bluuebunny/crossref_metadata_2025 huggingface dataset:
Fine Particulate Matter Perturbs the Pulmonary Microbiota in Broiler Chickens
Authors: Zhou Ying , Xu Bin , Wang Linyi , Zhang Chaoshuai , Li Shaoyu
Published: September 2023

(1) Fine particulate matter (PM2.5) seriously affects the respiratory tract health of both animals and humans. Growing evidence indicates that the pulmonary microbiota is involved in the development of respiratory tract health; however, there is still much that is unknown about the specific changes of pulmonary microbiota caused by PM2.5 in broilers. (2) In this experiment, a total of 48 broilers were randomly divided into a control group and PM-exposure group. The experiment lasted for 21 days. Microbiota, inflammation biomarkers, and histological markers in the lungs were determined. (3) On the last day of the experiment, PM significantly disrupted the structure of lung tissue and induced chronic pulmonary inflammation by increasing IL-6, TNFα, and IFNγ expression and decreasing IL-10 expression. PM exposure significantly altered the α and β diversity of pulmonary microbiota. At the phylum level, PM exposure significantly decreased the Firmicutes abundance and increased the abundance of Actinobacteria and Proteobacteria. At the genus level, PM exposure significantly increased the abundance of Rhodococcus, Achromobacter, Pseudomonas, and Ochrobactrum. We also observed positive associations of the above altered genera with lung TNFα and IFNγ expression. (4) The results suggest that PM perturbs the pulmonary microbiota and induces chronic inflammation, and the pulmonary microbiota possibly contributes to the development of lung inflammation.
Reduction in Cold Stress in an Innovative Metabolic Cage Housing System Increases Animal Welfare in Laboratory Mice
Authors: Wittek Laura , Touma Chadi , Nitezki Tina , Laeger Thomas , Krämer Stephanie , Raila Jens
Published: September 2023

Housing in metabolic cages can induce a pronounced stress response. Metabolic cage systems imply housing mice on metal wire mesh for the collection of urine and feces in addition to monitoring food and water intake. Moreover, mice are single-housed, and no nesting, bedding, or enrichment material is provided, which is often argued to have a not negligible impact on animal welfare due to cold stress. We therefore attempted to reduce stress during metabolic cage housing for mice by comparing an innovative metabolic cage (IMC) with a commercially available metabolic cage from Tecniplast GmbH (TMC) and a control cage. Substantial refinement measures were incorporated into the IMC cage design. In the frame of a multifactorial approach for severity assessment, parameters such as body weight, body composition, food intake, cage and body surface temperature (thermal imaging), mRNA expression of uncoupling protein 1 (Ucp1) in brown adipose tissue (BAT), fur score, and fecal corticosterone metabolites (CMs) were included. Female and male C57BL/6J mice were single-housed for 24 h in either conventional Macrolon cages (control), IMC, or TMC for two sessions. Body weight decreased less in the IMC (females—1st restraint: −6.94%; 2nd restraint: −6.89%; males—1st restraint: −8.08%; 2nd restraint: −5.82%) compared to the TMC (females—1st restraint: −13.2%; 2nd restraint: −15.0%; males—1st restraint: −13.1%; 2nd restraint: −14.9%) and the IMC possessed a higher cage temperature (females—1st restraint: 23.7 °C; 2nd restraint: 23.5 °C; males—1st restraint: 23.3 °C; 2nd restraint: 23.5 °C) compared with the TMC (females—1st restraint: 22.4 °C; 2nd restraint: 22.5 °C; males—1st restraint: 22.6 °C; 2nd restraint: 22.4 °C). The concentration of fecal corticosterone metabolites in the TMC (females—1st restraint: 1376 ng/g dry weight (DW); 2nd restraint: 2098 ng/g DW; males—1st restraint: 1030 ng/g DW; 2nd restraint: 1163 ng/g DW) was higher compared to control cage housing (females—1st restraint: 640 ng/g DW; 2nd restraint: 941 ng/g DW; males—1st restraint: 504 ng/g DW; 2nd restraint: 537 ng/g DW). Our results show the stress potential induced by metabolic cage restraint that is markedly influenced by the lower housing temperature. The IMC represents a first attempt to target cold stress reduction during metabolic cage application thereby producing more animal welfare friendlydata.
Exploratory Study on Individual Locomotor Activity in Local Dual-Purpose and Commercial Breeder Pullets
Authors: Schürmann Pia , Becker Senta , Krause E. Tobias , Hillemacher Sonja , Büscher Wolfgang , Tiemann Inga
Published: September 2023

