bluuebunny/crossref_metadata_2025_split huggingface dataset:
Attention embedded lightweight network for maize disease recognition
Authors: Chen Junde , Wang Wenhua , Zhang Defu , Zeb Adnan , Nanehkaran Yaser Ahangari 
Published: November 2020

AbstractCrop disease has a negative impact on food security. If diverse crop diseases are not identified in time, they can spread and influence the quality, quantity, and production of grain. Severe crop diseases can even result in complete failure of the harvest. Recent developments in deep learning, particularly convolutional neural networks (CNNs), have exhibited impressive performance in both image recognition and classification. In this study, we propose a novel network architecture, namely Mobile‐DANet, to identify maize crop diseases. Based on DenseNet, we retained the structure of the transition layers and used the depthwise separable convolution in dense blocks instead of the traditional convolution layers, and then embedded the attention module to learn the importance of interchannel relationship and spatial points for input features. In addition, transfer learning was used in model training. By this means, we improved the accuracy of the model while saving more computational power than deep CNNs. This model achieved an average accuracy of 98.50% on the open maize data set, and even with complicated backdrop conditions, Mobile‐DANet realized an average accuracy of 95.86% for identifying maize crop diseases on a local data set. The experimental findings show the effectiveness and feasibility of the Mobile‐DANet. Our data set is available at https://github.com/xtu502/maize‐disease‐identification.
Optimizing the quality of clinical studies on oral microbiome: A practical guide for planning, performing, and reporting
Authors: Zaura Egija , Pappalardo Vincent Y. , Buijs Mark J. , Volgenant Catherine M. C. , Brandt Bernd W. 
Published: November 2020

AbstractWith this review, we aim to increase the quality standards for clinical studies with microbiome as an output parameter. We critically address the existing body of evidence for good quality practices in oral microbiome studies based on 16S rRNA gene amplicon sequencing. First, we discuss the usefulness of microbiome profile analyses. Is a microbiome study actually the best approach for answering the research question? This is followed by addressing the criteria for the most appropriate study design, sample size, and the necessary data (study metadata) that should be collected. Next, we evaluate the available evidence for best practices in sample collection, transport, storage, and DNA isolation. Finally, an overview of possible sequencing options (eg, 16S rRNA gene hypervariable regions, sequencing platforms), processing and data interpretation approaches, as well as requirements for meaningful data storage, sharing, and reporting are provided.
A Risk‐Science Approach to Vulnerability Classification
Authors: Thekdi Shital A. , Aven Terje 
Published: November 2020

AbstractAdvancements in the risk literature and recent events have highlighted the need for recognizing and managing system vulnerabilities. However, established definitions of vulnerability typically involve only static concepts that are limited to measurement of system characteristics. Advancements in risk modeling, combined with the dynamic nature of data availability, and processing call for the need to understand the various dimensions and time‐dependent properties of vulnerability within risk‐informed decision making. There is need to: (1) Understand and classify aspects of vulnerability that exist in various systems, such as related to engineering, business, and healthcare, while recognizing both properties of the system and associated knowledge, (2) reconcile these definitions of vulnerabilities with existing concepts, such as sensitivity analysis and fragility, and (3) explore the implications of various types of vulnerability on risk management decisions. The main contributions of this work include classifying dynamic characteristics of system vulnerability and leveraging information about the multidimensional properties of vulnerability within risk management decisions that apply to a collection of risk events. As a proof of concept, we illustrate the vulnerability classification on the COVID‐19 pandemic. This article will be of interest to both risk researchers and practitioners.
Progradation of a mid‐Cretaceous distributive fluvial system: The upper member of the Bima Formation, Northern Benue Trough, Nigeria
Authors: Aliyuda Kachalla , Howell John 
Published: November 2020

