bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep CNN-Based Materials Location and Recognition for Industrial Multi-Crane Visual Sorting System in 5G Network
Authors: Fu Meixia , Wang Qu , Wang Jianquan , Sun Lei , Ma Zhangchao , Zhang Chaoyi , Guan Wanqing , Liu Qiang , Wang Danshi , Li Wei
Published: January 2023

Intelligent manufacturing is a challenging and compelling topic in Industry 4.0. Many computer vision (CV)-based applications have attracted widespread interest from researchers and industries around the world. However, it is difficult to integrate visual recognition algorithms with industrial control systems. The low-level devices are controlled by traditional programmable logic controllers (PLCs) that cannot realize data communication due to different industrial control protocols. In this article, we develop a multi-crane visual sorting system with cloud PLCs in a 5G environment, in which deep convolutional neural network (CNN)-based character recognition and dynamic scheduling are designed for materials in intelligent manufacturing. First, an YOLOv5-based algorithm is applied to locate the position of objects on the conveyor belt. Then, we propose a Chinese character recognition network (CCRNet) to significantly recognize each object from the original image. The position, type, and timestamp of each object are sent to cloud PLCs that are virtualized in the cloud to replace the function of traditional PLCs in the terminal. After that, we propose a dynamic scheduling method to sort the materials in minimum time. Finally, we establish a real experimental platform of a multi-crane visual sorting system to verify the performance of the proposed methods.
Research on Artificial Intelligence in New Year Prints: The Application of the Generated Pop Art Style Images on Cultural and Creative Products
Authors: Zhang Bolun , Romainoor Nurul Hanim
Published: January 2023

Chinese New Year prints constitute a significant component of the country’s cultural heritage and folk art. Yangliuqing New Year prints are the most important and widely circulated of all the different kinds of New Year prints. Due to a variety of factors including societal change, industrial structure change, and economic development, New Year prints, which were deeply rooted in agricultural society, have been adversely impacted, and have even reached the brink of disappearance. With the protection and effort from the government and researchers, New Year prints can finally be preserved. However, the underlying problems remain, such as receiving little attention, a singular product form, and being unable to keep up with the times, especially among the younger generation. In this paper, the researchers first processed Yangliuqing New Year prints through the GANs model. Then, the image is segmented by binarization and color extraction of images from the Pop art dataset by the K-Means algorithm, followed by colorizing the binarized and segmented image. Finally, usable high-quality Pop art style Yangliuqing New Year prints are generated. The generated images are used in the development of cultural and creative products. Questionnaires were then distributed based on the empirical research scale. The results of this study are as follows: 1. The method proposed in this study can generate high-quality Pop art style New Year prints. 2 Using Pop art style New Year print images in the design of cultural and creative products is popular among the younger generation, and they possess a great propensity to purchase. This study solves the problems encountered by the current cultural heritage of New Year prints, and broadens the artistic expression forms and product categories, and provides research ideas for the cultural heritage of the same type that is facing similar problems. In the future, researchers will continue to explore the incorporation of AI technology in New Year prints to stimulate the vitality of traditional cultural heritage.
Analysis of a Modified System of Infectious Disease in a Closed and Convex Subset of a Function Space with Numerical Study
Authors: Shaikh Tahira Sumbal , Akgül Ali , Rehman Muhammad Aziz ur , Ahmed Nauman , Iqbal Muhammad Sajid , Shahid Naveed , Rafiq Muhammad , De la Sen Manuel
Published: January 2023

In this article, the transmission dynamical model of the deadly infectious disease named Ebola is investigated. This disease identified in the Democratic Republic of Congo (DRC) and Sudan (now South Sudan) and was identified in 1976. The novelty of the model under discussion is the inclusion of advection and diffusion in each compartmental equation. The addition of these two terms makes the model more general. Similar to a simple population dynamic system, the prescribed model also has two equilibrium points and an important threshold, known as the basic reproductive number. The current work comprises the existence and uniqueness of the solution, the numerical analysis of the model, and finally, the graphical simulations. In the section on the existence and uniqueness of the solutions, the optimal existence is assessed in a closed and convex subset of function space. For the numerical study, a nonstandard finite difference (NSFD) scheme is adopted to approximate the solution of the continuous mathematical model. The main reason for the adoption of this technique is delineated in the form of the positivity of the state variables, which is necessary for any population model. The positivity of the applied scheme is verified by the concept of M-matrices. Since the numerical method gives a discrete system of difference equations corresponding to a continuous system, some other relevant properties are also needed to describe it. In this respect, the consistency and stability of the designed technique are corroborated by using Taylor’s series expansion and Von Neumann’s stability criteria, respectively. To authenticate the proposed NSFD method, two other illustrious techniques are applied for the sake of comparison. In the end, numerical simulations are also performed that show the efficiency of the prescribed technique, while the existing techniques fail to do so.
Boundary-Value Problem for Nonlinear Fractional Differential Equations of Variable Order with Finite Delay via Kuratowski Measure of Noncompactness
Authors: Telli Benoumran , Souid Mohammed Said , Stamova Ivanka
Published: January 2023

