bluuebunny/crossref_metadata_2025 huggingface dataset:
The Use of PCMs and PV Solar Panels in Higher Education Buildings towards Energy Savings and Decarbonization: A Case Study
Authors: Sedaghat Mojtaba , Heydari Amir Hossein , Santos Paulo
Published: August 2024

Buildings are one the largest energy-consuming sectors in the world, and it is crucial to find solutions to reduce their energy consumption. One way to evaluate these solutions is using building simulation software, which provides a comprehensive perspective. In this article, using DesignBuilder software (v 6.1), the effect of using phase-change materials (PCMs) on the external walls and ceiling of the Department of Mechanical Engineering of Shahid Beheshti University (Tehran, Iran) has been investigated. The methodology involves the use of a layer of PCMs for three locations: (1) on the walls; (2) on the ceiling; and (3) on both the walls and ceiling, with/without PV panels, which leads to seven scenarios (alongside the reference one). The result shows that using PCMs has a greater impact on the heating load than the cooling one and is more effective on ceilings than walls. For the simultaneous use of PCMs in the ceilings and walls, the heating and cooling loads, in comparison with the initial condition of the building, are reduced by 24%, and 12%, respectively. When using solar panels, the heating load increases by 12.6%, and the cooling load decreases by 8.6%, whereas the total energy consumption of the building is fairly constant when using both PV panels and PCMs. In these last conditions, the primary evaluated values shifted significantly. Notably, CO2 emissions saw a nearly 50% reduction, making the simultaneous use of PV panels and PCMs on both walls and ceilings the best performance option.
Unlocking Public Engagement in Reused Industrial Heritage: Weighting Point Evaluation Method for Cultural Expression
Authors: Zheng Xuesen , Chen Tan , Zheng Chunhui , Heath Timothy
Published: August 2024

Industrial heritage has attracted much attention because of its significant historical and cultural values. Nowadays, the functional transformation of industrial heritage buildings, such as museums, parks, and so on, into public-space-oriented buildings has been taking place all over the world. The public users of these public realms become the main audiences of industrial culture. Architects transmit the industrial culture therein to public users by using the design language. However, differences in the public’s understanding of design from different backgrounds may affect the attractiveness of the project. The tension between industrial culture and public acceptance becomes a key issue in industrial heritage renovation. The proposal of the “weighting point evaluation method” is the aim of this study, which demonstrates the usability of this mathematical and statistical method for the assessment of the cultural expression aspect in the renovation of industrial heritage. Such a quantitative assessment method is used to find the strengths and weaknesses that exist in the project, thus providing a reference point for optimizing future development. The methodology was applied at the Dalian Industrial Culture Exhibition Hall to demonstrate its validity. The results of the methodology in practice identified four aspects of the experience of public users concerned with the case and, at the same time, identified the strengths and weaknesses of the project in terms of cultural expression, providing an important reference point for further optimization in the future. Moreover, it also demonstrates flexibility and generalizability in responding to different expressions in different projects due to the variability of the weighting judgements of the methodology.
Is Autophagy Targeting a Valid Adjuvant Strategy in Conjunction with Tyrosine Kinase Inhibitors?
Authors: Elshazly Ahmed M. , Xu Jingwen , Melhem Nebras , Abdulnaby Alsayed , Elzahed Aya A. , Saleh Tareq , Gewirtz David A.
Published: August 2024

Tyrosine kinase inhibitors (TKIs) represent a relatively large class of small-molecule inhibitors that compete with ATP for the catalytic binding site of tyrosine kinase proteins. While TKIs have demonstrated effectiveness in the treatment of multiple malignancies, including chronic myelogenous leukemia, gastrointestinal tumors, non-small cell lung cancers, and HER2-overexpressing breast cancers, as is almost always the case with anti-neoplastic agents, the development of resistance often imposes a limit on drug efficacy. One common survival response utilized by tumor cells to ensure their survival in response to different stressors, including anti-neoplastic drugs, is that of autophagy. The autophagic machinery in response to TKIs in multiple tumor models has largely been shown to be cytoprotective in nature, although there are a number of cases where autophagy has demonstrated a cytotoxic function. In this review, we provide an overview of the literature examining the role that autophagy plays in response to TKIs in different preclinical tumor model systems in an effort to determine whether autophagy suppression or modulation could be an effective adjuvant strategy to increase efficiency and/or overcome resistance to TKIs.
The Association of Immune-Related Adverse Events with the Efficacy of Atezolizumab in Previously Treated Advanced Non-Small-Cell Lung Cancer Patients: A Single-Center Experience
Authors: Marković Filip , Stjepanović Mihailo , Samardžić Natalija , Kontić Milica
Published: August 2024

