bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unravelling Channel Structure–Diffusivity Relationships in Zeolite ZSM‐5 at the Single‐Molecule Level
Authors: Fu Donglong , Maris J. J. Erik , Stanciakova Katarina , Nikolopoulos Nikolaos , van der Heijden Onno , Mandemaker Laurens D. B. , Siemons Marijn E. , Salas Pastene Desiree , Kapitein Lukas C. , Rabouw Freddy T. , Meirer Florian , Weckhuysen Bert M. 
Published: November 2021

AbstractThe development of improved zeolite materials for applications in separation and catalysis requires understanding of mass transport. Herein, diffusion of single molecules is tracked in the straight and sinusoidal channels of the industrially relevant ZSM‐5 zeolites using a combination of single‐molecule localization microscopy and uniformly oriented zeolite thin films. Distinct motion behaviors are observed in zeolite channels with the same geometry, suggesting heterogeneous guest–host interactions. Quantification of the diffusion heterogeneities in the sinusoidal and straight channels suggests that the geometry of zeolite channels dictates the mobility and motion behavior of the guest molecules, resulting in diffusion anisotropy. The study of hierarchical zeolites shows that the addition of secondary pore networks primarily enhances the diffusivity of sinusoidal zeolite channels, and thus alleviating the diffusion limitations of microporous zeolites.
Macro‐porous permeability aspects of MgSO4 salt hydrate foams for energy storage applications
Authors: Calabrese Luigi , Hernández Leonor , Mondragón Rosa , Cabeza Luisa F. 
Published: November 2021

AbstractIn the present work a macroporous silicone foam, able to contain the magnesium sulfate, was chosen as matrix for the reversible hydration/dehydration process of the salt hydrate. The aim of the article was addressed towards the assessment of the relationship among microstructure, permeability and mass diffusion of the composite foam. This aspect represents an essential step for the future industrial development of this composite material. The results show that the filler content influences the foam morphology where a transition from closed to mixed and then closed cell again was observed with increasing filler content. Consequently, depending on the distribution and interconnection of the structural channels, a different effectiveness in guaranteeing mass diffusion phenomena was identified. In particular, permeability tests show that foams with 50 wt% of salt hydrates have a highly interconnected microstructure allowing a permeability over three times higher than a closed cell structure making it suitable for thermochemical energy storage applications.
‘What am I Bringing into the Room?’ Perception and Management of Interviewer Bias in Child Sexual Abuse Interviews: An Interpretative Phenomenological Analysis
Authors: Lacey Eimear , Nunkoosing Karl 
Published: November 2021

Several high‐profile cases in the USA in the 1980s and 1990s revealed the impact that interviewer bias can have on children's accounts of child sexual abuse (CSA). Since then, researchers and practitioners have explored techniques to address this, leading to refined interviewing techniques, greater understanding of suggestibility and memory, and the development of best practice guidelines. However, a gap remains in understanding how professionals themselves manage their interviewer bias. This interpretative phenomenological analysis (IPA) examines professionals' perceptions and management of interviewer bias when assessing CSA allegations. Eight professionals across social work, clinical/counselling psychology and psychiatry employed in specialist services across Ireland participated in semi‐structured interviews to explore this question. Ethical approval was obtained from the relevant university and the first author's organisational panel. IPA identified three superordinate themes: Quality Assurance; Collaborative Approach; and Professional Identity ‐ Personal Self. The professionals considered interviewer bias to have potentially detrimental impacts upon both the interview process and possible outcomes. They move from a definition of bias related specifically to a priori beliefs to a definition in which bias is a more dynamic process. A multidisciplinary approach alongside the constant reviewing of practice is considered essential to ensuring a high standard of practice, accountability and integrity of assessments.‘This interpretative phenomenological analysis (IPA) examines professionals' perceptions and management of interviewer bias when assessing CSA allegations’Key Practitioner Messages

