bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Role of Connective Tissue Growth Factor in the Regulation of the Epithelial Phenotype
Authors: Gogoi Radhika P. , Galoforo Sandra , Fox Alexandra , Morris Colton , Ramos Harry , Gogoi Vir K. , Chehade Hussein , Adzibolosu Nicholas K. , Shi Chenjun , Zhang Jitao , Tedja Roslyn , Morris Robert , Alvero Ayesha B. , Mor Gil
Published: October 2023

Background: Epithelial–mesenchymal transition (EMT) is a biological process where epithelial cells lose their adhesive properties and gain invasive, metastatic, and mesenchymal properties. Maintaining the balance between the epithelial and mesenchymal stage is essential for tissue homeostasis. Many of the genes promoting mesenchymal transformation have been identified; however, our understanding of the genes responsible for maintaining the epithelial phenotype is limited. Our objective was to identify the genes responsible for maintaining the epithelial phenotype and inhibiting EMT. Methods: RNA seq was performed using an vitro model of EMT. CTGF expression was determined via qPCR and Western blot analysis. The knockout of CTGF was completed using the CTGF sgRNA CRISPR/CAS9. The tumorigenic potential was determined using NCG mice. Results: The knockout of CTGF in epithelial ovarian cancer cells leads to the acquisition of functional characteristics associated with the mesenchymal phenotype such as anoikis resistance, cytoskeleton remodeling, increased cell stiffness, and the acquisition of invasion and tumorigenic capacity. Conclusions: We identified CTGF is an important regulator of the epithelial phenotype, and its loss is associated with the early cellular modifications required for EMT. We describe a novel role for CTGF, regulating cytoskeleton and the extracellular matrix interactions necessary for the conservation of epithelial structure and function. These findings provide a new window into understanding the early stages of mesenchymal transformation.
The Evolving Pathways of the Efficacy of and Resistance to CDK4/6 Inhibitors in Breast Cancer
Authors: Gomes Inês , Abreu Catarina , Costa Luis , Casimiro Sandra
Published: October 2023

The approval of cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) in combination with endocrine therapy (ET) has remarkably improved the survival outcomes of patients with advanced hormone receptor-positive (HR+) breast cancer (BC), becoming the new standard of care treatment in these patients. Despite the efficacy of this therapeutic combination, intrinsic and acquired resistance inevitably occurs and represents a major clinical challenge. Several mechanisms associated with resistance to CDK4/6i have been identified, including both cell cycle-related and cell cycle-nonspecific mechanisms. This review discusses new insights underlying the mechanisms of action of CDK4/6i, which are more far-reaching than initially thought, and the currently available evidence of the mechanisms of resistance to CDK4/6i in BC. Finally, it highlights possible treatment strategies to improve CDK4/6i efficacy, summarizing the most relevant clinical data on novel combination therapies involving CDK4/6i.
Investigating Carvedilol’s Repurposing for the Treatment of Non-Small Cell Lung Cancer via Aldehyde Dehydrogenase Activity Modulation in the Presence of β-Adrenergic Agonists
Authors: Ikhmais Balqis A. , Hammad Alaa M. , Abusara Osama H. , Hamadneh Lama , Abumansour Hamza , Abdallah Qasem M. , Ibrahim Ali I. M. , Elsalem Lina , Awad Mariam , Alshehada Rahaf
Published: October 2023

Repurposing existing drugs appears to be a potential solution for addressing the challenges in the treatment of non-small cell lung cancer (NSCLC). β-adrenoceptor antagonist drugs (β-blockers) have tumor-inhibiting effects, making them promising candidates for potential NSCLC treatment. This study investigates the anticancer potential of a subset of β-blockers in NSCLC cell lines; A549 and H1299. Additionally, it investigates the underlying mechanism behind β-blockers’ anticancer effect by influencing a potential novel target named aldehyde dehydrogenase (ALDH). The MTT assay assessed β-blockers’ cytotoxicity on both cell lines, while Western blot and NADH fluorescence assays evaluated their influence on ALDH protein expression and activity. Carvedilol (CAR) was the most effective blocker in reducing cell survival of A549 and H1299 with IC50 of 18 µM and 13.7 µM, respectively. Significantly, CAR led to a 50% reduction in ALDH expression and 80% decrease in ALDH activity in A549 cells, especially when combined with β-agonists, in comparison to the control. This effect might be attributed to β-agonist blockade or an alternative pathway. This novel finding adds to our understanding of CAR’s multifaceted anticancer properties, implying that combining CAR with β-agonists could be a useful strategy for lung cancer treatment.
Lactic Acid Bacteria-Derived Exopolysaccharides Mitigate the Oxidative Response via the NRF2-KEAP1 Pathway in PC12 Cells
Authors: Şirin Seda
Published: October 2023

