bluuebunny/crossref_metadata_2025 huggingface dataset:
Posterior Sagittal Anorectoplasty for Acquired Imperforate Anus Complicated by Anorectal Necrosis: A Case Report
Authors: Chen Yea-Ling , Su Yu-Tsun , Yeh Ming-Lun , Yang Yung-Ning , Tsai Ching-Chung , Ko Po-Jui
Published: March 2022

Anorectal necrosis is an uncommon lethal disease in children, characterized by necrosis of the mucosa of the anus and rectum. The difference between anorectal necrosis and Fournier’s gangrene is that anorectal necrosis does not affect the genital organs. The treatment for anorectal necrosis includes debridement of the anus, colostomy, and the use of broad-spectrum antibiotics. However, anorectal necrosis may lead to anal stricture, anal malfunction, or even acquired atresia of the anus. There is no consensus on the treatment for acquired imperforate anus. Herein, we report a case of a four-month-old boy with acquired imperforate anus complicated by anorectal necrosis. We describe our experience performing posterior sagittal anorectoplasty to reconstruct a neo-anus in such a rare case.
Microstructure and Corrosion Resistance of an HVAF-Sprayed Al-Based Amorphous Coating on Magnesium Alloys
Authors: Wen Shu , Wang Xiaoming , Ren Zhiqiang
Published: March 2022

An Al86Ni6Y4.5Co2La1.5 amorphous coating was prepared on a ZM5 magnesium alloys substrate by using high-velocity air fuel (HVAF) spray. The coating contained a 75.8% amorphous phase (volume fraction) in addition to the crystallization phases of α-Al, Al4NiY, and Al9Ni5Y3. The microhardness reached 420 HV0.05 for the coating. The coating could endure 500 h neutral salt spray tests without apparent corrosion. Moreover, the coating exhibited a much nobler corrosion potential and two orders of magnitude smaller corrosion current density compared to the substrate. These improvements can be attributed to the compact coating structure and the passive film formed during corrosion.
The Discharge Performance of Mg-3In-xCa Alloy Anodes for Mg–Air Batteries
Authors: Liu Huikun , Zhao Guochen , Li Hang , Tang Shouqiu , Xiu Dapeng , Wang Jin , Yu Huan , Cheng Kaiming , Huang Yuanfeng , Zhou Jixue
Published: March 2022

Considering the advantage of safety and cost, designing a Mg–air battery with high capacity has been highly sought in recent years. However, self-corrosion and passivation of Mg anode critically reduce discharge performance, hindering the large-scale application of Mg–air batteries. In this study, a series of as-cast and extruded Mg-3In-xCa alloys were successfully fabricated. Microstructures, chemical composition, and discharge performance were investigated to optimize the content of Ca (x). The selected Mg–air battery with Mg-3In-3Ca alloy as anode represented the best battery performance, including 0.738 V of discharge voltage, 1323.92 mAh g−1 of specific capacity, and 61.74% of anodic efficiency at discharge current density of 30 mA cm−2. All of its parameters were vastly superior to pure Mg–air battery. In addition, the synergistic effects of In and Ca on promoting electrode properties were evaluated in detail, using SEM and electrochemical analysis, which is expected to trigger follow-up research in designing high-performance Mg–air batteries.
Mineralization Reaction of Calcium Nitrate and Sodium Silicate in Cement-Based Materials
Authors: Belmonte Isabel Miñano , Soler Mariano Calabuig , Saorin Francisco J. Benito , Costa Carlos J. Parra , López Carlos L. Rodríguez , del Pozo Martin Jorge , Pacheco Víctor Martinez , Torrano Pilar Hidalgo
Published: March 2022

The research consists in the design of the new cementitious materials capable of mitigating microfisurative damage through autonomous healing. This lies in the characterization of the materials to employees, study of the expanding agents (sodium silicate and calcium nitrate) and analysis of its mechanical properties and durability. The results revealed that under laboratory conditions, the applied repair agents proved to be powerful in producing an increase in the content of ettringite, favoring the sealing of the fissure. When they heal themselves, they lead to an improvement in durability and mechanical performance.
Compression Behavior of SLM-Prepared 316L Shwartz Diamond Structures under Dynamic Loading
Authors: Ma Qingyan , Li Zhonghua , Li Jiaxin
Published: March 2022

In this paper, the compression behavior of a triply minimal periodic surface (Shwartz Diamond) fabricated by selective laser melting (SLM) under different loading rates was studied. A quasi-static strain rate of 2.22 × 10−3/s was tested using a universal testing machine, and a strain rate of 650/s was tested by Hopkinson pressure bar (SHPB). The results showed that the yield stress of all structures increased under dynamic load, and the DIF of sheet structure was higher than that of the skeleton structure, among which the DIF of GSHD was the largest and most sensitive to strain rate. However, the normalized SEA of USHD was the highest.
Nanocarrier-Based Management of Venous and Arterial Thrombosis
Authors: Haba Mihai Ștefan Cristian , Șerban Dragomir N. , Șerban Ionela Lăcrămioara , Tudorancea Ivona Maria , Haba Raluca Maria , Mărănducă Minela Aida , Tănase Daniela Maria , Iliescu Radu , Tudorancea Ionuț
Published: March 2022

