bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aqueous Aluminum‐Carbon Rechargeable Batteries
Authors: Smajic Jasmin , Hasanov Bashir E. , Alazmi Amira , Emwas Abdul‐Hamid , Wehbe Nimer , Genovese Alessandro , El Labban Abdulrahman , Costa Pedro M. F. J. 
Published: December 2021

AbstractCarbon cathodes have shown excellent electrochemical behavior in aluminum batteries based on non‐aqueous electrolytes. By contrast, their use in Al systems operating in a salt‐water medium is plagued by poor and unstable performance. Herein, it is sustained that a successful C cathode for rechargeable aqueous Al batteries requires surface customization to enable hydrophilicity and grafting of charged Al molecules. Employing a freeze‐dried reduced graphene oxide (rGO) as the active electrode material, an aqueous Al‐C battery is assembled with a high energy density (136 Wh kg−1 per cathode mass) and one of the best capacity retentions reported (≈60% across a range of current densities and constant Coulombic efficiencies close to unit). Furthermore, the rGO cathode more than doubles the benchmark for life cycles (to ≈200 cycles) and can be charged rapidly (<5 min). To explain this response, a charge storage mechanism is proposed wherein the [Al(H2O)6]3+ ions do not get desolvated when inserted into the cathode. The guest Al ions (surface adsorbed or intercalated) act as proton donors and may get anchored on the oxygen moieties of the rGO, further promoting the formation of an electrochemical double layer. A mixed charge‐storage regime follows that stabilizes the carbon cathode and enables an unprecedented response.
Small‐Sized Deformable Shear Sensor Array for Direct Monitoring of Quantitative Shear Distribution
Authors: Suh Wonjeong , Park Chaeyong , Oh Joosung , Moon Sungmin , Choi Seungmoon , Kim Youn Soo , Jeong Unyong 
Published: December 2021

AbstractAn array of shear sensors is essential in tactile sensation as well as the pressure sensors. Surprisingly, however, the shear sensor array is rarely investigated mainly due to the structural complexity to measure the horizontal forces from various directions and also due to the mechanical softness required for preventing the slip of an object. Here, an array of small shear sensors that can recognize both shear force and shear rotational angle is fabricated. All the device components are made of deformable materials to acquire the softness of the sensor. This work presents a novel design for the small‐sized shear sensor array and the required material conditions for the design. By using an ion gel as the capacitive sensing material, the shear sensor array shows high sensitivity and excellent reliability under repeated shear forces. This work demonstrates playing computer game with the shear sensor and sensing the frictional force distribution, which is possible through the recognition of multiple shear stimuli and spatial shear distribution (force, rotational angle) when static/dynamic shear forces are simultaneously applied from various directions.
Martini 3 Coarse‐Grained Force Field: Small Molecules
Authors: Alessandri Riccardo , Barnoud Jonathan , Gertsen Anders S. , Patmanidis Ilias , de Vries Alex H. , Souza Paulo C. T. , Marrink Siewert J. 
Published: December 2021

AbstractThe recent re‐parametrization of the Martini coarse‐grained force field, Martini 3, improved the accuracy of the model in predicting molecular packing and interactions in molecular dynamics simulations. Here, we describe how small molecules can be accurately parametrized within the Martini 3 framework and present a database of validated small molecule models. We pay particular attention to the description of aliphatic and aromatic ring‐like structures, which are ubiquitous in small molecules such as solvents and drugs or in building blocks constituting macromolecules such as proteins and synthetic polymers. In Martini 3, ring‐like structures are described by models that use higher resolution coarse‐grained particles (small and tiny particles). As such, the present database constitutes one of the cornerstones of the calibration of the new Martini 3 small and tiny particle sizes. The models show excellent partitioning behavior and solvent properties. Miscibility trends between different bulk phases are also captured, completing the set of thermodynamic properties considered during the parametrization. We also show how the new bead sizes allow for a good representation of molecular volume, which translates into better structural properties such as stacking distances. We further present design strategies to build Martini 3 models for small molecules of increased complexity.
Establishment of Human Pluripotent Stem Cell‐Derived Skin Organoids Enabled Pathophysiological Model of SARS‐CoV‐2 Infection
Authors: Ma Jie , liu Jia , Gao Dunqin , Li Xiao , Zhang Qiyu , Lv Luye , Wang Yujie , Li Jun , Zhu Yunping , Wu Zhihong , Hu Hengrui , Li Yufeng , Ma Longda , Liu Qian , Hu Zhihong , Zhang Shuyang , Zhou Yiwu , Wang Manli , Leng Ling 
Published: December 2021

