Miracle-dz/UniFAR-FTUs huggingface dataset:
SkinGest: artificial skin for gesture recognition via filmy stretchable strain sensors*

ABSTRACT Stretchable sensors are promising in the field of wearable robotics. To date, it is still a challenge to design an artificial skin with thin and sensitive stretchable sensors. In this paper, we present a new artificial skin, SkinGest, integrating filmy stretchable strain sensors and machine learning algorithms for gesture recognition of human hands. The presented sensor has a sandwich structure consisting of two elastomer layers on the outside and one soft electrode layer in the middle. Based on the improved fabrication process, we make the sensor’s thickness down to 150 µm, while keeping the gauge factor (GF) up to 8. Then, we integrate the machine learning algorithms (using LDA, KNN and SVM classifiers) with the stretchable sensors in our SkinGest system for gesture recognition. Supported by the experimental data from different subjects, our SkinGest system succeeds in identifying American sign language 0–9 with an average accuracy of 98%. The results demonstrate that the proposed SkinGest system provides a promising platform for future potential virtual reality and sign language recognition applications. GRAPHICAL ABSTRACT
Mapping the nanomechanical properties of graphene suspended on silica nanoparticles

ABSTRACT Using nanoparticles to impart extrinsic rippling in graphene is a relatively new method to induce strain and to tailor the properties of graphene. Here, we study the structure and elastic properties of graphene grown by chemical vapour deposition and transferred onto a continuous layer of SiO2 nanoparticles with diameters of around 25 nm, prepared by Langmuir–Blodgett technique on Si substrate. We show that the transferred graphene follows only roughly the morphology induced by nanoparticles. The graphene membrane parts bridging the nanoparticles are suspended and their adhesion to the atomic force microscope tip is larger compared to that of supported graphene parts. These suspended graphene regions can be deformed with forces of the order of 10 nN. The elastic modulus of graphene was determined from indentation measurements performed on suspended membrane regions with diameters in the 100 nm range.
Crowdsourcing StoryLines: Harnessing the Crowd for Causal Relation Annotation

This paper describes a crowdsourcing experiment on the annotation of plot-like structures in English news articles. CrowdThruth methodology and metrics have been applied to select valid annotations from the crowd. We further run an in-depth analysis of the annotated data by comparing them with available expert data. Our results show a valuable use of crowdsourcing annotations for such complex semantic tasks, and suggest a new annotation approach which combine crowd and experts.
Implementing an Interactive Reflection Model in EAP: Optimizing Student and Teacher Learning through Action Research

In this article, the authors, a teacher-researcher and an English Language Teaching (ELT) professor, report on a colloborative action research study which investigated how integrating systematic reflection into academic English courses at the tertiary level fostered both teacher and student learning. Using constructivist theory as a framework, they developed an interactive reflection model in which the students and teacher engage in a twoway process of reflection to improve their performance. Through reflective dialogue and reflective writing tasks, students explored their strengths and weaknesses in relation to the tasks they performed. Reflecting with students and on students’ reflections became a journey of discovery for the teacher-researcher and contributed to her professional development. Drawing on data from students’ oral and written reflective work, the teacher’s reflective journal and students’ evaluation of the effectiveness of the reflective tasks, the authors identify how adopting an interactive reflection model contributes to the learning process.
Measuring customer‐based brand equity: empirical evidence from the sportswear market in China

Purpose – This study seeks to examine the practicality and applications of a customer‐based brand equity model in the Chinese sportswear market.Design/methodology/approach – Based on Aaker's well‐known conceptual framework of brand equity, this study employed structural equation modeling to investigate the causal relationships among the four dimensions of brand equity and overall brand equity in the sportswear industry. The present study used a sample of 304 actual consumers from China's two largest cities, Beijing and Shanghai.Findings – The findings conclude that brand association and brand loyalty are influential dimensions of brand equity. Weak support was found for the perceived quality and brand awareness dimensions.Research limitations/implications – Future research needs to be done if the results are to be expanded into other regional Chinese markets in light of the significant gaps between different regions. Further research also could strengthen this analysis by adding performance measurement in.
Centennial to millennial geomagnetic secular variation

SUMMARY A time-varying spherical harmonic model of the palaeomagnetic field for 0‐7 ka is used to investigate large-scale global geomagnetic secular variation on centennial to millennial scales. We study dipole moment evolution over the past 7 kyr, and estimate its rate of change using the Gauss coefficients of degree 1 (dipole coefficients) from the CALS7K.2 field model and by two alternative methods that confirm the robustness of the predicted variations. All methods show substantial dipole moment variation on timescales ranging from centennial to millennial. The dipole moment from CALS7K.2 has the best resolution and is able to resolve the general decrease in dipole moment seen in historical observations since about 1830. The currently observed rate of dipole decay is underestimated by CALS7K.2, but is still not extraordinarily strong in comparison to the rates of change shown by the model over the whole 7 kyr interval. Truly continuous phases of dipole decrease or increase are decadal to centennial in length rather than longer-term features. The general large-scale secular variation shows substantial changes in power in higher spherical harmonic degrees on similar timescales to the dipole. Comparisons are made between statistical variations calculated directly from CALS7K.2 and longer-term palaeosecular variation models: CALS7K.2 has lower overall variance in the dipole and quadrupole terms, but exhibits an imbalance between dispersion in g 1 and h 1 , suggestive
The Solubility of Sulphur in Hydrous Rhyolitic Melts

