostic model was constructed based on differentially expressed genes (DEGs) via the LASSO-Cox analysis, which showed the accuracy of predicting the prognosis of LUAD patients using the ROC curve. A high-risk score was related to a high immune score, stromal score, and tumor mutation burden (TMB). Patients had better OS with low risk compared with those with high risk. The sensitivities of different risk groups to chemotherapeutic drugs were explored. Finally, the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients was verified via qRT-PCR. Conclusions: The lactate subtypes were independent prognostic biomarkers in LUAD. Additionally, the difference in the lactate subtypes was an indispensable feature for the individual TME. The comprehensive evaluation of the lactate subtypes in the single tumor would help us to understand the infiltration characteristics of TME and guide immunotherapy strategies.
Efficient U-Net Architecture with Multiple Encoders and Attention Mechanism Decoders for Brain Tumor Segmentation
Authors: Aboussaleh Ilyasse , Riffi Jamal , Fazazy Khalid El , Mahraz Mohamed Adnane , Tairi Hamid
Published: February 2023

The brain is the center of human control and communication. Hence, it is very important to protect it and provide ideal conditions for it to function. Brain cancer remains one of the leading causes of death in the world, and the detection of malignant brain tumors is a priority in medical image segmentation. The brain tumor segmentation task aims to identify the pixels that belong to the abnormal areas when compared to normal tissue. Deep learning has shown in recent years its power to solve this problem, especially the U-Net-like architectures. In this paper, we proposed an efficient U-Net architecture with three different encoders: VGG-19, ResNet50, and MobileNetV2. This is based on transfer learning followed by a bidirectional features pyramid network applied to each encoder to obtain more spatial pertinent features. Then, we fused the feature maps extracted from the output of each network and merged them into our decoder with an attention mechanism. The method was evaluated on the BraTS 2020 dataset to segment the different types of tumors and the results show a good performance in terms of dice similarity, with coefficients of 0.8741, 0.8069, and 0.7033 for the whole tumor, core tumor, and enhancing tumor, respectively.
The Female Reproductive Tract Microbiome and Cancerogenesis: A Review Story of Bacteria, Hormones, and Disease
Authors: Trifanescu Oana Gabriela , Trifanescu Raluca Alexandra , Mitrica Radu Iulian , Bran Diana Maria , Serbanescu Georgia Luiza , Valcauan Laurentiu , Marinescu Serban Andrei , Gales Laurentia Nicoleta , Tanase Bogdan Cosmin , Anghel Rodica Maricela
Published: February 2023

The microbiota is the complex community of microorganisms that populate a particular environment in the human body, whereas the microbiome is defined by the entire habitat—microorganisms and their environment. The most abundant and, therefore, the most studied microbiome is that of the gastrointestinal tract. However, the microbiome of the female reproductive tract is an interesting research avenue, and this article explores its role in disease development. The vagina is the reproductive organ that hosts the largest number of bacteria, with a healthy profile represented mainly by Lactobacillus spp. On the other hand, the female upper reproductive tract (uterus, Fallopian tubes, ovaries) contains only a very small number of bacteria. Previously considered sterile, recent studies have shown the presence of a small microbiota here, but there are still debates on whether this is a physiologic or pathologic occurrence. Of particular note is that estrogen levels significantly influence the composition of the microbiota of the female reproductive tract. More and more studies show a link between the microbiome of the female reproductive tract and the development of gynecological cancers. This article reviews some of these findings.
Therapy-Acquired Clonal Mutations in Thiopurine Drug-Response Genes Drive Majority of Early Relapses in Pediatric B-Cell Precursor Acute Lymphoblastic Leukemia
Authors: Thakur Rozy , Bhatia Prateek , Singh Minu , Sreedharanunni Sreejesh , Sharma Pankaj , Singh Aditya , Trehan Amita
Published: February 2023

