bluuebunny/crossref_metadata_2025 huggingface dataset:
A Three-Way Acceleration Approach for Interval-Valued Multi-Attribute Decision-Making Problems
Authors: Liu Yue , Xiao Yang , Li Tieshan , Jia Yunjie
Published: July 2023

As an essential part of modern intelligent decision-making science, multi-attribute decision-making problems can effectively select and rank all candidate schemes under multiple indicators. Because of the complexity of the real environment and the uncertainty of the decision-making problem, interval numbers are often used to represent the evaluation information of the object. The existing methods of the multi-attribute decision-making problems rarely use the object set but give the decision results by selection or ranking, which often have strong subjectivity. We propose a ranking method from an acceleration viewpoint based on the three-way decision model to solve the interval-valued multi-attribute decision-making problem. A distance measure of two objects is a measure that describes the relationship between objects. Therefore, the fuzzy dominance distance is introduced to express order relations among objects. First, we present a method to compare any two interval numbers, which converts interval numbers into connection numbers according to the characteristics of interval numbers in multi-attribute decision-making problems. Second, the three-way decision theory is introduced to divide the object set into high, medium, and low dominance regions for the speed and rationality of decision-making. Finally, the multi-attribute decision-making problems can be simplified into the problem of selection in three regions by ranking the objects of the selected region. Unlike traditional methods, the experiments demonstrate that our proposed method has the lowest cost. Our method is shown to be efficient and can obtain comparable results.
An Improved LSTM-Based Failure Classification Model for Financial Companies Using Natural Language Processing
Authors: Wang Zhan , Kim Soyeon , Joe Inwhee
Published: July 2023

The Korean e-commerce market represents a large percentage of the global retail distribution market, a market that continues to grow each year, and online payments are rapidly becoming a mainstream payment method. As e-commerce becomes more active, many companies that support electronic payments are increasing the number of franchisees. Electronic payments have become an indispensable part of people’s lives. However, the types of statistical information on the results of electronic payment transactions are not consistent across companies, and it is difficult to automatically determine the error status of a transaction if no one directly confirms the error messages generated during payment. To address these issues, we propose an optimized LSTM model. In this study, we classify the error content in statistical information based on natural language processing to determine the error status of the current failed transaction. We collected 11,865 response messages from various vendors and financial companies and labelled them with an LSTM classifier model to create a dataset. We then trained this dataset with simple RNN, LSTM, and GRU models and compared their performance. The results show that the optimized LSTM model with the attention layer added to the dropout layer and the bidirectional recursive layer achieves an accuracy of about 92% or more. When the model is applied to e-commerce services, any error in the transaction status of the system can be automatically detected by the model.
Concentration Influence of Complexing Agent on Electrodeposited Zn-Ni Alloy
Authors: Son Byung-Ki , Choi Ji-Won , Jeon Su-Byung , Son In-Joon
Published: July 2023

Zinc (Zn) coatings, which are widely used to protect metals from corrosion, can be further improved by alloying with nickel (Ni). Increasing the Ni content enhances the corrosion-resistant properties of the Zn coating. This study investigated the effect of tetraethylenepentamine (TEPA) concentration on the Ni content and the properties of the Zn-Ni alloy coating. Zn-Ni alloy coatings were electrodeposited via the Hull cell test with TEPA concentrations of 0, 0.035, 0.07, and 0.1 M. We found that increasing the TEPA concentration improved the brightness of the coating at low current density and influenced the crystal orientation and morphology. When the TEPA concentration was increased to 0.7 M, the Ni content of the Zn-Ni alloy coating significantly increased before leveling off. However, the thickness of the coatings decreased with increasing TEPA concentration. The electrochemical behavior of the Zn-Ni alloy electrodeposition was validated via partial polarization curves of the Zn and Ni depositions.
Unified Plasticity Potential of Soils
Authors: Firincioglu Bekir Salih , Bilsel Huriye
Published: July 2023

Soil plasticity characteristics are of great importance to practicing engineers and academics due to their wide range of applications mainly concerning settlement and soil strength assessment and volume change behavior. Therefore, assigning a plasticity value to soils under any discipline concerning soil engineering is critical. This is almost always carried out by determining plasticity index of soils in geotechnical engineering. However, overall plasticity characteristics of soils might not be reflected by using plasticity index alone. This research demonstrates the creation of a single model to define the plasticity potential of soils by using multivariate statistical techniques. Various soil properties including mineralogical features were integrated into the model. Some of these properties explained the soil plasticity positively and some of them negatively. The difference in plasticity characteristics of clayey soils were also identified. The model is created to be applied simply by using only two inputs for worldwide suitability. A single expression and two different scaled charts are proposed along with six ranges of plasticity potential for easy and broader application. This model proved that plasticity index alone needs refinement in practical applications.
Research on Hybrid Recommendation Model for Personalized Recommendation Scenarios
Authors: Ni Wenkai , Du Yanhui , Ma Xingbang , Lv Haibin
Published: July 2023

