bluuebunny/crossref_metadata_2025 huggingface dataset:
The Microstructure Evolution during Divorced Eutectoid Transformation in a κ-Carbide Reinforced High Specific Young’s Modulus Steel
Authors: Yang Fuming , Chen Peng , Li Xiaowu
Published: September 2022

High specific Young’s modulus steel reinforced by κ-carbides has the characteristics of high strength and low density, which introduces potential applications of this material in automotive parts with a stiffness requirement. In this work, a 780 MPa grade Fe-Al-C high specific Young’s modulus steel was developed, and the addition of high contents of carbon and aluminum introduced a large fraction of κ-carbides into the steel matrix. To improve the ductility of this steel, a divorced eutectoid transformation (DET) treatment was adopted to regulate the microstructure of κ-carbides. A detailed evolution of κ-carbide during DET was investigated by staged quenching and microstructure characterization. It has been found for the first time that the κ-pearlite transformation and κ-carbides precipitation were mainly completed in the early stage during slow cooling, and the spheroidization of κ-carbides was mainly completed in the later stage. In addition, the effect of DET parameters on the microstructure evolution was analyzed, and it was found that a better spheroidization effect of carbides can be obtained at a lower cooling rate.
Prevalence of Symptomatic Nonstenotic Carotid Disease Using Simultaneous Non-Contrast Angiography and Intraplaque Hemorrhage Imaging for MR Screen Protocol
Authors: Lee Chae Rin , Yang Jun Cheol , Lee Ui Yun , Hwang Seung Bae , Chung Gyung Ho , Kwak Hyo Sung
Published: September 2022

Background: To determine the prevalence of symptomatic nonstenotic carotid disease (SyNC) using simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) imaging for patients with acute stroke as an MR screen protocol and to assess imaging findings of carotid plaques. Patients and Methods: From May 2020 to October 2021, 2459 patients with suspected acute neurological symptoms were evaluated with brain diffusion-weighted imaging (DWI) and carotid SNAP imaging. We analyzed the degree of stenosis and intraplaque hemorrhage (IPH) using SNAP imaging. Prevalence of SyNC and risk factors for stroke in patients with SyNC were determined. We performed subgroup multivariate analysis between SyNC and other etiologies of stroke (non-SyNC). Results: Of 4608 carotid arteries in 2304 patients enrolled in this study, 454 (9.9%) plaques (both lesions in 128 patients) were found on SNAP imaging. Of these plaques, 353 (77.8%) showed stenosis of <50%. Of plaques with <50% stenosis, 47 (13.3%) patients had a territorial acute focal infarction. Seventeen (36.2%) were classified with embolic stroke of undetermined source (ESUS) and SyNC. High maximal wall thickness and carotid IPH were identified as influencing factors for SyNC. Conclusion: For patients with <50% stenosis and territorial infarction, SyNC is a relatively important source of stroke. Especially, high maximal wall thickness and carotid IPH are important risk factors for SyNC.
Use of Anti-Thrombotic Drugs and In-Hospital Mortality in Acute Aortic Dissection Patients
Authors: Hori Kensuke , Morikawa Nagisa , Tayama Eiki , Fukumoto Yoshihiro
Published: September 2022

Acute aortic dissection occurs due to a primary tear in the aortic intima, with blood from the aortic lumen entering the adjacent diseased media. In the clinical setting, practitioners often hesitate before the use of anti-thrombotic drugs in the acute phase of aortic dissection. Therefore, we examined the clinical course in patients who had already received antithrombotic therapies at the onset of acute aortic dissection, and who were given anti-thrombotic drugs in the acute phase during hospitalization. We retrospectively enrolled 685 consecutive patients with acute aortic dissection (type A/B: 454/231), who were transferred to Kurume University Hospital from 2004 to 2020. In types A and B, there were no significant differences between in-hospital mortality with or without antithrombotic therapies at the onset (14.3% vs. 16.4%, p = 0.66 in type A, 2.6% vs. 7.3%, p = 0.29 in type B). Patients in type A who survived more than a day and were treated with anti-thrombotic drugs during hospitalization had significantly lower in-hospital mortality compared with those who received no anti-thrombotic drugs in the acute phase (2.2% vs. 16.1%, p < 0.001), while there was no significant difference between in-hospital mortality in the two type-B groups (2.4% vs. 4.9%, p = 0.48). Although there were variations in response among patients with acute aortic dissection, anti-thrombotic drugs did not worsen in-hospital mortality for patients with acute aortic dissection, indicating that medical staff should not hesitate to administer anti-thrombotic drugs if indicated.
Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy
Authors: Pyka Thomas , Krzyzanowska Iwona , Rominger Axel , Delbridge Claire , Meyer Bernhard , Boeckh-Behrens Tobias , Zimmer Claus , Gempt Jens
Published: September 2022

