bluuebunny/crossref_metadata_2025 huggingface dataset:
Damage Prediction Observation for Existing Buildings in Sabah under Moderate Risk Earthquakes
Authors: Harith Noor Sheena Herayani , Hassan Nur Izzati Husna , Samir Samnursidah , Tom Ngui Min Fui , Bakar Nabilah Abu , Mohamad Habib Musa
Published: June 2023

Seismic design in building construction is still new in Malaysia. Sabah, a Malaysian state, is situated southeast of the Eurasian Plate, between the highly active Philippine Sea Plate and Indo-Australian Plate, and has a history of earthquakes, with the largest measuring a magnitude of 6.3 (2015). Although small earthquakes occur annually, most old buildings in Sabah were built pre-code and designed without considering earthquake loadings. This study aimed to analyze the potential damage to buildings in Sabah based on their vulnerability to moderate earthquakes. More than 500 buildings in seven districts were evaluated using a quantitative method based on score assignment, within 100 kilometers of the epicenters. According to the findings, more than 160 buildings in the Kota Kinabalu and Kudat districts were assessed as vulnerable to Grade 4 damage. In Ranau, Kota Marudu, Tawau, Semporna, and Lahad Datu, most buildings had a Grade 3 damage potential, with some at Grade 2 or 4. This study’s findings provide a summary of the damage risk for structures in Sabah and offer a starting point for planning and developing safer buildings that can withstand local seismic conditions. The resulting building-grade damage map can be used as a reference for future damage mitigation measures.
Environment-Aware Worker Trajectory Prediction Using Surveillance Camera in Modular Construction Facilities
Authors: Yang Qiuling , Mei Qipei , Fan Chao , Ma Meng , Li Xinming
Published: June 2023

The safety of workers in modular construction remains a concern due to the dynamic hazardous work environments and unawareness of the potential proximity of equipment. To avoid potential contact collisions and to provide a safe workplace, workers’ trajectory prediction is required. With recent technology advancements, the study in the area of trajectory prediction has benefited from various data-driven approaches. However, existing data-driven approaches are mostly limited to considering only the movement information of workers in the workplace, resulting in poor estimation accuracy. In this study, we propose an environment-aware worker trajectory prediction framework based on long short-term memory (LSTM) network to not only take the individual movement into account but also the surrounding information to fully exploit the context in the modular construction facilities. By incorporating worker-to-worker interactions as well as environment-to-worker interactions into our prediction model, a sequence of the worker’s future positions can be predicted. Extensive numerical tests on synthetic as well as modular construction datasets show the improved prediction performance of the proposed approach in comparison to several state-of-the-art alternatives. This study offers a systematic and flexible framework to incorporate rich contextual information into the prediction model in modular construction. The observation of how to integrate construction data analytics into a single framework could be inspiring for further future research to support robust construction safety practices.
The Influence of Leadership on the Projectification of the Public Construction Sector in Germany
Authors: Lühr Gunnar , Wagner Reinhard , Radujković Mladen
Published: June 2023

While the projectification of society continues to evolve, it is clearly lagging behind in the public construction sector in Germany. The purpose of the research upon which this article is based was to reveal the role that leadership has on the projectification of the construction sector and to identify the differences between the public and private sectors. Building on the theoretical concept of Institutional Work, semi-structured focus group interviews were conducted on both sides of the construction sector in Germany to ultimately reconcile the findings. The interview’s transcripts were analyzed by applying qualitative content analysis. The responses from the private sector show a very high significance of projects for everyday work and a further trend toward projectification in enterprises. This development is attributable to a positive image of executing projects in the private sector and to the leadership provided. In contrast, projects in the public sector still play a rather subordinate role and tend to be perceived culturally and cognitively as being exceptional. As projects are increasingly important for the public sector, leaders can play a key role in nurturing the necessary cultural and cognitive conditions for projectification. The application of Institutional Work concepts opens promising perspectives for future research in the context of projectification.
Response to Controlled Ovarian Stimulation Is Not Impaired in Young Patients with a Sarcoma: Results from a Monocentric Case–Control Study
Authors: Cioffi Raffaella , Pagliardini Luca , Quartucci Antonio , Papaleo Enrico , Vanni Valeria Stella , Provenzano Salvatore , Bertulli Rossella , Candiani Massimo , Mangili Giorgia
Published: June 2023

Sarcomas are relatively common in the young and their treatment can impair fertility. Fertility preservation can be achieved via the cryopreservation of gametes after controlled ovarian stimulation before cancer treatment. A reduced response to hormonal stimulation in patients suffering from certain types of malignancy is reported. The purpose of this study was to assess the performance of oocyte cryopreservation in patients with sarcoma by comparing their outcomes with those of a population without cancer. Patients were matched by age with control women undergoing hormonal stimulation for isolated male factor infertility. The population included 84 women with a sarcoma and 355 controls. In the final analysis, 37 patients with sarcoma were matched in a 1:3 ratio with 109 healthy controls. Patients with sarcoma were generally younger and were stimulated with lower FSH doses. They did not perform worse than controls during stimulation, with an average retrieval of 10.6 oocytes vs. 8.1 in the controls. Linear regression on the number of retrieved mature oocytes confirmed that patients with sarcoma performed comparably to controls. In conclusion, patients with sarcoma can expect retrieval outcomes comparable to those of patients without cancer.
Anoikis-Related Gene Signature for Prognostication of Pancreatic Adenocarcinoma: A Multi-Omics Exploration and Verification Study
Authors: Zhang Jin , Li Xuesong , Lu Yi , Wang Guowen , Ma Ying
Published: June 2023