Methods: Forty pediatric (0–12 years) B-ALL DNA samples (20 paired Diagnosis-Relapse) and an additional six B-ALL DNA samples (without relapse at 3 years post treatment), as the non-relapse arm, were retrieved from the biobank for advanced genomic analysis. Deep sequencing (1050–5000X; mean 1600X) was performed using a custom NGS panel of 74 genes incorporating unique molecular barcodes. Results: A total 47 major clones (>25% VAF) and 188 minor clones were noted in 40 cases after bioinformatic data filtering. Of the forty-seven major clones, eight (17%) were diagnosis-specific, seventeen (36%) were relapse-specific and 11 (23%) were shared. In the control arm, no pathogenic major clone was noted in any of the six samples. The most common clonal evolution pattern observed was therapy-acquired (TA), with 9/20 (45%), followed by M-M, with 5/20 (25%), m-M, with 4/20 (20%) and unclassified (UNC) 2/20 (10%). The TA clonal pattern was predominant in early relapses 7/12 (58%), with 71% (5/7) having major clonal mutations in the NT5C2 or PMS2 gene related to thiopurine-dose response. In addition, 60% (3/5) of these cases were preceded by an initial hit in the epigenetic regulator, KMT2D. Mutations in common relapse-enriched genes comprised 33% of the very early relapses, 50% of the early and 40% of the late relapses. Overall, 14/46 (30%) of the samples showed the hypermutation phenotype, of which the majority (50%) had a TA pattern of relapse. Conclusions: Our study highlights the high frequency of early relapses driven by TA clones, demonstrating the need to identify their early rise during chemotherapy by digital PCR.
The Anthropometric Measurement of Nasal Landmark Locations by Digital 2D Photogrammetry Using the Convolutional Neural Network
Authors: Minh Trieu Nguyen , Truong Thinh Nguyen
Published: February 2023

Measuring and labeling human face landmarks are time-consuming jobs that are conducted by experts. Currently, the applications of the Convolutional Neural Network (CNN) for image segmentation and classification have made great progress. The nose is arguably one of the most attractive parts of the human face. Rhinoplasty surgery is increasingly performed in females and also in males since surgery can help to enhance patient satisfaction with the resulting perceived beautiful ratio following the neoclassical proportions. In this study, the CNN model is introduced to extract facial landmarks based on medical theories: it learns the landmarks and recognizes them based on feature extraction during training. The comparison between experiments has proved that the CNN model can detect landmarks depending on desired requirements. Anthropometric measurements are carried out by automatic measurement divided into three images with frontal, lateral, and mental views. Measurements are performed including 12 linear distances and 10 angles. The results of the study were evaluated as satisfactory with a normalized mean error (NME) of 1.05, an average error for linear measurements of 0.508 mm, and 0.498° for angle measurements. Through its results, this study proposed a low-cost automatic anthropometric measurement system with high accuracy and stability.
Neurological Wilson’s Disease Signs—Hepatic Encephalopathy or Copper Toxicosis?
Authors: Jopowicz Anna , Tarnacka Beata
Published: February 2023

Wilson’s disease (WD) is a rare autosomal recessive (AR) disorder resulting from mutations in the ATP7B gene, which is responsible for the encryption of transmembrane copper transporting ATPase. The symptomatic presentation of the disease is estimated to be about 1 in 30,000. The impairment of ATP7B function results in a copper overload in hepatocytes, which further leads to liver pathology. This copper overload also occurs in other organs, most particularly in the brain. This could then cause the occurrence of neurological and psychiatric disorders. Symptoms differ substantially and most often occur between the ages of 5 and 35 years. Early symptoms are commonly hepatic, neurological, or psychiatric. While disease presentation is most often asymptomatic, it could also range as far as to include fulminant hepatic failure, ataxia, and cognitive disorders. Various treatments are available for Wilson’s disease, including chelation therapy and zinc salts, which can reverse copper overload through different mechanisms. In select cases, liver transplantation is recommended. New medications, such as tetrathiomolybdate salts, are currently being investigated in clinical trials. With prompt diagnosis and treatment, prognosis is favorable; however, diagnosing patients before the onset of severe symptoms is a significant concern. Early screening for WD could help in diagnosing patients earlier and improving treatment outcomes.
DBE-Net: Dual Boundary-Guided Attention Exploration Network for Polyp Segmentation
Authors: Ma Haichao , Xu Chao , Nie Chao , Han Jubao , Li Yingjie , Liu Chuanxu
Published: February 2023

