bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility and acceptability of a CF‐specific cognitive‐behavioral preventive intervention for adults integrated into team‐based care
Authors: Friedman Deborah , Smith Beth A. , Bruce Amanda , Schwartz Carolyn E. , Lee Hang , Pinsky Hanna , Gootkind Elizabeth , Hardcastle Margot , Shea Nicole , Roach Christine M. , Miller Caitlin , Polineni Deepika , Salathe Matthias , Quittner Alexandra L. , Georgiopoulos Anna M. 
Published: August 2022

AbstractBackgroundA cystic fibrosis (CF)‐specific cognitive‐behavioral therapy intervention (CF‐CBT) was developed in partnership with the CF community to advance preventive mental health care. Multidisciplinary providers across three centers were trained to deliver CF‐CBT for this pilot assessing feasibility/acceptability and preliminary effectiveness of an integrated model of care.MethodsThe 8‐session CF‐CBT was delivered to 14 adults with mild depression and/or anxiety symptoms in‐person and via audio telehealth. Assessment of attrition, engagement, homework completion, treatment satisfaction, and treatment fidelity informed feasibility/acceptability assessment. Mental health outcomes included depression, anxiety, quality of life (Cystic Fibrosis Questionnaire‐Revised [CFQ‐R), perceived stress and coping. Preliminary effectiveness was evaluated with Cohen's d metric of effect sizes (ES) of pre‐post mean change scores.ResultsA total of 108 sessions were conducted; 13 adults completed the intervention; 1 discontinued early. Engagement, homework completion, and treatment acceptability were highly rated (mean = 30; SD = 2, range: 27–32 on a 32‐point scale). Fidelity scores ranged from 85.7% to 93.6%. Large ES changes reflected improvements in depressive symptoms (−0.83), CFQ‐R (Vitality scale: 1.11), and Relaxation Skills (0.93); moderate ES for CFQ‐R Role Functioning (0.63), Awareness of Tension (0.62), Coping Confidence (0.70) and CF‐specific Coping (0.55); and small ES for anxiety symptoms (−0.22), perceived stress (−0.25), Behavioral Activation (0.29), and several CFQ‐R domains, including Emotional Functioning (0.29). Two CFQ‐R subscales decreased (Body Image, Eating Concerns).ConclusionsResults indicated feasibility and acceptability of CF‐CBT and its integration into team‐based CF care with promising effectiveness, especially for depression. A multicenter randomized controlled trial of CF‐CBT will further examine effectiveness of a CF‐specific integrated care model.
Front Cover Image, Volume 78, Issue 9
Authors: Zhang Mengdi , Yan Junjie , Ali Abid , Gao Yulin 
Published: August 2022

The cover image is based on the Research Article Potato plant variety affects the performance and oviposition preference of Phthorimaea operculella Zeller (Lepidoptera: Gelechiidae) by Mengdi Zhang et al., https://doi.org/10.1002/ps.6625. Image Credit: Yulin Gao.image
Assessment of a zinc finger protein gene (MPZC3H10) as potential RNAi target for green peach aphid Myzus persicae control
Authors: Xie Xiucheng , Shang Feng , Ding Bi‐Yue , Yang Li , Wang Jin‐Jun 
Published: August 2022

AbstractBACKGROUNDRNA interference (RNAi) has potential application in pest control, and selection of the specific target gene is one of the key steps in RNAi. As an important effector, the zinc finger protein (ZFP) gene has high similarity among aphid species, and may have potential use in an RNAi‐based pest control strategy. This study assessed the control efficiency of an RNAi target, MPZC3H10, a CCCH‐type ZFP gene, against green peach aphid.RESULTSZC3H10 amino acid sequence similarity is more than 97.71% among the five tested aphid species: Myzus persicae, Aphis citricidus, Acyrthosiphon pisum, Diuraphis noxia and Rhopalosiphum maidis. However, no homologous sequence was found in the transcriptome of their ladybeetle predator, Propylaea japonica. Spatial expression patterns revealed that MPZC3H10 showed high expression in the muscle and fat body of M. persicae. The RNAi bioassay revealed that silencing of MPZC3H10 resulted in high mortality (53.33%) in M. persicae. By contrast, there were no observed negative effects on the growth and development of P. japonica when fed on aphids treated with double‐stranded RNA (dsRNA) or injected with a “high dose” of dsRNA.CONCLUSIONTargeting MPZC3H10 showed promising efficiency for green peach aphid control via artificially designed dsRNA, and was safe for the predatory ladybeetle. © 2022 Society of Chemical Industry.
The basics of quantum computing for chemists
Authors: Claudino Daniel 
Published: August 2022

