bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Al Addition on the Microstructure and Wear Behavior of Laser Cladding FeCoCrNiAlx High-Entropy Alloy Coatings
Authors: Liu Yang , Xu Zhixiang , Xu Gaojie , Chen Hongyong
Published: February 2023

In order to improve the wear properties of FeCoCrNi high entropy alloy (HEA), laser cladding was applied to fabricate FeCoCrNiAlx HEA coatings with different Al additions. The Al-modified coatings exhibited excellent metallurgical bonding interfaces with the substrates. The microstructure of FeCoCrNiAl0.5 coating was the same as of the FeCoCrNi coating: face-centered cubic (FCC). However, the microstructure of FeCoCrNiAl was different: body-centered cubic (BCC) with more Al atoms distributed inside the grains. As the Al content in the coating was increased, the hardness increased as well from 202 to 546 HV0.2, while CoF and wear rate decreased from 0.62 to 0.1 and from 8.55 × 10−7 to 8.24 × 10−9 mm3/(Nm), respectively. The wear mechanisms changed from the mixture of abrasive, adhesive, and oxidative wear patterns to the mixture of abrasive and oxidative patterns. Such a change indicates that the Al addition indeed improved the wear resistance of FeCoCrNiAlx HEA coatings. Our results expand knowledge on HEA coating applications as wear-resistant materials in various applied industrial fields.
‘Beyond Cancer’ Rehabilitation Program to Support Breast Cancer Survivors to Return to Health, Wellness and Work: Feasibility Study Outcomes
Authors: Sheppard Dianne M. , O’Connor Moira , Jefford Michael , Lamb Georgina , Frost Dorothy , Ellis Niki , Halkett Georgia K. B.
Published: February 2023

More women are returning to work following breast cancer treatment. Our team designed ‘Beyond Cancer’, a multimodal rehabilitation program to support breast cancer survivors to return to work. This study aimed to determine the feasibility of the intervention from the breast cancer survivor, employer and occupational rehabilitation provider perspectives. The feasibility design focused on implementation, acceptability and preliminary indications of efficacy. Primary outcome measures included work status, work capacity and perceived support at work. Responses were compared with an historical usual care group of mixed cancer survivors. The tailored intervention was delivered over 33 weeks (on average) by trained occupational rehabilitation consultants. Eighty-four women with breast cancer (mean age = 50.8 years, SD = 8.24) who were unable to work in their pre-diagnosis capacity for >3 months participated. Results provided preliminary indications of efficacy for primary work outcomes, including work capacity relative to the historical usual care group, and some secondary biopsychosocial variables (physical fatigue, return to work expectations). The intervention was acceptable, demonstrated strong participant engagement and high satisfaction. Feasibility has been demonstrated for this multimodal intervention focused on returning to sustainable work for women with breast cancer. Future research is required with people diagnosed with other cancer types to demonstrate broader implementation.
Fault Diagnosis Techniques for Nuclear Power Plants: A Review from the Artificial Intelligence Perspective
Authors: Qi Ben , Liang Jingang , Tong Jiejuan
Published: February 2023

Fault diagnosis plays an important role in complex and safety-critical systems such as nuclear power plants (NPPs). With the development of artificial intelligence (AI), extensive research has been carried out for fast and efficient fault diagnosis based on intelligent methods. This paper presents a review of various AI-based system-level fault diagnosis methods for NPPs. We first discuss the development history of AI. Based on this exposition, AI-based fault diagnosis techniques are classified into knowledge-driven and data-driven approaches. For knowledge-driven methods, we discuss both the early if–then-based fault diagnosis techniques and the current new theory-based ones. The principles, application, and comparative analysis of the representative methods are systematically described. For data-driven strategies, we discuss single-algorithm-based techniques such as ANN, SVM, PCA, DT, and clustering, as well as hybrid techniques that combine algorithms together. The advantages and disadvantages of both knowledge-driven and data-driven methods are compared, illustrating the tendency to combine the two approaches. Finally, we provide some possible future research directions and suggestions.
Adaptive Double Kalman Filter Method for Smoothing Wind Power in Multi-Type Energy Storage System
Authors: Qin Lei , Sun Na , Dong Haiying
Published: February 2023

At present, in the situation that wind power penetration is increasing year by year, the use of a hybrid energy storage system (HESS) to smooth out wind power fluctuations becomes an effective method. However, the existing control strategy has the problem of inadequate utilization of fluctuating power. In this paper, we propose a control strategy for smoothing wind power fluctuations based on double Kalman filters with adaptive adjustment of the state of charge (SOC). Firstly, considering the wind power’s active power grid constraint, the parameters of the dual Kalman filter are adaptively adjusted according to the original output power to obtain the target grid power synchronously, and the total smoothing command of the energy storage system is determined with the goal of improving the SOC of the lithium battery. On this basis, the SOC of the supercapacitor is considered to be improved, and the adaptive low-pass filter is used for the secondary distribution of the energy storage power command to achieve fine-grained management of the output power of HESS. The final simulation results show that the obtained smoothed wind power satisfies the 1 min and 10 min fluctuation criteria, and the minimum capacity required for lithium batteries is reduced by 0.07 MW·h under the same initial conditions as in the proposed method in this paper; it can use the fluctuating power when the SOC crosses the limit, and has a regulating effect on the SOC of HESS to improve the wind power smoothing ability and realize the stable grid-connection requirement of wind power.
Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review
Authors: Islam Md Tariqul , Hossain M. J.
Published: February 2023