AbstractCoronavirus disease 2019 (COVID‐19) patients with impact on skin and hair loss are reported. Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is detected in the skin of some patients; however, the detailed pathological features of skin tissues from patients infected with SARS‐CoV‐2 at a molecular level are limited. Especially, the ability of SARS‐CoV‐2 to infect skin cells and impact their function is not well understood. A proteome map of COVID‐19 skin is established here and the susceptibility of human‐induced pluripotent stem cell (hiPSC)‐derived skin organoids with hair follicles and nervous system is investigated, to SARS‐CoV‐2 infection. It is shown that KRT17+ hair follicles can be infected by SARS‐CoV‐2 and are associated with the impaired development of hair follicles and epidermis. Different types of nervous system cells are also found to be infected, which can lead to neuron death. Findings from the present work provide evidence for the association between COVID‐19 and hair loss. hiPSC‐derived skin organoids are also presented as an experimental model which can be used to investigate the susceptibility of skin cells to SARS‐CoV‐2 infection and can help identify various pathological mechanisms and drug screening strategies.
Organic Log‐Domain Integrator Synapse
Authors: Hosseini Mohammad Javad Mirshojaeian , Donati Elisa , Indiveri Giacomo , Nawrocki Robert A. 
Published: December 2021

AbstractSynapses play a critical role in memory, learning, and cognition. Their main functions include converting presynaptic voltage spikes to postsynaptic currents, as well as scaling the input signal. Several brain‐inspired architectures have been proposed to emulate the behavior of biological synapses. While these are useful to explore the properties of nervous systems, the challenge of making biocompatible and flexible circuits with biologically plausible time constants and tunable gain remains. Here, a physically flexible organic log‐domain integrator synaptic circuit is shown to address this challenge. In particular, the circuit is fabricated using organic‐based materials that are electrically active, offer flexibility and biocompatibility, as well as time constants (critical in learning neural codes and encoding spatiotemporal patterns) that are biologically plausible. Using a 10 nF synaptic capacitor, the time constant reached 126 and 221 ms before and during bending, respectively. The flexible synaptic circuit is characterized before and during bending, followed with studies on the effects of weighting voltage, synaptic capacitance, and disparity in presynaptic signals on the time constant.
Tuning the Structure, Magnetic, and High Frequency Properties of Sc‐Doped Sr0.5Ba0.5ScxFe12‐xO19/NiFe2O4 Hard/Soft Nanocomposites
Authors: Almessiere Munirah A. , Slimani Yassine , Algarou Norah A. , Vakhitov Maksim G. , Klygach Denis S. , Baykal Abdulhadi , Zubar Tatyana I. , Trukhanov Sergei V. , Trukhanov Alex V. , Attia Hussein , Sertkol Murat , Auwal İsmail A. 
Published: December 2021

AbstractThe Sr0.5Ba0.5ScxFe12–xO19(SrBaSc)/NiFe2O4(NiFe) hard–soft nanocomposites (NCs) are synthesized by in situ sol–gel route. Impact of Sc3+ doping on their structure, morphology, and magnetic properties are examined. X‐ray diﬀraction confirms the coexistence of SrBaSc and NiFe phases without any impurity. Morphology of NCs reveals a cluster of hexagonal plate decorated by spherical grains. Magnetic characteristics of the NCs are examined by using a vibration sample magnetometer at room temperature and 10 K. The x = 0.000 sample shows some kinks in their M–H loops and the occurrence of two peaks in dM/dH(H). All the NCs with Sc3+ exhibit smooth shapes of M–H curves with single peak, revealing the complete and perfect exchange coupling behavior. The diverse magnetic parameters at both temperatures are determined. The values of saturation and remanent magnetizations are decreasing with the Sc content increase. The intensive electromagnetic absorption is observed in all the samples. Reﬂection loss (RL) of more than ‐18 dB is observed above 3 GHz. Strong coupling between Sc concentration and amplitude–frequency characteristics of the RL can be used for developing of the functional media for high‐frequency devices and will open broad perspectives for practical application in radar‐absorbing technology and electromagnetic compatibility.
In‐Situ Loading Bridgman Growth of Mg3Bi1.49Sb0.5Te0.01 Bulk Crystals for Thermoelectric Applications
Authors: Wang Qi‐Qi , Li Fan , Xia Sheng‐Qing , Liu Jian , Liu Xiao‐Cun , Chen Ling , Zhang Cheng‐Qian 
Published: December 2021