Both static and dynamic O-(2-[18F]fluoroethyl)-l-tyrosine-(FET)-PET and 1H magnetic resonance spectroscopy (MRS) are useful tools for grading and prognostication in gliomas. However, little is known about the potential of multimodal imaging comprising both procedures. We therefore acquired NAA/Cr and Cho/Cr ratios in multi-voxel MRS as well as FET-PET parameters in 67 glioma patients and determined multiparametric parameter combinations. Using receiver operating characteristics, differentiation between low-grade and high-grade glioma was possible by static FET-PET (area under the curve (AUC) 0.86, p = 0.001), time-to-peak (TTP; AUC 0.79, p = 0.049), and using the Cho/Cr ratio (AUC 0.72, p = 0.039), while the multimodal analysis led to improved discrimination with an AUC of 0.97 (p = 0.001). In order to distinguish glioblastoma from non-glioblastoma, MRS (NAA/Cr ratio, AUC 0.66, p = 0.031), and dynamic FET-PET (AUC 0.88, p = 0.001) were superior to static FET imaging. The multimodal analysis increased the accuracy with an AUC of 0.97 (p < 0.001). In the survival analysis, PET parameters, but not spectroscopy, were significantly correlated with overall survival (OS, static PET p = 0.014, TTP p = 0.012), still, the multiparametric analysis, including MRS, was also useful for the prediction of OS (p = 0.002). In conclusion, FET-PET and MRS provide complementary information to better characterize gliomas before therapy, which is particularly interesting with respect to the increasing use of hybrid PET/MRI for brain tumors.
Cardiac Imaging and Management of Cardiac Disease in Asymptomatic Renal Transplant Candidates: A Current Update
Authors: Lioudaki Eirini , Androvitsanea Ariadni , Petrakis Ioannis , Bakogiannis Constantinos , Androulakis Emmanuel
Published: September 2022

Given the high cardiovascular risk accompanying end-stage kidney disease, it would be of paramount importance for the clinical nephrologist to know which screening method(s) identify high-risk patients and whether screening asymptomatic transplant candidates effectively reduces cardiovascular risk in the perioperative setting as well as in the longer term. Within this review, key studies concerning the above questions are reported and critically analyzed. The lack of unified screening criteria and of a prognostically sufficient screening cardiovascular effect for renal transplant candidates sets the foundation for a personalized patient approach in the near future and highlights the need for well-designed studies to produce robust evidence which will address the above questions.
Diagnosis and Management of Pelvic Venous Disorders in Females
Authors: Marcelin Clément , Le Bras Yann , Molina Andreo Isabelle , Jambon Eva , Grenier Nicolas
Published: September 2022

Pelvic venous pathologies in females are responsible for chronic symptoms grouped under the term pelvic congestion syndrome, which includes chronic pelvic pain, perineal heaviness, urgency, and postcoital pain, along with vulvar, perineal, and lower limb varicose veins. These conditions are also associated with ovarian and pelvic venous reflux and venous obstruction. This review aimed to explore the clinical and imaging modalities for diagnosing pelvic congestion syndrome, pelvic venous pathologies, their therapeutic management, and their outcomes.
Recurrent Disseminated Intravascular Coagulation in Metastatic Castration-Resistant Prostate Cancer: A Case Report
Authors: Giszas Benjamin , Fritzenwanger Michael , Grimm Marc-Oliver , Stallmach Andreas , Reuken Philipp A.
Published: September 2022

Disseminated intravascular coagulation (DIC) is a systemic disease characterized by simultaneous thrombosis, bleeding, and partially excessive fibrinolysis. Systemic shock, trauma, bacterial toxins, and procoagulants-expressing solid and hematologic malignancies are common causes of this life-threatening hemorrhagic complication and often require treatment in intensive care units. We describe a case of an elderly man with recurrent severe bleeding events in the cause of DIC, including epistaxis, hemoptysis, hematuria, and gastrointestinal bleeding. Laboratory investigations revealed elevated prostate-specific antigen (PSA), suggesting an underlying prostate cancer. Despite intensified coagulatory therapy, the coagulation disorder could not be stabilized. A single injection of degarelix, a gonadotropin-releasing hormone (GnRH) receptor antagonist, led to rapid stabilization of the coagulation and decreased PSA within days. One year after initiating androgen-deprivation therapy, there were recurrent transfusion-requiring bleeding events, and a concomitant PSA increase occurred, suggesting metastatic castration-resistant disease associated with DIC. This case emphasizes DIC as a possible primary phenomenon and indicator for the progression of the underlying malignancy, as well as the importance of etiological therapies in the management of DIC.
Kaniadakis Functions beyond Statistical Mechanics: Weakest-Link Scaling, Power-Law Tails, and Modified Lognormal Distribution
Authors: Hristopulos Dionissios T. , Baxevani Anastassia
Published: September 2022

Probabilistic models with flexible tail behavior have important applications in engineering and earth science. We introduce a nonlinear normalizing transformation and its inverse based on the deformed lognormal and exponential functions proposed by Kaniadakis. The deformed exponential transform can be used to generate skewed data from normal variates. We apply this transform to a censored autoregressive model for the generation of precipitation time series. We also highlight the connection between the heavy-tailed κ-Weibull distribution and weakest-link scaling theory, which makes the κ-Weibull suitable for modeling the mechanical strength distribution of materials. Finally, we introduce the κ-lognormal probability distribution and calculate the generalized (power) mean of κ-lognormal variables. The κ-lognormal distribution is a suitable candidate for the permeability of random porous media. In summary, the κ-deformations allow for the modification of tails of classical distribution models (e.g., Weibull, lognormal), thus enabling new directions of research in the analysis of spatiotemporal data with skewed distributions.
Implementation of Quantum Algorithms via Fast Three-Rydberg-Atom CCZ Gates
Authors: Tang Shiqing , Yang Chong , Li Dongxiao , Shao Xiaoqiang
Published: September 2022