Improving animal welfare is a prerequisite for the societal acceptance of poultry production. Support for improvements requires practical tools to quantify animal welfare and identify predispositions at the individual level, where possible. In this study, the activities and behavior of dual-purpose chickens (N = 245) and commercial breeders (N = 224) were analyzed. The general locomotor activity (GLA) data were collected using an RFID system over five days with 9-to-14-week-old animals. The results show that the animals of comparable age and stocking density differed from each other in their activity (p ≤ 0.001) according to breed, but no sex differences were observed (p = 0.159). No correlations were found between GLA and plumage condition (p > 0.05). The individual variations within the breeds are presented and discussed on an animal-by-animal level, providing new insights into the individual behavioral variability of chickens. The RFID systems can reliably generate GLA data that help to understand the potential interplay between behavior and animal welfare. The technology is also suitable for creating individual (personality) profiles that can be used for breeding. With a better understanding of the role of activity, husbandry and management practices can be adapted to improve animal welfare.
Analysis of Early Growth of Piglets from Hyperprolific Sows Using Random Regression Coefficient
Authors: Škorput Dubravko , Jančo Nina , Karolyi Danijel , Kaić Ana , Luković Zoran
Published: September 2023

Management of hyperprolific sows is challenging when it comes to controlling birth weight variability and piglet survival in large litters. The growth of low birth weight piglets can be compromised and have a negative impact on production efficiency. The objective of the study was to apply a random regression coefficient model to estimate the main effects of the growth of piglets of highly prolific sows. The dataset contained growth data for 360 piglets from 25 Pen Ar Lan Naima sows. In addition to routine procedures after farrowing, piglets were weighed five times: on day 1 after farrowing, on day 14 of life, at weaning on day 28, on day 30 of nursery period, and at the end of the nursery period when piglets were 83 days old. Data were treated as longitudinal, with body weight as the dependent variable. Fitting age as a quadratic regression within piglets in the random part of the model helped to determine the significant effect of birth weight, litter size, and parity on the growth of the piglets. Since the piglets from large litters often have non-uniform birth weights and this can affect further growth, the use of a random regression coefficient model is practical for analysing the growth of such piglets due to the ability to describe the individual growth pattern of every individual.
Characterizing Chronologically Aged Basic Oxygen Furnace Slags as Aggregates and Their Use in Asphalt Concrete Mix as Filler
Authors: Nugmanova Assel , Shon Chang-Seon , Kim Jong Ryeol , Rossi Cesare Oliviero
Published: September 2023

Before using basic oxygen furnace slag (BOFS) in any engineering application, it is important to determine its properties. The chemical composition, mineralogy, and physical properties of BOF slag are subject to large fluctuations as a result of different raw additives, different compositions of the molten iron used for producing the steel, oxygen stirring of a molten pool, uneven temperature fields, and other complex physical conditions. Thus, in this research, the engineering properties of BOF slag aggregates with different ages were identified, and then the feasibility of BOF slag aggregates in mortar application was investigated. It was found that stockpiled BOFS was harder than fresh BOF slag, which had lower aggregate crushing values and lower LA abrasion values. Also, stockpiled BOFS showed less expansion than fresh BOF slag regardless of water and 1 M NaOH solution immersion. The chemical reaction between f-CaO, f-MgO, and water due to weathering in the field extremely reduced the expansion of BOFS submerged in water. BOFS may contain reactive silica, which causes an alkali–silica reaction (ASR). Stockpiled BOFS (100%, 75%, 50%, 25%) used as a mineral filler in asphalt concrete mix brought about low tensile strength at break up (crack), low compressive strength at +50 °C, poor cohesion, and residual porosity. However, these parameters were partially improved with the use of a thermostable adhesive additive for road bitumen based on polyphosphoric acid esters. The comprehensive assessment in this study indicates that while some mixtures meet the specified criteria for certain properties, there are challenges, particularly regarding crack resistance and cohesion, that need to be addressed to fully align with the standard. Adjustments to the mixture proportions, the exploration of alternative additives, and the use of different types of fillers may be necessary to achieve the desired properties, especially in terms of crack resistance and cohesion.
Reducing Video Coding Complexity Based on CNN-CBAM in HEVC
Authors: Li Huayu , Wei Geng , Wang Ting , Bui ThiOanh , Zeng Qian , Wang Ruliang
Published: September 2023

High-efficiency video coding (HEVC) outperforms H.264 in coding efficiency. However, the rate–distortion optimization (RDO) process in coding tree unit (CTU) partitioning requires an exhaustive exploration of all possible quad-tree partitions, resulting in high encoding complexity. To simplify this process, this paper proposed a convolution neural network (CNN) based optimization algorithm combined with a hybrid attention mechanism module. Firstly, we designed a CNN compatible with the current coding unit (CU) size to accurately predict the CU partitions. In addition, we also designed a convolution block to enhance the information interaction between CU blocks. Then, we introduced the convolution block attention module (CBAM) into CNN, called CNN-CBAM. This module concentrates on important regions in the image and attends to the target object correctly. Finally, we integrated the CNN-CBAM into the HEVC coding framework for CU partition prediction in advance. The proposed network was trained, validated, and tested using a large scale dataset covering various scenes and objects, which provides extensive samples for intra-frame CU partition prediction in HEVC. The experimental findings demonstrate that our scheme can reduce the coding time by up to 64.05% on average compared to a traditional HM16.5 encoder, with only 0.09 dB degradation in BD-PSNR and a 1.94% increase in BD-BR.
Risk Assessment of Compound Dynamic Disaster Based on AHP-EWM
Authors: Zhang Runjie , Tian Da , Wang Hongwei , Kang Xinyue , Wang Gang , Xu Lianman
Published: September 2023

