Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrical Properties and Biological Synaptic Simulation of Ag/MXene/SiO2/Pt RRAM Devices

Utilizing electronic devices to emulate biological synapses for the construction of artificial neural networks has provided a feasible research approach for the future development of artificial intelligence systems. Until now, different kinds of electronic devices have been proposed in the realization of biological synapse functions. However, the device stability and the power consumption are major challenges for future industrialization applications. Herein, an electronic synapse of MXene/SiO2 structure-based resistive random-access memory (RRAM) devices has been designed and fabricated by taking advantage of the desirable properties of SiO2 and 2D MXene material. The proposed RRAM devices, Ag/MXene/SiO2/Pt, exhibit the resistance switching characteristics where both the volatile and nonvolatile behaviors coexist in a single device. These intriguing features of the Ag/MXene/SiO2/Pt devices make them more applicable for emulating biological synaptic plasticity. Additionally, the conductive mechanisms of the Ag/MXene/SiO2/Pt RRAM devices have been discussed on the basis of our experimental results.
Expérimentations autour des architectures d'apprentissage par transfert pour l'extraction de relations biomédicales

L'extraction de relations (ER) consiste a identifier et a structurer automatiquement des relations a partir de textes. Recemment, BERT a permis d'ameliorer les performances de plusieurs tâches de TAL, dont l'ER. Cependant, la meilleure facon d'utiliser BERT, dans une architecture d'apprentissage automatique avec une strategie par transfert reste une question ouverte, car elle depend a la fois de la tâche et du domaine d'application. Dans ce travail, nous explorons diverses architectures d'ER qui s'appuient sur BERT et deux strategies de transfert (gel des poids ou reglage fin) sur deux corpus biomedicaux. Parmi les architectures et strategies de transfert testees, *BERT-segMCNN avec reglage fin atteint des performances superieures a l'etat de l'art sur les deux corpus (amelioration absolue de 1,73% et 32,77% sur ChemProt et PGxCorpus respectivement). Nos experiences illustrent l'interet attendu du reglage fin avec BERT, et de facon plus originale l'interet d'ajouter aux representations de BERT une information structurelle en considerant la segmentation des phrases.
Investigação das correlações existentes entre o ciclo vigília-sono e a dor num modelo experimental de fibromialgia

Sleep disorders are highly prevalent in patients with fibromyalgia. Many of the daytime symptoms, such as excessive sleepiness and fatigue, can be related to non-restorative sleep patterns and associated with the typical pain conditions of the disease. In this context, we aim to study the possible correlations between the sleep-wake cycle and pain behavior in an animal model of fibromyalgia induced by repeated injections of reserpine. Male and female adult Wistar rats received chronic implants to record EEG and EMG activity. Injections of reserpine produced increases in the response to mechanical stimulation detected using the von Frey test. The reserpine treated rats showed increased incidence of the behavioral states of the sleep-wake cycle with concomitant reduction in the respective durations, showing fragmentation of the cycle. Additionally, the presence of aberrant behaviors was observed in these animals accompanied by notable electroencephalographic changes when compared to control animals. Also noteworthy are changes in specific frequency bands of the EEG corresponding to attentive wakefulness and slow-wave sleep states. Based on these findings, it is possible to infer that the reserpine model of fibromyalgia can be a useful model for this disease in humans.
Prognostic Value of Muscle Mass Measured via Brain Computed Tomography in Neurocritically Ill Patients

