bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the Accuracy for Amplitude and Frequency of Analytical Equation of Single-ended Ring Oscillators Based on Circuit and Transistor Parameters
Authors: Moradnezhad Mehrdad , Miar-Naimi Hossein 
Published: August 2022

Abstract

The analytical relationships presented for amplitude and frequency of the ring oscillator are derived approximately due to the nonlinear nature of this oscillator. In the case where the transistors experience the cut-off region, the relationships presented so far have no connection between the frequency and the dimensions of the transistor, which is not valid in practice. In this paper, considering the circuit's governing equation and the ring oscillator's output waveform, a relation for the frequency is presented, including the dimensions of the transistor. Also, a simple and approximately accurate relationship for the oscillator amplitude is provided in this case. The validity of these relationships has been investigated by analyzing and simulating a single-ended oscillator in 0.18µm technology.
Comprehensive analysis of THz metasurface imaging for glioblastoma in orthotopic xenograft mouse model
Authors: Seo Minah , Roh Yeeun , Kim Kyu-hyeon , Lee Geon , Lee Jinwoo , Kim Taeyeon , Shin Beomju , Lee Taikjin , Kang Dong Min , Kim Yun Kyung 
Published: August 2022

Abstract
Terahertz optical detection and imaging technologies demonstrate great potential and challenges in various bio-applications and medical tools owing to low-energy non-ionizing characteristics and ultra-broadband spectral information, including many molecular fingerprints. Furthermore, recent advances in the terahertz sensing platform have accelerated the applicability with the help of various metasurfaces and enhanced the performance of optical detection and imaging technologies in terms of sensitivity and selectivity. This study demonstrates a highly advanced label-free terahertz imaging technique based on the enhanced signal via terahertz metasurface and further treatment exploiting an artificial neural network for mouse brain imaging beyond the absorption cross-section limit. The criteria for extracting the glioma part using the algorithm with more than 99% accuracy was verified using the fluorescence-labeled images as training sets. An accurate complex refractive index for brain cancer and normal tissues to expand the capability for the potential clinical applications of terahertz radiation was determined using a reliable numerical solution based on the finite element method simulation.
Experimental Investigation of an External Discharge Very Low Power (&lt;20W) Hall Thruster
Authors: Hamo Omri , Lev Dan R. , Rubanovich Maxim , Kapulkin Alexander , Lefkowitz Joseph 
Published: August 2022

Abstract
A sub 20 W wall-less Hall Effect Thruster (HET) was developed at the Asher Space Research Institute (ASRI), Technion. In this work, an initial study of the thruster performance and underlying physics was conducted. It was found that the anode efficiency of the thruster was low (~1%), mainly due to the low mass utilization efficiency. Typical performance figures are 90 μN of thrust, specific impulse of 90 s and anode efficiency of ~1% at 3-4 W anode power. The thruster far-field plume was analyzed using a retarding potential analyzer. It was found that the beam divergence was relatively low at 57.7° (for 95% of the beam current) compared to other wall-less HETs. The voltage utilization efficiency was 38% for a discharge voltage of 1 kV and a mass flow rate of 1 sccm xenon. We speculate that the leading driver to the low mass utilization efficiency is the small ionization fraction associated with these very low power wall-less devices. It was found that the beam efficiency can be over 90% at discharge power levels < 3 W, and decreases with power down to less than 50%.
Partition defective 3 promotes TAZ nuclear localization and promotes Amphiregulin transcription to promote liver hepatocellular carcinoma cell invasion, migration and epithelial mesenchymal
Authors: Fu Hai-Yan , Wang Qiu-Hong , Li Hong-Juan , Gao Jian-Peng , Liu Li , Tang Bo , Wei Dong , Xu Bin , Tong Xin , Li Jie , Luo Yu 
Published: August 2022