Parabiotics, including L-EPSs, have been administered to patients with neurodegenerative disorders. However, the antioxidant properties of L-EPSs against H2O2-induced oxidative stress in PC12 cells have not been studied. Herein, we aimed to investigate the antioxidant properties of the L-EPSs, their plausible targets, and their mechanism of action. We first determined the amount of L-EPSs in Lactobacillus delbrueckii ssp. bulgaricus B3 and Lactiplantibacillus plantarum GD2 using spectrophotometry. Afterwards, we studied their effects on TDH, TOS/TAS, antioxidant enzyme activities, and intracellular ROS level. Finally, we used qRT-PCR and ELISA to determine the effects of L-EPSs on the NRF2-KEAP1 pathway. According to our results, the L-EPS groups exhibited significantly higher total thiol activity, native thiol activity, disulfide activity, TAS levels, antioxidant enzyme levels, and gene expression levels (GCLC, HO-1, NRF2, and NQO1) than did the H2O2 group. Additionally, the L-EPS groups caused significant reductions in TOS levels and KEAP1 gene expression levels compared with those in the H2O2 group. Our results indicate that H2O2-induced oxidative stress was modified by L-EPSs. Thus, we revealed that L-EPSs, which regulate H2O2-induced oxidative stress, could have applications in the field of neurochemistry.
Computational “Accompaniment” of the Introduction of New Mathematical Concepts
Authors: Lavrenov Andrey , Tolkacheva Elena , Pozdniakov Sergei
Published: October 2023

The computational capabilities of computer tools expand the student’s search capabilities. Conducting computational experiments in the classroom is no longer an organizational problem. This raises the “black box” problem, when the student perceives the computational module as a magician’s box and loses conceptual control over the computational process. This article analyses the use of various computer tools, both existing and specially created for “key” computational experiments, that aim at revealing the essential aspects of the introduced concepts using specific examples. This article deals with a number of topics of algebra and calculus that are transitional from school to university, and it shows how computational experiments in the form of a “transparent” box can be used.
A Randomized, Double-Blind, Placebo-Controlled Pilot Study to Evaluate the Efficacy and Safety of Latanoprost for Eyelash Growth in Aesthetic Medicine
Authors: Espinoza-Silva Janette Ivone , Macias-Nevarez Ernesto , Scheckhuber Christian Quintus , Tienda-Vázquez Mario Adrián
Published: October 2023

Eyelashes, in addition to fulfilling eye-protective functions, generate an aesthetic impact. Latanoprost is a prostaglandin analog, commonly used for the treatment of glaucoma and intraocular hypertension. The side effect reported most often is the stimulation of eyelash growth. The aim of this study was to evaluate the efficacy and safety of latanoprost in inducing eyelash growth and darkening. Thirty healthy volunteers were recruited in a 3-month, randomized, double-blind, placebo-controlled pilot study. A transparent eyelash mascara was used as a vehicle. The placebo group (n = 15) received only the vehicle, and the latanoprost group (n = 15) received the vehicle + 0.005% latanoprost. The participants were asked to apply the latanoprost topically to the eyelashes while avoiding entry into the eye, daily at night. The latanoprost group showed a significant increase in eyelash length and color change, while the placebo group maintained eyelash length and color throughout the study. The intraocular pressures of all the participants were maintained in normal ranges (10–20 mmHg). Topical application of both the placebo and the latanoprost medications was well tolerated; none of the participants withdrew, generated side effects, or developed any ophthalmic pathology. In conclusion, latanoprost is effective and safe to stimulate the growth of eyelashes.
Effect of Phenolic Compounds Extracted from Turmeric (Curcuma longa L.) and Ginger (Zingiber officinale) on Cutaneous Wound Healing in Wistar Rats
Authors: Bouchama Chaymae , Zinedine Abdellah , Rocha João Miguel , Chadli Noureddine , El Ghadraoui Lahsen , Chabir Rachida , Raoui Sidi Mohammed , Errachidi Faouzi
Published: October 2023

Turmeric and ginger, widely used rhizomes in culinary arts, have several beneficial biological activities, such as hypoglycemic, hepato-protective, antimicrobial, and antioxidant properties. This work investigated the effects of three phenolic extracts isolated from turmeric and ginger rhizomes on anti-inflammatory and healing properties using the solid–liquid extraction method. Wistar rats were used as a biological model. The anti-inflammatory activity was evaluated on induced edema in the rat’s hind paw using carrageenan (1%). Paw volume was measured at 0 min, 45 min, 3 h, and 5 h. Treatment with turmeric and ginger extracts, administered at a dose of 100 mg/kg, revealed a reduction in edema volume by 98.8%, 94.8%, and 98.3% using an aqueous extract of turmeric, ethanolic extract of turmeric, and methanolic extract of ginger, respectively. The healing activity parameters of induced burns on the rat’s dorsal region in nine groups (7 rats each) were monitored daily throughout the experiment’s duration. Results showed that the application of creams composed of petroleum jelly dispersing turmeric and ginger extracts to wounds at a dose of 100 mg/kg g induced complete healing after 19 days while the negative control was only 60% cured. On day 14, the aqueous, ethanolic, and methanolic turmeric extracts nearly resulted in complete tissue repair by 95.26%, 98.34%, and 87.39%, respectively. According to the chromatographic analysis (Sephadex G50 column), there is a variation in the molecular weight distribution of phenolic compounds (polymers, oligomers, and monomers) in the three studied extracts, which has a differential effect on the anti-inflammatory and wound healing activities of the extracts.
Effectiveness of Immune Checkpoint Inhibitor with Anti-PD-1 Monotherapy or in Combination with Ipilimumab in Younger versus Older Adults with Advanced Melanoma
Authors: Woo Taylor E. , Stukalin Igor , Ding Philip Q. , Goutam Siddhartha , Sander Michael , Ewanchuk Benjamin , Cheung Winson Y. , Heng Daniel Y. C. , Cheng Tina
Published: October 2023