This paper is devoted to boundary-value problems for Riemann–Liouville-type fractional differential equations of variable order involving finite delays. The existence of solutions is first studied using a Darbo’s fixed-point theorem and the Kuratowski measure of noncompactness. Secondly, the Ulam–Hyers stability criteria are examined. All of the results in this study are established with the help of generalized intervals and piecewise constant functions. We convert the Riemann–Liouville fractional variable-order problem to equivalent standard Riemann–Liouville problems of fractional-constant orders. Finally, two examples are constructed to illustrate the validity of the observed results.
The Level of Selected Blood Parameters in Young Soccer Players in Relation to the Concentration of 25(OH)D at the Beginning and End of Autumn
Authors: Jastrzębska Joanna , Skalska Maria , Radzimiński Łukasz , Sánchez Guillermo F. López , Weiss Katja , Knechtle Beat
Published: January 2023

This study aimed to demonstrate the changes of selected blood parameters in relation to 25(OH)D concentration during the autumn period in young soccer players. A total of 35 participants’ results (age: 17.5 ± 0.6 years, body mass 71.3 ± 6.9 kg) were tested twice: in mid-September and in mid-December and divided into subgroups with regard to two criteria. First, according to the initial level of the 25(OH)D concentration (optimal group—ODG, suboptimal group—SDG), second, according to drops in 25(OH)D concentration (high drop group—HDG, low drop group—LDG). A significant decrease (p < 0.001) in the 25(OH)D concentration was reported in the total group (TGr) and in all subgroups. Blood parameters such as white blood cells, red blood cells, haemoglobin and haematocrit increased significantly (p < 0.05) in TGr during the analysed period of time. The analysis of changes in the lipid profile did not expose significant differences except triglycerides. The asparagine amino transferase and creatine kinase activity decreased significantly after autumn in all analysed groups. The declining level of 25(OH)D concentration should be compensated (e.g., with vitamin D supplementation) during autumn. Applied training loads could also influence the blood parameters variability in young soccer players. Regular measurements of 25(OH)D concentration are helpful in identifying potential drops and allows for the preparation of individual supplementation plans for the players.
Sub-Millisecond Photoinduced Dynamics of Free and EL222-Bound FMN by Stimulated Raman and Visible Absorption Spectroscopies
Authors: Liu Yingliang , Chaudhari Aditya S. , Chatterjee Aditi , Andrikopoulos Prokopis C. , Picchiotti Alessandra , Rebarz Mateusz , Kloz Miroslav , Lorenz-Fonfria Victor A. , Schneider Bohdan , Fuertes Gustavo
Published: January 2023

Time-resolved femtosecond-stimulated Raman spectroscopy (FSRS) provides valuable information on the structural dynamics of biomolecules. However, FSRS has been applied mainly up to the nanoseconds regime and above 700 cm−1, which covers only part of the spectrum of biologically relevant time scales and Raman shifts. Here we report on a broadband (~200–2200 cm−1) dual transient visible absorption (visTA)/FSRS set-up that can accommodate time delays from a few femtoseconds to several hundreds of microseconds after illumination with an actinic pump. The extended time scale and wavenumber range allowed us to monitor the complete excited-state dynamics of the biological chromophore flavin mononucleotide (FMN), both free in solution and embedded in two variants of the bacterial light-oxygen-voltage (LOV) photoreceptor EL222. The observed lifetimes and intermediate states (singlet, triplet, and adduct) are in agreement with previous time-resolved infrared spectroscopy experiments. Importantly, we found evidence for additional dynamical events, particularly upon analysis of the low-frequency Raman region below 1000 cm−1. We show that fs-to-sub-ms visTA/FSRS with a broad wavenumber range is a useful tool to characterize short-lived conformationally excited states in flavoproteins and potentially other light-responsive proteins.
Combining Semi-Targeted Metabolomics and Machine Learning to Identify Metabolic Alterations in the Serum and Urine of Hospitalized Patients with COVID-19
Authors: Baiges-Gaya Gerard , Iftimie Simona , Castañé Helena , Rodríguez-Tomàs Elisabet , Jiménez-Franco Andrea , López-Azcona Ana F. , Castro Antoni , Camps Jordi , Joven Jorge
Published: January 2023

Viral infections cause metabolic dysregulation in the infected organism. The present study used metabolomics techniques and machine learning algorithms to retrospectively analyze the alterations of a broad panel of metabolites in the serum and urine of a cohort of 126 patients hospitalized with COVID-19. Results were compared with those of 50 healthy subjects and 45 COVID-19-negative patients but with bacterial infectious diseases. Metabolites were analyzed by gas chromatography coupled to quadrupole time-of-flight mass spectrometry. The main metabolites altered in the sera of COVID-19 patients were those of pentose glucuronate interconversion, ascorbate and fructose metabolism, nucleotide sugars, and nucleotide and amino acid metabolism. Alterations in serum maltose, mannonic acid, xylitol, or glyceric acid metabolites segregated positive patients from the control group with high diagnostic accuracy, while succinic acid segregated positive patients from those with other disparate infectious diseases. Increased lauric acid concentrations were associated with the severity of infection and death. Urine analyses could not discriminate between groups. Targeted metabolomics and machine learning algorithms facilitated the exploration of the metabolic alterations underlying COVID-19 infection, and to identify the potential biomarkers for the diagnosis and prognosis of the disease.
ImmunoPET Directed to the Brain: A New Tool for Preclinical and Clinical Neuroscience
Authors: de Lucas Ángel García , Lamminmäki Urpo , López-Picón Francisco R.
Published: January 2023