Distribution network operators face technical and operational challenges in integrating the increasing number of distributed energy resources (DER) with the distribution network. The hosting capacity analysis quantifies the level of power quality violation on the network due to the high penetration of the DER, such as over voltage, under voltage, transformer and feeder overloading, and protection failures. Real-time monitoring of the power quality factors such as the voltage, current, angle, frequency, harmonics and overloading that would help the distribution network operators overcome the challenges created by the high penetration of the DER. In this paper, different conventional hosting capacity analysis methods have been discussed. These methods have been compared based on the network constraints, impact factors, required input data, computational efficiency, and output accuracy. The artificial intelligence approaches of the hosting capacity analysis for the real-time monitoring of distribution network parameters have also been covered in this paper. Different artificial intelligence techniques have been analysed for sustainable integration, power system optimisation, and overcoming real-time monitoring challenges of conventional hosting capacity analysis methods. An overview of the conventional hosting capacity analysis methods, artificial intelligence techniques for overcoming the challenges of distributed energy resources integration, and different impact factors affecting the real-time hosting capacity analysis has been summarised. The distribution system operators and researchers will find the review paper as an easy reference for planning and further research. Finally, it is evident that artificial intelligence techniques could be a better alternative solution for real-time estimation and forecasting of the distribution network hosting capacity considering the intermittent nature of the DER, consumer loads, and network constraints.
Energy Transition Scenarios for Energy Poverty Alleviation: Analysis of the Delphi Study
Authors: Tundys Blanka , Bretyn Agnieszka
Published: February 2023

Energy poverty is a phenomenon that is affecting an increasing number of EU citizens. It occurs when people are unable to buy enough energy to meet their needs at a socially acceptable level. Despite the many efforts and measures taken to prevent this negative phenomenon, the looming energy crisis could exacerbate it. On the one hand, efforts towards energy transition are intended to prevent this phenomenon, but on the other hand, inadequate restraint on the energy market may lead to its escalation. Various scenarios need to be analysed to ensure that the risks associated with energy shortages do not lead to even greater levels of energy poverty, with negative consequences for societies, economies, and the environment. Using a scenario approach and expert research, as well as mathematical–statistical tools, the article presents possible scenarios related to the implementation of measures affecting energy transformation and the transition to renewable energy sources in economies. These measures can change the phenomenon of energy poverty. The results of the analysis conducted in the article showed that there is a relationship between the increase in GDP per capita and the degree of energy consumption from renewable sources. In addition, there is a negative correlation between the degree of use of energy from renewable sources and the problem of energy poverty, especially in countries with a relatively lower level of GDP per capita. The current economic and political situation requires research in this area and the identification of possible solutions, as energy poverty is becoming a major social problem. The measures taken to promote sustainable development in an energy crisis situation might not be able to be implemented in a highly satisfactory manner.
Control and Implementation of an Energy Management Strategy for a PV–Wind–Battery Microgrid Based on an Intelligent Prediction Algorithm of Energy Production
Authors: Mahjoub Sameh , Chrifi-Alaoui Larbi , Drid Saïd , Derbel Nabil
Published: February 2023

This paper describes an energy management strategy for a DC microgrid that utilizes a hybrid renewable energy system (HRES) composed of a photovoltaic (PV) module, a wind turbine based on a permanent magnetic synchronous generator (PMSG), and a battery energy storage system (BESS). The strategy is designed to provide a flexible and reliable system architecture that ensures continuous power supply to loads under all conditions. The control scheme is based on the generation of reference source currents and the management of power flux. To optimize the supply–demand balance and ensure optimal power sharing, the strategy employs artificial intelligence algorithms that use previous data, constantly updated forecasts (such as weather forecasts and local production data), and other factors to control all system components in an optimal manner. A double-input single-output DC–DC converter is used to extract the maximum power point tracking (MPPT) from each source. This allows the converter to still transfer power from one source to another even if one of the sources is unable to generate power. In this HRES configuration, all the sources are connected in parallel through the common DC–DC converter. The strategy also includes a long short-term memory (LSTM) network-based forecasting approach to predict the available energy production and the battery state of charge (SOC). The system is tested using Matlab/Simulink and validated experimentally in a laboratory setting.
Risk-Based Assessment of the Reliability Level for Extreme Limit States in IEC 61400-1
Authors: Nielsen Jannie Sønderkær , Toft Henrik Stensgaard , Violato Gustavo Oliveira
Published: February 2023

