bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combined experimental and density functional theory studies on novel 9‐(4/3/2‐cyanophenyl)‐9H‐carbazole‐3‐carbonitrile compounds for organic electronics
Authors: Patil Bhausaheb , Lade Jatin , Sathe Pratima , Tripathi Anuj , Pownthurai B. , Chetti Prabhakar , Jadhav Yogesh , Chaskar Atul 
Published: March 2021

AbstractWe have synthesized a series of novel hybrid molecules 9‐(2‐cyanophenyl)‐9H‐carbazole‐3‐carbonitrile (o‐CNCbzCN), 9‐(3‐cyanophenyl)‐9H‐carbazole‐3‐carbonitrile (m‐CNCbzCN) and 9‐(4‐cyanophenyl)‐9H‐carbazole‐3‐carbonitrile (p‐CNCbzCN), comprising electron‐donating carbazole and electron‐accepting nitrile groups. Three positional isomers were synthesized with a view to tune photophysical and electrochemical properties of the hybrids. The photophysical study displayed absorption maxima in the range of 281–340 nm and 277–298 nm whereas emission maxima in the range of 349–366 nm and 366–369 nm in toluene and dimethylformamide (DMF), respectively. These molecules demonstrated suitable frontier molecular orbital (FMO) energy levels and ensure good thermal and morphological stability. Among these synthesized molecules, m‐CNCbzCN showed very high decomposition temperature (Td = 341°C) whereas p‐CNCbzCN exhibited good glass transition (Tg = 182°C) as well as melting temperature (Tm = 236°C), indicating its significant stability and potential utility as a bipolar host material for efficient phosphorescent organic light‐emitting diodes (PhOLEDs).
Toward Highly Robust Nonvolatile Multilevel Memory by Fine Tuning of the Nanostructural Crystalline Solid‐State Order
Authors: Li Yang , Zhang Cheng , Ling Songtao , Ma Chunlan , Zhang Jinlei , Jiang Yucheng , Zhao Run , Li Hua , Lu Jianmei , Zhang Qichun 
Published: March 2021

AbstractOrganic resistive memory (ORM) offers great promise for next‐generation high‐density multilevel‐cell (MLC) data storage. However, the fine tuning of crystalline order among its active layer still remains challenging, which largely restricts ORM behavior. Here, an exceptional solid‐state transition from disordered orientations to highly‐uniform orientation within the ORM layer is facilely triggered via molecular strategic tailoring. Two diketopyrrolopyrrole‐based small molecular analogues (NI1TDPP and NI2TDPP) are demonstrated to display different symmetry. The asymmetric NI1TDPP shows an irregular solid‐state texture, while the centro‐symmetric NI2TDPP conforms to an ordered out‐of‐plane single‐crystalline pattern that aligns with the foremost charge transportation along the substrate normal, and exhibits excellent MLC memory characteristics. Moreover, this highly oriented pattern guarantees the large‐area film uniformity, leading to the twofold increase in the yield of as‐fabricated ORM devices. This study reveals that the solid‐state crystalline nanostructural order of organic materials can be controlled by reasonable molecular design to actuate high‐performance organic electronic circuits.
Nonrelativistic open string and Yang-Mills theory
Authors: Gomis Jaume , Yan Ziqi , Yu Matthew 
Published: March 2021

Abstract
The classical and quantum worldsheet theory describing nonrelativistic open string theory in an arbitrary nonrelativistic open and closed string background is constructed. We show that the low energy dynamics of open strings ending on n coincident D-branes in flat spacetime is described by a Galilean invariant U(n) Yang-Mills theory. We also study nonrelativistic open string excitations with winding number and demonstrate that their dynamics can be encoded into a local gauge theory in one higher dimension. By demanding conformal invariance of the boundary couplings, the nonlinear equations of motion that govern the consistent open string backgrounds coupled to an arbitrary closed background (described by a string Newton-Cartan geometry, Kalb-Ramond, and dilaton field) are derived and shown to emerge from a Galilean invariant Dirac-Born-Infeld type action.
Setting the string shoving picture in a new frame
Authors: Bierlich Christian , Chakraborty Smita , Gustafson Gösta , Lönnblad Leif 
Published: March 2021

Abstract
Based on the recent success of the Angantyr model in describing multiplicity distributions of the hadronic final state in high energy heavy ion collisions, we investigate how far one can go with a such a string-based scenario to describe also flow effects measured in such collisions.For this purpose we improve our previous so-called shoving model, where strings that are close in space-time tend to repel each other in a way that could generate anisotropic flow, and we find that this model can indeed generate such flows in AA collisions. The flow generated is not quite enough to reproduce measurements, but we identify some shortcomings in the presented implementation of the model that, when fixed, could plausibly give a more realistic amount of flow.
Probing light dark scalars with future experiments
Authors: Bertuzzo Enrico , Taoso Marco 
Published: March 2021