Immuno-positron emission tomography (immunoPET) is a non-invasive in vivo imaging method based on tracking and quantifying radiolabeled monoclonal antibodies (mAbs) and other related molecules, such as antibody fragments, nanobodies, or affibodies. However, the success of immunoPET in neuroimaging is limited because intact antibodies cannot penetrate the blood–brain barrier (BBB). In neuro-oncology, immunoPET has been successfully applied to brain tumors because of the compromised BBB. Different strategies, such as changes in antibody properties, use of physiological mechanisms in the BBB, or induced changes to BBB permeability, have been developed to deliver antibodies to the brain. These approaches have recently started to be applied in preclinical central nervous system PET studies. Therefore, immunoPET could be a new approach for developing more specific PET probes directed to different brain targets.
The Double-Edged Role of Extracellular Vesicles in the Hallmarks of Aging
Authors: Romero-García Nekane , Huete-Acevedo Javier , Mas-Bargues Cristina , Sanz-Ros Jorge , Dromant Mar , Borrás Consuelo
Published: January 2023

The exponential growth in the elderly population and their associated socioeconomic burden have recently brought aging research into the spotlight. To integrate current knowledge and guide potential interventions, nine biochemical pathways are summarized under the term hallmarks of aging. These hallmarks are deeply inter-related and act together to drive the aging process. Altered intercellular communication is particularly relevant since it explains how damage at the cellular level translates into age-related loss of function at the organismal level. As the main effectors of intercellular communication, extracellular vesicles (EVs) might play a key role in the aggravation or mitigation of the hallmarks of aging. This review aims to summarize this role and to provide context for the multiple emerging EV-based gerotherapeutic strategies that are currently under study.
Exploring the Impact of COVID-19 on Individuals with Eating Disorders in Saudi Arabia: A Thematic Analysis
Authors: Jawed Aisha , Lim Mengyu , Harrison Amy , Esposito Gianluca , Adusumilli Nandini , Dimitriou Dagmara
Published: January 2023

Food and sleep are critical for human survival. However, for individuals with eating disorders, they face two critical disruptions in terms of abnormal feeding patterns as well as poor sleep. These difficulties are exacerbated as a result of the recent coronavirus pandemic, which caused drastic changes in daily life schedules and living arrangements. The current study therefore aims to explore, through qualitative means, how individuals with eating disorders are affected during the subsequent lockdowns, with a particular emphasis on the pandemic’s impact on their sleep in Saudi Arabia. Two groups of participants were recruited: participants with eating disorders and healthy controls. Based on thematic analysis of focus group discussion data, it was found that both types of participants experienced poorer sleep and poorer mental health. Participants with eating disorders too showed a deterioration of their symptoms. However, healthy participants tended to show greater levels of recovery and coping. Based on the study findings, recommendations for future studies are made.
Experimental and Numerical Investigation of the Shear Performance of PSCC Shear Connectors with Poured UHPC
Authors: Zhou Fengli , Guo Chunwu , Zhang Jiangtao , Guo Jincen , Jiang Jinlong , Ning Lulin
Published: January 2023

Assembled steel-composite bridges generally use stud connectors to achieve the connection between the deck slab and the steel main girders. However, the commonly-used cluster studs weaken the integrity of the precast deck slabs and are not conducive to reducing the size of the precast deck slabs. Based on the excellent mechanical performance of UHPC, a precast steel-concrete composite bridge system consisting of precast bridge deck slabs, bonding cavities, and steel girders was proposed in this study. The system was named PSCC (Precast Steel-Concrete Connectors). To verify the applicability of PSCC connectors in engineering, push-out tests and finite element analysis were carried out in this paper to investigate the shear performance and influence parameters of PSCC connectors. The results showed that compared with the full bonding at the steel-UHPC interface, the shear bearing capacity of the specimens with 30% debonded area rate (the ratio of defect area to total interface area) and the shear bearing capacity of the specimens with 60% debonded area rate decreased by 0.35% and 9.74%, the elastic stiffness decreased by 14.86% and 21.72%, and the elastic-plastic stiffness decreased by 1.6% and 12.8%, respectively. When the steel-UHPC percentage of debonded area is less than 30%, the shear resistance of PSCC connectors is affected very little. However, when the steel-UHPC percentage of debonded area is 60%, the shear resistance of PSCC connectors is greatly affected. Therefore, adequate filling of the UHPC connection layer should be ensured in the project. In addition, the PSCC connectors have excellent ductility, their characteristic slip value Su is much higher than the EC4 specification of 6 mm, and they have better shear performance than conventionally installed stud connectors. According to the results of the parametric analysis, it was found that the failure mode of the PSCC connectors was shear reinforcement fracture when the area ratio of shear reinforcement to stud was less than 1.55, under the premise of the same material strength. On the contrary, the failure mode of PSCC connections was stud fracture. When the transverse spacing of both studs and shear reinforcement is 4d, the PSCC connectors can maintain a high ultimate load capacity while reducing the amount of UHPC in the bonding cavity. Therefore, 4d was chosen as the best spacing for both studs and shear reinforcement.
Effects of Tree Arrangement and Leaf Area Index on the Thermal Comfort of Outdoor Children’s Activity Space in Hot-Humid Areas
Authors: Guo Tongye , Zhao Yang , Yang Jiahao , Zhong Zhengnan , Ji Kefu , Zhong Ziyu , Luo Xinyi
Published: January 2023