Multiqubit CCZ gates form one of the building blocks of quantum algorithms and have been involved in achieving many theoretical and experimental triumphs. Designing a simple and efficient multiqubit gate for quantum algorithms is still by no means trivial as the number of qubits increases. Here, by virtue of the Rydberg blockade effect, we propose a scheme to rapidly implement a three-Rydberg-atom CCZ gate via a single Rydberg pulse, and successfully apply the gate to realize the three-qubit refined Deutsch–Jozsa algorithm and three-qubit Grover search. The logical states of the three-qubit gate are encoded to the same ground states to avoid an adverse effect of the atomic spontaneous emission. Furthermore, there is no requirement for individual addressing of atoms in our protocol.
Research of Software Defect Prediction Model Based on Complex Network and Graph Neural Network
Authors: Cui Mengtian , Long Songlin , Jiang Yue , Na Xu
Published: September 2022

The goal of software defect prediction is to make predictions by mining the historical data using models. Current software defect prediction models mainly focus on the code features of software modules. However, they ignore the connection between software modules. This paper proposed a software defect prediction framework based on graph neural network from a complex network perspective. Firstly, we consider the software as a graph, where nodes represent the classes, and edges represent the dependencies between the classes. Then, we divide the graph into multiple subgraphs using the community detection algorithm. Thirdly, the representation vectors of the nodes are learned through the improved graph neural network model. Lastly, we use the representation vector of node to classify the software defects. The proposed model is tested on the PROMISE dataset, using two graph convolution methods, based on the spectral domain and spatial domain in the graph neural network. The investigation indicated that both convolution methods showed an improvement in various metrics, such as accuracy, F-measure, and MCC (Matthews correlation coefficient) by 86.6%, 85.8%, and 73.5%, and 87.5%, 85.9%, and 75.5%, respectively. The average improvement of various metrics was noted as 9.0%, 10.5%, and 17.5%, and 6.3%, 7.0%, and 12.1%, respectively, compared with the benchmark models.
Selection of Optimal Palmer Predictors for Increasing the Predictability of the Danube Discharge: New Findings Based on Information Theory and Partial Wavelet Coherence Analysis
Authors: Mares Ileana , Mares Constantin , Dobrica Venera , Demetrescu Crisan
Published: September 2022

The purpose of this study was to obtain synergistic information and details in the time–frequency domain of the relationships between the Palmer drought indices in the upper and middle Danube River basin and the discharge (Q) in the lower basin. Four indices were considered: the Palmer drought severity index (PDSI), Palmer hydrological drought index (PHDI), weighted PDSI (WPLM) and Palmer Z-index (ZIND). These indices were quantified through the first principal component (PC1) analysis of empirical orthogonal function (EOF) decomposition, which was obtained from hydro-meteorological parameters at 15 stations located along the Danube River basin. The influences of these indices on the Danube discharge were tested, both simultaneously and with certain lags, via linear and nonlinear methods applying the elements of information theory. Linear connections were generally obtained for synchronous links in the same season, and nonlinear ones for the predictors considered with certain lags (in advance) compared to the discharge predictand. The redundancy–synergy index was also considered to eliminate redundant predictors. Few cases were obtained in which all four predictors could be considered together to establish a significant information base for the discharge evolution. In the fall season, nonstationarity was tested through wavelet analysis applied for the multivariate case, using partial wavelet coherence (pwc). The results differed, depending on the predictor kept in pwc, and on those excluded.
An Optimized Black-Box Adversarial Simulator Attack Based on Meta-Learning
Authors: Chen Zhiyu , Ding Jianyu , Wu Fei , Zhang Chi , Sun Yiming , Sun Jing , Liu Shangdong , Ji Yimu
Published: September 2022

Much research on adversarial attacks has proved that deep neural networks have certain security vulnerabilities. Among potential attacks, black-box adversarial attacks are considered the most realistic based on the the natural hidden nature of deep neural networks. Such attacks have become a critical academic emphasis in the current security field. However, current black-box attack methods still have shortcomings, resulting in incomplete utilization of query information. Our research, based on the newly proposed Simulator Attack, proves the correctness and usability of feature layer information in a simulator model obtained by meta-learning for the first time. Then, we propose an optimized Simulator Attack+ based on this discovery. Our optimization methods used in Simulator Attack+ include: (1) a feature attentional boosting module that uses the feature layer information of the simulator to enhance the attack and accelerate the generation of adversarial examples; (2) a linear self-adaptive simulator-predict interval mechanism that allows the simulator model to be fully fine-tuned in the early stage of the attack and dynamically adjusts the interval for querying the black-box model; and (3) an unsupervised clustering module to provide a warm-start for targeted attacks. Results from experiments on the CIFAR-10 and CIFAR-100 datasets clearly show that Simulator Attack+ can further reduce the number of consuming queries to improve query efficiency while maintaining the attack.
CSR in Poland and the Implementation of Sustainable Development Goals in the Energy Sector during the COVID-19 Pandemic
Authors: Lecka Izabella , Gudowski Janusz , Wołowiec Tomasz
Published: September 2022

