bluuebunny/crossref_metadata_2025 huggingface dataset:
Short- and Long-Term Chest-CT Findings after Recovery from COVID-19: A Systematic Review and Meta-Analysis
Authors: Babar Mustufa , Jamil Hasan , Mehta Neil , Moutwakil Ahmed , Duong Tim Q.
Published: March 2024

While ground-glass opacity, consolidation, and fibrosis in the lungs are some of the hallmarks of acute SAR-CoV-2 infection, it remains unclear whether these pulmonary radiological findings would resolve after acute symptoms have subsided. We conducted a systematic review and meta-analysis to evaluate chest computed tomography (CT) abnormalities stratified by COVID-19 disease severity and multiple timepoints post-infection. PubMed/MEDLINE was searched for relevant articles until 23 May 2023. Studies with COVID-19-recovered patients and follow-up chest CT at least 12 months post-infection were included. CT findings were evaluated at short-term (1–6 months) and long-term (12–24 months) follow-ups and by disease severity (severe and non-severe). A generalized linear mixed-effects model with random effects was used to estimate event rates for CT findings. A total of 2517 studies were identified, of which 43 met the inclusion (N = 8858 patients). Fibrotic-like changes had the highest event rate at short-term (0.44 [0.3–0.59]) and long-term (0.38 [0.23–0.56]) follow-ups. A meta-regression showed that over time the event rates decreased for any abnormality (β = −0.137, p = 0.002), ground-glass opacities (β = −0.169, p < 0.001), increased for honeycombing (β = 0.075, p = 0.03), and did not change for fibrotic-like changes, bronchiectasis, reticulation, and interlobular septal thickening (p > 0.05 for all). The severe subgroup had significantly higher rates of any abnormalities (p < 0.001), bronchiectasis (p = 0.02), fibrotic-like changes (p = 0.03), and reticulation (p < 0.001) at long-term follow-ups when compared to the non-severe subgroup. In conclusion, significant CT abnormalities remained up to 2 years post-COVID-19, especially in patients with severe disease. Long-lasting pulmonary abnormalities post-SARS-CoV-2 infection signal a future public health concern, necessitating extended monitoring, rehabilitation, survivor support, vaccination, and ongoing research for targeted therapies.
Determination of l-Asparaginase Activity and Its Therapeutic Monitoring in Children with Hematological Malignancies in a Single Croatian Center
Authors: Lenicek Krleza Jasna , Katusic Bojanac Ana , Jakovljevic Gordana
Published: March 2024

Background: Among malignant diseases which develop during childhood, hematological cancers, such as leukemias and lymphomas, are the most common. Outcomes have greatly improved due to the refinement of multiagent chemotherapy regimens that include enhanced asparaginase therapy. In this study, we aimed to evaluate our experiences related to the analytical and clinical significance of determining l-Asparaginase activity. Methods: Since 2016, the Laboratory of the Children’s Hospital Zagreb has routinely measured l-Asparaginase activity and to date, has measured more than 280 examples of activity in a total of 57 children with hematological malignancy treated at the Pediatric Oncology Department of the Children’s Hospital Zagreb. Three asparaginase products were available: native E. colil-Asparaginase; a pegylated form of this enzyme; and a native product from Erwinia chrysanthemi. A retrospective data analysis was performed. Results: Out of the fifty-seven children, seven had an allergic reaction (12.3%), five (8.8%) had silent inactivation, and seven (12.3%) developed acute pancreatitis. Allergic reactions and silent inactivation were more common in children treated with native E. colil-Asparaginase, while pancreatitis was more common in children treated with the pegylated form. Conclusions: The monitoring of l-Asparaginase activity may help to optimize therapy by identifying patients with ‘silent inactivation’, and/or by dose correction when l-Asparaginase activity is too high (slow elimination).
Photon-Counting Detector CT Virtual Monoenergetic Images in Cervical Trauma Imaging—Optimization of Dental Metal Artifacts and Image Quality
Authors: Dillinger Daniel , Overhoff Daniel , Froelich Matthias F. , Kaatsch Hanns L. , Booz Christian , Hagen Achim , Vogl Thomas J. , Schönberg Stefan O. , Waldeck Stephan
Published: March 2024