Immune checkpoint inhibitors (ICIs) are pivotal in managing metastatic non-oncogene addicted non-small-cell lung cancer (NSCLC). They have unique toxicities known as immune-related adverse events (irAEs). Previous studies have linked irAEs during atezolizumab-based first-line treatments in advanced NSCLC with improved outcomes. This study explored the association between irAEs and the efficacy of atezolizumab in advanced NSCLC patients who had previously received platinum-based chemotherapy. The study involved 105 advanced NSCLC patients who received atezolizumab monotherapy after progressing on at least one line of platinum-based chemotherapy from a single academic institution in Serbia. Data were obtained from a hospital lung cancer registry. Among the participants, 63.8% were male, with the majority being current (53.3%) or former smokers (37.1%). About half had a good performance status (ECOG PS 0–1) at the start of atezolizumab treatment. irAEs occurred in 23 patients (21.9%). The median progression-free survival (mPFS) was significantly longer for patients with irAEs (13.03 months) compared to those without (3.4 months) (HR 0.365 [95% CI, 0.195–0.681], p = 0.002). irAEs and ECOG PS 0–1 were predictors of longer mPFS, with irAEs being more common in patients with good performance status (p = 0.01). irAEs were linked to improved mPFS in NSCLC patients treated with atezolizumab after multiple lines of platinum-based chemotherapy.
The Impact of Oral Microbiome Dysbiosis on the Aetiology, Pathogenesis, and Development of Oral Cancer
Authors: Talapko Jasminka , Erić Suzana , Meštrović Tomislav , Stipetić Marinka Mravak , Juzbašić Martina , Katalinić Darko , Bekić Sanja , Muršić Dora , Flam Josipa , Belić Dino , Lešić Davor , Fureš Rajko , Markanović Manda , Škrlec Ivana
Published: August 2024

Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer. Although the oral cavity is an easily accessible area for visual examination, the OSCC is more often detected at an advanced stage. The global prevalence of OSCC is around 6%, with increasing trends posing a significant health problem due to the increase in morbidity and mortality. The oral cavity microbiome has been the target of numerous studies, with findings highlighting the significant role of dysbiosis in developing OSCC. Dysbiosis can significantly increase pathobionts (bacteria, viruses, fungi, and parasites) that trigger inflammation through their virulence and pathogenicity factors. In contrast, chronic bacterial inflammation contributes to the development of OSCC. Pathobionts also have other effects, such as the impact on the immune system, which can alter immune responses and contribute to a pro-inflammatory environment. Poor oral hygiene and carbohydrate-rich foods can also increase the risk of developing oral cancer. The risk factors and mechanisms of OSCC development are not yet fully understood and remain a frequent research topic. For this reason, this narrative review concentrates on the issue of dysbiosis as the potential cause of OSCC, as well as the underlying mechanisms involved.
Unraveling Childhood Obesity: A Grounded Theory Approach to Psychological, Social, Parental, and Biological Factors
Authors: Karakitsiou Georgia , Plakias Spyridon , Christidi Foteini , Tsiakiri Anna
Published: August 2024

Childhood obesity is a major medical and public health issue of global interest, which is influenced by a diverse array of factors and carries significant medical and psychosocial implications. Despite the extensive studies that have been conducted to explore the specific issue, the impact of several factors that influence, generate, worsen, and make chronic the phenomenon needs further exploration. This study aimed to construct a grounded theory that includes and connects the psychological, social, parental, and biological factors affecting childhood obesity. Key psychological factors include mental health issues such as depression and emotional eating, while social factors encompass socioeconomic status and cultural influences. Parental factors involve parenting styles and feeding practices, and biological factors relate to genetic predispositions and prenatal conditions. These factors interact in complex ways, highlighting the multifactorial nature of childhood obesity. The study employed a qualitative grounded theory approach, using research articles to achieve a thorough understanding. Qualitative analysis of the articles was conducted using Atlas.ti 24.0 software. Twenty-five research articles were required to reach theoretical saturation. The analysis resulted in 336 codes that were grouped into seven broad categories and twenty-four different subcategories. Through the construction of the theoretical framework, it was recognized that obesity in minors is a complex and multifactorial issue and that the network of causes and influencing factors covers a broad spectrum ranging from the individual to the family, and subsequently to society at large, which interact with each other.
Experience with Pediatric Chronic Immune Thrombocytopenia over 30 Years in the Era before Eltrombopag
Authors: Koc Begum S. , Ozdemir Gul Nihal , Alakbarli Javid , Apak Hilmi , Celkan Tiraje
Published: August 2024

Background: There is limited information on the natural course of chronic ITP in children. We aimed to evaluate the clinical and demographic characteristics of children with chronic ITP in the era before the availability of eltrombopag. Methods: A total of 86 children with chronic ITP between 1978–2014 were included. Demographic findings, laboratory results, clinical signs, bleeding scores, response time and time of complete remission were recorded. Results: The male/female ratio was 1.09, and median follow-up time was 3 years (range: 1.5–17 years). The median age at diagnosis of chronic ITP was 7 years (range: 2–17), and the median initial platelet count was 10 × 109/L (range: 1–66 × 109/L). Petechiae/ecchymoses were the most common clinical sign (86%) and followed by mucosal bleeding (39.5%). Severe bleeding was seen in 5% of the patients. None of them had intracranial hemorrhage. Twenty patients underwent splenectomy, and the rate of complete remission was 70%. Spontaneous complete remission was seen in 29% of the patients, and the median time to spontaneous complete remission was 3 years. Conclusions: Our study showed that almost one-third of patients with chronic ITP experienced spontaneous complete remission in an average of 3 years, and splenectomy provided satisfactory results in severe cases. This study demonstrates the natural history of chronic ITP in childhood before the era of eltrombopag.
Tracking Listening Skill Development in Infants and Children with Hearing Loss: A Normative Dataset for the Functional Listening Index—Paediatric (FLI-P®)
Authors: Cowan Robert S. C. , Davis Aleisha , Watkins Pia , Neal Katie , Brookman Ruth , Seeto Mark , Oliver Janette
Published: August 2024

