Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of fMRI Signals Using Brain Activation-Based Decision Tree

Spatio–temporal activation of different brain regions characterizes a task performed by an individual. The consistency of the activation and the dynamics of the same between the brain regions reveal the functional relationship among the regions. In this letter, we propose a novel method to classify functional magnetic resonance imaging (fMRI) data captured while performing certain cognitive tasks. In the present analysis, four tasks are used, namely, visual word and objects, visual working memory, Simon task, and tone counting. A generalized temporal consistency in activation level (GTCAL) of the brain regions is proposed as a feature to construct a decision tree for the classification. Hammersmith atlas is used for parcellation of the brain regions. The decision tree-based approach enables to overcome the ambiguity arising due to partial similarity in the activation/deactivation of pairwise brain regions for different tasks. The proposed approach is found to outperform the existing methods of classification, namely, cross correlation, Euclidean distance, city block distance, Wasserstein distance, and temporal consistency in activation level. Such a classification of fMRI data for different functional tasks is useful to characterize the effect of aging in healthy population and to study various neurological disease conditions.
Bidirectional Selective Detect-and-Forward (DetF) Multi-Relay Systems With Regularized WDFDC Receivers

In this work, we consider a selective Detect-and-Forward (a symbol based decode-and-forward) (DetF) multi-relay two-way network employing differential MPSK with regularized Weighted Decision Feedback Differential Coherent (WDFDC) receivers. Regularized WDFDC receivers based on a regularized linear predictor (RLP) were proposed for one-way relay networks where it was shown to mitigate the performance loss due to decision feedback error propagation and intermittent transmission between relay nodes and the destination.This paper introduces regularized WDFDC receivers for two way selective DetF relay networks, employing various protocols with and without network coding, and using multiple relays. For each protocol, an optimal destination threshold is derived to decide if a relay transmits or remains silent. Furthermore, analytical performance bounds, providing insights to the effects that cause degradation, are also derived. Extensive simulation results demonstrate that the use of network coding achieves higher bandwidth efficiency, but suffers an error rate performance loss. Diversity gains can be achieved when the number of relays increases. However, repeated transmissions from the same relay do not yield extra diversity gains.
Slew-rate Comparison of single-ended amplifiers-the Folded Cascode and the Recycling Folded Cascode

In this paper, two cascode amplifiers are analyzed. For comparison purposes, same design specifications were used to size them by using the gm/ID methodology (CMOS 130 nm). In this analysis, slew-rate is the target because settling time strongly depends on it. Corners-based simulations were carried out to assess the process variations effect on the amplifiers performance. From this study the recycling folded cascode amplifier gives the highighest value and is more tolerant to process variations.
Parkinsonism: Onset, progression, and mortality

PARKINSONISM, described in its entirety over one hundred and fifty years ago,’ rarely presents itself as a diagnostic problem. In consequence, little scrutiny has been directed to the marked variability of this frequently encountered neurological syndrome and to the progression of the disease in large groups of patients. As with most chronic neurological disorders, marked diversity can be expected to exist in age and mode of onset, relative prominence of the cardinal signs and symptoms, rate of progression, and resultant degree of functional impairment. Controversy over the effectiveness of therapeutic measures for parkinsonism is due partially to this wide variability and to the paucity of clinical information about the natural history of the syndrome. It is also re-
The Arabidopsis RHD 3 gene is required for cell wall biosynthesis and actin organization

The Arabidopsis thaliana (L.) Heynh. ROOT HAIR DEFECTIVE3 (RHD3) gene has previously been shown to be essential for normal cell expansion [H. Wang et al. (1997) Genes Dev 11:799–811]. In this report, we demonstrated that mutation of the RHD3 gene in the Arabidopsis fragile fiber 4 (fra4) mutant caused a dramatic reduction in the wall thickness of fibers, vessels, and pith cells in the inflorescence stems and, concomitantly, a decrease in the mechanical strength of stems. The reduced wall thickness in the fra4mutant was accompanied by an alteration in cell wall composition. Consistent with the defective fiber and vessel wall phenotypes, the RHD3 gene exhibited a strong expression in developing fiber and xylem cells. We showed that the Arabidopsis genome contains two additional RHD3-like genes, one of which was expressed specifically in flowers. In addition, we found that mutation of the RHD3 gene caused an alteration in the organization of the actin cytoskeleton but no effects on cortical microtubules. Our findings suggest an essential role of RHD3 in cell wall biosynthesis and actin organization, both of which are known to be important for cell expansion.
Saussurea arctecapitulata Lipsch. – new species for the flora of Russia