Anoikis, a form of apoptosis that occurs due to detachment of cells from the extracellular matrix, has been linked to the development of cancer in several studies. However, its role in pancreatic cancer remains incompletely understood. In this study, we utilized univariate Cox regression and LASSO regression analyses to establish a prognostic model for pancreatic adenocarcinoma based on anoikis-related genes in the TCGA database. Additionally, we performed univariate and multifactorial Cox analyses of protein expression results for TCGA pancreatic adenocarcinoma. We further explored the difference in immune infiltration between the high-risk and low-risk groups and verified the expression of the screened genes using quantitative real-time PCR (qRT-PCR). Our findings indicate that numerous anoikis-related genes are linked to pancreatic adenocarcinoma prognosis. We identified seven prognostic genes (MET, DYNLL2, CDK1, TNFSF10, PIP5K1C, MSLN, GKN1) and validated that their related proteins, such as EGFR and MMP2, have a significant impact on the prognosis of pancreatic adenocarcinoma. Based on clustering analyses of the seven prognostic genes, patients could be classified into three distinct categories, for which somatic mutations varied significantly across the groups. High-risk and low-risk groups also exhibited significant differences in immune infiltration. All genes were found to be highly expressed in pancreatic cancer cell lines (ASPC-1, CFPAC-1) as compared to a normal pancreatic cell line (HPDE). Based on the seven anoikis-related genes, we formulated a robust prognostic model with high predictive accuracy. We also identified the significant impact of KRAS, P53, and CDKN2A mutations on the prognosis of this fatal disease. Therefore, our study highlights the crucial role of anoikis in the development of the pancreatic adenocarcinoma tumor microenvironment.
Tumor Microenvironment as a Therapeutic Target in Melanoma Treatment
Authors: Kharouf Naji , Flanagan Thomas W. , Hassan Sofie-Yasmin , Shalaby Hosam , Khabaz Marla , Hassan Sarah-Lilly , Megahed Mosaad , Haikel Youssef , Santourlidis Simeon , Hassan Mohamed
Published: June 2023

The role of the tumor microenvironment in tumor growth and therapy has recently attracted more attention in research and drug development. The ability of the microenvironment to trigger tumor maintenance, progression, and resistance is the main cause for treatment failure and tumor relapse. Accumulated evidence indicates that the maintenance and progression of tumor cells is determined by components of the microenvironment, which include stromal cells (endothelial cells, fibroblasts, mesenchymal stem cells, and immune cells), extracellular matrix (ECM), and soluble molecules (chemokines, cytokines, growth factors, and extracellular vesicles). As a solid tumor, melanoma is not only a tumor mass of monolithic tumor cells, but it also contains supporting stroma, ECM, and soluble molecules. Melanoma cells are continuously in interaction with the components of the microenvironment. In the present review, we focus on the role of the tumor microenvironment components in the modulation of tumor progression and treatment resistance as well as the impact of the tumor microenvironment as a therapeutic target in melanoma.
Direct Intra-Patient Comparison of Scaffold Protein-Based Tracers, [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3, for Imaging of HER2-Positive Breast Cancer
Authors: Bragina Olga , Chernov Vladimir , Schulga Alexey , Konovalova Elena , Hober Sophia , Deyev Sergey , Sörensen Jens , Tolmachev Vladimir
Published: June 2023

Previous Phase I clinical evaluations of the radiolabelled scaffold proteins [99mTc]Tc-ADAPT6 and DARPin [99mTc]Tc-(HE)3-G3 in breast cancer patients have demonstrated their safety and indicated their capability to discriminate between HER2-positive and HER2-negative tumours. The objective of this study was to compare the imaging of HER2-positive tumours in the same patients using [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3. Eleven treatment-naïve female patients (26–65 years) with HER2-positive primary and metastatic breast cancer were included in the study. Each patient was intravenously injected with [99mTc]Tc-ADAPT6, followed by an [99mTc]Tc-(HE)3-G3 injection 3–4 days later and chest SPECT/CT was performed. All primary tumours were clearly visualized using both tracers. The uptake of [99mTc]Tc-ADAPT6 in primary tumours (SUVmax = 4.7 ± 2.1) was significantly higher (p < 0.005) than the uptake of [99mTc]Tc-(HE)3-G3 (SUVmax = 3.5 ± 1.7). There was no significant difference in primary tumour-to-contralateral site values for [99mTc]Tc-ADAPT6 (15.2 ± 7.4) and [99mTc]Tc-(HE)3-G3 (19.6 ± 12.4). All known lymph node metastases were visualized using both tracers. The uptake of [99mTc]Tc-ADAPT6 in all extrahepatic soft tissue lesions was significantly (p < 0.0004) higher than the uptake of [99mTc]Tc-(HE)3-G3. In conclusion, [99mTc]Tc-ADAPT6 and [99mTc]Tc-(HE)3-G3 are suitable for the visualization of HER2-positive breast cancer. At the selected time points, [99mTc]Tc-ADAPT6 has a significantly higher uptake in soft tissue lesions, which might be an advantage for the visualization of small metastases.
Prognostic Value of SGK1 and Bcl-2 in Invasive Breast Cancer
Authors: Al-Alem Umaima , Rauscher Garth H. , Alem Qais Al , Kajdacsy-Balla Andre , Mahmoud Abeer M.
Published: June 2023