Interviewer bias is dynamic and can develop at any stage of an intervention thus potentially affecting outcomes.
Investigative interview protocols/guidance provide security for practitioners who make significant decisions regarding alleged CSA.
Professionals view multidisciplinary teamwork and co‐working as essential to maintaining the integrity of their assessments.
Practitioners are encouraged to reflect on their potential biases in a conscious manner, by thinking explicitly about information, maintaining a neutral stance, questioning and testing information, and seeking alternative explanations.
Precipitation variability can bias estimates of ecological controls on ecosystem productivity response to precipitation change
Authors: Parolari Anthony J. , Paschalis Athanasios 
Published: November 2021

AbstractAnnual vegetation aboveground net primary productivity (ANPP) exhibits a non‐linear dependence on annual precipitation. A common pattern of non‐linearity, called asymmetry, arises when productivity responses in wet years are larger than declines in dry years. To date, ANPP asymmetry has been attributed primarily to vegetation water stress, an internal ecosystem response to precipitation and soil water availability. However, when quantified via the asymmetry index (AI) estimated from productivity measurements, the asymmetry can be a sampling artefact that arises from a positively skewed annual precipitation distribution. In this paper, we aimed to separate the sampling effect (from external precipitation variability) from the non‐linear response of the system (the internal ecosystem dynamics). We constructed a probabilistic model that integrates the precipitation distribution with the precipitation‐productivity response curve (PPT‐ANPP curve), derived using empirical formulae and a process‐based soil water balance model. The model was used to derive the probability density function of AI and to attribute its shape to the PPT distribution and the PPT‐ANPP response curve. The models were compared to data from 47 grasslands. Results demonstrated that positively skewed precipitation produces a positive AI as a statistical artefact. The non‐linear ecosystem PPT‐ANPP dependence can further enhance or dampen this statistical artefact. In all sites, the precipitation skew highly affected the probability of correctly identifying asymmetry using AI. Observed negative asymmetry arises from a larger soil water holding capacity and positive asymmetry from plant water stress. More robust statistical indicators of non‐linear ecological responses to climate variability are needed to improve ecosystem forecasts.
Effects of different batteries and dispatch strategies on performance of standalonePV/WT/DG/battery system: A case study
Authors: R. K. Dhavala , H. N. Suresh , S. Rajanna , M. Ramesh 
Published: November 2021

AbstractThe idea of integrated hybrid renewable energy systems (IHRES) is gaining attention for electrification of rural areas where on‐grid electricity supply is uneconomical. From this point of view, the technical and economic feasibility analysis is carried out for a standalone IHRES in a remote area of Malnad region in Karnataka, India. Solar and wind energy are the prominent renewable resources available in the selected area for study. In the present study, lithium‐ion, lead‐acid and zinc‐bromide batteries effect on “PV‐WT‐DG‐Battery” system is examined and compared. The control strategies used in the study are “load following (LF)” and “predictive dispatch (PD).” The simulation results reveal that the “cost of energy (COE)” and “net present cost (NPC)” are found to be low in zinc‐bromide batterybased system with “PD control strategy.” The NPC and COE are found to be $55 262 and $0.35 per kWh for optimal system. Zinc‐bromide batteries are best suited for remote electrification with less load demand. The sensitivity analysis shows that there is a minimal effect on the performance of the planned IHRES upon variation in the “inflation rate,” “discount rate,” and “diesel price.”
A Bayesian hierarchically structured prior for gene‐based association testing with multiple traits in genome‐wide association studies
Authors: Yang Yi , Basu Saonli , Zhang Lin 
Published: November 2021

AbstractAlthough genome‐wide association studies (GWAS) often collect data on multiple correlated traits for complex diseases, conventional gene‐based analysis is usually univariate, and therefore, treating traits as uncorrelated. Multivariate analysis of multiple correlated traits can potentially increase the power to detect genes that affect some or all of these traits. In this study, we propose the multivariate hierarchically structured variable selection (HSVS‐M) model, a flexible Bayesian model that tests the association of a gene with multiple correlated traits. With only summary statistics, HSVS‐M can account for the correlations among genetic variants and among traits simultaneously and can also estimate the various directions and magnitudes of associations between a gene and multiple traits. Simulation studies show that HSVS‐M substantially outperforms competing methods in various scenarios, particularly when variants in a gene are associated with a trait in similar directions and magnitudes. We applied HSVS‐M to the summary statistics of a meta‐analysis GWAS on four lipid traits from the Global Lipids Genetics Consortium and identified 15 genes that have also been confirmed as risk factors in previous studies.
Efficient prediction for high precision CO‐N2 potential energy surface by stacking ensemble DNN
Authors: Xu Shanshan , Li You , Wang Donghan , Fang Chao , Luo Chengwei , Deng Jiankun , Hu LiHong , Li Hui , Li Hongzhi 
Published: November 2021