The annual target reliability level for structural components is given as β = 3.3 in the main design standard for wind turbines IEC 61400-1 ed. 4. However, since the same safety factors are used for a range of load cases and limit states, deviations in the obtained reliability level can be expected, and it should be considered how to handle this in relation to the development of the IEC TS 61400-9 on probabilistic design measures. In this paper, structural reliability analyses were performed for components designed using safety factors for a range of extreme load cases, and by using the correlation between limit states for different years, the development of the reliability level over time was calculated. A relative risk-based assessment was applied to assess the optimal target reliability level and safety factors. The risk-based assessment explicitly includes the uncertainties, benefits, and costs and can motivate differentiation of the annual reliability level between load cases. Annual reliability indices were found to be in the range of 2.9–3.4, and although this includes values below the target of 3.3, it was also found that the optimal reliability indices were in the same range. The variation in reliability level can be motivated since the optimal target reliability is found to be lower than the current target for load cases with high correlation, as this causes the lifetime reliability level to be comparable to that of other extreme load cases with less correlation.
Possible Mechanisms of Oxidative Stress-Induced Skin Cellular Senescence, Inflammation, and Cancer and the Therapeutic Potential of Plant Polyphenols
Authors: Liu Hui-Min , Cheng Ming-Yan , Xun Meng-Han , Zhao Zhi-Wei , Zhang Yun , Tang Wei , Cheng Jun , Ni Jia , Wang Wei
Published: February 2023

As the greatest defense organ of the body, the skin is exposed to endogenous and external stressors that produce reactive oxygen species (ROS). When the antioxidant system of the body fails to eliminate ROS, oxidative stress is initiated, which results in skin cellular senescence, inflammation, and cancer. Two main possible mechanisms underlie oxidative stress-induced skin cellular senescence, inflammation, and cancer. One mechanism is that ROS directly degrade biological macromolecules, including proteins, DNA, and lipids, that are essential for cell metabolism, survival, and genetics. Another one is that ROS mediate signaling pathways, such as MAPK, JAK/STAT, PI3K/AKT/mTOR, NF-κB, Nrf2, and SIRT1/FOXO, affecting cytokine release and enzyme expression. As natural antioxidants, plant polyphenols are safe and exhibit a therapeutic potential. We here discuss in detail the therapeutic potential of selected polyphenolic compounds and outline relevant molecular targets. Polyphenols selected here for study according to their structural classification include curcumin, catechins, resveratrol, quercetin, ellagic acid, and procyanidins. Finally, the latest delivery of plant polyphenols to the skin (taking curcumin as an example) and the current status of clinical research are summarized, providing a theoretical foundation for future clinical research and the generation of new pharmaceuticals and cosmetics.
The Titrated Mannitol Improved Central [99mTc] Tc TRODAT-1 Uptake in an Animal Model—A Clinically Feasible Application
Authors: Chang Kang-Wei , Chang Po-Ling , Tsai Chi-Jung , Tsai Ya-Ju , Wu Ping-Hsiu , Lee Hsin-Lun , Lai Yu-Hua , Wong Ching-Yee Oliver , Huang Wen-Sheng
Published: February 2023

[99mTc]Tc TRODAT-1 is a widely used single photon emission tomography (SPECT) radiopharmaceutical in Asian practice for early detection of central dopaminergic disorders. However, its imaging quality remains sub-optimal. To overcome this problem, mannitol, an osmotic agent was used to observe its effect on improving striatal [99mTc]Tc TRODAT-1 uptake in rat brain by titrated human dosages to investigate a clinically feasible way to improve human imaging quality. [99mTc]Tc TRODAT-1 synthesis and quality control were performed as described. Sprague–Dawley rats were used for this study. The animal in vivo nanoSPECT/CT and ex vivo autoradiography were employed to observe and verify the striatal [99mTc]Tc TRODAT-1 uptake in rat brains using clinically equivalent doses (i.e., 0, 1 and 2 mL groups, each n = 5) of mannitol (20% w/v, equivalent to 200 mg/mL) by an intravenous administration. Specific binding ratios (SBRs) were calculated to express the central striatal uptake in different experimental groups. In the NanoSPECT/CT imaging, the highest SBRs of striatal [99mTc]Tc TRODAT-1 were reached at 75–90 min post-injection. The averaged striatal SBRs were 0.85 ± 0.13 (2 mL normal saline, the control group), 0.94 ± 0.26 (1 mL mannitol group) and 1.36 ± 0.12 (2 mL mannitol group, p < 0.01 which were significantly different than the control as well as 1 mL mannitol groups (p < 0.05). The SBRs from ex vivo autoradiography also showed a comparable trend of the striatal [99mTc]Tc TRODAT-1 uptake in the 2 mL, 1 mL mannitol and the control groups (1.76 ± 0.52, 0.91 ± 0.29, and 0.21 ± 0.03, respectively, p < 0.05). No remarkable changes of vital signs were found in the mannitol groups and the controls. Pre-treated mannitol revealed a significant increase of the central striatal [99mTc]Tc TRODAT-1 uptake in a rat model which not only enabled us to perform pre-clinical studies of dopaminergic related disorders but also provided a potential way to further optimize image quality in clinical practice.
The Role of Cytoskeleton Protein 4.1 in Immunotherapy
Authors: Si Chaohua , Yuan Lihua , Chen Chen , Wang Ting , Kang Qiaozhen
Published: February 2023