Background: The majority of melanoma is diagnosed in individuals between 55 and 84 years old. Current data varied in reporting differences in survival outcomes amongst different age groups. Methods: A retrospective, multi-center, provincial cohort database was used to investigate the relationship between age (<65 or ≥65 years old) and overall survival. Patients must have had histologically confirmed locally advanced or metastatic melanoma and had to have received at least one cycle of immunotherapy (single agent nivolumab, pembrolizumab, or combination ipilimumab plus nivolumab). Results: From August 2013 to May 2020, we identified 497 patients (median age = 64 [range 12–96 years]; 65.2% men; 36.4% with a BRAF mutation (V600E and V600K)). Of these, 260 were < 65 years old, and 237 were ≥65 years old. A total of 39.1% of the patients in the younger cohort received combination ICI compared with 10.2% in the older cohort, and the difference was statistically significant. Median survival amongst individuals aged ≥65 years old was shorter compared to individuals <65 years old, with a median overall survival of 17.1 (95% CI 12.3–22.9 months) months and 22.2 months (95% CI 18.7–33.8 months), respectively (p = 0.04), at a median follow-up of 34.4 months (range: 1.84–81.4 months). The survival difference was present in the cutaneous melanoma cohort where median OS was 18.2 months (95% CI 12.3–30.4 months) in patients ≥65 years old and 23.8 months (95% CI 19.2–48.2 months) in patients <65 years old, p = 0.04. There were no significant differences by age in the non-cutaneous melanoma cohort. A combination of nivolumab plus ipilimumab was associated with an improved overall survival hazard ratio of 0.48 (95% CI 0.36–0.65) as compared to anti-PD-1 monotherapy alone (p < 0.001). In the cutaneous cohort treated with anti-PD-1 monotherapy (n = 306), no significant differences were seen with median OS at 16.1 months (95% CI 11.4–25.7 months) in patients ≥65 years old and 17.1 months (95% CI 12.0–22.2 months) in patients <65 years old (p = 0.84). Tumor response to anti-PD-1 was higher in the older patients compared with the response in younger patients with cutaneous melanoma. Conclusions: Older melanoma patients have similar survival compared with younger patients after receiving the same treatment with anti-PD-1 monotherapy. The superior survival observed in the younger patients is possibly related to the higher utilization of combination ICI. Tumor response to immunotherapy is superior in older patients with cutaneous melanoma; however, younger patients may improve their survival by using combination ICI.
Unraveling the Mysteries of Perineural Invasion in Benign and Malignant Conditions
Authors: Bahmad Hisham F. , Gogola Samantha , Rejzer Michael , Stoyanov Kalin , Gomez Aaron S. , Valencia Ann-Katrin , Cummings Adonicah , Skerry Timothy , Alloush Ferial , Aljamal Abed A. , Deb Arunima , Alghamdi Sarah , Poppiti Robert
Published: October 2023

Perineural invasion (PNI) is defined as the dissemination of neoplastic cells within the perineural space. PNI can be a strong indicator of malignancy and is linked to poor prognosis and adverse outcomes in various malignant neoplasms; nevertheless, it can also be seen in benign pathologic conditions. In this review article, we discuss various signaling pathways and neurotrophic factors implicated in the development and progression of PNI. We also describe the methodology, benefits, and limitations of different in vitro, ex vivo, and in vivo models of PNI. The spectrum of presentation for PNI can range from diffuse spread within large nerves (“named” nerves) all the way through localized spread into unnamed microscopic nerves. Therefore, the clinical significance of PNI is related to its extent rather than its mere presence or absence. In this article, we discuss the guidelines for the identification and quantification of PNI in different malignant neoplasms based on the College of American Pathologists (CAP) and World Health Organization (WHO) recommendations. We also describe benign pathologic conditions and neoplasms demonstrating PNI and potential mimics of PNI. Finally, we explore avenues for the future development of targeted therapy options via modulation of signaling pathways involved in PNI.
Optimizing Stage Construction and Level Balancing of Match-3 Puzzle Game with PPO Algorithm Machine Learning
Authors: Kim Byounggwon , Kim Jungyoon
Published: October 2023

Although the global market has witnessed a proliferation of diverse match-3 puzzle games, achieving success in this competitive market remains challenging. The crucial factors that determine the success of match-3 puzzle games are the creation of numerous engaging stages and precise level balancing. The purpose of this study is to propose a match-3 puzzle game system that aims at identifying the most effective algorithm for training artificial intelligence agents in stage construction and level balancing verification. To validate the systems’ usefulness, this paper conducted experiments with the Proximal Policy Optimization (PPO) algorithm and obtained cumulative reward and entropy value graphs. Consequently, it has been confirmed that the system can be employed to compare learning outcomes for each algorithm and identify the optimal algorithm suitable for match-3 puzzle games. The use of machine learning technology in match-3 puzzle games holds the promise of revolutionizing game development and leading to the creation of more captivating and rewarding gaming experiences for players.
Voronoi Tessellation for Efficient Sampling in Gaussian Process-Based Robotic Motion Planning
Authors: Park Jee-Yong , Lee Hoosang , Kim Changhyeon , Ryu Jeha
Published: October 2023