It is crucial to understand molecular alterations in breast cancer and how they relate to clinicopathologic factors. We have previously shown that the glucocorticoid receptor (GCR) protein expression was reduced in invasive breast carcinoma compared to normal breast tissue. Glucocorticoids, signaling through the GCR, regulate several cellular processes via downstream targets such as serum/glucocorticoid-regulated kinase 1 (SGK1) and B-cell lymphoma 2 (Bcl-2). We measured the expression of SGK1 and Bcl-2, in respective breast cancer tissue arrays, from a multiracial cohort of breast cancer patients. Higher cytoplasmic SGK1 staining was stronger in breast cancer tissue compared to normal tissue, especially in hormone receptor-negative cases. Conversely, the expression of cytoplasmic Bcl-2 was reduced in breast cancer compared to normal tissue, especially in hormone receptor-negative cases. Bcl-2 staining was associated with the self-reported racial/ethnic category, an earlier clinical stage, a lower histological grade, and a higher survival rate. Bcl-2 expression was associated with longer survival in models adjusted for age and race (HR = 0.32, 95% CI: 0.15, 0.65), and Bcl-2 expression remained strongly positively associated with protection from breast cancer death, with additional adjustments for ER/PR status (HR = 0.41, 95% CI: 0.2, 0.85). SGK1 and Bcl-2 may play biological roles in breast cancer development and/or progression.
Photodeposition of Hydroxyapatite into a Titanium Dioxide Nanotubular Layer Using Ca(EDTA) Complex Decomposition
Authors: Yurova Veronika Yu. , Zyrianova Polina I. , Nesterov Pavel V. , Goncharov Vyacheslav V. , Skorb Ekaterina V. , Ulasevich Sviatlana A.
Published: June 2023

A new photocatalytic hydroxyapatite (HA) synthesis method has been developed. This method is based on the unique ability of the TiO2 photocatalyst to decompose the Ca(EDTA) complex under UV illumination. As a result, released Ca2+ ions react with PO43− ions forming the HA particles. The photocatalytic formation of hydroxyapatite is found to have a fractional order, which may indicate the complex reaction mechanism and the presence of several limiting stages. The TNT-HA samples were studied by XRD, FTIR, SEM, GDOES, and biocompatibility study. High biocompatibility of the surfaces is proven by pre-osteoblast cell growth.
Potential Diagnostic Value of Salivary Tumor Markers in Breast, Lung and Ovarian Cancer: A Preliminary Study
Authors: Bel’skaya Lyudmila V. , Sarf Elena A. , Loginova Alexandra I. , Vyushkov Dmitry M. , Choi En Djun
Published: June 2023

The aim of the study was to determine the content of tumor markers for breast, lung and ovarian cancer in saliva, as well as for benign diseases of the corresponding organs and in the control group, and to evaluate their diagnostic significance. Strictly before the start of treatment, saliva samples were obtained and the concentrations of tumor markers (AFP, NSE, HE4, CA15-3, CA72-4, CA125 and CEA) were determined using an enzyme immunoassay (ELISA). CA125 and HE4 were simultaneously determined to be in the blood serum of patients with ovarian cancer. The concentrations of salivary CEA, NSE, CA15-3, CA72-4 and CA125 of the control group were significantly lower than in oncological diseases; however, these tumor markers also increased in saliva with benign diseases. The content of tumor markers depends on the stage of cancer, and the presence of lymph node metastasis; however, the identified patterns are statistically unreliable. The determination of HE4 and AFP in saliva was not informative. In general, the area of potential use of tumor markers in saliva is extremely narrow. Thus, CEA may be diagnostic for breast and lung cancer, but not for ovarian cancer. CA72-4 is most informative for ovarian mucinous carcinoma. None of the markers showed significant differences between malignant and non-malignant pathologies.
Comparative Effectiveness of Chemotherapy Alone Versus Radiotherapy-Based Regimens in Locally Advanced Pancreatic Cancer: A Real-World Multicenter Analysis (PAULA-1)
Authors: Arcelli Alessandra , Tarantino Giuseppe , Cellini Francesco , Buwenge Milly , Macchia Gabriella , Bertini Federica , Guido Alessandra , Deodato Francesco , Cilla Savino , Scotti Valerio , Rosetto Maria Elena , Djan Igor , Parisi Salvatore , Mattiucci Gian Carlo , Fiore Michele , Bonomo Pierluigi , Belgioia Liliana , Niespolo Rita Marina , Gabriele Pietro , Di Marco Mariacristina , Simoni Nicola , Ma Johnny , Strigari Lidia , Mazzarotto Renzo , Morganti Alessio Giuseppe
Published: June 2023

