bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic MRI segmentation of pectoralis major muscle using deep learning
Authors: Godoy Ivan Rodrigues Barros , Silva Raian Portela , Rodrigues Tatiane Cantarelli , Skaf Abdalla Youssef , de Castro Pochini Alberto , Yamada André Fukunishi 
Published: March 2022

AbstractTo develop and validate a deep convolutional neural network (CNN) method capable of selecting the greatest Pectoralis Major Cross-Sectional Area (PMM-CSA) and automatically segmenting PMM on an axial Magnetic Resonance Imaging (MRI). We hypothesized a CNN technique can accurately perform both tasks compared with manual reference standards. Our method is based on two steps: (A) segmentation model, (B) PMM-CSA selection. In step A, we manually segmented the PMM on 134 axial T1-weighted PM MRIs. The segmentation model was trained from scratch (MONAI/Pytorch SegResNet, 4 mini-batch, 1000 epochs, dropout 0.20, Adam, learning rate 0.0005, cosine annealing, softmax). Mean-dice score determined the segmentation score on 8 internal axial T1-weighted PM MRIs. In step B, we used the OpenCV2 (version 4.5.1,https://opencv.org) framework to calculate the PMM-CSA of the model predictions and ground truth. Then, we selected the top-3 slices with the largest cross-sectional area and compared them with the ground truth. If one of the selected was in the top-3 from the ground truth, then we considered it to be a success. A top-3 accuracy evaluated this method on 8 axial T1-weighted PM MRIs internal test cases. The segmentation model (Step A) produced an accurate pectoralis muscle segmentation with a Mean Dice score of 0.94 ± 0.01. The results of Step B showed top-3 accuracy > 98% to select an appropriate axial image with the greatest PMM-CSA. Our results show an overall accurate selection of PMM-CSA and automated PM muscle segmentation using a combination of deep CNN algorithms.
Parental education related to their children’s health in late childhood and early adolescence for Pacific families within New Zealand
Authors: Schluter Philip J. , Kokaua Jesse , Tautolo El-Shadan , Iusitini Leon , Richards Rosalina , Ruhe Troy 
Published: March 2022

AbstractPacific people continue to carry a disproportionately heavy social and health burden relative to their non-Pacific peers in New Zealand, and those with less formal education are experiencing social and health declines. Improving education and educational needs is seen as being central to decreasing these health inequities. While expansive, the empirical evidence-base supporting this stance is relatively weak and increasingly conflicting. Using a large birth cohort of 1,368 eligible Pacific children, together with their mothers and fathers, this study longitudinally investigates the relationship between paternal education levels and sentinel measures of their children’s physical health, mental health and health risk taking behaviours during late childhood and early adolescence. In adjusted analyses, it was found that mothers and fathers who undertook further schooling over the 0–6 years postpartum period had children with significantly lower logarithmically transformed body mass index increases at 11-years and 14-years measurement waves compared to 9-years levels than those who did not study (p = 0.017 and p = 0.022, respectively). Furthermore, fathers who undertook further schooling over this 0–6 years postpartum period also had children with significantly lower odds of risk taking behaviours (p = 0.013). These results support policy aimed at increasing educational opportunities for Pacific people in New Zealand.
Hydrogen phosphate selectively induces MDA MB 231 triple negative breast cancer cell death in vitro
Authors: Shanti Aya , Al Adem Kenana , Stefanini Cesare , Lee Sungmun 
Published: March 2022