The coal mine in deep mining can easily form a compound dynamic disaster with the characteristics of rock burst and gas outburst. In this paper, the analytic hierarchy process (AHP) and the entropy weight method (EWM) are combined, and the fuzzy comprehensive evaluation (FCE) secondary evaluation model of compound dynamic disaster is proposed to evaluate the risk of compound dynamic disaster, which avoids the problems of the imperfect evaluation index system and strong subjectivity of index weight. Based on the statistical analysis of typical compound dynamic disaster cases in China, three first-level indicators were established, and sixteen second-level indicators were developed. The verification results show that the accuracy and weight are better than the traditional evaluation methods. Combined with geological and mining data, the compound dynamic disaster risk assessment was carried out on the second mining area of mine B, in the Pingdingshan mining area, and the result was grade II (weak risk). Corresponding prevention measures and parameters were implemented, and no compound dynamic disaster occurred during the working face excavation.
Modeling and Design Enhancement of Electrothermal Actuators for Microgripping Applications
Authors: Pour Parham Dadash , Ghommem Mehdi , Abdelkefi Abdessattar
Published: September 2023

Microgrippers are miniature tools that have the capability to handle and manipulate micro- and nano-scale objects. The present work demonstrates the potential impact of the incorporation of perforations on a ‘hot and cold arm’ electrothermal actuation mechanism in order to improve the operation of microgrippers in terms of arm opening and operating temperature. By applying a voltage to one arm and setting the other as a ground, the current passes through the electrothermal actuator and induces its displacement along the in-plane direction. The difference in the geometry of the two arms causes one arm to expand more than the other and this results in transverse bending. A computational model was developed using a finite element analysis tool to simulate the response of the thermal actuators with varying geometries and investigate the impact of incorporating perforations on the arms of the thermal actuators to enhance its performance in terms of deflection and operating temperature. The simulation results were compared to their experimental counterparts reported in the literature. A good agreement between the numerical and experimental data was obtained. A novel design of a microgripper, made of perforated electrothermal actuators, was introduced. Its main characteristics, including the tip opening of the gripper arms, the applied voltage, and the stress and temperature distributions, were analyzed using the developed computational model. Different perforation shape and distribution were investigated. The present study demonstrates the capability of perforations to enhance the operation of microgrippers as manifested by the obtained higher tip displacement and lower tip temperature in comparison to conventional microgripper designs made of non-perforated thermal actuators. Furthermore, the highest stress generated on the microgripper elements was found to be much lower than the yield strength of the constituent material, which indicates proper functioning without any mechanical failure.
Design of Dual-Notch-Filter-Based Controllers for Enhancing the Dynamic Response of Universal Single-Phase Grid-Connected Power Converters
Authors: Borafker Sahar , Strajnikov Pavel , Kuperman Alon
Published: September 2023

Trade-off between transient response and grid-side current quality is a well-known issue of single-phase mains-connected power converters. A dual-loop control structure (usually based on PI or type-II controllers) is typically employed in such systems to regulate the DC link voltage to a constant reference (in order to maintain power balance) while forcing the grid-side current to have a specific shape (in order to comply with power quality requirements). Introducing notch term/s (tuned to certain multiple/s of the mains base frequency) into one of the loops allows either for the improvement of the dynamic performance without worsening the total harmonic distortion of grid-side current or for the enhancement of the current quality without impairing the dynamic response. Since the maximum tolerable value of total harmonic distortion is typically imposed by a certain power quality standard, it is desirable to enhance the transient response of the power converter system as much as possible while keeping the total harmonic distortion at the maximum allowed value. However, universal off-grid operating power conversion systems must support both 50 Hz and 60 Hz mains; consequently, tuning the notch term/s to 50 Hz multiple/s would not be sufficient for a 60 Hz mains operation and vice-versa. Consequently, this work examines the possibility of introducing a dual-notch term into the control loop in order to cover both above-mentioned base frequencies. It is demonstrated that under typical base frequency uncertainty values, the performances of dual-notch terms are nearly decoupled so that the term tuned to a 50 Hz frequency (and optionally to its multiples) has nearly no influence at a 60 Hz mains operation and vice-versa. Consequently, the methodology allows for the improvement of the dynamics of universal grid-connected power converters without total harmonic distortion (THD) deterioration. A stability analysis of the proposed control structure is carried out and quantitative design guidelines, allowing for the attainment of an optimized dynamic response for a given maximum tolerable total harmonic distortion, minimum allowed phase margin and a certain base frequency uncertainty, are established. It is shown that a DC link voltage loop bandwidth of 52 Hz may be attained while keeping the grid-side current THD below 5%. Simulations and experimental results support well the proposed design methodology.
Computer Vision Based Planogram Compliance Evaluation
Authors: Laitala Julius , Ruotsalainen Laura
Published: September 2023