Different options for locally advanced pancreatic cancer (LAPC) are available based on international guidelines: chemotherapy (CHT), chemoradiation (CRT), and stereotactic body radiotherapy (SBRT). However, the role of radiotherapy is debated in LAPC. We retrospectively compared CHT, CRT, and SBRT ± CHT in a real-world setting in terms of overall survival (OS), local control (LC), and distant metastasis-free survival (DMFS). LAPC patients from a multicentric retrospective database were included (2005–2018). Survival curves were calculated using the Kaplan–Meier method. Multivariable Cox analysis was performed to identify predictors of LC, OS, and DMFS. Of the 419 patients included, 71.1% were treated with CRT, 15.5% with CHT, and 13.4% with SBRT. Multivariable analysis showed higher LC rates for CRT (HR: 0.56, 95%CI 0.34–0.92, p = 0.022) or SBRT (HR: 0.27, 95%CI 0.13–0.54, p < 0.001), compared to CHT. CRT (HR: 0.44, 95%CI 0.28–0.70, p < 0.001) and SBRT (HR: 0.40, 95%CI 0.22–0.74, p = 0.003) were predictors of prolonged OS with respect to CHT. No significant differences were recorded in terms of DMFS. In selected patients, the addition of radiotherapy to CHT is still an option to be considered. In patients referred for radiotherapy, CRT can be replaced by SBRT considering its duration, higher LC rate, and OS rate, which are at least comparable to that of CRT.
Translational Models in Glioma Immunotherapy Research
Authors: Ren Alexander L. , Wu Janet Y. , Lee Si Yeon , Lim Michael
Published: June 2023

Immunotherapy is a promising therapeutic domain for the treatment of gliomas. However, clinical trials of various immunotherapeutic modalities have not yielded significant improvements in patient survival. Preclinical models for glioma research should faithfully represent clinically observed features regarding glioma behavior, mutational load, tumor interactions with stromal cells, and immunosuppressive mechanisms. In this review, we dive into the common preclinical models used in glioma immunology, discuss their advantages and disadvantages, and highlight examples of their utilization in translational research.
In-Network Learning: Distributed Training and Inference in Networks
Authors: Moldoveanu Matei , Zaidi Abdellatif
Published: June 2023

In this paper, we study distributed inference and learning over networks which can be modeled by a directed graph. A subset of the nodes observes different features, which are all relevant/required for the inference task that needs to be performed at some distant end (fusion) node. We develop a learning algorithm and an architecture that can combine the information from the observed distributed features, using the processing units available across the networks. In particular, we employ information-theoretic tools to analyze how inference propagates and fuses across a network. Based on the insights gained from this analysis, we derive a loss function that effectively balances the model’s performance with the amount of information transmitted across the network. We study the design criterion of our proposed architecture and its bandwidth requirements. Furthermore, we discuss implementation aspects using neural networks in typical wireless radio access and provide experiments that illustrate benefits over state-of-the-art techniques.
Utility–Privacy Trade-Offs with Limited Leakage for Encoder
Authors: Shinohara Naruki , Yagi Hideki
Published: June 2023

The utilization of databases such as IoT has progressed, and understanding how to protect the privacy of data is an important issue. As pioneering work, in 1983, Yamamoto assumed the source (database), which consists of public information and private information, and found theoretical limits (first-order rate analysis) among the coding rate, utility and privacy for the decoder in two special cases. In this paper, we consider a more general case based on the work by Shinohara and Yagi in 2022. Introducing a measure of privacy for the encoder, we investigate the following two problems: The first problem is the first-order rate analysis among the coding rate, utility, privacy for the decoder, and privacy for the encoder, in which utility is measured by the expected distortion or the excess-distortion probability. The second task is establishing the strong converse theorem for utility–privacy trade-offs, in which utility is measured by the excess-distortion probability. These results may lead to a more refined analysis such as the second-order rate analysis.
Bifocal Dual Reflectarray with Curved Main Surface
Authors: Pino Antonio , Rodriguez-Vaqueiro Yolanda , Martinez-de-Rioja Eduardo , Martinez-de-Rioja Daniel , González-Valdés Borja , Arias Marcos , Rubiños Oscar , Encinar José Antonio , Toso Giovanni
Published: June 2023

This paper presents a novel approach to synthesizing curved reflectarrays using Geometrical Optics (GO). It introduces the concepts of virtual normal and path length shift, which enable a vector-based formulation of the problem that can be solved using ray tracing techniques. The formulation is applied for the design of two different versions of a Dual Bifocal Reflectarray with a parabolic main surface and a flat subreflectarray. The first version aims to enhance the performance of the multibeam antenna by providing a focal ring located at the feed cluster plane. The second version focuses on improving the scanning characteristics of the antenna in the horizontal plane by incorporating two foci. The synthesis procedure yields samples of the path length shift or its derivatives. To reconstruct the phase distribution, an interpolation scheme is employed and described in this paper. Numerical results are presented for both the focal-ring and two-foci configurations, demonstrating the feasibility of this solution for multibeam or scanning satellite antennas operating in the Ka.
Multimodal Fine-Grained Transformer Model for Pest Recognition
Authors: Zhang Yinshuo , Chen Lei , Yuan Yuan
Published: June 2023