AbstractThe rapid and successful strides in quantum chemistry in the past decades can be largely credited to a conspicuous synergy between theoretical and computational advancements. However, the architectural computer archetype that enabled such a progress is approaching a state of more stagnant development. One of the most promising technological avenues for the continuing progress of quantum chemistry is the emerging quantum computing paradigm. This revolutionary proposal comes with several challenges, which span a wide array of disciplines. In chemistry, it implies, among other things, a need to reformulate some of its long established cornerstones in order to adjust to the operational demands and constraints of quantum computers. Due to its relatively recent emergence, much of quantum computing may still seem fairly nebulous and largely unknown to most chemists. It is in this context that here we review and illustrate the basic aspects of quantum information and their relation to quantum computing insofar as enabling simulations of quantum chemistry. We consider some of the most relevant developments in light of these aspects and discuss the current landscape when of relevance to quantum chemical simulations in quantum computers.
Daily sleep in relation to subjective and physiological stress in an occupational context: Daily vigour as a mediator
Authors: Kinnunen Ulla , Van Laethem Michelle , Sianoja Marjaana , de Bloom Jessica 
Published: August 2022

AbstractStudies on the stress‐sleep relationship consistently demonstrate negative effects of stress on sleep. The reversed relation, however, has received less research attention. Also, field studies on physiological stress are scarce. The aim of this day‐level diary study was to examine daily relationships between sleep quality and quantity, and subjective and physiological stress in an occupational context. Moreover, we examined daily vigour as an underlying mechanism of the sleep‐stress relationship. Participants were 167 knowledge workers who filled in daily questionnaires measuring sleep quality and quantity, morning vigour and subjective afternoon stress on Tuesdays and Thursdays for 5 weeks. Physiological stress was assessed with cortisol decline from morning peak to evening, and with blood pressure in the afternoon. Multilevel path analysis results showed that better sleep quality and longer sleep hours predicted increased vigour the following morning, which in turn predicted lower subjective stress in the afternoon. Sleep quality and quantity were not related to physiological stress neither directly nor indirectly via morning vigour. On the basis of our results, sleep should be considered as a factor affecting vigour which in turn seems to lower stress.
Stress Analysis and Q‐Factor of Free‐Standing (La,Sr)MnO3Oxide Resonators
Authors: Manca Nicola , Remaggi Federico , Plaza Alejandro E. , Varbaro Lucia , Bernini Cristina , Pellegrino Luca , Marré Daniele 
Published: August 2022

AbstractHigh‐sensitivity nanomechanical sensors are mostly based on silicon technology and related materials. The use of functional materials, such as complex oxides having strong interplay between structural, electronic, and magnetic properties, may open possibilities for developing new mechanical transduction schemes and for further enhancement of the device performances. The integration of these materials into micro/nano‐electro‐mechanical systems (MEMS/NEMS) is still at its very beginning and critical basic aspects related to the stress state and the quality factors of mechanical resonators made from epitaxial oxide thin films need to be investigated. Here, suspended micro‐bridges are realized from single‐crystal thin films of (La0.7,Sr0.3)MnO3(LSMO), a prototypical complex oxide showing ferromagnetic ground state at room temperature. These devices are characterized in terms of resonance frequency, stress state, and Q‐factor. LSMO resonators are highly stressed, with a maximum value of ≈260 MPa. The temperature dependence of their mechanical resonance is discussed considering both thermal strain and the temperature‐dependent Young's modulus. The measured Q‐factors reach few tens of thousands at room temperature, with indications of further improvements by optimizing the fabrication protocols. These results demonstrate that complex oxides are suitable to realize high Q‐factor mechanical resonators, paving the way toward the development of full‐oxide MEMS/NEMS sensors.
Cation‐Selective Oxide Semiconductor Mesoporous Membranes for Biomimetic Ion Rectification and Light‐Powered Ion Pumping
Authors: Li Li , Sun Mingyan , Hu Ziying , Nie Xiaoyan , Xiao Tianliang , Liu Zhaoyue 
Published: August 2022

