bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Effect of Vibrating Process on the Compactness of Slipform Concrete
Authors: Chai Min , Hu Changbin , Cheng Mingyue
Published: July 2023

Compaction directly affects concrete’s strength and durability. In this paper, the relationship between vibration parameters and compactness is modeled by using colored aggregates and image methods to analyze the compactness of concrete characterized by pore structure. Experiments were conducted to investigate the effects of vibrating frequency and duration on the aggregate distribution coefficient, segregation rate, and porosity of slipform concrete. The test results showed that the smaller the aggregate size under high-frequency pounding, the better the concrete compactness. In addition, the aggregate segregation rate and concrete strength increased and then decreased with the pounding length, and the greater the pounding frequency, the more pronounced the trend. Lastly, the concrete’s internal porosity increased and then decreased with the pounding length. This study obtained the control range of aggregate segregation rate and porosity through analysis, and established equations for the optimal vibration parameters and paving speed of sliding form concrete to guide the reasonable control of actual sliding form paving and vibration construction processes.
From Seeing to Knowing with Artificial Intelligence: A Scoping Review of Point-of-Care Ultrasound in Low-Resource Settings
Authors: Venkatayogi Nethra , Gupta Maanas , Gupta Alaukik , Nallaparaju Shreya , Cheemalamarri Nithya , Gilari Krithika , Pathak Shireen , Vishwanath Krithik , Soney Carel , Bhattacharya Tanisha , Maleki Nirvana , Purkayastha Saptarshi , Gichoya Judy Wawira
Published: July 2023

The utilization of ultrasound imaging for early visualization has been imperative in disease detection, especially in the first responder setting. Over the past decade, rapid advancements in the underlying technology of ultrasound have allowed for the development of portable point-of-care ultrasounds (POCUS) with handheld devices. The application of POCUS is versatile, as seen by its use in pulmonary, cardiovascular, and neonatal imaging, among many others. However, despite these advances, there is an inherent inability of translating POCUS devices to low-resource settings (LRS). To bridge these gaps, the implementation of artificial intelligence offers an interesting opportunity. Our work reviews recent applications of POCUS devices within LRS from 2016 to 2023, identifying the most commonly utilized clinical applications and areas where further innovation is needed. Furthermore, we pinpoint areas of POCUS technologies that can be improved using state-of-art artificial intelligence technologies, thus enabling the widespread adoption of POCUS devices in low-resource settings.
Microbial-Based Heavy Metal Bioremediation: Toxicity and Eco-Friendly Approaches to Heavy Metal Decontamination
Authors: Zhou Biao , Zhang Tiejian , Wang Fei
Published: July 2023

There are several industrial processes in which heavy metals are used, including but not limited to chrome plating and tanning. Amongst the most toxic heavy metals to human health are arsenic, cadmium, chromium, lead, copper, nickel, and mercury. The aforementioned toxic metals possess the ability to cause contamination upon their release into the environment. Humans and aquatic and terrestrial animals are at risk from heavy metals in water and soil. Heavy metal toxicity has the potential to result in several health complications, such as renal and hepatic impairment, dermatological afflictions, cognitive lethargy, and potentially oncogenic manifestations. The removal of heavy metals from wastewater and soil can be accomplished using a variety of conventional methods, such as membrane filtration, reverse osmosis, chemical reduction, and adsorption. These methods have several disadvantages, such as generating an abundance of secondary pollutants, and entail significantly higher costs in comparison to biological methods. Conversely, eco-friendly techniques based on microbes have numerous advantages. This review provides a comprehensive overview of biological processes that remove heavy metal ions, both metabolically dependent and metabolically independent. Additionally, we also focused on the source and toxicity of these heavy metals. This study is expected to be particularly beneficial for the development of biological heavy metal treatment systems for soil and water.
Estimation of Methane Gas Production in Turkey Using Machine Learning Methods
Authors: Ünal Uyar Güler Ferhan , Terzioğlu Mustafa , Kayakuş Mehmet , Tutcu Burçin , Çoşgun Ahmet , Tonguç Güray , Kaplan Yildirim Rüya
Published: July 2023

Methane gas emission into the atmosphere is rising due to the use of fossil-based resources in post-industrial energy use, as well as the increase in food demand and organic wastes that comes with an increasing human population. For this reason, methane gas, which is among the greenhouse gases, is seen as an important cause of climate change along with carbon dioxide. The aim of this study was to predict, using machine learning, the emission of methane gas, which has a greater effect on the warming of the atmosphere than other greenhouse gases. Methane gas estimation in Turkey was carried out using machine learning methods. The R2 metric was calculated as logistic regression (LR) 94.9%, artificial neural networks (ANNs) 93.6%, and support vector regression (SVR) 92.3%. All three machine learning methods used in the study were close to ideal statistical criteria. LR had the least error and highest prediction success, followed by ANNs and then SVR. The models provided successful results, which will be useful in the formulation of policies in terms of animal production (especially cattle production) and the disposal of organic human wastes, which are thought to be the main causes of methane gas emission.
Investigation of Durability Properties for Lightweight Structural Concrete with Hemp Shives Instead of Aggregate
Authors: Horszczaruk Elżbieta , Strzałkowski Jarosław , Głowacka Anna , Paszkiewicz Oliwia , Markowska-Szczupak Agata
Published: July 2023