Automatic segmentation of polyps during colonoscopy can help doctors accurately find the polyp area and remove abnormal tissues in time to reduce the possibility of polyps transforming into cancer. However, the current polyp segmentation research still has the following problems: blurry polyp boundaries, multi-scale adaptability of polyps, and close resemblances between polyps and nearby normal tissues. To tackle these issues, this paper proposes a dual boundary-guided attention exploration network (DBE-Net) for polyp segmentation. Firstly, we propose a dual boundary-guided attention exploration module to solve the boundary-blurring problem. This module uses a coarse-to-fine strategy to progressively approximate the real polyp boundary. Secondly, a multi-scale context aggregation enhancement module is introduced to accommodate the multi-scale variation of polyps. Finally, we propose a low-level detail enhancement module, which can extract more low-level details and promote the performance of the overall network. Extensive experiments on five polyp segmentation benchmark datasets show that our method achieves superior performance and stronger generalization ability than state-of-the-art methods. Especially for CVC-ColonDB and ETIS, two challenging datasets among the five datasets, our method achieves excellent results of 82.4% and 80.6% in terms of mDice (mean dice similarity coefficient) and improves by 5.1% and 5.9% compared to the state-of-the-art methods.
Lung Ultrasound Score in Neonates with Congenital Diaphragmatic Hernia (CDH-LUS): A Cross-Sectional Study
Authors: Maddaloni Chiara , De Rose Domenico Umberto , Ronci Sara , Bersani Iliana , Martini Ludovica , Caoci Stefano , Capolupo Irma , Conforti Andrea , Bagolan Pietro , Dotta Andrea , Calzolari Flaminia
Published: February 2023

Introduction: The use of a lung ultrasound (LUS) score has been described in the early phases of neonatal respiratory distress syndrome; however, there is still no data regarding the application of the LUS score to neonates with a congenital diaphragmatic hernia (CDH). The objective of this observational cross-sectional study was to explore, for the first time, the postnatal changes in LUS score patterns in neonates with CDH, with the creation of a new specific CDH-LUS score. Methods: We included all consecutive neonates with a prenatal diagnosis of CDH admitted to our Neonatal Intensive Care Unit (NICU) from June 2022 to December 2022 who underwent lung ultrasonography. Lung ultrasonography (LUS) was determined at scheduled time points: (T0) during the first 24 h of life; (T1) at 24–48 h of life; (T2) within 12 h of surgical repair; (T3) a week after the surgical repair. We used a modified LUS score (CDH-LUS), starting from the original 0–3 score. We assigned 4 as a score in the presence of herniated viscera in the hemithorax (liver, small bowel, stomach, or heart in the case of a mediastinal shift) in the preoperative scans or pleural effusions in the postoperative scans. Results: We included in this observational cross-sectional study 13 infants: twelve/13 had a left-sided hernia (2 severe, 3 moderate, and 7 mild cases), while one patient had a right-sided severe hernia. The median CDH-LUS score was 22 (IQR 16–28) during the first 24 h of life (T0), 21 (IQR 15–22) at 24–48 h of life (T1), 14 (IQR 12–18) within 12 h of surgical repair (T2) and 4 (IQR 2–15) a week after the surgical repair (T3). The CDH-LUS significantly dropped over time from the first 24 h of life (T0) to a week after the surgical repair (T3), according to ANOVA for repeated measures. Conclusion: We showed a significant improvement in CDH-LUS scores from the immediate postoperative period, with normal ultrasonographic evaluations a week after surgery in most patients.
Faux Semblants: A Critical Outlook on the Commercialization of Digital Art
Authors: Grba Dejan
Published: February 2023