Saussurea arctecapitulata, a herbaceous perennial species, belonging to the type section of the genus Saussurea, previously known only from a few localities in the northern Mongolia, has been found in the Naryn River Valley during field trips to the territory of Republic of Tuva. This article presents an updated description accompanied by photos of the species in nature, updated data on the distribution of the species, as well as phylogenetic relationships with morphologically similar species of the section based on the variability of the site ITS1-5.8S-ITS2.
Purification and characterization of a recombinant laccaseâ•’like multiâ•’copper oxidase from <i>Paenibacillus glucanolyticus </i><fc>SLM</fc>1

Aims: The aim of this study was to evaluate the activity of a novel bacterial laccase-like multi-copper oxidase (LMCO) from Paenibacillus glucanolyticus SLM1: a bacterium isolated from pulp and paper waste. Methods and Results: A new bacterial LMCO gene (CuOx) from P. glucanolyticus SLM1 was identified and cloned into pET22b. The protein it encodes was recombinantly expressed in Escherichia coli. The recombinant P. glucanolyticus LMCO had a molecular weight of approximately 90 kDa and demonstrated oxidation of the LMCO substrates 2,20-Azino-bis(3ethylbenzothiazoline-6-sulfonate) (ABTS), catechol, and 2,6-Dimethoxyphenol (2,6-DMP), with the oxidation of ABTS occurring to the greatest extent (776 U mg 1 under optimal conditions of pH 7 and 40°C). Furthermore, recombinant P. glucanolyticus CuOx retained activity against ABTS in the presence of 1 mol l 1 NaCl, 50% dimethyl sulfoxide and 5% Tween-80 and can decolorize several types of dyes. Conclusions: This enzyme has a neutral pH optimum, is capable of decolorizing dyes, and is active in the presence salt, detergents and surfactant. The characteristics of this enzyme suggest that it could be used for a variety of industrial applications. Significance and Impact of the Study: This work characterizes a unique bacterial LMCO with activity higher than that of previously characterized fungal or bacterial LMCOs. This enzyme may have utility for industrial bleaching, treatment of dye effluent, and lignin removal.
Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency

In finite-fault modeling of earthquake ground motions, a large fault is divided into N subfaults, where each subfault is considered as a small point source. The ground motions contributed by each subfault can be calculated by the stochastic point-source method and then summed at the observation point, with a proper time delay, to obtain the ground motion from the entire fault. A new variation of this approach is introduced based on a "dynamic corner frequency. " In this model, the corner frequency is a function of time, and the rupture history controls the frequency content of the simulated time series of each subfault. The rupture begins with a high corner frequency and progresses to lower corner frequencies as the ruptured area grows. Limiting the number of active subfaults in the calculation of dynamic corner frequency can control the amplitude of lower frequencies. Our dynamic corner frequency approach has several advantages over previous formulations of the stochastic finite-fault method, including conservation of radiated energy at high frequencies regardless of subfault size, application to a broader mag- nitude range, and control of the relative amplitude of higher versus lower frequencies. The model parameters of the new approach are calibrated by finding the best overall fit to a ground-motion database from 27 well-recorded earthquakes in California. The lowest average residuals are obtained for a dynamic corner frequency model with a stress drop of 60 bars and with 25% of the fault actively slipping at any time in the rupture. As an additional tool to allow the stochastic modeling to generate the impulsive long-period velocity pulses that can be caused by forward directivity of the source, the analytical approach proposed by Mavroeidis and Papageorgiou (2003) has been included in our program. This novel mathematical model of near-fault ground mo- tions is based on a few additional input parameters that have an unambiguous physi- cal meaning; the method has been shown by Mavroeidis and Papageorgiou to sim- ulate the entire set of available near-fault displacement and velocity records, as well as the corresponding deformation, velocity, and acceleration response spectra. The inclusion of this analytical model of long-period pulses substantially increases the power of the stochastic finite-fault simulation method to model broadband time his- tories over a wide range of distances, magnitudes, and frequencies.
RUNOFF GENERATION ON ABANDONED FIELDS IN THE CENTRAL EBRO BASIN - RESULTS FROM MODELLING