The paper presents the results of testing the performance of lightweight structural concrete containing hemp shives as an aggregate. It has been analysed how the higher binder content and use of the Portland cement affect the thermal and microbiological properties of the lightweight concrete. The aggregates of the plant origin and cement are incompatible because the plant chemical compounds, dissolved in water or an alkaline environment, inhibit cement hydration. To avoid this, mineralisation of the aggregates of plant origin is necessary. The most often used binder in hemp concrete is hydrated lime, a mineraliser. An addition of hydrated lime and sodium trisilicate was used for hemp shiv mineralisation in the tested materials with a cement binder. Concrete containing hemp shiv and cement binder, of which volume share in the concrete was at most 15%, was prepared as a reference concrete. In the remaining three concretes, the total content of the binder in relation to hemp shiv (by mass) was increased 2.5 times. It was shown that lime-binder hemp concrete offers a promising antimicrobial strategy, as it can inhibit bacterial and fungal growth on their surface with superior efficacy. The best results were obtained for tested concretes with the cement–lime binder regarding compressive strength; the average compressive strength was 9.56 MPa.
GIS-Based Multi-Objective Routing Approach for Street-Based Sporting-Event Routing
Authors: Yoon Young-Joon , Kim Seo-Yeon , Lee Yun-Ku , Ham Namhyuk , Kim Ju-Hyung , Kim Jae-Jun
Published: July 2023

This study proposes a decision-making framework that integrates a routing model based on the geographic information system (GIS) and a genetic algorithm into a building-information modeling (BIM) environment to overcoming the limitations of the planning process of traditional street-based sporting events. There is a lack of research on improving the manually conducted decision-making processes for street-based sporting events. Moreover, previous routing studies were limited to GIS environments, and proposals for decision-making models integrated with BIM environments are lacking. In this study, the applicability of the framework was verified by presenting the variables of the existing GIS-based routing model as environmental variables to consider the impact of street-based sports events on a city. The evaluation model for the route selection was parameterized independently, such that its priority could be changed according to the user’s needs. Moreover, we integrated the data into BIM to create and analyze models that assess urban effects. This method is a decision-making system for policymakers and event planners to promptly conduct initial venue surveys through the technological integration of GIS–routing–BIM. Additionally, the GIS stipulated in this study can be applied to other cities. The Gwanghwamun area of Seoul, South Korea, was selected as the case study.
Enhanced Electrical Injury Using Triangular Interdigitated Electrodes for Catheter-Based Irreversible Electroporation
Authors: Lee Dong-Jin , Kim Dae Yu
Published: July 2023

Irreversible electroporation (IRE) is a promising nonthermal ablation technique that uses high-voltage electrical pulses to create permanent pores in the cell membrane of target tissue. Recently, endoscopic IRE with catheter-based electrodes has attracted significant attention as a potential alternative tool for gastrointestinal tumors, but it has been challenged owing to the limited electric field distribution in an in-plane electrode configuration, in which rectangular interdigitated electrodes (IDEs) are commonly used. Herein, we report an enhanced electrical injury in tissue using triangular IDEs that cause strong electric fields to be induced at the tip of the electrode fingers. A set of 10 pulses with a duration of 100 μs and a frequency of 1 Hz were delivered to the tissue, and a finite element method was used to calculate the electrical injury in the gastrointestinal model. The probability of cell death by electrical injury at the triangular IDEs increases by approximately 10 times compared to that of conventional rectangular IDEs at the same electrode distance. These results could potentially pave the way toward designing electrodes in catheter-based IRE devices.
Experimental Design and Validation of an Adjustable Straw Guide Structure for a Grain Combine Harvester Thresher Based on a Material Movement Model
Authors: Wu Luofa , Chen Daogen , Xu Xieqing , Wu Yanqi
Published: July 2023

The threshing device is the core component of the grain combine harvester, and the straw guide board plays an important role in the threshing device. In the past, the guiding structure of the threshing device could not optimize the working performance of the machine by adjusting the spiral angle. In this study, an adjustable straw guide board was designed, and the movement model of the straw on the straw guide board was analyzed. The response surface method was used to perform field experiments, and the experimental data were analyzed using quadratic polynomial regression. The results show that the drum rotation speed, operating speed, and spiral angle of the straw guide board have significant effects on the percentage of loss rate (PLR), percentage of impurities rate (PIR), and percentage of broken rate (PBR). Further optimization analysis showed that the predicted values of the PLR, PIR, and PBR were 1.18%, 0.72%, and 0.54%, respectively, whereas the experimental verification values were 1.26%, 0.73%, and 0.61%, respectively. The absolute errors between the experimental and predicted values were very small; however, the optimized field test verified values decreased by 8.31%, 50.04%, and 60.30%, respectively, which indicates that the optimized harvester had better operation quality.
Incorporating Multi-Hypotheses as Soft-Templates in Neural Headline Generation
Authors: A Yana , Liu Zhenghao , Dong Suyalatu , Bu Fanyu
Published: July 2023