One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowledge graphs, but it is susceptible to localization issues in user portrait updating. In this study, we propose NRH (Node2vec-side and RippleNet Hybrid Model), a hybrid recommendation model based on RippleNet that uses Node2vec-side for item portrait modeling and explores potential association relationships of items; the user portrait is split into two parts, namely, a static history portrait and a dynamic preference portrait; the NRH model adopts a hybrid recommendation approach based on collaborative filtering and a knowledge graph to obtain the user’s preferences on three publicly accessible datasets; and comparison experiments with the mainstream model are lastly carried out. The AUC and ACC increased, respectively, by 0.9% to 29.5% and 1.6% to 31.4% in the MovieLens-1M dataset, by 1.5% to 17.1% and 4.4% to 18.7% in the Book-Crossing dataset, and by 0.8% to 27.9% and 2.9% to 24.1% in the Last.FM dataset. The RippleNet model was used for comparison experiments comparing suggestion diversity. According to the experimental findings, the NRH model performs better in accuracy and variety than the popular customized knowledge graph recommendation algorithms now in use.
The Evolution of Triamcinolone Acetonide Therapeutic Use in Retinal Diseases: From Off-Label Intravitreal Injection to Advanced Nano-Drug Delivery Systems
Authors: Aceves-Franco Luis Abraham , Sanchez-Aguilar Oscar Eduardo , Barragan-Arias Allen Rafael , Ponce-Gallegos Marco Antonio , Navarro-Partida Jose , Santos Arturo
Published: July 2023

Ophthalmic drug delivery to the posterior segment of the eye has been challenging due to the complex ocular anatomy. Intravitreal injection of drugs was introduced to deliver therapeutic doses in the posterior segment. Different posterior segment diseases including age-related macular degeneration, diabetic macular edema, retinal vein occlusions, uveitis, and cystoid macular edema, among others, have been historically treated with intravitreal corticosteroids injections, and more recently with intravitreal corticosteroids drug implants. Triamcinolone acetonide (TA) is the most frequently used intraocular synthetic corticosteroid. Using nanoparticle-based TA delivery systems has been proposed as an alternative to intravitreal injections in the treatment of posterior segment diseases. From these novel delivery systems, topical liposomes have been the most promising strategy. This review is oriented to exhibit triamcinolone acetonide drug evolution and its results in treating posterior segment diseases using diverse delivery platforms.
Efficacy and Safety of the Use of SGLT2 Inhibitors in Patients on Incremental Hemodialysis: Maximizing Residual Renal Function, Is There a Role for SGLT2 Inhibitors?
Authors: De La Flor José C. , Villa Daniel , Cruzado Leónidas , Apaza Jacqueline , Valga Francisco , Zamora Rocío , Marschall Alexander , Cieza Michael , Deira Javier , Rodeles Miguel
Published: July 2023

SGLT-2i are the new standard of care for diabetic kidney disease (DKD), but previous studies have not included patients on kidney replacement therapy (KRT). Due to their high risk of cardiovascular, renal complications, and mortality, these patients would benefit the most from this therapy. Residual kidney function (RKF) conveys a survival benefit and cardiovascular health among hemodialysis (HD) patients, especially those on incremental hemodialysis (iHD). We retrospectively describe the safety and efficacy of SGLT2i regarding RKF preservation in seven diabetic patients with different clinical backgrounds who underwent iHD (one or two sessions per week) during a 12-month follow-up. All patients preserved RKF, measured as residual kidney urea clearance (KrU) in 24 h after the introduction of SGLT2i. KrU levels improved significantly from 4.91 ± 1.14 mL/min to 7.28 ± 1.68 mL/min at 12 months (p = 0.028). Pre-hemodialysis blood pressure improved 9.95% in mean systolic blood pressure (SBP) (p = 0.015) and 10.95% in mean diastolic blood pressure (DBP) (p = 0.041); as a result, antihypertensive medication was modified. Improvements in blood uric acid, hemoglobin A1c, urine albumin/creatinine ratio (UACR), and 24 h proteinuria were also significant. Regarding side effects, two patients developed uncomplicated urinary tract infections that were resolved. No other complications were reported. The use of SGLT2i in our sample of DKD patients starting iHD on a 1–2 weekly regimen appears to be safe and effective in preserving RKF.
A Torque Control Strategy for a Robotic Dolphin Platform Based on Angle of Attack Feedback
Authors: Wang Tianzhu , Yu Junzhi , Chen Di , Meng Yan
Published: July 2023

Biological fish can always sense the state of water flow and regulate the angle of attack in time, so as to maintain the highest movement efficiency during periodic flapping. The biological adjustment of the caudal fin’s angle of attack (AoA) depends on the contraction/relaxation of the tail muscles, accompanying the variation in tail stiffness. During an interaction with external fluid, it helps to maintain the optimal angle of attack during movement, to improve the propulsion performance. Inspired by this, this paper proposes a tail joint motion control scheme based on AoA feedback for the high-speed swimming of bionic dolphins. Firstly, the kinematic characteristics of the designed robot dolphin are analyzed, and the hardware basis is clarified. Second, aiming at the deficiency of the tail motor, which cannot effectively cooperate with the waist joint motor during high-frequency movement, a compensation model for the friction force and latex skin-restoring force is designed, and a joint angle control algorithm based on fuzzy inference is proposed to realize the tracking of the desired joint angle for the tail joint in torque mode. In addition, a tail joint closed-loop control scheme based on angle of attack feedback is proposed to improve the motion performance. Finally, experiments verify the effectiveness of the proposed motion control scheme.
Bearing Capacity of Transmission Poles under Combined Wind and Rain Excitations Based on the Deep Learning Method
Authors: Fu Xing , Xu Xu , Liu Huijuan , Wang Wenming , Zhu Dengjie
Published: July 2023