AbstractWe investigate a dark sector containing a pair of light non-degenerate scalar particles, with masses in the MeV-GeV range, coupled to the visibile sector through heavier mediators. The heaviest dark state is long-lived, and its decays offer new testable signals. We analyze the prospects for detection with the proposed beam-dump facility SHiP, and the proposed LHC experiments FASER and MATHUSLA. Moreover, we consider bounds from the beam-dump experiment CHARM and from colliders (LEP, LHC and BaBar). We present our results both in terms of an effective field theory, where the heavy mediators have been integrated out, and of a simplified model containing a vector boson mediator, which can be heavy ≳$$ \mathcal{O}(1) $$O1TeV, or light$$ \mathcal{O}(10) $$O10GeV. We show that future experiments can test large portions of the parameter space currently unexplored, and that they are complementary to future High-Luminosity LHC searches.
L∗-based learning of Markov decision processes (extended version)
Authors: Tappler Martin , Aichernig Bernhard K. , Bacci Giovanni , Eichlseder Maria , Larsen Kim G. 
Published: March 2021

Abstract

Automata learning techniques automatically generate systemmodels fromtest observations. Typically, these techniques fall into two categories: passive and active. On the one hand, passive learning assumes no interaction with the system under learning and uses a predetermined training set, e.g., system logs. On the other hand, active learning techniques collect training data by actively querying the system under learning, allowing one to steer the discovery ofmeaningful information about the systemunder learning leading to effective learning strategies. A notable example of active learning technique for regular languages is Angluin’s

L
∗

-algorithm. The

L
∗

-algorithm describes the strategy of a student who learns the minimal deterministic finite automaton of an unknown regular language

L

by asking a succinct number of queries to a teacher who knows

L

.

In this work, we study

L
∗

-based learning of deterministic Markov decision processes, a class of Markov decision processes where an observation following an action uniquely determines a successor state. For this purpose, we first assume an ideal setting with a teacher who provides perfect information to the student. Then, we relax this assumption and present a novel learning algorithm that collects information by sampling execution traces of the system via testing.

Experiments performed on an implementation of our sampling-based algorithm suggest that our method achieves better accuracy than state-of-the-art passive learning techniques using the same amount of test obser vations. In contrast to existing learning algorithms which assume a predefined number of states, our algorithm learns the complete model structure including the state space.
Need for speed: evaluation of dilute and shoot-mass spectrometry for accelerated metabolic phenotyping in bioprocess development
Authors: Reiter Alexander , Herbst Laura , Wiechert Wolfgang , Oldiges Marco 
Published: March 2021

AbstractWith the utilization of small-scale and highly parallelized cultivation platforms embedded in laboratory robotics, microbial phenotyping and bioprocess development have been substantially accelerated, thus generating a bottleneck in bioanalytical bioprocess sample analytics. While microscale cultivation platforms allow the monitoring of typical process parameters, only limited information about product and by-product formation is provided without comprehensive analytics. The use of liquid chromatography mass spectrometry can provide such a comprehensive and quantitative insight, but is often limited by analysis runtime and throughput. In this study, we developed and evaluated six methods for amino acid quantification based on two strong cation exchanger columns and a dilute and shoot approach in hyphenation with either a triple-quadrupole or a quadrupole time-of-flight mass spectrometer. Isotope dilution mass spectrometry with 13C15N labeled amino acids was used to correct for matrix effects. The versatility of the methods for metabolite profiling studies of microbial cultivation supernatants is confirmed by a detailed method validation study. The methods using chromatography columns showed a linear range of approx. 4 orders of magnitude, sufficient response factors, and low quantification limits (7–443 nM) for single analytes. Overall, relative standard deviation was comparable for all analytes, with < 8% and < 11% for unbuffered and buffered media, respectively. The dilute and shoot methods with an analysis time of 1 min provided similar performance but showed a factor of up to 35 times higher throughput. The performance and applicability of the dilute and shoot method are demonstrated using a library of Corynebacterium glutamicum strains producing l-histidine, obtained from random mutagenesis, which were cultivated in a microscale cultivation platform.
Graphical abstract
Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable‑density and shear flows
Authors: Fratantonio Dominique , Lai Chris C. K. , Charonko John , Prestridge Kathy 
Published: March 2021

Abstract
This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor’s hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian–Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor’s hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier–Stokes equations compared to the mean flow convective method.

