bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring PIF4's contribution to early flowering in plants under daily variable temperature and its tissue‐specific flowering gene network
Authors: Jenkitkonchai Jutapak , Marriott Poppy , Yang Weibing , Sriden Napaporn , Jung Jae‐Hoon , Wigge Philip A. , Charoensawan Varodom 
Published: July 2021

AbstractMolecular mechanisms of how constant temperatures affect flowering time have been largely characterized in the model plant Arabidopsis thaliana; however, the effect of natural daily variable temperature outside laboratories is only partly explored. Several flowering genes have been shown to play important roles in temperature responses, including PHYTOCHROME‐INTERACTING FACTOR 4 (PIF4) and FLOWERING LOCUS C (FLC), the two genes encoding for the transcription factors (TFs) that act antagonistically to regulate flowering time by activating and repressing floral integrator FLOWERING LOCUS T (FT), respectively. In this study, we have taken a multidisciplinary approach to explore the contribution of PIF4 to the early flowering observed in the daily variable temperature (VAR) and to broaden its transcriptional network using publicly available transcriptomic data. We observed early flowering in the natural accessions Col‐0, C24 and their late flowering hybrid C24xCol grown under VAR, as compared with a constant temperature (CON). The loss‐of‐function mutation of PIF4 exhibits later flowering in VAR in both the Col‐0 parent and the C24xCol hybrid, suggesting that PIF4, at least in part, contributes to acceleration of flowering in the VAR condition. To investigate the interplay between PIF4 and its flowering regulator counterparts, FLC and FT, we performed transcriptional analyses and found that VAR increased PIF4 transcription at the end of the day when temperature peaked at 32°C, when FT transcription was also elevated. On the other hand, we observed a decrease in FLC transcription in the 4‐week‐old plants grown in VAR, as well as in the plants with PIF4 overexpression grown in CON. These results raise a possibility that PIF4 might also regulate FT indirectly through the repression of FLC, in addition to the well‐characterized direct control of PIF4 over FT. To further expand our view on the PIF4‐orientated flowering gene network in response to temperature changes, we have constructed a coexpression–transcriptional regulatory network by combining publicly available transcriptomic data and gene regulatory interactions of PIF4 and its closely related flowering genes, PIF5, FLC, and ELF3. The network model reveals conserved and tissue‐specific regulatory functions, which are useful for confirming as well as predicting the functions and regulatory interactions between these key flowering genes.
Measuring canopy height in soybean and wheat using a low‐cost depth camera
Authors: Morrison Malcolm J. , Gahagan Alison Claire , Lefebvre Marc Bruno 
Published: July 2021

AbstractCanopy height is an essential trait in high throughput phenotyping that is often only captured as a single point, which is not always representative of canopy height. New 3D depth cameras such as the RealSense D415 (Intel Corporation, Santa Clara, CA, USA) may provide a fast and affordable solution for measuring height from portable, ground‐based phenomics systems. Our goal was to determine if the D415 was effective at measuring crop heights under field conditions in wheat (Triticum aestivum) and soybean (Glycine max) plots. The D415 camera was integrated into our PlotCam platform using the open software development kit from Intel. Distance arrays were captured for each plot at weekly intervals over the growing season. These were compared to canopy heights measured using a single point LiDAR (SPL) system operated by hand. Over the growing season the D415 heights were significantly correlated with the SPL heights in both wheat and soybean with coefficients of 0.77 and 0.95 and NRMSE 0.23 and 0.17 m, respectively. Early season D415 height measurements were not as similar to the SPL as the mid‐and late‐season measurements in wheat and soybean. The relatively low cost and open software development kit of the D415 makes it a promising tool for high throughput phenotyping applications.
Molecular innovations underlying resistance to nicotine and neonicotinoids in the aphid Myzus persicae
Authors: Troczka Bartlomiej J , Singh Kumar Saurabh , Zimmer Christoph T , Vontas John , Nauen Ralf , Hayward Alex , Bass Chris 
Published: July 2021