Generally, only wind effect is considered in the collapse evaluation of transmission poles (TPs). However, during a typhoon landing, the rainfall is usually very heavy and the influence of the wind and rainfall should be considered simultaneously. To estimate the bearing capacity of TPs accurately during a typhoon, this paper proposes a method for predicting the water content distribution of soil based on the deep learning method. Then, the earth pressure distribution related to the rainfall is obtained. Furthermore, according to the static balance principle, the ultimate overturning moment of the TPs is obtained, and the corresponding critical wind speed is determined via a numerical simulation. Finally, a case study is tested and the collapse evaluation of TPs under the combined effects of wind and rainfall is obtained. The results show that the critical wind speed when considering rainfall is less than the value when ignoring the rainfall effect. The traditional method overestimates the structural safety of the TPs because the rainfall has a significant reduction on the bearing capacity of TPs.
Bibliometric Analysis on the Application of Fuzzy Logic into Marketing Strategy
Authors: Rosário Albérico Travassos , Dias Joana Carmo , Ferreira Hélder
Published: July 2023

Fuzzy marketing considers the degree to which a customer belongs to specific segments and subsequently allows them to be targeted with messages that engage them emotionally. To better understand the application and importance of fuzzy logic in marketing strategy, we developed a systematic literature review with bibliometric analysis to examine a sample of 96 studies from the SCOPUS database to identify research activity on this topic until December 2022. It was possible to create a connection between these concepts, marketing and fuzzy logic, to increase the efforts of marketing professionals. For instance, the results show that adopting approaches such as fuzzy marketing or the fuzzy marketing mix model enhances the company’s capability to build stronger customer relationships, enhance profitability, and improve marketing performance.
Actin Cytoskeleton Polymerization and Focal Adhesion as Important Factors in the Pathomechanism and Potential Targets of Mucopolysaccharidosis Treatment
Authors: Gaffke Lidia , Rintz Estera , Pierzynowska Karolina , Węgrzyn Grzegorz
Published: July 2023

The main approach used in the current therapy of mucopolysaccharidosis (MPS) is to reduce the levels of glycosaminoglycans (GAGs) in cells, the deposits considered to be the main cause of the disease. Previous studies have revealed significant differences in the expression of genes encoding proteins involved in many processes, like those related to actin filaments, in MPS cells. Since the regulation of actin filaments is essential for the intracellular transport of specific molecules, the process which may affect the course of MPSs, the aim of this study was to evaluate the changes that occur in the actin cytoskeleton and focal adhesion in cells derived from patients with this disease, as well as in the MPS I mouse model, and to assess whether they could be potential therapeutic targets for different MPS types. Western-blotting, flow cytometry and transcriptomic analyses were employed to address these issues. The levels of the key proteins involved in the studied processes, before and after specific treatment, were assessed. We have also analyzed transcripts whose levels were significantly altered in MPS cells. We identified genes whose expressions were changed in the majority of MPS types and those with particularly highly altered expression. For the first time, significant changes in the expression of genes involved in the actin cytoskeleton structure/functions were revealed which may be considered as an additional element in the pathogenesis of MPSs. Our results suggest the possibility of using the actin cytoskeleton as a potential target in therapeutic approaches for this disease.
Drug Regulatory-Compliant Validation of a qPCR Assay for Bioanalysis Studies of a Cell Therapy Product with a Special Focus on Matrix Interferences in a Wide Range of Organ Tissues
Authors: Schröder Hannes M. , Niebergall-Roth Elke , Norrick Alexandra , Esterlechner Jasmina , Ganss Christoph , Frank Markus H. , Kluth Mark A.
Published: July 2023

Quantitative polymerase chain reaction (qPCR) has emerged as an important bioanalytical method for assessing the pharmacokinetics of human-cell-based medicinal products after xenotransplantation into immunodeficient mice. A particular challenge in bioanalytical qPCR studies is that the different tissues of the host organism can affect amplification efficiency and amplicon detection to varying degrees, and ignoring these matrix effects can easily cause a significant underestimation of the true number of target cells in a sample. Here, we describe the development and drug regulatory-compliant validation of a TaqMan® qPCR assay for the quantification of mesenchymal stromal cells in the range of 125 to 20,000 cells/200 µL lysate via the amplification of a human-specific, highly repetitive α-satellite DNA sequence of the chromosome 17 centromere region HSSATA17. An assessment of matrix effects in 14 different mouse tissues and blood revealed a wide range of spike recovery rates across the different tissue types, from 11 to 174%. Based on these observations, we propose performing systematic spike-and-recovery experiments during assay validation and correcting for the effects of the different tissue matrices on cell quantification in subsequent bioanalytical studies by multiplying the back-calculated cell number by tissue-specific factors derived from the inverse of the validated percent recovery rate.
Repeated Social Defeat Stress Induces HMGB1 Nuclear Export in Prefrontal Neurons, Leading to Social Avoidance in Mice
Authors: Kitaoka Shiho , Tomohiro Ayaka , Ukeshima Shinya , Liu Keyue , Wake Hidenori , Kimura Shinya H. , Yamamoto Yasuhiko , Nishibori Masahiro , Furuyashiki Tomoyuki
Published: July 2023