Graphic abstract
Two-phase survey on the frequency of use and safety of MRI for hearing implant recipients
Authors: van de Heyning Paul , Mertens Griet , Topsakal Vedat , de Brito Ruben , Wimmer Wilhelm , Caversaccio Marco D. , Dazert Stefan , Volkenstein Stefan , Zernotti Mario , Parnes Lorne S. , Staecker Hinrich , Bruce Iain A. , Rajan Gunesh , Atlas Marcus , Friedland Peter , Skarzynski Piotr H. , Sugarova Serafima , Kuzovkov Vladislav , Hagr Abdulrahman , Mlynski Robert , Schmutzhard Joachim , Usami Shin-Ichi , Lassaletta Luis , Gavilán Javier , Godey Benoit , Raine Christopher H. , Hagen Rudolf , Sprinzl Georg M. , Brown Kevin , Baumgartner Wolf-Dieter , Karltorp Eva 
Published: March 2021

Abstract
Purpose
Magnetic resonance imaging (MRI) is often used to visualize and diagnose soft tissues. Hearing implant (HI) recipients are likely to require at least one MRI scan during their lifetime. However, the MRI scanner can interact with the implant magnet, resulting in complications for the HI recipient. This survey, which was conducted in two phases, aimed to evaluate the safety and performance of MRI scans for individuals with a HI manufactured by MED-EL (MED-EL GmbH, Innsbruck, Austria).

Methods
A survey was developed and distributed in two phases to HEARRING clinics to obtain information about the use of MRI for recipients of MED-EL devices. Phase 1 focused on how often MRI is used in diagnostic imaging of the head region of the cochlear implant (CI) recipients. Phase 2 collected safety information about MRI scans performed on HI recipients.

Results
106 of the 126 MRI scans reported in this survey were performed at a field strength of 1.5 T, on HI recipients who wore the SYNCHRONY CI or SYNCHRONY ABI. The head and spine were the most frequently imaged regions. 123 of the 126 scans were performed without any complications; two HI recipients experienced discomfort/pain. One recipient required reimplantation after an MRI was performed using a scanner that had not been approved for that implant. There was only one case that required surgical removal of the implant to reduce the imaging artefact.

Conclusion
Individuals with either a SYNCHRONY CI or SYNCHRONY ABI from MED-EL can safely undergo a 1.5 T MRI when it is performed according to the manufacturer’s safety policies and procedures.
White Paper by the European Society for Swallowing Disorders: Screening and Non-instrumental Assessment for Dysphagia in Adults
Authors: Speyer Renée , Cordier Reinie , Farneti Daniele , Nascimento Weslania , Pilz Walmari , Verin Eric , Walshe Margaret , Woisard Virginie 
Published: March 2021

AbstractThis White Paper by the European Society for Swallowing Disorders (ESSD) reports on the current state of screening and non-instrumental assessment for dysphagia in adults. An overview is provided on the measures that are available, and how to select screening tools and assessments. Emphasis is placed on different types of screening, patient-reported measures, assessment of anatomy and physiology of the swallowing act, and clinical swallowing evaluation. Many screening and non-instrumental assessments are available for evaluating dysphagia in adults; however, their use may not be warranted due to poor diagnostic performance or lacking robust psychometric properties. This white paper provides recommendations on how to select best evidence-based screening tools and non-instrumental assessments for use in clinical practice targeting different constructs, target populations and respondents, based on criteria for diagnostic performance, psychometric properties (reliability, validity, and responsiveness), and feasibility. In addition, gaps in research that need to be addressed in future studies are discussed. The following recommendations are made: (1) discontinue the use of non-validated dysphagia screening tools and assessments; (2) implement screening using tools that have optimal diagnostic performance in selected populations that are at risk of dysphagia, such as stroke patients, frail older persons, patients with progressive neurological diseases, persons with cerebral palsy, and patients with head and neck cancer; (3) implement measures that demonstrate robust psychometric properties; and (4) provide quality training in dysphagia screening and assessment to all clinicians involved in the care and management of persons with dysphagia.
Alexithymia and Autistic Traits as Contributing Factors to Empathy Difficulties in Preadolescent Children
Authors: Speyer Lydia Gabriela , Brown Ruth Harriet , Camus Lorna , Murray Aja Louise , Auyeung Bonnie 
Published: March 2021