Background: Longitudinal studies highlight the importance of early intervention and timely device fitting for language development in children with congenital or early acquired hearing loss. Due to the variability in hearing loss, comorbidities, family circumstances, and service access, individualised monitoring of listening development is essential to inform decision-making. The Functional Listening Index—Paediatric (FLI-P), a 64-item hierarchical checklist of listening skills, has been validated for children with hearing loss aged 0–6 years. This study aimed to develop benchmarks for the FLI-P in typically hearing children, allowing for comparison with individual children with hearing loss. Methods: FLI-P scores were obtained from parents/caregivers of 561 typically hearing children aged 0–72 months. Each child’s FLI-P score was categorised into a 6-month age block, with a minimum of 36 data points per block. Quantile regression was employed to establish percentiles of FLI-P scores by age. Results: FLI-P scores were successfully recorded for all 561 children. Regression analysis determined that the 16th and 84th percentiles of FLI-P scores corresponded to approximately ±1 standard deviation from the median score for each age group. A graphical representation of these percentile trajectories was created to facilitate comparison between children with hearing loss and the normative data. Conclusion: A normative dataset of FLI-P scores from typically hearing children has been established, allowing for comparisons with the scores and developmental trajectories of individual children with hearing loss. The study demonstrates how FLI-P can guide early intervention decisions and effectively monitor progress.
Dronabinol Is Not a Game Changer in Pediatric Palliative Care: Results from a Retrospective Study
Authors: Hauch Holger , Lisakowski Annika , Wager Julia , Zernikow Boris
Published: August 2024

Background/Objectives: Patients with life-limiting conditions (LLCs) often suffer from restlessness, spasticity, pain, and seizures. Dronabinol (DRB) may have a relieving effect; however, data on the effectiveness of DRB in children with LLCs are limited to outpatients. The aim of this study was to assess the efficacy and safety of DRB. Methods: Retrospective analysis of inpatients. Results: From 2011 to 2021, 1219 patients were admitted. Of these, 63 patients (63.5% male, age: 10.4 (SD = 6.3) years) were treated with DRB; 96.8% had a neurological disease, and 26 patients were started on DRB (group A), while 37 were admitted with existing DRB (group B). The effective doses were 0.21 (SD = 0.11) in group A and 0.48 (SD = 0.5) mg/kg/BW/day in group B (p = 0.01). Subjective response rates to DRB in both groups (good/moderate effect) were 9.5%/38.1% for spasticity and 1.6%/25.4% for restlessness. However, no reduction in seizures, restlessness, or demand medication was observed in 24 h protocols when patients started DRB in group A. Three patients experienced severe side effects (e.g., respiratory depression). Other side effects included fatigue (22.2%) and behavioral problems (14.3%). Conclusions: Subjective positive effects could not be confirmed by more objective data. Side effects can be severe. Thus, DRB should be started in a well-monitored setting and only with clear indications.
An Expected Goals on Target (xGOT) Metric as a New Metric for Analyzing Elite Soccer Player Performance
Authors: Ruiz-de-Alarcón-Quintero Anselmo , De-la-Cruz-Torres Blanca
Published: August 2024

Introduction: Football analysis is an applied research area that has seen a huge upsurge in recent years. More complex analysis to understand the soccer players’ or teams’ performances during matches is required. The objective of this study was to prove the usefulness of the expected goals on target (xGOT) metric, as a good indicator of a soccer team’s performance in professional Spanish football leagues, both in the women’s and men’s categories. Method: The data for the Spanish teams were collected from the statistical website Football Reference. The 2023/24 season was analyzed for Spanish leagues, both in the women’s and men’s categories (LigaF and LaLiga, respectively). For all teams, the following variables were calculated: goals, possession value (PV), expected goals (xG) and xGOT. All data obtained for each variable were normalized by match (90 min). A descriptive and correlational statistical analysis was carried out. Results: In the men’s league, this study found a high correlation between goals per match and xGOT (R2 = 0.9248) while in the women’s league, there was a high correlation between goals per match (R2 = 0.9820) and xG and between goals per match and xGOT (R2 = 0.9574). Conclusions: In the LaLiga, the xGOT was the best metric that represented the match result while in the LigaF, the xG and the xGOT were the best metrics that represented the match score.
Dynamics of Cognitive Impairment in MCI Patients over a Three-Year Period: The Informative Role of Blood Biomarkers, Neuroimaging, and Genetic Factors
Authors: Morozova Irina , Zorkina Yana , Berdalin Alexander , Ikonnikova Anna , Emelyanova Marina , Fedoseeva Elena , Antonova Olga , Gryadunov Dmitry , Andryushchenko Alisa , Ushakova Valeriya , Abramova Olga , Zeltser Angelina , Kurmishev Marat , Savilov Victor , Osipova Natalia , Preobrazhenskaya Irina , Kostyuk Georgy , Morozova Anna
Published: August 2024