Deep learning has shown great potential in smart agriculture, especially in the field of pest recognition. However, existing methods require large datasets and do not exploit the semantic associations between multimodal data. To address these problems, this paper proposes a multimodal fine-grained transformer (MMFGT) model, a novel pest recognition method that improves three aspects of transformer architecture to meet the needs of few-shot pest recognition. On the one hand, the MMFGT uses self-supervised learning to extend the transformer structure to extract target features using contrastive learning to reduce the reliance on data volume. On the other hand, fine-grained recognition is integrated into the MMFGT to focus attention on finely differentiated areas of pest images to improve recognition accuracy. In addition, the MMFGT further improves the performance in pest recognition by using the joint multimodal information from the pest’s image and natural language description. Extensive experimental results demonstrate that the MMFGT obtains more competitive results compared to other excellent models, such as ResNet, ViT, SwinT, DINO, and EsViT, in pest recognition tasks, with recognition accuracy up to 98.12% and achieving 5.92% higher accuracy compared to the state-of-the-art DINO method for the baseline.
Human Action Recognition Using Key-Frame Attention-Based LSTM Networks
Authors: Yang Changxuan , Mei Feng , Zang Tuo , Tu Jianfeng , Jiang Nan , Liu Lingfeng
Published: June 2023

Human action recognition is a classical problem in computer vision and machine learning, and the task of effectively and efficiently recognising human actions is a concern for researchers. In this paper, we propose a key-frame-based approach to human action recognition. First, we designed a key-frame attention-based LSTM network (KF-LSTM) using the attention mechanism, which can be combined with LSTM to effectively recognise human action sequences by assigning different weight scale values to give more attention to key frames. In addition, we designed a new key-frame extraction method by combining an automatic segmentation model based on the autoregressive moving average (ARMA) algorithm and the K-means clustering algorithm. This method effectively avoids the possibility of inter-frame confusion in the temporal sequence of key frames of different actions and ensures that the subsequent human action recognition task proceeds smoothly. The dataset used in the experiments was acquired with an IMU sensor-based motion capture device, and we separately extracted the motion features of each joint using a manual method and then performed collective inference.
Which Influencers Can Maximize PCR of E-Commerce?
Authors: Oh Hayoung , Lee Jiyoon , Lee Joo-Sik , Kim Sung-Min , Lim Sechang , Jung Dongha
Published: June 2023

The Web has provided an increasing proportion of use as a medium for e-commerce in addition to various recommender systems. It can be used for analyzing recommendation system-based feedback (e.g., a form in which a user inputs their preferences for various items as numerical values into a specific evaluation system) to estimate customer interest; in addition, analyzing multi-modal types of feedback (e.g., product purchase traces, inquiry lists, inquiry times, and comments) with deep learning can also be used to estimate user interest. As many companies around the world promote their products through micro-influencers on the Web, related research has continued to predict the purchase conversion rate of the influencer through a variety of technologies. In this work, we present a multi-modal micro-influencer analysis scheme for a marketing maximization strategy. Our scheme uses the multi-modal data stored in Mecha Solution’s own shopping mall of Korea, as well as famous Korean Internet platforms, and Coupang, Naver, and Oliveyoung’s data such as article posting comments and statistics information. By extracting the main characteristics of the real article postings from real users as opposed to those from factitious influencers posting articles and comments and identifying articles other than advertisements, influencer scores are obtained, assuming that articles other than advertisements can further increase the purchase conversion rate. Based on influencer score, we propose a multi-modal micro-influencer analysis scheme that recommends influencers use content-based collaborative filtering and user-based collaborative filtering for items that the influencer has not yet reviewed. The experiment was implemented to prove that the proposed scheme successfully achieves this goal.
The Hybrid Brake Model and Its Validation
Authors: Holtmann Christoph , Köhler Christoph , Weber Christian , Rinderknecht Frank
Published: June 2023

As an extension of a paper published at the 24th International Conference on Mechatronics Technology, ICMT 2021 conference, this paper shows the concept, design method, and model of a hybrid brake with additional validation. An eddy current brake cannot be used to decelerate a vehicle to a standstill. However, the magnetic attraction force between the rotor and stator of an eddy current brake can be used to generate an additional mechanical friction torque. By using a disc spring between the rotor and stator, the eddy current brake is extended to a so-called hybrid brake. In particular, the model and design method of the disc spring are the focus of this work. Using a system model that includes the electromagnetic and mechanical domains, the wear reduction compared to a conventional friction brake and the dynamic behaviour depending on the spring parameters are investigated. Finally, a disc spring is designed in FEM with the desired force–displacement curve. In addition, a working demonstrator of a hybrid brake is constructed, and the electromagnetic and mechanical system models are compared with the experimental results. For the first time, it is shown that the concept of using the magnetic attraction force between the rotor and stator of an eddy current brake for braking to a stop is working. In a speed range of 0–7500 rpm, it is possible to generate a torque of 100 Nm, whereby at speeds higher than 3500 rpm, the torque is generated in a wear-free manner by eddy currents. However, in order to be valid, the model must be extended to represent the deformation of the rotor.
Power Quality Measurement Results for a Configurable Urban Low-Voltage DC Microgrid
Authors: van den Brom Helko E. , van Leeuwen Ronald , Maroulis Gerasimos , Shah Samad , Mackay Laurens
Published: June 2023