Cardiovascular diseases represent the leading cause of mortality worldwide, with recent epidemiological studies revealing an increasing trend of prevalence and incidence globally. Among cardiovascular disorders, both arterial and venous thrombosis and particularly their acute life-threating complications such as ischemic stroke, acute myocardial infarction, deep venous thrombosis and pulmonary embolism are responsible for more than 25% of all deaths worldwide. The modern approach following progresses in anticoagulant, thrombolytic and antiaggregant therapies has significantly improved the prognoses of these conditions in the last past decades. However, several challenges still remain such as achieving the optimal drug concentration at the injured site, reducing the shortcomings of drug resistance and the incidence of life-threatening hemorrhages. Nanomedicine is a well-known field of medicine in which atomic and molecular structures ranging between 0.1–100 nm are used in various domains due to their specific mechanical, electrical, thermal and magnetic properties. Recent experimental and clinical evidence have shown that nanotechnology could be a safe, effective and an appealing approach for various non-cardiovascular and cardiovascular diseases such as thromboembolic conditions. In this review, we have described the most promising nanotechnology-based approaches not only for the diagnosis, but also for the treatment of vascular thrombotic diseases.
The Clinical Impact of Neoadjuvant Endocrine Treatment on Luminal-like Breast Cancers and Its Prognostic Significance: Results from a Single-Institution Prospective Cohort Study
Authors: Martí Covadonga , Yébenes Laura , Oliver José María , Moreno Elisa , Frías Laura , Berjón Alberto , Loayza Adolfo , Meléndez Marcos , Roca María José , Córdoba Vicenta , Hardisson David , Rodríguez María Ángeles , Sánchez-Méndez José Ignacio
Published: March 2022

Purpose: Neoadjuvant endocrine treatment (NET) has become a useful tool for the downstaging of luminal-like breast cancers in postmenopausal patients. It enables us to increase breast- conserving surgery (BCS) rates, provides an opportunity for us to assess in vivo NET effectiveness, and allows us to study any biological changes that may act as valid biomarkers. The purpose of this study was to evaluate the safety and effectiveness of NET, and to assess the role of Ki67 proliferation rate changes as an indicator of endocrine responsiveness. Methods: From 2016 to 2020, a single-institution cohort of patients, treated with NET and further surgery, was evaluated. In patients with Ki67 ≥ 10%, a second core biopsy was performed after four weeks. Information regarding histopathological and clinical changes was gathered. Results: A total of 115 estrogen receptor-positive (ER+)/HER2-negative patients were included. The median treatment duration was 5.0 months (IQR: 2.0–6.0). The median maximum size in the surgical sample was 40% smaller than the pretreatment size measured by ultrasound (p < 0.0001). The median pretreatment Ki67 expression was 20.0% (IQR: 12.0–30.0), and was reduced to 5.0% (IQR: 1.8–10.0) after four weeks, and to 2.0% (IQR: 1.0–8.0) in the surgical sample (p < 0.0001). BCS was performed on 98 patients (85.2%). No pathological complete responses were recorded. A larger Ki67 fold change after four weeks was significantly related to a PEPI score of zero (p < 0.002). No differences were observed between luminal A- and B-like tumors, with regard to fold change and PEPI score. Conclusions: In our cohort, NET was proven to be effective for tumor size and Ki67 downstaging. This resulted in a higher rate of conservative surgery, aided in therapeutic decision making, provided prognostic information, and constituted a safe and well-tolerated approach.
Evaluation of Expressed MicroRNAs as Prospective Biomarkers for Detection of Breast Cancer
Authors: Mohamed Amal Ahmed , Allam Ahmed E. , Aref Ahmed M. , Mahmoud Maha Osama , Eldesoky Noha A. , Fawazy Naglaa , Sakr Yasser , Sobeih Mohamed Emam , Albogami Sarah , Fayad Eman , Althobaiti Fayez , Jafri Ibrahim , Alsharif Ghadi , El-Sayed Marwa , Abdelgeliel Asmaa Sayed , Abdel Aziz Rania S.
Published: March 2022

Background: Early detection and screening of breast cancer (BC) might help improve the prognosis of BC patients. This study evaluated the use of serum microRNAs (miRs) as non-invasive biomarkers in BC patients. Methods: Using quantitative real-time polymerase chain reaction, we evaluated the serum expression of four candidate miRs (miR-155, miR-373, miR-10b, and miR-34a) in 99 Egyptian BC patients and 40 healthy subjects (as a control). The miRs expression was correlated with clinicopathological data. In addition, the sensitivity and specificity of the miRs were determined using receiver operating characteristic (ROC) curve analysis. Results: Serum miR-155, miR-373, and miR-10b expression were significantly upregulated (p < 0.001), while serum miR-34a was downregulated (p < 0.00) in nonmetastatic (M0) BC patients compared to the control group. In addition, serum miR-155 and miR-10b were upregulated in BC patients with large tumor sizes and extensive nodal involvement (p < 0.001). ROC curve analysis showed high diagnostic accuracy (area under the curve = 1.0) when the four miRs were combined. Serum miR-373 was significantly upregulated in the human epidermal growth factor 2–negative (p < 0.001), estrogen receptor–positive (p < 0.005), and progesterone receptor (PR)-positive (p < 0.024) in BC patients, and serum miR-155 was significantly upregulated in PR-negative (p < 0.001) BC patients while both serum miR-155 and miR-373 were positively correlated with the tumor grade. Conclusions: Circulating serum miR-155, miR-373, miR-10b, and miR-34a are potential biomarkers for early BC detection in Egyptian patients and their combination shows high sensitivity and specificity.
Learning Visible Thermal Person Re-Identification via Spatial Dependence and Dual-Constraint Loss
Authors: Wang Chuandong , Zhang Chi , Feng Yujian , Ji Yimu , Ding Jianyu
Published: March 2022