AbstractArtificial membranes precisely imitating the biological functions of ion channels and ion pumps have attracted significant attention to explore nanofluidic energy conversion. Herein, inspired by the cyclic ion transport for the photosynthesis in purple bacteria, a bilayer inorganic membrane (TiO2/AAO) composed of oxide semiconductor (TiO2) mesopores on anodic alumina (AAO) macropores is we developed. This inorganic membrane achieves the functions of ion channels and ion pumps, including the ion rectification and light‐powered ion pumping. The asymmetric charge distribution across the bilayer membrane contributes to the cationic selectivity and ion rectification characteristics. The electrons induced by ultraviolet irradiation introduce a built‐in electric field across TiO2/AAO membrane, which pumps the active ion transport from a low to a high concentration. This work integrates the functions of biological ion channels and ion pumps within an artificial membrane for the first time, which paves the way to explore multifunctional membranes analogous to its biological counterpart.
A Hierarchical Si/C Nanocomposite of Stable Conductive Network Formed Through Thermal Phase Separation of Asphaltenes for High‐Performance Li‐Ion Batteries
Authors: Tan Wen , Wang Lina , Lu Zhouguang , Yang Fan , Xu Zhenghe 
Published: August 2022

AbstractSilicon is one of the most promising anode materials for lithium‐ion batteries. However, the huge volume change of silicon during lithiation/delithiation triggers continuous growth of solid‐electrolyte interphase, loss of conductive contacts and structural collapse of the electrode, which causes a rapid deterioration of battery capacities. Inspired by the polyaromatic molecular nature and phase separation of asphaltenes in bitumen during thermal cracking, a hierarchical Si/C nanocomposite of robust carbon coatings and a firmly connected carbon framework on the silicon surface is synthesized by controlling the concentration of asphaltenes as carbon source and hence desired phase separation during the subsequent carbonization. The electrode made using this special Si/C nanocomposite exhibits a high reversible capacity of 1149 mAh g−1 after 600 cycles with a capacity retention of 98.5% and the operation ability at a high mass loading over 10 mg cm−2 or an area capacity of 23.8 mAh cm−2, which represents one of the highest area capacities reported in open literature but with much more stable and prolonged operations. This simple and efficient strategy is easy to scale up for commercial production to meet the rapid growth of the electric vehicle industry.
Brain Wave‐Like Signal Modulator by Ionic Nanochannel Rectifier Bridges
Authors: Lu Bingxin , Xiao Tianliang , Zhang Caili , Jiang Jiaqiao , Wang Yuting , Diao Xungang , Zhai Jin 
Published: August 2022

AbstractSmart modulation of bioelectric signals is of great significance for the development of brain‐computer interfaces, bio‐computers, and other technologies. The regulation and transmission of bioelectrical signals are realized through the synergistic action of various ion channels in organisms. The bionic nanochannels, which have similar physiological working environment and ion rectification as their biological counterparts, can be used to construct ion rectifier bridges to modulate the bioelectric signals. Here, the artificial smart ionic rectifier bridge with light response is constructed by anodic aluminum oxide (AAO)/poly (spiropyran acrylate) (PSP) nanochannels. The output ion current of the rectifier bridge can be switched between “ON” and “OFF” states by irradiation with UV and visible (Vis) light, and the conversion efficiency (η) of the system in “ON” state is ≈70.5%. The controllable modulation of brain wave‐like signal can be realized by ionic rectifier bridge. The ion transport properties and processes of ion rectifier bridges are explained using theoretical calculations based on Poisson–Nernst–Planck (PNP) equations. These findings have significant implications for the understanding of the intelligent ionic circuit and combination of artificial smart ionic channels to organisms, which provide new avenues for development of intelligent ion devices.
Achieving and Understanding of Highly Efficient Ternary Organic Photovoltaics: From Morphology and Energy Loss to Working Mechanism
Authors: Li Shuixing , Zhan Lingling , Li Yaokai , He Chengliang , Zuo Lijian , Shi Minmin , Chen Hongzheng 
Published: August 2022