The growing use of renewable energy sources and sustainable technologies has increased the attractiveness of low-voltage DC distribution grids. Despite initial research and standardization work, the definition of power quality (PQ) issues and their related compatibility levels in DC grids and the related measurement techniques remain in their infancy. The lack of available measurement results obtained in real-world situations is a major shortcoming. In this paper, the results of a measurement campaign obtained in a configurable bipolar 350 V/700 V DC microgrid in an urban environment are presented. Voltage and current signals were registered continuously at different positions in the microgrid with a sampling rate of 500 kSa/s while changing the configuration of the microgrid; the resulting data were analyzed afterwards, with a focus on DC voltage and current variation, ripple, and spectral analysis. The measurements were taken with custom-designed metrology-sound measurement equipment. The measurement results provide input to the development of DC PQ analysis tools and the standardization of DC PQ measurement methods. Furthermore, the experience obtained will be beneficial for utility companies and regulatory authorities for reliable planning-level and compatibility-level surveys.
Route Planning for Electric Vehicles Including Driving Style, HVAC, Payload and Battery Health
Authors: Ponso Alberto , Bonfitto Angelo , Belingardi Giovanni
Published: June 2023

The increasing environmental awareness paired with the rise of global warming effects has led, in the past few years, to an increase in the sales of electric vehicles (EVs), partly but not only, caused by governmental incentives. A significant roadblock in the mass transition to EVs can be found in the so-called range anxiety: not only do EVs have, generally, considerably shorter ranges than their internal combustion engine vehicle (ICEV) equivalents, but recharge takes significantly longer than does filling up a gas tank, and charging stations are less widespread than are petrol stations. To counteract this, EV manufacturers are developing route planners which select the best route to go from A to B according to the range of the vehicle and the availability of charging stations. These tools are indeed powerful but do not account for the state of health (SoH) of the battery or for temperature conditions, two factors which may severely degrade the range of an EV. This article presents an innovative route planning method which takes into account SoH, temperature and driving style and selects, along the planned route, the charging stations among those which can be reached with the energy of the battery. To verify its proper operativity, simulations were conducted, highlighting the risk of running out of battery before destination, considering if the route is planned based on the declared range, and taking into account battery SoH, external temperature and driving style.
Simulation of the Progress of the Decarbonization Process in Poland’s Road Transport Sector
Authors: Pyra Mariusz
Published: June 2023

In the years ahead, the majority of the EU member states will be implementing their energy and climate plans. These plans are aimed at fulfilling obligations related to the strategy for the Sustainable and Smart Mobility Strategy and the “Fit for 55” package. The European Commission has presented highly challenging proposals for the decarbonization of the transport sector through electrification and support for innovation. The decarbonization of transport will not be possible without cooperation and mutual understanding between manufacturers, suppliers, and customers, or without proper organization of the transport process itself. High-emission means of transport must be replaced with low-emission ones. In the EU, road transport generates 70% of all transport emissions. There are few scalable decarbonization opportunities in the transport sector. Various kinds of solutions should be promoted, yet at the same time, it is imperative to analyze the current situation and forecast desirable potential future outcomes. By employing optimization theory tools, specifically the SOLVER add-in—an Excel-based optimization tool—the optimum structure of the stock of road transport vehicles in Poland’s commercial road transport sector was searched for. Several research hypotheses were formulated, primarily focusing on the potential for electric vehicles to reduce emissions significantly. These findings suggest a promising outlook for this transition, with particular implications for decision-makers in the field of shaping transport policy. As a result of the conducted analyses and simulations, the hypothesis—that the application of selected elements of optimization theory tools allows us to determine the optimum stock structure of the Polish road transport sector in terms of propulsion system type (emission performance) in the context of pollutant emission targets set for the sector resulting from the EU’s climate policy targets, the European Green Deal, and the EU’s transport policy in terms of decarbonization, taking into account determinants and constraints included in the analysis—was confirmed. An important finding and result is the statement that, in its current state, the Polish road transport sector is not ready for the challenges related to the new goals of climate policy, the European Green Deal, and EU transport policy in the context of decarbonization.
Review on Artificial Intelligence-Based Fault Location Methods in Power Distribution Networks
Authors: Rezapour Hamed , Jamali Sadegh , Bahmanyar Alireza
Published: June 2023

This paper provides a comprehensive and systematic review of fault localization methods based on artificial intelligence (AI) in power distribution networks described in the literature. The review is organized into several sections that cover different aspects of the methods proposed. It first discusses the advantages and disadvantages of various techniques used, including neural networks, fuzzy logic, and reinforcement learning. The paper then compares the types of input and output data generated by these algorithms. The review also analyzes the data-gathering systems, including the sensors and measurement equipment used to collect data for fault diagnosis. In addition, it discusses fault type and DG considerations, which, together with the data-gathering systems, determine the applicability range of the methods. Finally, the paper concludes with a discussion of future trends and research gaps in the field of AI-based fault location methods. Highlighting the advantages, limitations, and requirements of current AI-based methods, this review can serve the researchers working in the field of fault location in power systems to select the most appropriate method based on their distribution system and requirements, and to identify the key areas for future research.
On-Road Experimental Campaign for Machine Learning Based State of Health Estimation of High-Voltage Batteries in Electric Vehicles
Authors: Lelli Edoardo , Musa Alessia , Batista Emilio , Misul Daniela Anna , Belingardi Giovanni
Published: June 2023