AbstractThe green peach aphid, Myzus persicae, is a globally distributed highly damaging crop pest. This species has demonstrated an exceptional ability to evolve resistance to both synthetic insecticides used for control, and natural insecticides produced by certain plants as a chemical defense against insect attack. Here we review work characterizing the evolution of resistance in M. persicae to the natural insecticide nicotine and the structurally related class of synthetic neonicotinoid insecticides. We outline how research on this topic has provided insights into long‐standing questions of both evolutionary and applied importance. These include questions pertaining to the origins of novel traits, the number and nature of mutational events or ‘adaptive steps’ underlying the evolution of new phenotypes, and whether host plant adaptations can be co‐opted to confer resistance to synthetic insecticides. Finally, research on the molecular mechanisms underlying insecticide resistance in M. persicae has generated several outstanding questions on the genetic architecture of resistance to both natural and synthetic xenobiotics, and we conclude by identifying key knowledge gaps for future research. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Prediction of overall survival in patients across solid tumors following atezolizumab treatments: A tumor growth inhibition–overall survival modeling framework
Authors: Chan Phyllis , Marchand Mathilde , Yoshida Kenta , Vadhavkar Shweta , Wang Nina , Lin Alyse , Wu Benjamin , Ballinger Marcus , Sternheim Nitzan , Jin Jin Y. , Bruno René 
Published: July 2021

AbstractThe objectives of the study were to use tumor size data from 10 phase II/III atezolizumab studies across five solid tumor types to estimate tumor growth inhibition (TGI) metrics and assess the impact of TGI metrics and baseline prognostic factors on overall survival (OS) for each tumor type. TGI metrics were estimated from biexponential models and posttreatment longitudinal data of 6699 patients. TGI‐OS full models were built using parametric survival regression by including all significant baseline covariates from the Cox univariate analysis followed by a backward elimination step. The model performance was evaluated for each trial by 1000 simulations of the OS distributions and hazard ratios (HR) of the atezolizumab‐containing arms versus the respective controls. The tumor growth rate estimate was the most significant predictor of OS across all tumor types. Several baseline prognostic factors, such as inflammatory status (C‐reactive protein, albumin, and/or neutrophil‐to‐lymphocyte ratio), tumor burden (sum of longest diameters, number of metastatic sites, and/or presence of liver metastases), Eastern Cooperative Oncology Group performance status, and lactate dehydrogenase were also highly significant across multiple studies in the final multivariate models. TGI‐OS models adequately described the OS distribution. The model‐predicted HRs indicated good model performance across the 10 studies, with observed HRs within the 95% prediction intervals for all study arms versus controls. Multivariate TGI‐OS models developed for different solid tumor types were able to predict treatment effect with various atezolizumab monotherapy or combination regimens and could be used to support design and analysis of future studies.
Reproductive status of a remnant Lake sturgeon (Acipenser fulvescens) population: Spawning and larval drift in the lower Fox River, Wisconsin
Authors: Tucker Stefan R. , Houghton Christopher J. , Harris Brandon S. , Elliott Robert F. , Donofrio Michael C. , Forsythe Patrick S. 
Published: July 2021

AbstractThe Lower Fox River is a modified tributary of Green Bay, Lake Michigan that hosts a remnant Lake Sturgeon (Acipenser fulvescens) population. Reproduction has been confirmed, although annual spawning events have been described as small and concerns regarding the long‐term viability of the population remain. Contemporary and comprehensive surveys of spawning habitat, spawning stock, and production to the larval stage have not been conducted. The goal of this study was to describe spawning habitat, determine the size and demographic structure of the spawning stock, and quantify larval production (2017–2019) to identify impediments to population growth and recovery. Over 130 adults were present during annual spawning runs and spawning activity was consistently concentrated along the eastern riverbank. Adequate population structure exists to support reproductive success, but larval catch was low, ranging from 0 to 14 larvae captured annually. Evaluation of the riverbed below the De Pere Dam suggests the extent of the substrate available for spawning adult Lake Sturgeon is lower (~70% less) than previously described. Habitat deemed suitable for spawning exists offshore below the dam, but most habitat used for spawning is arranged along the eastern man‐made shoreline. However, nearshore spawning is problematic at this location due to fluctuating discharge from dam operation and periodic seiche events. Possible impediments limiting the success of Lake Sturgeon reproduction include dewatering of eggs, retention of eggs and larvae, algae colonization, and egg predation. We discuss these issues in the context of previous Lake Sturgeon research, future monitoring of spawning adults/larval production, and the likelihood that river habitat improvement will foster increased reproductive success.
Significantly Raised Visible‐Light Photocatalytic H2 Evolution on a 2D/2D ReS2/In2ZnS4 van der Waals Heterostructure
Authors: Ran Jingrun , Zhang Hongping , Qu Jiangtao , Shan Jieqiong , Davey Kenneth , Cairney Julie M. , Jing Liqiang , Qiao Shi‐Zhang 
Published: July 2021