AbstractTernary strategy, adding an additional donor (D) or acceptor (A) into conventional binary D:A blend, has shown great potential in improving photovoltaic performances of organic photovoltaics (OPVs) for practical applications. Herein, this review is presented on how efficient ternary OPVs are realized from the aspects of morphology, energy loss, and working mechanism. As to morphology, the role of third component on the formation of preferred alloy‐like‐phase and vertical‐phase, which are driven by the miscibility tuning, is discussed. For energy loss, the effect of the third component on the luminescence enhancement and energetic disordering suppression, which lead to favorable increase of voltage, is presented. Regarding working mechanism, dilution effect and relationships between two acceptors or donor/acceptor, which explain the observed device parameters variations, are analyzed. Finally, some future directions concerning ternary OPVs are pointed out. Therefore, this review can provide a comprehensive understanding of working principles and effective routes for high‐efficiency ternary systems, advancing the commercialization of OPVs.
Evaluating the benefits of empowering model‐driven development with a machine learning classifier
Authors: Marcén Ana C. , Pérez Francisca , Pastor Óscar , Cetina Carlos 
Published: August 2022

AbstractIncreasingly, the model driven engineering (MDE) community is paying more attention to the techniques offered by the machine learning (ML) community. This has led to the application of ML techniques to MDE related tasks in hope of increasing the current benefits of MDE. Nevertheless, there is a lack of empirical experiments that evaluate the benefits that ML brings to MDE. In this work, we evaluate the benefits of empowering model engineers of model‐driven development (MDD) with an ML classifier. To do this, we tackled how to embed the ML classifier as part of the MDD. Then, this was evaluated using two different real industrial cases. Our results show that despite the ML part takes an extra effort, the use of the ML classifier pays off in terms of the quality results, the perceived usefulness, and intention to use.
Understanding perceived influencers on project outcomes and quantifying disciplinary similarities in academic literature
Authors: Eaton Casey , Banks Amanda , Weger Kristin , Mesmer Bryan , Moreland Robert 
Published: August 2022

AbstractModern systems rely on contributions from many disciplines, requiring a systems perspective when evaluating project outcomes. This investigation provides insight into categorizations of influencers on project outcomes across a range of disciplines and the challenges in categorizing perceived influencers on project outcomes when multiple disciplines are collaborating on a project. This research identifies 390 categorizations from 12 disciplines through systematic review, extracts over 4000 perceived influencers on project outcomes as metadata and analyses the categorizations with a focus on disciplinary similarities. The results of the meta‐analysis indicate that contents of categorizations of perceived influencers on project outcomes are diverse, both within and across disciplines, highlighting the significance of understanding the disciplinary contributions to project outcomes, in order to develop successful systems. Findings indicate that practising systems engineers need to consider the many perspectives that are entangled in the design of complex multidisciplinary systems into a holistic view of the system.
Exchange of ammine‐ and fluorido‐ligands in complex salts: The series [Cr(NH3)6][AlF6], [Cr(NH3)5F][SiF6] and K2[Cr(NH3)4F2][Si(NH3)0.5F5.5]2
Authors: Bäucker Christian , Niewa Rainer 
Published: August 2022

AbstractThe three amminechromium(III) complex compounds [Cr(NH3)6][AlF6], [Cr(NH3)5F][SiF6] and K2[Cr(NH3)4F2][Si(NH3)0.5F5.5]2 were obtained from ammonothermal synthesis at Tmax=724 K and pmax=2120 bar. Crystal structures were determined from single crystal X‐ray diffraction. The gradual exchange of ammine ligands by fluoride ligands in the amminechromium(III) ions is reflected by an intriguing change in color. The mutual ligand exchange between ammonia ligands and fluoride ions occurs in both the cations and the anions, indicating the various dissolved species present under the synthetic conditions.
Trainify: A CEGAR-Driven Training and Verification Framework for Safe Deep Reinforcement Learning
Authors: Jin Peng , Tian Jiaxu , Zhi Dapeng , Wen Xuejun , Zhang Min 
Published: August 2022