The present study investigates the use of machine learning algorithms to estimate the state of health (SOH) of high-voltage batteries in electric vehicles. The analysis is based on open-circuit voltage (OCV) measurements from 12 vehicles with different mileage conditions and focuses on establishing a correlation between the OCV values, the energy stored in the battery, and the battery SOH. The experimental campaign was conducted at the Hyundai Motor Europe Technical Center GmbH (Germany), and the data collection process took advantage of the ETAS Integrated Calibration and Application Tool (INCA) and the ETAS Measure Data Analyzer (MDA) software. Six machine learning algorithms are evaluated and compared, namely linear regression, k-nearest neighbors, support vector machine, random forest, classification and regression tree, and neural network. Among the evaluated algorithms, random forest (RF) exhibits the best performance in predicting the state of health of high-voltage batteries, both for the OCV and the capacity (C) estimation. Specifically, if compared to the worst algorithm (i.e., linear regression), RF achieves a remarkable improvement with a reduction of 96% and 97% in the mean absolute error for the OCV and the C estimation, respectively. Furthermore, the comparison highlighted the main differences in the performance, complexity, interpretability, and specific features of the six algorithms. The findings of the present study will contribute to the development of efficient maintenance strategies, thus reducing the risk of unexpected battery failures.
Optimization Study on Salinity Gradient Energy Capture from Brine and Dilute Brine
Authors: Gao Hailong , Xiao Zhiyong , Zhang Jie , Zhang Xiaohan , Liu Xiangdong , Liu Xinying , Cui Jin , Li Jianbo
Published: June 2023

The power conversion of salinity gradient energy (SGE) between concentrated brine from seawater desalination and seawater by reverse electrodialysis (RED) benefits energy conservation and also dilutes the discharge concentration to relieve the damage to coastal ecosystems. However, two key performance indexes of the maximum net power density and energy conversion efficiency for a RED stack harvesting the energy usually cannot reach the optimal simultaneously. Here, an optimization study on the two indexes was implemented to improve the performance of RED in harvesting the energy. A RED model for capturing the SGE between concentrated brine and seawater was constructed, and the correlation coefficients in the model were experimentally determined. Based on the model, the effects of a single variable (concentration, flow rate, temperature, thickness of the compartment, length of the electrode) on the performance of a RED stack are analyzed. The multi-objective optimization method based on the genetic algorithm was further introduced to obtain the optimal solution set, which could achieve the larger net power density and energy conversion efficiency with coordination. The ranges of optimal feed parameters and stack size were also obtained. The optimal flow velocity of the dilute solution and the concentration of the dilute solution are approximately 7.3 mm/s and 0.4 mol/kg, respectively.
Economic/Environmental Optimal Power Flow Using a Multiobjective Convex Formulation
Authors: Yamaguti Lucas do Carmo , Home-Ortiz Juan Manuel , Pourakbari-Kasmaei Mahdi , Mantovani José Roberto Sanches
Published: June 2023

This paper addresses the problem of economic/environmental optimal power flow with a multiobjective formulation using a second-order conic programming (SOCP) optimization model. This problem formulation considers renewable energy sources (RES), fossil-fuel-based power generation units, and voltage control. The proposed SOCP model is a stochastic scenario-based approach to deal with RES and load behavior uncertainties. An ε-constrained algorithm is used to handle the following three objective functions: (1) the costs of power generation, (2) active power losses in the branches, and (3) the emission of pollutant gases produced by fossil-fuel-based power generation units. For comparative purposes, the SOCP model is also presented using a linearized formulation, and numerical results are presented using a 118-bus system. The results confirm that changing the energy matrices directly affects the cost of objective functions. Additionally, using a linearized SOCP model significantly reduces reactive power violation in the generation units when compared to the nonlinearized SOCP model, but also increases the computational time consumed.
Optimization Method Based on Hybrid Surrogate Model for Pulse-Jet Cleaning Performance of Bag Filter
Authors: Sun Shirong , Liu Libing , Yang Zeqing , Cui Wei , Yang Chenghao , Zhang Yanrui , Chen Yingshu
Published: June 2023

The pulse-jet cleaning process is a critical part of the bag filter workflow. The dust-cleaning effect has a significant impact on the operating stability of bag filters. Aiming at the multi-parameter optimization problem involved in the pulse-jet cleaning process of bag filters, the construction method of hybrid surrogate models based on second-order polynomial response surface models (PRSMs), radial basis functions (RBFs), and Kriging sub-surrogate models is investigated. With four sub-surrogate model hybrid modes, the corresponding hybrid surrogate models, namely PR-HSM, PK-HSM, RK-HSM, and PRK-HSM, are constructed for the multi-parameter optimization involved in the pulse-jet cleaning process of bag filters, and their objective function is the average pressure on the inner side wall of the filter bag at 1 m from the bag bottom. The genetic algorithm is applied to search for the optimal parameter combination of the pulse-jet cleaning process. The results of simulation experiments and optimization calculations show that compared with the sub-surrogate model PRSM, the evaluation indices RMSE, R2, and RAAE of the hybrid surrogate model RK-HSM are 9.91%, 4.41%, and 15.60% better, respectively, which greatly enhances the reliability and practicability of the hybrid surrogate model. After using the RK-HSM, the optimized average pressure F on the inner side wall of the filter bag at 1 m from the bag bottom is −1205.1605 Pa, which is 1321.4543 Pa higher than the average pressure value under the initial parameter condition set by experience, and 58.4012 Pa to 515.2836 Pa higher than using the three sub-surrogate models, verifying its usefulness.
Characterisation of the Enzymatically Extracted Oat Protein Concentrate after Defatting and Its Applicability for Wet Extrusion
Authors: Sargautis Darius , Kince Tatjana , Gramatina Ilze
Published: June 2023