On-line motion planning in dynamically changing environments poses a significant challenge in the design of autonomous robotic system. Conventional methods often require intricate design choices, while modern deep reinforcement learning (DRL) approaches demand vast amounts of robot motion data. Gaussian process (GP) regression-based imitation learning approaches address such issues by harnessing the GP’s data-efficient learning capabilities to infer generalized policies from a limited number of demonstrations, which can intuitively be generated by human operators. GP-based methods, however, are limited in data scalability as computation becomes cubically expensive as the amount of learned data increases. This issue is addressed by proposing Voronoi tessellation sampling, a novel data sampling strategy for learning GP-based robotic motion planning, where spatial correlation between input features and the output of the trajectory prediction model is exploited to select the data to be learned that are informative yet learnable by the model. Where the baseline is set by an imitation learning framework that uses GP regression to infer trajectories that learns policies optimized via a stochastic, reward-based optimization algorithm, experimental results demonstrate that the proposed method can learn optimal policies spanning over all of feature space using fewer data compared to the baseline method.
A Novel Hybrid Imperialist Competitive Algorithm–Particle Swarm Optimization Metaheuristic Optimization Algorithm for Cost-Effective Energy Management in Multi-Source Residential Microgrids
Authors: Charadi Ssadik , Chakir Houssam Eddine , Redouane Abdelbari , El Hasnaoui Abdennebi , El Bhiri Brahim
Published: October 2023

The integration of renewable sources and energy storage in residential microgrids offers energy efficiency and emission reduction potential. Effective energy management is vital for optimizing resources and lowering costs. In this paper, we propose a novel approach, combining the imperialist competitive algorithm (ICA) with particle swarm optimization (PSO) as ICA-PSO to enhance energy management. The proposed energy management system operates in an offline mode, anticipating data for the upcoming 24 h, including consumption predictions, tariff rates, and meteorological data. This anticipatory approach facilitates optimal power distribution among the various connected sources within the microgrid. The performance of the proposed hybrid ICA-PSO algorithm is evaluated by comparing it with three selected benchmark algorithms, namely the genetic algorithm (GA), ICA, and PSO. This comparison aims to assess the effectiveness of the ICA-PSO algorithm in optimizing energy management in multi-source residential microgrids. The simulation results, obtained using Matlab 2023a, provide clear evidence of the effectiveness of the hybrid ICA-PSO algorithm in achieving optimal power flows and delivering substantial cost savings. The hybrid algorithm outperforms the benchmark algorithms with cost reductions of 4.47%, 14.93%, and 26% compared to ICA, PSO, and GA, respectively. Furthermore, it achieves a remarkable participation rate of 50.6% for renewable resources in the energy mix, surpassing the participation levels of the ICA (42.88%), PSO (40.51%), and GA (38.95%). This research contributes to the advancement of power flow management techniques in the context of multi-source residential microgrids, paving the way for further research and development in this field.
Review of Façade Photovoltaic Solutions for Less Energy-Hungry Buildings
Authors: Mangherini Giulio , Diolaiti Valentina , Bernardoni Paolo , Andreoli Alfredo , Vincenzi Donato
Published: October 2023

Building-integrated photovoltaic technologies have considerable potential for the generation of onsite renewable energy. Despite this, their market penetration is in a relatively embryonic phase with respect to grounded or building-attached solutions, and they have limited commercial application. Their integration into building façades may represent a key asset in meeting the net-zero emissions by 2050 scenario, in particular for high-rise buildings in which the roof-to-façade ratio is unfavorable for the fulfillment of the energy load using only roof photovoltaic technology. Moreover, different façade orientations extend the production time throughout the day, flattening the power generation curve. Because of the present interest in BIPV systems, several researchers have conducted high-quality reviews focused on specific designs. In this work, various photovoltaic technologies and methods used to manufacture façade BIPV devices are reviewed with the aim of presenting researchers with the recent technological advancements and providing an overview of photovoltaic systems designed for different purposes and their applications rather than a detailed analysis of a specific technology. Lastly, future prospects and the limitations of building-integrated photovoltaic devices are presented.
Linear Quadratic Gaussian Control of a 6-DOF Aircraft Landing Gear
Authors: Nkemdirim Chimezirim Miracle , Alzayed Mohamad , Chaoui Hicham
Published: October 2023

The suspension system of the aircraft, provided by the landing gear, is a crucial part of landing, take-off, and taxiing. It is important that this suspension system not only adequately supports the airframe of the aircraft but also provides a comfortable, seamless ride for the passengers. However, the landing gear is usually riddled with issues, such as landing vibrations that affect passenger comfort and cause damage to the aircraft’s airframe. To reduce these vibrations, this paper proposes the use of a Linear Quadratic Gaussian (LQG) controller to control a 6-DOF aircraft landing gear. The LQG controller is an optimal controller that combines the Linear Quadratic Regulator (LQR) controller with the Kalman filter to compute the system’s control signals and estimate the system’s states. In this paper, the state space model of the 6-DOF landing gear is derived, and the mathematical model of the LQG controller is calculated. The controller’s performance is then tested via MATLAB/Simulink and compared with an equally simple control strategy, the PID controller. The results obtained from the testing process indicate that the LQG controller surpasses the PID controller in reducing landing vibrations, maintaining the aircraft’s airframe, and providing passenger comfort.
Energy Management Systems in Sustainable Smart Cities Based on the Internet of Energy: A Technical Review
Authors: Mishra Priyanka , Singh Ghanshyam
Published: October 2023