AbstractRecent evidence suggests that, contrary to traditional views, empathy difficulties may not be a core feature of autism; but are rather due to co-occurring alexithymia. Empathy, alexithymia and autistic traits have yet to be examined concurrently in children. Therefore, we examined the co-occurrence of empathy difficulties and alexithymia in 59 typically developing and 5 autistic children. Multiple measures (self-report, parent-report and a behavioural task) were used to evaluate empathy and to assess differences in self- and parent-reports using multiple regressions. Alexithymia was found to predict empathy significantly better than autistic traits, providing support for the alexithymia hypothesis. From a therapeutic perspective, results suggest autistic children who screen positive for elevated alexithymic traits may benefit from additional support targeting emotion identification.
Assessing local impacts of water use on human health: evaluation of water footprint models in the Province Punjab, Pakistan
Authors: Mikosch Natalia , Berger Markus , Huber Elena , Finkbeiner Matthias 
Published: March 2021

Abstract
Purpose
The water footprint (WF) method is widely applied to quantify water use along the life cycle of products and organizations and to evaluate the resulting impacts on human health. This study analyzes the cause-effect chains for the human health damage related to the water use on a local scale in the Province Punjab of Pakistan, evaluates their consistency with existing WF models, and provides recommendations for future model development.

Method
Locally occurring cause-effect chains are analyzed based on site observations in Punjab and a literature review. Then, existing WF models are compared to the findings in the study area including their comprehensiveness (covered cause-effect chains), relevance (contribution of the modeled cause-effect chain to the total health damage), and representativeness (correspondence with the local cause-effect chain). Finally, recommendations for the development of new characterization models describing the local cause-effect chains are provided.

Results and discussion
The cause-effect chains for the agricultural water deprivation include malnutrition due to reduced food availability and income loss as well as diseases resulting from the use of wastewater for irrigation, out of which only the first one is addressed by existing WF models. The cause-effect chain for the infectious diseases due to domestic water deprivation is associated primarily with the absence of water supply systems, while the linkage to the water consumption of a product system was not identified. The cause-effect chains related to the water pollution include the exposure via agricultural products, fish, and drinking water, all of which are reflected in existing impact assessment models. Including the groundwater compartment may increase the relevance of the model for the study area.

Conclusions
Most cause-effect chains identified on the local scale are consistent with existing WF models. Modeling currently missing cause-effect chains for the impacts related to the income loss and wastewater usage for irrigation can enhance the assessment of the human health damage in water footprinting.
A scalable and spatiotemporally resolved agricultural life cycle assessment of California almonds
Authors: Marvinney Elias , Kendall Alissa 
Published: March 2021

AbstractPurposeCalifornia’s Central Valley produces more than 75% of global commercial almond supply, making the life cycle performance of almond production in California of global interest. This article describes the life cycle assessment of California almond production using a Scalable, Process-based, Agronomically Responsive Cropping System Life Cycle Assessment (SPARCS-LCA) model that includes crop responses to orchard management and modeling of California’s water supply and biomass energy infrastructure.MethodsA spatially and temporally resolved LCA model was developed to reflect the regional climate, resource, and agronomic conditions across California’s Central Valley by hydrologic subregion (San Joaquin Valley, Sacramento Valley, and Tulare Lake regions). The model couples a LCA framework with region-specific data, including water supply infrastructure and economics, crop productivity response models, and dynamic co-product markets, to characterize the environmental performance of California almonds. Previous LCAs of California almond found that irrigation and management of co-products were most influential in determining life cycle CO2eq emissions and energy intensity of California almond production, and both have experienced extensive changes since previous studies due to drought and changing regulatory conditions, making them a focus of sensitivity and scenario analysis.Results and discussionResults using economic allocation show that 1 kg of hulled, brown-skin almond kernel at post-harvest facility gate causes 1.92 kg CO2eq (GWP100), 50.9 MJ energy use, and 4820 L freshwater use, with regional ranges of 2.0–2.69 kg CO2eq, 42.7–59.4 MJ, and 4540–5150 L, respectively. With a substitution approach for co-product allocation, 1 kg almond kernel results in 1.23 kg CO2eq, 18.05 MJ energy use, and 4804 L freshwater use, with regional ranges of 0.51–1.95 kg CO2eq, 3.68–36.5 MJ, and 4521–5140 L, respectively. Almond freshwater use is comparable with other nut crops in California and globally. Results showed significant variability across subregions. While the San Joaquin Valley performed best in most impact categories, the Tulare Lake region produced the lowest eutrophication impacts.ConclusionWhile CO2eq and energy intensity of almond production increased over previous estimates, so too did credits to the system for displacement of dairy feed. These changes result from a more comprehensive model scope and improved assumptions, as well as drought-related increases in groundwater depth and associated energy demand, and decreased utilization of biomass residues for energy recovery due to closure of bioenergy plants in California. The variation among different impact categories between subregions and over time highlight the need for spatially and temporally resolved agricultural LCA.