AbstractPhosphate ions are the most abundant anions inside the cells, and they are increasingly gaining attention as key modulators of cellular function and gene expression. However, little is known about the effect of inorganic phosphate ions on cancer cells, particularly breast cancer cells. Here, we investigated the toxicity of different phosphate compounds to triple-negative human breast cancer cells, particularly, MDA-MB-231, and compared it to that of human monocytes, THP-1. We found that, unlike dihydrogen phosphate (H2PO4−), hydrogen phosphate (HPO42−) at 20 mM or lower concentrations induced breast cancer cell death more than immune cell death, mainly via apoptosis. We correlate this effect to the fact that phosphate in the form of HPO42−raises pH levels to alkaline levels which are not optimum for transport of phosphate into cancer cells. The results in this study highlight the importance of further exploring hydrogen phosphate (HPO42−) as a potential therapeutic for the treatment of breast cancer.
Inhibition of triple negative breast cancer-associated inflammation, tumor growth and brain colonization by targeting monoacylglycerol lipase
Authors: Benchama Othman , Tyukhtenko Sergiy , Malamas Michael S. , Williams Mark K. , Makriyannis Alexandros , Avraham Hava Karsenty 
Published: March 2022

AbstractWhile the prevalence of breast cancer metastasis in the brain is significantly higher in triple negative breast cancers (TNBCs), there is a lack of novel and/or improved therapies for these patients. Monoacylglycerol lipase (MAGL) is a hydrolase involved in lipid metabolism that catalyzes the degradation of 2-arachidonoylglycerol (2-AG) linked to generation of pro- and anti-inflammatory molecules. Here, we targeted MAGL in TNBCs, using a potent carbamate-based inhibitor AM9928 (hMAGL IC50 = 9 nM) with prolonged pharmacodynamic effects (46 h of target residence time). AM9928 blocked TNBC cell adhesion and transmigration across human brain microvascular endothelial cells (HBMECs) in 3D co-cultures. In addition, AM9928 inhibited the secretion of IL-6, IL-8, and VEGF-A from TNBC cells. TNBC-derived exosomes activated HBMECs resulting in secretion of elevated levels of IL-8 and VEGF, which were inhibited by AM9928. Using in vivo studies of syngeneic GFP-4T1-BrM5 mammary tumor cells, AM9928 inhibited tumor growth in the mammary fat pads and attenuated blood brain barrier (BBB) permeability changes, resulting in reduced TNBC colonization in brain. Together, these results support the potential clinical application of MAGL inhibitors as novel treatments for TNBC.
Scalable and accurate multi-GPU-based image reconstruction of large-scale ptychography data
Authors: Yu Xiaodong , Nikitin Viktor , Ching Daniel J. , Aslan Selin , Gürsoy Doğa , Biçer Tekin 
Published: March 2022

AbstractWhile the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological specimens, the corresponding experiments can yield terabyte-scale volumes of data that can impose a heavy burden on the computing platform. Although graphics processing units (GPUs) provide high performance for such large-scale ptychography datasets, a single GPU is typically insufficient for analysis and reconstruction. Several works have considered leveraging multiple GPUs to accelerate the ptychographic reconstruction. However, most of these works utilize only the Message Passing Interface to handle the communications between GPUs. This approach poses inefficiency for a hardware configuration that has multiple GPUs in a single node, especially while reconstructing a single large projection, since it provides no optimizations to handle the heterogeneous GPU interconnections containing both low-speed (e.g., PCIe) and high-speed links (e.g., NVLink). In this paper, we provide an optimized intranode multi-GPU implementation that can efficiently solve large-scale ptychographic reconstruction problems. We focus on the maximum likelihood reconstruction problem using a conjugate gradient (CG) method for the solution and propose a novel hybrid parallelization model to address the performance bottlenecks in the CG solver. Accordingly, we have developed a tool, called PtyGer (Ptychographic GPU(multiple)-based reconstruction), implementing our hybrid parallelization model design. A comprehensive evaluation verifies that PtyGer can fully preserve the original algorithm’s accuracy while achieving outstanding intranode GPU scalability.
Route planning for electric vehicles
Authors: Ben Abbes Sirine , Rejeb Lilia , Baati Lasaad 
Published: March 2022

