Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibitory Potency of Selected Therapeutic Bioactive Molecules of Standardized Terminalia arjuna ( Roxb . ) Extract on CYP 3 A 4 and CYP 2 D 6 : Exploring Possible Herb-Drug Interactions

A number of significant herbal drug interactions have their origins in the alteration of cytochrome P450 (CYP) activity by various phytochemicals. In the present study, inhibition potential of Terminalia arjuna extracts and its constituent gallic acid (GA) and ellagic acid (EA) to cause herb-drug interactions through rat liver cytochrome enzymes, CYP3A4, and CYP2D6 was evaluated, a rapid RP-HPLC method was developed for quantitative estimation of GA and EA in the extract. In vitro safety of the extract and active components were evaluated through CYP450 inhibition method using pooled rat microsomes and high throughput fluorometric assay with CYP3A4 and CYP2D6. The binding mode and the molecular interaction of GA and EA within the CYP3A4 and CYP2D6 active site were demonstrated using an in-silico docking studies. From CYP450-CO Complex assay, the inhibitory potential of T. arjuna standardized extract (31.02 ± 2.24%), was found to be less than positive control. In high throughput fluorometric assay, T. arjuna extracts exhibited higher IC50 values (48.06 ± 1.14-57.89 ± 2.15 μg/mL) compared to positive inhibitors and lower than GA (66.54 ± 1.04-83.84 ± 1.06 μg/mL), EA (69.47 ± 1.18-102.69 ± 2.87 μg/mL) on CYP3A4 and CYP2D6. Based on the inhibitory potential of test samples, it can be concluded that T. arjuna and its standardized bioactive molecules could produce weak interaction potential when co-administered with conventional medicines.
Adaptive-Latency DRAM (AL-DRAM)

This paper summarizes the idea of Adaptive-Latency DRAM (AL-DRAM), which was published in HPCA 2015. The key goal of AL-DRAM is to exploit the extra margin that is built into the DRAM timing parameters to reduce DRAM latency. The key observation is that the timing parameters are dictated by the worst-case temperatures and worst-case DRAM cells, both of which lead to small amount of charge storage and hence high access latency. One can therefore reduce latency by adapting the timing parameters to the current operating temperature and the current DIMM that is being accessed. Using an FPGA-based testing platform, our work first characterizes the extra margin for 115 DRAM modules from three major manufacturers. The experimental results demonstrate that it is possible to reduce four of the most critical timing parameters by a minimum/maximum of 17.3%/54.8% at 55C while maintaining reliable operation. AL-DRAM adaptively selects between multiple different timing parameters for each DRAM module based on its current operating condition. AL-DRAM does not require any changes to the DRAM chip or its interface; it only requires multiple different timing parameters to be specified and supported by the memory controller. Real system evaluations show that AL-DRAM improves the performance of memory-intensive workloads by an average of 14% without introducing any errors.
Improvements on Learning Tetris with the Cross-entropy Method Notes Improvements on Learning Tetris with Cross-entropy

For playing the game of Tetris well, training a controller by the cross-entropy method seems to be a viable way (Szita and L˝ orincz, 2006; Thiery and Scherrer, 2009). We consider this method to tune an evaluation-based one-piece controller as suggested by Szita and L˝ orincz and we introduce some improvements. In this context, we discuss the influence of the noise, and we perform experiments with several sets of features such as those introduced by Bertsekas and Tsitsiklis (1996), by Dellacherie (Fahey, 2003), and some original features. This approach leads to a controller that out-performs the previous known results. On the original game of Tetris, we show that with probability 0.95 it achieves at least 910, 000 ± 5% lines per game on average. On a simplified version of Tetris considered by most research works, it achieves 35, 000, 000 ± 20% lines per game on average. We used this approach when we took part with the program BCTS in the 2008 Tetris domain Reinforcement Learning Competition and won the competition.
Clouds–SST relationship and interannual variability modes of Indian summer monsoon in the context of clouds and SSTs: observational and modelling aspects

