bluuebunny/crossref_metadata_2025_split huggingface dataset:
A flexible tactile sensor that uses polyimide/graphene oxide nanofiber as dielectric membrane for vertical and lateral force detection
Authors: Wu Dezhi , Cheng Xianshu , Chen Zhuo , Xu Zhenjin , Zhu Minjie , Zhao Yang , Zhu Rui , Lin Liwei 
Published: May 2022

Abstract
Flexible force sensors are of great interest in the fields of healthcare, physiological signals, and aircraft smart skin applications because of their compatibility with curved surfaces. However, the simultaneous detection of multidirectional forces remains an engineering challenge, despite the great progress made in recent years. Herein, we present the development of a flexible capacitive force sensor capable of efficiently distinguishing normal and sliding shear forces. A two-layer electrospun polyimide/graphene oxide (PI/GO) nanofiber membrane is used as the dielectric layer, which is sandwiched between one top electrode and four symmetrically distributed bottom electrodes. This composite membrane has an improved dielectric constant, a reduced friction coefficient, and good compressibility, leading to superior performance that includes high sensitivity over a wide operational range with measured results of 3 MPa−1 for 0–242 kPa (0–2.2 N) and 0.92 MPa−1 for 242–550 kPa (2.2–5 N) in the normal direction; and better than 1 N−1 for 0–3 N in the x- and y-axis directions. The system also has a low detection limit of 10 Pa, fast response and recovery times of 39 ms and 13 ms, respectively, a good cyclic stability of 10,000 cycles at a pressure of 176 kPa, and promising potential for use in high-temperature environments (200 °C). Moreover, a prototype 4 × 4 sensor array has been fabricated and successfully used in a robotic system to grasp objects and operate a wireless toy car. As such, the proposed system could offer superior capabilities in simultaneous multidirectional force sensing for applications such as intelligent robots, human–machine interaction, and smart skin.
Simulation study on 3D convolutional neural networks for time-of-flight prediction in monolithic PET detectors using digitized waveforms
Authors: Maebe Jens , Vandenberghe Stefaan 
Published: May 2022

Abstract

Objective. We investigate the use of 3D convolutional neural networks for gamma arrival time estimation in monolithic scintillation detectors. Approach. The required data is obtained by Monte Carlo simulation in GATE v8.2, based on a 50 × 50 × 16 mm3 monolithic LYSO crystal coupled to an 8 × 8 readout array of silicon photomultipliers (SiPMs). The electronic signals are simulated as a sum of bi-exponentional functions centered around the scintillation photon detection times. We include various effects of statistical fluctuations present in non-ideal SiPMs, such as dark counts and limited photon detection efficiency. The data was simulated for two distinct overvoltages of the SensL J-Series 60 035 SiPMs, in order to test the effects of different SiPM parameters. The neural network uses the array of detector waveforms, digitized at 10 GS s−1, to predict the time at which the gamma arrived at the crystal. Main results. Best results were achieved for an overvoltage of +6 V, at which point the SiPM reaches its optimal photon detection efficiency, resulting in a coincidence time resolution (CTR) of 141 ps full width at half maximum (FWHM). It is a 26% improvement compared to a simple averaging of the first few SiPM timestamps obtained by leading edge discrimination, which in comparison produced a CTR of 177 ps FWHM. In addition, better detector uniformity was achieved, although some degradation near the corners did remain. Significance. These improvements in time resolution can lead to higher signal-to-noise ratios in time-of-flight positron emission tomography, ultimately resulting in better diagnostic capabilities.
Is there a need for individualized adjustment of electrode belt position during EIT-guided titration of positive end-expiratory pressure?
Authors: Zhao Zhanqi , Chen Tsai-Fen , Teng Hui-Chen , Wang Yi-Chun , Chang Mei-Yun , Chang Hou-Tai , Frerichs Inéz , Fu Feng , Möller Knut 
Published: May 2022