Visible thermal person re-identification (VT Re-ID) is the task of matching pedestrian images collected by thermal and visible light cameras. The two main challenges presented by VT Re-ID are the intra-class variation between pedestrian images and the cross-modality difference between visible and thermal images. Existing works have principally focused on local representation through cross-modality feature distribution, but ignore the internal connection of the local features of pedestrian body parts. Therefore, this paper proposes a dual-path attention network model to establish the spatial dependency relationship between the local features of the pedestrian feature map and to effectively enhance the feature extraction. Meanwhile, we propose cross-modality dual-constraint loss, which adds the center and boundary constraints for each class distribution in the embedding space to promote compactness within the class and enhance the separability between classes. Our experimental results show that our proposed approach has advantages over the state-of-the-art methods on the two public datasets SYSU-MM01 and RegDB. The result for the SYSU-MM01 is Rank-1/mAP 57.74%/54.35%, and the result for the RegDB is Rank-1/mAP 76.07%/69.43%.
Experimental Study on Wave Characteristics of Stilling Basin with a Negative Step
Authors: Huang Guibing , Diao Mingjun , Jiang Lei , Wang Chuan’ai , Jia Wang
Published: March 2022

Stilling basin with a negative step is an important structure in hydraulic systems, because it can avoid atomization and decrease scouring problems. Although stilling basins with a negative step have attracted much attention from researchers, few researchers have focused on the wave characteristics. In this research, an experimental study on the wave characteristics of stilling basins with a negative step was carried out. The wave height, average period, wave probability density and power spectrum along the flow direction of different stilling basins with a negative step were described based on the wave theory, and the results indicate discharge and step height have a significant effect on the wave characteristics. The relationships between the different characteristic wave heights, and the empirical formula for the relative characteristic wave height are obtained. Finally, the dimensionless standard deviation at the end of the stilling basin with a negative step is linearly related to the flow-energy ratio and the relative step height under B-jump.
The Higher Education Commitment Challenge: Impacts of Physical and Cultural Dimensions in the First-Year Students’ Sense of Belonging
Authors: Dias Diana
Published: March 2022

The students’ perceptions and experiences about the organizational attributes of the higher education institution in which they are enrolled seem to have a strong influence on their integration, sense of belonging, and commitment to their new academic reality. The present paper focuses on the analysis of how first-year students build a sense of belonging and commitment to the higher education institution that welcomes them, focusing on institutional attributes that can act as (positive or negative) catalysts, such as physical and cultural dimensions. However, besides physical and cultural dimensions, it is crucial to consider its synergies with psychological, social, organisational, political, and axiological dimensions that have emerged as critical variables for contextualizing the analysis. The results suggest that the physical dimension nourishes the students’ feelings of belonging, namely through the felt need to develop skills to manage their interaction with the spatial dimension of the institution that welcomes them. Moreover, newcomers’ self-concept seems to be significantly increased by the feeling that they are now part of a cultural but also social elite. On the other hand, the feeling of integration seems to be supported basically on successful peer relationships. This perceived prestige of the higher education institution where they now belong represents, a anteriori, a crucial demand for the career management of the Bourdieu’ “heirs,” and, a posteriori, a real (and sometimes surprising) achievement for first-generation students.
Modeling of Multiscale Wave Interactions Based on an Iterative Scheme of MoM-PO-EPA Algorithm
Authors: Guo Liangshuai , Li Maokun , Xu Shenheng , Yang Fan , Li Jun
Published: March 2022

Electromagnetic modeling of multiscale wave interactions is a challenging task. This is because wave physics exhibit different characteristics at different length scales that require suitable modeling algorithms. Combining these algorithms to model multiscale wave physics requires careful design and tuning. In this study, we investigated a hybrid algorithm based on the method of moment (MoM), iterative physical optics (IPO) approximation, and the equivalence principle algorithm (EPA). EPA modeled targets with details, MoM modeled targets with moderate scales, and IPO modeled electrically large scatterers. The virtual equivalence surfaces in EPA worked as interfaces between relatively large and small scatterers. An iterative scheme is used to solve the targets instead of a matrix equation with large dimensions. This algorithm achieved a good balance between accuracy and efficiency. Numerical examples of modeling the plane-wave scattering of multiscale targets verify its performance for 2D and 3D problems. The iterative scheme can become faster and need less memory usage when solving the multiscale scatterers.
Hybrid Feature Reduction Using PCC-Stacked Autoencoders for Gold/Oil Prices Forecasting under COVID-19 Pandemic
Authors: Samee Nagwan Abdel , Atteia Ghada , Alkanhel Reem , Alhussan Amel Ali , AlEisa Hussah Nasser
Published: March 2022