Arranging products in stores according to planograms, optimized product arrangement maps, is an important sales enabler and necessary for keeping up with the highly competitive modern retail market. Key benefits of planograms include increased efficiency, maximized retail store space, increased customer satisfaction, visual appeal, and increased revenue. The planograms are realized into product arrangements by humans, a process that is prone to mistakes. Therefore, for optimal merchandising performance, the planogram compliance of the arrangements needs to be evaluated from time to time. We investigate utilizing a computer vision problem setting—retail product detection—to automate planogram compliance evaluation. Retail product detection comprises product detection and classification. The detected and classified products can be compared to the planogram in order to evaluate compliance. In this paper, we propose a novel retail product detection pipeline combining a Gaussian layer network product proposal generator and domain invariant hierarchical embedding (DIHE) classifier. We utilize the detection pipeline with RANSAC pose estimation for planogram compliance evaluation. As the existing metrics for evaluating the planogram compliance evaluation performance assume unrealistically that the test image matches the planogram, we propose a novel metric, called normalized planogram compliance error (EPC), for benchmarking real-world setups. We evaluate the performance of our method with two datasets: the only open-source dataset with planogram evaluation data, GP-180, and our own dataset collected from a large Nordic retailer. Based on the evaluation, our method provides an improved planogram compliance evaluation pipeline, with accurate product location estimation when using real-life images that include entire shelves, unlike previous research that has only used images with few products. Our analysis also demonstrates that our method requires less processing time than the state-of-the-art compliance evaluation methods.
Towards Privacy Preserving in 6G Networks: Verifiable Searchable Symmetric Encryption Based on Blockchain
Authors: Peng Tianqi , Gong Bei , Zhang Jiangjiang
Published: September 2023

The blockchain-based searchable symmetric encryption (SSE) scheme allows the retrieval and verification of outsourced data on cloud servers in sixth generation (6G) networks while ensuring the privacy of data. However, existing schemes are challenging to comprehensively meet the requirements of 6G-based intelligent application systems for low latency, high security, and high reliability. To address these limitations, we present VSSE, a novel blockchain-based SSE scheme designed for 6G-based intelligent application systems. Our scheme constructs a state chain structure to resist file injection attacks, thereby ensuring forward privacy. Moreover, we execute the search and verification operations separately on the cloud server and blockchain, while introducing a bitmap index structure and message authentication code (MAC) technology to achieve efficient searching and dynamic verification. Notably, VSSE also includes access control functionality, permitting only authorized users to access relevant files. The combination of remarkable efficiency and strong security establishes our VSSE as an ideal solution suitable for implementation in G-based intelligent application systems.
Cortical Neurons Adjust the Action Potential Onset Features as a Function of Stimulus Type
Authors: Aldohbeyb Ahmed A. , Alokaily Ahmad O.
Published: September 2023

Pyramidal neurons and interneurons play critical roles in regulating the neuronal activities in the mammalian cortex, where they exhibit different firing patterns. Pyramidal neurons mainly exhibit regular-spiking firing patterns, while interneurons have fast-spiking firing patterns. Cortical neurons have distinct action potential onset dynamics, in which the evoked action potential is rapid and highly variable. However, it is still unclear how cortical regular-spiking and fast-spiking neurons discriminate between different types of stimuli by changing their action potential onset parameters. Thus, we used intracellular recordings of regular-spiking and fast-spiking neurons, taken from layer 2/3 in the somatosensory cortex of adult mice, to investigate changes in the action potential waveform in response to two distinct stimulation protocols: the conventional step-and-hold and frozen noise. The results show that the frozen noise stimulation paradigm evoked more rapid action potential with lower threshold potential in both neuron types. Nevertheless, the difference in the action potential rapidity in response to different stimuli was significant in regular-spiking pyramidal neurons while insignificant in fast-spiking interneurons. Furthermore, the threshold variation was significantly higher for regular-spiking neurons than for fast-spiking neurons. Our findings demonstrate that different types of cortical neurons exhibit various onset dynamics of the action potentials, implying that different mechanisms govern the initiation of action potentials across cortical neuron subtypes.
The Impact of Additive Manufacturing Constraints and Design Objectives on Structural Topology Optimization
Authors: Dangal Babin , Jung Sangjin
Published: September 2023