Abstract

Objective. The aim of the present study was to evaluate the variation of tidal volume-to-impedance ratio (V
T/Z
T) during positive end-expiratory pressure (PEEP) titration with electrical impedance tomography (EIT) measurement. Approach. Forty-two patients with acute respiratory distress syndrome were retrospectively analyzed. An incremental and subsequently a decremental PEEP trial were performed with steps of 2 cm H2O and duration of 2 min per step during volume-controlled ventilation with decelerating flow. EIT measurement was conducted in the 5th intercostal space and V
T was recorded simultaneously. The variation of V
T/Z
T (RatioV) was defined as the changes in percentage to average ratio per cm H2O PEEP change. A z-score > 1 was considered as a significant variation and an implication that the measurement plane was inadequate. Main results. The RatioV of 42 patients was 1.29 ± 0.80%·cm H2O−1. A z-score of 1 corresponded to the variation of 2.09%·cm H2O−1. Seven patients (16.7%) had a z-score > 1 and showed either positive or negative correlation between the volume-to-impedance ratio and PEEP. Significance. Electrode placement at 5th intercostal space might not be ideal for every individual during EIT measurement. Evaluation of volume-to-impedance ratio variation is necessary for patients undergoing maneuvers with wide alteration in absolute lung volume.
Quantum counterpart of energy equipartition theorem for fermionic systems
Authors: Kaur Jasleen , Ghosh Aritra , Bandyopadhyay Malay 
Published: May 2022

Abstract
In this brief report, following the recent developments on formulating a quantum analogue of the classical energy equipartition theorem for open systems where the heat bath comprises of independent oscillators, i.e. bosonic degrees of freedom, we present an analogous result for fermionic systems. The most general case where the system is connected to multiple reservoirs is considered and the mean energy in the steady state is expressed as an integral over the reservoir frequencies. Physically this would correspond to summing over the contributions of the bath degrees of freedom to the mean energy of the system over a suitable distribution function ρ(ω) dependent on the system parameters. This result holds for nonequilibrium steady states, even in the nonlinear regime far from equilibrium. We also analyze the zero temperature behaviour and low temperature corrections to the mean energy of the system.
Early-detection surveillance for stem rust of wheat: insights from a global epidemic network based on airborne connectivity and host phenology
Authors: Radici Andrea , Martinetti Davide , Bevacqua Daniele 
Published: May 2022

Abstract
Stem rust of wheat, caused by the airborne pathogen Puccinia graminis, is a re-emerging crop disease representing a major concern to global food security. Potential long-distance transport by wind over a worldwide distributed host represents a challenge to effective surveillance and control of this disease. To monitor this disease, we have created a global epidemic network for stem rust of wheat combining (a) Lagrangian simulations of air-mass trajectories computed with the NOAA’s HYSPLIT model; (b) land use from the Map Spatial Production Allocation Model and (c) meteorological and environmental conditions that are known to affect bio-physical processes involved in the biology of P. graminis spores. Our findings are in agreement with the well known north-American ‘Puccinia pathway’ and suggest the existence of other sub-continental pathways at the global scale. We used network theory to conceive surveillance strategies aimed at early detection of outbreaks while minimizing the number of nodes to be surveilled (also referred to as sentinels). We found that the set cover algorithm, due the high average connectivity of the network (density = 0.4%), performs better than a number of other network metrics and permits us to identify an optimal sentinel set (1% of the network nodes) to surveil 50% of the network. Our results also show that effective surveillance plans for stem rust of wheat can be designed, but that they need to account for the actual geographical scale of the underlying epidemiological process and call for an international and trans-boundary approach.
Classification of stochastic processes by convolutional neural networks
Authors: AL-hada Eman A , Tang Xiangong , Deng Weihua 
Published: May 2022

Abstract
Stochastic processes (SPs) appear in a wide field, such as ecology, biology, chemistry, and computer science. In transport dynamics, deviations from Brownian motion leading to anomalous diffusion (AnDi) are found, including transport mechanisms, cellular organization, signaling, and more. For various reasons, identifying AnDi is still challenging; for example, (i) a system can have different physical processes running simultaneously, (ii) the analysis of the mean-squared displacements (MSDs) of the diffusing particles is used to distinguish between normal diffusion and AnDi. However, MSD calculations are not very informative because different models can yield curves with the same scaling exponent. Recently, proposals have suggested several new approaches. The majority of these are based on the machine learning (ML) revolution. This paper is based on ML algorithms known as the convolutional neural network to classify SPs. To do this, we generated the dataset from published paper codes for 12 SPs. We use a pre-trained model, the ResNet-50, to automatically classify the dataset. Accuracy of 99% has been achieved by running the ResNet-50 model on the dataset. We also show the comparison of the Resnet18 and GoogleNet models with the ResNet-50 model. The ResNet-50 model outperforms these models in terms of classification accuracy.
Increased sensitivity of smart contact lenses for continuous intraocular pressure measurement using ring-shaped design
Authors: Helgason Rick , Lai Yongjun 
Published: May 2022