Given the high growth rates of cognitive decline among the elderly population and the lack of effective etiological treatments, early diagnosis of cognitive impairment progression is an imperative task for modern science and medicine. It is of particular interest to identify predictors of an unfavorable subsequent course of cognitive disorders, specifically, rapid progression. Our study assessed the informative role of various risk factors on the dynamics of cognitive impairment among mild cognitive impairment (MCI) patients. The study included patients with MCI (N = 338) who underwent neuropsychological assessment, magnetic resonance imaging (MRI) examination, blood sampling for general and biochemical analysis, APOE genotyping, and polygenic risk score (PRS) evaluation. The APOE ε4/ε4 genotype was found to be associated with a diminished overall cognitive scores initial assessment and negative cognitive dynamics. No associations were found between cognitive changes and the PRS. The progression of cognitive impairment was associated with the width of the third ventricle and hematological parameters, specifically, hematocrit and erythrocyte levels. The absence of significant associations between the dynamics of cognitive decline and PRS over three years can be attributed to the provided suitable medical care for the prevention of cognitive impairment. Adding other risk factors and their inclusion in panels assessing the risk of progression of cognitive impairment should be considered.
Assessing the Effectiveness of Selective RET Inhibitors in RET-Positive Cancers through Fluorodeoxyglucose Uptake Analysis
Authors: Kairemo Kalevi , Macapinlac Homer A. , Gouda Mohammed , Subbiah Vivek
Published: August 2024

Selective RET inhibitors, such as selpercatinib and pralsetinib, have revolutionized the treatment of cancers with RET gene alterations. These inhibitors have shown remarkable clinical efficacy, particularly in RET-driven lung cancer, medullary thyroid cancer, and other solid tumors driven by RET gene fusions. The assessment of treatment response in oncology has been greatly enhanced by Fluorodeoxyglucose Positron Emission Tomography (FDG-PET), a valuable tool that measures tumor metabolism and provides early indicators of treatment effectiveness. This work explores the effectiveness of selective RET inhibitors in targeting RET-positive cancers and investigates the utility of FDG-PET in assessing treatment response. The paper includes insightful case studies that highlight the successful application of RET inhibitors in the treatment of RET-positive cancers. The findings suggest that FDG-PET has the potential to serve as a non-invasive biomarker for monitoring treatment response in patients with RET-positive cancers. However, further research is required to establish standardized criteria for interpreting FDG-PET scans in the context of selective RET inhibitors and to uncover the broader applications of FDG-PET in precision oncology.
Ultrasound Assessment of Sarcopenia in Alcoholic Liver Disease
Authors: Enciu Vlad-Teodor , Ologeanu Priscila Madalina , Fierbinteanu-Braticevici Carmen
Published: August 2024

Malnutrition frequently affects patients with alcoholic liver disease (ALD), with important impacts on disease prognosis. Sarcopenia, the clinical phenotype of malnutrition characterized by skeletal muscle loss, is the major component responsible for adverse events in this population. The aim of this study is to assess the use of ultrasound (US) skeletal muscle performance in stratifying ALD disease severity. We recruited 43 patients with ALD and divided them into two groups: alcoholic hepatitis (AH) and alcoholic cirrhosis (AC). We evaluated disease-specific clinical and biological parameters and their relation to US Rectus Femoris muscle (RFM) measurements, including RFM thickness, stiffness (RFMS) and echogenicity (RFE). A thirty-seconds chairs stand test (30sCST) was used as the sarcopenia surrogate test. RMF thickness correlated with platelet count and serum albumin (p < 0.001). Both RFM and RFMS correlated with disease severity (p < 0.001) and 30sCST (p < 0.001, p = 0.002). Patients with AH had more severe US muscle abnormalities compared to AC (RFMS 1.78 m/s vs. 1.35 m/s, p = 0.001) and the highest prevalence of RFE (χ2 = 8.652, p = 0.003). Rectus Femoris US assessment could represent a reliable tool in the diagnosis and severity stratification of ALD-induced sarcopenia.
Effects of Virtual Rehabilitation Training on Post-Stroke Executive and Praxis Skills and Depression Symptoms: A Quasi-Randomised Clinical Trial
Authors: De Luca Rosaria , Gangemi Antonio , Maggio Maria Grazia , Bonanno Mirjam , Calderone Andrea , Mazzurco Masi Vincenza Maura , Rifici Carmela , Cappadona Irene , Pagano Maria , Cardile Davide , Giuffrida Giulia Maria , Ielo Augusto , Quartarone Angelo , Calabrò Rocco Salvatore , Corallo Francesco
Published: August 2024