Abstract
Background
Partition defective 3 (PARD3) regulates cell polarity and functions as a cancer promoting or tumor suppressor in different cancer types. PARD3 was reported to be highly expressed in liver hepatocellular carcinoma (LIHC) tissues and high expression of PARD3 was significantly associated with poor clinicopathological features and lower overall survival, but whether PARD3 regulated invasion, migration and epithelial mesenchymal transition (EMT) in LIHC has not been reported.
Objectives
To investigate the effect and mechanism of PARD3 on LIHC cell invasion, migration and EMT.
Methods
PARD3 expression in LIHC tumor group and relationship with survival were queried according to the GEPIA website. PARD3 mRNA and protein expression in 41 clinical samples were determined by RT-qPCR and immunohistochemistry (IHC), respectively. PARD3, transcriptional coactivator with PDZ-binding motif (TAZ)and amphiregulin ༈AREG༉expression in HepG2 cells with overexpression or knockdown, and the expression of PARD3, TAZ, AREG and EMT related proteins were determined by Western blot. Transwell assay for HepG2cell invasion ability. The migration ability of HepG2 cells was detected by wound healing experiments. TAZ localization was detected by immunofluorescence. Co-IP detected the effect of PARD3 on TAZ and TAZ TEAD binding. The effect of TAZ on AREG transcript levels was examined by RT-qPCR.
Results
PARD3 was found to be highly expressed in LIHC tumor group by GEPIA website query, and the expression of PARD3 gradually increased with increasing tumor stage, and high expression of PARD3 usually means low overall survival in LIHC. We also found that PARD3 was highly expressed in LIHC tissues. Knockdown of PARD3 inhibited HepG2 cell invasion, migration and EMT, while overexpression of PARD3 played the opposite role. Moreover, PARD3 promotes AREG transcription by promoting TAZ nuclear localization, which in turn promotes LIHC cell invasion, migration and EMT.
Conclusion
PARD3 promotes TAZ nuclear localization and promotes AREG transcription to promote epithelial mesenchymal transition in LIHC.
Economics at the FTC: Estimating Harm from Deception and Analyzing Mergers
Authors: Vita Michael , Brand Keith , Larson-Koester Miriam , Petek Nathan , Taragin Charles , Violette William , Wood Daniel H. 
Published: August 2022

Abstract
Economists in the Federal Trade Commission’s Bureau of Economics perform economic analysis in support of the Commission’s dual missions to protect consumers and competition by preventing anticompetitive, deceptive, and unfair business practices through law enforcement, advocacy, and education. This article first presents summaries of analyses economists performed to estimate the consumer harm from two different types of deception involving misleading information about lease terms and suppression of negative product reviews. The essay next turns to economic analysis of mergers, first considering vertical issues that arose in a semiconductor merger and then, finally, a discussion of how complementarity between hospitals may impact the analysis of hospital mergers.
Vitamin D Level, pain severity and Quality of life among hemodialysis patients: a cross-sectional study
Authors: Ishtawi Shaima , Jomaa Dana , Nizar Aisha , Abdalla Mazen , Hamdan Zakaria , Nazzal Zaher 
Published: August 2022

Abstract
Background
Pain is a common complaint among hemodialysis patients. End-stage renal disease patients are at high risk of vitamin D deficiency and poor Quality of life (QoL). This study aims to find the prevalence of chronic pain and its correlation with QoL and vitamin D level among hemodialysis patients in Palestine.
Methods
This cross-sectional study was conducted between October 2021 to February 2022 at the hemodialysis unit of An-Najah National University Hospital, Palestine. We used the brief pain inventory, the medical outcomes study 36-item short-form health survey, and Serum 25-hydroxyvitamin D to assess chronic pain, QoL, and vitamin D deficiency. A multiple linear regression analysis models determined the correlation between the QoL scores and other independent variables.
Results
The study included 200 patients, 38.1% (95% CI: 31.3–45.4%) of whom had chronic pain and 77.7% (95% CI: 71.0-83.4%) had deficient Vitamin D levels. QoL scores were generally low, with the highest score in social functioning, followed by mental health, while the lowest was found in role emotional and physical functioning. Sex, number of comorbidities, and vitamin D level are significantly correlated with pain severity. Employment, numbers of comorbidities, pain severity, and albumin level are significantly associated with the Physical component of QoL. On the other hand, employment and pain severity are significantly related to the mental component of QoL.
Conclusions
Low vitamin D levels, chronic pain, and low QoL scores are common among hemodialysis patients. Vitamin D is negatively correlated with pain severity. Unemployment, comorbidities, severe pain, and low level of albumin are associated with reduced QoL scores. Healthcare workers should assess and manage HD patients' chronic pain to improve their QoL and reduce suffering.
Interchange reconnection within coronal holes powers the fast solar wind
Authors: Bale Stuart , Drake James , McManus Michael , Desai Mihir , Badman Samuel , Larson Davin , Swisdak Marc , Raouafi Nour , Phan Tai , Velli Marco , McComas David , Cohen Christina , Mitchell Donald , Panasenco Olga , Kasper Justin 
Published: August 2022