Abstract
Smart contact lenses with continuous intraocular pressure (IOP) sensors are emerging as an alternate system for monitoring the progression and treatment of glaucoma. To date, such sensors have primarily consisted of strain gauges embedded on traditional contact lenses. This work presents a novel smart contact lens design consisting of a ring-shaped contact lens with a piezoresistive strain gauge. We observe an increase in IOP measurement sensitivity of the device with an increase inner diameter of the ring. Ring-shaped sensors with an inner diameter of 2.7 mm show an increase in sensitivity of up to 7.1% and ring-shaped sensors with an inner diameter of 4.7 mm show an increase in sensitivity of up to 17.9%. It is expected that by incorporating a ring-shaped lens, other strain gauge-based smart contact lenses in the literature would experience similar increase in sensitivity.
Multimode capacity of atomic-frequency comb quantum memories
Authors: Ortu Antonio , Rakonjac Jelena V , Holzäpfel Adrian , Seri Alessandro , Grandi Samuele , Mazzera Margherita , de Riedmatten Hugues , Afzelius Mikael 
Published: May 2022

Abstract
Ensemble-based quantum memories are key to developing multiplexed quantum repeaters, able to overcome the intrinsic rate limitation imposed by finite communication times over long distances. Rare-earth ion doped crystals are main candidates for highly multimode quantum memories, where time, frequency and spatial multiplexing can be exploited to store multiple modes. In this context the atomic frequency comb (AFC) quantum memory provides large temporal multimode capacity, which can readily be combined with multiplexing in frequency and space. In this article, we derive theoretical formulas for quantifying the temporal multimode capacity of AFC-based memories, for both optical memories with fixed storage time and spin-wave memories with longer storage times and on-demand read out. The temporal multimode capacity is expressed in key memory parameters, such as AFC bandwidth, fixed-delay storage time, memory efficiency, and control field Rabi frequency. Current experiments in europium- and praseodymium-doped Y2SiO5 are analyzed within this theoretical framework, which is also tested with newly acquired data, as prospects for higher temporal capacity in these materials are considered. In addition we consider the possibility of spectral and spatial multiplexing to further increase the mode capacity, with examples given for praseodymium doped Y2SiO5.
Experimental and simulation studies on hybrid incremental sheet forming
Authors: Jagtap Rahul , Bendure Sahil , Kumar Parshant , Sharma Ankush 
Published: May 2022

Abstract
In the present research work, parts are formed using two-step hybrid incremental sheet forming (HISF) process. The effect of process parameters such as preform tool size, tool diameter, and preforming depth on thinning in the formed part is studied. A simulation model is developed and simulation results are compared with the experimental results. Also, results of HISF process are compared with the results of single point incremental sheet forming. The simulation results are in good agreement with the experimental results. It is observed that HISF process results in lower thinning as compared to SPIF process. Further, it is found that preform tool size has considerable influence on the minimum thickness of formed part. Large preform tools result in relatively lower thinning.
Dynamic stability analysis in sandwich composite laminated face structure with partially treated magnetorheological fluid-filled core
Authors: Jonna Naresh , Srinivas J 
Published: May 2022