AbstractDeep Reinforcement Learning (DRL) has demonstrated its strength in developing intelligent systems. These systems shall be formally guaranteed to be trustworthy when applied to safety-critical domains, which is typically achieved by formal verification performed after training. This train-then-verify process has two limits: (i) trained systems are difficult to formally verify due to their continuous and infinite state space and inexplicable AI components (i.e., deep neural networks), and (ii) the ex post facto detection of bugs increases both the time- and money-wise cost of training and deployment. In this paper, we propose a novel verification-in-the-loop training framework called Trainify for developing safe DRL systems driven by counterexample-guided abstraction and refinement. Specifically, Trainify trains a DRL system on a finite set of coarsely abstracted but efficiently verifiable state spaces. When verification fails, we refine the abstraction based on returned counterexamples and train again on the finer abstract states. The process is iterated until all predefined properties are verified against the trained system. We demonstrate the effectiveness of our framework on six classic control systems. The experimental results show that our framework yields more reliable DRL systems with provable guarantees without sacrificing system performance such as cumulative reward and robustness than conventional DRL approaches.
Proof-Guided Underapproximation Widening for Bounded Model Checking
Authors: Chatterjee Prantik , Meda Jaydeepsinh , Lal Akash , Roy Subhajit 
Published: August 2022

AbstractBounded Model Checking (BMC) is a popularly used strategy for program verification and it has been explored extensively over the past decade. Despite such a long history, BMC still faces scalability challenges as programs continue to grow larger and more complex. One approach that has proven to be effective in verifying large programs is called Counterexample Guided Abstraction Refinement (CEGAR). In this work, we propose a complementary approach to CEGAR for bounded model checking of sequential programs: in contrast to CEGAR, our algorithm gradually widens underapproximations of a program, guided by the proofs of unsatisfiability. We implemented our ideas in a tool called Legion. We compare the performance of Legion against that of Corral, a state-of-the-art verifier from Microsoft, that utilizes the CEGAR strategy. We conduct our experiments on 727 Windows and Linux device driver benchmarks. We find that Legion is able to solve 12% more instances than Corral and that Legion exhibits a complementary behavior to that of Corral. Motivated by this, we also build a portfolio verifier, $$\textsc {Legion}^{+}$$

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, solves 15% more benchmarks than Corral with similar computational resource constraints (i.e. each verifier in the portfolio is run with a time budget that is half of the time budget of Corral). Moreover, it is found to be $$2.9\times $$

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SolCMC: Solidity Compiler’s Model Checker
Authors: Alt Leonardo , Blicha Martin , Hyvärinen Antti E. J. , Sharygina Natasha 
Published: August 2022

AbstractFormally verifying smart contracts is important due to their immutable nature, usual open source licenses, and high financial incentives for exploits. Since 2019 the Ethereum Foundation’s Solidity compiler ships with a model checker. The checker, called SolCMC, has two different reasoning engines and tracks closely the development of the Solidity language. We describe SolCMC’s architecture and use from the perspective of developers of both smart contracts and tools for software verification, and show how to analyze nontrivial properties of real life contracts in a fully automated manner.
UCLID5: Multi-modal Formal Modeling, Verification, and Synthesis
Authors: Polgreen Elizabeth , Cheang Kevin , Gaddamadugu Pranav , Godbole Adwait , Laeufer Kevin , Lin Shaokai , Manerkar Yatin A. , Mora Federico , Seshia Sanjit A. 
Published: August 2022

AbstractUCLID5 is a tool for the multi-modal formal modeling, verification, and synthesis of systems. It enables one to tackle verification problems for heterogeneous systems such as combinations of hardware and software, or those that have multiple, varied specifications, or systems that require hybrid modes of modeling. A novel aspect of UCLID5 is an emphasis on the use of syntax-guided and inductive synthesis to automate steps in modeling and verification. This tool paper presents new developments in the UCLID5 tool including new language features, integration with new techniques for syntax-guided synthesis and satisfiability solving, support for hyperproperties and combinations of axiomatic and operational modeling, demonstrations on new problem classes, and a robust implementation.
Does a Program Yield the Right Distribution?
Authors: Chen Mingshuai , Katoen Joost-Pieter , Klinkenberg Lutz , Winkler Tobias 
Published: August 2022

AbstractWe study discrete probabilistic programs with potentially unbounded looping behaviors over an infinite state space. We present, to the best of our knowledge,the first decidability result for the problem of determining whether such a program generates exactly a specified distribution over its outputs(provided the program terminates almost-surely). The class of distributions that can be specified in our formalism consists of standard distributions (geometric, uniform, etc.) and finite convolutions thereof. Our method relies on representing these (possibly infinite-support) distributions asprobability generating functionswhich admit effective arithmetic operations. We have automated our techniques in a tool called$$\textsc {Prodigy}$$PRODIGY, which supports automatic invariance checking, compositional reasoning of nested loops, and efficient queries to the output distribution, as demonstrated by experiments.