Miracle-dz/UniFAR-FTUs huggingface dataset:
Free Vibration Analysis of a Free-Free Single-Tapered Beam Carrying Arbitrary Concentrated Elements Using Modified Mode-Superposition Method (MMSM)

The literature contains scant information on the free vibration analyses of the loaded single-tapered beams (STBs) (i.e., STBs carrying concentrated elements (CEs)) Furthermore, even when such studies have been performed, they generally only consider the case of constrained (e.g., free-clamped (F-C)) beams. In other words, the problem of unconstrained (e.g., freeefree (F-F)) loaded STBs has not yet to be addressed. Thus, the present study employs the modified modesuperposition method (MMSM) to investigate the free vibration characteristics of the F-F loaded STB carrying arbitrary various CEs. The investigation focuses particularly on the natural frequencies and mode shapes of the rigid-body motions and elastic vibrations of the STB. The presented MMSM differs from the conventional mode-superposition method (CMSM) in that the mode shapes of the rigid-body motions of the F-F bare STB are also taken into account, whereas the CMSM considers only the elastic vibration of the STB. The numerical results show that, for the considered F-F loaded STB problem, the CMSM provides neither any information regarding the rigid-body motions of the beam, nor any satisfactory solutions for the elastic vibrations. The correctness of the presented theory and developed computer code is demonstrated by comparing the numerical results obtained using the proposed MMSMwith those obtained from the finite element method (FEM). It is shown that the two sets of results are in good agreements.
Language mapping functions: Improving softmax estimation and word embedding quality

One of the best methods for estimating the softmax layer in neural network language models is the noise‐contrastive estimation (NCE) method. However, this method is not proper for word embedding applications compared with some other robust methods such as the negative sampling (NEG) method. The NEG method implements the pointwise mutual information (PMI) relation between the word‐context space in the neural network, and the NCE method implements conditional probability. Both the NCE and NEG methods use dot‐product‐based mapping to map words and contexts vector to the probabilities. This article presents the parametric objective function, which uses the mapping function as the parameter. Also, we obtained a parametric relation between word‐context space according to the mapping parameter. Using the parametric objective function, we identify conditions for a mapping that make it a proper selection for both softmax estimation and word embedding. The article also presents two specific mapping functions with the required conditions, and we compared their performance with that of the dot‐product mapping function. The performance of the new mapping functions is also reported over common word embedding and language models' benchmarks.
In situ determination of the electrochemically active platinum surface area: key to improvement of solid acid fuel cells

The electrochemically active surface area (ECSA) is an important parameter when investigating and developing electrodes for fuel cells. Various methods exist to determine the ECSA of polymer electrolyte membrane fuel cells both in and ex situ. However, for intermediate-temperature solid acid fuel cells (SAFC), a quantitative method to determine the ECSA has not yet been established. Here, we show that analysis of the electrochemical surface oxide reduction is a viable approach to quantify the ECSA in SAFCs. We validate the method using a Pt foil as model electrode and ex situ hydrogen underpotential deposition measurements. The applicability to SAFCs with composite powder electrodes is demonstrated in combination with an accelerated degradation test. The results reveal a surprisingly low decrease of the ECSA during operation of solid acid fuel cells. The method will enable a better understanding of novel nano-composite electrodes that are necessary for high performance devices.
Technological advances in preclinical meta-research

Metaresearch is a scientific field involving the study of research itself. It has been applied to clinical trials since the 1980s,1 but has only become an emerging discipline over the last decade in the preclinical field. The primary tool of metaresearch is the systematic review, which uses predefined methods to provide a transparent and comprehensive summary of the evidence relating to a research question. A systematic review is defined as ‘a review that uses explicit, systematic methods to collate and synthesize findings of studies that address a clearly formulated question’. 2 Systematic reviews allow for evaluation of methods and comprehensiveness of reporting, to assay likelihood of reproducibility and potential for translatability to subsequent domains of research and can investigate the impact of incentives on primary research. This, in turn, allows for a more rigorous understanding of what makes research reliable, and how research can be improved,3 while driving evidence-based decisions for future research.4 5 Systematic reviews typically comprise several steps. Before beginning a systematic review, it is recommended that the author team develop a protocol, which defines the research question and the methods that will be used to conduct, analyse and report the findings of the review. The research question determines the resources required to complete the review, the broader the question and the larger the field the more resource intensive a review will be. The search strategy is developed to identify as much potentially relevant literature as possible, often involving searching of multiple databases. Following database searches, deduplication (if searching multiple database with overlapping coverage), the unique search results are screened for inclusion or exclusion. Full-text retrieval may be conducted before or after title and abstract citation screening. Metadata including information regarding reported study quality and design, and outcome data are then extracted from the included …
The role of exercise selection in regional Muscle Hypertrophy: A randomized controlled trial