AbstractHigh‐dimensional potential energy surface (PES) for van der Waals systems with spectroscopic accuracy, is of great importance for quantum dynamics and an extremely challenge job. CO‐N2 is a typical van der Waals system and its high‐precision PES may help elucidate weak interaction mechanisms. Taking CO‐N2 potential energies calculated by CCSD(T)‐F12b/aug‐cc‐pVQZ as the benchmark, we establish an accurate, robust, and efficient machine learning model by using only four molecular structure descriptors based on 7966 benchmark potential energies. The highest accuracy is obtained by a stacking ensemble DNN (SeDNN). Its evaluation parameters MAE, RMSE, and R2 reach 0.096, 0.163, 0.9999 cm−1, respectively, and the spectroscopic accuracy for vibration spectrum is achieved with predicted PES, which shows SeDNN superior goodness‐of‐fit and prediction performance. An elaborated PES with the reported global minimum has been predicted with the model, which perfectly reproduces CCSD(T) potential energies and the analytical MLR PES [PCCP, 2018, 20, 2036]. The critical points (global minimum, TSI, TSII, and their barriers), potential curve, and entire PES profile are remarkably consistent with CCSD(T) calculations. To further improve the usability of constructing PESs in practice, the size of the training set (energy points) for the model is reduced to 50%, 30%, and 20% of the database, respectively. The results show that even training with the smallest training set (1593 points), the PES only differs 2.555 cm−1 with the analytic MLR PES. Therefore, the proposed SeDNN is promisingly an alternative efficient tool to construct subtle PES for van der Waals systems.
Role of autophagy in intervertebral disc degeneration
Authors: Kritschil Rebecca , Scott Melanie , Sowa Gwendolyn , Vo Nam 
Published: November 2021

AbstractIntervertebral disc degeneration (IDD) is a leading contributor to low back pain. The intervertebral disc (IVD) is composed of three tissue types: the central gelatinous nucleus pulposus (NP) tissue, the surrounding annulus fibrosus (AF) tissue, and the inferior and superior cartilage endplates. The IVD microenvironment is hypoxic, acidic, hyperosmotic, and low in nutrients because it is mostly avascular. The cellular processes that underlie IDD initiation and progression are still poorly understood. Specifically, a lack of understanding regarding NP cell metabolism and physiology hinders the development of effective therapeutics to treat IDD patients. Autophagy is a vital intracellular degradation process that removes damaged organelles, misfolded proteins, and intracellular pathogens and recycles the degraded components for cellular energy and function. NP cells have adapted to survive within their harsh tissue microenvironment using processes that are largely unknown, and we postulate autophagy is one of these undiscovered mechanisms. In this review, we describe unique features of the IVD tissue, review how physiological stressors impact autophagy in NP cells in vitro, survey the current understanding of autophagy regulation in the IVD, and assess the relationship between autophagy and IDD. Published studies confirm autophagy markers are present in IVD tissue, and IVD cells can regulate autophagy in response to cellular stressors in vitro. However, data are still lacking to determine the exact mechanisms regulating autophagy in IVD cells. More in‐depth research is needed to establish whether autophagy is necessary to maintain IVD cell health and validate autophagy as a relevant therapeutic target for treating IDD.
Evaluation of snow depth and snow cover represented by multiple datasets over the Tianshan Mountains: Remote sensing, reanalysis, and simulation
Authors: Li Qian , Yang Tao , Li Lanhai 
Published: November 2021