Objectives: The aim of this study was to analyze the extent of dental metal artifacts in virtual monoenergetic (VME) images, as they often compromise image quality by obscuring soft tissue affecting vascular attenuation reducing sensitivity in the detection of dissections. Methods: Neck photon-counting CT datasets of 50 patients undergoing contrast-enhanced trauma CT were analyzed. Hyperattenuation and hypoattenuation artifacts, muscle with and without artifacts and vessels with and without artifacts were measured at energy levels from 40 keV to 190 keV. The corrected artifact burden, corrected image noise and artifact index were calculated. We also assessed subjective image quality on a Likert-scale. Results: Our study showed a lower artifact burden and less noise in artifact-affected areas above the energy levels of 70 keV for hyperattenuation artifacts (conventional polychromatic CT images 1123 ± 625 HU vs. 70 keV VME 1089 ± 733 HU, p = 0.125) and above of 80 keV for hypoattenuation artifacts (conventional CT images −1166 ± 779 HU vs. 80 keV VME −1170 ± 851 HU, p = 0.927). Vascular structures were less hampered by metal artifacts than muscles (e.g., corrected artifact burden at 40 keV muscle 158 ± 125 HU vs. vessels −63 ± 158 HU p < 0.001), which was also reflected in the subjective image assessment, which showed better ratings at higher keV values and overall better ratings for vascular structures than for the overall artifact burden. Conclusions: Our research suggests 70 keV might be the best compromise for reducing metal artifacts affecting vascular structures and preventing vascular contrast if solely using VME reconstructions. VME imaging shows only significant effects on the general artifact burden. Vascular structures generally experience fewer metal artifacts than soft tissue due to their greater distance from the teeth, which are a common source of such artifacts.
A Rare Case of Dirofilariasis in the Genian Region
Authors: Nicolau Andrei , Sava Florin Petrică , Severin Florentina , Ciofu Mihai Liviu , Ferariu Dan , Dodu Daniela , Costan Victor Vlad
Published: March 2024

Dirofilariasis is an infectious disease caused by species of the Dirofilaria genus. It is manifested by the appearance of a subcutaneous swelling, especially in the eye region. We present the case of a 29-year-old patient who presented with facial asymmetry in the right genian region. Following clinical and paraclinical evaluations, the diagnosis of a parasitic cyst was established in the context of dirofilariasis with Dirofilaria repens (D. repens). Treatment consisted of surgical excision of the formation associated with prophylactic antibiotic medication. Macroscopic analysis of the excision piece revealed a structure that contained a cystic cavity and a filamentous form with a length of approximately 10 mm and a diameter of 1 mm. This is the first case of dirofilariasis located in the genian region reported in Romania. The overview of this pathology is important to raise awareness among physicians about its presence and clinical variations. Understanding such cases helps healthcare professionals enhance diagnostic skills, refine treatment strategies, and provide valuable insights into the prevalence and clinical presentation, fostering early detection and timely intervention. Detailed case reports contribute to the understanding of the disease’s epidemiology, including risk factors and transmission patterns, which is essential for effective public health strategies.
Unmanned Aircraft Systems in Road Assessment: A Novel Approach to the Pavement Condition Index and VIZIR Methodologies
Authors: Ortega Rengifo Diana Marcela , Capa Salinas Jose , Perez Caicedo Javier Alexander , Rojas Manzano Manuel Alejandro
Published: March 2024

This paper presents an innovative approach to road assessment, focusing on enhancing the Pavement Condition Index (PCI) and Visión Inspection de Zones et Itinéraires Á Risque (VIZIR) methodologies by integrating Unmanned Aircraft System (UAS) technology. The research was conducted in an urban setting, utilizing a UAS to capture high-resolution imagery, which was subsequently processed to generate detailed orthomosaics of road surfaces. This study critically analyzed the discrepancies between traditional field measurements and UAS-derived data in pavement condition assessment. The study findings demonstrate that photogrammetry-derived data from UAS offer at least similar or, in some cases, improved information on the collection of a comprehensive state of roadways, particularly in local and collector roads. Furthermore, this study proposed key modifications to the existing methodologies, including dividing the road network into segments for more precise and relevant data collection. These enhancements aim to address the limitations of current practices in capturing the diverse and dynamic conditions of urban infrastructure. Integrating UAS technology improves the measurement of pavement condition assessments and offers a more efficient, cost-effective, and scalable approach to urban infrastructure management. The implications of this study are significant for urban planners and policymakers, providing a robust framework for future infrastructure assessment and maintenance strategies.
Design and Demonstration of a Tandem Dual-Rotor Aerial–Aquatic Vehicle
Authors: Wu Sihuan , Shao Maosen , Wu Sifan , He Zhilin , Wang Hui , Zhang Jinxiu , You Yue
Published: March 2024

Aerial–aquatic vehicles (AAVs) hold great promise for marine applications, offering adaptability to diverse environments by seamlessly transitioning between underwater and aerial operations. Nevertheless, the design of AAVs poses inherent challenges, owing to the distinct characteristics of different fluid media. This article introduces a novel solution in the form of a tandem dual-rotor aerial–aquatic vehicle, strategically engineered to overcome these challenges. The proposed vehicle boasts a slender and streamlined body, enhancing its underwater mobility while utilizing a tandem rotor for aerial maneuvers. Outdoor scene tests were conducted to assess the tandem dual-rotor AAV’s diverse capabilities, including flying, hovering, and executing repeated cross-media locomotion. Notably, its versatility was further demonstrated through swift surface swimming on water. In addition to aerial evaluations, an underwater experiment was undertaken to evaluate the AAV’s ability to traverse narrow underwater passages. This capability was successfully validated through the creation of a narrow underwater gap. The comprehensive exploration of the tandem dual-rotor AAV’s potential is presented in this article, encompassing its foundational principles, overall design, simulation analysis, and avionics system design. The preliminary research and design outlined herein offer a proof of concept for the tandem dual-rotor AAV, establishing a robust foundation for AAVs seeking optimal performance in both water and air environments. This contribution serves as a valuable reference solution for the advancement of AAV technology.
FE-FAIR: Feature-Enhanced Fused Attention for Image Super-Resolution
Authors: Guo Aiying , Shen Kai , Liu Jingjing
Published: March 2024