ABSTRACT There is emerging evidence suggesting that muscle growth is not homogeneous through the muscle. The aim of the present study was to analyse the role of exercise selection in regional hypertrophy. Two randomly allocated groups with equal training volume and intensity performed squats in the smith machine (SMTH group) or the leg extension exercise (LEG group). Growth in proximal, central and distal regions of the rectus femoris (RF) and vastus lateralis (VL) muscles, jump height and body composition were analysed. Results show that the three regions of RF grew significantly in the participants of the LEG group (p < 0.05), while only the central region of VL grew significantly in the SMTH group (p < 0.05). In summary, this study confirms that exercise selection plays a role in regional hypertrophy. Whilst there may be still other factors that determine how muscles grow, it seems that the chosen exercises may be responsible of the differences observed in this study.
Exploring the Determinants of Users’ Continuance Intention to Use Mobile Banking Services in Kuwait : Extending the Expectation-Confirmation Model

While a great body of information systems (IS) literature has discussed mobile banking (m-banking) services, most of these studies have focused on the adoption or acceptance phases of this technology; with little attention was given to users’ intension to continue using such technology. This paper aims at investigating the most important factors that predict users’ continuous intension to use m-banking services in the post-adoption phase. This paper presents a conceptualization and validation of an extended expectation-confirmation model (ECM). A total of 303 Kuwaiti users of m-banking services participated in this study. Partial least squares (PLS) of structure equation modelling (SEM) technique was used to analyze the data. The results mainly showed that users’ continuous intension to use m-banking services is significantly influenced by perceived trust, satisfaction, self-efficacy, performance expectancy and effort expectancy. Theoretical and practical contributions as well as the research limitations and future directions are discussed.
Carbon (δ13C) dynamics in agroecosystems under traditional and minimum tillage systems: a review

Following cultivation, substantial loss of soil organic matter occurs in surface soil layers. No-till is an agronomic practice to reverse or slow the loss of soil organic matter. We reviewed 95 research papers that used 13C natural abundance of soils to quantify the impact of tillage on the C dynamics of cropping systems. New C (from current cropping systems) accumulated in the surface soil under no-till, whereas the most extreme cultivation (mouldboard ploughing) mixed new C throughout the soil. There was a decline in soil C with years of cultivation. Compared with land that had been tilled, no-till generally had little impact on the accumulation on soil organic C. Tillage and residue retention caused stratification in C stocks that depended on tillage depth, with the highest C concentrations and stocks found in the surface under no-till. Shifts in the δ13C signature indicated significant exchange of ‘new’ C for the original (old) C. Tillage methods had no impact on the size and δ13C signature of the microbial biomass pool. Change in δ13C indicates that microbial biomass rapidly incorporates new carbon. The largest change in the δ13C values (Δ13C) was observed in the coarse sand fraction, whereas the smallest change occurred in the clay fraction. Comparison of conventional vs no-till showed inconsistent results on the effect of tillage on C in the different particle size fractions. Natural 13C abundance data show that no-till cropping systems do not result in increases in soil organic C in the top 0.30 m of soil.
Single Mode, Air-Cladded Optical Waveguides Supported by a Nano-Fin Fabricated with Direct Laser Writing

Single-mode, air-cladded optical waveguides have wavelength scale diameters, making them very fragile and difficult to handle and yet highly desirable for sensing and inter-chip photonic interconnects. These contradictory qualities are resolved in this work by supporting the optical waveguide with a nano-fin structure attached to a substrate, narrow enough and sufficiently tall to minimally impact the wave-guiding metrics of the solid core while providing structural mechanical integrity. The design considerations for the nano-fin-supported waveguide and its realization using a commercial direct laser writing system based on two-photon activation of a photopolymer is reported herein. The 3D printed waveguides are characterized and experimentally assessed, demonstrating low birefringence and an estimated propagation loss for LP01x and LP01y of 2.9 dB/mm and 3.4 dB/mm, respectively, attributed to surface roughness and the relatively high refractive index contrast with air.
Assessment of the Vulnerability of Selected Key Elements of Rail Transport. Slovak Case Study