AbstractMountain snowpacks play important roles in water resource and ecological system. However, existing snow depth products show great uncertainties across the Tianshan Mountains, Central Asia. This study evaluated and compared four snow depth datasets over the Tianshan Mountains, including snow depth datasets from ERA5, ERA5‐Land, passive microwave, as well as a dynamically downscaled simulation by Weather Research and Forecasting (WRF) model. The snow depth was evaluated against in situ observations while the snow cover extent was evaluated by interactive multisensor snow and ice mapping system (IMS) snow cover. Furthermore, the snow‐related metrics, such as annual mean snow depth and snow cover days, were compared among the four datasets. The results showed that the spatial patterns of snow‐related metrics were relatively consistent among datasets, although discrepancies existed in magnitude. Additionally, the temporal variations in snow‐related metrics depended on the dataset employed. The simulated snow depth from WRF got the lowest bias in daily snow depth value against the in situ observations (mean bias = 0.12 cm, root mean square error = 2.08 cm), additionally, it had the best performance in classifying correct snow grids compared with IMS (probability of detection = 0.766). It also outperformed in annual mean snow depth and snow cover days by 47.2 and 13.3% compared with ERA5‐Land snow depth. This study highlights the confidence in characterizing both the spatial pattern and temporal variations of snow depth products based on WRF model simulation.
Perinatal socio‐behavioral and obstetric predictors of metabolically healthy and unhealthy obesity in adult offspring
Authors: Talisman Shahar , Friedlander Yechiel , Hochner Hagit 
Published: November 2021

AbstractObjectiveThe purpose of this study was to investigate whether obstetric and perinatal socio‐behavioral characteristics at the time of pregnancy predict obesity phenotypes of adult offspring.MethodsThe Jerusalem Perinatal Study was conducted among 17,003 deliveries during 1974 to 1976. Follow‐up studies were conducted during 2007 to 2009 and 2017 to 2019 among 1,440 offspring undergoing examinations. Offspring were classified into four phenotypes according to obesity and metabolic status: metabolically healthy normal weight (MHNW, reference group), unhealthy normal weight, healthy obesity (MHO), and unhealthy obesity (MUO). Regression models were carried out to identify perinatal predictors for risk phenotypes at age 30 to 35 years, emphasizing the differentiation between socio‐behavioral and obstetric features.ResultsA total of 15.7% of participants were classified as MUO, and 5.4% were classified as MHO. Low socioeconomic status was associated with both obesity phenotypes (e.g., odds ratio [OR]MHO/MHNW = 2.98, p < 0.001). High socioeconomic status was associated with MUO (ORMUO/MHNW = 1.93, p = 0.002). Maternal low education was also associated with both obesity phenotypes (ORMUO/MHNW = 2.46, p < 0.001, ORMHO/MHNW = 2.45, p = 0.005). Participants with MUO were more likely to have a smoking father (ORMUO/MHNW = 1.48, p = 0.021).ConclusionsPerinatal socio‐behavioral characteristics are associated with adult obesity phenotypes. The findings point to possible mechanisms underlying the development of obesity in young adults and, thus, contribute toward identifying high‐risk groups that would mostly benefit from obesity risk‐reduction interventions.
Influence of CeO2as dispersoid in blend poly(styrene‐co‐methylmethacrylate) as electrolyte for lithium‐ion battery
Authors: Ramachandran Murugesan , Subadevi Rengapillai , Rajkumar Palanisamy , Muthupradeepa Rajendran , Sivakumar Marimuthu 
Published: November 2021

AbstractPoly(styrene‐co‐methylmethacrylate) P(S‐MMA) composite polymer electrolytes are having massive consideration for solid‐state electrochemical devices. There are numerous tactics implement to improve the ambient temperature ionic conductivity such as the addition of plasticizers, the inclusion of nanosize ceramic fillers and blending with the host polymer, which were carried out in this work. The effect of CeO2 on the P(S‐MMA)‐poly(vinylidene fluoride) (25:75 of 27 wt%)‐LiClO4 (8 wt%)‐ethylene carbonate:propylene carbonate (1:1 of 65 wt%) system prepared via a conventional solution casting technique. The as‐prepared polymer membranes were characterized using XRD, Fourier transform infrared spectroscopy, thermogravimetry and differential thermal analysis, SEM and AC impedance analyses. The composite polymer blend gel electrolyte system exhibits high ionic conductivity (2.51 × 10−2 S cm−1) with 6 wt% CeO2 nanofiller at ambient temperature. The conductivity enhancement is due to the presence of a rise in the amorphous content; it is in well concurrence with the XRD results. The optimum electrolyte was used to design the LiFePO4/composite gel polymer electrolyte/Li cell couple in a 2032 type coin cell. It possesses a discharge capacity of 151 mA h g−1 at 0.1 C. © 2021 Society of Industrial Chemistry.
Terahertz Quantum Cascade Lasers as Enabling Quantum Technology
Authors: Vitiello Miriam Serena , De Natale Paolo 
Published: November 2021