We investigated whether skeletal muscle mass estimated via brain computed tomography (CT) can be used to predict neurological outcomes in neurocritically ill patients. Adult patients who were admitted to the neurosurgical intensive care unit (ICU) from January 2010 to September 2019 were eligible. We included patients who were hospitalized in the neurosurgical ICU for more than 7 days. Cross-sectional areas of paravertebral muscle at the first cervical vertebra level (C1-CSA) and temporalis muscle thickness (TMT) on brain CT were measured to evaluate skeletal muscle mass. Primary outcome was Glasgow Outcome Scale score at 3 months. Change of C1-CSA (adjusted odds ratio [OR]: 1.36, 95% confidence interval [CI]: 1.054–1.761) and change of TMT (adjusted OR: 1.27, 95% CI: 1.028–1.576) were significantly associated with poor neurological outcome (Hosmer–Lemeshow test, Chi-square = 11.4, df = 8, p = 0.178) with areas under the curve of 0.803 (95% CI 0.740–0.866) using 10-fold cross validation method. Especially, risk of poor neurologic outcome was proportional to changes of C1-CSA and TMT. In this study, the follow-up skeletal muscle mass at first week from ICU admission, based on changes in C1-CSA and TMT, was associated with neurological prognosis in neurocritically ill patients.
New Efficient Algorithm for the Discrete Hartley Transform

In real-time signal processing applications, the discrete version of the transform introduced by Hartley (DHT) has been proved to be an efficient substitute to the discrete Fourier transform (DFT). A new algorithm for fast calculations of the DHT (FHT) based on radix -2/4/8 method is introduced in this paper. In comparison with the split radix FHT algorithm, the proposed algorithm has a comparable arithmetic complexity, but preserves the regularity and the simple butterfly structure of the radix-2 algorithm. The development of the algorithm is motivated by firstly deriving a new radix-2/8 FHT algorithm and then cascading it with the radix-4 and radix-2 FHT algorithms. The arithmetic complexity of the developed algorithm has been implemented and analyzed by calculating the number of real additions and multiplications for different transform lengths. Comparisons with the existing FHT algorithms have shown that this algorithm can be considered as a good compromise between structural and arithmetic complexity.
Biomass-derived porous carbon materials with sulfur and nitrogen dual-doping for energy storage

Nowadays, energy shortage is a serious socioeconomic problem. The recovery of biomass can make a very significant contribution in alleviating the burden on already-strained energy resources. Broad beans, which are abundant in amino acids and vitamins, are extensively cultivated worldwide. However, a large quantity of by-product, broad bean shells, remains unused and pollutes the environment from the incinerating and/or uncontrolled decomposition that results. In this paper, we report the synthesis of sulfur and nitrogen dual-doping porous carbon materials, for use as the electrode materials of energy storage devices, produced by carbonizing the shells of broad beans by a chemical activation. The specific capacitance of the as-prepared porous carbon material is as high as 202 F g−1, with a superior cycling performance for electric double layer capacitors at a current density of 0.5 A g−1. Furthermore, it also shows a stable performance for lithium ion batteries and sodium ion batteries, which suggests that it has a promising potential for wide applications in the field of energy storage devices.
Influence of Sintering Temperature on the Properties of Porous Ceramic Support Prepared by Uniaxial Dry Compaction Method Using Low-Cost Raw Materials for Membrane Applications

In this article, we have reported the fabrication of stable macroporous ceramic support using low-cost inorganic raw materials by uniaxial dry compaction technique. The supports were prepared by mixing of inexpensive raw materials such as kaolin, quartz, calcium carbonate, sodium carbonate, boric acid, sodium metasilicate, and polyvinyl alcohol as a binder. The prepared green supports were sintered at different temperatures ranging between 900 and 1000°C. The raw materials and the sintered supports were characterized by thermogravimetric analysis, particle size distribution (PSD), X-ray diffraction, and scanning electron microscopy analysis. The influence of sintering temperature on the membrane structure, porosity, flexural strength, chemical stability, and the pure water permeability was also examined. It was observed that the average pore size and the flexural strength of the sintered supports increase with an increase in the sintering temperature. The porosity of the sintered supports was obtained in the ranges between 22 and 40%. The chemical stability of the sintered supports was found to be good. Based on the results obtained, the support sintered at 950°C (porosity of 30%, mechanical strength of 28 MPa, and average pore size of 3.45 µm) was considered as the optimum support for membrane applications. The ceramic support cost was estimated to be $67/m2 according to the raw material price. Henceforth, these low-cost membrane supports with better properties could be suggested for cheaper application in chemical and biochemical processes.
Collection of municipal solid waste in developing countries