To analyze the impact of different objective functions and additive manufacturing (AM) constraints on structural topology optimization, it is necessary to perform an in-depth comparative study. This analysis should consider specific structural design factors, such as compliance, volume, or stress minimization, and assess their effects on the topology optimization for AM. In addition, the inclusion of AM constraints can have a significant influence on various aspects, including optimal part geometry, part volume, support structure volume, and structural performance. Thus, it is essential to investigate and compare these factors to determine the optimal part design for AM. This study focuses on comparing topology optimization results obtained using compliance, stress, or multi-objective minimization, with and without AM constraints. A comparative analysis was conducted in the study, utilizing three structural design examples: cantilever beam, bridge-shaped structure, and L-shaped beam. The comparison results provide insights into the effects of build orientation, AM constraints such as overhang, and different design objectives on the structural topology optimization for AM.
Improved Lightweight Multi-Target Recognition Model for Live Streaming Scenes
Authors: Li Zongwei , Qiao Kai , Chen Jianing , Li Zhenyu , Zhang Yanhui
Published: September 2023

Nowadays, the commercial potential of live e-commerce is being continuously explored, and machine vision algorithms are gradually attracting the attention of marketers and researchers. During live streaming, the visuals can be effectively captured by algorithms, thereby providing additional data support. This paper aims to consider the diversity of live streaming devices and proposes an extremely lightweight and high-precision model to meet different requirements in live streaming scenarios. Building upon yolov5s, we incorporate the MobileNetV3 module and the CA attention mechanism to optimize the model. Furthermore, we construct a multi-object dataset specific to live streaming scenarios, including anchor facial expressions and commodities. A series of experiments have demonstrated that our model realized a 0.4% improvement in accuracy compared to the original model, while reducing its weight to 10.52%.
Optimizing CuFeS2 Chalcopyrite Thin Film Synthesis: A Comprehensive Three-Step Approach Using Ball-Milling, Thermal Evaporation, and Sulfurization Applied for Thermoelectric Generation
Authors: Malagutti Marcelo Augusto , Lohani Ketan , D’Incau Mirco , Nautiyal Himanshu , Ataollahi Narges , Scardi Paolo
Published: September 2023

CuFeS2 (CFS) stands out as a promising narrow band-gap semiconductor for thermoelectric (TE) applications. However, its high lattice thermal conductivity is one of the factors hampering its potential for TE generation. A common strategy for tackling this problem is to produce this material in thin film form. Thus, this study aims to practically understand and optimize the synthesis of CFS 2D materials using a simple three-step approach of ball-milling, thermal evaporation, and sulfurization of the CuFe metallic precursors. The tools for thin film characterization employ X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDXS), and Hall-effect measurements. DFT phase diagrams are also used to understand the energy of formation of the secondary phases present in the film. Here, we highlight that the ball-milling mechanisms, allied with high vacuum and high energy density during evaporation, are essential for the interdiffusion of Cu and Fe during the evaporation process. The film presented a flower-like morphology and p-type semiconducting behavior. A proof-of-concept Thermoelectric Generator (TEG) was designed in an in-plane geometry, showing a power output per unit active area of 114 nW cm−2 (ΔT = 180 °C), comparable to other Cu-based materials, thus demonstrating the feasibility of this method of synthesis for TE applications.
Fast 3D Reconstruction of UAV Images Based on Neural Radiance Field
Authors: Jiang Cancheng , Shao Hua
Published: September 2023

Traditional methods for 3D reconstruction of unmanned aerial vehicle (UAV) images often rely on classical multi-view 3D reconstruction techniques. This classical approach involves a sequential process encompassing feature extraction, matching, depth fusion, point cloud integration, and mesh creation. However, these steps, particularly those that feature extraction and matching, are intricate and time-consuming. Furthermore, as the number of steps increases, a corresponding amplification of cumulative error occurs, leading to its continual augmentation. Additionally, these methods typically utilize explicit representation, which can result in issues such as model discontinuity and missing data during the reconstruction process. To effectively address the challenges associated with heightened temporal expenditures, the absence of key elements, and the fragmented models inherent in three-dimensional reconstruction using Unmanned Aerial Vehicle (UAV) imagery, an alternative approach is introduced—the neural radiance field. This novel method leverages neural networks to intricately fit spatial information within the scene, thereby streamlining the reconstruction steps and rectifying model deficiencies. The neural radiance field method employs a fully connected neural network to meticulously model object surfaces and directly generate the 3D object model. This methodology simplifies the intricacies found in conventional 3D reconstruction processes. Implicitly encapsulating scene characteristics, the neural radiance field allows for iterative refinement of neural network parameters via the utilization of volume rendering techniques. Experimental results substantiate the efficacy of this approach, demonstrating its ability to complete scene reconstruction within a mere 5 min timeframe, thereby reducing reconstruction time by 90% while markedly enhancing reconstruction quality.
A Novel Charging Station on Overhead Power Lines for Autonomous Unmanned Drones
Authors: Muñoz-Gómez Antonio-Miguel , Marredo-Píriz Juan-Manuel , Ballestín-Fuertes Javier , Sanz-Osorio José-Francisco
Published: September 2023

