bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Integrated InSAR-Borehole Inclinometer-Numerical Modeling Approach to the Assessment of a Slow-Moving Landslide
Authors: Francioni Mirko , Stead Doug , Sharma Jayanti , Clague John J. , Brideau Marc-André 
Published: June 2021

ABSTRACT
We use results of satellite-based interferometric synthetic aperture radar, Global Positioning System, and borehole inclinometer data to constrain numerical models that improve understanding of slope deformation at the Alexandria landslide, British Columbia, Canada. Surface monitoring data and borehole slope inclinometer measurements provide important insight into the slope failure mechanism. We initially analyzed the data in a geographic information system (GIS) to create thematic maps of the landslide area (hillshade, slope, and aspect), to identify key geological features, and to produce an engineering geomorphology map of the landslide. The monitoring data and the geological/engineering geomorphological models provide important constraints for two-dimensional landslide limit equilibrium and finite difference analyses. The initial limit equilibrium analysis improved understanding of the sliding surfaces. The finite difference models were then used to simulate and investigate the potential slope deformation mechanism. The combined slope monitoring/modeling results show that the Alexandria landslide is a slow-moving, multiple-block, retrogressive slope failure. The close agreement between the limit equilibrium and finite difference analyses, together with the satellite and ground-based slope monitoring and GIS data, highlight the importance of using a multidisciplinary/integrated approach in landslide studies.
Sparse Neural Networks for Inference of Interwell Connectivity and Production Prediction
Authors: Yu Junjie , Jahandideh Atefeh , Hakim-Elahi Siavash , Jafarpour Behnam 
Published: June 2021

Summary
A new neural network-based proxy model is presented for prediction of well production performance and interpretation of interwell connectivity in large oil fields. The workflow consists of two stages. The first stage uses feature learning to describe the general input-output relations that exist among the wells and to characterize the interwell connectivity. In the second stage, the identified interwell connectivity patterns are used as network topology to develop a multilayer neural network proxy model, with nonlinear activation functions, to predict the production performance of each producer. The estimation of connectivity patterns in the first stage serves as an interpretable feature-learning step to improve the effectiveness of the proxy model in the second stage. Identification of interwell connectivity is based on the selection property of the ℓ1-norm minimization by promoting sparsity in the estimated connectivity weights. The sparsity of the network is motivated by the domain knowledge that each production well is mainly supported by a few nearby injection wells. That is, a proxy model that allows each producer to communicate with all the other wells in the field is inherently redundant and must have an unknown sparse representation. The sparse structure of the connection weights in the resulting network is detected by promoting sparsity during the training process. Two synthetic numerical examples, with known solutions, are first used to demonstrate the functionality and effectiveness of ℓ1-norm regularization for interwell connectivity identification. The workflow is then applied to a real field waterflooding example in Long Beach to predict oil production and to infer interwell connectivity information. Overall, the workflow provides a proxy model that effectively combines the implicit physical information from simulated data with reservoir engineering insight to identify interwell connectivity and to predict well production trends.
Primary Pituitary EBV-associated NK/T-cell Lymphoma
Authors: Motov Stefan , Butenschoen Vicki Marie , Ryang Yu-Mi , Gempt Jens , Boeckh-Behrens Tobias , Liesche-Starnecker Friederike , Schneller Folker , Rothhammer Veit , Seifert Christian , Slotta-Huspenina Julia 
Published: June 2021

Abstract
BackgroundPrimary pituitary NK-/T-cell lymphomas are extremely rare pathologies and there is only limited information about their clinical course, treatment and prognosis.Case presentationWe present a case of a 78-year-old patient with a sellar nodular mass. After onset of symptoms with productive cough, hoarseness, swallowing disorder and recurrent fever her condition rapidly deteriorated. Open biopsy through a right pterional approach was performed and histopathological evaluation revealed an EBV-associated NK/ T-cell lymphoma. High-dose corticosteroid therapy was initiated. However the patient passed away 37 days after admission due to respiratory insufficiency. ConclusionWe describe an unusual case of EBV-associated NK-/T-cell lymphoma of the CNS manifesting as a pituitary gland tumor. This particular entity presented with a pronounced aggressive local tumor growth with lethal outcome.
Diffusion modeling reveals effects of multiple release sites and human activity on a recolonizing apex predator
Authors: Eisaguirre Joseph , Williams Perry , Lu Xinyi , Kissling Michelle , Beatty William , Esslinger George , Womble Jamie , Hooten Mevin 
Published: June 2021