The results from several rainfall simulations performed on two abandoned fields of different ages in the Central Ebro Depression have been analysed by application of the physically based hydraulic model HILLFLOW 1D. The data gained by the simulations was used to parame - terise the model. Afterwards, the runoff generation characteristics were determined by simulation of different rainfall intensities and different macroporosities of the soil. The young fallow land shows a minimum inten - sity for runoff generation of 6 mm h-1. An increase of the rainfall intensity leads rapidly to a growing runoff coefficient, being the value modelled for 30 mm h-1 nearly the same as the simulated one (40 mm h-1). Another con - clusion of the simulations and their modelling is the homogeneity of the soils on the young fallow land, with no macroporosity all over the profile. On the other hand, the rainfall simulations and the modelling on the old fallow land show a high variability of rainfall-runo ff response patterns, strongly conditioned by the presence of macropores. They are distributed very irregularly throughout the soil of the old fallow land. In both cases, water infiltrates only little into the soil matrix, for that measures for enhan- cing soil hydraulic properties are needed. RESUMEN: Se han analizado los resultados de numerosas simulacio - nes de lluvia en campos abandonados de diferente antuguedad en la Depresion central del Ebro aplicando el modelo hidrologico de base fisi ca HILLFLOW 1D. Los datos de las simulaciones se utilizaron para para - metrizar el modelo. A continuacion, las caracteristicas de la generacion de escorrentia se analizaron modelizando diferentes intensidades de lluvia y volumenes de macroporos en el suelo. En el campo recientemente aban - donado se pudo calcular una intensidad de llluvia minima para la gene- racion de escor rentia de 6 mm h-1. Una intensidad de precipitacion cr e - ciente produce un incremento muy fuerte del coeficiente de escor rentia, de modo que precipitaciones de 30 mm h-1 se diferencian poco de las simu- ladas con 40 mm h-1. Otra conclusion es que los suelos del campo recien - temente abandonado son muy homogeneos y estan caracterizados por la ausencia de macroporos. La respuesta de la generacion de escor rentia a la precipitacion es en cambio muy variable en el campo abandonado anti -
The Seepage Calculation and the Drainage Design of Tailings Dam

The seepage stability is the important factor which impacts the safety and stability of the tailings dam,and the position of the saturation line directly affects the safety and stability of the tailings dam.Taking the concrete tailings dam for example,and based on the measured data on drilling,the suitable calculation parameter and boundary condition are chosen to build a reasonable calculation model to analyze the seepage situation of the tailings dam when the drainage facility is normal or damaged.The conclusion is that the permeability of the primary dam has a close relationship with the seepage stability of the tailings dam.When the impermeable layer of the primary dam is blocked,the permeability at exit is reduced and the saturation line of the dam rises,and even the water may exude from the dam slope.The seepage scheme with the local horizontal holes can effectively reduce the saturation line and ensure the safety of the dam.
UvA-DARE ( Digital Academic Repository ) Out-of-sample comparison of copula specifications in multivariate density forecasts

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions on the competing copulas: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte Carlo simulations demonstrate that the proposed test has satisfactory size and power properties in finite samples. Applying the test to daily exchange rate returns of several major currencies against the US dollar we find that the Student-t copula is favored over Gaussian, Gumbel and Clayton copulas.
Advances in the Utilization of Next Generation Sequencing Data in the Colombian Sugarcane Breeding Program