Abstract
Sandwich composites with controllable cores have wide applications in aerospace structures. This paper presents a dynamic modeling and stability analysis of sandwich beams with a partially filled magneto-rheological (MR) fluid core covered by laminated composite face sheets in the supersonic flow regime. The equations of motion of the resulting system are formulated using energy expressions and the Hamilton principle. Finite element modeling is employed to solve the equations with different boundary conditions. Initially, free vibration analysis is performed and the effect of the magnetic field on the natural frequencies of the beam is reported. In order to minimize the weight, the magnetorheological fluid is filled at selected cells in the core layer. The locations and sizes of these cells affect the modal characteristics and flutter stability of the beam. Also, the impact of core layer thickness under different boundary conditions is studied. Furthermore, the influence of magnetic field on the critical pressure in supersonic flow regime is investigated using first-order piston theory to identify the unstable regions. The results revealed that the size and position of the MR section in the beam and the applied magnetic field strength drastically influence the natural frequencies of partially treated magnetorheological laminated sandwich beams. The influencing variables are identified from main-effect plots using analysis of variance study.
Theta–gamma coupling as a cortical biomarker of brain–computer interface-mediated motor recovery in chronic stroke
Authors: Rustamov Nabi , Humphries Joseph , Carter Alexandre , Leuthardt Eric C. 
Published: May 2022

Abstract
Chronic stroke patients with upper-limb motor disabilities are now beginning to see treatment options that were not previously available. To date, the two options recently approved by the United States Food and Drug Administration include vagus nerve stimulation and brain–computer interface therapy. While the mechanisms for vagus nerve stimulation have been well defined, the mechanisms underlying brain–computer interface-driven motor rehabilitation are largely unknown. Given that cross-frequency coupling has been associated with a wide variety of higher-order functions involved in learning and memory, we hypothesized this rhythm-specific mechanism would correlate with the functional improvements effected by a brain–computer interface. This study investigated whether the motor improvements in chronic stroke patients induced with a brain–computer interface therapy are associated with alterations in phase–amplitude coupling, a type of cross-frequency coupling. Seventeen chronic hemiparetic stroke patients used a robotic hand orthosis controlled with contralesional motor cortical signals measured with EEG. Patients regularly performed a therapeutic brain–computer interface task for 12 weeks. Resting-state EEG recordings and motor function data were acquired before initiating brain–computer interface therapy and once every 4 weeks after the therapy. Changes in phase–amplitude coupling values were assessed and correlated with motor function improvements. To establish whether coupling between two different frequency bands was more functionally important than either of those rhythms alone, we calculated power spectra as well. We found that theta–gamma coupling was enhanced bilaterally at the motor areas and showed significant correlations across brain–computer interface therapy sessions. Importantly, an increase in theta–gamma coupling positively correlated with motor recovery over the course of rehabilitation. The sources of theta–gamma coupling increase following brain–computer interface therapy were mostly located in the hand regions of the primary motor cortex on the left and right cerebral hemispheres. Beta–gamma coupling decreased bilaterally at the frontal areas following the therapy, but these effects did not correlate with motor recovery. Alpha–gamma coupling was not altered by brain–computer interface therapy. Power spectra did not change significantly over the course of the brain–computer interface therapy. The significant functional improvement in chronic stroke patients induced by brain–computer interface therapy was strongly correlated with increased theta–gamma coupling in bihemispheric motor regions. These findings support the notion that specific cross-frequency coupling dynamics in the brain likely play a mechanistic role in mediating motor recovery in the chronic phase of stroke recovery.
Long-Term Mortality of Tuberculosis Survivors in Korea: A Population-based Longitudinal Study
Authors: Choi Hayoung , Han Kyungdo , Jung Jin-Hyung , Park Sang Hyun , Kim Sang Hyuk , Kang Hyung Koo , Sohn Jang Won , Shin Dong Wook , Lee Hyun 
Published: May 2022

Abstract

Background
When assessing long-term tuberculosis (TB) mortality, few studies addressed the impact of behavior habits and socioeconomic status. Therefore, we aimed to evaluate long-term TB mortality and risk factors while accounting for potential confounders.

Methods
This cohort study included TB survivors (n = 82 098) aged ≥20 years between 2010 and 2017, and 1:1 age- and sex-matched controls (n = 82 098). The participants were followed up for death 1 year after study enrollment until December 2018. Long-term mortality was adjusted for behavior habits (smoking, alcohol consumption, or exercise), income level, body mass index (BMI), and comorbidities.