AbstractBasin‐wide analysis of an ancient distributive fluvial system (the upper Bima Formation) was carried out using field‐based observation/measurement and ‘photo‐realistic’ virtual outcrop data from 19 locations with good exposure of the upper Bima Formation in the Northern Benue Trough. The goal of this study is to provide an assessment of the spatial distribution of both vertical and lateral trends within the upper Bima distributive fluvial system. Vertical and lateral variations of the different facies of the formation were assessed quantitatively; this includes the analysis of the vertical and lateral distribution of proximal, medial and distal facies, the thickness and widths of channel fill deposits, grain‐size variation and the proportion of floodplain to channel fill deposits across the 19 locations in the basin. Trends observed across the sections indicate a progradation of the mega‐fan. The facies tracts preserved within the different portions of the distributive fluvial system vary. In the proximal part, in Lamurde, Tashan Alaji, Ture and Tula, the sections show only medial passing up to proximal facies. The distal lacustrine facies at the base of the section are absent. In the medial part of the system at Hinna, the successions preserve distal passing upward into medial facies. The gradual lateral transition from proximal to medial to distal facies, upward decrease in floodplain to channel fill deposits, upward increase in channel fill thicknesses and widths, all suggest that the Bima system is a prograding distributive fluvial system.
Differences in pacing pattern and sub‐technique selection between young and adult competitive cross‐country skiers
Authors: Sollie Ove , Gløersen Øyvind , Gilgien Matthias , Losnegard Thomas 
Published: November 2020

The present study describes differences in pacing patterns and sub‐technique selection in young compared to adult competitive cross‐country skiers. Eleven young male skiers (YOS) (14.4 ± 0.5 years, O2peak 63.9 ± 2.8 mL∙kg‐1∙min‐1) and eight adult male skiers (ADS) (22.6 ± 4.3 years, O2peak 77.4 ± 4.4 mL∙kg‐1∙min‐1) performed a free technique rollerski time trial (TT) over a distance of 4.3 km (YOS) and 13.1 km (ADS) to simulate normal racing distances. A GNSS/IMU system was used to track position, speed, and classify sub‐techniques. Skiing economy and O2peak were measured on an additional day to calculate the relative oxygen demand (O2dem) in 13 segments of the TT. YOS were slower than ADS in all types of terrain (mean speed difference of 13%), with differences for uphills of 19%, undulating terrain of 11% and downhills of 8% (all P < .05). The mean relative O2dem tended to be higher for YOS compared to ADS (120% vs 112% of O2peak, P = .09), and the difference was more pronounced in the initial four segments of the race (130% vs 110% of O2peak, P < .01). YOS used more of the sub‐technique Gear 2 (23 ± 7 vs 14 ± 4%), less Gear 3 (36 ± 7 vs 45 ± 5%), and had more frequent transitions between sub‐techniques (18 ± 2 vs 15 ± 3 km‐1) (all P < .05) than ADS. Over an age‐related distance, young skiers tend to exhibit higher mean exercise intensity than adult elite skiers, with a more pronounced positive pacing pattern. Differences in physical ability affect speed and sub‐technique selections, implying a need for differentiating technical training for different ages and levels.
Intersecting Vulnerabilities, Intersectional Discrimination, and Stigmatization Among People Living Homeless in Nicaragua
Authors: Vázquez José Juan , Suarez Alexia C. , Berríos Alberto E. , Panadero Sonia 
Published: November 2020

ObjectiveThe main objective of this study is to examine the intersecting vulnerabilities, intersectional discrimination, and stigmatization experienced by homeless people living in León (Nicaragua).MethodThe data analyzed come from a Point‐In‐Time count carried out in the city of León, which identified 82 people living homeless. Forty‐seven of the people identified responded to a brief questionnaire that provided more accurate information.ResultsThe results obtained showed that people living homeless in León largely presented “non‐white” ethnic‐racial traits, poor personal hygiene, readily visible physical health problems, and observable symptoms associated with mental health problems and alcohol and/or drug abuse.ConclusionsThe information we obtained showed that people living homeless in León were subject to multiple intersecting vulnerabilities and aggravated forms of intersectional discrimination and social stigmatization, with a cumulative effect that could be highly detrimental to their social inclusion processes, leading to high levels of chronification of homelessness.
“GIS works!”—But why, how, and for whom? Findings from a systematic review
Authors: Schulze Uwe 
Published: November 2020