Abstract
Background: Reintroducing predators is a promising conservation tool to help remedy human-caused ecosystem changes. However, the growth and spread of a reintroduced population is a spatiotemporal process that is driven by a suite of factors, such as habitat change, human activity, and prey availability. Sea otters (Enhydra lutris) are apex predators of nearshore marine ecosystems that had declined nearly to extinction across much of their range by the early 20th century. In Southeast Alaska, which is comprised of a diverse matrix of nearshore habitat and managed areas, reintroduction of 413 individuals in the late 1960s initiated the growth and spread of a population that now exceeds 25,000. Methods: Periodic aerial surveys in the region provide a time series of spatially-explicit data to investigate factors influencing this successful and ongoing recovery. We integrated an ecological diffusion model that accounted for spatially-variable motility and density-dependent population growth, as well as multiple population epicenters, into a Bayesian hierarchical framework to help understand the factors influencing the success of this recovery. Results: Our results indicated that sea otters exhibited higher residence time as well as greater equilibrium abundance in Glacier Bay, a protected area, and in areas where there is limited or no commercial fishing. Asymptotic spread rates suggested sea otters colonized Southeast Alaska at rates of 1-8 km/yr with lower rates occurring in areas correlated with higher residence time, which primarily included areas near shore and closed to commercial fishing. Further, we found that the intrinsic growth rate of sea otters may be higher than previous estimates suggested. Conclusions: This study shows how predator recolonization can occur from multiple population epicenters. Additionally, our results suggest spatial heterogeneity in the physical environment as well as human activity and management can influence recolonization processes, both in terms of movement (or motility) and density dependence.
Understanding Regulation of Non-Utility Water Supply Systems from the Household Perspective
Authors: Ikpeh Iniobong James , Soetanto Robby , Anvuur Aaron 
Published: June 2021

Abstract
PurposeThe article seeks to examine the understanding of regulation of Non-Utility Water Supply Systems (NUWSS) from perspective of water users in households, the behavioural dimensions of regulation and aspects of the non-utility water supply system that can be regulated.Research Method/DesignThe theory of planned behaviour was used to identify determinants to regulatory compliance across the groups of indicators identified for the regulation of water supply systems. To understand household perception of regulation, interviews were conducted, with questions put to water users in households. A qualitative research approach was adopted, using interviews, and focus group discussion with water users in households.FindingsThe findings indicate that households hold varied perceptions on regulation across the components of the water supply system. Specifically, regulatory compliance by households was influenced by crucial elements such as preferential compliance to regulation within specific aspects of the water supply system. Limitations and implicationsThe inference from this research is based on households from one state in Nigeria. Further exploration of this research in multiple cities and states would widen the applicability of the findings in different contexts.Originality/valueThe study examines regulation and regulatory compliance from the perspective of households who predominantly use Non-Utility Water Supply System (NUWSS) in sub-Saharan Africa.
Evaluation of the Complicated Storm Sewer Networks Design Method and the Rational Method Using a Risk-Based Simulation-Optimization Approach
Authors: Samani Jamal Mohammad Vali , Sadeghi Sonia , Samani Hossein Mohammad Vali 
Published: June 2021

