bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel method to predict nonvisible symptoms using machine learning in cancer palliative care
Authors: Shimada Kazuki , Tsuneto Satoru 
Published: July 2022

Abstract
Purpose: Patients with cancer at the end of life may find it difficult to express their symptoms if they can no longer communicate verbally because of deteriorating health.Methods: In this study, we assessed these symptoms using machine learning. We conducted a clinical survey of 213 cancer patients from August 2015 to August 2016. We divided the reported symptoms into two groups—visible and nonvisible symptoms. Our machine learning model used patient background data and visible symptoms to predict nonvisible symptoms: pain, dyspnea, fatigue, drowsiness, anxiety, delirium, inadequate informed consent, and spiritual issues.Results: The highest and/or lowest values for prediction accuracy, sensitivity, and specificity, respectively, are as follows: 88.0%/55.5%, 84.9%/3.3%, and 96.7%/24.1%.Conclusion: This work will facilitate better assessment and management of symptoms in patients with cancer. To the best of our knowledge, this study is the first to predict non-visible symptoms using decision tree analyses for patients with cancer receiving palliative care. Notably, applications based on our results may assess symptoms to the same extent as healthcare professionals.
Evaluation of intracellular water lifetime of glioma cells measured using Dynamic Contrast-Enhanced MRI with two flip angles
Authors: Kiser Karl , Zhang Jin , Das Ayesha Bharadwaj , Tranos James A. , Wadghiri Youssef Zaim , Kim S. Gene 
Published: July 2022

Abstract
This manuscript aims to evaluate the robustness and significance of the intracellular water lifetime (τi) parameter estimated using the two flip-angle Dynamic Contrast-Enhanced (DCE) MRI approach. The repeatability of contrast kinetic parameter measurement was assessed by a test-retest experiment (n=7). The association of τi with cellular metabolism was investigated through DCE-MRI and FDG-PET experiments (n=7). Tumor response to a combination therapy of bevacizumab and fluorouracil (5FU) monitored by contrast kinetic parameters including τi (n=10). Test-retest experiments demonstrated compartmental volume fractions (ve and vp) remained consistent between scans while the vascular functional measures (Fp and PS) and ti showed noticeable changes, most likely due to physiological changes of the tumor. The standardized uptake value (SUV) of tumors has a strong negative linear correlation with ti (R2=0.838), a positive correlation with Fp (R2=0.504), and weak correlations with ve (R2=0.150), vp (R2=0.077), PS (R2 =0.117), Ktrans (R2 =0.088) and whole tumor volume (R2=0.174). In the treatment study, the ti of the treated group was significantly higher than the control group one day after bevacizumab treatment and increased significantly after 5FU treatment compared to the baseline. This study results support the feasibility of measuring τi using the two flip-angle DCE-MRI approach in cancer imaging.
Analysis of Mueller-Muller Clock and Data Recovery Circuits with a Linearized Model
Authors: Gu Youzhi , Feng Xinjie , Chi Runze , Chen Yongzhen , Wu Jiangfeng 
Published: July 2022

Abstract
With the development of high-speed analog-to-digital converter (ADC) based wireline receivers, Mueller-Muller clock and data recovery (MM-CDR) circuit also get more and more attention. But in the design stage, the MM-CDR circuit used in ADC-based wireline receiver is difficult to evaluate its loop performance, owing to the lack of linearized model of Mueller-Muller phase detector (MMPD). In this paper, by analyzing the slope and distribution of the signal at different positions, a linearized model of MMPD is proposed and the model is combined with an entire MM-CDR system to analyze the performance of the MM-CDR loop. Through the analysis of the linearized model and the verification of the actual simulation, we can know that when the VREF level in the MMPD is set equal to the amplitude of the main-cursor h0, the MMPD can obtain the maximum gain, and the jitter transfer function and jitter tolerance can achieve optimum performance.
Comparison of the DRASTIC+L and Modified VABHAT models in vulnerability assessment of Karaj Aquifer, Central Iran, using MCDM, SWARA, and BWM methods
Authors: Shakeri Reza , Alijani Farshad , Nassery Hamid Reza 
Published: July 2022