Inflammation has been associated with depression, and innate immune receptors, such as the Toll-like receptor (TLR) 2/4 in the medial prefrontal cortex (mPFC), are crucial for chronic stress-induced depression-related behaviors in mice. HMGB1, a putative ligand for TLR2/4, has been suggested to promote depression-related behaviors under acute stress. However, the roles of endogenous HMGB1 under chronic stress remain to be investigated. Here, we found that the cerebroventricular infusion of HMGB1 proteins blocked stress-induced social avoidance and that HMGB1-neutralizing antibodies augmented repeated social defeat stress-induced social avoidance in mice, suggesting the antidepressive-like effect of HMGB1 in the brain. By contrast, the infusion of HMGB1-neutralizing antibodies to the mPFC and HMGB1 knockout in α-CaMKII-positive forebrain neurons attenuated the social avoidance, suggesting the pro-depressive-like effect of HMGB1 released from prefrontal neurons under chronic stress. In addition, repeated social defeat stress induced HMGB1 nuclear export selectively in mPFC neurons, which was abolished in the mice lacking RAGE, one of HMGB1 receptors, suggesting the positive feedback loop of HMGB1-RAGE signaling under chronic stress. These findings pave the way for identifying multiple roles of HMGB1 in the brain for chronic stress and depression.
Preparation and Enhanced Acetone-Sensing Properties of ZIF-8-Derived Co3O4@ZnO Microspheres
Authors: Fan Xiangxiang , Yang Susu , Huang Chun , Lu Yujie , Dai Pan
Published: July 2023

In this work, ZIF-8-derived Co3O4@ZnO microspheres were prepared by a liquid-phase concentration-controlled nucleation strategy. The results of the material characterization showed that Co3O4@ZnO microspheres were obtained, and the surface structure could be controlled with the concentration of the ligand. Compared with pure Co3O4 microspheres, the operating temperature of optimized Co3O4@ZnO microspheres increased by 90 °C after the gas-sensing test. The response to 50 ppm acetone of Co3O4@ZnO microspheres was 4.5 times higher than that of pure Co3O4, and the detection limit reached 0.5 ppm. Meanwhile, Co3O4@ZnO microspheres showed a shorter response-recovery time and better selectivity. The enhanced-sensing mechanism of the ZIF-8-derived Co3O4@ZnO microspheres was also analyzed.
Laparotomy versus Peritoneal Drainage as Primary Treatment for Surgical Necrotizing Enterocolitis or Spontaneous Intestinal Perforation in Preterm Neonates: A Systematic Review and Meta-Analysis
Authors: Solis-Garcia Gonzalo , Pierro Agostino , Jasani Bonny
Published: July 2023

Aim: to systematically review and meta-analyze the impact on morbidity and mortality of peritoneal drainage (PD) compared to laparotomy (LAP) in preterm neonates with surgical NEC (sNEC) or spontaneous intestinal perforation (SIP). Methods: Medical databases were searched until June 2022 for studies comparing PD and LAP as primary surgical treatment of preterm neonates with sNEC or SIP. The primary outcome was survival during hospitalization; predefined secondary outcomes included need for parenteral nutrition at 90 days, time to reach full enteral feeds, need for subsequent laparotomy, duration of hospitalization and complications. Results: Three RCTs (N = 493) and 49 observational studies (N = 19,447) were included. No differences were found in the primary outcome for RCTs, but pooled observational data showed that, compared to LAP, infants with sNEC/SIP who underwent PD had lower survival [48 studies; N = 19,416; RR 0.85; 95% CI 0.79–0.90; GRADE: low]. Observational studies also showed that the subgroup of infants with sNEC had increased survival in the LAP group (30 studies; N = 9370; RR = 0.82; 95% CI 0.72–0.91; GRADE: low). Conclusions: Compared to LAP, PD as primary surgical treatment for sNEC or SIP has similar survival rates when analyzing data from RCTs. PD was associated with lower survival rates in observational studies.
Clinical Outcomes in a Large Canadian Centralized CLL Clinic Based on Treatment and Molecular Factors over a Decade
Authors: Yang Jiayu , Yang Lin , Tordon Bryan , Bucher Oliver , Nugent Zoann , Landego Ivan , Bourrier Nicole , Uminski Kelsey , Brown Kevin , Squires Mandy , Marshall Aaron J. , Katyal Sachin , Mahmud Salah , Decker Kathleen , Geirnaert Marc , Dawe David E. , Gibson Spencer B. , Johnston James B. , Banerji Versha
Published: July 2023