Introduction: Apraxia is a neurological disorder that is common after a stroke and impairs the planning and execution of movements. In the rehabilitation field, virtual reality (VR) presents new opportunities and offers advantages to both rehabilitation teams and individuals with neurological conditions. Indeed, VR can stimulate and improve cognitive reserve and abilities, including executive function, and enhance the patient’s emotional status. Aim: The objective of this research is to determine the effectiveness of VR in improving praxis skills and behavioural functioning in individuals with severe stroke. Methods: A total of 20 stroke patients were enrolled from February 2022 to March 2023 and divided by the order of their recruitment into two groups: the experimental group (EG: n = 10) received training to improve their praxis skills using VR whereas the control one (CG: n = 10) received the same amount of standard training. All patients underwent an evaluation using a psychometric battery that consisted of the Hamilton Rating Scale for Depression (HRS-D), Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB), Spinnler and Tognoni test, and De Renzi and Faglioni test. Valuations were performed before rehabilitation (T0) and after its completion (T1). Results: Both groups demonstrated significant improvements post-intervention. The EG showed a greater enhancement in their MMSE scores (p = 0.002), and reductions in both ideomotor and constructive apraxia (p = 0.002 for both), compared to the CG. The VR-based training also resulted in significant improvements in their depression symptoms (HRSD scores improved, p = 0.012 in EG vs. p = 0.021 in CG). Conclusions: This pilot study suggests that VR could help reduce cognitive, constructive apraxia and ideomotor apraxia symptoms caused by stroke injury.
A DDoS Tracking Scheme Utilizing Adaptive Beam Search with Unmanned Aerial Vehicles in Smart Grid
Authors: Guo Wei , Zhang Zhi , Chang Liyuan , Song Yue , Yin Liuguo
Published: August 2024

As IoT technology advances, the smart grid (SG) has become crucial to industrial infrastructure. However, SG faces security challenges, particularly from distributed denial of service (DDoS) attacks, due to inadequate security mechanisms for IoT devices. Moreover, the extensive deployment of SG exposes communication links to attacks, potentially disrupting communications and power supply. Link flooding attacks (LFAs) targeting congested backbone links have increasingly become a focal point of DDoS attacks. To address LFAs, we propose integrating unmanned aerial vehicles (UAVs) into the Smart Grid (SG) to offer a three-dimensional defense perspective. This strategy includes enhancing the speed and accuracy of attack path tracking as well as alleviating communication congestion. Therefore, our new DDoS tracking scheme leverages UAV mobility and employs beam search with adaptive beam width to reconstruct attack paths and pinpoint attack sources. This scheme features a threshold iterative update mechanism that refines the threshold each round based on prior results, improving attack path reconstruction accuracy. An adaptive beam width method evaluates the number of abnormal nodes based on the current threshold, enabling precise tracking of multiple attack paths and enhancing scheme automation. Additionally, our path-checking and merging method optimizes path reconstruction by merging overlapping paths and excluding previously searched nodes, thus avoiding redundant searches and infinite loops. Simulation results on the Keysight Ixia platform demonstrate a 98.89% attack path coverage with a minimal error tracking rate of 2.05%. Furthermore, simulations on the NS-3 platform show that drone integration not only bolsters security but also significantly enhances network performance, with communication effectiveness improving by 88.05% and recovering to 82.70% of normal levels under attack conditions.
Does Industrial Structure Upgrading Promote China’s Outward Foreign Direct Investment (OFDI) in ASEAN Countries? Evidence from Provincial Panels
Authors: Li Ai , Zhao Jinjing , Su Zhenqing , Su Miao
Published: August 2024

Numerous studies have explored the impact of Outward Foreign Direct Investment (OFDI) on upgrading industrial structures in home countries. However, a notable gap exists in the literature regarding the reverse relationship. Based on the cross-border greenfield investment data of Chinese provinces in Association of Southeast Asian Nations (ASEAN) countries from 2003 to 2021, this study employed the Ordinary Least Squares (OLS) model to evaluate the impact of industrial upgrading in each province on OFDI to address this gap. The findings suggest that China’s industrial structure upgrading significantly promotes OFDI toward ASEAN countries, though the effect varies by region within China and by the income levels of host countries. Regionally, industrial upgrading in eastern China notably stimulates OFDI growth, while the effect is not significant in the central and western regions, reflecting inconsistent evolution of industrial structures in various regions. Regarding host country income levels, the promotion effect of industrial structure upgrading on OFDI is influenced by the economic development level of the host country. Furthermore, we find that R&D intensity acts as a moderator that links industrial structural upgrading to OFDI responses. These findings withstand robustness checks, including tests for endogeneity. Ultimately, this study provides policy insights for strengthening the virtuous cycle between industrial upgrading and OFDI.
Examining the Effects of Peer-Led Team Learning as a Support for Community College Transfer Students’ STEM Achievement
Authors: Meador Audrey , Lockwood Pamela , Subburaj Vinitha , Subburaj Anitha
Published: August 2024

Peer-led Team Learning (PLTL) is a model of instruction and learning that has been used to address low success rates in various science, technology, engineering, and mathematics (STEM) courses and other fields in higher education. (1) While research conveying the efficacy of this model of instruction remains mixed, this project sought to add to the body of knowledge communicating the benefits of PLTL for STEM achievement. This study examined the experiences of STEM community college transfer students’ engagement in PLTL within their major course of study when a suite of supports was provided. (2) Specifically, study participants were enrolled in degree programs at a four-year rural, regional university in the engineering, computer science, and mathematics (ECSM) fields and were provided social, financial, and academic assistance. Qualitative analysis of the data revealed that with a PLTL component, community college transfer students were more likely to participate, engage, and perform better in coursework given the additional supports. (3) Study participants indicated the community of learners created through PLTL was a primary motivator for continued engagement and progress towards ECSM degree attainment. (4) Implications for practice extend to engagement and retention efforts of STEM students from the community college population
Transient Synchronization Stability Analysis and Enhancement Control for Power Self-Synchronization Control Converters
Authors: Shi Huabo , Shi Peng , Zhou Bo , Wang Xi , Zeng Xueyang , Ma Junpeng
Published: August 2024