AbstractThe single crystal growth of Mg3Bi2‐based thermoelectric materials is of great significance for their applications near room temperature. So far, it is still a big challenge to grow such bulk single crystals and attempts are primarily focused on the metal flux methods. For the first time, bulk single crystals of n‐type Mg3Bi1.49Sb0.5Te0.01 are directly grown by applying an In‐situ Loading Bridgman method. The as‐grown single crystal features an excellent carrier mobility of 220 cm2 V−1 s−1, which is among the best compared to other Mg3Bi2‐based bulk materials. Besides, this method is successfully developed to fast grow uniform polycrystalline materials with high thermoelectric and mechanic performance. As demonstrated by the single‐leg device, a large temperature difference of 10.5 K is achieved at the supplied electric current of 0.6 A, much superior to other room temperature state‐of‐the‐art thermoelectric materials. With the single crystalline and polycrystalline materials prepared reliably and conveniently, in‐depth investigations on the Mg3Bi2 thermoelectric system can be greatly benefited, which should as well significantly facilitate their practical applications at room temperature.
Bio‐Inspired Computational Design of Vascularized Electrodes for High‐Performance Fast‐Charging Batteries Optimized by Deep Learning
Authors: Sui Chenxi , Li Yao‐Yu , Li Xiuqiang , Higueros Genesis , Wang Keyu , Xie Wanrong , Hsu Po‐Chun 
Published: December 2021

AbstractSlow ionic transport and high voltage drop (IR drop) of homogeneous porous electrodes are the critical causes of severe performance degradation of lithium‐ion batteries at high charging rates. Herein, it is numerically demonstrated that a bio‐inspired vascularized porous electrode can simultaneously solve these two problems by introducing low tortuous channels and graded porosity, which can be verified by porous electrode theory. To optimize the vasculature structural parameters, artificial neural networks are employed to accelerate the computation of possible structures with high accuracy. Furthermore, an inverse‐design searching library is compiled to find the optimal vascular structures under different industrial fabrication and design criteria. The prototype delivers a customizable package containing optimal geometric parameters and their uncertainty and sensitivity analysis. Finally, the full‐vascularized cell shows a 66% improvement in charging capacity compared to the traditional homogeneous cell under 3.2 C current density in a numerical simulation. This computational research provides an innovative methodology to solve the fast‐charging problem in batteries and broaden the applicability of deep learning algorithms to different scientific or engineering areas.
Dementia care in China: Challenges and recommendations
Authors: Zhao Wenhong 
Published: December 2021

AbstractBackgroundIn China, approximately 84.9% of people with dementia are cared for by family caregivers. Health professionals working in the departments where people with dementia are cared for in public tertiary hospitals are the primary sources to offer a formal diagnosis and treatment to people with dementia in China. The aim of this study was to explore family caregivers’ expectations on dementia care, and the dementia knowledge and attitudes of health professionals in China.MethodMixed method was used to collect data from April to December 2019. Surveys were used to evaluate health professionals’ (n=603) dementia knowledge and attitudes in eleven public tertiary hospitals in Hebei Province in China. Semi‐structured interviews were conducted in three public tertiary hospitals where family caregivers of people with dementia (n=21) were recruited.ResultThe health professionals demonstrated limited knowledge of dementia and a low level of positive attitude. They expressed that it was challenging to communicate with people with dementia and to cope with their symptoms. Family caregivers reported that they received limited support from the community, hospital, and society and they held little hope of receiving such support. Most of the caregivers expected more financial support from the government, and more training in dementia care from health professionals. They also expressed their desire to have a professional caregiver in the nursing homes to provide optimal dementia care for their relatives.ConclusionHealth services in China are inadequately prepared to deal with the challenges of dementia care. More emphasis is needed on specialized education and training for caregivers and health professionals to improve their knowledge and to modify their attitudes. Family caregivers expected more support from the health system to enable improved care for people with dementia. An integrated health system for dementia care is needed in China.
Computational identification of inhibitors of MSUT‐2 using quantum machine learning and molecular docking for the treatment of Alzheimer's disease
Authors: Ganesh Rithvik 
Published: December 2021