Neural models are widely applied to headline generation. Template-based methods are a promising direction to overcome the shortcomings of the neural headline generation (NHG) model in generating duplicate or extra words. Previous works often retrieve relevant headlines from the training data and adopt them as the soft template to guide the NHG model. However, these works had two drawbacks: reliance on additional retrieval tools, and uncertainty regarding semantic consistency between the retrieved headline and the source article. The NHG model uncertainty can be utilized to generate hypotheses. The hypotheses generated based on a well-trained NHG model not only contain salient information but also exhibit diversity, making them suitable as soft templates. In this study, we use a basic NHG model to generate multiple diverse hypotheses as candidate templates. Then, we propose a novel Multiple-Hypotheses-based NHG (MH-NHG) model. Experiments on English headline generation tasks demonstrate that it outperforms several baseline systems and achieves a comparable performance with the state-of-the-art system. This indicates that MH-NHG can generate more accurate headlines guided by multiple hypotheses.
Research on Multi-Sensor Simultaneous Localization and Mapping Technology for Complex Environment of Construction Machinery
Authors: Ren Haoling , Zhao Yaping , Lin Tianliang , Wu Jiangdong
Published: July 2023

Simultaneous localization and mapping (SLAM), as a key task of unmanned vehicles for construction machinery, is of great significance for later path planning and control. Construction tasks in the engineering field are mostly carried out in bridges, tunnels, open fields, etc. The prominent features of these environments are high scene similarity, few geometric features, and large-scale repetitive texture information, which is prone to sensor detection degradation. This leads to positioning drift and map building failure. The traditional method of motion estimation and 3D reconstruction uses a single sensor, which lacks enough information, has poor adaptability to the environment, and cannot guarantee good positioning accuracy and robustness in complex environments. Currently, the strategy of multi-sensor fusion is proven to be an effective solution and is widely studied. This paper proposes a SLAM framework that integrates LiDAR, IMU, and camera. It tightly couples the texture information observed by camera, the geometric information scanned by LiDAR, and the measured value of IMU, allowing visual-inertial odometry (VIO) and LiDAR-inertial odometry (LIO) common implementation. The LIO subsystem extracts point cloud features and matches them with the global map. The obtained pose estimation can be used for the initialization of the VIO subsystem. The VIO system uses direct method to minimize the photometric error and IMU measurement error between images to estimate the pose of the robot and the geometric structure of the scene. The two subsystems assist each other to perform pose estimation, and can operate normally even when any subsystem fails. A factor graph is used to combine all constraints to achieve global pose optimization. Keyframe and sliding window strategies are used to ensure real-time performance. Through real-vehicle testing, the system can perform incremental and real-time state estimation and reconstruct a dense 3D point cloud map, which can effectively solve the problems of positioning drift and mapping failure in the lack of geometric features or challenging construction environments.
Real-Time Information Fusion System Implementation Based on ARM-Based FPGA
Authors: Tsai Yu-Hsiang , Yan Yung-Jhe , Hsiao Meng-Hsin , Yu Tzu-Yi , Ou-Yang Mang
Published: July 2023

In this study, an information fusion system displayed fusion information on a transparent display by considering the relationships among the display, background exhibit, and user’s gaze direction. We used an ARM-based field-programmable gate array (FPGA) to perform virtual–real fusion of this system as well as evaluated the virtual–real fusion execution speed. The ARM-based FPGA used Intel® RealsenseTM D435i depth cameras to capture depth and color images of an observer and exhibit. The image data was received by the ARM side and fed to the FPGA side for real-time object detection. The FPGA accelerated the computation of the convolution neural networks to recognize observers and exhibits. In addition, a module performed by the FPGA was developed for rapid registration between the color and depth images. The module calculated the size and position of the information displayed on a transparent display according to the pixel coordinates and depth values of the human eye and exhibit. A personal computer with GPU RTX2060 performed information fusion in ~47 ms, whereas the ARM-based FPGA accomplished it in 25 ms. Thus, the fusion speed of the ARM-based FPGA was 1.8 times faster than on the computer.
Development of Far-UVC-Based Surface Disinfection Prototype for Public Buses
Authors: Drungilas Darius , Kurmis Mindaugas , Tadzijevas Arturas , Lukosius Zydrunas , Sapalas Deivydas , Jankunas Valdas , Martinkenas Arvydas , Didziokas Rimantas , Gruode Jurate
Published: July 2023

This paper presents a prototype of a disinfection system for public transport specifically aiming to disinfect surfaces contaminated with the SARS-CoV-2 virus on buses using 222 nm wavelength far-ultraviolet light (far-UVC). Our study involved testing the developed technical system installed in a 12 m long M3 category urban bus, an investigation of optimal far-UVC light angles, and the determination of disinfection parameters for bus seat disinfection. The study identified the ideal positioning of a light source for effective disinfection and analyzed three disinfection scenarios, considering zone coverage, disinfection time, and energy demand. A subsystem employing real-time occupancy monitoring enhances the disinfection process in crowded areas of buses. An energy efficiency assessment model is proposed for optimizing energy consumption. Furthermore, the energy consumption analyses in different disinfection scenarios provide valuable insights for optimizing energy usage in public transport disinfection.
Numerical Solutions of the Nonlinear Dispersive Shallow Water Wave Equations Based on the Space–Time Coupled Generalized Finite Difference Scheme
Authors: Li Po-Wei , Hu Shenghan , Zhang Mengyao
Published: July 2023