Abstract
One of the most important and perilous groundwater contaminants is nitrate, which is considered a potential environmental risk in Iran and an international issue globally. The study area is the Karaj unconfined aquifer, Central Iran, subjected to quantity and quality hazards due to unbalanced urban, industrial, and agricultural developments. Evaluation of the vulnerability condition of this aquifer against nitrate as the Contamination index is essential since the most amount of consumption water in the area is provided from groundwater. The study aims to detect vulnerable zones of the Karaj aquifer using DRASTIC + L and Modified VEBHAT vulnerability models. The weighting of the parameters has been performed employing the recent Multiple-Criteria Decision-Making (MCDM) methods, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM). The results demonstrated that the most vulnerability had occurred from the east to the south of the aquifer (high to super-critical), including urban and residential areas, regarding both the vulnerability models' plots. The plots of the two methods are similar and did not exhibit considerable differences. The Modified VEBHAT has more certainty than the DRASTIC + L and has optimized and improved the DRASTIC + L model because the most vulnerable zone in the output plots of the Modified VEBHAT model is in the east of the aquifer, which has good agreement with the nitrate contaminant mass with the highest concentration.
DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding
Authors: Mirsadeghi Maryam , Shalchian Majid , Kheradpisheh Saeed Reza 
Published: July 2022

Abstract
Backpropagation is the most popular and common algorithm for training of traditional deep neural networks. Herewe propose temporal version of backpropagation to directly train spiking neural networks with deep structure andsingle spikebased temporal coding scheme (DS4NN). We consider a convolutional spiking neural networkconsisting of simple non-leaky integrate-and-fire (IF) neurons, and a temporal coding known as timeto-first-spikecoding. These together lead to lower computational cost and higher inference speed. We use surrogate gradient atfiring times to solve the non-differentiability of spike times with respect to membrane potential of spiking neurons,and to prevent the emergence of dead neurons in deep layers, we propose a relative encoding scheme fordetermining desired firing times. Evaluations on two classification tasks of MNIST and FashionMNIST datasetsconfirm the capability of DS4NN on deep SNNs. It achieves the accuracy of 99.3% and 91.6% on respectivelyMNIST and FashionMNIST datasets with the mean required number of 1126 and 1863 spikes in the whole network.This shows that the proposed approach can make fast decisions with low cost and high accuracy.
Phytoplankton Bloom Changes during Three Regime Shift derived from Sea Ice Concentration in Ross Sea, Antarctica
Authors: Jo Young-Heon , Bae Dukwon , Yang Hyunjin , Park JinKu , Kim Hyun-Cheol 
Published: July 2022

Abstract
Sea ice concentration (SIC) plays an important role in the Antarctic polynyas, especially biological changes through chlorophyll-a (CHL) concentration phenology. To understand how much SIC changes affect CHL, the regime shift index (RSI) was applied to SIC anomaly and we obtained three regimes: 1997–2004 for Regime 1 (R1), 2005–2016 for Regime 2 (R2), and 2016–2019 for Regime 3 (R3). Based on reconstructed daily remotely sensed CHL observations using a random forest algorithm with 11 physical predictors, our analysis revealed that: (1) the earlier the SIC melting time, the earlier the CHL bloom peaks for each regime resulting from sea ice melting duration and physical forces; (2) SIC changes account for 10%-12.5% of CHL variation, which is the first estimation in the Ross Sea polynya; and (3) although they are significantly influenced by SIC changes, the 11 physical predictors for CHL were more dominant for each regime. Thus, these results could explain why CHL decreased even in with unprecedent decrease in Antarctic SIC from 2016. Therefore, this quantitative analysis can estimate the contribution of SIC formation and physical environmental parameters to CHL changes based on the random forest machine learning algorithm.
End of life care needs in cancer patients at home: A retrospective study on clinical, geographical and socio-cultural differences
Authors: Ostan Rita , Varani Silvia , Pannuti Francesco , Pannuti Raffaella , Biasco Guido , Bruera Eduardo 
Published: July 2022