apparent divide also in the Coalition Government at Secretary of State level (Communities and Local Government, Conservative, on the one hand; and Energy and Climate Change, Liberal Democrat, on the other hand). New planning legislation gives local residential communities the power to oppose onshore windfarm developments. Further, the UK is not on track to meet her EU-derived or self-stated (but now relaxed or timeline extended) targets. Case study material comes from the UK (Chapter 10 by Sims and Dent), the USA (Chapter 11 by Hoen), as well as Australia and New Zealand (Chapter 12 by Bond). The concluding chapter is by Dent and Sims. Practitioners and also students of valuation and surveying should find this up to date and full of usefulness.
Anodic Behavior of Copper in 1-Hydroxyethylene-1, 1-Diphosphonic Acid (HEDPA) Baths

The electrochemical behavior of anodic dissolution of copper electrode was investigated in non-cyanide alkaline electrolyte containing 1-hydroxyethylene-1, 1-diphosphonic acid (HEDPA) as a complexing agent. Electrochemical behavior of copper electrode was studied by cyclic voltammetry. X-ray photoelectron spectroscopy was used to study morphologies of copper electrode after dissolution under different potentials. The results showed that in cyclic voltammetry curve of the 1-hydroxyethylene-1,1-diphosphonic Acid(HEDPA) baths, the first peak of copper anode was diffusion-controlled, associated with the formation of Cu2O. The second oxidation peak came from generating CuO and the third peak was the formation of CuO/Cu(OH)2 compound.
Effect of heat treatment and wax impregnation on dimensional stability of Pterocarpus macrocarpus wood.

In order to improve dimensional stability and control deformation, heat treatment (HT) and wax impregnation (WI) were conducted to large size boards (LB) of Pterocarpus macrocarpus and the tangential swelling were compared in various relative humidity (RH) conditions. The results show that the tangential swelling and shrinking of control group and treated group performed differently corresponded to various relative humidity (RH). Comparing with control group, the swelling ratio of HT combined WI group was much less, and followed by 180°C-3h HT group. The maximum swelling ratio decreased by 31% and 29% in humidity chamber and indoor conditions respectively. The swelling ratio was affected by size of samples, LB showed smaller welling ratio than small sample. Wax filled in cell cavities and presented uneven distributions after impregnation. The rate of wood hygroscopicity was reduced after HT combined WI treatment which was an effective method on improvement of wood dimensional stability.
Cell-imprinted substrates: in search of nanotopographical fingerprints that guide stem cell differentiation

Cell-imprinted substrates direct stem cell differentiation into various lineages, suggesting the idea of lineage-specific nanotopography. We herein examined the surface topography of five different imprinted cell patterns using AFM imaging and statistical analysis of amplitude, spatial, and hybrid roughness parameters. The results suggest that different cell imprints possess distinguished nanotopographical features.
Amine-Modified Polyborazylenes: Second-Generation Precursors to Boron Nitride

New second-generation polymeric precursors to BN ceramics have been synthesized in high yield by the reaction of polyborazylene (PB), [B3N3H∼3.5]x, with diethylamine (DEA), dipentylamine (DPA), and hexamethyldisilazane (HMD). Elemental analyses and the spectroscopic data indicate that the resulting DEA-PB, DPA-PB, and HMD-PB polymers contain boron-bonded amino groups attached to the polyborazylene backbone. Analysis of volatile byproducts of the reaction suggests modification of PB with DEA and DPA occurs primarily through dehydrocoupling reactions, while the reaction with HMD involves amine Si−N bond cleavage with elimination of trimethylsilane. Combined molecular weight/infrared spectroscopy studies show the polymers are modified throughout the molecular weight distribution. Modification with HMD results in increased molecular weights due to cross-linking reactions involving the silazane. The DEA-PB and DPA-PB polymers have lower molecular weights than the starting PB, with the highest amine concentrati.
Microscopy images segmentation algorithm based on shearlet neural network