FISH cytogenetics, TP53 sequencing, and IGHV mutational status are increasingly used as prognostic and predictive markers in chronic lymphocytic leukemia (CLL), particularly as components of the CLL International Prognostic Index (CLL-IPI) and in directing therapy with novel agents. However, testing outside of clinical trials is not routinely available in Canada. As a centralized CLL clinic at CancerCare Manitoba, we are the first Canadian province to evaluate clinical outcomes and survivorship over a long period of time, incorporating the impact of molecular testing and the CLL-IPI score. We performed a retrospective analysis on 1315 patients diagnosed between 1960 and 2018, followed over a 12-year period, where 411 patients had molecular testing and 233 patients had a known CLL-IPI score at the time of treatment. Overall, 40.3% (n = 530) of patients received treatment, and 47.5% (n = 252) of patients received multiple lines of therapy. High-risk FISH and CLL-IPI (4-10) were associated with higher mortality (HR 2.03, p = 0.001; HR 2.64, p = 0.002), consistent with other studies. Over time, there was an increase in the use of targeted agents in treated patients. The use of Bruton’s tyrosine kinase inhibitors improved survival in patients with unmutated IGHV and/or TP53 aberrations (HR 2.20, p = 0.001). The major cause of death in patients who received treatment was treatment/disease-related (32%, n = 42) and secondary malignancies (57%, n = 53) in those who were treatment-naïve. Our data demonstrate the importance of molecular testing in determining survivorship in CLL and underpinning the likely immune differences in outcomes for those treated for CLL.
Predicting Complicated Appendicitis in Children: Pros and Cons of a New Score Combining Clinical Signs, Laboratory Values, and Ultrasound Images (CLU Score)
Authors: Bekiaridou Konstantina , Kambouri Katerina , Giatromanolaki Alexandra , Foutzitzi Soultana , Kouroupi Maria , Aggelidou Maria , Deftereos Savas
Published: July 2023

Background: This retrospective study aimed to combine the clinical signs, laboratory values, and ultrasound images of 199 children with acute appendicitis in order to create a new predictive score for complicated appendicitis in children. Methods: The study included children who had clinical examination of abdominal pain (description of pain, anorexia, body temperature, nausea or vomiting, duration of symptoms), laboratory findings on admission (white blood cell, platelets, neutrophils, C-reactive protein), preoperative abdominal ultrasound, and histopathological report after an operation for appendicitis in their records during the period from January 2016 to February 2022. Results: According to the statistical analysis of the values using multivariate logistic regression models, the patients with appendiceal diameter ≥ 8.45 mm, no target sign appearance, appendicolith, abscess, peritonitis, neutrophils ≥ 78.95%, C-reactive protein ≥ 1.99 mg/dL, body temperature ≥ 38 °C, pain migration to right lower quadrant, and duration of symptoms < 24 h were more likely to suffer from complicated appendicitis. The new score was comprised of the 10 variables that were found statistically significant in the multivariate logistic model. Each of these variables was assigned a score of 1 due to the values that were associated with complicated appendicitis. Conclusions: A cutoff value of ≥4 has been a good indicator of the final score. The sensitivity with the usage of this score is 81.1%, the specificity 82.4%, the PPV 73.2%, the NPV approaches 88% and finally the accuracy is 81.9%. Also, the pros and cons of this score are discussed in this study.
A Multivariant Surrogate Neutralization Assay Identifies Variant-Specific Neutralizing Antibody Profiles in Primary SARS-CoV-2 Omicron Infection
Authors: Springer David Niklas , Traugott Marianna , Reuberger Elisabeth , Kothbauer Klaus Benjamin , Borsodi Christian , Nägeli Michelle , Oelschlägel Theresa , Kelani Hasan , Lammel Oliver , Deutsch Josef , Puchhammer-Stöckl Elisabeth , Höltl Eva , Aberle Judith Helene , Stiasny Karin , Weseslindtner Lukas
Published: July 2023

Primary infection with the Omicron variant of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) can be serologically identified with distinct profiles of neutralizing antibodies (nAbs), as indicated by high titers against the Omicron variant and low titers against the ancestral wild-type (WT). Here, we evaluated whether a novel surrogate virus neutralization assay (sVNT) that simultaneously quantifies the binding inhibition of angiotensin-converting enzyme 2 (ACE2) to the proteins of the WT- and Omicron-specific receptor-binding domains (RBDs) can identify nAb profiles after primary Omicron infection with accuracy similar to that of variant-specific live-virus neutralization tests (NTs). Therefore, we comparatively tested 205 samples from individuals after primary infection with the Omicron variant and the WT, and vaccinated subjects with or without Omicron breakthrough infections. Indeed, variant-specific RBD-ACE2 binding inhibition levels significantly correlated with respective NT titers (p < 0.0001, Spearman’s r = 0.92 and r = 0.80 for WT and Omicron, respectively). In addition, samples from individuals after primary Omicron infection were securely identified with the sVNT according to their distinctive nAb profiles (area under the curve = 0.99; sensitivity: 97.2%; specificity: 97.84%). Thus, when laborious live-virus NTs are not feasible, the novel sVNT we evaluated in this study may serve as an acceptable substitute for the serological identification of individuals with primary Omicron infection.
Joint Trajectory Planning, Service Function Deploying, and DAG Task Scheduling in UAV-Empowered Edge Computing
Authors: Jia Runa , Zhao Kuang , Wei Xianglin , Zhang Guoliang , Wang Yangang , Tu Gangyi
Published: July 2023