The financial markets have been influenced by the emerging spread of Coronavirus disease, COVID-19. The oil, and gold as well have experienced a downward trend due to the increased rate in the number of confirmed COVID-19 cases. Lately, the published COVID data comprised new variables that may influence the accuracy of the oil/gold prices forecasting models including the Stringency index, Reproduction rate, Positive Rate, and Vaccinations. In this study, Deep Autoencoders are introduced and combined with the well-known approach: Pearson Correlation Coefficient, PCC, analysis in selecting the key features that affect the accuracy of the forecasting models of gold and oil prices with respect to COVID-19 pandemic. We have utilized a hybrid approach of PCC along with a 2-Stage Stacked Autoencoder, SA, to extract the latent features which are then submitted to Neural Network, NN, regression model. The NN regressor has been trained using the Bayesian Regularization-backpropagation algorithm which provides a good generalization for small noisy datasets. The hybrid approach has yielded the minimum MSE values of 8.97 × 10−3 and 5.356 × 10−2 on the oil/gold validation set, respectively. Compared to the existing approaches, the proposed approach has outperformed the ARIMA, ML based regression models in forecasting the oil/gold prices. In addition, the introduced framework has yielded lower Mean Absolute Error, MAE, than the Recurrent Neural Network, RNN, and the Principal Component Analysis, PCA, for dimension reduction. The retrieved results showed that the hybrid method produced more robust features by considering the relationship between the input features.
Study on Body Size Measurement Method of Goat and Cattle under Different Background Based on Deep Learning
Authors: Li Keqiang , Teng Guifa
Published: March 2022

The feasibility of using depth sensors to measure the body size of livestock has been extensively tested. Most existing methods are only capable of measuring the body size of specific livestock in a specific background. In this study, we proposed a unique method of livestock body size measurement using deep learning. By training the data of cattle and goat with same feature points, different animal sizes can be measured under different backgrounds. First, a novel penalty function and an autoregressive model were introduced to reconstruct the depth image with super-resolution, and the effect of distance and illumination on the depth image was reduced. Second, under the U-Net neural network, the characteristics exhibited by the attention module and the DropBlock were adopted to improve the robustness of the background and trunk segmentation. Lastly, this study initially exploited the idea of human joint point location to accurately locate the livestock body feature points, and the livestock was accurately measured. According to the results, the average accuracy of this method was 93.59%. The correct key points for detecting the points of withers, shoulder points, shallowest part of the chest, highest point of the hip bones and ischia tuberosity had the percentages of 96.7%, 89.3%, 95.6%, 90.5% and 94.5%, respectively. In addition, the mean relative errors of withers height, hip height, body length and chest depth were only 1.86%, 2.07%, 2.42% and 2.72%, respectively.
Performance Comparison of Quantized Control Synthesis Methods of Antenna Arrays
Authors: Pánek David , Orosz Tamás , Karban Pavel , Gnawa Deubauh Cedrick D. , Neghab Hamid Keshmiri
Published: March 2022

There is a great potential in small satellite technology for testing new sensors, processes, and technologies for space applications. Antennas need careful design when developing a small satellite to establish stable communication between the ground station and the satellite. This work is motivated by the design of an antenna array for a future rotatorless base station for the VZLUSAT group of Czech nano-satellites. The realized antenna array must cover a relatively broad range of elevation and azimuth angles, and the control must be fast enough to track the satellite in low Earth orbits. The paper deals with possibilities of synthesis of quantized control of the antenna array. It compares quantization influence for well-known deterministic synthesis methods. It shows the method for decreasing computational cost of synthesis using optimization approach and presents the multi-criteria optimization as a tool for reaching required radiation pattern shape and low sensitivity to quantization at the same time.
Tobacco Spatial Data Intelligent Visual Analysis
Authors: Yang Bo , Tian Dong , Shan Guihua
Published: March 2022

A multi-module visualization framework is designed and a visual analysis system called TobaccoGeoVis is implemented to analyze tobacco spatial data efficiently. The proposed system provides a visualization technology for overlaying multiple graphics on a map to enrich the form of tobacco spatial data visualization. The system also adopts artificial intelligence algorithms and multi-view linkage interactive methods and provides flexible data-attribute field mapping and graphical parameter configuration to analyze tobacco spatial data. We demonstrated that the system is user-friendly and the applied visualization methods are effective using cases selected from the three sets of data.
EOSOLAR Project: Assessment of Wind Resources of a Coastal Equatorial Region of Brazil—Overview and Preliminary Results
Authors: Assireu Arcilan T. , Pimenta Felipe M. , de Freitas Ramon M. , Saavedra Osvaldo R. , Neto Francisco L. A. , Júnior Audálio R. Torres , Oliveira Clóvis B. M. , Lopes Denivaldo C. P. , de Lima Shigeaki L. , Veras Rafael B. S. , Saraiva Natália P. , Marcondes Luiz G. P. , Oliveira Denisson Q.
Published: March 2022