Conventional grid-forming control often destabilizes voltage source converters (VSCs) in stiff grids, and transient synchronization instability will occur in the grid fault condition. Therefore, power self-synchronization control (PSSC) is first introduced for enhancing the small-signal stability of grid-forming control in the case of a short circuit ratio ranging from 1 to infinity. Meanwhile, the transient synchronization instability for the grid-forming converter with PSSC in the grid fault condition is analyzed by the phase portrait, and a transient stability enhancement control (TSEC) scheme is combined with a PSSC-based VSC, which can efficiently eliminate the risk of losing synchronization in the arbitrary SCR. Finally, experimental results are provided to confirm the theoretical analysis.
Fault Localization in Multi-Terminal DC Distribution Networks Based on PSO Algorithm
Authors: Wang Mingyuan , Xu Yan
Published: August 2024

Flexible DC power grids are widely recognized as an important component of building smart grids. Compared with traditional AC power grids, flexible DC power grids have strong technical advantages in islanding power supplies, distributed power supplies, regional power supplies, and AC system interconnection. In multi-terminal flexible DC power grids containing renewable energy sources such as solar and wind power, due to the instability and intermittency of renewable energy, it is usually necessary to add energy storage units to pre-regulate the power of the multi-terminal flexible DC power grid in islanded operation. Aiming at the important problem of large current impact and serious consequences when the flexible DC distribution network fails, a combined location method combining an improved impedance method (series current-limiting reactors at both ends of the line to obtain a more accurate current differential value) and a particle swarm optimization algorithm is proposed. Initially, by establishing the enhanced impedance model, the differential variables under the conditions of inter-electrode short-circuit and single-pole grounding fault can be obtained. Then tailor-made fitness functions are designed for these two models to optimize parameter identification. Subsequently, the iterative parameters of the particle swarm optimization algorithm are fine-tuned, giving it dynamic sociality and self-learning ability in the iterative process, which significantly improves the convergence speed and successfully avoids local optimization. Finally, various fault types in a six-terminal DC distribution network are simulated and analyzed by MATLAB, and the results show that this method has good accuracy and robustness. This research provides strong theoretical and methodological support for improving the safety and reliability of DC distribution systems.
Diesel Engine Turbocharger Monitoring by Processing Accelerometric Signals through Empirical Mode Decomposition and Independent Component Analysis
Authors: Chiavola Ornella , Palmieri Fulvio , Bocchetta Gabriele , Fiori Giorgia , Scorza Andrea
Published: August 2024

In this study, a method for the monitoring of internal combustion engine operation by vibration signals is proposed. The work falls within the context of the increasingly stringent standards relating to the environmental impact of engines and the development of monitoring and control techniques to ensure increased engine performance as well as fuel saving and reduction of pollutant emissions. Experimentation was performed on a turbocharged light-duty compression ignition direct-injection engine. Two monoaxial accelerometers were installed on the engine compressor case, the speed of which has been demonstrated to be closely related to the engine operation. Vibration measurements of the engine compressor case have been processed by combining the Empirical Mode Decomposition technique with Independent Component Analysis and Short Time Fourier Transform to indirectly estimate the turbocharger speed. The obtained traces have been compared to the direct turbocharger velocity measures during the stationary running of the engine (speed and load conditions varied in the complete engine’s range of operation). The results point out the potentiality of the methodology in algorithms devoted to identifying modifications of the combustion development regarding regular operation via indirect turbocharger speed monitoring.
Reflux Power Optimization of a Dual-Active Hybrid Full-Bridge Converter Based on Active Disturbance Rejection Control
Authors: Luo Shuang , He Guofeng , Hou Ning
Published: August 2024

The dual-active hybrid full-bridge (H-FDAB) DC–DC converter has great potential in medium-voltage high-power photovoltaic power station applications by introducing a three-level bridge arm to increase the output voltage range. However, its mathematical model and optimum modulation schemes have not been fully explored. Under the traditional PI control, the H-FDAB DC–DC converter will produce significant reflux power, which will lead to a decrease in converter efficiency and output voltage fluctuation. On this basis, this paper proposes a reflux power optimization strategy for an H-FDAB DC-DC converter based on active disturbance rejection control (ADRC). Firstly, the structure and power characteristics of the H-FDAB DC–DC converter are analyzed, and the relationship among the reflux power, the transmission power, and the phase shift angle is derived. Secondly, to reduce the complexity of the control calculation, upon the foundation of dual phase-shifting modulation, the Karush–Kuhn–Tucker (KKT) condition is used to solve for the phase shift angle that corresponds to the minimum reflux power. Simultaneously, we develop an ADRC loop utilizing an extended state observer (ESO) for the real-time estimation of system states. We also consider the sudden changes in input voltage, load switching, and transmission power fluctuations caused by reflux power optimization strategies as system disturbances and compensate for them accordingly. Finally, the experiments conclusively validate the designed control strategy’s correctness and feasibility.
Whale Optimization Algorithm BP Neural Network with Chaotic Mapping Improving for SOC Estimation of LMFP Battery
Authors: Ouyang Jian , Lin Hao , Hong Ye
Published: August 2024