This study examines the relationship between clouds and sea surface temperatures (SSTs) during Indian Summer Monsoon (ISM). Observation reveals dominance of high‐level clouds in the monsoon region. NCEP Climate Forecast System version 2 (CFSv2) is able to replicate the observed high‐level cloud fractions although it underestimates the magnitude. Cloud–SST relationship for observation depicts dominance of positive correlation over equatorial Indian Ocean region which is well recapitulated in CFSv2 simulations. To investigate the most dominating patterns of interannual variability of rainfall, SST and clouds, empirical orthogonal function (EOF) analysis is performed on seasonal JJAS (June–September) dataset. EOF analysis signifies that high‐level clouds are highly correlated with rainfall for observations during ISM season. This study has also investigated relationship of clouds and El Niño Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) during ISM period. Interannual variations of clouds connote significant correlation with ENSO index (Nino 3/Nino 3.4). First principal component (PC1) of high‐level clouds and ENSO index indicate significant negative correlation. EOF analysis based on observation also connotes that first mode (second) of EOF analysis is associated with ENSO (IOD). It is also confirmed by maximum covariance analysis (MCA). CFSv2 is also able to depict the significant negative correlation between PC1 of high‐level clouds and ENSO index. Observation based second principal component (PC2) of high‐level clouds and IOD index exhibits significant positive correlation. It gives indication that PC2 of observed high‐level clouds can be associated with IOD. In contrast, PC2 of CFSv2 simulated high‐level cloud and IOD index are not correlated. EOF analysis based on CFSv2 shows that the first mode of EOF analysis is associated with ENSO; however, second mode of EOF is not related with IOD. MCA analysis also supports these findings. It means that CFSv2 has good ability to represent ENSO as compared with IOD.
GM Technology Adoption, Production Risk and On-farm Varietal Diversity

This paper examines the impact of transgenic technology adoption on varietal diversity. Transgenic pest-resistant varieties are hypothesized to reduce farmers’ demand for on-farm diversity through an act of substitution, as both serve as production risk reducing instruments. This adverse agro-biodiversity impact might be partially counteracted by an expanding seed sector, supplying a large number of transgenic varieties. The case of Bt cotton in India is taken for empirical illustration. The production function analyses show that both Bt technology and on-farm varietal diversity enhance yield, while reducing the production risk. With few Bt varieties available in the first years, technology adoption entailed a reduction in on-farm varietal diversity. This effect, however, was partially offset by more Bt varieties becoming available over time.
3D wave-equation dispersion inversion of surface waves

The 2D wave-equation dispersion inversion (WD) methodology is extended to the inversion of three-dimensional data for a 3D shear-wave velocity model. The objective function of 3D WD is the sum of the squared wavenumber differences along each azimuth angle between the predicted and observed 3D dispersion curves. The 3D dispersion curves are obtained by wavenumber-frequency analysis of the fundamental Rayleigh waves in each 3D shot gather. The S-wave velocity update is computed by a weighted zero-lag crosscorrelation between the source wavefield and the back-projected receiver-side wavefield for each azimuth angle. The synthetic and field data examples demonstrate that the 3D WD method can accurately estimate the 3D S-wave velocity model in laterally heterogeneous media.
Performance Optimization of Error Detection Based on Speculative Reconfiguration

This paper presents an approach to minimize the average program execution time by optimizing the hardware/software implementation of error detection. We leverage the advantages of partial dynamic reconfiguration of FPGAs in order to speculatively place in hardware those error detection components that will provide the highest reduction of execution time. Our optimization algorithm uses frequency information from a counter-based execution profile of the program. Starting from a control flow graph representation, we build the interval structure and the control dependence graph, which we then use to guide our error detection optimization algorithm.
Who Wins the Olympic Games: Economic Resources and Medal Totals

This paper examines determinants of Olympic success at the country level. Does the United States win its fair share of Olympic medals? Why does China win only 6 of the medals even though it has one-fifth of the world's population? We consider the role of population and economic resources in determining medal totals from 1960 to 1996. At the margin, population and income per capita have similar effects, suggesting that both a large population and high per capita GDP are needed to generate high medal totals. We also provide out-of-sample predictions for the 2000 Olympics in Sydney.
Disentangling the magnetic force noise contribution in LISA Pathfinder