Experiments performed at 2 kbar, in the temperature range 800–1000°C, with fO2 between NNO–2·3 and NNO+2·9 (where NNO is the nickel–nickel oxide buffer), and varying amounts of sulphur added to hydrous metaluminous rhyolite bulk compositions, were used to constrain the solubility of sulphur in rhyolite melts. The results show that fS2 exerts a dominant control on the sulphur solubility in hydrous silicate melts and that, depending on fO2, a rhyolitic melt can reach sulphur contents close to 1000 ppm at high fS2. At fO2 below NNO+1, the addition of iron to a sulphur-bearing rhyolite magma produces massive crystallization of pyrrhotite and does not enhance the sulphur solubility of the melt. For a given fO2, the melt-sulphur-content increases with fS2. For fixed fO2 and fS2, temperature exerts a positive control on sulphur solubilities, at least for fO2 below NNO+1. The mole fraction of dissolved sulphur exhibits essentially linear dependence on fH2S at low fO2 and, although the experimental evidence is less clear, on fSO2 at high fO2. The minimum in sulphur solubility corresponds to the redox range where both fH2S and fSO2 are approximately equal. A thermodynamic model of sulphur solubility in hydrous rhyolite melts is derived assuming that total dissolved sulphur results from the additive effects of H2S and SO2 dissolution reactions. The model reproduces well the minimum of sulphur solubility at around NNO+1, in addition to the variation of the sulphide to sulphate ratio with fO2. A simple empirical model of sulphur solubility in rhyolitic melts is derived, and shows good correspondence between model and observations for high-silica rhyolites.
The Middle-Income Trap: Issues for Members of the Association of Southeast Asian Nations

The problem faced by many of the economies making up the Association of Southeast Asian Nations (ASEAN) is whether they can avoid the middle-income trap and advance to the high-income level. What is needed for them to avoid the middle-income trap? This paper attempts to answer this question by building an analytical framework based on the factors that determine each development stage of an economy, and by comparing the current situation of four ASEAN middle-income countries with the experience of the Republic of Korea, a country that managed to overcome the middle-income trap and reach the high-income level in the late 1990s.
Regional dynamics of seasonal variability in the South China Sea

Abstract Dynamics of the seasonal cycle of sea surface height (SSH) in the South China Sea (SCS) are studied using observations as well as numerical and theoretical models. Seasonal variability of the SCS is interpreted in light of large-scale dynamics and Rossby waves. It is found that the seasonal cycle over most of the SCS basin is determined predominantly by the regional ocean dynamics within the SCS. The SSH variability is shown to be forced mainly by surface wind curl on baroclinic Rossby waves. Annual baroclinic Rossby waves cross the basin in less than a few months, leaving the upper ocean in a quasi-steady Sverdrup balance. An anomalous cyclonic (anticyclonic) gyre is generated in winter (summer) by the anomalous cyclonic (anticyclonic) wind curl that is associated with the northeasterly (southwesterly) monsoon. In addition, surface heat flux acts to enhance the wind-generated variability. The winter surface cooling (warming) cools (warms) the mixed layer especially in the central SCS, reducing (.
Understanding e-learning adoption in Brazil: Major determinants and gender effects

The objective of this study is to examine factors influencing e-learning adoption and the moderating role of gender. This study extends the technology acceptance model (TAM) by adding attitude and social interaction. The new construct of social interaction is applied to the South American context. Gender effects on e-learning adoption from educators’ perspectives have seldom been explored. The data collection takes place in three major Brazilian universities. In total, 446 faculty members responded to the questionnaire. Our structural equation modeling reveals that ease of use and perceived usefulness are significant antecedents of attitude, which in turn affects intention. However, unlike the original TAM, perceived usefulness is not a direct driver of intention. In terms of moderation, gender affects three relationships: (1) ease of use –› perceived usefulness; (2) perceived usefulness –› attitude, and (3) intention –› actual behavior. The analysis is carried out in a single country; thus, caution should be taken in generalization of the results. The findings will help academics, educators, and policy makers to better understand the mechanism of e-learning adoption in Brazil.
The determination of short circuits and grounding faults in electric power systems using time-frequency analysis