Microscopic images are becoming important and need to be studied to know the details and how-to quantitatively evaluate decellularization. Most of the existing research focuses on deep learning-based techniques that lack simplification for decellularization. A new computational method for the segmentation microscopy images based on the shearlet neural network (SNN) has been introduced. The proposal is to link the concept of shearlets transform and neural networks into a single unit. The method contains a feed-forward neural network and uses a single hidden layer. The activation functions are depending on the standard shearlet transform. The proposed SNN is a powerful technology for segmenting an electron microscopic image that is trained without relying on the pre-information of the data. The shearlet neural networks capture the features of full accuracy and contextual information, respectively. The expected value for specific inputs is estimated by learning the functional configuration of a network for the sequence of the observed values. Experimental results on the segmentation of two-dimensional microscopy images are promising and confirm the benefits of the proposed approach. Lastly, we investigate on a challenging dataset ISBI 2012 that our method (SNN) achieves superior outcomes when compared to classical and deep learning-based methods.
Nexus Between Sectoral Shift and Stock Return: Insights From Bangladesh

The objective of this study is to examine the impact of sectoral shift on the stock return of Bangladesh. This study employs auto-regressive distributive lag (ARDL) approach using the weekly data of various sectoral indices of Bangladesh over the period from May 1999 to September 2016. The findings tend to indicate that there has possible sectoral portfolio diversification in the market and ‘general product industry' is the most exogenous and profitable sector from the rest. This study is one of the first attempts of the sectoral analysis and its impact on the stock return with the reference to Bangladesh. Furthermore, this study can be a benchmark for the policymakers of emerging economies to find the impact of economic transformation in the stock returns of the equity markets.
Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

This article investigates the command filtered adaptive neural tracking control for uncertain nonlinear time-delay systems subject to asymmetric time-varying full state constraints and actuator saturation. To stabilize such a class of systems, the radial basis function neural networks and the backstepping technique are used to structure an adaptive controller. The command filter is utilized to overcome the complexity explosion problem in backstepping. By employing the Lyapunov–Krasovskii functionals, the effect of time-delay is eliminated. The asymmetric time-varying barrier Lyapunov functions are designed to ensure full state constraint satisfaction. Moreover, the hyperbolic tangent function and an instrumental variable are introduced to deal with actuator saturation. All signals in the closed-loop system are proved to be bounded and the tracking error converges to a small neighborhood of the origin. Finally, two examples are provided to illustrate the effectiveness of the proposed method.
Directed Photocurrents in Nanostructured TiO 2 /SnO 2 Heterojunction Diodes

Time-resolved photocharge (TRPC) measurements are applied for the first time to demonstrate the presence of a contact potential between lightly sintered colloidal nanocrystalline TiO2 films deposited on transparent highly conductive tin oxide films degenerately doped with fluorine, SnO2(F). By virtue of its contactless nature and absence of an externally applied field, TRPC has previously been demonstrated to possess the capability to directly probe the electric field in semiconductor heterojunction particulate materials without the complications and ambiguities encountered with many other measurement techniques. Using TRPC, vectorial directions of photoelectron currents in glass/SnO2(F)/TiO2 samples, as determined by signal polarity, are found to be dependent on their orientation with respect to the incident photon flux (i.e., negative polarity for exposure through the glass; positive polarity for exposure directly on the TiO2). This implies that photoelectrons always flow toward the SnO2(F)/TiO2 interfa.
Concurrent Validity of ActiGraph GT3X+ and Axivity AX3 Accelerometers for Estimating Physical Activity and Sedentary Behavior

