Miracle-dz/UniFAR-FTUs huggingface dataset:
Mental Toughness Measurement for Psychological Skills Training Intervention, Translation and Adaptation

JAMATUL SHAHIDAH SHAARI, LIM BOON HOOI, JAMILAH AHMAD RADZI, SİSWANTOYO, SRI SUMARTININGGSIH & NOR EEZA ZAINAL ABIDIN Faculy of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam 2,6 Centre for Sport and Exercise Sciences, University of Malaya, Malaysia Fculty of Sports Science and Recreation, Universiti Teknologi MARA, Perlis Sport Science Faculty, Yogyakarta State University, Indonesia Faculty of Sport Science, Universitas Negeri Semarang, Indonesia ABSTRACT
Detection of morphed faces from single images: a multi-algorithm fusion approach

The vulnerability of face, fingerprint and iris recognition systems to attacks based on morphed biometric samples has been established in the recent past. However, so far a reliable detection of morphed biometric samples has remained an unsolved research challenge. In this work, we propose the first multi-algorithm fusion approach to detect morphed facial images. The FRGCv2 face database is used to create a set of 4,808 morphed and 2,210 bona fide face images which are divided into a training and test set. From a single cropped facial image features are extracted using four types of complementary feature extraction algorithms, including texture descriptors, keypoint extractors, gradient estimators and a deep learning-based method. By performing a score-level fusion of comparison scores obtained by four different types of feature extractors, a detection equal error rate (D-EER) of 2.8% is achieved. Compared to the best single algorithm approach achieving a D-EER of 5.5%, the D-EER of the proposed multi-algorithm fusion system is almost twice as low, confirming the soundness of the presented approach.
Exploring the Impact of Job Satisfaction Domains on Firm Performance: Evidence from Great Britain

Firm productivity and performance and their determinants are a well addressed topic in the field of management and industrial organization. However, how different job satisfaction domains affect the firm performance remains relatively rare. The aim of this study is to explore the impact of seven job satisfaction domains on firm performance. The analysis relies on firm-level data derived from the Workforce Employment Relations Survey (WERS) in 2004 and 2011 in Great Britain. To reduce the endogeneity issue coming from possible reverse causality between the job satisfaction and firm performance we apply the Two Stage Least Squares (2SLS) method. The findings show that satisfaction with job security and the work itself have the strongest positive impact followed by training, income and sense of achievement. The findings provide valuable insights to firms and managers about the identification of the most important job satisfaction domains affecting firm performance, varying by the industry, firm type and workplace management. This is especially the case in the post-crisis period of 2007, where working conditions have experienced major changes, and will experience further changes and new challenges due to the COVID-19 pandemic.
Physical constraints in the deep hypolimnion of a subalpine lake driving planktonic Bacteria and Archaea distribution

The study of the hydrodynamics of the hypolimnion of a deep holo-oligomictic lake (Lake Maggiore, Northern Italy, zmax¼370 m) during the last 28 years showed that hypolimnetic waters remained isolated, not exchanging with the mixing zone even in winter when the full overturn conditions are most likely. The thickness of the isolated layer can range from 100 to 300 m. Thus, water masses of variable size reside in the lake for many years, and their physical and chemical conditions remain relatively unaffected by seasonal variability and epilimnetic imputs. In the hypolimnetic waters prokaryote abundance is three times lower than in the mixing layer but cell size is significantly higher. In addition, the relative abundance of Archaea and Crenarchaeota increases with depth in respect to that of Bacteria. The heterogeneous distribution of the two domains within the habitat can be attributed to the existence in the same environment of isolated water masses.
The Relationship between Health Care Spending, Gross Domestic Product, GDP per Capita and Economic Growth in Iran

This paper examines causal relationship between Health expenditure and GDP for Iran using annual data over the period 1970-2008. The Gregory-Hansen (1996) cointegration technique, allowing for the presence of potential structural breaks in data, is applied to empirically examine the long-run co-movement between health spending and output. The results suggest that there is a long-run relationship between these variables and the income elasticity for health care spending is greater than one during the period after Islamic Revolution (1979-2008). The Granger Causality test indicates a strong unidirectional effect from GDP to health expenditure, although providing no support to the view that health expenditure promotes long-term economic growth. The evidence for Iran clearly supports the ‘Income View’ over the ‘Health View’.
Soil searching by an arti cial root

We model an arti cial root which grows in the soil for underground prospecting. Its evolution is described by a controlled system of two integro-partial di erential equations: one for the growth of the body and the other for the elongation of the tip. At any given time, the angular velocity of the root is obtained by solving a minimization problem with state constraints. We prove the existence of solutions to the evolution problem, up to the rst time where a "breakdown con guration" is reached. Some numerical simulations are performed, to test the e ectiveness of our feedback control algorithm.
Environmental control of land-atmosphere CO2 fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types