Transformers have performed better than traditional convolutional neural networks (CNNs) for image super-resolution (SR) reconstruction in recent years. Currently, shifted window multi-head self-attention based on the swin transformer is a typical method. Specifically, the multi-head self-attention is used to extract local features in each window, and then a shifted window strategy is used to discover information interaction between different windows. However, this information interaction method needs to be more efficient and include some global feature information, which limits the model’s performance to a certain extent. Furthermore, optimizing the utilization of shallow features, which exhibit significant energy reserves and invaluable low-frequency information, is critical for advancing the efficacy of super-resolution techniques. In order to solve the above issues, we propose the feature-enhanced fused attention (FE-FAIR) method for image super-resolution. Specifically, we design the multi-scale feature extraction module (MSFE) as a shallow feature extraction layer to extract rich low-frequency information from different scales. In addition, we propose the fused attention block (FAB), which introduces channel attention in the form of residual connection based on shifted window self-attention, effectively achieving the fusion of global and local features. Simultaneously, we also discuss other methods to enhance the performance of the FE-FAIR method, such as optimizing the loss function, increasing the window size, and using pre-training strategies. Compared with state-of-the-art SR methods, our proposed method demonstrates better performance. For instance, FE-FAIR outperforms SwinIR by over 0.9 dB when evaluated on the Urban100 (×4) dataset.
Heterostructure-Based Optoelectronic Neuromorphic Devices
Authors: Park Jisoo , Shin Jihyun , Yoo Hocheon
Published: March 2024

The concept of neuromorphic devices, aiming to process large amounts of information in parallel, at low power, high speed, and high efficiency, is to mimic the functions of human brain by emulating biological neural behavior. Optoelectronic neuromorphic devices are particularly suitable for neuromorphic applications with their ability to generate various pulses based on wavelength and to control synaptic stimulation. Each wavelength (ultraviolet, visible, and infrared) has specific advantages and optimal applications. Here, the heterostructure-based optoelectronic neuromorphic devices are explored across the full wavelength range (ultraviolet to infrared) by categorizing them on the basis of irradiated wavelength and structure (two-terminal and three-terminal) with respect to emerging optoelectrical materials. The relationship between neuromorphic applications, light wavelength, and mechanism is revisited. Finally, the potential and challenging aspects of next-generation optoelectronic neuromorphic devices are presented, which can assist in the design of suitable materials and structures for neuromorphic-based applications.
Fast and Accurate Short-Term Load Forecasting with a Hybrid Model
Authors: Shin Sang Mun , Rasheed Asad , Kil-Heum Park , Veluvolu Kalyana C.
Published: March 2024

Short-term electric load forecasting (STLF) plays a pivotal role in modern power system management, bolstering forecasting accuracy and efficiency. This enhancement assists power utilities in formulating robust operational strategies, consequently fostering economic and social advantages within the systems. Existing methods employed for STLF either exhibit poor forecasting performance or require longer computational time. To address these challenges, this paper introduces a hybrid learning approach comprising variational mode decomposition (VMD) and random vector functional link network (RVFL). The RVFL network, serving as a universal approximator, showcases remarkable accuracy and fast computation, owing to the randomly generated weights connecting input and hidden layers. Additionally, the direct links between hidden and output layers, combined with the availability of a closed-form solution for parameter computation, further contribute to its efficiency. The effectiveness of the proposed VMD-RVFL was assessed using electric load datasets obtained from the Australian Energy Market Operator (AEMO). Moreover, the effectiveness of the proposed method is demonstrated by comparing it with existing benchmark forecasting methods using two performance indices such as root mean square error (RMSE) and mean absolute percentage error (MAPE). As a result, our proposed method requires less computational time and yielded accurate and robust prediction performance when compared with existing methods.
A Method for Assessing the Degradation of PVC-Insulated Low-Voltage Distribution Cables Exposed to Short-Term Cyclic Aging
Authors: Bal Semih , Tamus Zoltán Ádám
Published: March 2024

The distribution grid comprises cables with diverse constructions. The insulating material used in low-voltage (LV) distribution cables is predominantly PVC. Furthermore, the presence of cables with different structures in the grid poses challenges in detecting the aging of the cable network. Finding a universal and dependable condition-monitoring technique that can be applied to various types of cables is indeed a challenge. The diverse construction and materials used in different cables make it difficult to identify a single monitoring approach that can effectively assess the condition of all cables. To address this issue, this study aims to compare the thermal aging behavior of different LV distribution cables with various structures, i.e., one cable contains a PVC belting layer, while the other contains filler material. The growing adoption of distributed generation sources, electric vehicles, and new consumer appliances in low-voltage distribution grids can lead to short, repetitive overloads on the low-voltage cable network. Hence, these cable samples were exposed to short-term cyclic accelerated aging in the climate chamber at 110 °C. The cable’s overall behavior under thermal stress was evaluated through frequency and time domain electrical measurements (including tan δ and extended voltage response) and a mechanical measurement (Shore D). The tan δ was measured in the frequency range of 20 Hz–500 kHz by using the Wayne-Kerr impedance analyzer. The extended voltage response measurement was conducted using a C# application developed in-house specifically for laboratory measurements in the .NET environment. The study observed a strong correlation between the different measurement methods used, indicating that electrical methods have the potential to be adopted as a non-destructive condition-monitoring technique.
Image Processing in L1-Norm-Based Discrete Cartesian and Polar Coordinates
Authors: Lee Geunmin , Kim Wonha
Published: March 2024