The aim of this paper was to examine whether the COVID-19 epidemic has slowed the fulfilment of one of the core tasks of the energy sector “Ensure Access to Affordable, Reliable, Sustainable and Modern Energy for All” (SDG7) taking into account corporate social responsibility. Four research questions and hypotheses were posed, relating to the perspectives of local authorities, the activities of large energy companies, the impact of the epidemic on the implementation of the SDG7 and, in addition, to the understanding of CSR principles from the point of view of ordinary entrepreneurs. A qualitative descriptive analysis based on two reliable databases and a survey procedure (Question 4) was used to answer the research questions posed. The goal was achieved by positively confirming three hypotheses and testing one negatively, relating to COVID-19’s slowing role in SDG7 implementation. The analysis showed that the 2020–2021 epidemic in Poland has led to more initiatives in this area, contrary to expectations. However, they were linked to the simultaneous implementation of other SDGs, which distorted their importance for achieving Goal 7. In summary, although energy companies were more active than expected during the epidemic, they had a low contribution to SDG 7. This also applies to local authorities. An analysis of the knowledge about CSR in a group of entrepreneurs from the Lublin district (case study) confirmed the opinion appearing in the literature about the lack of understanding of the concept and the need for its application.
Economic and Energy Performance of Heating and Ventilation Systems in Deep Retrofitted Norwegian Detached Houses
Authors: Heide Vegard , Thingbø Håkon Selstad , Lien Anne Gunnarshaug , Georges Laurent
Published: September 2022

The aim of this study was to evaluate the life-cycle costs (LCC) and energy performance of different heating and ventilation systems (HVAC) in deep-energy renovation of Norwegian detached houses. Eight different HVAC combinations based on heat pumps are compared using two case buildings, with different performance levels for the building envelope. The case buildings are small wooden dwellings without a hydronic heating system, which is representative of existing Norwegian detached houses. The insulation level had only a limited effect on the relative performance of the various HVAC combinations. Many solutions with medium and higher investments have a payback time close to the technical lifetime. Uncertainty regarding investment costs is important and affects the relative performance between HVAC combinations. Electricity prices also have a decisive influence on the relative performance. Solutions with lower investment costs often lead to low total costs but higher energy use. However, solutions with medium investment cost lead to a significant reduction in energy use and only a minor increase in total costs. Improving the cost-effectiveness of these technologies (reduced investment costs, grants, increased electricity price) would unlock large energy-saving potential. The lack of hydronic distribution systems in existing Norwegian buildings is a barrier to implementing air-to-water and ground-source heat pumps. For the investigated cases, the current government subsidies in Norway do not seem large enough to make investments in deep-energy renovation profitable.
An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function
Authors: Jin Shousong , Chen Yanxi , Shao Yiping , Wang Yaliang
Published: September 2022

There are many factors affecting the assembly quality of rotate vector reducer, and the assembly quality is unstable. Matching is an assembly method that can obtain high-precision products or avoid a large number of secondary rejects. Selecting suitable parts to assemble together can improve the transmission accuracy of the reducer. In the actual assembly of the reducer, the success rate of one-time selection of parts is low, and “trial and error assembly” will lead to a waste of labor, time cost, and errors accumulation. In view of this situation, a dendritic neural network prediction model based on mass production and practical engineering applications has been established. The size parameters of the parts that affected transmission error of the reducer were selected as influencing factors for input. The key performance index of reducer was transmission error as output index. After data standardization preprocessing, a quality prediction model was established to predict the transmission error. The experimental results show that the dendritic neural network model can realize the regression prediction of reducer mass and has good prediction accuracy and generalization capability. The proposed method can provide help for the selection of parts in the assembly process of the RV reducer.
Performance Prediction for a Marine Diesel Engine Waste Heat Absorption Refrigeration System
Authors: Sun Yongchao , Sun Pengyuan , Zhang Zhixiang , Zhang Shuchao , Zhao Jian , Mei Ning
Published: September 2022

The output of the absorption refrigeration system driven by exhaust gas is unstable and the efficiency is low. Therefore, it is necessary to keep the performance of absorption refrigeration systems in a stable state. This will help predict the dynamic parameters of the system and thus control the output of the system. This paper presents a machine-learning algorithm for predicting the key parameters of an ammonia–water absorption refrigeration system. Three new machine-learning algorithms, Elman, BP neural network (BPNN), and extreme learning machine (ELM), are tested to predict the system parameters. The key control parameters of the system are predicted according to the exhaust gas parameters, and the cooling system is adjusted according to the predicted values to achieve the goal of stable cooling output. After comparison, the ELM algorithm has a fast learning speed, good generalization performance, and small test set error sum, so it is selected as the final optimal prediction algorithm.
Analysis of the Structure of Driver Maneuvers in Different Road Conditions
Authors: Jurecki Rafał , Stańczyk Tomasz , Ziubiński Mateusz
Published: September 2022