The EOSOLAR project was designed to investigate the structure of the atmospheric boundary layer in an equatorial coastal zone, where the discontinuity of surface conditions induces non-stationarity gradients of wind speeds and the development of internal boundary layers. The proposed methodology considers several aspects of the sea–land transition meteorology that are essential for precisely estimating wind–solar energy potential and assessment of structural loads on wind turbines. Infrared (LIDAR) and acoustic (SODAR) ground-based remote sensing instruments and micrometeorological towers were installed in a near-shore equatorial area of northeast Brazil, in order to provide a comprehensive view of meteorological processes. This paper reports a description of the project study area, methodology, and instrumentation used. Details of instruments configurations, a validation of micrometeorology towers, and a comparison between the LIDAR and SODAR are presented. Results of the first field campaign measuring the coastal flow, integrating the micrometeorological tower and LIDAR observations are described.
Synthesis of Application-Optimized Air Gap Field Distributions in Synchronous Machines
Authors: Palka Ryszard
Published: March 2022

This paper deals with the method of shaping the magnetic field distribution in the air gap of a synchronous machine. The main goal is to obtain a specific distribution of the magnetic field in the machine’s air gap to enable easier powering, to increase the torque and power density, or to limit the content of higher harmonics in the induced voltage and torque. This method can be applied for both the electrically excited machines and permanent magnets excited machines. The problem has been reduced to solving a modified system of algebraic equations obtained by the finite element method. The presented examples show the effectiveness of the proposed method both in shaping the contours of the air gap and the magnetization of permanent magnets placed on the rotor. The method can particularly be used in the design of the high-speed synchronous machines.
Optimal Management for EV Charging Stations: A Win–Win Strategy for Different Stakeholders Using Constrained Deep Q-Learning
Authors: Paraskevas Athanasios , Aletras Dimitrios , Chrysopoulos Antonios , Marinopoulos Antonios , Doukas Dimitrios I.
Published: March 2022

Given the additional awareness of the increasing energy demand and gas emissions’ effects, the decarbonization of the transportation sector is of great significance. In particular, the adoption of electric vehicles (EVs) seems a promising option, under the condition that public charging infrastructure is available. However, devising a pricing and scheduling strategy for public EV charging stations is a non-trivial albeit important task. The reason is that a sub-optimal decision could lead to high waiting times or extreme changes to the power load profile. In addition, in the context of the problem of optimal pricing and scheduling for EV charging stations, the interests of different stakeholders ought to be taken into account (such as those of the station owner and the EV owners). This work proposes a deep reinforcement learning-based (DRL) agent that can optimize pricing and charging control in a public EV charging station under a real-time varying electricity price. The primary goal is to maximize the station’s profits while simultaneously ensuring that the customers’ charging demands are also satisfied. Moreover, the DRL approach is data-driven; it can operate under uncertainties without requiring explicit models of the environment. Variants of scheduling and DRL training algorithms from the literature are also proposed to ensure that both the conflicting objectives are achieved. Experimental results validate the effectiveness of the proposed approach.
Current Status and Future Trends of Power Quality Analysis
Authors: Remigio-Carmona Paula , González-de-la-Rosa Juan-José , Florencias-Oliveros Olivia , Sierra-Fernández José-María , Fernández-Morales Javier , Espinosa-Gavira Manuel-Jesús , Agüera-Pérez Agustín , Palomares-Salas José-Carlos
Published: March 2022

In this article, a systematic literature review of 153 articles on power quality analysis in PV systems published in the last 20 years is presented. This provides readers with an overview on PQ trends in several fields related to instrumental techniques that are being used in the smart grid to visualize the quality of the energy, establishing a solid literature base from which to start future research. A preliminary appreciation allows us to intuit that higher-order statistics are not implemented in measurement equipment and that traditional instrumentation is still used for the performance of measurement campaigns, not yielding the expected results since the information processed does not come from an electrical network from 20 years ago. Instead, current networks contain numerous coupled load effects; thus, new disturbances are not simple; they are usually complex events, the sum of several types of disturbances. Likewise, depending on the type of installation, the objective of the PQ analysis changes, either by detecting certain events or simply focusing on seeing the state of the network.
Physical Model Test and Heat Transfer Analysis on Backfilling Construction of Qinghai-Tibet Transmission Line Tower Foundation
Authors: Zhang Jun , Zhou Chenglin , Zhang Ze , Melnikov Andrey , Jin Doudou , Zhang Shengrong
Published: March 2022