This study applies the space–time generalized finite difference scheme to solve nonlinear dispersive shallow water waves described by the modified Camassa–Holm equation, the modified Degasperis–Procesi equation, the Fornberg–Whitham equation, and its modified form. The proposed meshless numerical scheme combines the space–time generalized finite difference method, the two-step Newton’s method, and the time-marching method. The space–time approach treats the temporal derivative as a spatial derivative. This enables the discretization of all partial derivatives using a spatial discretization method and efficiently handles mixed derivatives with the proposed mesh-less numerical scheme. The space–time generalized finite difference method is derived from Taylor series expansion and the moving least-squares method. The numerical discretization process only involves functional data and weighting coefficients on the central and neighboring nodes. This results in a sparse matrix system of nonlinear algebraic equations that can be efficiently solved using the two-step Newton’s method. Additionally, the time-marching method is employed to advance the space–time domain along the time axis. Several numerical examples are presented to validate the effectiveness of the proposed space–time generalized finite difference scheme.
Construction of Air Quality Level Prediction Model Based on STEPDISC-PCA-BP
Authors: Liu Min , Hu Hua , Zhang Liqian , Zhang Yongan , Li Jia
Published: July 2023

Air quality level has a complex nonlinear relationship with air pollutant and meteorological conditions, including multiple factors, overlapping information, and difficulty solving equations. In order to identify significant factors, remove correlations, reduce data dimensionality, and simplify the model structure, a BP neural network model for air quality level prediction optimized by stepwise discriminant analysis (STEPDISC) and principal component analysis (PCA) is proposed with 12 factors of historical daily meteorology and air pollutants in Bayannur city as samples. The results showed that, at the significance level of 0.01, the STEPDISC method retained 9 significant impact factors. The PCA method made an orthogonal linear combination of the 9 factors to form the principal components, and the contribution of the top 5 principal components were 37.6%, 19.2%, 15.3%, 8.8%, and 7.7%. At a contribution threshold of 0.85, the top 5 principal component scores were used as input nodes to construct the STEPDISC-PCA-BP model, which had a prediction accuracy of 85.5%.Compared with the PCA-BP and BP model, which had a prediction accuracy of 61.8% and 56.7%, respectively, the STEPDISC-PCA-BP model has a higher prediction accuracy, shorter time, and lower complexity of structure and data dimensionality, and can provide the necessary technical support for the local air quality improvement.
An Improved Multi-Scale Feature Fusion for Skin Lesion Segmentation
Authors: Liu Luzhou , Zhang Xiaoxia , Li Yingwei , Xu Zhinan
Published: July 2023

Accurate segmentation of skin lesions is still a challenging task for automatic diagnostic systems because of the significant shape variations and blurred boundaries of the lesions. This paper proposes a multi-scale convolutional neural network, REDAUNet, based on UNet3+ to enhance network performance for practical applications in skin segmentation. First, the network employs a new encoder module composed of four feature extraction layers through two cross-residual (CR) units. This configuration allows the module to extract deep semantic information while avoiding gradient vanishing problems. Subsequently, a lightweight and efficient channel attention (ECA) module is introduced during the encoder’s feature extraction stage. The attention module assigns suitable weights to channels through attention learning and effectively captures inter-channel interaction information. Finally, the densely connected atrous spatial pyramid pooling module (DenseASPP) module is inserted between the encoder and decoder paths. This module integrates dense connections and ASPP, as well as multi-scale information fusion, to recognize lesions of varying sizes. The experimental studies in this paper were constructed on two public skin lesion datasets, namely, ISIC-2018 and ISIC-2017. The experimental results show that our model is more accurate in segmenting lesions of different shapes and achieves state-of-the-art performance in segmentation. In comparison to UNet3+, the proposed REDAUNet model shows improvements of 2.01%, 4.33%, and 2.68% in Dice, Spec, and mIoU metrics, respectively. These results suggest that REDAUNet is well-suited for skin lesion segmentation and can be effectively employed in computer-aided systems.
A Network Analysis Approach to Detecting Social Issues with Web-Based Data
Authors: Lee Seunghyun , Lee Jiho , Lee Jae-Min , Chun Hong-Woo , Yoon Janghyeok
Published: July 2023

Social issues refer to topics that occur and become increasingly focused in various areas of society. Because of the evolutionary pattern of issues, detecting social issues requires monitoring various stories formed by members of society over time. Various studies related to issue detection have been preceded, but it is necessary to supplement in two aspects: presenting the time when issues occurred and prioritizing issues by urgency. As a remedy, the purpose of this study is to propose a new approach to detecting social issues from web-based data through network analysis. Since stories that form social issues are composed of various keywords and topics, this study detects social issues by monitoring keyword co-occurrence networks constructed with web-based data. Specifically, this approach uses network structure entropy to identify a time period at which social issues occur. Next, a community detection algorithm is used to extract social issue candidates in the identified time period. Finally, social issues are detected by deriving the priority of social issue candidates through the centrality index of keywords constituting the candidates. This study detected South Korean social issue topics that attract people’s attention among the various topics of society. The proposed approach contributes to the existing literature by identifying when social issues occurred quantitatively based on the characteristics of issues. In addition, since the proposed approach detects urgent issues to be dealt with priority, it can support timely responses to social issues.
Wave Diffraction from a Bicone Conjoined with an Open-Ended Conical Cavity
Authors: Kuryliak Dozyslav B. , Sharabura Oleksiy M.
Published: July 2023