Abstract We assembled homogenized long-term time series, up to 19 years, of measurements of net ecosystem exchange of CO2 (NEE) and its partitioning between gross primary production (GPP) and respiration (Reco) for five different ecosystems representing the main plant functional types (PFTs) in France. Part of these data was analyzed to determine the influence of the main environmental variables on carbon fluxes between temperate ecosystems and the atmosphere, and to investigate the temporal patterns of their variations. A multi-temporal statistical analysis of the time series was conducted using random forest (RF) and wavelet coherence approaches. The RF analysis showed that, in all ecosystems, the incident solar radiation was highly correlated with GPP and that GPP was better correlated with the temporal variations of NEE than Reco. The air temperature was the second most important driver in ecosystems with seasonal foliage, i.e., deciduous forest, cropland and grassland; whereas variables related to air or soil drought were prominent in evergreen forest sites. The environmental control on CO2 fluxes was tighter at high frequency suggesting an increased resilience to environmental variations at longer time spans. The spectral analysis performed on three of the five sites selected revealed contrasting temporal patterns of the cross-coherence between CO2 fluxes and climate variables among ecosystems; these were related to the respective PFT, management and soil conditions. In all PFTs, the power spectrum of GPP was well correlated with NEE and clearly different from Reco. The spectral correlation analysis showed that the canopy phenology and disturbance regime condition the spectral correlation patterns of GPP and Reco with the soil moisture and atmospheric vapour deficit.
Sentiment Analysis of Twitter Data Using Machine Learning Algorithms

— In the current era, opinions and ideologies of people are often expressed through the internet via sites like social media sites, micro blogging sites, etc. Sentimental analysis, a part of text mining is used classify these opinions or sentiments in a positive, negative or neutral manner. For this particular work, the sentiments of the tweets or reviews published in the twitter is identified by specific keywords in tweets. They tweets are then classified as to whether they have a positive or a negative outlook. The sentiments of the tweets are based on a specific selection of tweets. In this paper, we will check the accuracy of different fields such as precision, accuracy, etc, with three machine learning classifiers, namely, Random Forest, Naive Bayes and Support Vector Machine(SVM).
The Relationship between Resource Configuration and the Type of Diversification—Take the Largest Corporations in Taiwan as Examples

It is important for an organization to recognize the importance of resource mobilization in formulating development strategies. The type of resources acquired by an organization also determines entering a new business territory. The previous study on this subject matter has often focused on the characteristics of one particular type of resources. This approach can construct a theoretical model with simplicity. However, it is debatable whether a single type of resources plays a key role in the decision process of development strategies when an enterprise seizes a chance to diversify its business scale. This problematic has not been discussed in previous research. This research starts with the literature review of the relationship between the type of resources and that of diversification. Through analyzing one particular type of resources and characteristics of resources, fruitful research results have been accumulated. However, it is also found that the same type of resources directs to different types of diversification. In reality, a company examines different types of resources while considering its development opportunity. That is, different types of resources mutually influence each other. If we reach an agreement on the above argument, it is understandable why one type of resources may result in different types of diversification. Furthermore, the relationship between resources and diversification can be examined through forming a resourceconfiguration perspective. This study is based on the analysis of 152 development projects of the largest Taiwanese enterprises. Through further analysis, it is attested that different types of resources mutually influence each other. That is, in the case of development strategies, due to various combinations with other resources, a specific type of resources can result in different types of diversification. Derived from the resource-configuration perspective, this research also reexamines the relationship between the type of resource configuration and that of diversification. It is shown that there are obvious associations between the two.
Continual Self-organized Learning of Hierarchical Mulitimodal ART

When people learn a concept of an object, we rely on many different sensory data. Depending on one single sensory system can possibly cause some confusion, but conjugating multiple systems in learning can resolve such uncertainties. In addition, human learning effectively utilises incremental learning strategies, which means that learning process continues as new training samples emerge. Taking advantage of these two observations, we suggest the Hierarchical Multi-modal Adaptive Resonance Theory model (HiMART). HiMART, in addition to taking advantage of incremental learning, builds the generalized multi-modal patterns that can later be used as long-term memories. Finally, we discuss further experiments using our model.
A 6.5~7.5-GHz CMOS Wideband FMCW Radar Transmitter based on Synthetic Bandwidth Technique