Magnetically-induced forces on the inertial masses on-board LISA Pathfinder are expected to be one of the dominant contributions to the mission noise budget, accounting for up to 40%. The origin of this disturbance is the coupling of the residual magnetization and susceptibility of the test masses with the environmental magnetic field. In order to fully understand this important part of the noise model, a set of coils and magnetometers are integrated as a part of the diagnostics subsystem. During operations a sequence of magnetic excitations will be applied to precisely determine the coupling of the magnetic environment to the test mass displacement using the on-board magnetometers. Since no direct measurement of the magnetic field in the test mass position will be available, an extrapolation of the magnetic measurements to the test mass position will be carried out as a part of the data analysis activities. In this paper we show the first results on the magnetic experiments during an end-to-end LISA Pathfinder simulation, and we describe the methods under development to map the magnetic field on-board. A post-publication change was made to this article on 26 Jun 2020 to add an author.
Dye sensitized solar cells with cobalt and iodine-based electrolyte: the role of thiocyanate-free ruthenium sensitizers

Three isomeric Ru(II) metal complexes with distinctively oriented tpiq ancillary chelates, TFRS-80a, 80b and 80c, were prepared from the condensation of Ru(4,4′-diethoxycarbonyl-2,2′-bipyridine) (p-cymene)Cl with tpiqH, i.e. 6-(5-(2,6-bis(hexyloxy)phenyl)thiophen-2-yl)-1-(3-(trifluoromethyl)-1H-pyrazol-5-yl)isoquinoline. Photophysical and electrochemical investigations, together with DFT and TD-DFT calculations, allowed a comprehensive understanding of their basic properties in both solution state and on TiO2 surface. DSC cells with both an ultra-thin layer of transparent TiO2 (3.6 μm) and I−/I3− electrolyte were fabricated, for which the symmetric sensitizers TFRS-80a and 80c showed better performances (η = 8.37 and 8.26%) over that of the asymmetric counterpart TFRS-80b (η = 5.55%), the latter suffered from poor dye loading and consequently lowered JSC and VOC. In sharp contrast, all DSC cells with [Co(phen)3]2+/3+ electrolyte gave superior efficiencies (η = 8.36–9.06%), for which the thiocyanate-free architecture, the improved light harvesting capability, and the possession of conjugated and bulky 5-(2,6-bis(hexyloxy)phenyl)thiophen-2-yl functional moieties are three primary factors governing the observed results.
Targeted overexpression of mitochondrial catalase prevents radiation-induced cognitive dysfunction.

AIMS Radiation-induced disruption of mitochondrial function can elevate oxidative stress and contribute to the metabolic perturbations believed to compromise the functionality of the central nervous system. To clarify the role of mitochondrial oxidative stress in mediating the adverse effects of radiation in the brain, we analyzed transgenic (mitochondrial catalase [MCAT]) mice that overexpress human catalase localized to the mitochondria. RESULTS Compared with wild-type (WT) controls, overexpression of the MCAT transgene significantly decreased cognitive dysfunction after proton irradiation. Significant improvements in behavioral performance found on novel object recognition and object recognition in place tasks were associated with a preservation of neuronal morphology. While the architecture of hippocampal CA1 neurons was significantly compromised in irradiated WT mice, the same neurons in MCAT mice did not exhibit extensive and significant radiation-induced reductions in dendritic complexity. Irradiated neurons from MCAT mice maintained dendritic branching and length compared with WT mice. Protected neuronal morphology in irradiated MCAT mice was also associated with a stabilization of radiation-induced variations in long-term potentiation. Stabilized synaptic activity in MCAT mice coincided with an altered composition of the synaptic AMPA receptor subunits GluR1/2. INNOVATION Our findings provide the first evidence that neurocognitive sequelae associated with radiation exposure can be reduced by overexpression of MCAT, operating through a mechanism involving the preservation of neuronal morphology. CONCLUSION Our article documents the neuroprotective properties of reducing mitochondrial reactive oxygen species through the targeted overexpression of catalase and how this ameliorates the adverse effects of proton irradiation in the brain.
Microfacies and diagenesis of older Pleistocene (pre‐last glacial maximum) reef deposits, Great Barrier Reef, Australia (IODP Expedition 325): A quantitative approach