AbstractOwing to dwindling fossil fuels reserves, the development of alternative renewable energy sources is globally important. Photocatalytic hydrogen (H2) evolution represents a practical and affordable alternative to convert sunlight into carbon‐free H2 fuel. Recently, 2D/2D van der Waals heterostructures (vdWHs) have attracted significant research attention for photocatalysis. Here, for the first time a ReS2/In2ZnS4 2D/2D vdWH synthesized via a facile physical mixing is reported. It exhibits a highly promoted photocatalytic H2‐evolution rate of 2515 µmol h−1 g−1. Importantly, this exceeds that for pristine In2ZnS4 by about 22.66 times. This, therefore, makes ReS2/In2ZnS4 one of the most efficient In2ZnS4‐based photocatalysts without noble‐metal cocatalysts. Advanced characterizations and theoretical computations results show that interlayer electronic interaction within ReS2/In2ZnS4 vdWH and atomic‐level S active centers along the edges of ReS2 NSs work collaboratively to result in the boosted light‐induced H2 evolution. Results will be of immediate benefit in the rational design and preparation of vdWHs for applications in catalysis/(opto)electronics.
Integrating Pt16Te Nanotroughs and Nanopillars into a 3D “Self‐Supported” Hierarchical Nanostructure for Boosting Methanol Electrooxidation
Authors: Geng Wen‐Chao , Zhang Yu‐Jie , Yu Lan , Li Jing‐Jing , Sang Ji‐Long , Li Yong‐Jun 
Published: July 2021

AbstractTo develop durable and low‐price catalysts of methanol oxidation to commercialize direct methanol fuel cell, many attempts have been made at fabricating Pt‐based hybrids by designing component‐, morphology‐, facet‐, integration‐pattern‐varied nanostructures, and have achieved considerable successes. However, most of present catalysts still lack robust catalytic durability especially owing to the corrosion of mixed carbon and the poor mechanical stability of catalyst layer. Herein, Te nanowire array is transformed at an air/water interface into a 3D Pt16Te hierarchical nanostructure via an interface‐confined galvanic replacement reaction. As‐formed Pt16Te nanostructure has an asymmetrical architecture composed of nanotroughs and nanopillars, and nanopillars are perpendicular to nanotroughs with a loose arrangement. Pt16Te hierarchical nanostructure has a “self‐supported” feature and, when directly used as the catalyst of methanol electrooxidation, exhibits superior catalytic activity (>four times larger in mass activity than state‐of‐the‐art Pt/C in either acidic or basic solution) and long‐term durability (after 500 cycles of cyclic voltammetric measurement, more than 55% of the initial specific activity remains whereas Pt/C only remains 22.2% in acidic solution and almost loses all activity in basic solution). This study fully demonstrates that designing “self‐supported” catalyst film may be the next promising step for improving the catalytic performance of Pt‐based hybrids.
All‐Organic Flexible Ferroelectret Nanogenerator with Fabric‐Based Electrodes for Self‐Powered Body Area Networks
Authors: Wang Ningzhen , Daniels Robert , Connelly Liam , Sotzing Michael , Wu Chao , Gerhard Reimund , Sotzing Gregory A. , Cao Yang 
Published: July 2021