A fully integrated wideband FMCW radar transmitter based on synthetic bandwidth technique has been proposed and implemented in 55-nm CMOS technology. The wideband chirp is synthesized by mixing 500-MHz chirp from low frequency phase locked loop (PLL) with multiple high frequency carriers generated from sub-harmonic injection locking oscillator (SHILO). The fast switching SHILO allows the combination of multiple 500-MHz chirps to form a wideband chirp at high frequency. In the design, a wideband fractional-N PLL with randomized phase interpolation, covering 1.8~2.3 GHz, is employed to generate the desired 500-MHz chirp while achieving low in-band phase noise of -115~120 dBc/Hz. The high frequency SHILO also attains similar low in-band phase noise thanks to the injection locking property while achieving fast switching time less than 14 ns. The proposed transmitter achieves final chirp bandwidth of 1 GHz with good phase noise performance. The technique can be easily extended for wider chirp bandwidth by increasing the number of output carriers from SHILO. The transmitter supports pulse repetition period ranging from 0.3 to 6.3 ms. It consumes 84 mW, while occupying a total active area of 2.24 mm2,
Serum Nitric Oxide Levels in Smokers with Chronic Periodontitis

Smoking is a major risk factor for periodontal diseases. Nitric oxide (NO) plays a crucial role in vascular tone regulation and is involved in the pathogenesis of periodontitis. The aim of the present study was to determine and compare serum levels of NO in healthy controls, smokers and nonsmokers with chronic periodontitis. A total of 90 subjects were divided into 3 equal groups of 30 control patients, 30 non-smokers with chronic periodontitis and 30 smokers with chronic periodontitis. Periodontal disease status was determined by recording probing pocket depth (PPD) and clinical attachment level (CAL). Serum nitric oxide activity was estimated using Griess colorimetric reactions. The results were compared and statistically analyzed using ANOVA. The mean NO levels in serum were found to be highest in smokers with periodontitis, followed by the periodontitis group, and then by the healthy controls (88.20±3.95, 82.29±3.54, and 64.69±2.16, μM/L respectively). The values were statistically significant between the groups (P<0.001). Serum NO was significantly increased in smokers with chronic periodontitis in comparison with non-smokers. Smoking seems to amplify this effect, which could explain the severity of periodontitis in smokers.More longitudinal, prospective studies will help to verify the observations of the present study. Further research in this direction could identify reliable markers to forecast the progression of periodontitis in high-risk groups. Clinical article (J Int Dent Med Res 2020; 13(2): 663-668)
Population structure analysis reveals the maintenance of isolated sub-populations of weedy rice

Chung J-W & Park Y-J (2010). Population structure analysis reveals the maintenance of isolated sub-populations of weedy rice. Weed Research 50, 606–620. Summary This study was conducted to assess the genetic diversity, population structure and linkage disequilibrium (LD) of weedy rice in Korea using 73 weedy rice, 24 landrace lines, 12 breeding lines and 24 international varieties. In total, 772 alleles were detected in 63 microsatellite loci. The number of alleles per marker locus ranged from two to 40, with an average of 12.3. The gene diversity and polymorphism information content value averaged 0.694 and 0.668, with a range of 0.016–0.941 and 0.016–0.946 respectively. In a model-based analysis of population structure, Korean rice germplasm was classified into four subpopulations, designated ‘cultivated indica’, ‘cultivated japonica’, ‘weedy indica’, ‘weedy japonica. ’ Pair-wise estimates of FST indicated different degrees of differentiation between the four model-based populations, with values ranging from 0.073 (between cultivated and weedy japonica) to 0.474 (between weedy japonica and weedy indica). The weedy indica population appeared to be highly differentiated, compared with the other populations. The cultivated indica lines had the highest gene diversity (0.58), followed by cultivated japonica (0.50), weedy japonica (0.42) and weedy indica (0.35). The total number of private alleles in weedy indica and japonica populations was 39 (23 markers) and 55 (22 markers) respectively. The average of LD (r2) of weedy indica and japonica types was higher than that of the two cultivated populations, both for inter- and intrachromosome values, indicating the possible reproductive and geographical isolation of sub-populations in cultivated rice fields.
Hordein variation in Brazilian barley varieties (Hordeum vulgare L.) and wild barley (H. euclaston Steud. and H. stenostachys Godr.)

No presente trabalho foi utilizada a tecnica de eletroforese vertical SDS-PAGE com o objetivo de analisar os padroes de polipeptideos de hordeina de variedades brasileiras de cevada (Hordeum vulgare L.) e de duas especies nativas de Hordeum do Sul do Brasil (H. euclaston Steud. e H. stenostachys Godr.). A analise de representantes das tres especies permitiu a identificacao de 40 bandas de polipeptideos de hordeina com peso molecular variando de 30.000 a 94.000 Da. Das 14 variedades analisadas, 12 mostraram polimorfismo intravarietal. O numero de bandas variou de 10 a 17 nas diferentes variedades e de 3 a 13 considerando sementes individuais, com um total de 26 bandas em H. vulgare. Fenogramas usando cada semente como OTU mostraram que as sementes da maioria das variedades nao formaram blocos distintos, espalhando-se em diferentes agrupamentos, junto com componentes de diferentes cultivares. As sementes de diferentes plantas das duas especies nativas tambem apresentaram grande variacao. Os pesos moleculares dos polipeptideos de hordeina das especies nativas foram bastante diferentes daqueles de H. vulgare. Os resultados indicaram que ha uma maior similaridade entre as duas especies nativas e maior distanciamento destas com a cevada cultivada, embora H. stenostachys seja um pouco mais relacionada com H. vulgare que H. euclaston.
An Algebraic Approach for the Stability Analysis of BLDC Motor Controllers