In this paper, we exploit state-of-the-art energy management in sustainable smart cities employing the Internet of Energy (IoE). The primary goal of this study is to leverage cutting-edge energy management techniques through the IoE in sustainable smart cities to bring about significant improvements in clean energy processes while targeting environmental benefits, efficiency enhancements, sustainability, and cost reduction. In this work, we present a comprehensive exploration of energy management strategies within the context of IoE-enabled sustainable smart cities. Firstly, we provide a detailed classification of diverse energy management approaches pertinent to IoE-based sustainable smart cities. This classification covers a spectrum of methodologies, including scheduling optimization, the design of low-power device transceivers, cognitive frameworks, and the integration of cloud computing technology. Furthermore, we highlight the pivotal role of smart grids as fundamental elements in the establishment of smart cities. Within this context, we offer a comprehensive overview of the essential components that underlie smart grids, with a notable focus on the intricate realm of micro/nanogrids. Moreover, our research delves comprehensively into energy harvesting within the context of smart cities. We analyze crucial facets like receiver design, energy optimization methods, a variety of energy sources, efficient energy scheduling approaches, and the establishment of effective energy routing mechanisms. Additionally, we delve into the multifaceted nature of sustainable smart cities across various domains. Our investigation reaches its culmination in the creation of a novel conceptual framework and the identification of enabling technologies centered on effective energy management. Lastly, we contribute to the field by outlining the current research challenges and mapping potential research directions relevant to energy management within sustainable smart cities, capitalizing on the capabilities of the IoT.
Stochastic Dynamical Modeling of Wind Farm Turbulence
Authors: Bhatt Aditya H. , Rodrigues Mireille , Bernardoni Federico , Leonardi Stefano , Zare Armin
Published: October 2023

Low-fidelity engineering wake models are often combined with linear superposition laws to predict wake velocities across wind farms under steady atmospheric conditions. While convenient for wind farm planning and long-term performance evaluation, such models are unable to capture the time-varying nature of the waked velocity field, as they are agnostic to the complex aerodynamic interactions among wind turbines and the effects of atmospheric boundary layer turbulence. To account for such effects while remaining amenable to conventional system-theoretic tools for flow estimation and control, we propose a new class of data-enhanced physics-based models for the dynamics of wind farm flow fluctuations. Our approach relies on the predictive capability of the stochastically forced linearized Navier–Stokes equations around static base flow profiles provided by conventional engineering wake models. We identify the stochastic forcing into the linearized dynamics via convex optimization to ensure statistical consistency with higher-fidelity models or experimental measurements while preserving model parsimony. We demonstrate the utility of our approach in completing the statistical signature of wake turbulence in accordance with large-eddy simulations of turbulent flow over a cascade of yawed wind turbines. Our numerical experiments provide insight into the significance of spatially distributed field measurements in recovering the statistical signature of wind farm turbulence and training stochastic linear models for short-term wind forecasting.
Real-Time Control of a Battery Energy Storage System Using a Reconfigurable Synchrophasor-Based Control System
Authors: Adhikari Prottay M. , Vanfretti Luigi , Chang Hao , Kar Koushik
Published: October 2023

Synchrophasor-driven smart grid applications aiming to orchestrate a diverse set of Distributed Energy Resources (DERs) require extensive infrastructure including substantial instrumentation hardware, communication network extensions and controller installations for coordinated operation. This can make the overall installation expensive. Additionally, due to the computational complexity and data-intensive nature of the PDC functionality, most of the existing PDC implementations are on a purely software level, making them unsuitable for the real-time applications. To address this, the current paper proposes an alternate architecture for the real-time synchrophasor-based control of DER applications (e.g., microgrids) incorporating a centralized synchronization hardware designed to replace aggregation Phasor Data Concentrators (PDCs) and supplementary control algorithms into a singular reconfigurable hardware. This particular hardware is termed a Synchrophasor Synchronization Gateway and Controller (SSGC). The robustness of the proposed architecture is tested by using real-time (RT) Controller Hardware-In-the-Loop (CHIL) simulation-based experiments by manipulating the communication network that connects the SSGC with multiple Phasor Measurement Unit (PMU) streams broadcasting data through the IEEE C37.118.2 protocol in real time. These PMU streams were generated by using a real-time microgrid model running on a Typhoon HIL 604 simulator. To manipulate the communication interface between the proposed SSGC hardware and the PMU streams, a configurable Wide Area Network (WAN) emulator and communication network impairment appliance deployed in the Candela Technologies CT910 external hardware was utilized. The real-time control system was expanded by incorporating a low-pass filter to eliminate the potential overswitching of a Battery Energy Storage System (BESS). The proposed architecture demonstrated a reliable performance under ideal to moderately tampered communication networks. However, under a significantly corrupted network, the performance of this architecture is acutely affected.
Thermo-Economic Performance Analysis of Modified Latent Heat Storage System for Residential Heating
Authors: Gao Xinyu , Li Ze , Yu Jiabang , Gao Jiayi , Yang Xiaohu , Sundén Bengt
Published: October 2023