During Integrated Ocean Drilling Program Expedition 325, 34 holes were drilled along five transects in front of the Great Barrier Reef of Australia, penetrating some 700 m of late Pleistocene reef deposits (post‐glacial; largely 20 to 10 kyr bp) in water depths of 42 to 127 m. In seven holes, drilled in water depths of 42 to 92 m on three transects, older Pleistocene (older than last glacial maximum, >20 kyr bp) reef deposits were recovered from lower core sections. In this study, facies, diagenetic features, mineralogy and stable isotope geochemistry of 100 samples from six of the latter holes were investigated and quantified. Lithologies are dominated by grain‐supported textures, and were to a large part deposited in high‐energy, reef or reef slope environments. Quantitative analyses allow 11 microfacies to be defined, including mixed skeletal packstone and grainstone, mudstone‐wackestone, coral packstone, coral grainstone, coralline algal grainstone, coral‐algal packstone, coralline algal packstone, Halimeda grainstone, microbialite and caliche. Microbialites, that are common in cavities of younger, post‐glacial deposits, are rare in pre‐last glacial maximum core sections, possibly due to a lack of open framework suitable for colonization by microbes. In pre‐last glacial maximum deposits of holes M0032A and M0033A (>20 kyr bp), marine diagenetic features are dominant; samples consist largely of aragonite and high‐magnesium calcite. Holes M0042A and M0057A, which contain the oldest rocks (>169 kyr bp), are characterized by meteoric diagenesis and samples mostly consist of low‐magnesium calcite. Holes M0042A, M0055A and M0056A (>30 kyr bp), and a horizon in the upper part of hole M0057A, contain both marine and meteoric diagenetic features. However, only one change from marine to meteoric pore water is recorded in contrast with the changes in diagenetic environment that might be inferred from the sea‐level history. Values of stable isotopes of oxygen and carbon are consistent with these findings. Samples from holes M0032A and M0033A reflect largely positive values (δ18O: −1 to +1‰ and δ13C: +1 to +4‰), whereas those from holes M0042A and M0057A are negative (δ18O: −4 to +2‰ and δ13C: −8 to +2‰). Holes M0055A and M0056A provide intermediate values, with slightly positive δ13C, and negative δ18O values. The type and intensity of meteroric diagenesis appears to have been controlled both by age and depth, i.e. the time available for diagenetic alteration, and reflects the relation between reef deposition and sea‐level change.
Relaciones entre empatía, conducta prosocial, agresividad, autoeficacia y responsabilidad personal y social de los escolares

Relationships among empathy, prosocial behavior, aggressiveness, self-efficacy and pupils' personal and social responsibility. The aim of this study was, on the one hand, to present/display the Spanish version of diverse instruments that assess Empathy, Prosocial behavior, Aggressiveness, Self-efficacy and Personal and social responsibility, and, on the other hand, to analyze which of these variables could predict responsibility. Participants were 822 pupils, ages 8 to 15 years, who studied in 11 educational centres of the Valencian Community. Measures include Spanish versions of the Index of Empathy for Children and Adolescents, Prosocial Behaviour, and Physical and Verbal Aggression, the Multidimensional Scale of Perceived Self-Efficacy, and the Contextual Self-Responsibility Questionnaire. Through structural equation modelling (SEM), the results showed positive relationships between Prosocial behaviour, Empathy, Self-efficacy, and Responsibility; and negative relationships between Aggressiveness and Responsibility. The results and implications for education are discussed.
Improved Protein Fold Assignment Using Support Vector Machines Currently He Is Supported by a Nih Training Grant: Cellular Signaling in Cardiovascular System. His Research Interests Include Machine Learning, Protein Folding, Structure Prediction, Protein Function Prediction, and Binding Prediction o