The cone-cylindrical pile foundation is a kind of shallow buried foundation, which needs to be open excavated and backfilled during construction. The density of the backfill is closely related to the refreezing process of the backfill. However, there is still a lack of relevant research on the relationship between backfill density and the refreezing process of backfill. The method of model experiment is selected to study the refreezing process of backfill under three backfill soil densities. The controlled density of backfill is 1.83, 1.62 and 1.36 g/cm3, and the times of freeze–thaw cycle is 14, 22 and 39, respectively. The main research findings are as follows: First, the effect of the initial temperature of the backfill on the refreezing is mainly reflected in the first three freeze–thaw cycles; the second is that the higher the density of the backfill, the faster the backfill responds to changes in outside air temperature, and the shorter the freezing time; third, the pile foundation is a good conductor of heat, which will cause the soil temperature change on the pile side to be significantly greater than that of the natural soil, and the temperature change of the pile foundation surface is greater than that of the backfill. The research results can provide a reference for the backfill construction of pile foundations in cold regions and the selection of boundary conditions for related numerical simulations.
Exploring Different Binders for a LiFePO4 Battery, Battery Testing, Modeling and Simulations
Authors: Baboo Joseph Paul , Yatoo Mudasir A. , Dent Matthew , Hojaji Najafabadi Elaheh , Lekakou Constantina , Slade Robert , Hinder Steven J. , Watts John F.
Published: March 2022

This paper focuses on the LiFePO4 (LFP) battery, a classical and one of the safest Li-ion battery technologies. To facilitate and make the cathode manufacture more sustainable, two Kynar® binders (Arkema, France) are investigated which are soluble in solvents with lower boiling points than the usual solvent for the classical PVDF binder. Li-LFP and graphite-Li half cells and graphite-LFP full cells are fabricated and tested in electrochemical impedance spectroscopy, cyclic voltammetry (CV) and galvanostatic charge-discharge cycling. The diffusion coefficients are determined from the CV plots, employing the Rendles-Shevchik equation, for the LFP electrodes with the three investigated binders and the graphite anode, and used as input data in simulations based on the single-particle model. Microstructural and surface composition characterization is performed on the LFP cathodes, pre-cycling and after 25 cycles, revealing the aging effects of SEI formation, loss of active lithium, surface cracking and fragmentation. In simulations of battery cycling, the single particle model is compared with an equivalent circuit model, concluding that the latter is more accurate to predict “future” cycles and the lifetime of the LFP battery by easily adjusting some of the model parameters as a function of the number of cycles on the basis of historical data of cell cycling.
Smart Metering Roll-Out in Europe: Where Do We Stand? Cost Benefit Analyses in the Clean Energy Package and Research Trends in the Green Deal
Authors: Vitiello Silvia , Andreadou Nikoleta , Ardelean Mircea , Fulli Gianluca
Published: March 2022

2020 was a key year for several targets in European energy and climate policy, including the requirement for European countries to deploy smart metering for at least 80% of electricity consumers. This target was set to ease the transition towards a consumer-centered and digitalized energy system. In fact, there are numerous applications that are facilitated or are directly linked to smart meters. Among others: demand response programs that enable consumers to be active in the energy market, and remote grid monitoring by the Distribution System Operator. In this paper, we analyze the initial provisions of the Third Energy Package and those of the Clean Energy Package, with particular focus on the recently approved directive on common rules for the internal market for electricity and the newly introduced smart meters specifications. We present the highlights of the national cost–benefit analyses for smart metering roll-out, focusing on the decisions made by the Member States with respect to a potential smart meter roll-out, that was targeted to be completed by 2020 and present the current situation of smart metering roll-out. We also present and categorize some of the R&I smart grid projects realized over recent years, focusing on the ones that deal with smart metering integration in order to depict the smart metering applications and technologies tested on the ground. Therefore, this paper portrays a full picture with respect to smart meters in Europe today and gives insights for monitoring smart metering roll-outs taking into account the current trends in smart metering applications.
Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies
Authors: Ruiz Duarte José Luis , Fan Neng
Published: March 2022

The international community has set ambitious targets to replace the use of fossil fuels for electricity generation with renewable energy sources. The use of large-scale (e.g., solar farms) and small-scale solutions (e.g., onsite green technologies) represents one way to achieve these goals. This paper presents a mathematical optimization framework to coordinate the energy decisions between the distribution network and the networked microgrids embedded within it. Utility-scale renewable and conventional generators are considered in the distribution network, while the microgrids include onsite renewable generation and energy storage. The distribution network operator utilizes demand-side management policies to improve the network’s efficiency, and the microgrids operate under these programs by reducing their energy usage, scheduling the electricity usage under dynamic tariffs, and supplying energy to the grid. The uncertainty of renewable energy sources is addressed by robust optimization. The decisions of the distribution network and the microgrids are made independently, whereas the proposed collaboration scheme allows for the alignment of the systems’ objectives. A case study is analyzed to show the capability of the model to assess multiple configurations, eliminating the necessity of load shedding, and increasing the power supplied by the microgrids (22.3 MW) and the renewable energy share by up to 5.03%.
Precipitation and Streamflow Reconstructions from Tree Rings for the Lower Kızılırmak River Basin, Turkey
Authors: Genç Sena , Güner Hüseyin Tuncay
Published: March 2022