Abstract
Purpose. Palliative care (PC) is recognized by a National Law in Italy, a country with a National Health Service covering the entire territory. However, the Italian PC system still presents regional heterogeneity, particularly regarding home care. Timely, effective and personalized identification of the multi-dimensional needs in advanced cancer patients are major goals of appropriate PC delivery. This retrospective study aims to describe geographical patterns in clinical and demographic characteristics at the inception point and their association with the intensity of care during the last month of life in advanced cancer patients assisted at-home. Methods. Cancer patients entered in home PC during 2020 in Italy were considered. The association between home PC services during the last month of life (primary outcome) and demographic data, performance status (KPS), symptoms, therapies at the entry was explored. Results. Among 1721 consecutive patients (919 in Centre-North and 802 in Centre-South Italy), patients from Centre-South were younger (p<.001), had worse KPS (p<.001), and shorter survival (p=.010). Patient age was inversely associated with the number of total/physician/nurses services during the last month of life (p<.001, p=.001, p=.008, respectively). Patients with severe symptoms (asthenia, pain and anxiety) at inception needed more PC services at the end-of-life (p=.026, p=.008, p=.038, respectively). The distribution of workload differed according the geographical area, with higher number of PC services provided by physicians (p<.001) in Centre-North and by nurses (p=.002) in Centre-South. Conclusion. These findings highlight major disparity in access and nature of PC in a country with universal access to health services.
In vitro Green Globular Body Induction, Proliferation and Plantlet Regeneration of Adiantum reniforme var. sinense
Authors: Lin Cheng-Wei , Shih Chia-Hung , Chu Yu , Kao Chien-Yuan 
Published: July 2022

Abstract
The induction of green globular bodies (GGBs) represents an unique phenomenon in the tissue culture of pteridophytes. In this first attempt study GGBs were induced with the embryos of Adiantum reniforme var. sinense. The influences of basal salts, plant growth regulators, sugar concentrations, and gelling agents on the proliferation and differentiation of GGBs were examined. The highest induction rate of GGBs resulted from Murashige & Skoog (MS) medium supplemented with benzyl aminopurine (BA) (0.1 mg L−1) and 1-naphthaleneacetic acid (NAA) (0.15 mg L−1). The subsequent proliferation of GGBs required a higher concentration of NAA (10 mg L−1) to have the highest fresh weight of 0.29 g. However, cytokinins, such as BA, kinetin (KT), and thidiazuron (TDZ), exhibited inhibitory effects on GGB proliferation. Hyponex was superior to MS medium in terms of GGBs proliferation and differentiation, which led to the highest fresh weight (1.72±0.63 g) and shoot number (7.25±1.89) after 60 days of cultivation. Among different sucrose concentration in media, GGBs cultured with 15 g L−1 sucrose had the highest fresh weight (1.01 g). Gelling agents also showed evident effects on the proliferation of GGBs, and the fresh weight of GGBs cultured in gelrite medium was approximately three times greater than that of GGBs cultured in agar medium. Distinct histological characteristics of embryos and GGBs were revealed by paraffin sections. All regenerates from GGBs survived in the greenhouse, with normal appearances, after acclimation in the medium of peat soil and pearlite (1:1).
Discernment of cerebral amyloid and cognitive status using ultrasensitive blood biomarkers collected with a non-traditional anticoagulant
Authors: Green Zachary D. , Kueck Paul J. , John Casey S. , Burns Jeffrey M. , Morris Jill K. 
Published: July 2022