This paper proposes a radial image processing method performed in an L1-norm-based discrete polar coordinate system. For this purpose, we address the problem that polar coordinates based on the L2-norm cannot exist in discrete systems and then develop a method for converting Cartesian coordinates to L1-norm-based discrete polar coordinates. The proposed method greatly reduces the directional variance occurring in the Cartesian coordinate system and so processes radial directional images along the directions of the local image signal flows. To verify the usages of the proposed method, it was applied to the stabilization of mass-type breast cancer images, a segmentation of extremely deformable objects such as biomedical objects. In all cases, the proposed method produced superior results compared to the processing in the Cartesian coordinate systems. The proposed method is useful for processing or analyzing diffusing and deformable images such as bio-cell and smoke images.
Dielectric-Loaded Horn Antenna Design and Simulation Using the Metamaterial Method
Authors: Zhang Bowen , Du Wei , Liu Nengwu , Fu Guang
Published: March 2024

In this paper, we propose the design and simulation of a dielectric horn antenna using the metamaterial method; this antenna has a double-layer dielectric waveguide transmission structure. With the continuous development of microwave feed sources, the traditional waveguide systems are no longer able to meet today’s antenna requirements. Consequently, dielectric-loading technology is gradually being applied to design horns. A key advantage of this antenna is its significantly expanded bandwidth of 163.3%. Furthermore, when compared to ridge horns, this dielectric-loaded horn demonstrates superior radiation properties across the entire frequency band, including aperture efficiency (95% in the L band, 65.4% in the S band, 41.5% in the C band, and 28.7% in the X band) and cross-polarization isolation (≥51.6 dB). In addition, before researching the theory of dielectric-loading technology, the modes of the horns should be analyzed. This helps us to better control the hybrid mode. The metamaterial method was applied to achieve stable dielectric properties. We finally conducted experiments on the antenna to validate the relevant theories and feasibility.
Applying Machine Learning to Construct a Printed Circuit Board Gold Finger Defect Detection System
Authors: Huang Chien-Yi , Tsai Pei-Xuan
Published: March 2024

Machine vision systems use industrial cameras’ digital sensors to collect images and use computers for image pre-processing, analysis, and the measurements of various features to make decisions. With increasing capacity and quality demands in the electronic industry, incoming quality control (IQC) standards are becoming more and more stringent. The industry’s incoming quality control is mainly based on manual sampling. Although it saves time and costs, the miss rate is still high. This study aimed to establish an automatic defect detection system that could quickly identify defects in the gold finger on printed circuit boards (PCBs) according to the manufacturer’s standard. In the general training iteration process of deep learning, parameters required for image processing and deductive reasoning operations are automatically updated. In this study, we discussed and compared the object detection networks of the YOLOv3 (You Only Look Once, Version 3) and Faster Region-Based Convolutional Neural Network (Faster R-CNN) algorithms. The results showed that the defect classification detection model, established based on the YOLOv3 network architecture, could identify defects with an accuracy of 95%. Therefore, the IQC sampling inspection was changed to a full inspection, and the surface mount technology (SMT) full inspection station was canceled to reduce the need for inspection personnel.
Utilizing Latent Diffusion Model to Accelerate Sampling Speed and Enhance Text Generation Quality
Authors: Li Chenyang , Zhang Long , Zheng Qiusheng
Published: March 2024

Diffusion models have achieved tremendous success in modeling continuous data modalities, such as images, audio, and video, yet their application in discrete data domains (e.g., natural language) has been limited. Existing methods primarily represent discrete text in a continuous diffusion space, incurring significant computational overhead during training and resulting in slow sampling speeds. This paper introduces LaDiffuSeq, a latent diffusion-based text generation model incorporating an encoder–decoder structure. Specifically, it first employs a pretrained encoder to map sequences composed of attributes and corresponding text into a low-dimensional latent vector space. Then, without the guidance of a classifier, it performs the diffusion process for the sequence’s corresponding latent space. Finally, a pretrained decoder is used to decode the newly generated latent vectors, producing target texts that are relevant to themes and possess multiple emotional granularities. Compared to the benchmark model, DiffuSeq, this model achieves BERTScore improvements of 0.105 and 0.009 on two public real-world datasets (ChnSentiCorp and a debate dataset), respectively; perplexity falls by 3.333 and 4.562; and it effectively quadruples the text generation sampling speed.
Circular Economy Aspects of Permanent Magnet Synchronous Reluctance Machine Design for Electric Vehicle Applications: A Review
Authors: Katona Mihály , Orosz Tamás
Published: March 2024