AbstractBackgroundAlzheimer's Disease is in a class of related neurodegenerative diseases known as tauopathies, where tau hyperphosphorylation leads to progressive neurological decline. MSUT‐2 has emerged as a viable target for the treatment of tauopathies like Alzheimer's, as the protein's interactions with the tau protein could be central to the accumulation and aggregation of tau. Quantum Computing and Machine Learning are two developing fields that have the capability to completely revolutionize the field of pharmacology. Developed architectures like Quantum Support Vector Machines can be scaled up readily as technology improves, further enhancing this breakthrough field’s implications on pharmacology.MethodIn the first phase of research, OpenEye's FILTER software was employed, which eliminated a set of starting compounds from ChemBridge's EXPRESS‐PICK Screening Library (over 500,000 compounds) that were predicted to be highly toxic and have low bioavailability. Next, a simple pharmacophore screen was performed using a set of known partial actives and inactives on OpenEye's ROCS tool. A modified Quantum Support Vector Machine algorithm was then run through IBM Qiskit. The model was trained using dozens of known chemical features of FDA‐approved chemical actives and inactives. Compounds were featurized using data from SwissADME. Following preprocessing and training, the model was executed to predict known actives from the remaining set of test compounds. Finally, compounds were subject to a precise molecular docking trial with MSUT‐2 (using OpenEye’s FRED tool and AUTODOCK Vina), where binding interaction strength was directly evaluated.ResultThis computational screening methodology resulted in numerous predicted inhibitors of MSUT‐2. To validate the methodology of this screening workflow, numerous known FDA‐approved drugs and actives for other diseases were successfully identified using the exact screening methodology utilized in this experiment through retrospective analysis.ConclusionIn conclusion, a promising computational screening methodology partially validated with translational data using advancements in Quantum Machine Learning has been identified. This exact workflow is novel and promising, and can easily be scaled up for comprehensive screening for a myriad of targets. 5 inhibitors for a promising yet underexplored target for Alzheimer’s disease, MSUT‐2, have also been identified in this study.
HOMESIDE—A home‐based family caregiver‐delivered music and reading intervention for people living with dementia: A randomised controlled trial
Authors: Baker Felicity , Odell‐Miller Helen , Wosch Thomas , Stensaeth Karette , Bukowska Anna , Clark Imogen 
Published: December 2021

AbstractBackgroundPharmacological interventions to address behavioural and psychological symptoms of dementia (BPSD) can have undesirable side effects, therefore non‐pharmacological approaches to managing symptoms may be preferable. Past studies show that music therapy can reduce BPSD, and other studies have explored how formal caregivers use music in their caring roles. However, no studies have examined the effects on BPSD of music interventions delivered by informal caregivers (CGs) in the home setting. Our project addresses the need for improved informal care by training cohabiting family CGs to implement music interventions that target BPSD, and the quality of life (QoL) and well‐being of people with dementia and CGs.MethodsAn international three‐arm parallel‐group randomised controlled trial has so far randomised 130 of the target 495 dyads from Australia, Germany, UK, Poland and Norway. Dyads are randomised equally to standard care (SC), a home‐based music programme plus SC, or a home‐based reading programme plus SC for 12 weeks. The primary outcome is BPSD of people with dementia (measured using the Neuropsychiatric Inventory‐Questionnaire). Secondary outcomes examine relationship quality between CG and people with dementia, depression, resilience, competence, QoL for CG and QoL for people with dementia. Outcomes are collected at baseline, at the end of the 12‐week intervention and at 6 months post randomisation. Resource Utilisation in Dementia captures economic data across the life of the intervention and at 6‐month follow‐up. Our presentation will briefly outline the study protocol and describe the caregiver training protocol and interventions in detail with video footage illustrating how the intervention looks in practice.
Discovery of screened potential inhibitors for Alzheimer disease responsible enzymes: Insights from atomistic simulations
Authors: Kandasamy Saravanan 
Published: December 2021