Hot-humid areas have long, hot summers and poor outdoor thermal comfort (OTC). The urban heat island (UHI) effect exacerbates the deterioration of OTC in hot-humid areas, seriously affecting the thermal safety of children’s outdoor activities. In this study, 60 scenes were simulated using ENVI-met based on different leaf area index (LAI) and planting arrangements to explore how tree LAI and planting arrangements affect the small-scale thermal environment during hot summer months and to assess OTC using the Universal Thermal Climate Index (UTCI). The research shows that (1) high LAI trees optimize OTC more than low LAI trees, but low LAI trees can be planted multiple times to achieve the level of optimization of high LAI trees; (2) increasing the number of trees optimizes the OTC of the study area, reducing the UTCI by up to 3.7 °C with increased planting compared to unshaded areas; (3) thickening the shade in the east–west direction optimizes the OTC of the study area more than thickening the shade in the north–south direction, with too much north–south shade optimizing the OTC of the study area by only 0.01%. This study provides practical advice for the design of planting in outdoor CAS in hot-humid areas.
Effect of Shear Deformation at Segmental Joints on the Short-Term Deflection of Large-Span Cantilever Cast Prestressed Concrete Box Girders
Authors: Liu Jie , Huang Xiangyu , Chen Juanjuan , Wu Qiaoyun
Published: January 2023

The excessive deflection of large-span cantilever cast prestressed concrete (LCCPC) box girders has always been a complex problem to be solved in bridge engineering. To analyze the effect of shear deformation at segmental joints on the deflection of LCCPC box girders, comparison tests were carried out on three prestressed concrete (PC) I-girders with joints and a PC I-girder without joints, and a finite element simulation method of segmental joints was proposed based on the tests. Subsequently, finite element analysis was conducted on a test girder and the Assistant Shipping Channel Bridge of Humen Bridge (a PC continuous rigid frame bridge with a main span of 270 m) using this method. The experimental and theoretical analysis results showed that the effect of the shear deformation at joints compared to the deformation at midspan of the girder specimens was negligible. Deformation at midspan of the specimens would not significantly increase, even if shear rigidity at the joints was significantly reduced or there were more joints in the girder specimen. The effect of shear deformation at segmental joints on the deflection of LCCPC box girders was quite small and thus insignificant.
Influence of Surface Coating towards the Controlled Toxicity of ZnO Nanoparticles In Vitro
Authors: Mohammad Faruq , Bwatanglang Ibrahim Birma , Al-Lohedan Hamad A. , Shaik Jilani Purusottapatnam , Al-Tilasi Hissah Hamad , Soleiman Ahmed A.
Published: January 2023

The uncertainties in ZnO-mediated toxicity and particle stability in a biological system remain a challenge and mitigate against deployment as next-generation nanoparticles (NPs), especially in biomedical applications. With that perspective, the present study investigates the surface chemical properties of ZnO NPs coated with three different surfactant biomolecules, namely polyethylene glycol (PEG), cetyltrimethylammonium bromide (CTAB), and sodium dodecyl sulfate (SDS) to control the toxicity-induced potentials. On the testing of the surface-functionalized ZnO NPs, notable changes in the particle sizes, morphology, zeta potential, and hydrodynamic size compared to the pure ZnO NPs are observed. In addition, FTIR spectroscopy, TGA, XRD, XPS, and HRTEM analysis showed significant changes in the surface structures and surface functional groups of the three different ZnO NPs on surface functionalization. Following the physical characterization, the cell viability of rat liver BRL-3A-treated ZnO–PEG, ZnO–CTAB, and ZnO–SDS compared to pure ZnO NPs (<50%) falls between 70% and 95% in a dose-determined manner. The cells treated with the pure ZnO NPs showed a higher percentage of apoptotic cells (~61%), which is significantly higher than the 3.4%, 1.5%, and 0.6% for ZnO–PEG-, ZnO–CTAB-, and ZnO–SDS-treated cells (respectively). Furthermore, the surface functionalization was significantly observed to reduce the content of reactive oxygen species (ROS) to 13.6%, 9.7%, and 2.6% compared to the content level of ~71% from the pure ZnO-treated cells. Besides the marked impairment of mitochondrial potentials induced by the pure ZnO NPs, the surfactant–ZnO NPs were observed to slow down the induction of DNA fragmentation and retain the structural integrity of mitochondrial membranes. The toxicity effects are controlled in the order of ZnO–SDS > ZnO–CTAB > ZnO–PEG, i.e., anionic > cationic > non-ionic. Overall from the analysis, the study stresses the importance of having a suitable surface ligand for the ZnO NPs so as to use them in the biomedical sector.
In Situ Synthesis of CuO/Cu2O Nanoparticle-Coating Nanoporous Alumina Membranes with Photocatalytic Activity under Visible Light Radiation
Authors: Durán Boris , Saldías César , Villarroel Roberto , Hevia Samuel A.
Published: January 2023