Innovative technological solutions have become increasingly critical in addressing the transportation sector’s environmental impact. Passenger vehicles present an opportunity to introduce novel drivetrain solutions that can quickly penetrate the electric vehicle market due to their shorter development time and lifetime compared to commercial vehicles. As environmental policy pressure increases and customers demand more sustainable products, shifting from a linear business approach to a circular economy model is in prospect. The new generation of economically competitive machines must be designed with a restorative intention, considering future reuse, refurbishment, remanufacture, and recycling possibilities. This review investigates the market penetration possibilities of permanent magnet-assisted synchronous reluctance machines for mini and small-segment electric vehicles, considering the urban environment and sustainability aspects of the circular economy model. When making changes to the materials used in an electric machine, it is crucial to evaluate their potential impact on efficiency while keeping the environmental impact of those materials in mind. The indirect ecological effect of the vehicle’s use phase may outweigh the reduction in manufacturing and recycling at its end-of-life. Therefore, thoroughly analysing the materials used in the design process is necessary to ensure maximum efficiency while minimising the environmental impact.
Evaluation of Recovery of Tight Sandstone Gas Reservoirs Based on a Seepage Steady-State Model
Authors: Zhang Jianzhong , Gao Shusheng , Xiong Wei , Ye Liyou , Liu Huaxun , Zhu Wenqing , An Weiguo , Han Donghuan , Lin Baicen
Published: March 2024

As an important indicator for measuring the effectiveness and level of oil and gas field development, recovery rate has always been a focus in the research of oil and gas fields. Reservoirs of tight sandstone gas formations have significant characteristics of low porosity, high permeability, and high water content, which leads to greater difficulty in their development and makes it challenging to evaluate the recovery rate. Newtonian mechanics, as an important component of the mechanical system, is an innovative application of classical mechanics in the field of seepage mechanics when applied to the two-phase flow of gas and water. Firstly, starting from the perspective of mechanics analysis, we derive a steady-state model for gas–water two-phase infiltration and obtain the productivity equation based on this model. Then, according to the steady-state model, we establish a method to calculate the effective control radius of gas reservoirs under different production conditions and reservoir physical properties. Finally, using Matlab 2018a programming based on the productivity equation, we calculate the gas recovery under different conditions during constant pressure drop production and constant production rate production. The results indicate that the effective control radius of the reservoir decreases with an increase in the economic ultimate daily gas production, increases with an increase in production pressure difference, slightly decreases with an increase in startup pressure gradient, and correspondingly increases with an increase in microtube radius and quantity. Regardless of whether it is production with a fixed pressure drop or production with a fixed production rate, the gas recovery decreases as the production pressure drop and bottomhole abandonment pressure increase, but it increases as the proportion of the single-well control radius increases. In production with a fixed pressure drop, the gas recovery remains consistent across different reservoir quality indices. However, in production with a fixed production rate, the gas recovery initially increases rapidly and then gradually slows down as the reservoir quality index increases, and there is an obvious critical permeability (0.1 mD). The research findings are based on the mechanical analysis of porous media, delving into the laws governing fluid flow during infiltration. The derived infiltration model can be used to calculate the effective control radius and evaluate recovery rates, providing practical guidance for reservoir development.
Research on Digital Twin Dynamic Modeling Method for Transmission Line Deicing System
Authors: Chen Qinghao , Liu Tianyu , Wang Zhangqi , Miao Rui
Published: March 2024

A digital twin is recognized as a pivotal technology in a new type of power system monitoring as it provides an effective method for monitoring the vibration caused by ice shedding in overhead transmission lines. The digital twin model differs from traditional models in that it has the characteristics of precise mapping and real-time simulation. These emerging characteristics lead to urgent updating of the existing modeling approaches. Therefore, the current study proposes a dynamic digital twin modeling method for transmission line ice-shedding systems. In this approach, an analytical solution for conductor deicing oscillation is proposed to describe the span and tension unchanged in any time period and then segmented and iteratively corrected with measured time-varying parameters to implement real-time simulation functionality. A dynamic geometric model for transmission lines is proposed based on the Unity3D platform. In addition, a human-computer interaction visualization platform is proposed to display twin data, with the objective of realizing precise mapping of real transmission lines. Finally, an application of this systematic approach to continuous three-span wire demonstrates the feasibility and effectiveness of the proposed approach.
Disturbance Observer-Based Robust Cooperative Adaptive Cruise Control Approach under Heterogeneous Vehicle
Authors: Kang Chang Mook
Published: March 2024