AbstractThis work addresses the multi‐objective route planning and charging problem for Battery Electric Vehicles (BEVs). The proposed solution is based on the NSGA‐II algorithm to derive the Pareto‐optimal set of eco‐routes with the minimum travel and charging time, distance, energy consumption and charging costs while complying with the constraints related to the battery State of Charge (SoC) and the status of charging stations. Influencing factors, such as, vehicle and battery parameters, weather conditions, driver behaviour, road grade, Time Of Use (TOU) electricity cost, and Charging Stations (CS) status and type, are taken into account. The final results of the proposed method are compared with the well‐established simulator SUMO.
A simplified sliding‐mode control method for multi‐level transformerless DVR
Authors: Komurcugil Hasan , Bayhan Sertac , Guler Naki , Abu‐Rub Haitham , Bagheri Farzaneh 
Published: March 2022

AbstractHere, a finite‐control‐set sliding‐mode control (FCS‐SMC) method is proposed for single‐phase three‐level T‐type inverter‐based transformerless dynamic voltage restorers (TDVRs). The inherent advantages of SMC (fast dynamic response and high robustness) are combined with FCS concept to increase the effectiveness of the method in achieving the desired control objectives. First, the use of FCS eliminates the modulator requirement, which reduces the design complexity in the practical implementation. Second, an effective method based on charging/discharging conditions of DC capacitors is proposed for balancing capacitor voltages using relevant switching state rather than combining DC voltage error with the inductor current error through a suitable weighting factor in forming the cost function. Therefore, the weighting factor necessity in the control algorithm is eliminated. Finally, the steady‐state error in the compensation voltage is eliminated by the proportional‐resonant (PR) controller. The studied T‐type inverter‐based TDVR topology offers an alternative solution to the existing DVR topologies. Experimental results are carried out to demonstrate the effectiveness of the proposed FCS‐SMC method in maintaining the load voltage at the desired level despite the voltage sags, swells, and distortions occurring in the grid voltage.
Generalized and symmetric coprime planar array for direction of arrival estimation
Authors: Ren Ming Jian , Hu Guoping , Shi Junpeng , Zhou Hao 
Published: March 2022

AbstractDegrees of freedom and mutual coupling are two important factors to determine the ability of direction of arrival (DOA) estimation. Although coprime planar array (CPPA) has less mutual coupling than hourglass array (HA) and ladder array (LA), its positive and negative covariance corresponding lags are discontinuous, resulting in low degrees of freedom. In this study, we propose a generalized and symmetric coprime planar array (GSCA) by employing the symmetric property of the difference co‐array. By moving one subarray and introducing a supplementary subarray, we construct a connected virtual uniform rectangular array (URA). Through further optimizing the sensor number, the redundant lags are reduced and the array structure is more general. We show that the degrees of freedom are much higher than those of CPPA, HA and LA. Besides, the mutual coupling is close to CPPA, but less than HA and LA. The superiority of GSCA is verified by simulations.
Bats host the most virulent—but not the most dangerous—zoonotic viruses
Authors: Guth Sarah , Mollentze Nardus , Renault Katia , Streicker Daniel G. , Visher Elisa , Boots Mike , Brook Cara E. 
Published: March 2022

Significance
The clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective “burden” on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human–animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.
Autoregulation of switching behavior by cellular compartment size
Authors: Jozsa Monika , Donchev Tihol Ivanov , Sepulchre Rodolphe , O’Leary Timothy 
Published: March 2022

Significance
Biochemical reactions often occur in small volumes within a cell, restricting the number of molecules to the hundreds or even tens. At this scale, reactions are discrete and stochastic, making reliable signaling difficult. This paper shows that the transition between discrete, stochastic reactions and macroscopic reactions can be exploited to make a self-regulating switch. This constitutes a previously unidentified kind of reaction network that may be present in small structures, such as synapses.
Differential elastic scattering cross-section of spin-polarized electron beams impinging on uranium
Authors: Dapor Maurizio 
Published: March 2022