The safety of road users is one of the priority issues taken into account in both the operation and design of vehicles. The presented work is part of a study that aims to develop a method for parametric assessment of driver behavior. The driving style of a driver depends on their skills and psychophysical characteristics, the type and performance of the vehicle used by the driver, and the type of road. This method involves the continuous measurement of the longitudinal and lateral acceleration values of a vehicle body. The paper analyzes how the type of road influences the structure of the maneuvers undertaken by the driver. The paper formulates criteria for distinguishing basic maneuvers (acceleration, braking, and turning). The structure of maneuvers was analyzed for two parameters: the extreme value of acceleration occurring during the execution of a given maneuver and the frequency of maneuvers during the passage of a given route. The analysis presented in this paper confirms that the type of road has a significant influence on the structure of the maneuvers undertaken by the driver.
Optimisation of Control Algorithm for Hydraulic Power Take-Off System in Wave Energy Converter
Authors: Andersen Niklas Enoch , Mathiasen Jakob Blåbjerg , Carøe Maja Grankær , Chen Chen , Helver Christian-Emil , Ludvigsen Allan Lynggaard , Ebsen Nis Frededal , Hansen Anders Hedegaard
Published: September 2022

Wave energy converters are still a maturing technology and, as such, still face a series of challenges before they can compete with already-established technologies. One of these challenges is optimising the amount of energy extracted from the waves and delivered to the power grid. This study investigates the possibility of increasing the energy output of the existing hydraulic power take-off system of a wave energy converter made by Floating Power Plant during small-scale testing of their hybrid wind and wave energy platform. This system consists of a floater arm that rotates an axle when displaced by the waves. When the axle rotates, two hydraulic cylinders are actuated, displacing oil to run through a hydraulic motor driving an electric generator. The energy extraction is controlled by implementing a control algorithm on a series of on/off valves, which decouples the two hydraulic cylinders driving the hydraulic motor, and by varying the applied torque from the generator to match the wave conditions. Finally, it is investigated whether adding high-pressure pathways to the cylinder pressure chambers is beneficial for maximum power point tracking with reactive control. The analysis is conducted through a numerical model developed in Simulink and verified by comparison to the experimental setup supplied by Floating Power Plant. The study finds that a continuous valve switching strategy is optimal compared to end-point switching and reactive control with high-pressure pathways.
UTC Synchronized Signal Generation for Synchrophasors and Sampled Values Measurements
Authors: Makowiecki Karol , Lisowiec Aleksander , Michalski Pawel , Habrych Marcin
Published: September 2022

This article describes two methods and circuits for generation of a signal synchronized to the Coordinated Universal Time (UTC) time scale. The signal is used as a sampling clock for a synchrophasor and Sampled Values generation. Both methods use a PPS (Pulse Per Second) pulse as a synchronization signal. In the first method, the synchronization procedure is implemented entirely in a Field Programmable Gate Array (FPGA) device. The second method uses a microcontroller and a Temperature Compensated Voltage Controlled Crystal Oscillator (TCVCXO). The common feature of the presented methods is that they are cost effective and use a minimal number of components. This paper presents the implementation details of both methods as well as the measurement results, which show that the accuracy of the synchronized signals in both procedures makes them suitable for use in synchrophasors and sampled values measurements.
Computational Fluid Dynamics and Experimental Analysis of a Wind Turbine Blade’s Frontal Section with and without Arrays of Dimpled Structures
Authors: Aziz Shahid , Khan Abdullah , Shah Imran , Khan Tariq Amin , Ali Yasir , Sohail Muhammad Umer , Rashid Badar , Jung Dong Won
Published: September 2022

Horizontal axis wind turbines are used for energy generation at domestic as well as industrial levels. In the wind turbines, a reduction in drag force and an increase in lift force are desired to increase the energy efficiency. In this research work, computational fluid dynamics (CFD) analysis has been performed on a turbine blade’s frontal section with an NACA S814 profile. The drag force has been reduced by introducing an array of dimpled structures at the blade surface. The dimpled structures generate a turbulent boundary layer flow on its surface that reduces the drag force and modifies the lift force because it has greater momentum than the laminar flow. The simulation results are verified by the experimental results performed in a wind tunnel and are in close harmony with the simulated results. For accurate results, CFD is performed on the blade’s frontal section at the angle of attack (AOA) with a domain of 0° to 80° and at multiple Reynolds numbers. The local attributes, lift force, drag force and pressure coefficient are numerically computed by using the three models on Ansys fluent: the Spalart-Allmaras, the k-epsilon (RNG) and the k-omega shear stress transport (SST).
Power Management and Power Quality System Applied in a Single-Phase Nanogrid
Authors: de Oliveira Fernando Marcos , Mariano Augusto Cesar Santos , Salvadori Fabiano , Ando Junior Oswaldo Hideo
Published: September 2022