Heralded by promises for the long-awaited economic empowerment of digital art and the paradigmatic shift of creative production, the art market’s fusion with blockchain technologies and the crypto economy has polarized opinions among artists, cultural workers, and economists. Its capricious dynamics and exuberance largely shroud the continuation of the art market’s ideology and the reinforcement of the disturbing political vectors of the crypto/blockchain complex. In this paper, I address several interrelated aspects of art tokenization in a compact and comprehensive critical framework that may be useful for a constructive discourse of contemporary digital art. By focusing on the core poetic principles of artmaking—which concern the historically informed autonomy of expression and socially responsible freedom of creative thinking—I identify some of the prospects for advancing digital art towards an ethically coherent and epistemologically relevant expressive stratum. The opening sections Introduction, Markets, and Contrivances outline the art market, its adoption of crypto technologies, and its influences on the production and expressive modes of digital art. Sections Ideologies and Myths describe the ideological and technical issues of the crypto economy, while Shams and Fallouts delve into the conceptual shortcomings and ethical, political, and creative consequences of the standard art tokenization rhetoric. The closing sections Options and Conclusion present the considerations for a productive assessment of blockchain technologies in digital art and summarize some of the alternative approaches for navigating and interfacing with the crypto art world.
Robotics in Dentistry: A Narrative Review
Authors: Liu Lipei , Watanabe Megumi , Ichikawa Tetsuo
Published: February 2023

Background: Robotics is progressing rapidly. The aim of this study was to provide a comprehensive overview of the basic and applied research status of robotics in dentistry and discusses its development and application prospects in several major professional fields of dentistry. Methods: A literature search was conducted on databases: MEDLINE, IEEE and Cochrane Library, using MeSH terms: [“robotics” and “dentistry”]. Result: Forty-nine articles were eventually selected according to certain inclusion criteria. There were 12 studies on prosthodontics, reaching 24%; 11 studies were on dental implantology, accounting for 23%. Scholars from China published the most articles, followed by Japan and the United States. The number of articles published between 2011 and 2015 was the largest. Conclusions: With the advancement of science and technology, the applications of robots in dental medicine has promoted the development of intelligent, precise, and minimally invasive dental treatments. Currently, robots are used in basic and applied research in various specialized fields of dentistry. Automatic tooth-crown-preparation robots, tooth-arrangement robots, drilling robots, and orthodontic archwire-bending robots that meet clinical requirements have been developed. We believe that in the near future, robots will change the existing dental treatment model and guide new directions for further development.
Entanglement Swapping and Swapped Entanglement
Authors: Zangi Sultan M. , Shukla Chitra , ur Rahman Atta , Zheng Bo
Published: February 2023

Entanglement swapping is gaining widespread attention due to its application in entanglement distribution among different parts of quantum appliances. We investigate the entanglement swapping for pure and noisy systems, and argue different entanglement quantifiers for quantum states. We explore the relationship between the entanglement of initial states and the average entanglement of final states in terms of concurrence and negativity. We find that if initial quantum states are maximally entangled and we make measurements in the Bell basis, then average concurrence and average negativity of final states give similar results. In this case, we simply obtain the average concurrence (average negativity) of the final states by taking the product of concurrences (negativities) of the initial states. However, the measurement in non-maximally entangled basis during entanglement swapping degrades the average swapped entanglement. Further, the product of the entanglement of the initial mixed states provides an upper bound to the average swapped entanglement of final states obtained after entanglement swapping. The negativity work well for weak entangled noisy states but concurrence gives better results for relatively strong entanglement regimes. We also discuss how successfully the output state can be used as a channel for the teleportation of an unknown qubit.
Galilean Bulk-Surface Electrothermodynamics and Applications to Electrochemistry
Authors: Müller Rüdiger , Landstorfer Manuel
Published: February 2023