We report the synthesis and characterization of CuO/Cu2O film supported on nanoporous alumina membranes (NAMs) and the photocatalytic properties in the removal of the organic pollutant methyl orange (MO). For this purpose, transparent nanostructured membranes were fabricated and sequentially modified with APTS ((3-aminopropyl)-trimethoxysilane) and EDTAD (ethylenediaminetetraacetic dianhydride) to form a highly functionalized surface with high density of carboxyl groups, which easily complex with copper cations. The Cu2+-modified membranes were annealed in a chemical vapor deposition (CVD) furnace to form a well-ordered nanostructured coating of CuO/Cu2O with photocatalytic properties. These modifications were followed by characterization with FT-IR and UV–visible spectra, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray spectroscopy (EDS). Finally, the photocatalytic performance of the NAM-CuO/Cu2O nanostructured membranes was tested in the aqueous removal of MO dye as a model reaction system. Our results revealed 50% photocatalytic removal of MO under continuous light irradiation for 2 h. The procedure presented in this work provides an adequate approach for the fabrication of nanostructured devices with photocatalytic properties for the degradation of organic compounds.
Insight into the Structural, Mechanical and Optoelectronic Properties of Ternary Cubic Barium-Based BaMCl3 (M = Ag, Cu) Chloroperovskites Compounds
Authors: Husain Mudasser , Ullah Abd , Algahtani Ali , Tirth Vineet , Al-Mughanam Tawfiq , Alghtani Abdulaziz H. , Sfina Nourreddine , Briki Khaoula , Albalawi Hind , Amin Mohammed A. , Azzouz-Rached Ahmed , Rahman Nasir
Published: January 2023

Prediction of new materials is crucial for the advancement of technology. Here, in this research work, the first-principle computation has been conducted utilizing the WIEN2K package to probe the structural, electronic, mechanical, and optical properties of barium-based chloroperovskites BaMCl3 (M = Ag, Cu) compounds. The optimized lattice constants are calculated for both compounds which are 9.90 Bohr for BaAgCl3 and 9.38 Bohr for BaCuCl3. To obtain better and more precise results for the electronic band’s structure, TDOS and PDOS (total and partial density of states), and the TB-mBJ potential approximation are employed. The indirect band gap (R–Γ) is found for both compounds having values of 1.173 eV and 2.30 eV for BaCuCl3 and BaAgCl3, respectively, which depicts its semiconducting nature. The calculation of elastic properties is conducted with IRelast code. The Cauchy pressure, Bulk modulus, Young’s modulus, Shear modulus, anisotropic ratio, Kleinman parameters, and Poisson’s ratio are calculated from the obtained elastic constants. The computation of elastic parameters indicates that the interested chloroperovskites are anisotropic, mechanically stable, hard to scratch, and ductile. From 0 eV to 40 eV incident photon energy ranges, the various optical parameter such as refractive index, absorption coefficient, dielectric function, reflectivity, extinction coefficient, and optical conductivity are analyzed. These compounds absorb maximum light within 5 to 25 eV incident photon energy. Hence, these materials are good light absorbers, therefore, they can be used in optoelectronic devices for high-frequency applications.
Design of a High Torque Density Robot Joint and Analysis of Force Control Method Applied for a Light Exoskeleton
Authors: Zhang Gan , Tong Qing , Zhang Taixun , Tao Jinxin , Qiu Anjian
Published: January 2023

In many robotic applications, the joint is required to have a small volume, low weight and high torque output. In this paper, based on the finite element analysis (FEA), a 36-slot 40-pole outer rotor surface-mounted permanent magnet (OR-SPM) motor with concentrated winding is designed for the exoskeleton robot. The fractional slot concentrated winding (FSCW) is employed to reduce end winding height, leading better portability. Since the motor is relatively flat, the 3D end effect is critical to the electromagnetic performances. Special attention is paid to 3D end effect during the multi-objective optimization of the OR–SPM motor. In order to increase the ending torque output, the planetary reducer is located between OR–SPM motor and load, and then system level optimization covering motor and reducer is carried out to achieve best torque output. In addition, the force impendence control method with parameter self-adaptive capability is proposed to improve user experience of the exoskeleton robot, where the key parameters in the algorithm vary according to different actions of the exoskeleton. In addition, the inertia of load is calculated using the parameter identification based on least squares method. Finally, the prototype of the joint is fabricated and tested to validate the above FEA results and control method. The user experience of the exoskeleton robot is also covered.
A Multidimensional Model for Recommendation Systems Based on Classification and Entropy
Authors: Yuan Yuyu , Chen Lei , Yang Jincui
Published: January 2023

The proliferation of false and redundant information on e-commerce platforms as well as the prevalence of ineffective recommendations and other untrustworthy behaviors has seriously impeded the healthy development of these platforms. To address these issues and enhance prediction accuracy and user trust, contemporary recommendation systems often utilize additional information (i.e., side information). In this work, we propose a model to improve the recommendation quality by employing the information entropy of user-item ratings. The entropy was used as side information to reflect the global rating behavior of the user and item. We also utilized the classification of the user and item as heuristic information to improve the prediction quality. In our best result, we achieved a significant improvement of 8.2% in prediction accuracy. The model classified the items by the users’ actual preference, which is more trustworthy for users. We evaluated our model with three real-world datasets. The performance of our proposed model was significantly better than the other baseline methods. The similarity calculation method employed in the present model has the potential to mitigate the data sparsity problem associated with correlation-based similarity. The proposed weight matrix has zero sparsity. Furthermore, the proposed model has a more favorable computational complexity for prediction compared to the conventional k-nearest neighbor method.
Framework for Detecting Breast Cancer Risk Presence Using Deep Learning
Authors: Humayun Mamoona , Khalil Muhammad Ibrahim , Almuayqil Saleh Naif , Jhanjhi N. Z.
Published: January 2023