Cytoskeleton protein 4.1 is an essential class of skeletal membrane protein, initially found in red blood cells, and can be classified into four types: 4.1R (red blood cell type), 4.1N (neuronal type), 4.1G (general type), and 4.1B (brain type). As research progressed, it was discovered that cytoskeleton protein 4.1 plays a vital role in cancer as a tumor suppressor. Many studies have also demonstrated that cytoskeleton protein 4.1 acts as a diagnostic and prognostic biomarker for tumors. Moreover, with the rise of immunotherapy, the tumor microenvironment as a treatment target in cancer has attracted great interest. Increasing evidence has shown the immunoregulatory potential of cytoskeleton protein 4.1 in the tumor microenvironment and treatment. In this review, we discuss the role of cytoskeleton protein 4.1 within the tumor microenvironment in immunoregulation and cancer development, with the intention of providing a new approach and new ideas for future cancer diagnosis and treatment.
Comparative Study of the Effect of Doping ZnTiO3 with Rare Earths (La and Ce) on the Adsorption and Photodegradation of Cyanide in Aqueous Systems
Authors: Jaramillo-Fierro Ximena , Cuenca Guisella , Ramón John
Published: February 2023

Cyanide is a highly toxic compound that can pose serious health problems to both humans and aquatic organisms. Therefore, the present comparative study focuses on the removal of total cyanide from aqueous solutions by photocatalytic adsorption and degradation methods using ZnTiO3 (ZTO), La/ZnTiO3 (La/ZTO), and Ce/ZnTiO3 (Ce/ZTO). The nanoparticles were synthesized by the sol-gel method and characterized by X-ray powder diffractometry (XRD), Scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS), Diffuse reflectance spectroscopy (DRS), and Specific surface area (SSA). The adsorption equilibrium data were fitted to the Langmuir and Freundlich isotherm models. Adsorption kinetics were also evaluated using the pseudo-first-order and pseudo-second-order models and the intraparticle diffusion model. Likewise, the photodegradation of cyanide under simulated sunlight was investigated and the reusability of the synthesized nanoparticles for cyanide removal in aqueous systems was determined. The results demonstrated the effectiveness of doping with lanthanum (La) and cerium (Ce) to improve the adsorbent and photocatalytic properties of ZTO. In general, La/ZTO showed the maximum percentage of total cyanide removal (99.0%) followed by Ce/ZTO (97.0%) and ZTO (93.6%). Finally, based on the evidence of this study, a mechanism for the removal of total cyanide from aqueous solutions using the synthesized nanoparticles was proposed.
The Strategies of Development of New Non-Toxic Inhibitors of Amyloid Formation
Authors: Galzitskaya Oxana V. , Grishin Sergei Y. , Glyakina Anna V. , Dovidchenko Nikita V. , Konstantinova Anastasiia V. , Kravchenko Sergey V. , Surin Alexey K.
Published: February 2023

In recent years, due to the aging of the population and the development of diagnostic medicine, the number of identified diseases associated with the accumulation of amyloid proteins has increased. Some of these proteins are known to cause a number of degenerative diseases in humans, such as amyloid-beta (Aβ) in Alzheimer’s disease (AD), α-synuclein in Parkinson’s disease (PD), and insulin and its analogues in insulin-derived amyloidosis. In this regard, it is important to develop strategies for the search and development of effective inhibitors of amyloid formation. Many studies have been carried out aimed at elucidating the mechanisms of amyloid aggregation of proteins and peptides. This review focuses on three amyloidogenic peptides and proteins—Aβ, α-synuclein, and insulin—for which we will consider amyloid fibril formation mechanisms and analyze existing and prospective strategies for the development of effective and non-toxic inhibitors of amyloid formation. The development of non-toxic inhibitors of amyloid will allow them to be used more effectively for the treatment of diseases associated with amyloid.
Voghera Sweet Pepper: A Potential Ally against Oxidative Stress and Aging
Authors: Gola Federica , Gaiaschi Ludovica , Roda Elisa , De Luca Fabrizio , Ferulli Federica , Vicini Riccardo , Rossi Paola , Bottone Maria Grazia
Published: February 2023

In the present study, the potential functional properties of the extracts from the edible part of Capsicum annuum L. var. Peperone di Voghera (VP) were studied. The phytochemical analysis revealed a high amount of ascorbic acid, paralleled by a low carotenoid content. Normal human diploid fibroblasts (NHDF) were chosen as the in vitro model models to investigate the effects of the VP extract on oxidative stress and aging pathways. The extract of Carmagnola pepper (CP), another important Italian variety, was used as the reference vegetable. The cytotoxicity evaluation was performed firstly, using a 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) assay, while the VP potential antioxidant and antiaging activity was investigated by immunofluorescence staining focusing on specifically selected proteins. The MTT data revealed the highest cell viability at a concentration of up to 1 mg/mL. The immunocytochemical analyses highlighted an increased expression of transcription factors and enzymes involved in redox homeostasis (Nrf2, SOD2, catalase), improved mitochondrial functionality, and the up-regulation of the longevity gene SIRT1. The present results supported the functional role of the VP pepper ecotype, suggesting a feasible use of its derived products as valuable food supplements.
The Role of Cytokines in the Metastasis of Solid Tumors to the Spine: Systematic Review
Authors: Łabędź Wojciech , Przybyla Anna , Zimna Agnieszka , Dąbrowski Mikołaj , Kubaszewski Łukasz
Published: February 2023