Solar energy is a sustainable source that can be effectively utilized to address winter heating challenges in buildings. To ensure the efficient application of solar energy for heating purposes and to maintain reliable performance of the heating system, the integration of phase-change materials (PCMs) in thermal energy storage (TES) systems has emerged as a crucial auxiliary approach. This study focuses on the design and simulation of four TES structures: smooth, finned, metallic foam, and metallic foam-finned tubes. It explores their thermal characteristics, such as complete melting time and heat flux, under various flow conditions. Additionally, a residential building in Xi’an is selected as the object, where the proposed solar energy phase-change TES system is employed to meet the heating demand. Economic indicators, including initial investment and investment payback period, are estimated using a static evaluation method. The results highlight that the complete melting time of the TES unit with a metallic foam-finned tube is 4800 s, which is 88.3% less than the smooth tube. Finally, based on the actual project, it is determined that the metallic foam-finned heating system, with an HTF flow rate of 0.25 m/s, requires the fewest TES devices (914) and has a payback period of 13 months.
Comparison between Physics-Based Approaches and Neural Networks for the Energy Consumption Optimization of an Automotive Production Industrial Process
Authors: Pelella Francesco , Viscito Luca , Magnea Federico , Zanella Alessandro , Patalano Stanislao , Mauro Alfonso William , Bianco Nicola
Published: October 2023

The automotive production sector plays a significant role in the energy consumption of all the industrial sphere, which currently represents approximately 38% of the total global energy use. Especially in production sites with several manufacturing lines working in parallel, the occurrence of failures and anomalies or sudden changes in the production volume may require a re-scheduling of the entire production process. In this regard, a digital twin of each phase of the process would give several indications about the new re-scheduled manufacture in terms of energy consumption and the control strategy to adopt. Therefore, the main goal of this paper is to propose different modeling approaches to a degreasing tank process, which is a preliminary phase at automotive production sites before the application of paint to car bodies. In detail, two different approaches have been developed: the first is a physics-based thermodynamic approach, which relies on the mass and energy balances of the system analyzed, and the second is machine learning-based, with the calibration of several artificial neural networks (ANNs). All the investigated approaches were assessed and compared, and it was determined that, for this application and with the data at our disposal, the thermodynamic approach has better prediction accuracy, with an overall mean absolute error (MAE) of 1.30 °C. Moreover, the model can be used to optimize the heat source policy of the tank, for which it has demonstrated, with historical data, an energy saving potentiality of up to 30%, and to simulate future scenarios in which, due to company constraints, a re-scheduling of the production of more work shifts is required.
Structural Vulnerability Analysis of Interdependent Electric Power and Natural Gas Systems
Authors: Amusan Olabode , Shi Shuomang , Wu Di , Liao Haitao
Published: October 2023

The growing use of gas-fired power generators and electricity-driven gas compressors and storage has increased the interdependence between electric power infrastructure and natural gas infrastructure. However, the increasing interdependence may spread the failures from one system to the other, causing subsequent failures in an integrated power and gas system (IPGS). This paper investigates the structural vulnerability of a realistic IPGS based on complex network theory. Different from the existing works with a focus on the static vulnerability analysis for an IPGS, this paper considers both static and dynamic vulnerability analysis. The former focuses on vulnerability analysis under random and selective failures without flow redistribution, while the latter concentrates on vulnerability analysis under cascading failures caused by flow redistribution. Also, different from the existing works with a focus on the IPGS as a whole, we not only analyze the vulnerability of the IPGS but also analyze the vulnerability of the power subsystem (PS) and gas subsystem (GS), in order to understand how the vulnerability of the IPGS is affected by its PS and GS. The analysis results show that (1) if the PS and GS are more susceptible to cascading failures than selective and random failures, the IPGS as a whole is also more vulnerable to cascading failures. (2) There are different dominant factors affecting the IPGS vulnerability under cascading failures and selective failures. Under cascading failures, the GS has a more significant impact on the IPGS vulnerability; under selective failures, the PS has a more important impact on the IPGS vulnerability. (3) The IPGS is more vulnerable to failures on the critical nodes, which are identified from the IPGS as a whole rather than from the individual PS or GS. The results provide insights into the design and planning of IPGSs to improve their overall reliability.
An IHPO-WNN-Based Federated Learning System for Area-Wide Power Load Forecasting Considering Data Security Protection
Authors: Shi Bujin , Zhou Xinbo , Li Peilin , Ma Wenyu , Pan Nan
Published: October 2023

With the rapid growth of power demand and the advancement of new power system intelligence, smart energy measurement system data quality and security are also facing the influence of diversified factors. To solve the series of problems such as low data prediction efficiency, poor security perception, and “data islands” of the new power system, this paper proposes a federated learning system based on the Improved Hunter–Prey Optimizer Optimized Wavelet Neural Network (IHPO-WNN) for the whole-domain power load prediction. An improved HPO algorithm based on Sine chaotic mapping, dynamic boundaries, and a parallel search mechanism is first proposed to improve the prediction and generalization ability of wavelet neural network models. Further considering the data privacy in each station area and the potential threat of cyber-attacks, a localized differential privacy-based federated learning architecture for load prediction is designed by using the above IHPO-WNN as a base model. In this paper, the actual dataset of a smart energy measurement master station is selected, and simulation experiments are carried out through MATLAB software to test and examine the performance of IHPO-WNN and the federal learning system, respectively, and the results show that the method proposed in this paper has high prediction accuracy and excellent practical performance.
Data-Based Orderly Charging Strategy Considering Users’ Charging Choices
Authors: Tao Ye , Chen Yupu , Huang Miaohua , Yang Lan
Published: October 2023