AbstractDue to their electrically polarized air‐filled internal pores, optimized ferroelectrets exhibit a remarkable piezoelectric response, making them suitable for energy harvesting. Expanded polytetrafluoroethylene (ePTFE) ferroelectret films are laminated with two fluorinated‐ethylene‐propylene (FEP) copolymer films and internally polarized by corona discharge. Poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS)‐coated spandex fabric is employed for the electrodes to assemble an all‐organic ferroelectret nanogenerator (FENG). The outer electret‐plus‐electrode double layers form active device layers with deformable electric dipoles that strongly contribute to the overall piezoelectric response in the proposed concept of wearable nanogenerators. Thus, the FENG with spandex electrodes generates a short‐circuit current which is twice as high as that with aluminum electrodes. The stacking sequence spandex/FEP/ePTFE/FEP/ePTFE/FEP/spandex with an average pore size of 3 µm in the ePTFE films yields the best overall performance, which is also demonstrated by the displacement‐versus‐electric‐field loop results. The all‐organic FENGs are stable up to 90 °C and still perform well 9 months after being polarized. An optimized FENG makes three light emitting diodes (LEDs) blink twice with the energy generated during a single footstep. The new all‐organic FENG can thus continuously power wearable electronic devices and is easily integrated, for example, with clothing, other textiles, or shoe insoles.
Propofol alleviates neuropathic pain in chronic constriction injury rat models via the microRNA‐140‐3p/Jagged‐1 peptide/Notch signaling pathway
Authors: Cheng Fang , Qin Wei , Yang Ai‐xing , Yan Feng‐feng , Chen Yu , Ma Jian‐Xin 
Published: July 2021

AbstractChronic constriction injury (CCI) of the sciatic nerve was used to establish neuropathic pain (NP) models in rats. CCI rats were then treated with propofol (Pro) and their paw withdrawal mechanical threshold (PWMT) and paw withdrawal thermal latency (PWTL) were measured. In addition, the expression patterns of tumor necrosis factor‐α (TNF‐α), interleukin‐1β (IL‐1β), and IL‐10 were detected. CCI rats treated with propofol were further injected with antagomiR‐140‐3p to verify the role of miR‐140‐3p in propofol's analgesic actions. In addition to confirming the relationship between miR‐140‐3p and JAG1, the expression patterns of JAG1 itself were detected. Propofol‐treated CCI rats were also injected with Ad‐JAG1 (adenovirus‐packaged JAG1 overexpression vector and Ad‐NC) to test the role of JAG1 in propofol's analgesic mechanism of action. Finally, the levels of JAG1 and Notch pathway‐related proteins were detectedResultsPropofol was found to alleviate NP, including thermal hyperalgesia and mechanical pain threshold. Propofol could also ameliorate neuroinflammation by up‐regulating the expression of IL‐10 and inhibiting the release of TNF‐α and IL‐1β. Mechanically, propofol enhanced the amount of miR‐140‐3p in CCI rats via the regulation of JAG1. Down‐regulation of miR‐140‐3p, or up‐regulation of JAG1, could reduce the protective effect of propofol against NP. Propofol inhibited the activation of Notch signaling via miR‐140‐3p/JAG1 to realize its analgesic effectConclusionOur findings indicated that propofol inhibits inflammatory responses and the Notch signaling pathway via miR‐140‐3p/JAG1 to alleviate NP. These data provide evidence to support a potential clinical therapy for NP.
Introduction
Authors: Wardle Heather 
Published: July 2021

AbstractRecent academic and policy attention focuses on the “convergence” of gambling and games. Yet, looking at the social and historical context of gambling and games, we see they were always intertwined, with both reflecting broader social, economic and cultural conditions. Setting out the argument for this book, this chapter contends that what we see today, with phenomena like loot boxes, is an acceleration of this trend, amplified by the changing technologies which underpin both industries. Little attention has been paid to these broader social and historical processes, which limits our understanding of them and our anticipation of what might happen next. This book aims to act as a primer to place the “convergence” of gambling and gaming within its rightful historical context and encourages us to take a broader perspective when thinking about the impact of these developments.
Learning Probabilistic Termination Proofs
Authors: Abate Alessandro , Giacobbe Mirco , Roy Diptarko 
Published: July 2021