Although many studies have investigated the role of cytokines in bone metastases, our knowledge of their function in spine metastasis is limited. Therefore, we performed a systematic review to map the available evidence on the involvement of cytokines in spine metastasis in solid tumors. A PubMed search identified 211 articles demonstrating a functional link between cytokines/cytokine receptors and bone metastases, including six articles confirming the role of cytokines/cytokine receptors in spine metastases. A total of 68 cytokines/cytokine receptors were identified to mediate bone metastases; 9 (mostly chemokines) played a role in spine metastases: CXC motif chemokine ligand (CXCL) 5, CXCL12, CXC motif chemokine receptor (CXCR) 4, CXCR6, interleukin (IL) 10 in prostate cancer, CX3C motif chemokine ligand (CX3CL) 1 and CX3C motif chemokine receptor (CX3CR) 1 in liver cancer, CC motif chemokine ligand (CCL) 2 in breast cancer, and transforming growth factor (TGF) β in skin cancer. Except for CXCR6, all cytokines/cytokine receptors were shown to operate in the spine, with CX3CL1, CX3CR1, IL10, CCL2, CXCL12, and CXCR4 mediating bone marrow colonization, CXCL5 and TGFβ promoting tumor cell proliferation, and TGFβ additionally driving bone remodeling. The number of cytokines/cytokine receptors confirmed to mediate spinal metastasis is low compared with the vast spectrum of cytokines/cytokine receptors participating in other parts of the skeleton. Therefore, further research is needed, including validation of the role of cytokines mediating metastases to other bones, to precisely address the unmet clinical need associated with spine metastases.
Co-Expression Analysis of Airway Epithelial Transcriptome in Asthma Patients with Eosinophilic vs. Non-Eosinophilic Airway Infiltration
Authors: Kozlik-Siwiec Pawel , Buregwa-Czuma Sylwia , Zawlik Izabela , Dziedzina Sylwia , Myszka Aleksander , Zuk-Kuwik Joanna , Siwiec-Kozlik Andzelika , Zarychta Jacek , Okon Krzysztof , Zareba Lech , Soja Jerzy , Jakiela Bogdan , Kepski Michał , Bazan Jan G. , Bazan-Socha Stanislawa
Published: February 2023

Asthma heterogeneity complicates the search for targeted treatment against airway inflammation and remodeling. We sought to investigate relations between eosinophilic inflammation, a phenotypic feature frequent in severe asthma, bronchial epithelial transcriptome, and functional and structural measures of airway remodeling. We compared epithelial gene expression, spirometry, airway cross-sectional geometry (computed tomography), reticular basement membrane thickness (histology), and blood and bronchoalveolar lavage (BAL) cytokines of n = 40 moderate to severe eosinophilic (EA) and non-eosinophilic asthma (NEA) patients distinguished by BAL eosinophilia. EA patients showed a similar extent of airway remodeling as NEA but had an increased expression of genes involved in the immune response and inflammation (e.g., KIR3DS1), reactive oxygen species generation (GYS2, ATPIF1), cell activation and proliferation (ANK3), cargo transporting (RAB4B, CPLX2), and tissue remodeling (FBLN1, SOX14, GSN), and a lower expression of genes involved in epithelial integrity (e.g., GJB1) and histone acetylation (SIN3A). Genes co-expressed in EA were involved in antiviral responses (e.g., ATP1B1), cell migration (EPS8L1, STOML3), cell adhesion (RAPH1), epithelial–mesenchymal transition (ASB3), and airway hyperreactivity and remodeling (FBN3, RECK), and several were linked to asthma in genome- (e.g., MRPL14, ASB3) or epigenome-wide association studies (CLC, GPI, SSCRB4, STRN4). Signaling pathways inferred from the co-expression pattern were associated with airway remodeling (e.g., TGF-β/Smad2/3, E2F/Rb, and Wnt/β-catenin).
A Multi-Stage Deep-Learning-Based Vehicle and License Plate Recognition System with Real-Time Edge Inference
Authors: Ammar Adel , Koubaa Anis , Boulila Wadii , Benjdira Bilel , Alhabashi Yasser
Published: February 2023

Video streaming-based real-time vehicle identification and license plate recognition systems are challenging to design and deploy in terms of real-time processing on edge, dealing with low image resolution, high noise, and identification. This paper addresses these issues by introducing a novel multi-stage, real-time, deep learning-based vehicle identification and license plate recognition system. The system is based on a set of algorithms that efficiently integrate two object detectors, an image classifier, and a multi-object tracker to recognize car models and license plates. The information redundancy of Saudi license plates’ Arabic and English characters is leveraged to boost the license plate recognition accuracy while satisfying real-time inference performance. The system optimally achieves real-time performance on edge GPU devices and maximizes models’ accuracy by taking advantage of the temporally redundant information of the video stream’s frames. The edge device sends a notification of the detected vehicle and its license plate only once to the cloud after completing the processing. The system was experimentally evaluated on vehicles and license plates in real-world unconstrained environments at several parking entrance gates. It achieves 17.1 FPS on a Jetson Xavier AGX edge device with no delay. The comparison between the accuracy on the videos and on static images extracted from them shows that the processing of video streams using this proposed system enhances the relative accuracy of the car model and license plate recognition by 13% and 40%, respectively. This research work has won two awards in 2021 and 2022.
Recent Development of Air Gauging in Industry 4.0 Context
Authors: Rucki Miroslaw
Published: February 2023