Efficient task scheduling plays a key role in unmanned aerial vehicle (UAV)-empowered edge computing due to the limitation in energy supply and computation resource on the UAV platforms. This problem becomes much more complicated when the processing-dependent tasks that can be described as directed acyclic graphs (DAGs) and each of their components can only be processed on a virtual machine or container that deploys the desired service function (SF). In this paper, we first build an optimization problem that aims to minimize the completion time of all DAG tasks subject to constraints including task dependency, computation resource occupied by the UAVs, etc. To tackle this problem, a genetic algorithm-based joint deployment and scheduling algorithm, named GA-JoDeS, is put forward, since solving the established 0–1 integer programming problem in polynomial time is infeasible. Subtask offloading decision and UAV position are encoded into the chromosome in the GA-JoDeS algorithm, and the fitness value of an individual is decided by the maximum completion time of all DAG tasks. Through selection, crossover, and mutation, the GA-JoDeS algorithm evolves until it determines the individual with the optimal fitness value as the suboptimal solution to the problem. To evaluate the performance of the proposal, a series of simulations is conducted, and three traditional methods are chosen as comparison benchmarks. The results show that the GA-JoDeS algorithm can convergence quickly, and it can effectively reduce the completion time of DAG tasks with different parameter settings.
U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations
Authors: Morfin Veytia Andres , Badea Calin Andrei , Patrinopoulou Niki , Daramouskas Ioannis , Ellerbroek Joost , Lappas Vaios , Kostopoulos Vassilios , Hoekstra Jacco
Published: July 2023

The interest in urban air mobility as a potential solution for urban congestion is steadily growing. Air operations in urban areas can present added complexity as compared with traditional air traffic management. As a result, it is necessary to test and develop novel airspace designs and rules. As airspace in urban areas is a scarce resource, creating structures and rules that effectively utilise the airspace is an important challenge. This work specifically focuses on layered airspace design in urban operations constrained to fly between the existing buildings. Two design parameters of airspace design are investigated with two sub-experiments. Sub-experiment 1 investigates layer function assignment by comparing concepts from previous research with different layer assignment distributions. Sub-experiment 2 investigates the flight rules of vertical distribution of traffic within the airspace, to determine whether this is best achieved in a static (pre-allocated) or dynamic manner. Both sub-experiments analyse the overall system safety, route duration, and route distance under increasing traffic demand. Results reveal that the importance of cruising airspace is apparent at high densities. Results also shows that the safest layer allocation flight rule depends on the traffic density. At lower densities dynamic rules help to spread traffic locally. However, when the airspace is saturated it is safer to pre-allocate flight heights if achieved uniformly.
Attention-Guided Huber Loss for Head Pose Estimation Based on Improved Capsule Network
Authors: Zhong Runhao , He Li , Wang Hongwei , Yuan Liang , Li Kexin , Liu Zhening
Published: July 2023

Head pose estimation is an important technology for analyzing human behavior and has been widely researched and applied in areas such as human–computer interaction and fatigue detection. However, traditional head pose estimation networks suffer from the problem of easily losing spatial structure information, particularly in complex scenarios where occlusions and multiple object detections are common, resulting in low accuracy. To address the above issues, we propose a head pose estimation model based on the residual network and capsule network. Firstly, a deep residual network is used to extract features from three stages, capturing spatial structure information at different levels, and a global attention block is employed to enhance the spatial weight of feature extraction. To effectively avoid the loss of spatial structure information, the features are encoded and transmitted to the output using an improved capsule network, which is enhanced in its generalization ability through self-attention routing mechanisms. To enhance the robustness of the model, we optimize Huber loss, which is first used in head pose estimation. Finally, experiments are conducted on three popular public datasets, 300W-LP, AFLW2000, and BIWI. The results demonstrate that the proposed method achieves state-of-the-art results, particularly in scenarios with occlusions.
Discovering Low-Dimensional Descriptions of Multineuronal Dependencies
Authors: Mitskopoulos Lazaros , Onken Arno
Published: July 2023

Coordinated activity in neural populations is crucial for information processing. Shedding light on the multivariate dependencies that shape multineuronal responses is important to understand neural codes. However, existing approaches based on pairwise linear correlations are inadequate at capturing complicated interaction patterns and miss features that shape aspects of the population function. Copula-based approaches address these shortcomings by extracting the dependence structures in the joint probability distribution of population responses. In this study, we aimed to dissect neural dependencies with a C-Vine copula approach coupled with normalizing flows for estimating copula densities. While this approach allows for more flexibility compared to fitting parametric copulas, drawing insights on the significance of these dependencies from large sets of copula densities is challenging. To alleviate this challenge, we used a weighted non-negative matrix factorization procedure to leverage shared latent features in neural population dependencies. We validated the method on simulated data and applied it on copulas we extracted from recordings of neurons in the mouse visual cortex as well as in the macaque motor cortex. Our findings reveal that neural dependencies occupy low-dimensional subspaces, but distinct modules are synergistically combined to give rise to diverse interaction patterns that may serve the population function.
“Teachers Are Rock Stars!” Rethinking Teaching and Teacher Education in a Post-Pandemic World: Innovative Disruption and Silver Linings
Authors: Pendergast Donna , O’Brien Mia
Published: July 2023