Sugarcane is a polyploid/aneuploid crop with a 2n chromosome number ranging between 80 and 130. This genomic complexity has made the implementation of breeding strategies based on molecular markers difficult. The recent advances in next generation sequencing technologies (NGS) have increased the number of markers that can be used in genotyping studies and thus offer new possibilities in breeding programs. At CENICAÑA, a diversity panel of 220 sugarcane genotypes, 130 representing the phenotypic diversity of CENICAÑA’s germplasm collection and 90 of breeding and economic importance for the center, was sequenced by GBS and RADSeq. Independently, each dataset was analyzed to identify high quality SNPs, calculate genetic distances among individuals, define population structures and perform Genome Wide Associations Studies (GWAS). RADSeq performed better in elucidating the genetic diversity of the population under study. Phylogenetic trees derived from GBS and RADSeq were not identical (groups coincided in 6070% of the cases), despite the high number of SNP markers used (>4,000 in each case). These data combined with genetic distances indexes revealed parental genotypes with potential for crossing aimed at increasing the overall genetic diversity. Population structure analyses detected four subpopulations that are in agreement with previous studies based on microsatellites. RAD sequencing performed better than GBS in detecting these subpopulations. SNP markers derived from GBS, on the other hand, showed a higher read depth compared to RADSeq. This could be important for mapping studies. Finally, our preliminary GWAS analysis revealed alleles with a significant association to traits such as sucrose content and flowering capacity. Currently, specific assays are being designed to validate these associations.
STATISTICAL PROPERTIES OF GAMMA-RAY BURST POLARIZATION

The emission mechanism and the origin and structure of magnetic fields in gamma-ray burst (GRB) jets are among the most important open questions concerning the nature of the central engine of GRBs. In spite of extensive observational efforts, these questions remain to be answered and are difficult or even impossible to infer with the spectral and light-curve information currently collected. Polarization measurements will lead to unambiguous answers to several of these questions. Recent developments in X-ray and γ-ray polarimetry techniques have demonstrated a significant increase in sensitivity, enabling several new mission concepts, e.g., Polarimeters for Energetic Transients (POET), providing wide field of view and broadband polarimetry measurements. If launched, missions of this kind would finally provide definitive measurements of GRB polarizations. We perform Monte Carlo simulations to derive the distribution of GRB polarizations in three emission models; the synchrotron model with a globally ordered magnetic field (SO model), the synchrotron model with a small-scale random magnetic field (SR model), and the Compton drag model (CD model). The results show that POET, or other polarimeters with similar capabilities, can constrain the GRB emission models by using the statistical properties of GRB polarizations. In particular, the ratio of the number of GRBs for which the polarization degrees can be measured to the number of GRBs that are detected (Nm/Nd) and the distributions of the polarization degrees (Π) can be used as the criteria. If Nm/Nd > 30% and Π is clustered between 0.2 and 0.7, the SO model will be favored. If, instead, Nm/Nd < 15%, then the SR or CD model will be favored. If several events with Π>0.8 are observed, then the CD model will be favored.
MODELING SOIL ORGANIC CARBON CHANGE IN CROPLANDS OF CHINA

Using 1990 conditions, we modeled carbon (C) and nitrogen (N) biogeochemical cycles in croplands of China (and, for comparison, the United States) to estimate the annual soil organic-carbon (SOC) balance for all cropland. Overall, we estimate that China's croplands lost 1.6% of their SOC (to a depth of 0.3 m) in 1990, and that U.S. cropland lost 0.1%. A key element in this difference was that ∼25% of aboveground crop residue in China was returned to the soil, compared to ∼90% in the United States. In China, SOC losses were greatest in the northeast (∼103 kg C·ha–1·yr–1), and were generally smaller (<0.5 × 103 kg C·ha–1·yr–1) in regions with a longer cultivation history. Some regions showed SOC gains, generally <103 kg C·ha–1·yr–1. Reduced organic-matter input to China's cropland soils, and lower overall SOC levels in those soils, led to lower levels of N mineralization in the simulations, consistent with higher rates of synthetic-fertilizer application in China. C and N cycles are closely linked to soil f.
Evaluation method for regulation and storage capacity of underground reservoir