AbstractThis article presents the findings from systematically reviewing 26 empirical research studies published from 2005 to 2014 on the use of GIS for learning and teaching. By employing methods of narrative synthesis and qualitative content analysis, the study gives evidence about the state of knowledge of competence‐based GIS education. The results explain what factors and variables effect GIS learning in terms of technology use, major subject contents, learning contexts, and didactic and pedagogical aspects. They also show what facets of knowledge, process skills, and affect the research literature has investigated. The analysis of the type and quality of the methods used indicates that current GIS education research is a heterogeneous field that needs a systematic research framework for future efforts, according to empirical education research.
Important considerations about space‐time data: Modeling, scrutiny, and ratification
Authors: Griffith Daniel A. 
Published: November 2020

AbstractSpace‐time data are becoming more abundant as time goes by, with hands‐on interest in them becoming more prevalent. These data have a very sensitive ordering in space and time, one that the simplest of recording errors can scramble. These data are also complex, containing both spatial and temporal autocorrelation coupled with their interaction. One goal of many researchers is to disentangle and account for these autocorrelation components in a parsimonious way. This article presents three competing model specifications to achieve this end. In addition, it outlines seven best practices for vetting space‐time datasets. This article cites a publicly available corrupt (containing at least errors of omission) rabies dataset to illustrate how a large volume of potentially valuable data can be rendered meaningless. In addition, it exemplifies postulated contentions about the United States National Cancer Institute Surveillance, Epidemiology, and End Results Program’s 1969–2018 population‐by‐county dataset, a collection of population counts held in high esteem. One major empirical finding is that this particular dataset exhibits traits that may merit remedial revisions action. A key conceptual finding is a suggested set of best practices for space‐time data proofreading. These two findings contribute to an ultimate goal of a large collection of certified open access space‐time datasets supporting repeatable and replicable scientific analyses.
A retrospective study assessing the characteristics of COVID‐19 convalescent plasma donors and donations
Authors: Del Fante Claudia , Franchini Massimo , Baldanti Fausto , Percivalle Elena , Glingani Claudia , Marano Giuseppe , Mengoli Carlo , Mortellaro Cristina , Viarengo Gianluca , Perotti Cesare , Liumbruno Giancarlo Maria 
Published: November 2020

AbstractBackgroundAlthough many trials are currently investigating the safety and efficacy of convalescent plasma (CP) in critically ill COVID‐19 patients, there is a paucity of ongoing and published studies evaluating the CP donors' side. This retrospective study reports the first Italian experience on CP donors' selection and donations.MethodsPatients aged 18‐68 years who had recovered from COVID‐19 at least 2 weeks previously were recruited between March 18 and June 30, 2020 in a study protocol at the Italian hospitals of Pavia and Mantova.ResultsDuring the study period, 494 of 512 donors recruited were judged eligible and underwent 504 plasmapheresis procedures. Eighty‐five percent (437/512) of the CP donors were males. The average time between symptom recovery and CP donation was 36.6 (±20.0) days. Four hundred and eighty‐eight plasmapheresis procedures (96.8%) were concluded and each unit was divided into two subunits (total 976) with an average volume of 316.2 (±22.7) mL. Ninety‐three percent (460/494) of CP donors at the time of plasma donation had a neutralizing IgG titer ≥1:80. Plasmapheresis‐related adverse reactions occurred in 2.6% (13/504) of cases; all the reactions were mild and none required therapeutic intervention. Donors' age and COVID‐19 severity were positively associated with greater antibody responses.ConclusionThis study demonstrates the feasibility and safety of a pilot CP program conducted in Italy. The identification of factors (ie, age and severity of COVID‐19) positively associated with higher neutralizing antibody titers at the time of donation may help to optimize the selection of CP donors.
G-torseurs en théorie de Hodgep-adique
Authors: Fargues Laurent 
Published: November 2020