Cancer is a complicated global health concern with a significant fatality rate. Breast cancer is among the leading causes of mortality each year. Advancements in prognoses have been progressively based primarily on the expression of genes, offering insight into robust and appropriate healthcare decisions, owing to the fast growth of advanced throughput sequencing techniques and the use of various deep learning approaches that have arisen in the past few years. Diagnostic-imaging disease indicators such as breast density and tissue texture are widely used by physicians and automated technology. The effective and specific identification of cancer risk presence can be used to inform tailored screening and preventive decisions. For several classifications and prediction applications, such as breast imaging, deep learning has increasingly emerged as an effective method. We present a deep learning model approach for predicting breast cancer risk primarily on this foundation. The proposed methodology is based on transfer learning using the InceptionResNetV2 deep learning model. Our experimental work on a breast cancer dataset demonstrates high model performance, with 91% accuracy. The proposed model includes risk markers that are used to improve breast cancer risk assessment scores and presents promising results compared to existing approaches. Deep learning models include risk markers that are used to improve accuracy scores. This article depicts breast cancer risk indicators, defines the proper usage, features, and limits of each risk forecasting model, and examines the increasing role of deep learning (DL) in risk detection. The proposed model could potentially be used to automate various types of medical imaging techniques.
Robust and Lightweight Deep Learning Model for Industrial Fault Diagnosis in Low-Quality and Noisy Data
Authors: Shin Jaegwang , Lee Suan
Published: January 2023

Machines in factories are typically operated 24 h a day to support production, which may result in malfunctions. Such mechanical malfunctions may disrupt factory output, resulting in financial losses or human casualties. Therefore, we investigate a deep learning model that can detect abnormalities in machines based on the operating noise. Various data preprocessing methods, including the discrete wavelet transform, the Hilbert transform, and short-time Fourier transform, were applied to extract characteristics from machine-operating noises. To create a model that can be used in factories, the environment of real factories was simulated by introducing noise and quality degradation to the sound dataset for Malfunctioning Industrial Machine Investigation and Inspection (MIMII). Thus, we proposed a lightweight model that runs reliably even in noisy and low-quality sound data environments, such as a real factory. We propose a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model using Short-Time Fourier Transforms (STFTs), and the proposed model can be very effective in terms of application because it is a lightweight model that requires only about 6.6% of the number of parameters used in the underlying CNN, and has only a performance difference within 0.5%.
Optimal Transshipment Route Planning Method Based on Deep Learning for Multimodal Transport Scenarios
Authors: Wang Pengjun , Qin Jiahao , Li Jiucheng , Wu Meng , Zhou Shan , Feng Le
Published: January 2023

The optimal path problem is an important topic in the current geographic information system (GIS) and computer science fields. The Dijkstra algorithm is a commonly used method to find the shortest path, which is usually used to find the least cost path from a single source. Based on the analysis and research of the traditional Dijkstra algorithm, this paper points out the problems of the Dijkstra algorithm and optimizes it to improve its storage capacity and operation efficiency. Then, combined with the traffic elements, a new network-based optimal path planning method is established. However, the existing network is far from actual operation in terms of the expansion of the transportation network, the uncertainty of the transportation environment, and the differences in the transportation area. Therefore, this paper proposes an optimal transshipment path planning method based on deep learning, which is oriented to multimodal transportation scenarios. This paper mainly introduces the intelligent transportation system and intelligent navigation system, and then conducts in-depth research on optimal path planning. This paper also uses the deep neural network algorithm to optimize the calculation, and finally analyzes its use and application. Simulation experiments were also performed to analyze the relationship between energy consumption, emissions, speed, load cost, and other factors under the optimal path. The final experimental results show that within the range of the emission limit of [100,200], the emission is 50%, the emission is less than 100%, but the emission is higher than 75%. In [100,200], 75% of the loading rate emits no less than 100%. In [200,300], the 50% and 100% emissions are the same. This also means that the emissions are the same but the paths are not necessarily the same.
Weighted Gene Co-Expression Network Analysis Reveals Hub Genes for Fuzz Development in Gossypium hirsutum
Authors: Jiao Yang , Long Yilei , Xu Kaixiang , Zhao Fuxiang , Zhao Jieyin , Li Shengmei , Geng Shiwei , Gao Wenju , Sun Peng , Deng Xiaojuan , Chen Quanjia , Li Chunpin , Qu Yanying
Published: January 2023