Cooperative adaptive cruise control (CACC) is one of the control methods that improves fuel efficiency by allowing multiple vehicles to drive in groups. In this paper, we propose a robust CACC with a heterogeneous vehicle using a disturbance observer. The longitudinal vehicle dynamics, including the engine dynamics, have been modeled as a first-order model using a time constant. However, the simplified first-order model varies in accuracy depending on the dynamic driving situation due to engine performance and air drag force. Designing a more accurate higher-order model might be a solution, but this has a high computational cost. Thus, we propose an augmented state observer for model uncertainties and disturbances. The proposed method makes it possible to design a CACC using nominal parameters without considering dynamic changes to the model parameters. Also, the proposed method can directly compensate for disturbances, compared to the adaptation technique, while also satisfying string stability. The proposed method was validated via computational simulations for heterogeneous traffic and experimental evaluation.
The Application of the Ultrasound Technique in the Production of Rosé and Red Wines
Authors: Lizama Victoria , Álvarez Inmaculada , García-Esparza María José
Published: March 2024

The application of the ultrasound technique (US) in the production of rosé and red wines has demonstrated that the aromatic composition of rose wine can be affected and that it contributes to increasing the color of red wines without increasing the extraction of astringent tannins. The ultrasound treatment has favored the extraction of anthocyanins, which has had an impact on the increase in color density (C.D.) and has allowed greater color stability over time. Moreover, significant differences have been found between the two US systems applied, with continuous treatment being more effective in the extraction of phenolic compounds than pulsed treatment. The application system of the US also affects the aromatic composition of the wines. These results are of interest, as some esters have been described as important odorants in wines.
Source-Separated Industrial Wastewater Is a Candidate for Biogas Production through Anaerobic Digestion
Authors: Elliott Jake A. K. , Krohn Christian , Ball Andrew S.
Published: March 2024

Anaerobic digestion is a potential treatment for industrial wastewater that provides valuable end-products, including renewable energy (biogas). However, waste streams may be too variable, too dilute at high volumes, or missing key components for stable digestion; all factors that increase costs and operational difficulty, making optimisation crucial. Anaerobic digestion may benefit from process intensification, particularly the novel combination of high-strength source-separated wastewater to minimise volume, together with the use of biosolids biochar as a chemical and microbial stabiliser. This study investigates the stability, yield, and microbial community dynamics of the anaerobic digestion of source-separated industrial wastewater from a food manufacturer and a logistics company, using biosolids biochar as an additive, focusing on gas and volatile fatty acid (VFA) production, process stability, and the microbial community using bench-scale semi-continuous reactors at 30- and 45-day hydraulic retention time (HRT). While gas yields were lower than expected, stability was possible at high HRT. Methane production reached 0.24 and 0.43 L day−1 per litre reactor working volume at 30- and 45-day HRT, respectively, despite high VFA concentration, and was linked to the relative abundance of Methanosarcina in the microbial community. Interactions between substrate, VFA concentration, and the microbial community were observed. Biochar-assisted anaerobic digestion holds promise for the treatment of source-separated wastewater.
Efficient and Secure Distributed Data Storage and Retrieval Using Interplanetary File System and Blockchain
Authors: Bin Saif Muhammad , Migliorini Sara , Spoto Fausto
Published: March 2024

Blockchain technology has been successfully applied in recent years to promote the immutability, traceability, and authenticity of previously collected and stored data. However, the amount of data stored in the blockchain is usually limited for economic and technological issues. Namely, the blockchain usually stores only a fingerprint of data, such as the hash of data, while full, raw information is stored off-chain. This is generally enough to guarantee immutability and traceability, but misses to support another important property, that is, data availability. This is particularly true when a traditional, centralized database is chosen for off-chain storage. For this reason, many proposals try to properly combine blockchain with decentralized IPFS storage. However, the storage of data on IPFS could pose some privacy problems. This paper proposes a solution that properly combines blockchain, IPFS, and encryption techniques to guarantee immutability, traceability, availability, and data privacy.
Linked Open Government Data: Still a Viable Option for Sharing and Integrating Public Data?
Authors: Quarati Alfonso , Albertoni Riccardo
Published: March 2024

Linked Data (LD) principles, when applied to Open Government Data (OGD), aim to make government data accessible and interconnected, unlocking its full potential and facilitating widespread reuse. As a modular and scalable solution to fragmented government data, Linked Open Government Data (LOGD) improve citizens’ understanding of government functions while promoting greater data interoperability, ultimately leading to more efficient government processes. However, despite promising developments in the early 2010s, including the release of LOGD datasets by some government agencies, and studies and methodological proposals by numerous scholars, a cursory examination of government websites and portals suggests that interest in this technology has gradually waned. Given the initial expectations surrounding LOGD, this paper goes beyond a superficial analysis and provides a deeper insight into the evolution of interest in LOGD by raising questions about the extent to which the dream of LD has influenced the reality of OGD and whether it remains sustainable.
Fire Protection of Steel Structures of Oil and Gas Facilities: Multilayer, Removable, Non-Combustible Covers
Authors: Gravit Marina , Prusakov Vasiliy , Shcheglov Nikita , Kotlyarskaya Irina
Published: March 2024