Abstract
In this study, optimal designs with minimum costs are obtained for various storm return periods. Then the risk analysis is used to determine the return period in which the design cost plus the damage risk cost is minimum. SWMM software was used to handle the simulation and the Network optimization was performed by using the genetic algorithm. The non-linear reservoir model to convert the rainfall into runoff and the dynamic wave model to perform the network hydraulic simulation in this software are utilized as a complicated simulation model. The results showed that the 10-year return-period storm in which the summation of the design and the damage risk costs are minimum is the one that should be selected. Also, the rational method of the software was applied as the simplest method of rainfall-runoff and the hydraulic calculations were performed using a Manning equation without considering the flow travel time. The results show that the return period of the risk analysis is the same as the first one whereas the total design costs are greater by 16.6%. Afterward, the classical rational method in which the flow travel time is considered was used to design the same network. The peak flows of the pipes were remarkably reduced, causing the design costs to be only 4.7% greater than the complicated precise method. It can be concluded that the simple classic rational method considering the flow travel time may be used in the design of storm sewer networks due to its acceptable accuracy and costs.
Paraneoplastic Cerebellar Degeneration Associated With anti-Yo Antibodies Appearing as a Leptomeningeal Cerebellar Carcinomatosis at Mri. A Case Report.
Authors: Napolitano Massimo , Ranieri Angelo , Alfieri Gennaro , Maniscalco Giorgia Teresa , Zeccolini Fabio , Boscaino Amedeo , Manzo Valentino 
Published: June 2021

Abstract
Anti Yo antibodies (AYA) are the antibodies most frequently identified with Paraneoplastic Cerebellar Degeneration (PCD). They are detected above all in PCD associated with breast and gynecologic malignancies. Here, we report a third case of PCD with cerebellar contrast enhancement findings at MRI. In fact, AYA cross anti cerebellar cortex immune reaction leads mainly to hyperintensity signals in T2-weighted-MRI sequences, followed by cerebellar atrophy. As such, meningeal contrast enhancement could lead to a diagnostic pitfall as it can be considered a carcinomatosis - above all in serum antibody negative cases as well as when a metastatic tumour is found. Our patient had no tumoral cells in the cerebrospinal fluid and her neurological syndrome remained stable after immunoglobulin treatment. AYA serum finding was diriment for PCD diagnosis.
Creating Speech Synthesis Process by Using Pulse Model in Log-Domain Vocoder With Whale Optimized Deep Convolution Neural Networks
Authors: N Radha , P Vijayalakshmi 
Published: June 2021

Abstract
Speech synthesis is an artificial production of human speech by utilizing computer systems called a speech synthesizer. Several statistical parameters are used in previous works to perform the speech synthesis process, but the vocoder is combined only the simpler model. Due to the lack of sequence of modeling, the quality degrading process is reducing the speech synthesis. Therefore, the Pulse model in log-domain vocoder with whale optimized deep convolution recurrent neural network is applied to investing the vocoder in this work. During this analysis, Mel-Generalized Cepstrum (MGC), maximum voice frequency (MVF), and F0 are applied to processing the signal to extracting the features, and the vocoder is generated successfully. The system's effectiveness is then evaluated using experimental results compared to deep neural networks and traditional recurrent networks.
A Workflow to Investigate the Impacts of Weathered Multi-Walled Carbon Nanotubes to the Mudsnail Lymnaea Stagnalis
Authors: Weise Katrin , Kurth Thomas , Politowski Irina , Winkelmann Carola , Schäffer Andreas , Kretschmar Susanne , Berendonk Thomas Ulrich , Jungmann Dirk 
Published: June 2021

Abstract
Although the development and application of nanomaterials is a growing industry, little data is available on the ecotoxicological effects on aquatic organisms. Therefore, we set up a workflow to address the potential uptake of weathered multi-walled carbon nanotubes (wMWCNTs) by a model organism, the pulmonary mudsnail Lymnaea stagnalis (L. stagnalis), which plays an important role in the food web. It represents a suitable organism for this approach because as a grazer it potentially ingests large amounts of sedimented wMWCNTs. As food source for L. stagnalis, benthic biofilm was investigated by the use of a transmission electron microscope (TEM), and a scanning electron microscope (SEM) after exposure with wMWCNTs. In addition, isotopic labeling was applied with 14C-wMWCNTs (0.1 mg/L) to quantify fate, behavior and enrichment of 14C-wMWCNTs in benthic biofilm and in L. stagnalis. Enrichment in benthic biofilm amounted to 529.0 µg wMWCNTs/g dry weight and in L. stagnalis to 79.6 µg wMWCNTs/g dry weight. A bioconcentration factor (BCF) for L. stagnalis was calculated (3,500 L/kg). We demonstrate the accumulation of wMWCNTs (10 mg/L) in the digestive tract of L. stagnalis in an effect study. Moreover, the physiological markers glycogen and triglycerides as indicators for the physiological state, as well as the RNA/DNA ratio as growth indicator were examined. No significant differences between exposed and control animals were analyzed for glycogen and triglycerides after 24 d of exposure, but a decreasing trend is recognizable for triglycerides. In contrast, the significant reduction in the RNA/DNA ratio of L. stagnalis indicated an inhibition of growth with a following recovery after depuration. The described workflow enables a comprehensive determination of the fate and the behavior of wMWCNTs in specifically and in general all kinds of CNT in the aquatic environment and therefore contributes to a holistic risk assessment of wMWCNTs.
A Multi Core Data Transmission and Management Method of the Wireless MIMO Network
Authors: Deng Changjian 
Published: June 2021