Because of the relatively large gap of knowledge between number of protein sequences and protein structures, the ability to construct a computational model predicting structure from sequence information has become an important area of research. The knowledge of a protein's structure is crucial in understanding its biological role. In this work, we present a support vector machine based method for recognising a protein's fold from sequence information alone, where this sequence has less similarity with sequences of known structures. We have focused on improving multi-class classification, parameter tuning, descriptor design, and feature selection. The current implementation demonstrates better prediction accuracy than previous similar approaches, and has similar performance when compared with straightforward threading. Ognjen Perisic is a third year PhD student of Bioinformatics in Department of Bioengineering at UIC. His research interests are in computational biophysics, free energy calculation, non-equilibrium statistical physics in biology, and protein structure prediction. in bioinformatics include: machine learning, protein folding, protein structure prediction, protein-protein and protein-DNA interactions, molecular dynamics and Monte Carlo simulations, protein function annotation, microarray and gene expression and gene regulation networks.
States at the Limit: Tracing Contemporary State-Society Relations in the Borderlands of Southeastern Turkey

There is theoretical significance to studying states and nations at their metaphorical and literal ‘borders’. Focusing on the contested border region of southeastern Anatolia, this chapter highlights the tensions, contradictions, and recent shifts in state-society relations in the rural spaces of the southeast. As I detail, state delivery of irrigated agriculture represents a recent and significant chapter in the evolving state-society relations in this contested border area. With contemporary changes associated with the large-scale Southeastern Anatolia Project (GAP), state influence in rural areas and encounters with the state by rural populations are intensified. This occurs both horizontally, in terms of infiltrating new spaces and life practices, and also vertically, in terms of intensified interaction, such as that associated with the increased incorporation of rural residents into the Turkish economy or the increased dependence of villagers on state services. Reading the state ethnographically through the differentiated responses of villagers to recent irrigation-related changes, my aim is to analyze how the state is lived, in very real terms, in the fabric of everyday life, and to consider what this suggests for understanding state-society relations and the changing citizen subjectivities in the liminal spaces of Turkey’s southeast.
A High Speed Block Convolution Using Ancient Indian Vedic Mathematics

In digital signal processing applications, the convolution with a very long sequence is often required. In order to compute convolution of long sequence, overlap-add method (OLA) and overlap-save method (OLS) can be considered. The OLA and OLS are well known efficient schemes for high-order filtering. The most commonly used implementation for digital filtering algorithms are digital signal processors, special purpose digital filtering chips and application specific integrated circuits (ASICs) for large volumes. In this paper, a high performance, high throughput and area efficient architecture for the field programmable gate array (FPGAs) implementation of block convolution process is proposed. The most significant aspect of the proposed method is the development of a multiplier architecture based on vertical and crosswise structure of ancient Indian Vedic mathematics and embedding it in OLA and OLS methods for improved efficiency. The coding is done in VHDL (very high speed integrated circuits hardware description language) and the FPGA synthesis is done using Xilinx Spartan library. The results shows that OLA and OLS method of block convolution implemented using Vedic multiplication is efficient in terms of area/speed compared to its implementation using conventional multiplier architectures.
Process defects and in situ monitoring methods in metal powder bed fusion: a review

Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and stability still represents a barrier for the industrial breakthrough. The most relevant metal AM applications currently involve industrial sectors (e.g. aerospace and bio-medical) where defects avoidance is fundamental. Because of this, there is the need to develop novel in situ monitoring tools able to keep under control the stability of the process on a layer-by-layer basis, and to detect the onset of defects as soon as possible. On the one hand, AM systems must be equipped with in situ sensing devices able to measure relevant quantities during the process, a.k. a. process signatures. On the other hand, in-process data analytics and statistical monitoring techniques are required to detect and localize the defects in an automated way. This paper reviews the literature and the commercial tools for in situ monitoring of powder bed fusion (PBF) processes. It explores the different categories of defects and their main causes, the most relevant process signatures and the in situ sensing approaches proposed so far. Particular attention is devoted to the development of automated defect detection rules and the study of process control strategies, which represent two critical fields for the development of future smart PBF systems.