Abstract
We investigate the effects of spin-polarization on the differential elastic scattering cross-section (DESCS) of electrons impinging on uranium atoms using the relativistic partial wave expansion method. The calculations presented here were obtained using the POLARe code. Changes in the shape of the DESCS of keV electron beams due to the transverse spin-polarization of the beam are demonstrated to be particularly intense for specific angles and relatively low energies of the incident beam. They can be used to establish the polarization degree of a given electron beam by comparing the POLARe theoretical calculations with experimental data.
Electron beam pumped light emitting devices
Authors: Cuesta Sergi , Harikumar Anjali , Monroy Eva 
Published: March 2022

Abstract
Electron beam pumping is a promising technique to fabricate compact and efficient light emitters (lamps or lasers) in those spectral ranges where electrical injection is problematic due to doping, transport or contacting issues. Interest in this technology has increased in recent years, particularly driven by the demand for ultraviolet sources and the difficulties in developing efficient AlGaN devices to cover the spectral range of 220–350 nm. The use of a highly energetic electron beam enables the semiconductor structure to be pumped without the need for doping or contacting. The active volume is defined by the acceleration voltage, which allows the homogeneous excitation of a large active volume. The efficiency of cathodoluminescent lamps can compete and even outperform light emitting diode in the deep ultraviolet window, and lasers can deliver high optical power (up to around 100 W). Here, we analyze the advantages and challenges of this technology platform, and discuss its potential applications.
A quality factor of forecasting error for sounding data in MBES
Authors: Zhou Tian , Yuan Weijia , Sun Yang , Xu Chao , Chen Baowei 
Published: March 2022

Abstract
The multi-beam sounding system achieves ultra-wide coverage and high-resolution measurement. Its significantly increased data density has great advantages in accurately depicting the topography of the seabed. However, this requires processing large amounts of data. A preprocessing method that performs in real time automatically identifies outliers in multi-beam bathymetry data, and provides corresponding bathymetry estimates, is able to provide a lot of effective information for the post-processing to improve the data processing efficiency and ensure data quality. In this work, we propose a quality factor (QF) forecasting error (QE) for detecting outliers and forecasting depth in multi-beam bathymetry data. On the basis of the existing QF model for a seabed detection method, and under the assumption of smooth seafloor terrain, we use the QF to select a suitable seabed detection method and eliminate the sounding points that correspond to poor echo characteristics. The uncertainty inferred by the QF is used as the initial parameter for Kalman filter estimation and the depth-value prediction model is formulated. The sounding sequence is sorted by the median value by using the sliding window method. After a second fitting and Kalman filtering, the depth of each point is predicted. A QF model based on forecasting errors is adopted to simplify and unify the outlier detection standards. The selection rules of window length and detection threshold are deeply studied on the basis of simulations performed in this work. For appropriate parameters, the proposed algorithm shows good detection capability for impulse anomalies, cluster anomalies and seabed topography undulations. In addition, the proposed method gives smooth depth-prediction values. Simulation results and analysis show that the proposed algorithm further detects outliers in depth sequences on the basis of the QF and forecasts the sounding points in real time. The QE threshold based on the relative depth is easy to select and is suitable for different sounding systems. This provides effective outlier detection information for post-processing.
Strong reduction of thermal conductivity of WSe2 with introduction of atomic defects
Authors: Wang Bowen , Yan Xuefei , Yan Hejin , Cai Yongqing 
Published: March 2022