The state of charge (SOC) is a core parameter in the battery management system for LMFP batteries. Accurate SOC estimation is crucial for ensuring the safety and reliability of energy storage applications and new energy vehicles. In order to achieve better SOC estimation accuracy, this article proposes an adaptive whale optimization algorithm (WOA) with chaotic mapping to improve the BP neural network (BPNN) model. The SOC estimation accuracy of the BPNN model was improved by utilizing WOA to find the optimal target weight values and thresholds. Comparative simulation experiments (including constant current and working condition discharge experiments) were conducted in Matlab/Simulink R2018a to verify the proposed algorithm and the other four algorithms. The experimental results show that the proposed algorithm had higher SOC estimation accuracy than the other four algorithms, and its prediction errors were less than 1%. This indicates that the proposed SOC estimation method has better prediction accuracy and stability, and has certain theoretical research significance.
A Review on Application of Pin-Fins in Enhancing Heat Transfer
Authors: Yang Tao , Zhang Xiaoming , Chang Zhenyuan , Xu Ran , Ma Jiaojiao , Xu Liang , Xi Lei
Published: August 2024

The pin-fin is one of the main technologies in enhancing heat transfer. The accelerated flow and vortex structures are produced, which can disrupt the development of the flow boundary layer. The configuration of the pin-fin is obvious for heat transfer and flow characteristics, including its shape, size, and arrangement in the cooling channel. This work provides a detailed introduction to the application of pin-fins in enhancing heat transfer and reducing flow resistance, including the conventional shapes, improved shapes based on circular pin-fins and irregular shapes. At the same time, the influence of the diameter, height and density of pin-fins on heat transfer and flow performance is studied, and the influence mechanism is analyzed from the perspective of boundary layers. In addition, some applications that combine pin-fins with other cooling methods to further improve performance are analyzed. In terms of the optimization technology, the structure optimization for pin-fin shape and the layout optimization for pin-fin array are summarized. Therefore, this review provides a wide range of literature for the design of internal cooling channel pin-fins.
Experimental Research and Improved Neural Network Optimization Based on the Ocean Thermal Energy Conversion Experimental Platform
Authors: Yu Yanni , Tian Mingqian , Liu Yanjun , Lu Beichen , Chen Yun
Published: August 2024

With the progress of research on ocean thermal energy conversion, the stabI have checked and revised all. le operation of ocean thermal energy conversion experiments has become a problem that cannot be ignored. The control foundation for stable operation is the accurate prediction of operational performance. In order to achieve accurate prediction and optimization of the performance of the ocean thermal energy conversion experimental platform, this article analyzes the experimental parameters of the turbine based on the basic experimental data obtained from the 50 kW OTEC experimental platform. Through the selection and training of experimental data, a GA-BP-OTE (GBO) model that can automatically select the number of hidden layer nodes was established using seven input parameters. Bayesian optimization was used to complete the optimization of hyperparameters, greatly reducing the training time of the surrogate model. Analyzing the prediction results of the GBO model, it is concluded that the GBO model has better prediction accuracy and has a very low prediction error in the prediction of small temperature changes in ocean thermal energy, proving the progressiveness of the model proposed in this article. The dual-objective optimization problem of turbine grid-connected power and isentropic efficiency is solved. The results show that the change in isentropic efficiency of the permeable device is affected by the combined influence of the seven parameters selected in this study, with the mass flow rate of the working fluid having the greatest impact. The MAPE of the GBO model turbine grid-connected power is 0.24547%, the MAPE of the turbine isentropic efficiency is 0.04%, and the MAPE of the turbine speed is 0.33%. The Pareto-optimal solution for the turbine grid-connected power is 40.1792 kW, with an isentropic efficiency of 0.837439.
Design and Implementation of Bridgeless Power Factor Corrector with Low Static Losses
Authors: Chivenkov Alexander , Aleshin Dmitriy , Trofimov Ivan , Shalukho Andrey
Published: August 2024

Research and development of power factor corrector (PFC) for AC/DC converters of single-phase AC power supply network are discussed within this article. Two-channel bridgeless PFC is proposed in this paper. The proposed converter allows us to lower current DC component generation in the power network and to reduce static and dynamic losses of semiconductor devices. The suggested solution characteristic features are the absence of a diode bridge while using two identical converters operating in different power network voltage half periods. Due to cumulative chokes in each converter, the function setting the consumption current sinusoidal form is realized with the ability of wide-range output voltage regulation. A number of Simulink-models have been developed in order to study operating modes and to test control algorithms of the proposed bridgeless PFC. The input current harmonic content, efficiency coefficient, passive elements’ electrical parameters, and output voltage pulsation coefficient of the proposed bridgeless PFC were researched by Simulink-models. The results obtained show the efficiency of the proposed solutions regarding PFC. The THD value does not exceed 1.3% in steady state mode and is not over 4% during the voltage stabilization process; the minimal value of the output voltage pulsation coefficient is 3.1%. The suggested solutions can be applied in accumulator batteries’ charging sets and DC motors’ reduced-current start.
Optimal Reconfiguration of Bipolar DC Networks Using Differential Evolution
Authors: Peres Wesley , Poubel Raphael Paulo Braga
Published: August 2024