This work aims to present an electrical power management system, between a photovoltaic generation system and a battery energy storage system, by using a low-power dual-stage microinverter connected to the electrical distribution network, configuring a nanogrid. The presented system is capable of performing the active power injection of the photovoltaic arrangement, increasing the availability of electrical energy through a maximum power point tracking algorithm. The system is also able to manage the processes of the charge and discharge of the battery system, where the energy storage system will serve as grid support when renewable power is not available. Furthermore, to ensure the quality of electric energy the proposed microinverter also has the characteristic of parallel active filter for suppression of harmonic currents and reactive compensation of local load current, ensuring the quality of electric energy. As a result, this work presents the system topology, modeling and control of electronic converters, the management strategy with its modes of operation and the results of numerical validation of the proposed system.
The Use of Epigenetic Biomarkers as Diagnostic and Therapeutic Options
Authors: Zhang Le , Rath Emma M. , Cheng Yuen Yee
Published: September 2022

The last few decades have brought tremendous advances in the mechanisms of epigenetic regulation, with DNA methylation, histone methylation and acetylation, microRNAs and other noncoding RNAs being among the most prominent [...]
Variation of Fertility and Phenological Synchronization in Cunninghamia lanceolata Seed Orchard: Implications for Seed Production
Authors: Xie Jiaxin , Huang Xin , Liu Yingquan , Zhu Peng , Zhu Yuanwei , Li Fengqing , Yao Jiabao , Chen Lianghua , Yang Hanbo
Published: September 2022

Reproductive synchronicity between parents influences the seed production and quality in seed orchards. Our objective was to determine clonal variation in fertility and phenological synchronization, as well as their effect on seed production, in a Chinese fir (Cunninghamia lanceolata) open-pollinated seed orchard. Significant variation of female fertility and male phenological synchronization occurred in the clones. The flowering of the male was 2 days earlier than the female. The gamete contribution of female and male were unbalanced between clones (the phenological synchronization indexes (POij) were 0.000–0.585 (as female) vs. 0.000–0.385 (as male)). In general, the average POij value of as a male was lower than as a female, but the number of male flowers were significantly higher than female, indicating that the management of female flowers should be enhanced. The average POij of self-pollination was 0.298, higher than cross-pollination (0.236), indicating that there was a larger probability to selfing in the orchard. The middle phenological type possessed higher phenological synchronization indexes than early and late phenological type. Genetic control was stronger for number of female flowers (H2 = 0.277) than for male and female initial stages and flower duration (H2 = 0.193–0.239). We found a positive correlation between POij and TSW (r = 0.756), SOsc (r = 0.612), and Cp (r = 0.337), suggesting the phenological synchronization determined the seed quality and yield. Comprehensively, this study provided fertility and phenology information for management of a Chinese fir seed orchard, as well as a reference for the establishment of advanced seed orchards of conifer trees.
Scaling Region of Weierstrass-Mandelbrot Function: Improvement Strategies for Fractal Ideality and Signal Simulation
Authors: Feng Feng , Zhang Kexin , Li Xinghui , Xia Yousheng , Yuan Meng , Feng Pingfa
Published: September 2022

Fractal dimension (D) is widely utilized in various fields to quantify the complexity of signals and other features. However, the fractal nature is limited to a certain scope of concerned scales, i.e., scaling region, even for a theoretically fractal profile generated through the Weierstrass-Mandelbrot (W-M) function. In this study, the scaling characteristics curves of profiles were calculated by using the roughness scaling extraction (RSE) algorithm, and an interception method was proposed to locate the two ends of the scaling region, which were named corner and drop phenomena, respectively. The results indicated that two factors, sampling length and flattening order, in the RSE algorithm could influence the scaling region length significantly. Based on the scaling region interception method and the above findings, the RSE algorithm was optimized to improve the accuracy of the D calculation, and the influence of sampling length was discussed by comparing the lower critical condition of the W-M function. To improve the ideality of fractal curves generated through the W-M function, the strategy of reducing the fundamental frequency was proposed to enlarge the scaling region. Moreover, the strategy of opposite operation was also proposed to improve the consistency of generated curves with actual signals, which could be conducive to practical simulations.
Specific Classes of Analytic Functions Communicated with a Q-Differential Operator Including a Generalized Hypergeometic Function
Authors: Alarifi Najla M. , Ibrahim Rabha W.
Published: September 2022

A special function is a function that is typically entitled after an early scientist who studied its features and has a specific application in mathematical physics or another area of mathematics. There are a few significant examples, including the hypergeometric function and its unique species. These types of special functions are generalized by fractional calculus, fractal, q-calculus, (q,p)-calculus and k-calculus. By engaging the notion of q-fractional calculus (QFC), we investigate the geometric properties of the generalized Prabhakar fractional differential operator in the open unit disk ∇:={ξ∈C:|ξ|<1}. Consequently, we insert the generalized operator in a special class of analytic functions. Our methodology is indicated by the usage of differential subordination and superordination theory. Accordingly, numerous fractional differential inequalities are organized. Additionally, as an application, we study the solution of special kinds of q–fractional differential equation.
Challenges in Tunneling in the Himalayas: A Survey of Several Prominent Excavation Projects in the Himalayan Mountain Range of South Asia
Authors: KC Diwakar , Gautam Kabindra , Dangi Harish , Kadel Sushma , Hu Liangbo
Published: September 2022