In this work, the balance equations of non-equilibrium thermodynamics are coupled to Galilean limit systems of the Maxwell equations, i.e., either to (i) the quasi-electrostatic limit or (ii) the quasi-magnetostatic limit. We explicitly consider a volume Ω, which is divided into Ω+ and Ω− by a possibly moving singular surface S, where a charged reacting mixture of a viscous medium can be present on each geometrical entity (Ω+,S,Ω−). By the restriction to the Galilean limits of the Maxwell equations, we achieve that only subsystems of equations for matter and electromagnetic fields are coupled that share identical transformation properties with respect to observer transformations. Moreover, the application of an entropy principle becomes more straightforward and finally helps estimate the limitations of the more general approach based the full set of Maxwell equations. Constitutive relations are provided based on an entropy principle, and particular care is taken in the analysis of the stress tensor and the momentum balance in the general case of non-constant scalar susceptibility. Finally, we summarise the application of the derived model framework to an electrochemical system with surface reactions.
Entropy and Cross-Level Orderliness in Light of the Interconnection between the Neural System and Consciousness
Authors: Kanaev Ilya A.
Published: February 2023

Despite recent advances, the origin and utility of consciousness remains under debate. Using an evolutionary perspective on the origin of consciousness, this review elaborates on the promising theoretical background suggested in the temporospatial theory of consciousness, which outlines world-brain alignment as a critical predisposition for controlling behavior and adaptation. Such a system can be evolutionarily effective only if it can provide instant cohesion between the subsystems, which is possible only if it performs an intrinsic activity modified in light of the incoming stimulation. One can assume that the world-brain interaction results in a particular interference pattern predetermined by connectome complexity. This is what organisms experience as their exclusive subjective state, allowing the anticipation of regularities in the environment. Thus, an anticipative system can emerge only in a regular environment, which guides natural selection by reinforcing corresponding reactions and decreasing the system entropy. Subsequent evolution requires complicated, layered structures and can be traced from simple organisms to human consciousness and society. This allows us to consider the mode of entropy as a subject of natural evolution rather than an individual entity.
Hospital Organizational Structure and Information Processing: An Entropy Perspective
Authors: Winasti Windi , Berden Hubert , van Merode Frits
Published: February 2023

Organizational structure enables organizations to achieve their goals. The chosen organizational structure determines, to a large extent, the flow of information streams and the manner and extent to which roles, power, and responsibilities are delegated and coordinated to achieve the organization’s goals. In this study, we applied information theory with entropy as the central concept to assess the effectiveness and costs of an organizational structure and its coordination processes. Entropy was used to measure the amount of uncertainty associated with probabilistic events. In the context of organizational design, entropy values can be assigned to specific organizational structures to gain insights into the factors that lead to delays in decision-making. We used Shannon’s entropy theory to quantify Galbraith’s organizational structure and coordination process as applied to the perinatology care system of Radboud University Medical Centre in the Netherlands. Our entropy analysis provided insights into how departments should be partitioned and which coordination mechanisms should be used to achieve organizational goals, such as minimizing delays in decision-making. Particularly, two types of entropy appear to be important: positional entropy and task allocation entropy. These are different dependent variables on the organizational design scenarios. Our analysis shows that entropy is one method to determine optimal organizational structures and coordination processes. Entropy can be used as a concrete way of assessing the effectiveness of organizational design given the level of uncertainty of the environment and the required speed of decision-making.
Observation and Analysis of Ejector Hysteresis Phenomena in the Hydrogen Recirculation Subsystem of PEMFCs
Authors: Li Mingyang , Lin Mingxing , Wang Lei , Wang Yanbo , Pan Fengwen , Zhao Xiaojun
Published: February 2023