The paper presents a review of the research reports published in 2012–2022, dedicated to air gauging. Since most of the results are somehow related to Industry 4.0 concept, the review put the air gauging to the context of fourth industrial revolution. It was found that despite substantial decrease of the number of published papers in recent years, the investigations are still performed to improve air gauges, both in static and in non-steady states. Researchers paid attention to the digitization of the results, models and simulations, uncertainty estimation, calibration, and linearization. Specific applications covered real-time monitoring and in-process control, as well as form and surface topography measurements. Proposed solutions for integration with computer systems seem suitable for the air gauges be included to the sensor networks built according to the Industry 4.0 concept.
Occupancy-Based Energy Consumption Estimation Improvement through Deep Learning
Authors: Kim Mi-Lim , Park Keon-Jun , Son Sung-Yong
Published: February 2023

The energy consumed in buildings constitutes more than half of the total electricity consumption and is highly correlated with the number of occupants; therefore, it is necessary to use occupancy information in energy consumption analysis. However, the number of occupants may not be accurate owing to measurement errors caused by various factors, such as the locations of sensors or cameras and the communication environment. In this study, occupancy was measured using an object recognition camera, the number of people was additionally collected by manual aggregation, measurement error in occupancy count was analyzed, and the true count was estimated using a deep learning model. The energy consumption based on occupancy was predicted using the measured and estimated values. To this end, deep learning was used to predict energy consumption after analyzing the correlation between occupancy and energy consumption. Results showed that the performance of occupancy estimation was 1.9 based on RMSE, which is a 71.1% improvement compared to the original occupancy sensing. The RMSE of predicted energy consumption based on the estimated occupancy was 56.0, which is a 5.2% improvement compared to the original energy estimation.
A Review of Embedded Machine Learning Based on Hardware, Application, and Sensing Scheme
Authors: Biglari Amin , Tang Wei
Published: February 2023

Machine learning is an expanding field with an ever-increasing role in everyday life, with its utility in the industrial, agricultural, and medical sectors being undeniable. Recently, this utility has come in the form of machine learning implementation on embedded system devices. While there have been steady advances in the performance, memory, and power consumption of embedded devices, most machine learning algorithms still have a very high power consumption and computational demand, making the implementation of embedded machine learning somewhat difficult. However, different devices can be implemented for different applications based on their overall processing power and performance. This paper presents an overview of several different implementations of machine learning on embedded systems divided by their specific device, application, specific machine learning algorithm, and sensors. We will mainly focus on NVIDIA Jetson and Raspberry Pi devices with a few different less utilized embedded computers, as well as which of these devices were more commonly used for specific applications in different fields. We will also briefly analyze the specific ML models most commonly implemented on the devices and the specific sensors that were used to gather input from the field. All of the papers included in this review were selected using Google Scholar and published papers in the IEEExplore database. The selection criterion for these papers was the usage of embedded computing systems in either a theoretical study or practical implementation of machine learning models. The papers needed to have provided either one or, preferably, all of the following results in their studies—the overall accuracy of the models on the system, the overall power consumption of the embedded machine learning system, and the inference time of their models on the embedded system. Embedded machine learning is experiencing an explosion in both scale and scope, both due to advances in system performance and machine learning models, as well as greater affordability and accessibility of both. Improvements are noted in quality, power usage, and effectiveness.
Surface Environment and Energy Density Effects on the Detection and Disinfection of Microorganisms Using a Portable Instrument
Authors: Shin Sungho , Dowden Brianna , Doh Iyll-Joon , Rajwa Bartek , Bae Euiwon , Robinson J. Paul
Published: February 2023

Real-time detection and disinfection of foodborne pathogens are important for preventing foodborne outbreaks and for maintaining a safe environment for consumers. There are numerous methods for the disinfection of hazardous organisms, including heat treatment, chemical reaction, filtration, and irradiation. This report evaluated a portable instrument to validate its simultaneous detection and disinfection capability in typical laboratory situations. In this challenging study, three gram-negative and two gram-positive microorganisms were used. For the detection of contamination, inoculations of various concentrations were dispensed on three different surface types to estimate the performance for minimum-detectable cell concentration. Inoculations higher than 103~104 CFU/mm2 and 0.15 mm of detectable contaminant size were estimated to generate a sufficient level of fluorescence signal. The evaluation of disinfection efficacy was conducted on three distinct types of surfaces, with the energy density of UVC light (275-nm) ranging from 4.5 to 22.5 mJ/cm2 and the exposure time varying from 1 to 5 s. The study determined the optimal energy dose for each of the microorganisms species. In addition, surface characteristics may also be an important factor that results in different inactivation efficacy. These results demonstrate that the proposed portable device could serve as an in-field detection and disinfection unit in various environments, and provide a more efficient and user-friendly way of performing disinfection on large surface areas.
Cross-Domain Open Set Fault Diagnosis Based on Weighted Domain Adaptation with Double Classifiers
Authors: Wang Huaqing , Xu Zhitao , Tong Xingwei , Song Liuyang
Published: February 2023