The Himalayas are one of the most unstable regions in the world. Underground excavations are very challenging in this region due to the fragile geology, tectonic activities and complex geological structures. In the present study, three hydropower head race tunnel projects from Nepal, as well as six additional tunnel projects from Bhutan, India and Pakistan located at different parts of the Himalayas, are reviewed with a focus on the common problems encountered during the tunneling and their possible causes and remedies. It is found that rock bursts often occurred around the overburden of 1000 m or higher, while tunnel squeezing problems were commonly observed in a wide range of overburden. Most of the rock failures occurred in sheared zones, thrusts and heavily weathered rock mass. The geological conditions around these projects are often characterized by significant presence of folds, faults, joints and interbedding of different types of rock strata; they are so complex and diverse that it is often difficult to accurately predict the field condition from conventional geotechnical site investigation. In many cases, the presence of shear zones, thrusts and tectonic activities has a strong influence on the in situ stress. Review of these prominent projects suggests that the complicated dynamics between a wide range of geological and geotechnical factors play a critical role in the tunneling in the Himalayas.
Key Factors and AI-Based Risk Prediction of Malnutrition in Hospitalized Older Women
Authors: Larburu Nekane , Artola Garazi , Kerexeta Jon , Caballero Maria , Ollo Borja , Lando Catherine M.
Published: September 2022

The numerous consequences caused by malnutrition in hospitalized patients can worsen their quality of life. The aim of this study was to evaluate the prevalence of malnutrition on the elderly population, especially focusing on women, identify key factors and develop a malnutrition risk predictive model. The study group consisted of 493 older women admitted to the Asunción Klinika Hospital in the Basque Region (Spain). For this purpose, demographic, clinical, laboratory, and admission information was gathered. Correlations and multivariate analyses and the MNA-SF screening test-based risk of malnutrition were performed. Additionally, different predictive models designed using this information were compared. The estimated frequency of malnutrition among this population in the Basque Region (Spain) is 13.8%, while 41.8% is considered at risk of malnutrition, which is increased in women, with up to 16.4% with malnutrition and 47.5% at risk of malnutrition. Sixteen variables were used to develop a predictive model obtaining Area Under the Curve (AUC) values of 0.76. Elderly women assisted at home and with high scores of dependency were identified as a risk group, as well as patients admitted in internal medicine units, and in admissions with high severity.
Molecular Pathogenesis of Follicular Lymphoma: From Genetics to Clinical Practice
Authors: López Cristina , Mozas Pablo , López-Guillermo Armando , Beà Sílvia
Published: September 2022

Follicular lymphoma (FL), a generally indolent disease that derives from germinal center (GC) B cells, represents around 20–25% of all new lymphomas diagnosed in Western countries. The characteristic t(14;18)(q32;q21) translocation that places the BCL2 oncogene under control of the immunoglobulin heavy-chain enhancer occurs in pro- or pre-B cells. However, additional secondary alterations are required for the development of overt FL, which mainly affects genes involved in epigenetic and transcriptional regulation, signaling and B cell differentiation, the BCR/NF-κB pathway, and proliferation/apoptosis. On the other hand, new insights into the FL pathogenesis suggest that FL lacking the BCL2 translocation might be a distinct biological entity with genomic features different from the classical FL. Although FL is considered an indolent disease, around 10–20% of cases eventually transform to an aggressive lymphoma, usually a diffuse large B cell lymphoma, generally by a divergent evolution process from a common altered precursor cell acquiring genomic alterations involved in the cell cycle and DNA damage responses. Importantly, FL tumor cells require interaction with the microenvironment, which sustains cell survival and proliferation. Although the use of rituximab has improved the outlook of most FL patients, further genomic studies are needed to identify those of high risk who can benefit from innovative therapies. This review provides an updated synopsis of FL, including the molecular and cellular pathogenesis, key events of transformation, and targeted treatments.
Research into the Optimal Regulation of the Groundwater Table and Quality in the Southern Plain of Beijing Using Geographic Information Systems Data and Machine Learning Algorithms
Authors: Li Chen , Men Baohui , Yin Shiyang , Zhang Teng , Wei Ling
Published: September 2022

The purpose of this paper is to provide new ideas and methods for the sustainable use of groundwater in areas with serious groundwater overexploitation and serious groundwater pollution. Geographic information systems (GIS) were combined with machine learning algorithms, water resources optimization technology, and groundwater numerical simulation to optimize the regulation of the groundwater table and quality beneath the Daxing District in the southern plain of Beijing. By collecting local consumption and supply data and observations of the groundwater table and quality in the connected aquifer beneath Daxing for the years 2006–2020, the corresponding water demands and groundwater impact were extrapolated for the years 2021–2025 based on the basis of the existing development model. Through the combination of GIS and machine learning algorithms, the NO3-N concentration of local groundwater monitoring points in wet years, normal years, and dry years were predicted. With respect to NO3-N pollution, three new groundwater exploitation regimes were devised, which we numbered 1 to 3. The optimal allocation of water resources was then calculated for wet year, typical year, and dry year scenarios for the year 2025. By comparing the water shortage, groundwater utilization rate, and NO3-N pollution under the new groundwater exploitation regimes, the optimal groundwater exploitation mode for the three different types of hydrological year was determined. The results indicate that NO3-N pollution was greatly reduced after the adoption of the optimal regimes and that the groundwater table demonstrated rapid recovery. These results can be of great help in realizing the management, supervision, and regulation of groundwater by combining GIS with machine learning algorithms.
How Are Macro-Scale and Micro-Scale Built Environments Associated with Running Activity? The Application of Strava Data and Deep Learning in Inner London
Authors: Jiang Hongchao , Dong Lin , Qiu Bing
Published: September 2022