Fuzzless Gossypium hirsutum mutants are ideal materials for investigating cotton fiber initiation and development. In this study, we used the fuzzless G. hirsutum mutant Xinluzao 50 FLM as the research material and combined it with other fuzzless materials for verification by RNA sequencing to explore the gene expression patterns and differences between genes in upland cotton during the fuzz period. A gene ontology (GO) enrichment analysis showed that differentially expressed genes (DEGs) were mainly enriched in the metabolic process, microtubule binding, and other pathways. A weighted gene co-expression network analysis (WGCNA) showed that two modules of Xinluzao 50 and Xinluzao 50 FLM and four modules of CSS386 and Sicala V-2 were highly correlated with fuzz. We selected the hub gene with the highest KME value among the six modules and constructed an interaction network. In addition, we selected some genes with high KME values from the six modules that were highly associated with fuzz in the four materials and found 19 common differential genes produced by the four materials. These 19 genes are likely involved in the formation of fuzz in upland cotton. Several hub genes belong to the arabinogalactan protein and GDSL lipase, which play important roles in fiber development. According to the differences in expression level, 4 genes were selected from the 19 genes and tested for their expression level in some fuzzless materials. The modules, hub genes, and common genes identified in this study can provide new insights into the formation of fiber and fuzz, and provide a reference for molecular design breeding for the genetic improvement of cotton fiber.
Lessons from Shawshank: Outlaws, Lawmen and the Spectacle of Punishment
Authors: Boyce Benjamin
Published: January 2023

For more than a century, cinema has offered a rich source of images and narratives about crime and punishment. Unfortunately, the restricted nature of correctional environments and the social stigma surrounding incarceration leave most viewers reliant on media representations for the majority of their knowledge about correctional spaces. In most media representations of crime and punishment, outlaws and lawmen are reduced to stereotypical archetypes, and incarcerated characters are some of the evilest villains one will ever encounter. Moreover, the prison environment is painted as a playground for bad behavior, as penance for redeemable outlaws, or as an outright paradox that claims to reduce criminality despite appearing to increase it. Our uncritical acceptance of such characterizations goes hand in hand with our cultural addiction to mass incarceration. Limitless stories about uncontainable monsters perpetrating awful crimes inside cushy taxpayer funded facilities endorse a worldview where a permanently expanding and harshening prison system is vital to the safety of a functioning society. In short, our reliance on the spectacle of punishment has left us woefully and willfully misinformed about prison and those who wind up there.
Visual Attention and Recognition Differences Based on Expertise in a Map Reading and Memorability Study
Authors: Keskin Merve , Krassanakis Vassilios , Çöltekin Arzu
Published: January 2023

This study investigates how expert and novice map users’ attention is influenced by the map design characteristics of 2D web maps by building and sharing a framework to analyze large volumes of eye tracking data. Our goal is to respond to the following research questions: (i) which map landmarks are easily remembered? (memorability), (ii) how are task difficulty and recognition performance associated? (task difficulty), and (iii) how do experts and novices differ in terms of recognition performance? (expertise). In this context, we developed an automated area-of-interest (AOI) analysis framework to evaluate participants’ fixation durations, and to assess the influence of linear and polygonal map features on spatial memory. Our results demonstrate task-relevant attention patterns by all participants, and better selective attention allocation by experts. However, overall, we observe that task type and map feature type mattered more than expertise when remembering the map content. Predominantly polygonal map features such as hydrographic areas and road junctions serve as attentive features in terms of map reading and memorability. We make our dataset entitled CartoGAZE publicly available.
Relationships between Jumping Performance and Psychological Readiness to Return to Sport 6 Months Following Anterior Cruciate Ligament Reconstruction: A Cross-Sectional Study
Authors: Legnani Claudio , Del Re Matteo , Viganò Marco , Peretti Giuseppe M. , Borgo Enrico , Ventura Alberto
Published: January 2023

Background: Investigating the relationship between functional capacity and psychological readiness is of paramount importance when planning sport resumption following knee surgery. The aim of this study was to prospectively assess clinical and functional outcomes in athletes 6 months after primary anterior cruciate ligament (ACL) reconstruction and to evaluate whether jumping ability is related to psychological readiness to return to sport following ACL surgery. Methods: Patients who underwent ACL reconstruction were prospectively enrolled and evaluated pre-operatively and 6 months after surgery. Assessment included Lysholm score, International Knee Documentation Committee (IKDC) Subjective Knee Form, Tegner activity level, and the ACL–Return to Sport after Injury (ACL-RSI) scale. Jumping ability was instrumentally assessed by an infrared optical acquisition system using a test battery including mono- and bipodalic vertical jump and a side hop test. Patients were dichotomized by ACL-RSI into two groups: group A (ACL-RSI > 60), and group B (ACL-RSI < 60). Results: Overall, 29 males and two females from the original study group of 37 patients (84%) were available for clinical evaluation. Mean age at surgery was 34.2 years (SD 11.3). Mean body mass index (BMI) was 25.4 (SD 3.7). Mean overall Lysholm, IKDC, and ACL-RSI scores increased from pre-operatively (p < 0.001). No differences in Tegner score were reported (p = 0.161). Similarly, improvement in most variables regarding jumping ability were observed at follow-up (p < 0.05). According to ACL-RSI, 20 subjects were allocated in group A (ACL-RSI > 60), while 11 were allocated in group B (ACL-RSI < 60). A statistically significant difference in favor of patients in group A was recorded for the post-operative Lysholm and Tegner score, as well as Side Hop test LSI level (p < 0.05), while a trend for IKDC was observed without statistical significance (p = 0.065). Conclusions: Patients with higher values of ACL-RSI scores showed better functional and clinical outcomes as well as improved performance 6 months after ACL reconstruction
Diabetes Mellitus and Obesity as Prognostic Factors in Arthroscopic Repair of Chronic Rotator Cuff Tears
Authors: Álvarez de la Cruz Javier , Méndez Ojeda Marye Mercé , Álvarez Benito Nuria , Herrera Rodríguez Alejandro , Pais Brito Jose Luis , Márquez Marfil Francisco Jesús
Published: January 2023