Abstract
Background: The development of biomarkers that are easy to collect, process, and store is a major goal of current Alzheimer’s Disease (AD) research, and underlies the growing interest in plasma biomarkers. Biomarkers with these qualities will improve confidence in diagnosis and allow for better monitoring of therapeutic interventions. However, blood collection strategies have historically differed between studies. We examined the ability of various ultrasensitive plasma biomarkers to predict cerebral amyloid status in cognitively unimpaired individuals when collected using acid citrate dextrose (ACD). We then examined the ability of these biomarkers to predict cognitive impairment, independent of amyloid status. Methods: We measured amyloid beta 42/40 ratio, pTau-181, neurofilament-light, and glial fibrillary acidic protein using the Quanterix Simoa® HD-X platform. To evaluate the discriminative accuracy of these biomarkers in determining cerebral amyloid status, we used both banked plasma and 18F-AV45 PET cerebral amyloid neuroimaging data from 140 cognitively unimpaired participants. We further examined their ability to discriminate cognitive status, by leveraging data from 42 cognitively impaired older adults. This study is the first to our knowledge to examine these specific tests using plasma collected using acid citrate dextrose (ACD), as well as the relationship with amyloid PET status. Results: Plasma AB42/40 had the highest AUC (0.833, 95% C.I. 0.767-0.899) at a cut-point of 0.0706 for discriminating between the two cerebral amyloid groups (sensitivity 76%, specificity 78.5%). Plasma NFL at a cut-point of 20.58pg/mL had the highest AUC (0.908, 95% CI 0.851-0.966) for discriminating cognitive impairment (sensitivity 84.8%, specificity 89.9%). The addition of age and apolipoprotein e4 status did not improve the discriminative accuracy of these biomarkers. Conclusions: Our results suggest that Aβ42/40 ratio is useful in discriminating clinician-rated elevated cerebral amyloid status, and that NFL is useful for discriminating cognitive impairment status. These findings reinforce the growing body of evidence regarding the general utility of these biomarkers, and extend their utility to plasma collected in a non-traditional anticoagulant.
Single-phase earth fault line selection method based on ICEEMAN grid
Authors: Lu Ming , Liu Zezhong , He Xianke , Chen Zuguo , Zou Ying 
Published: July 2022

Abstract
The neutral resonant grounding system occurs when the single-phase ground fault redundant fault information and the traditional fault routing party to the fault signal characteristics of the poor degree of self-adaptive extraction, routing accuracy is low and other problems. This paper proposes a single-phase ground fault routing method for distribution networks based on Improved Complete Ensemble Empirical Modal Decomposition of Noise (Improved complete ensemble EMD, ICEEMAN) and Stacking ensemble learning. Firstly, the transient zero-sequence currents are separated by combining the ICEEMAN and HHT energy spectra for the I.F. eigenmode components (IMF) and the transient non-I.F. component IMF. Then, the sample entropy of the transient non-working frequency component IMF is calculated as the fault feature. Finally, the Stacking ensemble learning model is built to select the fault lines. The experimental results show that this paper's new line selection method can accurately select the fault line under different fault locations, transition resistance, fault initial phase angle, and added noise. The adaptability and accuracy of the method in this paper are further verified by comparing it with EEMD-SVM and ICEEMDAN-Bagging, and thus it has strong robustness.
Effects of land-cover characteristics, physiochemical variables and river connectivity on fish assemblages in a lowland basin
Authors: Zhang Zhiming , Gao Junfeng , Cai Yongjiu 
Published: July 2022

Abstract
Human disturbances (e.g., land-use changes, dam construction, and pollutant emissions) can have severe environmental impacts on freshwater ecosystems. The main aim of this study was to detect the influences of physiochemical variables, land-cover characteristics, and river connectivity on fish assemblages in Lake Chaohu Basin, China. A cluster analysis of the river connectivity variables identified four groups of sites that were characterized by significantly different river-connectivity and longitudinal gradients in local scale. These four groups of sites showed increasing connectivity from the upper reaches to the lower reaches. At the same time, among the four groups, the values of the environmental variables generally increased from the upper reaches with less human activity towards the lower reaches with more human activities. For instance, some main physiochemical variables (e.g., river width, water depth, total phosphorus, nitrate, phosphate, and dissolved organic carbon) significantly increased among the four groups. In contrast, fish taxa richness and diversity indices were not significantly different among the four connectivity groups. However, fish assemblages showed significant variation among the connectivity groups (global R = 0.089, p = 0.026). In addition, the study determined that upper riparian land uses (e.g., woodland and grassland), flow velocity, and elevation were environmental variables regulating the variance in the fish communities, and for the connectivity variables, only river order and number of branches along a path to the left of the main stem affected the variance in the fish communities. Therefore, new practices aimed at maintaining and even increasing the riparian canopy coverage and the flow velocity of rivers should be integrated into local conservation planning for freshwater ecosystems, especially in the upper reaches of the basin.
Filling gaps in historical earthquake archive by geo-archaeological methods: a case history from Italy
Authors: Falcone Francesca , Valerio Eugenio di , Salvia Vasco La , Rosatelli Gianluigi , Perna Maria Grazia , Frances Rachel , STOPPA Francesco 
Published: July 2022