Abstract
The fast solar wind that fills the heliosphere originates from deep within regions of open magnetic field on the Sun called ‘coronal holes’. However the energy source responsible for accelerating the outflowing plasma to such high speeds is still widely debated, although there is broad evidence that it is ultimately magnetic in nature with candidate mechanisms including Alfven wave heating1,2 and interchange reconnection3,4. The magnetic field near the solar surface within coronal holes is structured on spatial scales associated with the boundaries of meso-scale supergranulation convection cells, where descending flows create intense bundles of magnetic field. The energy density in these ‘network’ magnetic field bundles is a likely candidate as an energy source of the wind. Here we report measurements of two fast solar wind streams from the Parker Solar Probe (PSP) spacecraft5 near its 10th perihelion which provides strong evidence for the interchange reconnection mechanism. Specifically, we show that supergranulation structure at the coronal hole base remains imprinted in the near-Sun solar wind resulting in asymmetric patches of magnetic "switchbacks'' 6,7 and bursty solar wind streams with corresponding energetic ions with power law distributions extending to beyond 100 keV. Particle-in-cell simulations of interchange reconnection between open and closed magnetic structures support key features of the observations, including the energetic ion spectra. Important characteristics of interchange reconnection in the low corona are inferred from the PSP data including that the reconnection is collisionless and that the rate of energy release is sufficient to heat the ambient plasma and drive the fast wind. In this reconnection scenario of solar wind energization, open magnetic flux undergoes continuous reconnection and the wind is driven both by the resulting plasma pressure and the radial Alfvenic flow bursts.
Integration of multi-omics data shows downregulation of mismatch repair, purin, and tubulin pathways in triple-negative chemotherapy-resistant breast tumors
Authors: Tang Xiaojia , Thompson Kevin J. , Kalari Krishna R. , Sinnwell Jason P. , Suman Vera J. , Vedell Peter T. , McLaughlin Sarah A. , Northfelt Donald W. , Aspitia Alvaro Moreno , Gray Richard J. , Carter Jodi M. , Weinshilboum Richard , Wang Liewei , Boughey Judy C. , Goetz Matthew P. 
Published: August 2022

AbstractBackground:Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). Response to NAC is prognostic, with reductions in low overall survival and disease-free survival rates in those patients who do not achieve pathological complete response (pCR). Based on this premise, we focused on patients with residual disease and hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence.Methods and Results: We investigated 24 TNBC tumors from 12 patients with pre- and post-NAC data, including four patients who recurred shortly after surgery(<24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and non-recurrent TNBC tumors; however, post-NAC samples demonstrated a significant alteration in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the paired NAC I-SPY1 trial confirmed 56 genesets. Underlying these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n=392) breast cancer data set with relapse-free survival (RFS) data was used to refine our gene list to a 17 gene signature. A three-fold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine learning models. Due to the limited studies with pre-and post-NAC TNBC tumor data, further validation of the signature is needed.Conclusion:Analysis of multi-omics data from post-NAC TNBC chemoresistant tumors showed downregulation of mismatch repair, purin, and tubulin pathways. Additionally, weidentified a 17 gene signature in TNBC associated with post-NAC recurrence enriched with down-regulation of immune genes.
DRNET: Improved Deep Learning Solution to detect Diabetic Retinopathy by incorporating Explainability, Uncertainty and Generalisation
Authors: Saxena Mudit , Narra Pratap , Saxena Rakhi 
Published: August 2022