AbstractQuantum cascade lasers (QCLs) represent the most fascinating achievement of quantum engineering, showing how artificial materials can be generated through quantum design, with tailor‐made properties. Their inherent quantum nature deeply affects their core physical parameters. QCLs indeed display intrinsic linewidths approaching the quantum limit, and show spontaneous phase‐locking of their emitted modes via intracavity four‐wave‐mixing, meaning that they can naturally operate as miniaturized metrological frequency rulers, also in frontier frequency domains, as the far‐infrared, yet unexplored in quantum science. Here, the authors discuss the fundamental quantum properties of QCLs operating at terahertz frequencies and their key technological performances, highlighting future perspectives of this frontier research field in disruptive areas of quantum technologies such as quantum sensing, quantum metrology, quantum imaging, and photonic‐based quantum computation.
Highly Sensitive Flexible Tactile Sensors in Wide Sensing Range Enabled by Hierarchical Topography of Biaxially Strained and Capillary‐Densified Carbon Nanotube Bundles
Authors: Sim Sangjun , Jo Eunhwan , Kang Yunsung , Chung Euichul , Kim Jongbaeg 
Published: November 2021

AbstractFlexible tactile sensors with high sensitivity have received considerable attention for their use in wearable electronics, human–machine interfaces, and health‐monitoring devices. Although various micro/nanostructured materials are introduced for high‐performance tactile sensors, simultaneously obtaining high sensitivity and a wide sensing range remains challenging. Here, a resistive tactile sensor is presented based on the hierarchical topography of carbon nanotubes (CNTs) prepared by a low‐cost and straightforward manufacturing process. The 3D hierarchical structure of the CNTs over large areas is formed by transferring vertically aligned CNT bundles to a prestrained elastomer substrate and subsequently densifying them through capillary forming, providing a monotonic increase in the contact area as applied pressure. The deformable and hierarchical structure of CNTs allows the sensor to exhibit a wide sensing range (0–100 kPa), high sensitivity (141.72 kPa−1), and low detection limit (10 Pa). Additionally, the capillary‐formed CNT structure results in increased durability of the sensor over repeated pressures. Based on these advantages, meaningful applications of tactile sensors, such as object recognition gloves and multidirectional force perceptions, are successfully realized. Given the scalable fabrication method, 3D hierarchically structured CNTs provide an essential step toward next‐generation wearable devices.
Subtle characteristic classes for Spin-torsors
Authors: Tanania Fabio 
Published: November 2021

AbstractExtending (Smirnov and Vishik, Subtle Characteristic Classes,arXiv:1401.6661), we obtain a complete description of the motivic cohomology with$${{\,\mathrm{\mathbb {Z}}\,}}/2$$Z/2-coefficients of the Nisnevich classifying space of the spin group$$Spin_n$$Spinnassociated to the standard split quadratic form. This provides us with very simple relations among subtle Stiefel–Whitney classes in the motivic cohomology of Čech simplicial schemes associated to quadratic forms from$$I^3$$I3, which are closely related to$$Spin_n$$Spinn-torsors over the point. These relations come from the action of the motivic Steenrod algebra on the second subtle Stiefel–Whitney class. Moreover, exploiting the relation between$$Spin_7$$Spin7and$$G_2$$G2, we describe completely the motivic cohomology ring of the Nisnevich classifying space of$$G_2$$G2. The result in topology was obtained by Quillen (Math Ann 194:197–212, 1971).