Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Change, Balance of Payments Constraint, and Economic Growth: Evidence from Vietnam

The impact of demand-side factors and rapid structural changes have largely been ignored in explaining the economic growth of Vietnam. This paper employs the multisectoral balance-of-payments constrained economic growth model to capture the influence of structural changes on the exports and economic growth of Vietnam over the period 1997–2016. Based on the estimates for the sectoral income elasticities of demand for exports and imports obtained from autoregressive distributed lag models, this paper argues that it is not relative prices but income that has played a significant role in Vietnam’s economic growth, the income elasticities of demand for exports have grown faster than those of demand for imports, and the weight of exports has significantly moved from primary to high-technology products. JEL Classification: E12, F43, O53
Sistemas de equações utilizados na construção de diagramas de manejo da densidade de povoamentos de teca

The aim objective of study was to evaluate the system of equations used at the construction of density management diagrams. The data was collected at clonal stands of teak in the southern-central region of Mato Grosso state, Brazil. The ages of the stand varied between one and eight years, where the measures were taken in circular plots. The plots had areas varying from 359 to 616 m 2 . The diameter at breast height and total height were measured from the trees that composed the plots. The volume was calculated in 827 trees by the Smalian’s method. Two systems of equation were used to carry this study out and the evaluation of the fit was made by the statistics: root mean square error (RMSE), percentage of root mean square error (RMSE (%)), coefficient of determination (R 2 ) represented by the squared correlation coefficient ( ), residuals in the percentage scale (residual (%)), and graphical analysis of the parameter fittings. The system of equation that obtain the best results was the proposed by Dean and Baldwin, with the statistic R 2 between 0,9942 - 0,9994, and RMSE (%) 2,88 - 1,84, regarding the other system that presented 0,9558 - 0,9539 and 13,94 -7,99 to the statistics R 2 and RMSE (%), respectively. The distribution of residues from the Dean and Baldwin system were also superior, corroborating the results of the statistical analyzes. The results of this work allow us to infer that the system of equations proposed by Dean and Baldwin is more accurate, and, therefore, the one indicated in the development of population density management diagrams in clonal teak stands.
Self‐Programming Synaptic Resistor Circuit for Intelligent Systems

Unlike artificial intelligent systems based on computers which have to be programmed for specific tasks, the human brain “self‐programs” in real time to create new tactics and adapt to arbitrary environments. Computers embedded in artificial intelligent systems execute arbitrary signal‐processing algorithms to outperform humans at specific tasks, but without the real‐time self‐programming functionality, they are preprogrammed by humans, fail in unpredictable environments beyond their preprogrammed domains, and lack general intelligence in arbitrary environments. Herein, a synaptic resistor circuit that self‐programs in arbitrary and unpredictable environments in real time is demonstrated. By integrating the synaptic signal processing, memory, and correlative learning functions in each synaptic resistor, the synaptic resistor circuit processes signals and self‐programs the circuit concurrently in real time with an energy efficiency about six orders higher than those of computers. In comparison with humans and a preprogrammed computer, the self‐programming synaptic resistor circuit dynamically modifies its algorithm to control a morphing wing in an unpredictable aerodynamic environment to improve its performance function with superior self‐programming speeds and accuracy. The synaptic resistor circuits potentially circumvent the fundamental limitations of computers, leading to a new intelligent platform with real‐time self‐programming functionality for artificial general intelligence.
On Channel Estimation in LTE-Based Downlink Narrowband Internet of Things Systems

Narrowband Internet of Things (NB-IoT) systems were specified by 3GPP in release 13 as a low power wide area network (LPWAN) technology to operate with a very narrow bandwidth of 180 kHz only. Due to fragile radio signal operating conditions (where a signal is weaker than noise), NB-IoT channel status becomes highly complex. Therefore, an effective and low complexity channel estimation will perform a significant role in the receiver operation. The linear minimum mean square error (LMMSE) scheme is very effective in estimating the channel but introduces massive complexity because of having complex matrix inversion. In this paper, we first derive the analytical model of the signal for long-term evolution (LTE)-based NB-IoT downlink systems and propose a reduced complexity LMMSE channel estimation for the downlink NB-IoT systems by applying singular value decomposition (SVD) technique along with partitioning the whole channel matrix into small submatrices. Furthermore, we apply the overlap banded technique to optimize the performance of the proposed channel estimator. As a result of exploiting several submatrices instead of a larger channel matrix, the operational complexity is significantly optimized. Lastly, we propose a polyphase filter structure for implementing the interpolation procedure instead of the conventional interpolation method to further optimize the performance and complexity of the proposed channel estimator further. The performance of the proposed technique has been justified by the mean square error (MSE), bit error rate (BER), and instantaneous throughput for the related signal-to-noise ratio (SNR). The system complexity is verified by the number of complex multiplications used. Simulation evaluations indicate that with the sacrifice of negligible performance, the proposed modified LMMSE technique along with the proposed interpolation possesses a good balance between the performance and the system complexity that could help the proposed techniques to be applied successfully in the low complexity NB-IoT systems.
When less is more: HRM implementation, legitimacy and decoupling