The optimization control and efficiency improvement of proton exchange membrane fuel cells (PEMFCs) are being paid more attention. Ejectors have been applied in PEMFC hydrogen recirculation subsystems due to the advantages of a simple structure and no power consumption. However, the hysteresis deviation of a proportional valve ejector is found in the loading and unloading processes such that the hysteresis phenomena can cause deviations in fuel cell control process and affect the power dynamic output stability of PEMFCs. This paper analyzes the causes and effects of proportional valve hysteresis phenomena through experiments and simulations. The results show that the resultant force of proportional valve armature is different in loading and unloading processes because of the hysteresis phenomena, and the maximum flow deviation is up to 0.42 g/s. The hysteresis phenomena of flow rate further cause a deviation of 68.7–89.3 kW in PEMFC power output. Finally, a control compensation model is proposed to effectively reduce the deviation. This study provides a reference for the control and optimization of PEMFC with ejector technology.
Research on the Contribution Mechanism of Vocational Human Capital Characteristics to Income
Authors: Hao Xiaowei , Yang Xi , Kou Kunzhao , Zhang Yu , Guo Congbin
Published: February 2023

Vocational education is an important way to accumulate human capital. Human capital is the core element of economic growth and has huge positive externalities. Building a scientific and effective human capital development system is an important driving force to improve workers’ living standards and promote innovative development. Based on statistical techniques such as Lasso dimensionality reduction, stepwise regression, and partial least squares, as well as on the 2012–2016 China Labor Force Dynamics Survey (CLDS), this paper studies the impact of human capital on workers’ wage income and capital income, and establishes an income-determining equation that can be used for interpretation and forecasting. The empirical results show that education, professional skills, health, and communication ability are important components of human capital and are significantly positively correlated with income. China should build a good and effective human capital development system to increase workers’ income and narrow the income gap among residents.
Exploring Students’ Mathematical Reasoning Behavior in Junior High Schools: A Grounded Theory
Authors: Rohati Rohati , Kusumah Yaya S. , Kusnandi Kusnandi
Published: February 2023

Mathematical reasoning is an essential ability that students must have in every mathematics lesson. However, student behavior during the process of mathematical reasoning has yet to be widely studied. This research explores the mathematical reasoning behavior of selected eighth-grade students to solve problems requiring a mathematical reasoning process. A qualitative methodology based on grounded theory was implemented, which included an in-depth analysis of student answers and student interviews. The data show that students are engaged in imitative, algorithmic, semi-creative, and creative reasoning behavior. Next, an in-depth explanation was carried out for four students from each level of mathematical reasoning behavior. Students from the imitative, algorithmic, semi-creative, and creative reasoning behavior groups showed consistency in answers and behavior for the given problems. The findings of this study can encourage teachers to focus on fostering the highest level of mathematical reasoning, namely creative mathematical reasoning, in students.
EKF-SLAM for Quadcopter Using Differential Flatness-Based LQR Control
Authors: Rauniyar Shyam , Bhalla Sameer , Choi Daegyun , Kim Donghoon
Published: February 2023

SLAM (Simultaneous Localization And Mapping) in unmanned aerial vehicles can be an advantageous proposition during dangerous missions where aggressive maneuvers are paramount. This paper proposes to achieve it for a quadcopter using a differential flatness-based linear quadratic regulator while utilizing sensor measurements of an inertial measurement unit and light detection and ranging considering sensors’ constraints, such as a limited sensing range and field of view. Additionally, a strategy to reduce the computational effort of Extended Kalman Filter-based SLAM (EKF-SLAM) is proposed. To validate the performance of the proposed approach, this work considers a quadcopter traversing an 8-shape trajectory for two scenarios of known and unknown landmarks. The estimation errors for the quadcopter states are comparable for both cases. The accuracy of the proposed method is evident from the Root-Mean-Square Errors (RMSE) of 0.04 m, 0.04 m/s, and 0.34 deg for the position, velocity, and attitude estimation of the quadcopter, respectively, including the RMSE of 0.03 m for the landmark position estimation. Lastly, the averaged computational time for each step of EKF-SLAM with respect to the number of landmarks can help to strategically choose the respective number of landmarks for each step to maximize the use of sensor data and improve performance.
Toward Adaptive Human–Robot Collaboration for the Inclusion of People with Disabilities in Manual Labor Tasks
Authors: Mandischer Nils , Gürtler Marius , Weidemann Carlo , Hüsing Elodie , Bezrucav Stefan-Octavian , Gossen Daniel , Brünjes Vincent , Hüsing Mathias , Corves Burkhard
Published: February 2023