The regulation and storage capacity of underground reservoir is defined from the point of view of keeping ecological balance and sustainable development and utilization of water resources of the watershed. The grey relation analysis model is combined with correlation analysis to establish the index system for comprehensive evaluation of the capacity. The projection pursuit model is introduced to establish the method for evaluation. This model is applied to evaluate and optimize the regulation and storage capacity of the underground reservoirs in lower Liaohe plain. The result shows that the projection pursuit model is capable and effective in analyzing and evaluating the regulation and storage capacity of underground reservoir.
Pacific Asia Conference on Information Systems ( PACIS ) 1-1-2007 Maintaining a Virtual Professional Community Through Positive Word of Mouth

To better understand the sustainability of a virtual professional community, the authors develop and test a research model of user intention to recommend the community to others. Specifically, intention to spread positive word of mouth is proposed to be determined by satisfaction, commitment, and group norm, with satisfaction and group norm positively impacting commitment. Using data obtained from users of a virtual professional community (an educational portal), the results supported nearly all hypothesized relationships. Only the relationship between satisfaction and commitment was not found to be significant. The authors conclude with a discussion of the findings and implications for both theory and practice.
Open Problem: Best Arm Identification: Almost Instance-Wise Optimality and the Gap Entropy Conjecture

The best arm identification problem (BEST-1-ARM) is the most basic pure exploration problem in stochastic multi-armed bandits. The problem has a long history and attracted significant attention for the last decade. However, we do not yet have a complete understanding of the optimal sample complexity of the problem: The state-of-the-art algorithms achieve a sample complexity of $O(\sum_{i=2}^{n} \Delta_{i}^{-2}(\ln\delta^{-1} + \ln\ln\Delta_i^{-1}))$ ($\Delta_{i}$ is the difference between the largest mean and the $i^{th}$ mean), while the best known lower bound is $\Omega(\sum_{i=2}^{n} \Delta_{i}^{-2}\ln\delta^{-1})$ for general instances and $\Omega(\Delta^{-2} \ln\ln \Delta^{-1})$ for the two-arm instances. We propose to study the instance-wise optimality for the BEST-1-ARM problem. Previous work has proved that it is impossible to have an instance optimal algorithm for the 2-arm problem. However, we conjecture that modulo the additive term $\Omega(\Delta_2^{-2} \ln\ln \Delta_2^{-1})$ (which is an upper bound and worst case lower bound for the 2-arm problem), there is an instance optimal algorithm for BEST-1-ARM. Moreover, we introduce a new quantity, called the gap entropy for a best-arm problem instance, and conjecture that it is the instance-wise lower bound. Hence, resolving this conjecture would provide a final answer to the old and basic problem.
Open problem: log(n) factor in "Local Glivenko-Cantelli

Can the log( n ) factor in the upper bound of Cohen and Kontorovich (COLT, 2023) be removed? Introduction. Cohen and Kontorovich (2023) considered the following problem. Let Y j , j ∈ N be a sequence of independent Binomial( n, p j ) random variables, where n ∈ N and p j ↓ 0 as j → ∞ . Since E Y j = np j , let us consider the centered, normalized process ¯ Y j := n − 1 Y j − p j . Finally, we define ∆ n to be the expected uniform absolute deviation:
Pacific Asia Conference on Information Systems ( PACIS ) Summer 6-27-2016 PREDICTING COMPANY REVENUE TREND USING FINANCIAL NEWS

Text data analysis has found its way in many applications, and our study focuses on the financial fields. Previous studies in financial indicator prediction are mostly based on econometric models. In recent years, with the advance of text mining techniques, more and more studies employ financial news as the data source for analysis. Most studies, however, aim to predict stock prices, identify the trend of stock market, and detect company bankruptcy or company fraud. We observe that company’ revenue, which can imply the company's cash flow and market share, is indeed an important financial indicator. In our study, we identify a few features that potentially impact company’s revenue and further propose an approach to deriving feature values from financial news data. Specifically, we develop a lexicon-based method that involves the automatic expansion of existing financial sentiment dictionary and the aggregation of sentiment values. Preliminary experimental results show that we are able to predict the revenue trend through the news articles in the last quarter with the accuracy up to 80%.