Abstract
All over the world, archaeological sites, which have alternated destruction and reconstruction following strong earthquakes can disclose important historical / seismological data. Particularly instructive is the case of St. Angel cave in Palombaro (Abruzzo Region, Italy). Combining the geological, archaeological, archaeometrical and chronachistic study, we constrained the seismic history of the last 1000 years of a large area of central Apennines of Italy, and therefore results are of wide interest. This place reveals various phases of worship, confirming itself as a place of religious importance bridging the gap between paganism and Christianity. The lithostratigraphy of the area made possible to practice water-worship, as deduced by a system of tubs present in the cave. The interpretation of the cult refers to chthonian divinities in charge of thaumaturgic properties symbolically linked to endogenous geologic phenomena. A rupestrian church from the 10th-11th -century was built and reported in a 1064 CE chronicle as dedicated to St. Michael Archangel. Two vast collapses of the church, have been documented by the archaeological stratigraphy, dating of the archaeological finds, layering of the church walls, and changes in style and building materials. Geoarchaeological data, combined with the chronicles, suggests that the first collapse should be attributed to the 1209 CE earthquake (Mw >>6, I HD). Therefore, the failure of the Church of St. Angel would represent the first evaluated point of the seismic damage extension, assessable to the IX MCS intensity. A more recent collapse is attributed to the 1706 CE earthquake (Mw 6.8, I XI MCS). Finally, the remains of the church were seriously damaged and spoiled after the 1933 earthquake (Mw 5.9, I IX MCS) and then poorly restored.
Operando condition reaction modeling shows highly dynamic attachment of oligomeric ruthenium catalysts
Authors: Trivino Juan Angel de Gracia , Ahlquist Mårten 
Published: July 2022

Abstract
To increase the stability and current density of molecular-catalyst-based electroanodes for water oxidation immobilization of the catalysts at the electrode surface is a common strategy. A prominent example it the oligomerized Ru(tda) molecular catalyst which showed outstanding current densities even at neutral pH values. One of the most challenging aspects of immobilized catalysts is to understand the interaction between the catalyst and the surface under operando conditions. Experiments are often performed under model conditions and computational methods to study reaction steps are typically limited to a few hundred atoms. In this study, we combined three computational methods, density functional theory electronic structure computations, molecular dynamics for large scale simulations of the catalyst-solid interaction, and empirical valence bond for reaction modeling the catalyst at the interface of a large carbon support and a phosphate water buffer. These techniques allowed us to explore the combined effects of solvent, hydrophobic directionality, and electric field on the attachment and reactivity of a Ru(tda) pentamer at a graphene surface. Our simulations have perfect agreement with the experimental characterization under model conditions. However, we find that under operando conditions, where the catalyst is oxidized to the active RuV state, with a phosphate containing electrolyte and an applied electric field, the attachment is completely reversed compared to the model conditions with RuII and organic solvents. This reversed attachment leads to a water excluded region close to the active RuV=O center. The EVB reaction modeling showed that the reaction could still proceed to form an O-O bond via the oxide relay mechanism where a dangling carboxylate reacts with the oxo via nucleophilic attack. We find that the activation energy is identical in water solution and at the electrode surface, showing how this mechanism is key to highly active molecular water oxidation catalysts immobilized on surfaces. Since attachment to surfaces could have strong, and often negative, influence on the reactions this study provides a guideline in how to model reactions without compromising the complexity of the electrode environment.