The application of transfer learning in fault diagnosis has been developed in recent years. It can use existing data to solve the problem of fault recognition under different working conditions. Due to the complexity of the equipment and the openness of the working environment in industrial production, the status of the equipment is changeable, and the collected signals can have new fault classes. Therefore, the open set recognition ability of the transfer learning method is an urgent research direction. The existing transfer learning model can have a severe negative transfer problem when solving the open set problem, resulting in the aliasing of samples in the feature space and the inability to separate the unknown classes. To solve this problem, we propose a Weighted Domain Adaptation with Double Classifiers (WDADC) method. Specifically, WDADC designs the weighting module based on Jensen–Shannon divergence, which can evaluate the similarity between each sample in the target domain and each class in the source domain. Based on this similarity, a weighted loss is constructed to promote the positive transfer between shared classes in the two domains to realize the recognition of shared classes and the separation of unknown classes. In addition, the structure of double classifiers in WDADC can mitigate the overfitting of the model by maximizing the discrepancy, which helps extract the domain-invariant and class-separable features of the samples when the discrepancy between the two domains is large. The model’s performance is verified in several fault datasets of rotating machinery. The results show that the method is effective in open set fault diagnosis and superior to the common domain adaptation methods.
Private ownership of land and rental agricultural land use
Authors:   All-Russian Research Institute of Agricultural Economics, FSBI FNC VNIIESH, Moscow, Alakoz V. V.
Published: February 2023

The article discusses issues of private property and rent of agricultural land use. Land policy in the field of agricultural land use in the post-reform period of the transition from the state and collective ownership of land to more individualized and sensitive structure of land ownership is not realized, the state "did not leave the land" and continues to rent unjustifiably large areas of productive agricultural land for short-term period of 3-5 years, provoking their depleting use, vicious practice of unwise consumption, encourages the excessive concentration of agricultural land for individuals to displace small and medium-sized agricultural business from agricultural production. It also attracts land speculators buying up agricultural land and creating the deficit in abundance; they are re-lease lands at a ten-fold rental payment, appropriating land rent owned by municipalities (rent in the regions of the Central Black Earth Economic Region exceeds the land tax calculated at an unreasonably underestimated tax rate of 0.3% by 60 times). The present-time land policy should focus on existing problems to ensure free access to land, protect the rights of land ownership, develop the land market, ensure environmental sustainability, and combat poverty. It is important to determine the current range of issues with which land policy must deal, highlight priority areas for improving it and organize the relevant activities of the state in the field of regulation of land relations.
Problems of sustainable development of agricultural production
Authors:   State University of Land Management, Moscow, Sagaydak A. A. , Seljanskij M. S ,   State University of Land Management, Moscow
Published: February 2023

The article describes the economic aspects of ensuring the sustainable development of agricultural production in modern conditions based on the rational use of production factors: land, labor and capital in agriculture.
The results of land evaluation in the North-West economic region
Authors:   St. Petersburg State Agrarian University, Pavlova V. A. , Baranova D. V. ,   St. Petersburg State Agrarian University
Published: February 2023

The article contains the results of land evaluation works in the North-West economic district, whose regions used various approaches to evaluation of agricultural land. As a result of the study, the authors proved that in the underdeveloped market of the best lands, the use of approaches other than profitable is impossible. On the results of the cadastral valuation in Novgorod region, it was proved that the application of a comparative approach to land evaluation of the indicated category leads to the fact that the value of agricultural land in less developed regions is several times higher than in the regions - leaders in economic development, while initially all regions are the parts of the North-West Economic Region and belong to the same natural and agricultural zone and province.
Inventory of real estate for subsequent cadastral registration in Moscow
Authors:   State University of Land Management, Moscow, Anafieva A. V.
Published: February 2023

The author paid a special attention to the inventory of real estate objects. Inventory is an actual problem for most major cities and Moscow is no exception. Inventory is a system for collecting, storing, and processing information about real estate objects, allowing further reliability of cadastral records about these objects. The characteristics of real estate objects, especially land plots, are of particular importance for their further management. Without any doubt, the land acts as a basis for the development of various industries. In this regard, this article analyzes the features of land inventory on the territory of Moscow in order to carry out further cadastral registration of such real estate objects.
Investigating inconsistent uncertainty quantification encountered in neural network modelling of nonlinear response of a laminar flame
Authors: Rywik Marcin , da Cruz David , Polifke Wolfgang
Published: February 2023