AbstractWe present the first machine learning approach to the termination analysis of probabilistic programs. Ranking supermartingales (RSMs) prove that probabilistic programs halt, in expectation, within a finite number of steps. While previously RSMs were directly synthesised from source code, our method learns them from sampled execution traces. We introduce theneural ranking supermartingale: we let a neural network fit an RSM over execution traces and then we verify it over the source code using satisfiability modulo theories (SMT); if the latter step produces a counterexample, we generate from it new sample traces and repeat learning in a counterexample-guided inductive synthesis loop, until the SMT solver confirms the validity of the RSM. The result is thus a sound witness of probabilistic termination. Our learning strategy is agnostic to the source code and its verification counterpart supports the widest range of probabilistic single-loop programs that any existing tool can handle to date. We demonstrate the efficacy of our method over a range of benchmarks that include linear and polynomial programs with discrete, continuous, state-dependent, multi-variate, hierarchical distributions, and distributions with undefined moments.
Foundations of Fine-Grained Explainability
Authors: Hallé Sylvain , Tremblay Hugo 
Published: July 2021

AbstractExplainability is the process of linking part of the inputs given to a calculation to its output, in such a way that the selected inputs somehow “cause” the result. We establish the formal foundations of a notion of explainability for arbitrary abstract functions manipulating nested data structures. We then establish explanation relationships for a set of elementary functions, and for compositions thereof. A fully functional implementation of these concepts is finally presented and experimentally evaluated.
Latticed k-Induction with an Application to Probabilistic Programs
Authors: Batz Kevin , Chen Mingshuai , Kaminski Benjamin Lucien , Katoen Joost-Pieter , Matheja Christoph , Schröer Philipp 
Published: July 2021

AbstractWe revisit two well-established verification techniques,k-inductionandbounded model checking(BMC), in the more general setting of fixed point theory over complete lattices. Our main theoretical contribution islatticed k-induction, which (i) generalizes classicalk-induction for verifying transition systems, (ii) generalizes Park induction for bounding fixed points of monotonic maps on complete lattices, and (iii) extends from naturalskto transfinite ordinals$$\kappa $$κ, thus yielding$$\kappa $$κ-induction.The lattice-theoretic understanding ofk-induction and BMC enables us to apply both techniques to thefully automatic verification of infinite-state probabilistic programs. Our prototypical implementation manages to automatically verify non-trivial specifications for probabilistic programs taken from the literature that—using existing techniques—cannot be verified without synthesizing a stronger inductive invariant first.
Rigorous Roundoff Error Analysis of Probabilistic Floating-Point Computations
Authors: Constantinides George , Dahlqvist Fredrik , Rakamarić Zvonimir , Salvia Rocco 
Published: July 2021

AbstractWe present a detailed study of roundoff errors in probabilistic floating-point computations. We derive closed-form expressions for the distribution of roundoff errors associated with a random variable, and we prove that roundoff errors are generally close to being uncorrelated with their generating distribution. Based on these theoretical advances, we propose a model of IEEE floating-point arithmetic for numerical expressions with probabilistic inputs and an algorithm for evaluating this model. Our algorithm provides rigorous bounds to the output and error distributions of arithmetic expressions over random variables, evaluated in the presence of roundoff errors. It keeps track of complex dependencies between random variables using an SMT solver, and is capable of providing sound but tight probabilistic bounds to roundoff errors using symbolic affine arithmetic. We implemented the algorithm in the PAF tool, and evaluated it on FPBench, a standard benchmark suite for the analysis of roundoff errors. Our evaluation shows that PAF computes tighter bounds than current state-of-the-art on almost all benchmarks.
Automatic Generation and Validation of Instruction Encoders and Decoders
Authors: Xu Xiangzhe , Wu Jinhua , Wang Yuting , Yin Zhenguo , Li Pengfei 
Published: July 2021

AbstractVerification of instruction encoders and decoders is essential for formalizing manipulation of machine code. The existing approaches cannot guarantee the critical consistency property, i.e., that an encoder and its corresponding decoder are mutual inverses of each other. We observe that consistent encoder-decoder pairs can be automatically derived from bijections inherently embedded in instruction formats. Based on this observation, we develop a framework for writing specifications that capture these bijections, for automatically generating encoders and decoders from these specifications, and for formally validating the consistency and soundness of the generated encoders and decoders by synthesizing proofs in Coq and discharging verification conditions using SMT solvers. We apply this framework to a subset of X86-32 instructions to illustrate its effectiveness in these regards. We also demonstrate that the generated encoders and decoders have reasonable performance.