In order to ensure that electrical energy reaches consumers uninterrupted, researchers constantly try to improve power transmission lines. To realize this improvement, probable faults should be analysed through every known method, and new methods should also be implemented. In this study, firstly, the Keban power transmission line located in the Eastern Anatolia region of Turkey was modelled. After that, probable short circuit scenarios were applied on the model, and the short circuit faults in the scenarios were analysed by using the Fourier analysis. The Fourier analysis is a mathematical method that is used as an effective way to determine the sudden changes in the frequency and time band. The study was successful in determining phase and grounding faults through the analyses of the scenarios using Fourier analysis. The fact that the mathematical method was applied on the probable scenarios on a physical model increases the importance of the study.
Bidirectional LSTM-CNNs-CRF Models for POS Tagging

In order to achieve state-of-the-art performance for part-of-speech(POS) tagging, the traditional systems require a significant amount of hand-crafted features and data pre-processing. In this thesis, we present a discriminative word embedding, character embedding and byte pair encoding (BPE) hybrid neural network architecture to implement a true end-to-end system without feature engineering and data pre-processing. The neural network architecture is a combination of bidirectional LSTM, CNNs, and CRF, which can achieve a state-of-the-art performance for a wide range of sequence labelling tasks. We evaluate our model on Universal Dependencies (UD) dataset for English, Spanish, and German POS tagging. It outperforms other models with 95.1%, 98.15%, and 93.43% accuracy on testing datasets respectively. Moreover, the largest improvements of our model appear on out-of-vocabulary corpora for Spanish and German. According to statistical significance testing, the improvements of English on testing and out-of-vocabulary corpora are not statistically significant. However, the improvements of the other more morphological languages are statistically significant on their corresponding corpora.
The Effects of Holistic Defense on Criminal Justice Outcomes

Debates over mass incarceration emphasize policing, bail, and sentencing reform, but give little attention to indigent defense. This omission seems surprising, given that interactions with government-provided counsel critically shape the experience of the vast majority of criminal defendants. This neglect in part reflects our lack of evidence-based knowledge regarding indigent defense, making it difficult to identify effective reforms. One newer model gaining support is the holistic defense model, in which public defenders work in interdisciplinary teams to address both the immediate case and the underlying life circumstances--such as drug addiction, mental illness, or family or housing instability--that contribute to client contact with the criminal justice system. This holistic model contrasts with the traditional public defense model which emphasizes criminal representation and courtroom advocacy. Proponents contend holistic defense improves case outcomes and reduces recidivism by better addressing clients’ underlying needs, while critics argue that diverting resources and attention from criminal advocacy weakens results. Although widely embraced, there is no systematic evidence demonstrating the relative merits of the holistic approach. This Article offers the first large-scale, rigorous evaluation of the impact of holistic representation on criminal justice outcomes. In the Bronx, a holistic defense provider (the Bronx Defenders) and a traditional defender (the Legal Aid Society) operate side-by-side within the same court system, with case assignment determined quasi-randomly based on court shift timing. Using administrative data covering over half a million cases and a quasi-experimental research design, we estimate the causal effect of holistic representation on case outcomes and future offending. Holistic representation does not affect conviction rates, but it reduces the likelihood of a custodial sentence by 16% and expected sentence length by 24%. Over the ten-year study period, holistic representation in the Bronx resulted in nearly 1.1 million fewer days of custodial punishment. As of one year post-arraignment and beyond, holistic representation has neither a positive or adverse effect on criminal justice contacts. While holistic representation does not dramatically reduce recidivism, as some proponents have claimed, strengthening indigent defense apparently offers considerable potential to reduce incarceration without harming public safety. Indigent defense thus deserves a more prominent place in conversations about how to address mass incarceration, and future research should examine the effects of this promising model beyond the criminal justice system and in other jurisdictions.
Using High‐Resolution Data to Assess Land Use Impact on Nitrate Dynamics in East African Tropical Montane Catchments

Land use change alters nitrate (NO3‐N) dynamics in stream water by changing nitrogen cycling, nutrient inputs, uptake and hydrological flow paths. There is little empirical evidence of these processes for East Africa. We collected a unique 2 year high‐resolution data set to assess the effects of land use (i.e., natural forest, smallholder agriculture and commercial tea plantations) on NO3‐N dynamics in three subcatchments within a headwater catchment in the Mau Forest Complex, Kenya's largest tropical montane forest. The natural forest subcatchment had the lowest NO3‐N concentrations (0.44 ± 0.043 mg N L−1) with no seasonal variation. NO3‐N concentrations in the smallholder agriculture (1.09 ± 0.11 mg N L−1) and tea plantation (2.13 ± 0.19 mg N L−1) subcatchments closely followed discharge patterns, indicating mobilization of NO3‐N during the rainy seasons. Hysteresis patterns of rainfall events indicate a shift from subsurface flow in the natural forest to surface runoff in agricultural subcatchments. Distinct peaks in NO3‐N concentrations were observed during rainfall events after a longer dry period in the forest and tea subcatchments. The high‐resolution data set enabled us to identify differences in NO3‐N transport of catchments under different land use, such as enhanced NO3‐N inputs to the stream during the rainy season and higher annual export in agricultural subcatchments (4.9 ± 0.3 to 12.0 ± 0.8 kg N ha−1 yr−1) than in natural forest (2.6 ± 0.2 kg N ha−1 yr−1). This emphasizes the usefulness of our monitoring approach to improve the understanding of land use effects on riverine N exports in tropical landscapes, but also the need to apply such methods in other regions.
ON THE ERGODIC MIXING THEOREM