An oat protein concentrate (OC1) was isolated from oat flour through starch enzymatic hydrolysis, by subsequent defatting by ethanol and supercritical fluid extraction (SFE) reaching protein concentrations of 78% and 77% by weight in dry matter, respectively. The protein characterisation and functional properties of the defatted oat protein concentrates were evaluated, compared and discussed. The solubility of defatted oat protein was minor in all ranges of measured pH (3–9), and foamability reached up to 27%. Further, an oat protein concentrate defatted by ethanol (ODE1) was extruded by a single screw extruder. The obtained extrudate was evaluated by scanning electron microscope (SEM), texture and colour analysers. The extrudate’s surface was well formed, smooth, and lacking a tendency to form a fibrillar structure. Textural analysis revealed a non-unform structure (fracturability 8.8–20.9 kg, hardness 26.3–44.1 kg) of the oat protein extrudate.
Factors Affecting the Consumption of Traditional Food in Tourism—Perceptions of the Management Sector of Catering Facilities
Authors: Kalenjuk Pivarski Bojana , Tekić Dragana , Šmugović Stefan , Banjac Maja , Novaković Aleksandra , Mutavdžić Beba , Ivanović Velibor , Tešanović Dragan , Đerčan Bojan , Ikonić Predrag , Petrović Marica , Udovičić Dragana Ilić , Popović Aleksandra Vasić , Marić Aleksandar
Published: June 2023

The topic of this study is the factors that influence the consumption of traditional food products (TFPs) in tourism, as seen from the perspective of management-sector employees in food and beverage catering facilities. The paper aims to analyse the economic, environmental, social, and touristic factors that highly influence the consumption patterns of catering facilities which are significant providers of traditional gastronomic experiences in tourism, by using the specially designed TFPct scale. The study was conducted on a sample of 300 catering facilities in AP Vojvodina (the Republic of Serbia). An explanatory factor analysis was used to confirm the key factors that influence the consumption of traditional products used to prepare the meals that are a part of what catering facilities offer. Subsequently, a binary logistics regression model was used to establish which of the indicated factors has a statistically significant effect on the management’s decision to purchase these products for their catering facility. The study showed that the TFPct scale is appropriate for this type of research, and that economic factors are key factors in the consumption of traditional products. Moreover, compared with other types of catering facilities, interest in the consumption of these products is clearly expressed by a la carte restaurants.
Miyeokgui (Undaria pinnatifida Sporophyll) Characteristic under Different Relative Humidity: Microbial Safety, Antioxidant Activity, Ascorbic Acid, Fucoxanthin, α-/β-/γ-Tocopherol Contents
Authors: Lee Kyo-Yeon , Kim Jong Min , Chun Jiyeon , Heo Ho Jin , Park Chae Eun , Choi Sung-Gil
Published: June 2023

This study aimed to investigate the effects of different relative humidities (%) on the microbial safety, antioxidant activity, ascorbic acid, fucoxanthin, and tocopherol contents of Undaria pinnatifida sporophyll powder (UPSP) stored for 4 weeks. The caking phenomenon did not occur in the 11–53% relative humidity conditions, but it did in the 69%, 81%, and 93% relative humidity conditions with caking index values of 88.30%, 99.75%, and 99.98%, respectively. The aerobic bacterial contents increased drastically in samples stored at 69–93% relative humidity. Ascorbic acid was unstable at high relative humidity, but fucoxanthin and tocopherol were more unstable at low relative humidity. Therefore, it was most stable at intermediate relative humidity. The 69% relative humidity sample had higher DPPH (12.57 g BHAE/kg), ABTS (4.87 g AAE/kg), and FRAP (4.60 g Fe (II)/kg) than the other samples. This study could be helpful for the storage and transport of UPSP under optimum relative humidity conditions, which can significantly prevent quality losses.
New Insight into the FS CMa System MWC 645 from Near-Infrared and Optical Spectroscopy
Authors: Torres Andrea Fabiana , Arias María Laura , Kraus Michaela , Mercanti Lorena Verónica , Eenmäe Tõnis
Published: June 2023

The B[e] phenomenon is manifested by a heterogeneous group of stars surrounded by gaseous and dusty circumstellar envelopes with similar physical conditions. Among these stars, the FS CMa-type objects are suspected to be binary systems, which could be experiencing or have undergone a mass-transfer process that could explain the large amount of material surrounding them. We aim to contribute to the knowledge of a recently confirmed binary, MWC 645, which could be undergoing an active mass-transfer process. We present near-infrared and optical spectra, identify atomic and molecular spectral features, and derive different quantitative properties of line profiles. Based on publicly available photometric data, we search for periodicity in the light curve and model the spectral energy distribution. We have detected molecular bands of CO in absorption at 1.62 μm and 2.3 μm for the first time. We derive an upper limit for the effective temperature of the cool binary component. We found a correlation between the enhancement of the Hα emission and the decrease in optical brightness that could be associated with mass-ejection events or an increase in mass loss. We outline the global properties of the envelope, possibly responsible for brightness variations due to a variable extinction, and briefly speculate on different possible scenarios.