The problem of axially symmetric TM-wave diffraction from a bicone conjoined with an open-ended conical cavity is analysed rigorously. The scatterer is formed by the perfectly conducting semi-infinite and truncated semi-infinite conical surfaces; the spherical termination of an internal area of the truncated cone creates the open-ended cavity. In this paper the certain physical aspects of diffraction which are known to cause mathematical difficulties are considered. It includes an accurate analysis of the wave-mode transformation phenomena at the open end of the cavity, as well as a study of wave radiation from the cavity into the biconical waveguide. The primary outcome of this paper is a precise treatment of the wave diffraction problem mentioned above using new techniques and establishing new properties of resonance modes’ penetration into the biconical waveguide region.
A Hybrid Retina Net Classifier for Thermal Imaging
Authors: Teju Ventrapragada , Sowmya Kambhampati Venkata , Kandula Srinivasa Rao , Stan Anca , Stan Ovidiu Petru
Published: July 2023

Thermal imaging is a cutting-edge technology which has the capability to detect objects in any environmental conditions, such as smoke, fog, smog, etc. This technology finds its importance mainly during nighttime since it does not require light to detect the objects. Applications of this technology span into various sectors, most importantly in border security to detect any incoming hazards. Object detection and classification are generally difficult with thermal imaging. In this paper, a one-stage deep convolution network-based object detection and classification called retina net is introduced. Existing surveys are based on object detection using infrared information obtained from the objects. This research is focused on detecting and identifying objects from thermal images and surveillance data.
Constant-Stress Modeling of Log-Normal Data under Progressive Type-I Interval Censoring: Maximum Likelihood and Bayesian Estimation Approaches
Authors: Sief Mohamed , Liu Xinsheng , Hosny Mona , Abd El-Raheem Abd El-Raheem M.
Published: July 2023

This paper discusses inferential approaches for the problem of constant-stress accelerated life testing when the failure data are progressive type-I interval censored. Both frequentist and Bayesian estimations are carried out under the assumption that the log-normal location parameter is nonconstant and follows a log-linear life-stress model. The confidence intervals of unknown parameters are also constructed based on asymptotic theory and Bayesian techniques. An analysis of a real data set is combined with a Monte Carlo simulation to provide a thorough assessment of the proposed methods.
Solving Location Assignment and Order Picker-Routing Problems in Warehouse Management
Authors: Bolaños-Zuñiga Johanna , Salazar-Aguilar M. Angélica , Saucedo-Martínez Jania Astrid
Published: July 2023

One of the critical warehousing processes is the order-picking process. This activity consists of retrieving items from their storage locations to fulfill the demand specified in the pick lists. Therefore, the storage location assignment affects the picking time and, consequently, reduces the operating costs of the warehouse. This work presents two alternative mixed-integer linear models and an adaptive multi-start heuristic (AMH) for solving the integrated storage location and picker-routing problem. The problem considers a warehouse with a general layout and precedence constraints for picking according to the products weight. Experimental work confirms the efficiency of the proposed reformulations since we found out a total of 334 tested instances and optimal solutions for 51 new cases and 62 new feasible solutions. The proposed AMH improved more than 29% of the best-known solutions and required an average execution time of 117 s. Consequently, our proposed algorithm is an attractive decision-making tool to achieve efficiency when solving practical situations in a warehouse.
Artificial Intelligence Opportunities to Diagnose Degradation Modes for Safety Operation in Lithium Batteries
Authors: Jaime-Barquero Edurne , Bekaert Emilie , Olarte Javier , Zulueta Ekaitz , Lopez-Guede Jose Manuel
Published: July 2023

The degradation and safety study of lithium-ion batteries is becoming increasingly important given that these batteries are widely used not only in electronic devices but also in automotive vehicles. Consequently, the detection of degradation modes that could lead to safety alerts is essential. Existing methodologies are diverse, experimental based, model based, and the new trends of artificial intelligence. This review aims to analyze the existing methodologies and compare them, opening the spectrum to those based on artificial intelligence (AI). AI-based studies are increasing in number and have a wide variety of applications, but no classification, in-depth analysis, or comparison with existing methodologies is yet available.
Three-Dimensional Nanoporous CNT@Mn3O4 Hybrid Anode: High Pseudocapacitive Contribution and Superior Lithium Storage
Authors: Zou Wei , Fang Hua , Ma Tengbo , Zhao Yanhui , Wang Lixia , Jia Xiaodong , Zhang Linsen
Published: July 2023