Abstract
Diabetic Retinopathy (DR) is the leading cause of blindness among adults and has no visible symptoms. Early detection is the key to prevent vision loss. Computer-Aided Diagnosis using Convolutional Neural Networks have recently gained momentum for DR detection as the cost can be significantly reduced while making the diagnosis more accessible. Even though these models give high accuracy, confidence in the diagnosis remains a mythical goal. In our opinion, the way to make the model’s diagnosis reliable is to enhance the trust in its predictions. In this work, we present a methodology to strengthen confidence in DR diagnosis using state of the art deep learning techniques by extending the pipeline with model uncertainty and explainability. Towards this goal, along with the model’s prediction we produce uncertainty scores and explainability maps to improve the users’ confidence in the diagnosis. Further, we attempt to generalise CNN models by exploring ensembling techniques such as bagging to improve performance of stand-alone models on external datasets i.e.-datasets other than the one that was used for training the model.
Approximation algorithms for the freeze tag problem inside polygons
Authors: Rajabi-Alni Fatemeh , Bagheri Alireza 
Published: August 2022

Abstract
The Freeze Tag Problem (FTP) aims at awakening a swarm of robots with one or more initial awake robots as soon as possible. Each awake robot must touch an sleeping robot to awake it. Once a robot is awakened, it can assist in awakening other sleeping robots. We study this problem inside a polygonal domain and present approximation algorithms for it.
Concise-Transparent Random Forest (C-T-RF): Using Impact Factor by Combining Accuracy and Transparency
Authors: Boruah Arpita Nath , Biswas Saroj Kumar 
Published: August 2022

Abstract
Ensemble learning is a hybrid learning system that exhibits a high level of performance by aggregating predictions of multiple classifiers and hence used to obtain a powerful predictive performance. Random Forest (RF) is an ensemble learning technique which executes a huge number of Decision Tree (DT) based on different subset of data and feature combinations. Regardless of its high-performance, RF is black box in nature which hinders the interpretability of the predictive model. A transparent system with less decision rules makes a system efficient, user convincing and manageable to a greater extent in fields like medical, business, banking etc. The expression of the decision rules into flowchart like representation makes the system transparent, explicitly understandable and closely resemblance to human reasoning. Therefore, to overcome the disadvantages of black box nature and to make it an efficient interpretable decision-making system, this paper proposes a condensed and a transparent RF named Concise-Transparent RF (C-T-RF), extracting the important decision rules hence making RF behaves like a white box which is transparent and comprehensible. The proposed model C-T-RF is compared with the performances of a simple DT and RF, Support Vector Machine (SVM) and Naïve Bayes in terms of classification accuracy, precision, recall and F1 score measures. In addition, C-T-RF is also compared with RuleFit and RF + DHC which are also rule-based methods. The performance of the proposed C-T-RF is validated with 12 well known UCI datasets and Kaggle and is observed from the experimental that the proposed C-T-RF is more efficient interpretable decision-making system.
Conceptual Blends and the Representation of the Syrian Refugees in the UNHCR Press Releases between 2011 and 2021
Authors: Ghachem Ines 
Published: August 2022