The COVID-19 pandemic amplified a pre-existing global education crisis. As teachers and systems alike have pivoted to keep the education of the next generation underway, the liminal space between normal and the new normal has provided the opportunity for innovative disruption and transformation to confront the status quo in ways that were previously unimaginable. It is in this space of possibility, in mid-2022, that 466 education stakeholders including teachers, academics, system leaders, and university students explored the idea of rethinking teaching and teacher education in a post-pandemic world. The participants of the study responded to a series of five questions about impact, spaces for transformation, and possible legacies. Inductive qualitative coding was employed to generate themes from the responses, and polling used to determine the frequency of agreement followed. Among the findings were insights into their experiences and the spaces for innovative disruption, with three areas most notable: the opportunity for valuing teachers’ expertise, noting their ‘rock star’ status during the lockdown phase of the pandemic; the need to focus on student and teacher wellbeing, equity and diversity; and the opportunity to innovate for enhanced flexibility for work structures, learning and connecting beyond the classroom.
A Metalens Design for On- and Off-Center Focusing with Amorphous Silicon Hydrogenated (a-Si:H)-Based 1D Array in Visible Spectrum
Authors: Ali Jawad , Ahmad Ashfaq , Choi Dong-you
Published: July 2023

The use of optical systems in medical imaging, computer electronics, large-scale industries, and space exploration is common. The performance of these devices is closely related to the compactness and fast responses of lenses that are used in these optical systems. Typical lenses suffer from several key issues, including limited efficiency, significant size, and the presence of diffraction-induced distortions that compromise their overall performance. Herein these limitations are addressed by designing and simulating an ultra-thin compact metalens also known as a flat lens using a dielectric metasurface. A 1D array of 31 nano-cylinders is placed on a glass substrate that is utilized for focusing the incident wave both on and off center in the focal plane using simulations. The nano-cylinders are comprised of amorphous silicon hydrogenated (a-Si:H), which has a varying radius in a 1D configuration. Amorphous silicon hydrogenated (a-Si:H) nano-cylinders are utilized for the manipulation of the phase of the incident beam working at a frequency of 474 THz. Three metalenses are introduced with focal lengths of 7.46 μm, 10 μm, and 12.99 μm, each having a numerical aperture (NA) of 0.7, 0.6, and 0.5, respectively. The designed single-array metalens showed a transmission efficiency of 73%. The nano-cylinders obtained a full 0–360 phase control that is beneficial in focusing the beam at the center and beyond the center. Symmetric focusing is obtained in the case of off-center focusing on both sides of the optical axis. The design and simulations of the metalens are performed using finite difference time domain (FDTD) simulation tools.
UGV Coverage Path Planning: An Energy-Efficient Approach through Turn Reduction
Authors: Baras Nikolaos , Dasygenis Minas
Published: July 2023

With the advent and rapid growth of automation, unmanned ground vehicles (UGVs) have emerged as a crucial technology, with applications spanning various domains, from agriculture to surveillance, logistics, and military operations. Alongside this surge in the utilization of robotics, novel complications inevitably emerge, posing intriguing questions and challenges to the academic and technological sectors. One such pressing challenge is the coverage path planning (CPP) problem, particularly the notion of optimizing UGV energy utilization during path planning, a significant yet relatively unexplored aspect within the research landscape. While numerous studies have proposed solutions to CPP with a single UGV, the introduction of multiple UGVs within a single environment reveals a unique set of challenges. A paramount concern in multi-UGV CPP is the effective allocation and division of the area among the UGVs. To address this issue, we propose an innovative approach that first segments the area into multiple subareas, which are then allocated to individual UGVs. Our methodology employs fine-tuned spanning trees to minimize the number of turns during navigation, resulting in more efficient and energy-aware coverage paths. As opposed to existing research focusing on models that allocate without optimization, our model utilizes a terrain-aware cost function, and an adaptive path replanning module, leading to a more flexible, effective, and energy-efficient path-planning solution. A series of simulations demonstrated the robustness and efficacy of our approach, highlighting its potential to significantly improve UGV endurance and mission effectiveness, even in challenging terrain conditions. The proposed solution provides a substantial contribution to the field of UGV path planning, addressing a crucial gap and enhancing the body of knowledge surrounding energy-efficient CPP for multi-UGV scenarios.
A Real-Time Application-Classification Vertical Handover Scheme for Coexisting Visible Light Communication and Radio Frequency Indoor Networks on Mobile Terminals
Authors: Cui Bingqi , Zhou Shengbang , Li Chuanqi , Zeng Qian , Zhou Peng , Chen Dong , Leng Yangyang , Chen Rui
Published: July 2023