The search for more efficient power grids has led to the concept of microgrids, based on the integration of new-generation technologies and energy storage systems. These devices inherently operate in DC, making DC microgrids a potential solution for improving power system operation. In particular, bipolar DC microgrids offer more flexibility due to their two voltage levels. However, more complex tools, such as optimal power flow (OPF) analysis, are required to analyze these systems. In line with these requirements, this paper proposes an OPF for bipolar DC microgrid reconfiguration aimed at minimizing power losses, considering dispersed generation (DG) and asymmetrical loads. This is a mixed-integer nonlinear optimization problem in which integer variables are associated with the switch statuses, and continuous variables are associated with the nodal voltages in each pole. The problem is formulated based on current injections and is solved by a hybridization of the differential evolution algorithm (to handle the integer variables) and the interior point method-based OPF (to minimize power losses). The results show a reduction in power losses of approximately 48.22% (33-bus microgrid without DG), 2.87% (33-bus microgrid with DG), 50.90% (69-bus microgrid without DG), and 50.50% (69-bus microgrid with DG) compared to the base case.
Distribution System State Estimation Based on Power Flow-Guided GraphSAGE
Authors: Zhai Baitong , Yang Dongsheng , Zhou Bowen , Li Guangdi
Published: August 2024

Acquiring real-time status information of the distribution system forms the foundation for optimizing the management of power system operations. However, missing measurements, bad data, and inaccurate system models present a formidable challenge for distribution system state estimation (DSSE) in practical applications. This paper proposes a physics-informed graphical learning state estimation approach, to address these limitations by integrating power flow equations and GraphSAGE. The generalization ability of GraphSAGE for unknown nodes is used to perform inductive learning of measurement information. For unseen measurement points in the training set, the simulation proves that the proposed approach can still satisfactorily predict the state quantity. The training process is guided by power flow equations to ensure it has physical significance. Additionally, the possibility of applying the proposed approach to an actual distribution area is explored. Equivalent preprocessing of the three-phase voltage measurement data of the actual distribution area is conducted to improve the estimation accuracy of the transformer measurement points and simplify the computation required for state estimation.
Decision-Making Model Supporting Eco-Innovation in Energy Production Based on Quality, Cost and Life Cycle Assessment (LCA)
Authors: Siwiec Dominika , Pacana Andrzej
Published: August 2024

Currently, the development of renewable energy products (RES) encourages the search for innovative solutions that take into account key criteria from the point of view of their sustainable development. Despite efforts in this area, there is a lack of approaches and tools to support this process. Therefore, the aim of the research was to develop a decision-making model supporting eco-innovation in products based on the key criteria of sustainable development: quality (customer satisfaction with use), environmental impact in the life cycle (LCA), and the cost of investment incurred in the product development. The functioning of the model was based on the following factors: (i) obtaining the voice of customers (VoC) and processing it into product criteria as part of the development of alternative production solutions (prototypes), (ii) prospective quality assessment and subsequent life cycle assessment of prototypes, (iii) cost analysis taking into account both quality and environmental criteria, (iv) interpretation of results and search for eco-innovative product solutions. Development decision-making is additionally supported by techniques implemented in the model, e.g., the CRITIC method, the LCA method with Ecoinvent database in OpenLCA, the CEA method, and the morphology method. The model was illustrated and tested for photovoltaic (PV) panels, after which a global sensitivity analysis was performed in Statistica. The test results showed that the main factor that influenced the PV development decisions was the investment cost, followed by quality (customer satisfaction) and then environmental impact in LCA.
α-Crystalline Domains and Intrinsically Disordered Regions Can Work in Parallel to Induce Accumulation of MBD6 at Chromocenters in Arabidopsis thaliana
Authors: Boone Brandon A. , Mendoza Cristy P. , Behrendt Noah J. , Jacobsen Steven E.
Published: August 2024

Proteins are localized and concentrated at cellular and genomic locations for specific and efficient functions. Efforts to understand protein accumulation in eukaryotic organisms have primarily focused on multivalent interactions between intrinsically disordered regions (IDRs) as mediators of protein condensation. We previously showed that α-crystalline domain (ACD) proteins 15 (ACD15) and 21 (ACD21) were required for multimerization and the accumulation of gene-silencing methyl-CpG-binding domain protein 6 (MBD6) at chromocenters in Arabidopsis thaliana. Here, we demonstrate that ACDs and IDRs can act as parallel mechanisms, facilitating higher-order MBD6 assemblies. Using human IDRs known to be important for protein accumulation, we replicated and enhanced the accumulation of MBD6 at chromocenters. In addition, IDRs fused to MBD6 could substitute for ACD function and partially reconstitute the MBD6 gene-silencing function. However, the accumulation of MBD6 by IDRs still required ACD15 and ACD21 for full effect. These results establish that ACD-mediated protein accumulation is a mechanism that can function similarly to and together with IDR-mediated mechanisms.