RésuméÉtant donné un groupe réductif$G$sur une extension de degré fini de$\mathbb {Q}_p$on classifie les$G$-fibrés sur la courbe introduite dans Fargues and Fontaine [Courbes et fibrés vectoriels en théorie de Hodge$p$-adique, Astérisque406(2018)]. Le résultat est interprété en termes de l'ensemble$B(G)$de Kottwitz. On calcule également la cohomologie étale de la courbe à coefficients de torsion en lien avec la théorie du corps de classe local.
Regional variation in the reliability of sweat rate measured via the ventilated capsule technique during passive heating
Authors: Rutherford Maura M. , Akerman Ashley P. , Notley Sean R. , Meade Robert D. , Schmidt Madison D. , Kenny Glen P. 
Published: November 2020

AbstractThe ventilated capsule technique is widely used to measure time‐dependent changes in sweating in humans. However, evaluations of its reliability (consistency) have been restricted to the forearm, despite extensive regional heterogeneity in the sweating response. Given the importance of such information for experimental design, statistical analysis and interpretation, we determined the reliability of local sweat rate at nine sites during whole‐body passive (resting) heating. On three separate occasions, a water‐perfused suit was used to increase and clamp oesophageal temperature 0.6, 1.2 and 1.8°C above baseline in 14 young men [24 (SD 5) years of age], while sweat rate was measured at the forehead, chest, abdomen, biceps, forearm, hand, quadriceps, calf and foot using ventilated capsules (3.8 cm2). Absolute and relative reliability were determined via the coefficient of variation (CV) and intraclass correlation coefficient (ICC), respectively. At low heat strain (0.6°C), almost all sites had acceptable relative reliability (ICC ≥ 0.70) and moderate absolute reliability (CV < 25%). At moderate heat strain (1.2°C), only the abdomen, hand, quadriceps and foot had acceptable relative reliability, whereas the forehead, abdomen, forearm, hand and quadriceps had moderate absolute reliability. At high heat strain (1.8°C), relative reliability was acceptable at the abdomen, quadriceps, calf and foot, whereas the chest, abdomen, forearm, hand, quadriceps, calf and foot had moderate absolute reliability. Our findings indicate that the measurement site and level of heat strain impact the consistency of local sweat rate measured via the ventilated capsule technique, and we demonstrate the possible implications for research design and data interpretation.
Programming with a read-eval-synth loop
Authors: Peleg Hila , Gabay Roi , Itzhaky Shachar , Yahav Eran 
Published: November 2020

A frequent programming pattern for small tasks, especially expressions, is to repeatedly evaluate the program on an input as its editing progresses. The Read-Eval-Print Loop (REPL) interaction model has been a successful model for this programming pattern. We present the new notion of Read-Eval-Synth Loop (RESL) that extends REPL by providing in-place synthesis on parts of the expression marked by the user. RESL eases programming by synthesizing parts of a required solution. The underlying synthesizer relies on a partial solution from the programmer and a few examples.
RESL hinges on bottom-up synthesis with general predicates and sketching, generalizing programming by example. To make RESL practical, we present a formal framework that extends observational equivalence to non-example specifications.
We evaluate RESL by conducting a controlled within-subjects user-study on 19 programmers from 8 companies, where programmers are asked to solve a small but challenging set of competitive programming problems. We find that programmers using RESL solve these problems with far less need to edit the code themselves and by browsing documentation far less. In addition, they are less likely to leave a task unfinished and more likely to be correct.
Adversarial examples for models of code
Authors: Yefet Noam , Alon Uri , Yahav Eran 
Published: November 2020

Neural models of code have shown impressive results when performing tasks such as predicting method names and identifying certain kinds of bugs. We show that these models are vulnerable to
adversarial examples
, and introduce a novel approach for
attacking
trained models of code using adversarial examples. The main idea of our approach is to force a given trained model to make an incorrect prediction, as specified by the adversary, by introducing small perturbations that do not change the program’s semantics, thereby creating an adversarial example. To find such perturbations, we present a new technique for Discrete Adversarial Manipulation of Programs (DAMP). DAMP works by deriving the desired prediction with respect to the model’s
inputs
, while holding the model weights constant, and following the gradients to slightly modify the input code.