The Kızılırmak River is the longest inland river, has the second-largest basin, and is one of the most important water sources of Turkey. On the other hand, flow data in the basin are too short-term and discordant, with too many gaps to provide reliable information regarding variations in river runoff. In this research, we reconstructed the April–July total precipitation and mean April–August streamflow of Gökırmak River at one gauge in the lower Kızılırmak River Basin using seven regional tree-ring chronologies. Tree-ring chronologies were highly correlated with the precipitation from April to July and with the streamflow from April to August. Both reconstructions successfully explained total variance in instrumental records with 0.36 (precipitation) and 0.35 (streamflow) R2 values. We provided 210 years (1794–2003) of precipitation and streamflow reconstructions, which largely overlapped. Five extreme dry (1840, 1842, 1873, 1887, and 1947) and four extreme wet years (1829, 1837, 1814 and 1881) were determined. The longest consecutive drought and wet events were three years long, for the periods of 1926–1928 and 1835–1837, respectively. The 13-year low-pass filter values highlighted a 30-year-long (from 1843 to 1872) stationary period of April–August mean streamflow.
Why Masses of Binary Black Hole Mergers Are Overestimated?
Authors: Křížek Michal , Somer Lawrence
Published: March 2022

We show that masses of binary black hole mergers are overestimated, since a large gravitational redshift is not taken into account. Such a phenomenon occurs due to time dilation in a close neighborhood of any black hole. This fact allows us to explain a high mass gap between observed binary neutron stars and calculated binary black hole mergers. We also present other reasons why masses of black hole mergers are determined incorrectly.
Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases
Authors: Videtič Paska Alja , Alič Urban , Zupanc Tomaž , Kouter Katarina
Published: March 2022

Suicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silico analysis algorithm that would help select the best suitable miRNAs that target the most interesting genes associated with suicidality. We used databases/web algorithms DIANA microT, miRDB, miRmap, miRWalk, and TargetScan and candidate genes SLC6A4, HTR1A, BDNF, NR3C1, ZNF714, and NRIP3. Based on a prediction algorithm, we have chosen miRNAs that are targeting regulation of the genes listed, and are at the same time being expressed in the brain. The highest ranking scores were obtained for hsa-miR-4516, hsa-miR-3135b, hsa-miR-124-3p, hsa-miR-129-5p, hsa-miR-27b-3p, hsa-miR-381-3p, hsa-miR-4286. Expression of these miRNAs was tested in the brain tissue of 40 suicide completers and controls, and hsa-miR-4516 and hsa-miR-381-3p showed a trend for statistical significance. We also checked the expression of the target genes of these miRNAs, and for NR3C1 expression was lower in suicide completers compared to controls, which is in accordance with the available literature results. To determine the miRNAs that are most suitable for further suicidality research, more studies, combining in silico analysis and wet lab experiments, should be performed.
Global Screening and Functional Identification of Major HSPs Involved in PVY Infection in Potato
Authors: Li Kun , Chen Ruhao , Tu Zheng , Nie Xianzhou , Song Botao , He Changzheng , Xie Conghua , Nie Bihua
Published: March 2022

HSP40 (also known as DnaJ), HSP70, and HSP90 are major heat shock protein (HSP) families that play critical roles in plant growth and development and stress adaption. Recently, several members of the three HSP families were reported to be widely involved in the plant host-virus interactions. However, their global expression profiles and core members recruited by viruses are largely unknown. In this study, a total of 89 StDnaJs were identified from a genome-wide survey, and their classification, phylogenetic relationships, chromosomal locations, and gene duplication events were further analyzed. Together with 20 StHSP70s and 7 StHSP90s previously identified in the potato genome, the global expression patterns of the members in 3 HSP families were investigated in 2 potato cultivars during Potato virus Y (PVY) infection using RNA-seq data. Of them, 16 genes (including 8 StDnaJs, 6 StHSP70s, and 2 StHSP90s) were significantly up- or downregulated. Further analysis using qRT-PCR demonstrated that 7 of the 16 genes (StDnaJ06, StDnaJ17, StDnaJ21, StDnaJ63, StHSP70-6, StHSP70-19, and StHSP90.5) were remarkably upregulated in the potato cultivar ‘Eshu 3’ after PVY infection, implying their potential roles in the potato-PVY compatible interaction. Subsequent virus-induced gene silencing (VIGS) assays showed that silencing of the homologous genes of StDnaJ17, StDnaJ21, StHSP70-6, and StHSP90.5 in Nicotiana. benthamiana plants dramatically reduced the accumulation of PVY, which indicated the four genes may function as susceptibility factors in PVY infection. This study provides candidate genes for exploring the mechanism of potato-PVY compatible interaction and benefits breeding work aiming to produce new cultivars with the ability to grow healthily under PVY infection.
Mapping Underwater Bathymetry of a Shallow River from Satellite Multispectral Imagery
Authors: Salavitabar Shayan , Li S. Samuel , Lak Behzad
Published: March 2022