To enhance the overall communication rate and capacity of mobile networks, a real-time application (RTA)-classification vertical handover (Ac-VHO) scheme is presented for indoor visible light communication (VLC) heterogeneous networks. The scheme considers user mobility, optical link instability, and the variability of real-time applications. It incorporates VLC line-of-sight (LOS) blocking and MT entry into co-channel interference (CCI) areas as triggers, while also providing differentiated delay tolerance intervals and optimized handover dwell time calculations for various RTAs, including video, audio (VoIP), and web/text. A simulation and comparative analysis demonstrate the superior performance of Ac-VHO in terms of signaling cost, and its average rate compared to other methods (hybrid application-aware VHO, dynamic time-dwelling VHO, and static time-dwelling VHO). In addition, it maintains a consistent and relatively high overall quality of user experience (QoE) for different RTA types.
Novel DQ-Based Multicarrier PWM Strategy for a Single-Phase F-Type Inverter
Authors: Abdullah Raad , Smida Mouna Ben , Thamallah Ali , Khalaf Aouse , Sakly Anis
Published: July 2023

This paper presents a novel DQ-based multicarrier pulse width modulation PWM for a single-phase, three-level PV-powered grid-connected F-type inverter. The main control objective in the proposed inverter is to regulate the grid current with low total harmonic distortion and load power components compensation. Despite the F-type inverter’s advanced advantages, there are only a few works addressing the control issue in the literature yet. The proposed control and switching methods aim to achieve both DC-side voltage balance and the lowest switching losses. The proposed scheme has been designed based on a modified multicarrier PWM switching algorithm. Consequently, the proposed control method is able to satisfy the requirements of DC-side voltage balance and achieve lower switching losses. A further advantage of the proposed control and switching methods is that they retain the main advantage of the F-Type inverter, which is that only 25% of the power switches are exposed to full DC voltage. This is an important advantage since it reduces the overall cost of the inverter and improves its reliability. Overall, the proposed modified multicarrier PWM switching algorithm appears to be a promising approach for controlling the F-Type inverter, offering improved performance and efficiency compared to other control methods. The theoretical model was verified through simulation using MATLAB/Simulink. According to the simulation results, the grid current and dc capacitor voltages are successfully managed in all operational situations.
A Deep-Neural-Network-Based Decoding Scheme in Wireless Communication Systems
Authors: Lei Yanchao , He Meilin , Song Huina , Teng Xuyang , Hu Zhirui , Pan Peng , Wang Haiquan
Published: July 2023

With the flourishing development of wireless communication, further challenges will be introduced by the future demands of emerging applications. However, in the face of more complex communication scenarios, favorable decoding results may not be yielded by conventional channel decoding schemes based on mathematical models. The remarkable contributions of deep neural networks (DNNs) in various fields have garnered widespread recognition, which has ignited our enthusiasm for their application in wireless communication systems. Therefore, a reliable DNN-based decoding scheme designed for wireless communication systems is proposed. This scheme comprises efficient local decoding using linear and nonlinear operations. To be specific, linear operations are carried out on the edges connecting neurons, while nonlinear operations are performed on each neuron. After forward propagation through the DNN, the loss value is estimated based on the output, and backward propagation is employed to update the weights and biases. This process is performed iteratively until a near-optimal message sequence is recovered. Various factors within the DNN are considered in the simulation and the potential impacts of each factor are analyzed. Simulation results indicate that our proposed DNN-based decoding scheme is superior to the conventional hard decision.
Bibliometric Review and Technical Summary of PWR Small Modular Reactors
Authors: Fernández-Arias Pablo , Vergara Diego , Antón-Sancho Álvaro
Published: July 2023

Given the real problem of climate change and the consequent need to reduce greenhouse gas emissions, nuclear energy can be considered a real technological option in the absence of a technology that can supply the population with sufficient electrical energy in a sustainable way. The research and development advances of new nuclear reactor designs are evident in the case of Small Modular Reactor (SMR) technology. Two goals are clear in such a technology: (i) reducing onsite construction costs and time; (ii) promoting economic efficiency through the mass production of nuclear reactors. In view of the interest generated by this technology, a technical summary of PWR-SMR design is included in this paper, utilizing the scientific method based on: (i) a bibliometric review of scientific publications related to SMRs; and (ii) a technical analysis of aspects of the different PWR-SMR designs. The results obtained in the present research show a growing interest on the part of the scientific community in research on PWR reactors integrated within SMR designs. Few countries are doing research in this area; however, those that are doing so have achieved greater technological advances in their designs, resulting in greater technological variety and a higher degree of maturity.
A Study of Factors Affecting National Energy Efficiency
Authors: Nevskaya Marina A. , Raikhlin Semen M. , Vinogradova Victoriya V. , Belyaev Victor V. , Khaikin Mark M.
Published: July 2023

National energy efficiency is a key driver for the sustainable development of society. However, the conditions for increasing energy efficiency vary widely around the world and depend on numerous controllable and uncontrollable factors. Existing indicators for assessing energy efficiency typically focus on individual factors, neglecting the complex interplay of socioeconomic, environmental, technological, and other factors that influence energy efficiency. This limitation hampers the quality of assessments. The goal of this study is to develop and apply a comprehensive methodological approach for assessing the influence of key factors on energy efficiency across different countries. The approach utilizes factor analysis methods to identify correlations between indicators and energy-efficiency factors. The study’s findings offer a model for assessing energy efficiency that enables a more profound and comprehensive analysis of the multifactorial impact experienced by national economies in various energy-efficiency domains and areas.