Fire protection is required to protect metal structures of oil and gas facilities from fires. Such fire protection should provide high fire resistance limits: 60, 90, 120 and more minutes. Specialists of LLC “RPC PROMIZOL ” developed a multilayer, removable type of fire protection made of superfine basalt fibre and ceramic materials for operation in Arctic conditions. Five experimental studies were carried out in standard and hydrocarbon fire regimes. The fire protection effectiveness of the products for I20 beams without load was obtained: a 50 mm thick coating provided 130 min of a standard fire regime; a 15 mm thick coating provided 60 min. The 15 mm thick coating provided 30 min of a hydrocarbon fire regime and the 50 mm thick coating provided 93 min of a hydrocarbon fire regime. The I40 beam under a load of 19.9 tf showed an R243 for the standard fire regime. The coefficients of effective thermal conductivity and specific heat capacity of fire-retardant compositions were determined by solving the inverse heat conduction problem. The problem was solved by modelling using the QuickField 7.0 software package, which implements FEM. Modelling showed that for obtaining the fire resistance limit R120 under the standard fire regime for the sample steel structure from an I40 beam, it is enough to apply fire protection with a thickness of 25 mm instead of 50 mm, which agrees with the experimental data. For the hydrocarbon regime, it is predicted that R120 can be obtained at a thickness of 45 mm instead of 50 mm.
The Effect of Varying the Air Flow in a Solar Collector on the Quality of Arabica Coffee Beans
Authors: Siagian Parulian , Napitupulu Farel Hasiholan , Ambarita Himsar , Sihombing Hendrik Voice , Sibagariang Yogie Probo , Siagian Horas Sotardodo
Published: March 2024

Agricultural commodity drying technology aims to maintain and improve the quality of agricultural products. Coffee quality is important for the welfare of coffee farmers, and drying technology plays an important role in determining the quality of coffee. Various drying models can be applied, including the traditional model that is still applied today: drying directly under solar radiation. One drying technology that can accelerate the drying time is varying the air velocity in the drying chamber. In this study, the air velocity was varied by 1–3 m/s over coffee bean samples with an initial weight of 1500 g that were dried in parallel simultaneously. The time required was 25 h, with a maximum radiation of 586.9 w/m2 and total solar energy over 3 days of 16.6 MJ/m2. It was found that good quality coffee was achieved using drying box 1, with a drying air velocity of 1.0 m/s, with which a final mass of 732.24 g was obtained with coffee moisture content of 12.0%, protein content of 11.7%, carbohydrate content of 21.7%, and free fatty acid content of 0.05%. Higher air velocities resulted in almost the same protein and carbohydrate content, as well as a fatty acid content of less than 0.1%, but a higher moisture content.
Simulation of Starch Gel Printing and Deformation Process Using COMSOL
Authors: Qin Zhou , Li Zhihua , Zou Xiaobo , Guo Ziang , Wang Siwen , Chen Zhiyang
Published: March 2024

The food industry holds immense promise for 3D printing technology. Current research focuses mainly on optimizing food material composition, molding characteristics, and printing parameters. However, there is a notable lack of comprehensive studies on the shape changes of food products, especially in modeling and simulating deformations. This study addresses this gap by conducting a detailed simulation of the starch gel printing and deformation process using COMSOL Multiphysics 6.2 software. Additive manufacturing (AM) technology is widely acclaimed for its user-friendly operation and cost-effectiveness. The 3D printing process may lead to changes in part dimensions and mechanical properties, attributable to the accumulation of residual stresses. Studies require a significant amount of time and effort to discover the optimal composition of the printed material and the most effective deformed 3D structure. There is a risk of failure, which can lead to wasted resources and research delays. To tackle this issue, this study thoroughly analyzes the physical properties of the gel material through COMSOL Multiphysics 6.2 software, It simulates the heat distribution during the 3D printing process, providing important insights into how materials melt and solidify. Three-part models with varying aspect ratios were meticulously designed to explore shape changes during both the printing process and exposure to an 80 °C environment, employing NMR and rheological characterization. Using the generalized Maxwell model for material simulation in COMSOL Multiphysics, the study predicted stress and deformation of the parts by analyzing solid heat transfer and solid mechanics physical fields. Simulation results showed that among three models utilizing a gel-PET plastic membrane bilayer structure, Model No. 1, with the largest aspect ratio, exhibited the most favorable deformation under an 80 °C baking environment. It displayed uniform bending in the transverse direction without significant excess warpage in the edge direction. In contrast, Models No. 2 and No. 3 showed varying degrees of excess warpage at the edges, with Model No. 3 exhibiting a more pronounced warpage. These findings closely aligned with the actual printing outcomes.
Understanding Ligilactobacillus salivarius from Probiotic Properties to Omics Technology: A Review
Authors: Yang Yong , Song Xin , Wang Guangqiang , Xia Yongjun , Xiong Zhiqiang , Ai Lianzhong
Published: March 2024