Results
During a median of 3.7 years of follow-up, the incidence rate of mortality was significantly higher in TB survivors than those in the matched controls (18.2 vs. 8.8 per 1000 person-years, P &lt; .001). Even after adjusting for potential confounders, the mortality risk was 1.62-fold (95% confidence interval [CI], 1.54–1.70) higher in TB survivors than those in the matched controls. In addition, the hazard of mortality in TB survivors relative to matched controls significantly increased in participants aged ≥30 years, with the highest risk in those in their 40s. Male sex (adjusted hazard ratio [HR]: 2.31; 95% CI, 2.16–2.47), smoking pack-years (HR: 1.005; 95% CI, 1.004–1.006), heavy alcohol consumption (HR: 1.12; 95% CI, 1.01–1.23), and lowest income (HR: 1.27; 95% CI, 1.18–1.37) were positively associated with increased hazards for mortality, whereas higher BMI (HR: 0.91; 95% CI, .90–.92) and regular exercise (HR: 0.82; 95% CI, .76–.88) reduced the hazards of long-term mortality in TB survivors.

Conclusions
The long-term mortality risk was significantly higher in TB survivors than those in the matched controls, even after adjusting for potential confounders.
Elusive workers are more likely to differentiate into replacement reproductives than aggressive workers in a lower termite
Authors: Bai Zhuang-Dong , Shi Chong-Yang , Sillam-Dussès David , Wang Rui-Wu 
Published: May 2022

Abstract
One of the most intriguing questions in eusocial insects is to understand how the overt reproductive conflict in the colony appears limited when queens or kings are senescent or lost because the morphologically similar individuals in the colony are reproductively totipotent. Whether there are some individuals who preferentially differentiate into replacement reproductives or not has received little attention. The consistent individual behavioral differences (also termed “animal personality”) of individuals from the colony can shape cunningly their task and consequently affect the colony fitness but have been rarely investigated in eusocial insects. Here, we used the termite Reticulitermes labralis to investigate if variations in individual personalities (elusiveness and aggressiveness) may predict which individuals will perform reproductive differentiation within colonies. We observed that when we separately reared elusive and aggressive workers, elusive workers differentiate into reproductives significantly earlier than aggressive workers. When we reared them together in the proportions 12:3, 10:5, and 8:7 (aggressive workers: elusive workers), the first reproductives mostly differentiated from the elusive workers, and the reproductives differentiated from the elusive workers significantly earlier than from aggressive workers. Furthermore, we found that the number of workers participating in reproductive differentiation was significantly lower in the groups of both types of workers than in groups containing only elusive workers. Our results demonstrate that the elusiveness trait was a strong predictor of workers’ differentiation into replacement reproductives in R. labralis. Moreover, our results suggest that individual personalities within the insect society could play a key role in resolving the overt reproductive conflict.
Social Brain Energetics: Ergonomic Efficiency, Neurometabolic Scaling, and Metabolic Polyphenism in Ants
Authors: Coto Zach N , Traniello James F A 
Published: May 2022

Abstract
Metabolism, a metric of the energy cost of behavior, plays a significant role in social evolution. Body size and metabolic scaling are coupled, and a socioecological pattern of increased body size is associated with dietary change and the formation of larger and more complex groups. These consequences of the adaptive radiation of animal societies beg questions concerning energy expenses, a substantial portion of which may involve the metabolic rates of brains that process social information. Brain size scales with body size, but little is understood about brain metabolic scaling. Social insects such as ants show wide variation in worker body size and morphology that correlates with brain size, structure, and worker task performance, which is dependent on sensory inputs and information-processing ability to generate behavior. Elevated production and maintenance costs in workers may impose energetic constraints on body size and brain size that are reflected in patterns of metabolic scaling. Models of brain evolution do not clearly predict patterns of brain metabolic scaling, nor do they specify its relationship to task performance and worker ergonomic efficiency, two key elements of social evolution in ants. Brain metabolic rate is rarely recorded and, therefore, the conditions under which brain metabolism influences the evolution of brain size are unclear. We propose that studies of morphological evolution, colony social organization, and worker ergonomic efficiency should be integrated with analyses of species-specific patterns of brain metabolic scaling to advance our understanding of brain evolution in ants.