Abstract
The thermal conductivities of pristine and defective single-layer tungsten diselenide (WSe2) are investigated by using equilibrium molecular dynamics method. The thermal conductivity of WSe2 increases dramatically with size below a characteristic of ~5 nm and levels off for broader samples and reaches a constant value of ~2 W/mK. By introducing atomic vacancies, we discovered that the thermal conductivity of WSe2 is significantly reduced. In particular, the W vacancy has a greater impact on thermal conductivity reduction than Se vacancies: the thermal conductivity of pristine WSe2 is reduced by ~60% and ~70% with the adding of ~1% of Se and W vacancies, respectively. The reduction of thermal conductivity is found to be related to the decrease of mean free path (MFP) of phonons in the defective WSe2. The MFP of WSe2 decreases from ~4.2 nm for perfect WSe2 to ~2.2 nm with the addition of 0.9% Se vacancies. More sophisticated types of point defects, such as vacancy clusters and anti-site defects, are explored in addition to single vacancies and are found to dramatically renormalize the phonons. The reconstruction of the bonds leads to localized phonons in the forbidden gap in the phonon density of states which leads to a drop in thermal conduction. This work demonstrates the influence of different defects on the thermal conductivity of single-layer WSe2, providing insight into the process of defect-induced phonon transport as well as ways to improve heat dissipation in WSe2-based electronic devices.
Optimization of laser deposited silver nanoparticle substrates for surface-enhanced raman spectroscopy
Authors: Paul Tristan C , Hagen Guy M , Pinchuk Anatoliy O , McNear Kelly L 
Published: March 2022

Abstract
Creating sensitive and reproducible substrates for surface-enhanced Raman spectroscopy (SERS) has been a challenge in recent years. While SERS offers significant benefits over traditional Raman spectroscopy, certain hindrances have limited their commercial use, especially in settings where low limits of detection are necessary. We studied a variety of laser-deposited silver microstructured SERS substrates with different morphology as a means to optimize analyte detection. We found that using a 405 nm laser to deposit lines of silver nanoparticles (AgNPS) from a 2 mM silver nitrate and sodium citrate solution offered not only the best enhancement, but also the most consistent and reproducible substrates. We also found that the probability of deposition by laser was wavelength dependent and that longer wavelengths were less likely to deposit than shorter wavelengths. This work offers a better understanding of the laser deposition process as well as how substrate shape and structure effect SERS signals.
Proteretic device: modelling and implementation in electronics and optical domain
Authors: Khan Salma , Azeemuddin Syed , Sohel Mohammed Arifuddin 
Published: March 2022

Abstract
This paper discusses the phenomena of proteresis, commonly known as inverse hysteresis, and the various methods to implement it. Proteresis generates an advanced response when compared to hysteresis, which improves the system’s speed, maintaining the noise immunity intact. This feature of proteresis is seen in multiple naturally occurring phenomena. The paper implements proteresis in domains of electronics and optics, keeping in view essential constraints like area, power, throughput, and speed. The electronic domain consists of two models, one using CMOS circuits and the other using discrete components. The transistor-level design of a proteretic device is on 180 nm CMOS technology, and proof of concept is demonstrated using post-layout simulations. This design is operated on a supply voltage of 1.8 V and consumes significantly less power of 633 µW at a moderate frequency of 10 MHz. The second implementation utilizes discrete components wherein the operational amplifier (op-amp) is utilized to realize the proteretic design. A discussion on the boundary conditions for switching from hysteretic to proteretic is also presented. This design operates at a supply voltage of 12 V from −6 to +6 V and has a high drive current. Finally, the third implementation is in the optical field using semiconductor ring lasers (SRLs). Rate equations are used to model SRL’s and injection locking phenomenon is applied for switching, which is used for high-speed operations.
Interdisciplinary approach by IT-technologies implementation into the civil procedure
Authors: Chernykh I I 
Published: March 2022

Abstract
This article substantiates that the demand for large research projects of the mega class in the field of social sciences is very high today. The system of regulators of public relations is faced with unprecedented challenges: from the need to develop state and world policies regarding the regulation of the use of AI and cyberspace to the determination of the boundaries of the possible replacement of humans with information technologies. The key aspect in this discourse is the activity of the state to ensure the protection of the rights in civil procedure. In this area, there is a need for an interdisciplinary and transnational nature of research. World legal practice needs a uniform approach to the digitalization of the law, to the status of IT-information, to its use in the cognitive activity of the court1. Introduction