Introduction: Accelerometers are commonly used to assess time-use behaviors related to physical activity, sedentary behavior, and sleep; however, as new accelerometer technologies emerge, it is important to ensure consistency with previous devices. This study aimed to evaluate the concurrent validity of the commonly used accelerometer, ActiGraph GT3X+, and the relatively new Axivity AX3 (fastened to the lower back) for detecting physical activity intensity and body postures when using direct observation as the criterion measure. Methods: A total of 41 children (aged 6–16 years) and 33 adults (aged 28–59 years) wore both monitors concurrently while performing 10 prescribed activities under laboratory conditions. The GT3X+ data were categorized into different physical activity intensity and posture categories using intensity-based cut points and ActiGraph proprietary inclinometer algorithms, respectively. The AX3 data were first converted to ActiGraph counts before being categorized into different physical activity intensity categories, while activity recognition models were used to detect the target postures. Sensitivity, specificity, and the balanced accuracy for intensity and posture category classification were calculated for each accelerometer. Differences in balanced accuracy between the devices and between children and adults were also calculated. Results: Both accelerometers obtained 74–96% balanced accuracy, with the AX3 performing slightly better (∼4% higher, p < .01) for detecting postures and physical activity intensity. Error in both devices was greatest when contrasting sitting/standing, sedentary/light intensity, and moderate/light intensity. Conclusion: In comparison with the GT3X+ accelerometer, AX3 was able to detect various postures and activity intensities with slightly higher balanced accuracy in children and adults.
Beef Cattle Response to Air Temperature

ABSTRACT BEEF cattle with an initial weight of about 600 lb (270 kg) fed a high energy ration were maintained at constant air temperatures of 20.3, 24.1 or 29.3 °C for 84 days. There was a significant depression in feed intake and rate of gain at 29.3 °C compared to 20.3 °C. A similar test at air temperatures of 21.1, 16.4 and 12.4 °C showed significant differences in rate of gain at the three temperatures with a decline with lowering temperature. This change and the accompanying change in feed efficiency does not seem to be explained by changes in thermal environment and the reason remains unclear.
A doubly accelerated degradation model based on the inverse Gaussian process and its objective Bayesian analysis

ABSTRACT The accelerated degradation test (ADT) is an effective method for evaluating the lifetime of high-reliability products. In this paper, a doubly accelerated degradation model based on the inverse Gaussian process is proposed to characterize the ADT data, and then an objective Bayesian approach is presented to analyze the model. Some important noninformative priors including the Jeffreys prior and reference priors under different group orderings are derived. The propriety of the posterior distributions under each prior is validated. A simulation study is carried out to show the superiority of objective Bayesian approach compared with the parametric Bootstrap method. Finally, the approach is applied to analyze a carbon film data.
Shift reagent 1H NMR study of methoxycoumarins

Attribution complete des deplacements chimiques protoniques de la coumarine, de tous ses derives monomethoxy et de 6 derives dimethoxy sur le cycle aromatique, en utilisant le reactif de deplacement Pr(fod) 5 : complexation du carbonyle de lactone, interaction avec 2 groupes methoxy en position ortho
An Examination of Teachers’ Attitudes Towards the National Park in Their Environment: The Isparta, Denizli Example

Environmental education in national parks is equivalent to an open and permanent education process in which individuals and communities become aware of their natural environment and gain a critical and sensitive attitude towards it and the use of its resources. The aim of this study was to examine the attitudes of teachers towards national parks who work in schools near different national parks in terms of different variables. As a work of descriptive research, it was conducted with a total of 167 teachers who worked in schools around Kovada Lake National Park, Kızıldağ National Park, and Honaz Mountain National Park. In the study, an attitude scale with a Cronbach’s Alpha coefficient of 0.83 and consisting of 32 items was used for the national parks. The SPSS (Statistical Package for Social Sciences Program) was used to evaluate the data obtained. A T-test and a one-way ANOVA test were used to analyze the data. According to the results obtained, teachers’ attitudes towards the national park did not show a significant difference in terms of their gender, their tenure, the branches they serve, their purpose of visiting the national park, their opinions on the importance attached to the national park, the different schools near the national park, the national park near the schools they worked in, their purpose in visiting the national park previously while they differed significantly according to whether the teachers had visited the national park before.