We show that our DAMP attack is effective across three neural architectures: code2vec, GGNN, and GNN-FiLM, in both Java and C#. Our evaluations demonstrate that DAMP has up to 89% success rate in changing a prediction to the adversary’s choice (a targeted attack) and a success rate of up to 94% in changing a given prediction to any incorrect prediction (a non-targeted attack). To defend a model against such attacks, we empirically examine a variety of possible defenses and discuss their trade-offs. We show that some of these defenses can dramatically drop the success rate of the attacker, with a minor penalty of 2% relative degradation in accuracy when they are not performing under attack.
Our code, data, and trained models are available at <a>https://github.com/tech-srl/adversarial-examples</a> .
Testing differential privacy with dual interpreters
Authors: Zhang Hengchu , Roth Edo , Haeberlen Andreas , Pierce Benjamin C. , Roth Aaron 
Published: November 2020

Applying differential privacy at scale requires convenient ways to check that programs computing with sensitive data appropriately preserve privacy. We propose here a fully automated framework for
testing
differential privacy, adapting a well-known “pointwise” technique from informal proofs of differential privacy. Our framework, called DPCheck, requires no programmer annotations, handles all previously verified or tested algorithms, and is the first fully automated framework to distinguish correct and buggy implementations of PrivTree, a probabilistically terminating algorithm that has not previously been mechanically checked.

We analyze the probability of DPCheck mistakenly accepting a non-private program and prove that, theoretically, the probability of false acceptance can be made exponentially small by suitable choice of test size.
We demonstrate DPCheck’s utility empirically by implementing all benchmark algorithms from prior work on mechanical verification of differential privacy, plus several others and their incorrect variants, and show DPCheck accepts the correct implementations and rejects the incorrect variants.
We also demonstrate how DPCheck can be deployed in a practical workflow to test differentially privacy for the 2020 US Census Disclosure Avoidance System (DAS).
Geometry types for graphics programming
Authors: Geisler Dietrich , Yoon Irene , Kabra Aditi , He Horace , Sanders Yinnon , Sampson Adrian 
Published: November 2020

In domains that deal with physical space and geometry, programmers need to track the coordinate systems that underpin a computation. We identify a class of geometry bugs that arise from confusing which coordinate system a vector belongs to. These bugs are not ruled out by current languages for vector-oriented computing, are difficult to check for at run time, and can generate subtly incorrect output that can be hard to test for.
We introduce a type system and language that prevents geometry bugs by reflecting the coordinate system for each geometric object. A value's geometry type encodes its reference frame, the kind of geometric object (such as a point or a direction), and the coordinate representation (such as Cartesian or spherical coordinates). We show how these types can rule out geometrically incorrect operations, and we show how to use them to automatically generate correct-by-construction code to transform vectors between coordinate systems. We implement a language for graphics programming, Gator, that checks geometry types and compiles to OpenGL's shading language, GLSL. Using case studies, we demonstrate that Gator can raise the level of abstraction for shader programming and prevent common errors without inducing significant annotation overhead or performance cost.
Hidden inheritance: an inline caching design for TypeScript performance
Authors: Wu Zhefeng , Sun Zhe , Gong Kai , Chen Lingyun , Liao Bin , Jin Yihua 
Published: November 2020

TypeScript is a dynamically typed language widely used to develop large-scale applications nowadays. These applications are usually designed with complex class or interface hierarchies and have highly polymorphic behaviors. These object-oriented (OO) features will lead to inefficient inline caches (ICs) or trigger deoptimizations, which impact the performance of TypeScript applications.
To address this problem, we introduce an inline caching design called hidden inheritance (HI). The basic idea of HI is to cache the static information of class or interface hierarchies into hidden classes, which are leveraged to generate efficient inline caches for improving the performance of OO-style TypeScript programs. The HI design is implemented in a TypeScript engine STSC (Static TypeScript Compiler) including a static compiler and a runtime system. STSC statically generates hidden classes and enhanced inline caches, which are applied to generate specialized machine code via ahead-of-time compilation (AOTC) or just-in-time compilation (JITC). To evaluate the efficiency of this technique, we implement STSC on a state-of-the-art JavaScript virtual machine V8 and demonstrate its performance improvements on industrial benchmarks and applications.