While human–robot collaboration is already integrated in industrial and service robotics applications, it is only used with able-bodied workers. However, collaboration through assistive robots is a major driver toward the inclusion of people with disabilities, which was demonstrated in recent research projects. Currently, inclusive robot workplaces have to be customized toward the work process and the individual needs of the person. Within, robots act along a fixed schedule and are not able to adapt to changes within the process or the needs of the interacting person. Hence, such workplaces are expensive and unappealing for companies of the first labor market, and do not realize the full potential of the technology. In this work, we propose a generalized approach toward the inclusion of people with disabilities with collaborative robots. To this end, we propose a system that analyzes the in situ capabilities of a person using a two-stage reasoning approach. The methodology is based on an ontology that allows the matchmaking of individual capabilities with process requirements. Capabilities are modeled in two time frames, through which fast (e.g., fatigue) and slow effects (e.g., worsening of illness) become distinguishable. The matchmaking is used in task allocation to establish high-level control over the assistive system. By this approach, inclusive workplaces become autonomously adaptive to the in situ capabilities of the individual person, without the need for customization. Therefore, collaborative workplaces become not only inclusive, but a contributor toward a labor market for all.
DpGuard: A Lightweight Attack Detection Method for an Industrial Bus Network
Authors: Li Zecun , Wei Qiang , Ma Rongkuan , Geng Yangyang , Yang Yahui , Lv Zhuo
Published: February 2023

In industrial control systems (ICSs), the PROFIBUS-DP (decentralized peripherals) protocol is widely used for communication between devices. Because PROFIBUS-DP is an unencrypted and insecure bus protocol, attackers can connect to the PROFIBUS-DP system and arbitrarily manipulate I/O process values, which may interrupt the normal operation of industrial equipment, or have more serious consequences. However, due to the complex structures of bus networks and the large number of attack areas, the existing scheme does not monitor all the messages in the industrial head office network and cannot effectively detect semantic attacks. To solve this problem, we propose a novel attack detection system DpGuard. DpGuard automatically builds a finite-state machine model of normal ICS behavior through a large number of historical ICS traffic data. The model includes state events, state transitions, state transition probability, and other normal behavior information. In addition, DpGuard records the execution status of the context data package, uses the real-time captured data package as the input of the model, and judges whether the state event and state transition probability conform to the constraints of the finite-state machine model, so as to identify the legitimate normal behavior of the ICS. Our proposal was evaluated using two Siemens PLCs (programmable logic controllers) deployed on the PROFIBUS-DP system. The experimental results demonstrated that the scheme could accurately detect fault injection and semantic attacks. Compared with other detection models, our scheme presented an improved detection performance, with a detection accuracy of 99.80%.
Wideband Direction-of-Arrival Estimation Based on Hierarchical Sparse Bayesian Learning for Signals with the Same or Different Frequency Bands
Authors: Yang Yixin , Zhang Yahao , Yang Long , Wang Yong
Published: February 2023