This work proposes a centralized data-based orderly charging strategy that considers the user’s charging choices. Three charging choices for different types of users are described. Then, a scheduling model of electric vehicles based on the time dimension is established. In this strategy, the optimization model not only considers the demand of the grid side and the user side, but also takes the driving data of electric vehicles as the driver. The grid-side optimization involves minimizing the equivalent load fluctuation, and the user-side is optimized to minimize the charging cost and maximize the charging electric quantity. The scheduling capabilities of the three charging strategies are analyzed based on a series of driving data of electric vehicles. The results show that the peak-valley difference and equivalent load fluctuation of the power grid in the data-based orderly charging strategy reduced by 22.2% and 22.7%, respectively, and the charging cost of users also reduced much more than the other two charging strategies. Additionally, the effect of users’ charging choices on the charging strategy is analyzed, and the results show that the orderly charging strategy that considers users’ charging choices can effectively decrease the scheduling deviation caused by users’ charging choices. It greatly improves the security and economy of the grid.
Numerical Study on the Combustion Properties of Ammonia/DME and Ammonia/DMM Mixtures
Authors: Zhang Yuanpu , Wang Qian , Dai Liming , Zhang Ming , Yu Chunkan
Published: October 2023

Ammonia (NH3) is considered a promising zero-carbon fuel and was extensively studied recently. Mixing high-reactivity oxygenated fuels such as dimethyl ether (DME) or dimethoxymethane (DMM) with ammonia is a realistic approach to overcome the low reactivity of NH3. To study the combustion characteristics of NH3/DMM and NH3/DME mixtures, we constructed a NH3/DMM chemical mechanism and tested its accuracy using measured laminar burning velocity (LBV) and ignition delay time (IDT) of both NH3/DMM and NH3/DME mixtures from the literature. The kinetic analysis of NH3/DMM flames using this mechanism reveals that the CH3 radicals generated from the oxidation of DMM substantially affects the oxidation pathway of NH3 at an early stage of flame propagation. We investigated the formation of nitrogen oxides (NOx) in NH3/DMM and NH3/DME flames and little difference can be found in the NOx emissions. Using NH3/DMM flames as an example, the peak NOx emissions are located at an equivalence ratio (φ) of 0.9 and a DMM fraction of 40% in the conditions studied. Kinetic analysis shows that NOx emission is dominated by NO, which primarily comes from fuel nitrogen of NH3. The addition of DMM at 40% significantly promotes the reactive radical pool (e.g., H, O, and OH) while the maintaining a high concentration of NO precursors (e.g., HNO, NO2, and N2O), which results in a high reaction rate of NO formation reaction and subsequently generates the highest NO emissions.
SARS-CoV-2 Variant-Specific Gastrointestinal Symptoms of COVID-19: 2023 Update
Authors: Slabakova Yoanna , Gerasoudis Stavros , Miteva Dimitrina , Peshevska-Sekulovska Monika , Batselova Hristiana , Snegarova Violeta , Vasilev Georgi V. , Vasilev Georgi H. , Sekulovski Metodija , Lazova Snezhina , Gulinac Milena , Tomov Latchezar , Velikova Tsvetelina
Published: October 2023

The gastrointestinal (GI) tract may be a significant entrance or interaction site for SARS-CoV-2; therefore, the gut mucosal immune system participates in virus interaction as a first-line physical and immunological defense, leading to GI involvement and symptoms. This review focuses on the GI symptoms associated with SARS-CoV-2 infection while providing specific results on variant-specific signs and syndromes related to coronavirus disease 2019 (COVID-19). The pattern of symptoms changed during the virus evolution, since the data provided a current and thorough picture of the symptoms experienced by SARS-CoV-2 infected people, and variations in symptom patterns occurred as the Alpha, Delta, and Omicron variants have spread. Since the beginning of the pandemic, GI symptoms have been linked to SARS-CoV-2 infections, even though most infected people do not report them. For example, diarrhea (28.2%) was the most frequently reported GI symptom in the early phase of the pandemic. The most observed GI tract symptoms during COVID-19 were anorexia (loss of appetite), nausea, vomiting, diarrhea, and abdominal pain, usually in at least one-third of the patients. Mesenteric ischemia and GI bleeding were less observed but more severe. While GI symptoms are not associated with increased mortality, they complicate the disease, increase the duration of the illness, and result in worse outcomes. Nevertheless, it is accepted that symptoms between variants differ significantly, i.e., the Omicron variant causes milder COVID-19 than the Delta. Still, the rate of GI symptoms has declined in the following variant-dominated phases of the pandemic (Alpha: 19.4%, Delta: 17.9%, Omicron: 13.8%), which was also demonstrated for other GI signs associated with COVID-19.
A Case of Foreign Body in the Biliary Tree and the Challenge of Hypereosinophilia
Authors: Sinagra Emanuele , Mandarino Francesco Vito , Rossi Francesca , Alloro Rita , Testai Sergio , Marasà Marta , Cristofalo Serena , Maida Marcello , Brinch Daniele , Conoscenti Giuseppe , Fasulo Ernesto , Raimondo Dario
Published: October 2023