AbstractBackgroundOne of the cruelest neurogenerative disorder is Alzheimer disease (AD) which majorly affects old aged humans. It initially affects a person’s ability to carry out daily functions and leads to death. Basically, many diverse factors are leading to neuronal cell death such as low level of acetylcholine, deposition of amyloid beta, aggregation of tau proteins, oxidative stress, neuro‐inflammation, excitotoxicity, genetic and heredity factors. Some of the recent reports also outline about AD and it was characterized by different hypothesis and are named as cholinergic hypothesis, amyloid hypothesis, tau hypothesis and others (oxidative stress and genetic). Therefore, the present study focused to identify a potential inhibitor to control the level of Alzheimer disease.MethodWe have selected two different databases (ZINC15 and DUNDEE) and four different enzymes (Acetylcholinesterase, Butyrylcholinesterase, β‐Secretase and Glycogen synthase kinase 3 beta) for the study and carried out the high throughput virtual screening (HTVS), molecular docking, molecular dynamics simulation and binding free energy calculation to understand the active site effects and its stability.ResultIn the AChE and BChE, the screened molecules are showing good binding with strong interactions; notably, π‐cationic interactions were observed between amine group of ligand and tyrosine, tryptophan residues of AChE. Whereas in the BChE, active site residue Glu197 is highly stable. The catalytic dyad residue Asp93 of BACE1 maintains their hydrogen bond and Asp133 of GSK3β also sustain the strong interactions during the MD simulation. Apart from this, the statistical parameters (RMSD, RMSF and Rg) of these complexes are acceptable.ConclusionIn‐silico based analyses demonstrate that all the selected molecules are forming strong hydrogen bonding with catalytic residues and these interactions are highly stable during the atomistic simulation with high affinity. This comparative study allows to understand binding affinity, stability of intermolecular interactions and molecular flexibility of the molecules in the active site of AChE/BChE enzymes. Computational understanding of unproven molecules may lead towards the developing against AD.
Clinical use of deep speech parameters derived from the semantic verbal fluency task
Authors: ter Huurne Daphne BG , Ramakers Inez HGB , Linz Nicklas , König Alexandra , Langel Kai , Lindsay Hali , Verhey Frans RJ , de Vugt Marjolein 
Published: December 2021

AbstractBackgroundPrevious research showed that semantic memory is a good indicator for cognitive decline in early phases of Alzheimer’s disease. Automatically derived deep speech parameters from the semantic verbal fluency (SVF) can potentially have an additional value to differentiate SCI, MCI and dementia, compared to the total fluency score. However, the added diagnostic value of (specific) deep speech parameters to the commonly clinically used SVF raw score remains unknown. In the Deepspa project, we investigated the (additional) value of automatically derived speech parameters in clinical practice. We also investigated the relation between automatically derived speech parameters of the SVF and other cognitive tasks, as well as disease severity and functioning in daily living.MethodIn the DeepSPA project, 140 participants were recruited from the memory clinic of the MUMC+ (SCI, MCI, ADD). All subjects underwent a cognitive assessment including the SVF. The SVF (animals, 60 seconds) was administered by use of the Delta application (ki elements). Disease severity and functioning in daily life were administered by the Clinical Dementia Rating Scale (CDR) and Disability Assessment for Dementia (DAD) respectively. The agreement between the automatic and clinical raw score of the SVF was assessed by the interclass correlation coefficient. The relation between the deep speech parameters, such as mean word frequency, temporal and semantic clusters, transition time between words etc., and syndrome diagnosis, DAD and CDR were investigated using stepwise regression analyses, corrected for age, education level and gender.ResultPreliminary results showed that deep speech parameters have an additional value in the classification of clinical diagnosis, and disease severity. More specifically, mean word frequency and the mean time between temporal clusters had an added value. The reliability between word count by the application and the clinician was good (ICC=.882, 95% CI = .820‐.923). Results about the relation between deep speech parameters and other cognitive performances will be available at the conference.ConclusionFirst results suggest that deep speech parameters have an additional value in the early diagnostics of cognitive impairments. More information about the value of these non‐invasive automatically derived deep speech parameters could improve diagnostic accuracy in clinical practice.