Metabolic diseases such as obesity and diabetes mellitus seem to have an influence on reoperation and long-term functional outcomes after arthroscopic repair of chronic rotator cuff tears. High prevalence of these pathologies can be found in the Canary Islands. A retrospective cohort study was carried out, in which 80 patients undergoing shoulder arthroscopic surgery for the repair of chronic rotator cuff tears were included, with a minimum follow up of 5 years, to study the occurrence of complications, reoperation, and functional outcomes. Functionality after surgery improved in 75% of patients with diabetes and remained the same or worsened in 25% (OR = 1.444). In the group of non-diabetic patients, 83.9% had improved function after surgery while it remained the same or worsened in 16.1% (OR = 0.830). Functionality after surgery improved in 76.6% of obese patients and remained the same or worsened in 23.4% (OR = 1.324). In the non-obese group, 87.9% had improved function after surgery, while it remained the same or worsened in 12.1% (OR = 0.598). Despite not obtaining statistically significant differences, the analysis of the results obtained suggests that obesity and diabetes could act by decreasing the subjective improvement in functionality after surgery, and, in the case of obesity, also increase the risk of reoperation.
SARS-CoV-2 Breakthrough Infections in Health Care Workers: An Italian Retrospective Cohort Study on Characteristics, Clinical Course and Outcomes
Authors: De Maria Luigi , Sponselli Stefania , Caputi Antonio , Stefanizzi Pasquale , Pipoli Antonella , Giannelli Gianmarco , Delvecchio Giuseppe , Tafuri Silvio , Inchingolo Francesco , Migliore Giovanni , Bianchi Francesco Paolo , Boffetta Paolo , Vimercati Luigi
Published: January 2023

Background: The aim of this study was to determine the characteristics, clinical course and outcomes of COVID-19 breakthrough infections (BIs) among healthcare workers (HCWs) of an Italian University Hospital. Methods: A retrospective observational study was conducted on 6111 HCWs, from January 2021 to February 2022. The study population was offered the full vaccination with BNT162b2 mRNA COVID-19 vaccine. To allow return to work after BI, the protocol required one negative nasopharyngeal RT-PCR swab followed by a medical examination to assess the HCW’s health status. Laboratory tests, instrumental tests and specialist evaluations were carried out if necessary. Results. The cases of BIs observed numbered 582 (9.7%). The frequency of BIs was significantly higher in females than in males (67% vs. 33%; p = 0.03), and in nurses than in all other professional categories (p = 0.001). A total of 88% of the HCWs affected by BI were still symptomatic after the negative swab. None of the instrumental tests carried out showed any new findings of pathological significance. All cases showed progressive disappearance of symptoms, such that no cases of long COVID and no hospitalization or deaths were recorded. Conclusions. Our results confirm that SARS-CoV-2 infections occur even after a full vaccination course; however, the clinical course is favorable and severe outcomes are reduced.
Surgical Pharmacy for Optimizing Medication Therapy Management Services within Enhanced Recovery after Surgery (ERAS®) Programs
Authors: Xie Jingwen , Huang Xiaoyan , Gao Min , Wei Li , Wang Ruolun , Chen Jisheng , Zeng Yingtong , Ji Bo , Liu Tao , Wang Jinghao , Wu Hongwei , Wang Yong , Qin Li , Wang Yiting , Zheng Zhuoling , Xue Jing , Wu Junyan , Chen Xiao , Zheng Zhihua , Li Xiaoyan
Published: January 2023

Drug-related problems (DRPs) are common among surgical patients, especially older patients with polypharmacy and underlying diseases. DRPs can potentially lead to morbidity, mortality, and increased treatment costs. The enhanced recovery after surgery (ERAS) system has shown great advantages in managing surgical patients. Medication therapy management for surgical patients (established as “surgical pharmacy” by Guangdong Province Pharmaceutical Association (GDPA)) is an important part of the ERAS system. Improper medication therapy management can lead to serious consequences and even death. In order to reduce DRPs further, and promote the rapid recovery of surgical patients, the need for pharmacists in the ERAS program is even more pressing. However, the medication therapy management services of surgical pharmacy and how surgical pharmacists should participate in ERAS programs are still unclear worldwide. Therefore, this article reviews the main perioperative medical management strategies and precautions from several aspects, including antimicrobial agents, antithrombotic agents, pain medication, nutritional therapy, blood glucose monitoring, blood pressure treatment, fluid management, treatment of nausea and vomiting, and management of postoperative delirium. Additionally, the way surgical pharmacists participate in perioperative medication management, and the relevant medication pathways are explored for optimizing medication therapy management services within the ERAS programs. This study will greatly assist surgical pharmacists’ work, contributing to surgeons accepting that pharmacists have an important role in the multidisciplinary team, benefitting medical workers in treating, counseling, and advocating for their patients, and further improving the effectiveness, safety and economy of medication therapy for patients and promoting patient recovery.