In all reported cases of foreign body migration or impaction in the biliary tree, there is no mention of the presence of hypereosinophilia among the laboratory findings. This could possibly be attributed to the local tissue reaction caused by the impacted foreign body. Here, we present our experience with the removal of a screw from a surgical retractor that became lodged in the common bile duct (CBD) and migrated in a patient who had previously undergone a left lateral hepatectomy for hepatic hydatidosis. The imaging was not sufficient to make a diagnosis, and the interpretation of hypereosinophilia in such a case could pose a challenge.
Health-Related, Social and Cognitive Factors Explaining Gambling Addiction
Authors: Esparza-Reig Javier , Martí-Vilar Manuel , González-Sala Francisco , Merino-Soto César , Hernández-Salinas Gregorio , Toledano-Toledano Filiberto
Published: October 2023

Background: Gambling addiction was the first addictive behavior not related to substance use that was recognized by the DSM-5. It shares diagnostics and comorbidity with other addictions. Extensive studies have investigated the clinical variables involved, but there have been fewer studies of related cognitive and social variables. In this research, an integrative model was developed to advance the understanding of gambling addiction, and an explanatory model was created based on the concept of cognitive distortions. Methods: The sample comprised 258 university students (59.5% women) with a mean age of 20.95 years (SD = 2.19). A series of questionnaires were administered to measure gambling addiction, depression, coping with stress, prosocial behavior, susceptibility to priming and cognitive distortions about gambling. In addition, correlations, multiple linear regressions and a simple mediation model of these variables were analyzed. Results: The results indicated that gambling addiction was correlated with a variety of clinical, social and cognitive factors. These factors contributed to a model that predicted 16.8% of the variance in gambling addiction and another model using cognitive distortions as a predictor and the maximum bet as a mediator that predicted 34.5% of the variance. Conclusions: The study represents an advance by developing a theoretical model from an integrative perspective and providing a new explanatory model. The findings of this research are of great importance in the development of prevention and intervention programs for gambling addiction.
Evaluating Feasibility of a Secondary Stroke Prevention Program
Authors: Hunter Stephanie , Vogel Kimberley , O’Leary Shane , Blennerhassett Jannette Maree
Published: October 2023

Healthy lifestyles including exercise and diet can reduce stroke risk, but stroke survivors often lack guidance to modify their lifestyles after hospital discharge. We evaluated the implementation of a new, secondary stroke prevention program involving supervised exercise, multidisciplinary education and coaching to address modifiable risk factors. The group-based program involved face-to-face and telehealth sessions. The primary outcomes were feasibility, examined via service information (referrals, uptake, participant demographics and costs), and participant acceptability (satisfaction and attendance). Secondary outcomes examined self-reported changes in lifestyle factors and pre–post scores on standardized clinical tests (e.g., waist circumference and 6-Minute Walk (6MWT)). We ran seven programs in 12 months, and 37 people participated. Attendance for education sessions was 79%, and 30/37 participants completed the full program. No adverse events occurred. Participant satisfaction was high for ‘relevance’ (100%), ‘felt safe to exercise’ (96%) and ‘intend to continue’ (96%). Most participants (88%) changed (on average) 2.5 lifestyle factors (diet, exercise, smoking and alcohol). Changes in clinical outcomes seemed promising, with some being statistically significant, e.g., 6MWT (MD 59 m, 95% CI 38 m to 80,159 m, p < 0.001) and waist circumference (MD −2.1 cm, 95%CI −3.9 cm to −1.4 cm, p < 0.001). The program was feasible to deliver, acceptable to participants and seemed beneficial for health. Access to similar programs may assist in secondary stroke prevention.
Acute Effect of Night Shift Work on Endothelial Function with and without Naps: A Scoping Review
Authors: Patterson Paul D. , Friedman Jacob C. , Ding Samuel , Miller Rebekah S. , Martin-Gill Christian , Hostler David , Platt Thomas E.
Published: October 2023

We examined the breadth and depth of the current evidence investigating napping/sleeping during night shift work and its impact on non-invasive measures of endothelial function. We used a scoping review study design and searched five databases: Ovid Medline, EMBASE, Ovid APA PsycInfo, Web of Science Core Collection, and EBSCO CINAHL. We limited our search to English language and publications from January 1980 to September 2022. Our reporting adhered to the PRISMA-ScR guidance for scoping reviews. Our search strategy yielded 1949 records (titles and abstracts) after deduplication, of which 36 were retained for full-text review. Five articles were retained, describing three observational and two experimental research studies with a total sample of 110 individuals, which examined the non-invasive indicators of endothelial function in relation to the exposure to night shift work. While there is some evidence of an effect of night shift work on the non-invasive indicators of endothelial function, this evidence is incomplete, limited to a small samples of shift workers, and is mostly restricted to one measurement technique for assessing endothelial function with diverse protocols. In addition, there is no identifiable research investigating the potential benefits of napping during night shift work on non-invasive measures of endothelial function.