Abstract
With the development of vehicle and mobile robot wireless technology, there are lots of data may transmit simultaneously. So, the paper proposes a multi core data transmission and network management method. In this method, the MIMO multi core system works in parallel mode; and it has multi agent feature in network operation, meanwhile it has feature of sub-graph decomposition characteristics also in MIMO topology of network. Based on the mathematical model of MIMO multi core system, the paper designs two prototype of network gateway, one is made of five CC2530 , a CAN module, and it is a demo of a vehicles gateway; the another is CC1320 multicore gateway system. The simulations and experiments show the feasibility and effective of this wireless multi core data transmission and management method
Attention mechanisms and deep learning for machine vision: A survey of the state of the art
Authors: Hafiz Abdul Mueed , Parah Shabir Ahmad , Bhat Rouf Ul Alam 
Published: June 2021

Abstract
With the advent of state of the art nature-inspired pure attention based models i.e. transformers, and their success in natural language processing (NLP), their extension to machine vision (MV) tasks was inevitable and much felt. Subsequently, vision transformers (ViTs) were introduced which are giving quite a challenge to the established deep learning based machine vision techniques. However, pure attention based models/architectures like transformers require huge data, large training times and large computational resources. Some recent works suggest that combinations of these two varied fields can prove to build systems which have the advantages of both these fields. Accordingly, this state of the art survey paper is introduced which hopefully will help readers get useful information about this interesting and potential research area. A gentle introduction to attention mechanisms is given, followed by a discussion of the popular attention based deep architectures. Subsequently, the major categories of the intersection of attention mechanisms and deep learning for machine vision (MV) based are discussed. Afterwards, the major algorithms, issues and trends within the scope of the paper are discussed.
​Isolation and Characterization of a Vibrio Sp. Strain MA3 Possibly Associated with Mass Mortalities of the Pearl Oyster Pinctada fucata
Authors: SAKATOKU Akihiro , Hatano Kaito , Tanaka Shoki , Isshiki Tadashi 
Published: June 2021

Abstract
In the summers of 2019 and 2020, a previously undescribed disease occurred in both juvenile and adult shellfish, causing mass mortalities in cultured pearl production, characterized by the major symptom of extreme atrophy of the soft tissues, including the mantle. However, the causative organism was uncertain. We isolated Vibrio sp. strain MA3 from the mantles of diseased pearl oysters Pinctada fucata. Analyses of 16S rRNA gene and DNA gyrase sequence homologies and its biochemical and morphological characteristics suggested that strain MA3 is a new strain of Vibrio alginolyticus. In addition, a hemolysin gene (Vhe1) of strain MA3 was detected as one of the virulence factors, and the complete sequence was determined. BLAST searches showed that Vhe1 shares 99.8% nucleotide sequence identity with Vibrio alginolyticus strain A056 lecithin-dependent hemolysin (ldh) gene, complete cds. Experimental infection of healthy oysters via injection with strain MA3 indicated it could cause high mortalities of the typically affected oysters from which the strain was isolated. These results suggest that the newly isolated Vibrio sp. strain MA3 is a putative causal agent of the recent disease outbreaks in Akoya pearl oysters.
Genetic Variants in Histone Modification Regions Are Associated With the Prognosis of Lung Adenocarcinoma
Authors: Kang Hyo-Gyoung , Lee Yong Hoon , Lee Shin Yup , Choi Jin Eun , Do Sook Kyung , Hong Mi Jeong , Lee Jang Hyuck , Jeong Ji Yun , Do Young Woo , Lee Eung Bae , Shin Kyung Min , Lee Won Ki , Choi Sun Ha , Seo Hye , Yoo Seung Soo , Lee Jaehee , Cha Seung Ick , Kim Chang Ho , Cho Sukki , Jheon Sanghoon , Park Jae Yong 
Published: June 2021