Wideband sparse Bayesian learning (WSBL) based on joint sparsity achieves high direction-of-arrival (DOA) estimation precision when the signals share the same frequency band. However, when the signal frequency bands are non-overlapped or partially overlapped, i.e., the frequency bands are different, the performance of the method degrades due to the improper prior on signal. This paper aims at extending the WSBL to a more general version, which is also suitable for the cases where the signal frequency bands are non-overlapped or partially overlapped. Given that the signals are sparsely distributed in the space, the signal matrix whose column is composed of the signal in each frequency bin is row-sparse. Moreover, the signal vectors in some frequency bins have different sparse supports when the signals occupy the different frequency bands. Therefore, a hierarchical sparse prior is assigned to the signal matrix, where a set of hyperparameters are used to ensure the row-sparsity and the other set are used to adjust the signal sparsity in each frequency bin. The DOAs are finally estimated in the Bayesian framework. The simulation results verify that the proposed method achieves good performance on estimation precision in both the same and different frequency band scenarios.
Additive Manufacturing of a Miniaturized X-Band Single-Ridge Waveguide Magic-T for Monopulse Radar Applications
Authors: Rossi Riccardo , Vincenti Gatti Roberto , Calignano Flaviana , Iuliano Luca , Chiarandini Simona
Published: February 2023

A low-profile single-ridge waveguide magic-T is proposed as a combination of two T-junctions at an X band. A slot coupling technique is used to reduce the component dimensions in the E-plane, thus leading to a low profile. The device can assume two configurations by arranging the sum and difference ports in the same or opposite direction, an attractive feature in the design of beamforming networks with complex routing. A magic-T prototype is fabricated using laser powder bed fusion additive manufacturing techniques. Good agreement between simulations and measurements is found.
DV-Hop Location Algorithm Based on RSSI Correction
Authors: Zhang Wanli , Yang Xiaoying
Published: February 2023

To increase the positioning accuracy of Distance Vector-Hop (DV-Hop) algorithm in non-uniform networks, an improved DV-Hop algorithm based on RSSI correction is proposed. The new algorithm first quantizes hops between two nodes by the ratio of the RSSI value between two nodes and the benchmark RSSI value, divides the hops continuously, calculates the average hop distance according to the Minimum Mean Square Error (MMSE) criterion of the best index based on the quantized hops, and then adds hop distance matching factor to the fitness function of each anchor node into the calculation of the hop distance fitness function to weight the fitness function. The change index value is introduced to obtain more accurate hop distance value, and then the estimation error of unknown node (UN) coordinate is modified by using the distance relationship between the UN and the nearest beacon node (BN), and the modified coordination position is further modified by using the triangle centroid to improve the accuracy of node positioning in the irregular network. The experimental results show that compared with the original DV-Hop, improved DV-Hop1, improved DV-Hop2 and improved DV-Hop3, the localization error of the improved algorithm in this paper is reduced by 58%, 45%, 34%, and 29%, respectively, on average, in the two network environments. Without increasing the hardware cost and energy consumption, the improved algorithm has excellent localization performance.
Budgeted Thompson Sampling for IRS Enabled WiGig Relaying
Authors: Hashima Sherief , Hatano Kohei , Takimoto Eiji , Mohamed Ehab Mahmoud
Published: February 2023

Intelligent reconfigurable surface (IRS) is a competitive relaying technology to widen the WiGig coverage range, as it offers an effective means of addressing blocking issues. However, selecting the optimal IRS relay for maximum attainable data rate is a time-consuming process, as it requires WiGig beamforming training (BT) to tune the phase shifts (PSs) for WiGig base station (WGBS) and IRS relays. This paper proposes a self-learning-based budgeted Thomson sampling approach for IRS relay probing (BTS-IRS) to address this challenge. The BT time cost of probing the IRS relay is incorporated into the main BTS formula, where both payoff and cost posterior distributions are sampled separately, their ratio is estimated, and the arm/IRS relay with the highest ratio is decided. This enables the IRS relay to be chosen with the lowest BT time cost. Numerical results demonstrate the improved performance of the BTS-IRS relaying technique regarding BT time consumption/cost, spectral efficiency, and attainable data rate when compared to other benchmarks.