Abstract

This paper examines the representation of refugees in a non-governmental organisation’s media discourse. This study draws on Critical Discourse Analysis and more specifically Van Dijk’s sociocognitive approach and Conceptual Blending Theory (Fauconnier & Turner 2002) through the focus on the two notions of representation and conceptual blends. The corpus analysed is made up of 331 press releases about the Syrian refugees posted between 2011 and 2021 on the UN High Commissioner for Refugees’ home website. The metaphor identification procedure and a reading of the concordances relating to the Syrian refugees led to the identification of the conceptual blends. Analysis of the conceptual blending networks relating to the Syrian refugees unveils how they are represented in the press releases over a decade. Analysis also reveals the UNHCR’s conceptualisations of ‘the crisis’, the refugees, and other parties. The study also shows that the management of ‘the burden’ reveals the kind of representations backgrounded due to fostering a categorisation of Us and Them instead of Us vs. Them.
PET radiotracers for whole-body in-vivo molecular imaging of prostatic neuroendocrine malignancies: A case series and review of literature
Authors: Cohen Dan , Krauthammer Shir Hazut , Fahoum Ibrahim , Kesler Mikhail , Even-Sapir Einat 
Published: August 2022

Abstract
BackgroundNeuroendocrine malignancies of the prostate represent a spectrum of diseases. Treatment-induced neuroendocrine differentiation (tiNED) in hormonally treated adenocarcinoma has been the subject of a large amount of recent research. However, the identification of neuroendocrine features in treatment-naïve prostatic tumor raises a differential diagnosis between prostatic adenocarcinoma with de-novo neuroendocrine differentiation (dNED) versus one of the primary prostatic neuroendocrine carcinomas (P-NEC). This case series focuses on the recent advances made in the field of whole-body in-vivo molecular imaging of patients with prostatic neuroendocrine malignancies, using the PET-CT technology. While [18F]FDG is being used as the main PET radiotracer in oncologic imaging and reflects glucose metabolism of malignant lesions, other molecules labeled with positron-emitting isotopes, mainly somatostatin-analogues labeled with 68Ga and PSMA-ligands labeled with either 18F or 68Ga, have been extensively studied and are now routinely used in departments of nuclear medicine and molecular imaging.Case presentationWe present three cases of patients with different pathologically-proven entities within the spectrum of prostatic neuroendocrine malignancies: a patient with tiNED, a patient with dNED, and a patient with P-NEC. The patients underwent PET-CT with different radiotracers, and the molecular imaging data were helpful in guiding clinical decisions. We summarize and discuss relevant published data on each of the presented entities from clinical, biological and molecular imaging standpoints. We also provide the reader with practical recommendation regarding the preferred PET radiotracer for imaging each entity.ConclusionSeveral PET radiotracers are available to characterize and assess whole-body extent of prostatic malignancies within the neuroendocrine spectrum. Awareness to clinical, biologic and pathologic data should guide the selection of preferred PET radiotracer for imaging each entity. This review is unique being directed to basic scientists, clinicians, pathologists, radiologists and nuclear medicine physicians, representing the multidisciplinary nature of oncologic research nowadays.
The evaluation of health dimensions during the COVID-19 era- A Short Report
Authors: Amer Faten 
Published: August 2022

Abstract

A balanced scorecard (BSC) is a management tool that has been used for 25 years to enhance the performance evaluation (PE) of health care organizations (HCOs). A heterogeneity in BSC dimensions was perceived. In our previous systematic review, we identified all the perspectives, dimensions, and key performance indicators (KPIs) utilized by health care management when using BSC. Additionally, we produced a figure that summarizes BSC perspectives and HCOs' PE major and subdimensions. We found no BSC implementation at HCOs during the COVID-19 pandemic; hence, we analyzed studies that evaluated BSC dimensions separately throughout the pandemic. Therefore, we searched Google Scholar and Google for "COVID-19" or "Coronavirus" or "pandemic" until June 2021. We found 59 relevant studies. The review's discussion section reviewed and discussed these papers' results. In this report, we summarized these results using a figure. This figure will provide a comprehensive strategy for managers and researchers involved in the PE of HCOs. They will also be able to better concentrate on addressing the subdimensions that were adversely affected. Moreover, this analysis will assist them in understanding which factors were explored thoroughly and what suggestions or interventions were used to improve their performance. Additionally, it will help researchers determine which subdimensions deserve additional investigation. As a consequence, it will improve HCOs' PE during the pandemic. We welcome other researchers to update BSC subdimension reviews using this figure tool as a guide for future PEs of HCOs. Additionally, we encourage them to search and include more databases in the analysis.