A composite electrode of carbon nanotube CNT@Mn3O4 nanocable was successfully synthesized via direct electrophoretic deposition onto a copper foil, followed by calcination. By uniformly depositing Mn3O4 nanoparticles on CNTs, a nanocable structure of CNT@Mn3O4 can be formed, where the CNT acts as a “highway” for electrons and ions to facilitate fast transportation. Moreover, capacitive energy storage processes play a crucial role in lithium (Li) storage, especially during high scan rates. The significant contribution of capacitance is highly advantageous for the rapid transfer of Li+ ions, which ultimately results in an improved reversible capacity and prolonged cycle stability of the battery. A high specific capacity of 1367 mAh g−1 was maintained over 300 charge–discharge cycles at a current density of 1 A g−1, indicating excellent capacity retention and an extended cycle life. Furthermore, the synthesis process was facile and cost-effective, obviating the need for complex procedures such as mixing and pasting. Additionally, no binder was required, thereby enhancing battery quality efficiency.
Semi-Supervised Medical Image Segmentation with Co-Distribution Alignment
Authors: Wang Tao , Huang Zhongzheng , Wu Jiawei , Cai Yuanzheng , Li Zuoyong
Published: July 2023

Medical image segmentation has made significant progress when a large amount of labeled data are available. However, annotating medical image segmentation datasets is expensive due to the requirement of professional skills. Additionally, classes are often unevenly distributed in medical images, which severely affects the classification performance on minority classes. To address these problems, this paper proposes Co-Distribution Alignment (Co-DA) for semi-supervised medical image segmentation. Specifically, Co-DA aligns marginal predictions on unlabeled data to marginal predictions on labeled data in a class-wise manner with two differently initialized models before using the pseudo-labels generated by one model to supervise the other. Besides, we design an over-expectation cross-entropy loss for filtering the unlabeled pixels to reduce noise in their pseudo-labels. Quantitative and qualitative experiments on three public datasets demonstrate that the proposed approach outperforms existing state-of-the-art semi-supervised medical image segmentation methods on both the 2D CaDIS dataset and the 3D LGE-MRI and ACDC datasets, achieving an mIoU of 0.8515 with only 24% labeled data on CaDIS, and a Dice score of 0.8824 and 0.8773 with only 20% data on LGE-MRI and ACDC, respectively.
Carbon Fiber-Reinforced PolyEtherEtherKetone (CFR-PEEK) Instrumentation in Degenerative Disease of Lumbar Spine: A Pilot Study
Authors: Ghermandi Riccardo , Tosini Giovanni , Lorenzi Alberto , Griffoni Cristiana , La Barbera Luigi , Girolami Marco , Pipola Valerio , Barbanti Brodano Giovanni , Bandiera Stefano , Terzi Silvia , Tedesco Giuseppe , Evangelisti Gisberto , Monetta Annalisa , Noli Luigi Emanuele , Falzetti Luigi , Gasbarrini Alessandro
Published: July 2023

CFR-PEEK is gaining popularity in spinal oncological applications due to its reduction of imaging artifacts and radiation scattering compared with titanium, which allows for better oncological follow-up and efficacy of radiotherapy. We evaluated the use of these materials for the treatment of lumbar degenerative diseases (DDs) and considered the biomechanical potential of the carbon fiber in relation to its modulus of elasticity being similar to that of bone. Twenty-eight patients with DDs were treated using CRF-PEEK instrumentation. The clinical and radiographic outcomes were collected at a 12-month FU. Spinal fusion was evaluated in the CT scans using Brantigan scores, while the clinical outcomes were evaluated using VAS, SF-12, and EQ-5D scores. Out of the patients evaluated at the 12-month FU, 89% showed complete or almost certain fusion (Brantigan score D and E) and presented a significant improvement in all clinical parameters; the patients also presented VAS scores ranging from 6.81 ± 2.01 to 0.85 ± 1.32, EQ-5D scores ranging from 53.4 ± 19.3 to 85.0 ± 13.7, SF-12 physical component scores (PCSs) ranging from 29.35 ± 7.04 to 51.36 ± 9.75, and SF-12 mental component scores (MCSs) ranging from 39.89 ± 11.70 to 53.24 ± 9.24. No mechanical complications related to the implant were detected, and the patients reported a better tolerance of the instrumentation compared with titanium. No other series of patients affected by DD that was stabilized using carbon fiber implants have been reported in the literature. The results of this pilot study indicate the efficacy and safety of these implants and support their use also for spinal degenerative diseases.
Aging in Normotensive and Spontaneously Hypertensive Rats: Focus on Erythrocyte Properties
Authors: Radosinska Jana , Kollarova Marta , Jasenovec Tomas , Radosinska Dominika , Vrbjar Norbert , Balis Peter , Puzserova Angelika
Published: July 2023