Rivers play an important role in water supply, waterway transport, and riverine species habitations. The underwater depth of a river channel is a fundamental geometric element and a key input to studies for the aforementioned and other applications. Traditional in-situ field surveys for flow depth measurements would incur high costs and encounter technical and/or logistical difficulties, particularly for river channels of large extents, very shallow channels, and remote, inaccessible channels. Recent advances in satellite remote sensing of inland water bodies like rivers, streams, and creeks have allowed mapping flow depth in an inexpensive, convenient, and efficient manner. The purpose of this paper is to demonstrate the retrieval of river flow depth from high-resolution (1.2 m) WorldView-3 satellite imagery. The depth retrieval methods are based on the ratio of top-of-atmosphere reflectance between two pairing wavelength bands of multispectral imagery. The originality of the methods lies in using analytical relationships without resorting to ground data of river flow depth for calibration, which improves from previous studies of remote sensing of river flow depth. The methods are successfully applied to mapping the underwater bathymetry of a 26 km reach of the Nicolet River in Quebec, Canada. This study shows the importance of geometric and radiometric corrections to the satellite images. The obtained flow depths using the ratio of reflectance of the red band (630–690 nm) to that of the green band (510–580 nm), among the eight bands in the visible spectrum, agree best with in-situ measurements. This study is perhaps the first use of the analytical approach for mapping river bathymetry. It is feasible to implement the approach to other river channels, with a good potential to reduce the costs and increase the efficiency of mapping river bathymetries.
The Absolute Age and Origin of the Giant Gypsum Geode of Pulpí (Almería, SE Spain)
Authors: Gázquez Fernando , Monteserín Ana , Obert Christina , Münker Carsten , Fernández-Cortés Ángel , Calaforra José María
Published: March 2022

Subaqueous gypsum (CaSO4·2H2O) crystals are relatively common in epithermal systems where sulfide ore deposits are present. The Giant Geode of Pulpí (Almería, SE Spain) hosts some of the largest (up to 2 m in length) subaqueous gypsum crystals discovered to date. Here, we present the first U-series ages of its crystals and reconstruct the oxygen and hydrogen isotopic composition (δ18O and δ2H) of the Pulpí paleo-aquifer from which the crystals formed by using stable isotopes of gypsum hydration water. We successfully dated the onset of gypsum precipitation in the Geode at 164 ± 15 ka. However, the extremely low U concentration (11 ppb) and relatively high detrital Th content (230Th/232Th 3.2) hinder accurate dating other gypsum samples. The δ18O and δD values of the paleo-aquifer during the growth of the crystals aligned with the local meteoric water line, suggesting that the sulfate-enriched mother solution consisted of meteoric water that recharged the aquifer during that period. The mean isotopic composition of the Pulpí paleo-aquifer (δ18O = −6.5 ± 0.1‰ and δ2H = −42.3 ± 0.5‰) during the formation of the crystals was similar to the current groundwater in this area (δ18O = −6.1 ± 0.8‰, δ2H = −42 ± 6‰). The isotopic differences observed in samples collected from distinct locations and in individual crystals were probably related to changes in the isotopic composition of the aquifer, as a consequence of varying climate that impacted on the isotopic composition of rainwater during thousands of years in this region. Our results indicated that subaqueous selenite crystals may be useful for paleo-hydrological reconstructions. However, improving the current analytical techniques for dating gypsum with low U concentrations will be essential to obtain accurate and reliable records from Quaternary gypsum cave crystals in the future.
Heart Failure in Older Adults: Medical Management and Advanced Therapies
Authors: Liu Ellen , Lampert Brent C.
Published: March 2022

As the population ages and the prevalence of heart failure increases, cardiologists and geriatricians can expect to see more elderly patients with heart failure in their everyday practice. With the advancement of medical care and technology, the options for heart failure management have expanded, though current guidelines are based on studies of younger populations, and the evidence in older populations is not as robust. Pharmacologic therapy remains the cornerstone of heart failure management and has improved long-term mortality. Prevention of sudden cardiac death with implantable devices is being more readily utilized in older patients. Advanced therapies have provided more options for end-stage heart failure, though its use is still limited in older patients. In this review, we discuss the current guidelines for medical management of heart failure in older adults, as well as the expanding literature on advanced therapies, such as heart transplantation in older patients with end-stage heart failure. We also discuss the importance of a multidisciplinary care approach including consideration of non-medical co-morbidities such as frailty and cognitive decline.
Is Altered Oculomotor Control during Smooth Pursuit Neck Torsion Test Related to Subjective Visual Complaints in Patients with Neck Pain Disorders?
Authors: Majcen Rosker Ziva , Vodicar Miha , Kristjansson Eythor
Published: March 2022

Subjective visual complaints are commonly reported in patients with neck pain, but their relation to objectively measured oculomotor functions during smooth pursuit neck torsion tests (SPNTs) has not yet been investigated. The aim of the study was to analyse classification accuracy of visual symptom intensity and frequency based on SPNT results. Forty-three patients with neck pain were referred by orthopaedic outpatient clinics where they were required to fill out 16-item proformas of visual complaints. Infrared video-oculography was used to measure smooth pursuit eye movements during neutral and neck torsion positions. Parameters of gain and SPNT difference (SPNTdiff) were taken into the Naïve Bayes model as classifiers, while intensity and frequency of visual symptoms were taken as predicted class. Intensity and, to a lesser degree, frequency of visual symptoms previously associated with neck pain or focal vision disorders (computer vision syndrome) showed better classification accuracy using gain at neck torsion position, indicating cervical driven visual disturbances. Moreover, SPNTdiff presented with slightly lower classification accuracy as compared to gain at neck torsion position. Our study confirmed the relationship between cervical driven oculomotor deficits and some visual complaints (concentrating to read, words moving on page, blurred vision, difficulty judging distance, sore eyes, heavy eyes, red eyes, and eyes strain).