Increases in means of transport, developed transport networks, and modernization dependent on computer technology not only lead to huge security demands but also require preventive measures and vulnerability assessments of key elements of transport infrastructure. The analyses carried out have shown that, though the importance of transport continues to grow, there is currently no system for assessing the vulnerability of essential elements that are necessary to keep rail transport safe and operational. Taking into account a number of criteria, the team of authors identified key elements of the railway transport infrastructure—bridges, tunnels, the width of the track, and the marshaling yard. The criteria applied included the significance and uniqueness of the element, its technical parameters, the difficulty of repair after possible damage, potential risks related to the location, and the analysis of rail safety based on statistical data and safety reports. The aim of this contribution is to present a multi-level model for assessing the vulnerability of key elements of rail transport infrastructure. The authors proceeded from the hypothesis that the vulnerability of key elements can be assessed using quantitative and qualitative parameters of the individual elements. The added value of the model is the methodological basis for a comprehensive vulnerability assessment system that will allow competent authorities to objectify the process of vulnerability assessment of key elements and to set up appropriate safeguards to enhance rail safety. The proposed model was verified on the Zilina-Vrútky track section, which is considered one of the most important railway junctions in Slovakia.
Longitudinal Associations of Perceived Social Inequality and Subjective Socioeconomic Status with Anxiety and Depression in University Students

Background: This study examined the longitudinal associations of perceived social inequality (PSI) and subjective socioeconomic status (SSS) with anxiety and depression. Methods: Data were collected across three time-points over a full semester in 2016 in South Korea. Participants completed an online self-report survey, and data from 247 participants were analyzed. Results: Older age was associated with lower PSI in treatment of women, and higher SSS was associated with lower overall PSI, particularly regarding the opportunity for advancement and law enforcement. Generalized estimating equation (GEE) analyses indicated that higher PSI was associated with clinical depression (OR=1.56) and lower SSS with clinical anxiety (OR=1.39) and depression (OR=1.38). Female students were also associated with clinical anxiety (OR=5.89) and depression at a marginally significant level (OR=1.93). Higher odds of anxiety were observed in students whose mothers have a high-school education as compared to those whose mothers have a university education or above (OR=2.29). Conclusions: Current results suggest the need to address the perceived social inequality and subjective socioeconomic status in the management of anxiety and depression in university students.
A Rapid Electrophoresis Method on Agarose Gel to Characterise Dairy Protein Aggregates

Heat treatment of milk may cause whey proteins and caseins to form aggregates. These soluble and micellar aggregates and their other properties (size, composition, shape, etc.) can affect the techno-functionalities to the milk, conferring interesting or negative features depending on the application in dairy industries. In this study, we propose a new approach to characterise those protein aggregates. SDS-agarose electrophoresis is followed by the calculation of a retention factor (Rf) for each protein spot. Rf allows milk aggregates to be compared qualitatively under the same conditions. This method could be transposed to the dairy industry for a better knowledge of the milk subsequent to heat treatment.
Spatial-spectral feature classification of hyperspectral image using a pretrained deep convolutional neural network

ABSTRACT Deep learning based methods have recently been successfully explored in hyperspectral image classification field. However, training a deep learning model still requires a large number of labeled samples, which is usually impractical in hyperspectral images. In this paper, a simple but effective feature extraction method is proposed for hyperspectral image classification. Specifically, a pretrained deep convolutional neural network based on the ImageNet dataset is used to extract spatial features of a hyperspectral image. Recently, it is easy to obtain a pretrained convolutional neural network on the Internet. Note that the pretrained models are trained by using the ImageNet dataset. This means that the proposed method does not need labeled hyperspectral samples to train the deep model. Therefore, the proposed method alleviates the problem of lacking labeled samples and avoids the artificial design of feature extraction rules. Finally, the extracted features are stacked with spectral features as the input of a support vector machine classifier. The proposed method is conducted on three widely used hyperspectral image datasets. The experimental results demonstrate that the proposed method could outperform the conventional feature extraction methods and deep learning based methods.
Elaboration par voie microfluidique de microcapsules monodisperses de verre de silice à caractéristiques morphologiques et optiques contrôlées

Les nanosciences representent, actuellement, un domaine de recherche en pleine expansion grâce aux nombreuses applications auxquelles elles peuvent etre associees, et en particulier a la course a la miniaturisation des systemes. De plus, il a rapidement ete montre que les proprietes physico-chimiques des materiaux a l’echelle nanometrique sont modifiees parfois de maniere drastique, a cause par exemple des effets quantiques apparaissant a des tailles aussi petites, mais aussi en raison des effets de confinement. Le confinement de molecules ou de particules a l’echelle nanoscopique necessite donc la fabrication de materiaux hotes possedant ce qu’il convient d’appeler des sites de confinement, c’est-a-dire des sites possedant une taille voisine de celle du systeme a inserer. Ce type de materiau est desormais relativement connu, et deux familles monopolisent l’interet, a savoir la silice mesoporeuse, aussi et recemment utilise, les verres bioactifs a base de silice ayant des caracteristiques controlees qui constituent des materiaux hotes de confinement qui peuvent etre immerges dans des fluides complexes tel que le plasma sanguin synthetique. Pour realiser ces travaux on a besoins d’appliquer plusieurs techniques de caracterisations telles que la diffusion des Rayons X et des Neutrons, la Microscopie Electronique a Balayage et a Transmission, la spectroscopie Infrarouge a Transforme de Fourier etc.De plus, ces dernieres annees, des systemes microfluidiques ont ete utilises pour elaborer des emulsions doubles, des microcapsules ou des microparticules, avec la particularite d’obtenir des populations tres monodisperses par rapport a celles obtenues avec des techniques plus traditionnelles et de morphologie controlee. Dans le domaine pharmaceutique, ces capacites sont particulierement interessantes pour la synthese de medicaments a liberation controlee. Elles permettent d’obtenir des particules monodisperses de polymere encapsulantes pour lesquelles l’effet de relargage brutal est diminue et qui possedent des vitesses de relargage plus lentes que celles observees avec des procedes de fabrication conventionnels.
The Role of Income and Property Taxes in Tax Transition and the Mediating Effect of Financial Development