Ligilactobacillus salivarius (basonym: Lactobacillus salivarius, L. salivarius) is a type of lactic acid bacteria (LAB) commonly found in the oropharyngeal-gastrointestinal tract (OGT). It has gained significant attention due to its probiotic and functional properties as well as its various health-promoting roles. L. salivarius strains exhibit strong resistance and adhesion in the OGT along with outstanding antioxidant and antimicrobial properties. Additionally, numerous L. salivarius strains have the ability to produce bacteriocins with antagonistic activity. These probiotic characteristics of L. salivarius indicate its remarkable potential in promoting favorable effects on human health. It has also been observed that L. salivarius has a positive effect on the composition of intestinal microbiota, thereby improving the metabolic profiling of intestinal microbiota, promoting a healthy and balanced internal environment. In recent years, multi-omics technologies such as genomics, transcriptomics, proteomics and metabolomics have been employed to gain a deeper understanding of the roles and mechanisms of L. salivarius associated with its functional properties. This review aims to provide an overview of the probiotic characteristics of L. salivarius, containing its specific interactions with the host microflora, as well as insights from omics studies.
Significance of Fabry-Perot Cavities for Space Gravitational Wave Antenna DECIGO
Authors: Tsuji Kenji , Ishikawa Tomohiro , Umemura Kurumi , Kawasaki Yuki , Iwaguchi Shoki , Shimizu Ryuma , Ando Masaki , Kawamura Seiji
Published: March 2024

DECIGO is a future Japanese project for the detection of gravitational waves in space. To conduct various scientific missions, including the verification of cosmic inflation through the detection of primordial gravitational waves as the main objective, DECIGO is designed to have high sensitivity in the frequency band from 0.1 to 10 Hz, with arms of length 1000 km. Furthermore, the use of the Fabry-Perotcavity in these arms has been established for the DECIGO project. In this paper, we scrutinize the significance of the Fabry-Perot cavity for promoting this project, with a focus on the possibility of observing gravitational waves from cosmic inflation and binary compact star systems as indicators. The results show that using the Fabry-Perot cavity is extremely beneficial for detecting them, and it is anticipated to enable the opening of a new window in gravitational wave astronomy.
Synthesis and Properties of Polyvinylidene Fluoride-Hexafluoropropylene Copolymer/Li6PS5Cl Gel Composite Electrolyte for Lithium Solid-State Batteries
Authors: Liang Xinghua , Shi Xueli , Lan Lingxiao , Qing Yunmei , Zhang Bing , Fang Zhijie , Wang Yujiang
Published: March 2024

Gel electrolytes for lithium-ion batteries continue to replace the organic liquid electrolytes in conventional batteries due to their advantages of being less prone to leakage and non-explosive and possessing a high modulus of elasticity. However, the development of gel electrolytes has been hindered by their generally low ionic conductivity at room temperature and high interfacial impedance with electrodes. In this paper, a poly (vinylidene fluoride)-hexafluoropropylene copolymer (PVdF-HFP) with a flexible structure, Li6PS5Cl (LPSCl) powder of the sulfur–silver–germanium ore type, and lithium perchlorate salt (LiClO4) were prepared into sulfide gel composite electrolyte films (GCEs) via a thermosetting process. The experimental results showed that the gel composite electrolyte with 1% LPSCl in the PVdF-HFP matrix exhibited an ionic conductivity as high as 1.27 × 10−3 S·cm−1 at 25 °C and a lithium ion transference number of 0.63. The assembled LiFePO4||GCEs||Li batteries have excellent rate (130 mAh·g−1 at 1 C and 54 mAh·g−1 at 5 C) and cycling (capacity retention was 93% after 100 cycles at 0.1 C and 80% after 150 cycles at 0.2 C) performance. This work provides new methods and strategies for the design and fabrication of solid-state batteries with high ionic conductivity and high specific energy.
Dissecting the Genetic Diversity of USDA Cowpea Germplasm Collection Using Kompetitive Allele Specific PCR-Single Nucleotide Polymorphism Markers
Authors: Potts Jesse , Michael Vincent N. , Meru Geoffrey , Wu Xingbo , Blair Matthew W.
Published: March 2024

Cowpea (Vigna unguiculata L. Walp) is an important grain legume crop of the subtropics, particularly in West Africa, where it contributes to the livelihoods of small-scale farmers. Despite being a drought-resilient crop, cowpea production is hampered by insect pests, diseases, parasitic weeds, and various abiotic stresses. Genetic improvement can help overcome these limitations, and exploring diverse cowpea genetic resources is crucial for cowpea breeding. This study evaluated the genetic diversity of 361 cowpea accessions from the USDA core collection for the species using 102 Kompetitive Allele Specific PCR (KASP) single nucleotide polymorphism (SNP) markers. A total of 102 KASP-SNP was validated in the germplasm panel, and 72 showed polymorphism across the germplasm panel. The polymorphism information content (PIC) of all SNPs ranged from 0.1 to 0.37, with an average of 0.29, while the mean observed heterozygosity was 0.52. The population structure revealed three distinct populations that clustered into two major groups after phylogenetic analysis. Analysis of molecular variance (AMOVA) indicated greater genetic variation within populations than among populations. Although cowpea generally has a narrow genetic diversity, the accessions used in this study exhibited considerable variation across geographical regions, sub-species, and improvement status. These results indicated that the selected KASP genotyping assay can provide robust and accurate genotyping data for application in the selection and management of cowpea germplasm in breeding programs and genebanks.