Erythrocyte deformability, crucial for oxygen delivery to tissues, plays an important role in the etiology of various diseases. As the factor maintaining the erythrocyte deformability, nitric oxide (NO) has been identified. Reduced NO bioavailability also plays a role in the pathogenesis of hypertension. Our aim was to determine whether aging and hypertension affect erythrocyte deformability and NO production by erythrocytes in experimental animals divided into six groups according to age (7, 20 and 52 weeks), labeled WKY-7, WKY-20 and WKY-52 for normotensive Wistar-Kyoto (WKY) rats, and SHR-7, SHR-20 and SHR-52 for spontaneously hypertensive rats (SHR). The filtration method for the determination of erythrocyte deformability and the fluorescent probe DAF-2 DA for NO production were applied. Deformability and NO production by erythrocytes increased at a younger age, while a decrease in both parameters was observed at an older age. Strain-related differences in deformability were observed at 7 and 52 weeks of age. SHR-7 had reduced deformability and SHR-52 had increased deformability compared with age-matched WKY. Changes in NO production under hypertensive conditions are an unlikely primary factor affecting erythrocyte deformability, whereas age-related changes in deformability are at least partially associated with changes in NO production. However, an interpretation of data obtained in erythrocyte parameters observed in SHRs of human hypertension requires precaution.
Recent Developments in CRISPR/Cas9 Genome-Editing Technology Related to Plant Disease Resistance and Abiotic Stress Tolerance
Authors: Erdoğan İbrahim , Cevher-Keskin Birsen , Bilir Özlem , Hong Yiguo , Tör Mahmut
Published: July 2023

The revolutionary CRISPR/Cas9 genome-editing technology has emerged as a powerful tool for plant improvement, offering unprecedented precision and efficiency in making targeted gene modifications. This powerful and practical approach to genome editing offers tremendous opportunities for crop improvement, surpassing the capabilities of conventional breeding techniques. This article provides an overview of recent advancements and challenges associated with the application of CRISPR/Cas9 in plant improvement. The potential of CRISPR/Cas9 in terms of developing crops with enhanced resistance to biotic and abiotic stresses is highlighted, with examples of genes edited to confer disease resistance, drought tolerance, salt tolerance, and cold tolerance. Here, we also discuss the importance of off-target effects and the efforts made to mitigate them, including the use of shorter single-guide RNAs and dual Cas9 nickases. Furthermore, alternative delivery methods, such as protein- and RNA-based approaches, are explored, and they could potentially avoid the integration of foreign DNA into the plant genome, thus alleviating concerns related to genetically modified organisms (GMOs). We emphasize the significance of CRISPR/Cas9 in accelerating crop breeding processes, reducing editing time and costs, and enabling the introduction of desired traits at the nucleotide level. As the field of genome editing continues to evolve, it is anticipated that CRISPR/Cas9 will remain a prominent tool for crop improvement, disease resistance, and adaptation to challenging environmental conditions.
Targeted Glutamate Supply Boosts Insulin Concentrations, Ovarian Activity, and Ovulation Rate in Yearling Goats during the Anestrous Season
Authors: Luna-Garcia Luis A. , Meza-Herrera Cesar A. , Perez-Marin Carlos C. , De Santiago-Miramontes Angeles , Flores-Salas Jessica M. , Corona Rebeca , Calderon-Leyva Guadalupe , Veliz-Deras Francisco G. , Navarrete-Molina Cayetano , Marin-Tinoco Ruben I.
Published: July 2023

The neuroendocrine regulation of the seasonal reproductive axis requires the integration of internal and external signals to ensure synchronized physiological and behavioral responses. Seasonal reproductive changes contribute to intermittent production, which poses challenges for optimizing goat product yields. Consequently, a significant objective in seasonal reproduction research is to attain continuous reproduction and enhance profitability in goat farming. Glutamate plays a crucial role as a modulator in several reproductive and metabolic processes. Hence, the aim of this study was to evaluate the potential impact of exogenous glutamate administration on serum insulin concentration and ovarian function during the out-of-season period in yearling goats. During the anestrous season, animals were randomly located in individual pens to form two experimental groups: (1) glutamate (n = 10, live weight (LW) = 29.1 ± 1.02 kg, body condition score (BCS) = 3.4 ± 0.2 units) and (2) control (n = 10; LW = 29.2 ± 1.07 kg, BCS = 3.5 ± 0.2), with no differences (p < 0.05) regarding LW and BCS. Then, goats were estrus-synchronized, and blood sampling was carried out for insulin quantification. Ovaries were ultrasonographically scanned to assess ovulation rate (OR), number of antral follicles (AFs), and total ovarian activity (TOA = OR + AF). The research outcomes support our working hypothesis. Certainly, our study confirms that those yearling goats treated with exogenous glutamate displayed the largest (p < 0.05) insulin concentrations across time as well as an augmented (p < 0.05) out-of-season ovarian activity.
Integrative CRISPR Activation and Small Molecule Inhibitor Screening for lncRNA Mediating BRAF Inhibitor Resistance in Melanoma
Authors: Shamloo Sama , Kloetgen Andreas , Petroulia Stavroula , Hockemeyer Kathryn , Sievers Sonja , Tsirigos Aristotelis , Aifantis Ioannis , Imig Jochen
Published: July 2023