The implementation of human resource (HR) policies often proves troublesome due to the appearance, and stubborn persistence, of gaps in the process. Human resource management (HRM) scholars problematise these gaps and advocate tight implementation to reduce gaps and to ensure the desired impact of policies on organisational performance. Drawing on organisational institutionalism, we contend that gaps in implementing HR policies can actually be productive, as they secure organisational legitimacy, and thus enable organisations to operate viably within several institutional environments. We suggest that different approaches to implementation are needed, some of them premised on accepting sustained implementation gaps. We introduce minimum and moderate implementation approaches, rooted in the notion of decoupling, to complement approaches aimed at tight implementation. Our aim is to support the further development of research based on a richer interpretation of HRM implementation challenges and choices they present for HR managers.
Cartesian Mesh Generation with Local Refinement for Immersed Boundary Approaches

In this paper, an efficient and robust Cartesian Mesh Generation with Local Refinement for an Immersed Boundary Approach is proposed, whose key feature is the capability of high Reynolds number simulations by the use of wall function models, bypassing the need for accurate boundary layer discretization. Starting from the discrete manifold model of the object to be analyzed, the proposed model generates Cartesian adaptive grids for a CFD simulation, with minimal user interactions; the most innovative aspect of this approach is that the automatic generation is based on the segmentation of the surfaces enveloping the object to be analyzed. The aim of this paper is to show that this automatic workflow is robust and enables to get quantitative results on geometrically complex configurations such as marine vehicles. To this purpose, the proposed methodology has been applied to the simulation of the flow past a BB2 submarine, discretized by non-uniform grid density. The obtained results are comparable with those obtained by classical body-fitted approaches but with a significant reduction of the time required for the mesh generation.
Morphology regulation of nanowire forests for tumour‐cell behaviours

Three-dimensional nanowire arrays based on different biomaterials have emerged as promising platforms for the studies of cell behaviours over the years. Fabrication of nanosurfaces with complex geometries and controllable morphologies is still a challenge. In this work, nanowire forests (NWFs), which exhibited various aspect ratios, were fabricated using a reactive ion etching technique. Especially, by regulating bombardment periods of oxygen and argon plasma, the aspect ratio of nanowires in NWFs could be decreased from 29:1 to 7:1. Based on superhydrophilicity of the NWFs, the interaction between the NWFs with various aspect ratios and HeLa cells (human cervical carcinoma cell line) after different culturing periods was systematically investigated. NWFs with a low aspect ratio provide appropriate nanosubstrates for the cells, enabling them to grow on and adhere to the surface. NWFs with a high aspect ratio exhibited low mechanical strength under initial cell adhesion, which further hindered cell growth and migration as the incubation time increased. These ﬁndings provide essential guidance in designing nanostructure geometries for more efﬁcient capture of circulating tumour cells and manipulation of cytomorphology in future.
Exploring the profiles of pre-service teachers technological pedagogical content knowledge (TPACK) on earth and space science offline and online course

This study reveals the comparison of the TPACK profiles of pre-service elementary school teachers in the Earth and Space Science (ESS) offline and online lectures. The sample consisted of 97 students who took offline lectures in the 2018/2019 academic year and 85 students who took online lectures in the 2019/2020 academic year. The research instrument consisted of 38 questionnaire items that assessed the self-efficacy of the TPACK-21 components. The correlation analysis results show that in all aspects of basic knowledge and secondary knowledge, ESS online courses provide better results in developing TPACK abilities than offline courses. However, the SEM analysis results show that the structure of the TPACK ability development model in the offline class appears to be more stable than the online class. This indicates a need for further development in online learning strategies and approaches to lead to a more significant contribution to the development of TPACK.
Flipped Classroom Among Minorities in the Context of Mathematics Learning: The Israeli Case