This paper investigates second wave tax transition (transfer of tax pressure from border taxation towards domestic taxation) concerns in developing countries. It essentially focuses on the compensation effects of incomes and property taxes over international trade tax revenue losses in developing countries. Using a generalized method of moment estimator, we come to the evidence that, incomes and property taxes are poor instruments to balance trade tax revenue losses of trade liberalization in these countries. However, a mediating effect of financial development in the compensation nexus driven by corporate income taxes was found. We explain this result by the fact that the use of financial sector generates paper trails to government in order to enforce and raise corporate income taxes. Financial development may progressively crowd-out informal sector and leads to business formalization. Surprising, we do not find any mediating effect of financial development in the compensation patterns with personal income taxes. Nevertheless, some heterogeneities were discovered. Financial development mediates the compensation patterns of personal income taxes in Latin American countries, while the effect holds on corporate income taxes in African countries. We conclude the paper by highlighting the important role of financial development in second generation tax transition concerns over developing countries.
Rattle-Type Diamine-Functionalized Mesoporous Silica Sphere for Carbon Dioxide Adsorption

A rattle-type diamine-functionalized mesoporous silica sphere (DA-RMSS) was fabricated stepwise using a self-templating method through cationic surfactant assisted selective etching strategy. The rattle-type morphology of the obtained DA-RMSS material was disclosed by transmission electron microscopy, while its chemical composition was characterized by CHN elemental analysis, Fourier transform infrared spectroscopy, and solid-state 29Si cross-polarization/magic-angle-spinning nuclear magnetic resonance spectroscopic measurement, which corroborates the successful formation of siloxane network and the incorporation of organic component. Moreover, nitrogen adsorption–desorption isotherm measurement was conducted to reveal that DA-RMSS possesses large Brunauer–Emmett–Teller (BET) specific surface area of 814 m2g–1, pore volume of 0.78 cm3g–1, and narrow pore size distribution centered at 3.0 nm. Furthermore, its uptake property on carbon dioxide was also investigated in this contribution.
Experimental and Computational analysis of springback in dual phase steels

In this work the comfortability of dual-phase automotive steel DP600 is studied through uniaxial tensile tests and V-die bending tests in different directions relative to the rolling direction. A microstructural analysis was also carried out in each characteristic region of the deformation zone, evidencing the changes in the morphology of the microstructure grains. Additionally, the plastic anisotropy of the material was studied by implementing the constitutive anisotropy models known as Hill-48 and Barlat-89. The results showed an increase in elastic recovery at 45 ° and 90 ° from the rolling direction. This variation can be attributed to the morphology of the martensite that created preferential location zones within the material during the rolling process. The two models Hill-48 and Barlat-89 correctly describe the yield surface and the plastic anisotropy obtained in the experimental tests carried out. The simulation using the finite element method and the Hill-48 model gave satisfactory results in the prediction of the elastic recovery as compared to the experimental results obtained with the V-die bending test.
Acoustic Software Defined Platform: A Versatile Sensing and General Benchmarking Platform

Acoustic sensing has attracted significant attention recently, thanks to the pervasive availability of device support. However, adopting consumer-grade devices (e.g., smartphones) to deploy acoustic sensing applications faces the challenge of device/OS heterogeneity. Researchers have to pay tremendous efforts in tackling platform-dependent details even in simply accessing raw audio samples, thus losing focus on innovating sensing algorithms. To this end, this paper presents the first Acoustic Software Defined Platform (ASDP): a versatile sensing and general benchmarking platform. ASDP encompasses several customized acoustic modules running on a ubiquitous computing board, backed by a dedicated software framework. It is superior to commodity devices in controlling and reconfiguring physical layer settings, thus offering much better usability. The tailored software framework abstracts platform details and provides user-friendly interface for fast prototyping, while maintaining adequate programmability. To demonstrate the usefulness of ASDP, we showcase several relevant applications based on it. The promising outcomes make us believe that the release of our ASDP could greatly advance acoustic sensing research.