Innovative drone-based technologies provide novel techniques to guarantee the safety and quality of power supply and to perform these tasks more efficiently. Electric multirotor drones, which are at the forefront of technology, face significant flight time limitations due to battery capacity and weight constraints that limit their autonomous operation. This paper presents a novel drone charging station that harvests energy from the magnetic field present in power lines to charge the drone’s battery. This approach relies on a charging station that is easy to install by the drone on an overhead AC power line without modifying the electrical infrastructure. This paper analyses the inductive coupling between the energy harvester and the power line, electrical protection, the power electronics required for maximum power point tracking and the mechanical design of the charging station. A drone that perches on a cable, an end effector for installation procedures and the charging maneuver are described, along with discussion of the robotic and electrical tests performed in a relevant environment. Finally, a lightweight drone charging station capable of harvesting 145 W of power from a 600 A line current is reported.
Adaptive Age Estimation towards Imbalanced Datasets
Authors: Dong Zhiang , Li Xiaoqiang
Published: September 2023

Current age estimation datasets often have a skewed long-tail distribution with significant data imbalance, rather than an ideal uniform distribution for each category. The existing age estimation algorithms that rely on label distribution do not leverage data density information to address the issue of data imbalance. To solve the aforementioned problem, this paper proposes a novel method based on cost-sensitive learning, namely Data-Imbalance Adaptive Age Regression (DIAAR), for age estimation. DIAAR consists of two main modules: the adaptive soft label (ASL) module and the Data Density Smoothing (DDS) module. The ASL module embeds soft labels in the form of probability in the age regression. It assigns different degrees of soft labels adaptively to head and tail data based on their density, which helps balance the dataset. The DDS module further addresses data imbalance by revising data density through kernel smoothing and reweighting the loss function accordingly. Experiments on two benchmark datasets show that DIAAR can effectively deal with data imbalance and improve the accuracy of age estimation, achieving an average improvement of 8% over the baseline models. Moreover, this approach can be applied to various methods based on convolutional neural network models.
Taxi Demand and Fare Prediction with Hybrid Models: Enhancing Efficiency and User Experience in City Transportation
Authors: Chou Ka Seng , Wong Kei Long , Zhang Boliang , Aguiari Davide , Im Sio Kei , Lam Chan Tong , Tse Rita , Tang Su-Kit , Pau Giovanni
Published: September 2023

An essential part of a city’s transportation infrastructure, taxis allow for regular encounters between drivers and customers. Nevertheless, there are issues with efficiency since there is an imbalance in the supply and demand for taxis. This study describes the creation of a platform that serves both customers and taxi drivers by offering immediate forecasts of demand and fare. Root mean squared error (RMSE) of 3.31 and a negative log-likelihood of −3.84, the long short-term memory recurrent neural network (LSTM-RNN) with the mixture density network (MDN) is employed to forecast taxi demand. The best RMSE of 3.24 is obtained for fare prediction via an ensemble learning model that integrates linear regression (LR), ridge regression (RR), and multilayer perceptron (MLP). To ensure peak performance, the models are systematically created, implemented, trained, and improved. By integrating these models into a web application interface, the taxi service system offers a better overall user experience, which improves urban mobility.
Intelligent Anomaly Detection System through Malware Image Augmentation in IIoT Environment Based on Digital Twin
Authors: Cha Hyun-Jong , Yang Ho-Kyung , Song You-Jin , Kang Ah Reum
Published: September 2023

Due to the recent rapid development of the ICT (Information and Communications Technology) field, the industrial sector is also experiencing rapid informatization. As a result, malware targeting information leakage and financial gain are increasingly found within IIoT (the Industrial Internet of Things). Moreover, the number of malware variants is rapidly increasing. Therefore, there is a pressing need for a safe and preemptive malware detection method capable of responding to these rapid changes. The existing malware detection method relies on specific byte sequence inclusion in a binary file. However, this method faces challenges in impacting the system or detecting variant malware. In this paper, we propose a data augmentation method based on an adversarial generative neural network to maintain a secure system and acquire necessary learning data. Specifically, we introduce a digital twin environment to safeguard systems and data. The proposed system creates fixed-size images from malware binaries in the virtual environment of the digital twin. Additionally, it generates new malware through an adversarial generative neural network. The image information produced in this manner is then employed for malware detection through deep learning. As a result, the detection performance, in preparation for the emergence of new malware, demonstrated high accuracy, exceeding 97%.
Target-Aware Feature Bottleneck for Real-Time Visual Tracking
Authors: Choi Janghoon
Published: September 2023