Neural network models, thanks to their flexibility and ability to approximate any function, are gaining popularity across all research fields. In thermoacoustics, one of their applications is modelling of a nonlinear flame response, learned from a single broadband forcing time series
obtained through a computational fluid dynamics simulation. However, the investigations on this flame modelling approach conducted by Jaensch et al. [1] and Tathawadekar et al. [2] report contradictory results, concerning the performance and uncertainty of the derived multi-layer perceptron
networks, despite using identical training data. This paper reevaluates their findings and aims to reconcile the opposing conclusions. This work demonstrates the reason for the different network performances, by reviewing the data split policies and identifying shuffling as a detrimental factor.
Additionally, in this study different regularisation techniques such as L1 and L2 regularisation as well as network size reduction are considered. Those are compared against the previously tested implementation of dropout [2], which was believed to be responsible for the difference in the
results between the two studies.
Analisis Yuridis Peran Kepolisian Dalam Penanggulangan Pelanggaran Lalu Lintas Melalui Keadilan Restoratif (Restorative Justice) di Wilayah Hukum Kepoliisian Resor (Polres) Ogan Komering Ilir
Authors: Muriyanto Muriyanto
Published: February 2023

Salah satu permasalahan di jalan raya yang selalu kita hadapi adalah masalah lalu lintas. Hal ini terbukti dengan adanya indikasi angka kecelakaan lalu lintas yang selalu meningkat. Sekarang perkembangan lalu lintas semakin meningkat sangat pesat, keadaan ini salah satu perwujudan dari perkembangan teknologi modern. Permasalahan dalam penelitian ini adalah Bagaimana implementasi penegakan hukum kepolisian dalam penanggulangan pelanggaran lalu lintas yang mengakibatkan kecelakaan melalui Keadilan Restoratif (Restorative Justice) di wilayah hukum Kepolisian Resor (Polres) Ogan Komering Ilir? Serta Apakah kendala yang dihadapi kepolisian dalam penanggulangan pelanggaran lalu lintas yang mengakibatkan kecelakaan melalui Keadilan Restoratif (Restorative Justice) di wilayah hukum Kepolisian Resor (Polres) Ogan Komering Ilir. Metode penelitian yang digunakan ialah penelitian yuridis normatif yang merupakan penelitian yang dilakukan dengan cara meneliti bahan pustaka atau data sekunder. Hasil penelitian ini adalah Implemenasi Penegakan Hukum untuk dapat menyelesaikan agar tidak terjadi penumpukan kasus kecelakan lalu lintas pada Polres Ogan Komering Ulu, maka jalan yang terbaik adalah dengan menerapkan penyelesaian restorative justice (keadilan restorative) yaitu mempertemukan antar pelaku-korban, dan pihak keluarga untuk menyelesaikan perselisihannya dengan disaksikan oleh Polisi setempat.
Investasi Asing & Alih Teknologi
Authors: Jamaluddin Fitriani , Faisal Fitriah , Kahfi Muhammad Ashabul
Published: February 2023

As a developing country, Indonesia requires a large enough capital to carry out national development. The capital needed for national development is not immediately available, but the Government must make useful policies in order to obtain large amounts of capital. One of the policies that can help Indonesia to obtain a large enough capital is the policy in the field of investment in the form of direct investment
Yudicial Review Omnibus Law Dalam Melindungi Pekerja dan Mengembangkan Investasi di Indonesia
Authors: Purwanto Muhammad Eko , Lubis Efridani
Published: February 2023

The urgency of the Omnibus Law as a solution to investment regulation in Indonesia is because Indonesia is a legal state that has the role of a welfare state. In addition, omnibus law is also a concept of a legal product that functions to consolidate various themes, materials, subjects, and laws and regulations in each sector to become one extensive and holistic legal product. With the establishment and promulgation of the omnibus, it is hoped that it will facilitate investment for investors, which will impact increasing the economy as people's prosperity. Omnibus law as the rule of law will embody the rule of law in the economic aspect as legal certainty, benefit, and justice. In addition, the Omnibus Law is also expected to protect the Indonesian workforce in the future, such as regulations regarding worker status, wages, working hours, compensation for layoffs, and the use of foreign workers. Directly or indirectly.
Efektivitas Persidangan Berbasis E-Court
Authors: Intihani Siti Nur , Arifudin Arifudin , Juliani Juliani
Published: February 2023

E-Court (Pengadilan Elektronik) adalah aplikasi yang berisi layanan untuk Pengguna Terdaftar untuk kasus online pendaftaran, memperoleh perkiraan biaya pengadilan online, pembayaran online, panggilan melalui saluran elektronik, dan percobaan yang dilakukan secara elektronik Peluncuran eCourt ini dinilai sebagai terobosan yang mampu mewujudkan uji coba yang sederhana, cepat, dan berhiaya rendah. Di sisi lain karena pandemi Covid-19, e-Court menjadi sarana bagi pencari keadilan yang memberikan kemudahan dan tidak perlu berhubungan dengan banyak orang Namun, yang perlu ditelaah lebih lanjut dan juga menjadi rumusan masalah dalam penelitian ini adalah bagaimana efektifkab sidang berbasis e-Court selama pandemi Covid-19 di PN Bekasi? Penelitian ini menggunakan metode penelitian yuridis normatif dan metode empiris, yaitu dengan menelaah primer data yang diperoleh langsung dari lokasi penelitian Haul penelitian menggambarkan bahwa berbasis e-Court sidang di masa pandemi Covid-19 di Pengadilan Negen Bekasi sudah efektif, sehingga dapat mempermudah dan mempercepat proses perkara dan mengurangi biaya Pengadilan meskipun dalam beberapa tahap proses uji coba masih konvensional yaitu pada tahap pembuktian dan pembacaan putusan