This study presents a designated Flipped Classroom (FC) mathematics environment that utilizes a unique online platform designed for Arab minority students in Israel. It investigates how studying in an FC affects conceptual understanding and motivation to study mathematics among Arab high school students. The study also explores the factors that contribute to effective learning in the FC environment. Participants were 75 Arab high school students in 10th and 11th grade who studied advanced mathematics. Each grade group was randomly divided into two subgroups: an FC group and a traditional classroom group (comparison group). Quantitative questionnaires given before and after the learning program served to measure students’ motivation and conceptual understanding of the derivative and integral topics. Additionally, a random sample of students who studied in the FC group and the teacher who taught all the groups were interviewed. The study describes the positive effect an FC environment has on students' conceptual understanding, particularly for 11th graders. The participants mostly appreciated how the FC resulted in less lecturing in class. The study contributes to the literature about FC among minorities and contributes to national and international efforts being made to reduce the gap in mathematics achievements between minorities and other sectors.
Mammal and bird species ranges overlap with armed conflicts and associated conservation threats

Armed conflicts are a pervasive global threat, but their implications for wildlife conservation remain unclear. Using a 30‐year spatial dataset of armed conflicts in conjunction with species range maps, we found that conflicts during 1989–2018 occurred within at least 4291 (78%) and 9056 (85%) terrestrial mammal and bird species ranges, respectively. For 4% overall and 5–7% of threatened species, conflicts within ranges have been both widespread (≥50% of range) and frequent (≥15 years). Further, an examination of International Union for Conservation of Nature Red List assessments revealed that ranges overlap with armed conflicts is associated with declining population trends of threatened species and distinct species threat portfolios in which hunting and habitat loss and degradation are more prominent. Our findings call for greater recognition and understanding of direct and indirect threats from armed conflicts in species conservation assessments and underscore the importance of addressing conflict resiliency in conservation plans for a wide suite of species.
Shape transformation of Ag nanospheres to triangular Ag nanoplates: Hydrogen peroxide is a magic reagent

ABSTRACT Triangular Ag nanoplates were prepared using AgNO3, PVP, NaBH4, Na3CA and H2O2 as reagents. The obtained triangular Ag NPs were characterized by transmission electron microscopy and UV-visible spectrophotometer. TEM results showed that, the edge lengths of triangular Ag NPs were in the range of 35–95 nm. The thicknesses were about 5 nm. In addition, not only the edge lengths, but the thicknesses of triangular Ag NPs became larger after H2O2 was injected without stir. Larger red-shifts in UV-visible adsorption spectra were also observed due to a formation of larger triangular Ag NPs. Oxidative dissolution and the mild reducing action of H2O2 under alkaline conditions served as the principal reactions for the shape transformation of Ag nanospheres to triangular Ag NPs.
Sensitivity Study on the Correlation Level of Seismic Failures in Seismic Probabilistic Safety Assessments

It is popular that correlated seismic failures spread over the fault tree of a seismic probabilistic safety assessment (PSA) for a nuclear power plant (NPP). To avoid the calculational difficulty of core damage frequency (CDF), the fault tree has been simplified by replacing correlated seismic failures with one typical seismic failure by assuming a full correlation among the correlated seismic failures. Then, the approximate seismic CDF of a seismic single-unit PSA (SUPSA) has been calculated for decades with this simplified SUPSA fault tree. Furthermore, current seismic multi-unit PSAs (MUPSAs) have been performed with imperfect seismic MUPSA models that were generated by combining such imperfect seismic SUPSA fault trees. The authors of this study recently developed a method that can calculate an accurate seismic CDF by converting correlated seismic failures into seismic common cause failures (CCFs). In this study, accurate and imperfect MUPSA models were created and their seismic CDFs were compared. The results of this study show that the seismic CDFs in SUPSA and MUPSA are drastically distorted and safety margins are accordingly distorted when the full correlation assumption is employed. Thus, this study shows that very careful attention should be paid to calculating and interpreting seismic CDFs for the single-unit and multi-unit NPP regulations.
Roughness of Fracture Surfaces in Numerical Models and Laboratory Experiments

Abstract. We investigate the influence of stress conditions during fracture formation on the geometry and roughness of fracture surfaces. Rough fracture surfaces have been generated in numerical simulations of triaxial deformation experiments using the Discrete Element Method and in laboratory experiments on limestone and sandstone samples. Digital surface models of the rock samples fractured in the laboratory experiments were produced using high resolution photogrammetry. The roughness of the surfaces was analyzed in terms of absolute roughness measures such as an estimated joint roughness coefficient (JRC) and in terms of its scaling properties. The results show that all analyzed surfaces are self-affine, but with different Hurst exponents between the numerical models and the real rock samples. Results from numerical simulations using a wide range of stress conditions to generate the fracture surfaces show a weak decrease of the Hurst exponents with increasing confining stress and a larger absolute roughness for transversely isotropic stress conditions compared to true triaxial conditions. Other than that, our results suggest that stress conditions have little influence on the surface roughness of newly formed fractures.
‘Education without limits’: The digital resettlement of post-secondary education and training in Singapore in the COVID-19 era