Recent Siamese network-based visual tracking approaches have achieved high performance metrics on numerous recent visual tracking benchmarks, where most of these trackers employ a backbone feature extractor network with a prediction head network for classification and regression tasks. However, there has been a constant trend of employing a larger and complex backbone network and prediction head networks for improved performance, where increased computational load can slow down the overall speed of the tracking algorithm. To address the aforementioned issues, we propose a novel target-aware feature bottleneck module for trackers, where the proposed bottleneck can elicit a target-aware feature in order to obtain a compact feature representation from the backbone network for improved speed and robustness. Our lightweight target-aware bottleneck module attends to the feature representation of the target region to elicit scene-specific information and generate feature-wise modulation weights that can adaptively change the importance of each feature. The proposed tracker is evaluated on large-scale visual tracking datasets, GOT-10k and LaSOT, and we achieve real-time speed in terms of computation and obtain improved accuracy over the baseline tracker algorithm with high performance metrics.
Art and the City Fiction in Japanese American Internment Camps: Sequels for Resiliency
Authors: Rodriguez-Cunill Inmaculada , Cabeza-Lainez Joseph , Lopez-Cabrales Maria del Mar
Published: September 2023

This article delves into the creation a fictional city solely for the development of Japanese American internment camps and the way in which sustainable arts and crafts played a significant role in ensuring survival in such a hostile environment. To this aim, we searched the literature and reviewed archives, primarily from the American West Coast. We demonstrate that beyond adaptation to the circumstances, the visual representation of the new city’s settlement, founding, and daily activities, instead of adding to the typical panoptic or sombre prison imagery, remains inscribed in the images selected by the inmates, and that the use of such images precisely fostered the inmates’ resiliency. This leads us to deduce that such ’city fiction’ was necessary in this case for survival and endurance, and that its artistic representation was primarily incorporated into the State’s ideological apparatus. On the other hand, occasional fissures subtly seethed with the violence exerted in the camps. In this way, we conclude that the artistic activity itself justified the city fiction, among other situations, revealing the conditions of systemic violence and oppression faced by the internees. Within this framework, we deem that the artworks hereby generated constitute a paramount historical document for resiliency’s sake. The arguments contained herein are still relevant, because everywhere around the world, situations of exclusion and confinement of displaced immigrants, or simply those considered misfits, are repeated time and time again. Nor have we alleviated the issue in any way today, since we disregard the lessons learned from the past.
Orthogonal Families of Bicircular Quartics, Quadratic Differentials, and Edwards Normal Form
Authors: Langer Joel C. , Singer David A.
Published: September 2023

Orthogonal families of bicircular quartics are naturally viewed as pairs of singular foliations of C^ by vertical and horizontal trajectories of a non-vanishing quadratic differential. Yet the identification of these trajectories with real quartics in CP2 is subtle. Here, we give an efficient, geometric argument in the course of updating the classical theory of confocal families in the modern language of quadratic differentials and the Edwards normal form for elliptic curves. In particular, we define a parameterized Edwards transformation, providing explicit birational equivalence between each curve in a confocal family and a fixed curve in normal form.
The Current Status of the Liver Liquid Biopsy in MASH Related HCC: Overview and Future Directions
Authors: Ugonabo Onyinye , Udoh Utibe-Abasi Sunday , Rajan Pradeep Kumar , Reeves Heather , Arcand Christina , Nakafuku Yuto , Joshi Tejas , Finley Rob , Pierre Sandrine V. , Sanabria Juan Ramon
Published: September 2023

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.
The Properties and Domain Requirements for Phase Separation of the Sup35 Prion Protein In Vivo
Authors: Grimes Bryan , Jacob Walter , Liberman Amanda R. , Kim Nathan , Zhao Xiaohong , Masison Daniel C. , Greene Lois E.
Published: September 2023

The Sup35 prion protein of budding yeast has been reported to undergo phase separation to form liquid droplets both at low pH in vitro and when energy depletion decreases the intracellular pH in vivo. It also has been shown using purified proteins that this phase separation is driven by the prion domain of Sup35 and does not re-quire its C-terminal domain. In contrast, we now find that a Sup35 fragment consisting of only the N-terminal prion domain and the M-domain does not phase separate in vivo; this phase separation of Sup35 requires the C-terminal domain, which binds Sup45 to form the translation termination complex. The phase-separated Sup35 not only colocalizes with Sup45 but also with Pub1, a stress granule marker protein. In addition, like stress granules, phase separation of Sup35 appears to require mRNA since cycloheximide treatment, which inhibits mRNA release from ribosomes, prevents phase separation of Sup35. Finally, unlike Sup35 in vitro, Sup35 condensates do not disassemble in vivo when the intracellular pH is increased. These results suggest that, in energy-depleted cells, Sup35 forms supramolecular assemblies that differ from the Sup35 liquid droplets that form in vitro.
Effects of Nitro-Oxidative Stress on Biomolecules: Part 1—Non-Reactive Molecular Dynamics Simulations
Authors: Ghasemitarei Maryam , Ghorbi Tayebeh , Yusupov Maksudbek , Zhang Yuantao , Zhao Tong , Shali Parisa , Bogaerts Annemie
Published: September 2023