Abstract
We investigated the association between genetic variants in the histone modification regions and the prognosis of lung adenocarcinoma after curative surgery. Potentially functional SNPs were selected using integrated analysis of ChIP-seq and RNA-seq. The SNPs were analyzed in a discovery set (n=166) and a validation set (n=238). The associations of the SNPs with overall survival (OS) and disease-free survival (DFS) were analyzed. A total of 279 SNPs were selected for genotyping. Among these, CAPN1 rs17583C>T was significantly associated with better OS and DFS (P = 0.001 and P = 0.007, respectively), and LINC00959 rs4751162A>G was significantly associated with worse DFS (P = 0.008). Luciferase assays showed a significantly lower promoter activity of CAPN1 in the rs17583 T allele than C allele (P = 0.008), and consistently the CT+TT genotypes had significantly lower CAPN1 expression than CC genotype (P = 0.01) in clinical samples. The rs4751162 G allele had higher promoter activity of GLRX3 than A allele (P = 0.05). The motif analyses and ChIP-qPCR confirmed that the variants are located in the active promoter/enhancer regions where transcription factor binding occurs. This study showed that genetic variants in the histone modification regions could predict the prognosis of lung adenocarcinoma after surgery.
The CN-index of hnRNP-DL Predicts an Individual “Window of Treatment Success” in RA Patients
Authors: Marklein Bianka , Jenning Madeleine , Konthur Zoltán , Häupl Thomas , Welzel Franziska , Nonhoff Ute , Krobitsch Sylvia , Mulder Debbie , Koenders Marije , Joshua Vijay , Cope Andrew , Shlomchik Mark , Anders Hans-Joachim , Burmester Gerd , Hensvold Aase , Catrina Anca , Johan Rönnelid , Steiner Günter , Skriner Karl 
Published: June 2021

Abstract
BackgroundThere is a need for biomarker to identify patients ‘at risk’ for rheumatoid arthritis (risk-RA) and to better predict the therapeutic response and in this study we tested the hypothesis that novel native and citrullinated heterogeneous nuclear ribonucleoprotein (hnRNP)-DL autoantibodies could be possible biomarkers.MethodsUsing Protein macroarray and ELISA, epitope recognition against hnRNP-DL was analysed in sera from different developed RA disease and diagnosed SLE patients. Toll-like receptor (TLR) 7/9 and myeloid differentiation primary response gene 88 (MyD88)-dependency were studied in sera from murine disease models. HnRNP-DL expression in cultivated cells and synovial tissue was analysed by indirect immunofluorescence, immunoblot and immunohistochemistry. ResultshnRNP-DL was highly expressed in stress granules, citrullinated in the rheumatoid joint and targeted by autoantibodies either as native or citrullinated proteins in patient subsets with different developed RA disease. Structural citrullination dependent epitopes (SCEs) of hnRNP-DL were detected in 58% of the SLE patients although 98% of these sera were α-CCP2-negative. To obtain a specific citrullinated signal value, we subtracted the native antibody value from the citrullinated signal. This CNDL (Citrullinated-Native-hnRNP-DL)-index identified and the bioinformatic value was explored, as a new value for an “individual window of treatment success” in early RA and for the detection of RF-IgM/α-CCP2 seronegative RA patients (24-46%). Negative CNDL-index was found in SLE patients, risk-RA- and early RA-cohorts such as EIRA where the majority of these patients are DAS28-responders to methotrexate (MTX) treatment (87%). High positive CNDL-values were associated with more severe RA, shared epitope and parenchymal changes in the lung. Specifically, native α-hnRNP-DL is TLR7/9-dependent, associated with pain and ROC-analysis revealed an association to initial MTX or etanercept treatment response, especially in seronegative RA patients.ConclusionCNDL-index defines patients is a possible biomarker for develop RA and the “window of treatment success” thereby potentially closing the sensitivity gap.