This paper presents an algebraic technique to compute the maximum time-delay that can be accepted in the control loop of a Brushless DC Motor (BLDCM) speed controller before the closed loop response becomes unstable. Using a recently proposed time-delay stability analysis methodology, we derive accurate stability conditions for the BLDCM speed controller. The results of applying the new method show that tuning the PI controller for very fast response in the order of magnitude of the BLDCM mechanical time constant cause the time-delay to significantly affect the system stability.
Spectral Methods for Ranking with Scarce Data

Given a number of pairwise preferences of items, a common task is to rank all the items. Examples include pairwise movie ratings, New Yorker cartoon caption contests, and many other consumer preferences tasks. What these settings have in common is two-fold: a scarcity of data (it may be costly to get comparisons for all the pairs of items) and additional feature information about the items (e.g., movie genre, director, and cast). In this paper we modify a popular and well studied method, RankCentrality for rank aggregation to account for few comparisons and that incorporates additional feature information. This method returns meaningful rankings even under scarce comparisons. Using diffusion based methods, we incorporate feature information that outperforms state-of-the-art methods in practice. We also provide improved sample complexity for RankCentrality in a variety of sampling schemes.
Biotic and abiotic factors influencing forage fish and pelagic nekton community in the Columbia River plume (USA) throughout the upwelling season 1999–2009

Large river plumes modify coastal environments and can impact production across multiple trophic levels. From 1999 to 2009, the assemblages of forage fish, predator fish, and other pelagic nekton were monitored in coastal waters associated with the Columbia River plume. Surveys were conducted at night to target vertically migrating species, and community structure evaluated to better understand ecological interactions. Distinct inshore and offshore communities were identified during spring and summer that were correlated with ocean temperature, salinity, plume volume, and upwelling intensity. Resident euryhaline forage fish species, such as smelts, anchovy, herring, market squid, juvenile salmon, and spiny dogfish, showed a high affinity for inshore habitat and the lower salinity plume during spring. Highly migratory species, such as sardine, piscivorous hake, sharks, and mackerels, were associated with warmer, saltier waters offshore, during strong upwelling periods in summer. Overall, our study of pelagic nekton revealed that temporal dynamics in abundance and community composition were associated with seasonal abiotic phenomenon, but not interannual, large-scale oceanographic processes. Forage fish assemblages differed seasonally and spatially from the assemblages of major piscivorous predators. This finding suggests a potential role of the plume as refuge for forage fish from predation by piscivorous fish in the northern California Current.
Low-Order Scaling G0W0 by Pair Atomic Density Fitting

We derive a low-scaling G0W0 algorithm for molecules using pair atomic density fitting (PADF) and an imaginary time representation of the Green’s function and describe its implementation in the Slater type orbital (STO)-based Amsterdam density functional (ADF) electronic structure code. We demonstrate the scalability of our algorithm on a series of water clusters with up to 432 atoms and 7776 basis functions and observe asymptotic quadratic scaling with realistic threshold qualities controlling distance effects and basis sets of triple-ζ (TZ) plus double polarization quality. Also owing to a very small prefactor, a G0W0 calculation for the largest of these clusters takes only 240 CPU hours with these settings. We assess the accuracy of our algorithm for HOMO and LUMO energies in the GW100 database. With errors of 0.24 eV for HOMO energies on the quadruple-ζ level, our implementation is less accurate than canonical all-electron implementations using the larger def2-QZVP GTO-type basis set. Apart from basis set errors, this is related to the well-known shortcomings of the GW space-time method using analytical continuation techniques as well as to numerical issues of the PADF approach of accurately representing diffuse atomic orbital (AO) products. We speculate that these difficulties might be overcome by using optimized auxiliary fit sets with more diffuse functions of higher angular momenta. Despite these shortcomings, for subsets of medium and large molecules from the GW5000 database, the error of our approach using basis sets of TZ and augmented double-ζ (DZ) quality is decreasing with system size. On the augmented DZ level, we reproduce canonical, complete basis set limit extrapolated reference values with an accuracy of 80 meV on average for a set of 20 large organic molecules. We anticipate our algorithm, in its current form, to be very useful in the study of single-particle properties of large organic systems such as chromophores and acceptor molecules.