Plasma medicine, or the biomedical application of cold atmospheric plasma (CAP), is an expanding field within plasma research. CAP has demonstrated remarkable versatility in diverse biological applications, including cancer treatment, wound healing, microorganism inactivation, and skin disease therapy. However, the precise mechanisms underlying the effects of CAP remain incompletely understood. The therapeutic effects of CAP are largely attributed to the generation of reactive oxygen and nitrogen species (RONS), which play a crucial role in the biological responses induced by CAP. Specifically, RONS produced during CAP treatment have the ability to chemically modify cell membranes and membrane proteins, causing nitro-oxidative stress, thereby leading to changes in membrane permeability and disruption of cellular processes. To gain atomic-level insights into these interactions, non-reactive molecular dynamics (MD) simulations have emerged as a valuable tool. These simulations facilitate the examination of larger-scale system dynamics, including protein-protein and protein-membrane interactions. In this comprehensive review, we focus on the applications of non-reactive MD simulations in studying the effects of CAP on cellular components and interactions at the atomic level, providing a detailed overview of the potential of CAP in medicine. We also review the results of other MD studies that are not related to plasma medicine but explore the effects of nitro-oxidative stress on cellular components and are therefore important for a broader understanding of the underlying processes.
Does the Brain Drain Effect Really Exist? A Meta-Analysis
Authors: Böttger Tobias , Poschik Michael , Zierer Klaus
Published: September 2023

Smartphones have become an indispensable part of everyday life. Given the current debate about the use of smartphones in classrooms and schools, it seems appropriate to examine their effects on aspects of cognitive performance in more detail. Ward and colleagues not only demonstrated the negative effect of smartphones on cognitive performance but also showed that the mere presence of these devices can have this effect—this is known as the Brain Drain effect. In the present article, a meta-analytic approach was adopted in order to verify these findings. Here we show a significant overall negative effect of smartphone use and presence. In a database search we identified 22 studies with a total of 43 relevant effects that could be assigned to the categories “memory”, “attention”, and “general cognitive performance”. A subgroup analysis suggests that not all cognitive domains are equally affected by the negative effect of smartphones. The heterogeneity of the effects reinforces this finding. The nationality of the test subjects or the origin of the studies was identified as a further key variable. Our findings also indicate that the distracting effect of smartphones varies on the area studies and further research is necessary. In view of the present research results, it seems important that people in general, and especially children and adolescents in schools and classrooms, learn how to deal with the distracting potential of smartphones.
Upcycling Fly Ash, Red Clay Brick Waste, and Paper Sludge as Feedstock for Manufacturing a Lightweight Extruded Composite: Design and Characterization
Authors: Ospina Salazar Ana María , Valencia Isaza Andrés , Restrepo Montoya José William , Mejía Arcila Johanna Mercedes , Valencia García Marco Fidel
Published: September 2023

In the context of the circular economy and the adoption of one of its business models, namely ”resource recovery”, this study presents an opportunity to valorize industrial and urban wastes using alkaline activation technology to produce hybrid binders. Several alkali-activated binders were produced using response surface methodology based on a mixture of 45/45/10 clay brick waste, fly ash, and Portland cement. The compressive strength and setting time of each were evaluated. The hybrid cementitious pastes achieved up to 45 MPa after 28 days of setting. Based on the experimental data, two binders were selected as the cementitious matrix for composites, with paper sludge as the lightweight aggregate. Incorporating up to 45% volume of paper sludge allowed extrusion of the materials. The addition of paper sludge reduced the compressive and flexural strength. These results were explained by the decrease in density and the increase in porosity. However, there was an improvement in the thermal properties of the composites; in particular, the thermal conductivity range between 0.35 and 0.49 W/mK. Finally, it was found that the composites with 25% volume of paper sludge had the best combination of properties, positioning them as potential construction materials.
Parametric Study of Additional Temperature Stresses in Continuously Welded Rails on Steel Truss Railway Bridges
Authors: Mirković Nikola , Nefovska-Danilović Marija , Ahac Maja , Lakušić Stjepan , Mirković Uroš , Zafirovski Zlatko
Published: September 2023

Additional temperature stresses in continuously welded rails (CWRs) are caused by track/bridge interaction (TBI) due to thermal actions. Exceeding permissible stresses in CWRs on the bridge can lead to track buckling or rail cracking, compromising the safety of railway traffic. The main aim of the conducted study is to determine the effects of the key parameters such as rail cross-sectional area, track longitudinal resistance, bridge expansion length, and longitudinal stiffness of the fixed bridge support on the reduction of additional temperature stresses in CWRs on steel truss railway bridges. To quantify the effects of these parameters, two steel railway bridges with CWRs and the maximum expansion lengths according to UIC Code 774-3 were analyzed: (1) simply supported truss bridge with expansion length of 60 m and (2) continuous truss bridge with expansion lengths of 2 × 60 m. According to the obtained results, the track longitudinal resistance had the most significant impact on additional temperature stresses in CWRs, leading to their reduction of up to 72%. The bridge expansion length and the rail cross-sectional area led to reductions of up to 25% and up to 18%, respectively. Considering the deformation criteria of TBI, the longitudinal stiffness of the fixed bridge support had a minor effect on the reduction of additional temperature stresses in CWRs.