The incidence of melanoma, being one of the most commonly occurring cancers, has been rising since the past decade. Patients at advanced stages of the disease have very poor prognoses, as opposed to at the earlier stages. The conventional targeted therapy is well defined and effective for advanced-stage melanomas for patients not responding to the standard-of-care immunotherapy. However, targeted therapies do not prove to be as effective as patients inevitably develop V-Raf Murine Sarcoma Viral Oncogene Homolog B (BRAF)-inhibitor resistance to the respective drugs. Factors which are driving melanoma drug resistance mainly involve mutations in the mitogen-activated protein kinase (MAPK) pathway, e.g., BRAF splice variants, neuroblastoma RAS viral oncogene homolog (NRAS) amplification or parallel survival pathways. However, those mechanisms do not explain all cases of occurring resistances. Therefore, other factors accounting for BRAFi resistance must be better understood. Among them there are long non-coding RNAs (lncRNAs), but these remain functionally poorly understood. Here, we conduct a comprehensive, unbiased, and integrative study of lncRNA expression, coupled with a Clustered Regularly Interspaced Short Palindromic Repeats/Cas9-mediated activation (CRISPRa) and small molecule inhibitor screening for BRAF inhibitor resistance to expand the knowledge of potentially druggable lncRNAs, their function, and pave the way for eventual combinatorial treatment approaches targeting diverse pathways in melanoma.
Allergic Diseases and Childhood Obesity: A Detrimental Link?
Authors: Stefani Camilla , Pecoraro Luca , Flodmark Carl-Erik , Zaffanello Marco , Piacentini Giorgio , Pietrobelli Angelo
Published: July 2023

Several epidemiological studies have described childhood obesity as a risk factor for atopic disease, particularly asthma. At the same time, this association seems to be more conflicting for allergic rhinitis, atopic dermatitis, and chronic urticaria. This article aims to deepen the possibility of a relationship between childhood obesity and allergic diseases. As regards asthma, the mechanical and inflammatory effects of obesity can lead to its development. In addition, excess adiposity is associated with increased production of inflammatory cytokines and adipokines, leading to low-grade systemic inflammation and an increased risk of asthma exacerbations. Allergic rhinitis, atopic dermatitis, food allergies, and chronic urticaria also seem to be related to this state of chronic low-grade systemic inflammation typical of obese children. Vitamin D deficiency appears to play a role in allergic rhinitis, while dyslipidemia and skin barrier defects could explain the link between obesity and atopic dermatitis. Starting from this evidence, it becomes of fundamental importance to act on body weight control to achieve general and allergic health, disentangling the detrimental link between obesity allergic diseases and childhood obesity. Further studies on the association between adiposity and atopy are needed, confirming the biologically active role of fat tissue in the development of allergic diseases and exploring the possibility of new therapeutic strategies.
Stereotactic Radiotherapy in Combination with Immunotherapy in Treatment of Advanced Recurrent Squamous Cell Carcinoma of the Larynx
Authors: Polanowski Paweł , Nasiek Aleksandra , Grządziel Aleksandra , Pietruszka Agnieszka , Składowski Krzysztof , Polanowska Katarzyna
Published: July 2023

Squamous cell carcinoma (SCC) of the larynx in advanced stages is a challenging malignancy to treat with a high recurrence and death rate. An individualized approach to treatment is crucial in such patients. We present a 58-year-old male patient with SCC of the larynx in the T3N0M0 stage who was treated with concurrent radiochemotherapy. A total of 17 months after the radical treatment, the patient underwent a laryngectomy due to recurrence. A total of 11 months after the operation, local failure was diagnosed. In the next order, the patient received six cycles of palliative chemotherapy according to cisplatin 100 mg/m2 and 5-fluorouracil 1000 mg/m2. After three months, due to progression, Nivolumab-based immunotherapy was administered, ensuring disease stabilization. After the 56th cycle of Nivolumab, another progression was documented. The addition of stereotactic radiotherapy (18 Gy in three fractions) to immunotherapy led to significant regression of the disease and enabled the continuation of Nivolumab to the 70th cycle. The presented case demonstrates the usefulness of the combination of stereotactic radiotherapy with immunotherapy in prolonging the local control.
Dietary Supplementation with 20-Hydroxyecdysone Ameliorates Hepatic Steatosis and Reduces White Adipose Tissue Mass in Ovariectomized Rats Fed a High-Fat, High-Fructose Diet
Authors: Buniam Jariya , Chansela Piyachat , Weerachayaphorn Jittima , Saengsirisuwan Vitoon
Published: July 2023

Metabolic dysfunction-associated fatty liver disease (MAFLD) is defined as hepatic steatosis in combination with overweight, diabetes, or other metabolic risk factors. MAFLD affects a significant number of the global population and imposes substantial clinical and economic burdens. With no approved pharmacotherapy, current treatment options are limited to diet and exercise. Therefore, the development of medicines for MAFLD treatment or prevention is necessary. 20-Hydroxyecdysone (20E) is a natural steroid found in edible plants and has been shown to improve metabolism and dyslipidemia. Therefore, it may be useful for MAFLD treatment. Here, we aimed to determine how dietary supplementation with 20E affects fat accumulation and lipogenesis in the liver and adipose tissue of ovariectomized rats fed a high-fat, high-fructose diet (OHFFD). We found that 20E reduced hepatic triglyceride content and visceral fat deposition. 20E increased the phosphorylation of AMP-activated protein kinase and acetyl CoA carboxylase while reducing the expression of fatty acid synthase in the liver and adipose tissue. Additionally, 20E increased hepatic expression of carnitine palmitoyltransferase-1 and reduced adipose expression of sterol regulatory element-binding protein-1. In conclusion, 20E demonstrated beneficial effects in rats with OHFFD-induced MAFLD. These findings suggest that 20E may represent a promising option for MAFLD prevention or treatment.