or what is equivalent, if for k in the complement of a set of density 0, m(E O T~*F)-> m(£)m(F), for each pair of measurable sets E, F. (The so-called mixing theorem of ergodic theory (see Halmos [5, p. 39] ) establishes the equivalence of (1.1) and each of the following two conditions: first, that the unitary operator l/r on L2 (T, S, m) induced by T has continuous spectrum on the subspace of L2 orthogonal to the constant functions; and second, that the Cartesian square T x T on the product space (T x T, S x S, m x m) is ergodic. This theorem appeared early in the modern development of ergodic theory, in works of von Neumann and Hopf, and unlike most of these early results, it appears to have resisted subsequent generalization. For example, no variant of the theorem seems to be known in case the measure-preserving transformation Tis noninvertible. In this situation the induced operator UT is, in general, a nonunitary isometry, to which ordinary spectral theory does not apply. In this note we prove an abstract mixing theorem in a setting considerably more general than the above. In place of the semigroup of non-negative integers we consider an arbitrary topological semigroup G which admits both a leftinvariant and a right-invariant Banach mean. This includes all abelian or compact topological semigroups, and an extensive class of discrete semigroups (see Day [1]). And, in place of the operator UT, we consider an arbitrary weakly continuous isometric representation Ux of G on a complex Hubert space. The operation lim (1 /n) 1Z"Zo is supplanted by "almost convergence," a notion introduced by G. Lorentz [6], and in turn, the condition that UT have continuous spectrum is supplanted by the condition that the representation Ux have no finite-dimensional subrepresentations. The abstract mixing theorem (proved in §3) specializes in the measure-theoretic case to a direct generalization of the classical mixing theorem (see §4). Our proof is quite elementary, consisting of a refinement for amenable semigroups of the traditional Peter-Weyl theory.
Self-Funded Social Impact Investment: An Interdisciplinary Analysis of the Sardex Mutual Credit System

ABSTRACT Sardex is a B2B electronic complementary currency and mutual credit system. It allows private funding to be endogenously generated within a geographically limited socio-economic context, rather than injected from exogenous sources, leading to a greater level of positive social impact. Sardex promotes stable and constructive integration of market activity with democratic institutions and socio-cultural values, and is hence identified with sustainable development. This paper presents a case study based on 29 semi-structured in-depth interviews of Sardex members. By drawing on monetary theory, sociology and anthropology, the paper argues that Sardex implements a form of self-funded social impact investment.
The Impact of Rewards and Motivation on Job Satisfaction in Water Utility Industry

This study aimed to examine the impacts of rewards and motivation on job satisfaction between public and private water utility organization in Malaysia using Perceived Amount of Rewards, WPI and JSS models. A total of 689 employees from both sectors participated in this study. Regression analysis was conducted to test the relationship between rewards, motivation and job satisfaction, while gap analysis was utilized to determine the significant differences on the level of rewards, motivation and job satisfaction between both sectors. The findings indicated that (1) rewards have a positive significant influenced on motivation; (2) motivation significantly positively influenced employees’ job satisfaction and (3) rewards have a positive significantly influenced on job satisfaction. The t-test result revealed that public water utility organization showed significantly higher on the levels of rewards, motivation and job satisfaction.
Simplifying Stochastic Mathematical Models of Biochemical Systems

Stochastic modeling of biochemical reactions taking place at the cellular level has become the subject of intense research in recent years. Molecular interactions in a single cell exhibit random fluctuations. These fluctuations may be significant when small populations of some reacting species are present and then a stochastic description of the cellular dynamics is required. Often, the biochemically reacting systems encountered in applications consist of many species interacting through many reaction channels. Also, the dynamics of such systems is typically non-linear and presents multiple time-scales. Consequently, the stochastic mathematical models of biochemical systems can be quite complex and their analysis challenging. In this paper, we present a method to reduce a stochastic continuous model of well-stirred biochemical systems, the Chemical Langevin Equation, while preserving the overall behavior of the system. Several tests of our method on models of practical interest gave excellent results.