Running can promote public health. However, the association between running and the built environment, especially in terms of micro street-level factors, has rarely been studied. This study explored the influence of built environments at different scales on running in Inner London. The 5Ds framework (density, diversity, design, destination accessibility, and distance to transit) was used to classify the macro-scale features, and computer vision (CV) and deep learning (DL) were used to measure the micro-scale features. We extracted the accumulated GPS running data of 40,290 sample points from Strava. The spatial autoregressive combined (SAC) model revealed the spatial autocorrelation effect. The result showed that, for macro-scale features: (1) running occurs more frequently on trunk, primary, secondary, and tertiary roads, cycleways, and footways, but runners choose tracks, paths, pedestrian streets, and service streets relatively less; (2) safety, larger open space areas, and longer street lengths promote running; (3) streets with higher accessibility might attract runners (according to a spatial syntactic analysis); and (4) higher job density, POI entropy, canopy density, and high levels of PM 2.5 might impede running. For micro-scale features: (1) wider roads (especially sidewalks), more streetlights, trees, higher sky openness, and proximity to mountains and water facilitate running; and (2) more architectural interfaces, fences, and plants with low branching points might hinder running. The results revealed the linkages between built environments (on the macro- and micro-scale) and running in Inner London, which can provide practical suggestions for creating running-friendly cities.
Trimetazidine, an Anti-Ischemic Drug, Reduces the Antielectroshock Effects of Certain First-Generation Antiepileptic Drugs
Authors: Borowicz-Reutt Kinga , Banach Monika
Published: September 2022

Trimetazidine (TMZ), an anti-ischemic drug for improving cellular metabolism, is mostly administered to patients with poorly controlled ischemic heart disease (IHD). Since IHD is considered the most frequent causative factor of cardiac arrhythmias, and these often coexist with seizure disorders, we decided to investigate the effect of TMZ in the electroconvulsive threshold test (ECT) and its influence on the action of four first-generation antiepileptic drugs in the maximal electroshock test (MES) in mice. The TMZ (up to 120 mg/kg) did not affect the ECT, but applied at doses of 20–120 mg/kg it decreased the antielectroshock action of phenobarbital. The TMZ (50–120 mg/kg) reduced the effect of phenytoin, and, when administered at a dose of 120 mg/kg, it diminished the action of carbamazepine. All of these revealed interactions seem to be pharmacodynamic, since the TMZ did not affect the brain levels of antiepileptic drugs. Furthermore, the combination of TMZ with valproate (but not with other antiepileptic drugs) significantly impaired motor coordination, evaluated using the chimney test. Long-term memory, assessed with a passive-avoidance task, was not affected by either the TMZ or its combinations with antiepileptic drugs. The obtained results suggest that TMZ may not be beneficial as an add-on therapy in patients with IHD and epilepsy.
Effects of Combined Pentadecanoic Acid and Tamoxifen Treatment on Tamoxifen Resistance in MCF−7/SC Breast Cancer Cells
Authors: To Ngoc Bao , Truong Vi Nguyen-Phuong , Ediriweera Meran Keshawa , Cho Somi Kim
Published: September 2022

Estrogen receptors are indicators of breast cancer adaptability to endocrine therapies, such as tamoxifen. Deficiency or absence of estrogen receptor α (ER−α) in breast cancer cells results in reduced efficacy of endocrine therapy. Here, we investigated the effect of combined tamoxifen and pentadecanoic acid therapy on ER−α−under−expressing breast cancer cells. Drug resistance gene expression patterns were determined by RNA sequencing analysis and in vitro experiments. For the first time, we demonstrate that the combined treatment of pentadecanoic acid, an odd−chain fatty acid, and tamoxifen synergistically suppresses the growth of human breast carcinoma MCF−7 stem cells (MCF−7/SCs), which were found to be tamoxifen−resistant and showed reduced ER−α expression compared with the parental MCF−7 cells. In addition, the combined treatment synergistically induced apoptosis and accumulation of sub−G1 cells and suppressed epithelial−to−mesenchymal transition (EMT). Exposure to this combination induces re−expression of ER−α at the transcriptional and protein levels, along with suppression of critical survival signal pathways, such as ERK1/2, MAPK, EGFR, and mTOR. Collectively, decreased ER−α expression was restored by pentadecanoic acid treatment, resulting in reversal of tamoxifen resistance. Overall, pentadecanoic acid exhibits the potential to enhance the efficacy of endocrine therapy in the treatment of ER−α−under−expressing breast cancer cells.