ABSTRACT This article reports on how those working in post-secondary education and training in Singapore perceive the professional effects of a transition to online learning, teaching and assessment (LTA) as a consequence of the COVID-19 global pandemic. It draws on a survey sample of n = 1553 educators and trainers working in Singapore and their perspectives on how a migration to online LTA is producing long-term, if not permanent, changes to the organisation and delivery of post-secondary education and training. It reveals a largely positive view of digital resettlement of education and training in Singapore as a consequence of COVID-19. Yet despite the articulation by respondents of ‘paradigm change’ and ‘education without limits’, we find that an embrace of digitalisation is mobilised (and manipulated) not so much by pedagogical concerns but by economic ambitions and a utilitarian logic common to the neoliberal incantations of a global education policy community.
sEMG-Based Continuous Estimation of Finger Kinematics via Large-Scale Temporal Convolutional Network

Since continuous motion control can provide a more natural, fast and accurate man–machine interface than that of discrete motion control, it has been widely used in human–robot cooperation (HRC). Among various biological signals, the surface electromyogram (sEMG)—the signal of actions potential superimposed on the surface of the skin containing the temporal and spatial information—is one of the best signals with which to extract human motion intentions. However, most of the current sEMG control methods can only perform discrete motion estimation, and thus fail to meet the requirements of continuous motion estimation. In this paper, we propose a novel method that applies a temporal convolutional network (TCN) to sEMG-based continuous estimation. After analyzing the relationship between the convolutional kernel’s size and the lengths of atomic segments (defined in this paper), we propose a large-scale temporal convolutional network (LS-TCN) to overcome the TCN’s problem: that it is difficult to fully extract the sEMG’s temporal features. When applying our proposed LS-TCN with a convolutional kernel size of 1 × 31 to continuously estimate the angles of the 10 main joints of fingers (based on the public dataset Ninapro), it can achieve a precision rate of 71.6%. Compared with TCN (kernel size of 1 × 3), LS-TCN (kernel size of 1 × 31) improves the precision rate by 6.6%.
Resource Scarcity and Sustainability—The Shapes Have Shifted but the Stakes Keep Rising

The objective is to provide an interpretive reading of the literature in resource scarcity and sustainability theory from the nineteenth century to the present time, focusing on shifts that have occurred in problem definition, conceptual framing, research tools applied, findings, and their implications. My reading shows, as one would expect, that the discourse has become more technical and the analysis more sophisticated; special cases have been incorporated into the mainstream of theory; and, where relevant, dynamic formulations have largely supplanted static analysis. However, that is barely scratching the surface. Here, I focus on more fundamental shifts. Exhaustible and renewable resource analyses were incorporated into the mainstream theory of financial and capital markets. Parallels between the resources and environmental spheres were discovered: market failure concepts, fundamental to environmental policy, found applications in the resources sector (e.g., fisheries), and renewable resource management concepts and approaches (e.g., waste assimilation capacity) were adopted in environmental policy. To motivate sustainability theory and assessment, there has been a foundational problem shift from restraining human greed to dealing with risk viewed as chance of harm, and a newfound willingness to look beyond stochastic risk to uncertainty, ambiguity, and gross ignorance. Newtonian dynamics, which seeks a stable equilibrium following a shock, gave way to a new dynamics of complexity that valued resilience in the face of shocks, warned of potential for regime shifts, and focused on the possibility of systemic collapse and recovery, perhaps incomplete. New concepts of sustainability (a safe minimum standard of conservation, the precautionary principle, and planetary boundaries) emerged, along with hybrid approaches such as WS-plus which treats weak sustainability (WS) as the default but may impose strong sustainability restrictions on a few essential but threatened resources. The strong sustainability objective has evolved from maintaining baseline flows of resource services to safety defined as minimizing the chance of irreversible collapse. New tools for management and policy (sustainability indicators and downscaled planetary boundaries) have proliferated, and still struggle to keep up with the emerging understanding of complex systems.
Measuring and Evaluating the Visual Complexity Of Chinese Ink Paintings

Painters arrange white space in contrast with chromatic space composed of strokes. This research measures white space, color complexity and stroke density in Chinese ink paintings and examines how these attributes influence the paintings’ perceived complexity. Empirical evidence from 21 well-known modern Chinese artists’ ink paintings shows that white space decreases paintings’ complexity, while chromatic space and stroke density increase complexity. We also reveal that a large rate of white space guides the viewers’ attention on chromatic space and enhances the impacts of color complexity and stroke density on perceived complexity. An eye-tracker measures viewers’ elaboration duration on each painting, which provides consistent evidence to validate our conclusion based on subjective reported visual complexity. Our research provides insights into the rhetorical role of white space in sensory information processing.