Miracle-dz/UniFAR-FTUs huggingface dataset:
General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix

This paper presents a new general four-component scattering power decomposition method by implementing a set of unitary transformations for the polarimetric coherency matrix. There exist nine real independent observation parameters in the 3 <formula formulatype="inline"><tex Notation="TeX">$\times$</tex></formula> 3 coherency matrix with respect to the second-order statistics of polarimetric information. The proposed method accounts for all observation parameters in the new scheme. It is known that the existing four-component decomposition method reduces the number of observation parameters from nine to eight by rotation of the coherency matrix and that it accounts for six parameters out of eight, leaving two parameters (i.e., the real and imaginary parts of <formula formulatype="inline"> <tex Notation="TeX">$T_{13}$</tex></formula> component) unaccounted for. By additional special unitary transformation to this rotated coherency matrix, it became possible to reduce the number of independent parameters from eight to seven. After the unitary transformation, the new four-component decomposition is carried out that accounts for all parameters in the coherency matrix, including the remaining <formula formulatype="inline"><tex Notation="TeX">$T_{13}$</tex> </formula> component. Therefore, the proposed method makes use of full utilization of polarimetric information in the decomposition. The decomposition also employs an extended volume scattering model, which discriminates volume scattering between dipole and dihedral scattering structures caused by the cross-polarized <formula formulatype="inline"><tex Notation="TeX">$HV$</tex></formula> component. It is found that the new method enhances the double-bounce scattering contributions over the urban areas compared with those of the existing four-component decomposition, resulting from the full utilization of polarimetric information, which requires highly improved acquisitions of the cross-polarized <formula formulatype="inline"><tex Notation="TeX">$HV$</tex></formula> component above the noise floor.
Genetic Differentiation and Systematic Evolution of Sichuan Rhesus Macaques

The rhesus macaque (Macaca mulatta) is perhaps the most widely distributed nonhuman primate, is used more extensively than any other primate species as animal models for the study of biomedicine. In this study, we sequenced and analysed a fragment of 491 bp of mitochondrial DNA (mtDNA) partial control region in 230 individuals belonging to 8 populations of Sichuan province of China. Among the 230 individuals, we observed 56 different haplotypes defined by 110 polymorphic sites. The average number of nucleotide differences (k) was 18.844, indicating that very high genetic differentiation and the extant Sichuan wild rhesus macaques population consists of diverse genetic groups in their maternal lineage. The mtDNA haplotypes of these Sichuan wild rhesus macaques clustered into two main clades (CladeⅠand Clade Ⅱ), may correspond to M. m. vestitus and M.m. lasiotis.
The human decision maker in finance

The market can provide commitment devices and other mechanisms to help people overcome these biases, but it can also exacerbate them. In general, the market will have weak or missing incentives for resolving these problems when borrowers are naïve about their biases or underestimate their lack of understanding. Moreover, organizations may deliberately misinform or underinform their customers about the terms of the contracts they are signing. The consequences of these biases can be profound for people in poverty, or on the edge of poverty, because they lack a margin for error. And because countries may not have the institutional capacity and the safety nets to safeguard individuals against financial losses, poor people need to be even more attentive to financial decisions (Mullainathan and Shafir 2009). Poverty also heightens uncertainty about future costs and benefits of different actions, magnifying the individual’s focus on the pressing and current scarcity of resources—and further complicating decision making for individuals who are often overwhelmed with numerous important day-to-day decisions (see chapter 4). Given these considerations, providing an appropriate institutional setting—that is, access to wellfunctioning financial markets and a sound regulatory environment—may not be enough to improve people’s decisions. In developing countries, more proactive policies may be necessary to address the behavioral constraints on financial decision making. For example, providing access to a new insurance instrument may not be sufficient to induce people to use it if they perceive the product as ambiguous or do not trust the institution issuing it. This chapter suggests ways that policy makers can make institutions more responsive to the behavioral factors driving people’s financial decisions. This Financial decisions are difficult. They typically involve great uncertainty about the future, whether about future income, cash (liquidity) needs, or interest rates. Much has been learned in recent years about how individuals actually make these decisions. More often than not, financial decision making is influenced by impulsive judgments, emotions, temptation, loss aversion, and procrastination. The research discussed in chapter 1 revealed systematic biases in decision making: that is, systematic departures from what individuals intend to do and say that they want to do and what they actually do. All these biases apply particularly to financial decision
Detecting differential usage of exons from RNA-seq data

RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package.
Deep cross-layer activation features for visual recognition

Convolutional Neural Networks (CNNs), which have nowadays dominated image analysis tasks, constitute feed-forward methods that model increasingly complex data structures and patterns along the subsequent hidden layers of the network. However, the common practice of using the activation features from the last network layer inevitably leads to a visual recognition bottleneck. This is due to the fact that discriminative features for different objects of varying complexity do not need to be extracted from the same layer. To this end, a novel frequency domain analysis of the feature maps of the same as well as of different network layers is proposed. In this way, the proposed method exploits more efficiently the knowledge that is stored in the actual CNN and facilitates in identifying the most discriminative features for every individual object type. Experimental results in a large-scale real-world Closed-Circuit Television (CCTV) surveillance and the PASCAL VOC 2012 datasets demonstrate the efficiency of the proposed approach.
The Oxidative Stress Response in Caenorhabditis elegans Requires the GATA Transcription Factor ELT-3 and SKN-1/Nrf2

Cellular damage caused by reactive oxygen species is believed to be a major contributor to age-associated diseases. Previously, we characterized the Caenorhabditis elegans Brap2 ortholog (BRAP-2) and found that it is required to prevent larval arrest in response to elevated levels of oxidative stress. Here, we report that C. elegans brap-2 mutants display increased expression of SKN-1-dependent, phase II detoxification enzymes that is dependent on PMK-1 (a p38 MAPK C. elegans ortholog). An RNA-interference screen was conducted using a transcription factor library to identify genes required for increased expression of the SKN-1 target gst-4 in brap-2 mutants. We identified ELT-3, a member of the GATA transcription factor family, as a positive regulator of gst-4p::gfp expression. We found that ELT-3 interacts with SKN-1 to activate gst-4 transcription in vitro and that elt-3 is required for enhanced gst-4 expression in the brap-2(ok1492) mutant in vivo. Furthermore, nematodes overexpressing SKN-1 required ELT-3 for life-span extension. Taken together, these results suggest a model where BRAP-2 acts as negative regulator of SKN-1 through inhibition of p38 MAPK activity, and that the GATA transcription factor ELT-3 is required along with SKN-1 for the phase II detoxification response in C. elegans.
The Protective Effect of Turnip Leaves Against Oxidative Stress Induced by High Cholesterol Diet in Adult Rats

The aim of the present study was to investigate the protective effect of turnip leaves against oxidative stress induced by high cholesterol diet in adult rats. Five groups of rats were used for 4 weeks, group (1) fed on basal diet (negative group), group (2) fed high cholesterol-diet (positive group), groups (3), (4) and (5) were fed high cholesterol-diets with addition of turnip leaves at three levels of intake (5, 10 and 15%, respectively). Results revealed that positive control group had significant increase in serum levels of total cholesterol (TC), triglycerides (TG), LDL-C, VLDL-C, ALT, AST, creatinine and urea as well as malondialdahyde (MOD) and nitric oxide (NO). However, there was significant decrease in serum level of HDL-C; total antioxidant capacity (TAC) and superoxide dismutase (SOD) compared to the negative control groups. Rats fed on high cholesterol diet at different levels of turnip leaves showed significant reduction in serum levels of TG, TC, LDL-C, VLDL-C, ALT, AST, creatinine, urea, MOD and NO, but significant increased in serum level HDL-C, TAC and SOD compared to the positive control group. Nutrition education programs are needed to inform the public about the importance of turnip leaves in decreasing the risk of heart disease.
Association between GRIN3A Gene Polymorphism in Kawasaki Disease and Coronary Artery Aneurysms in Taiwanese Children

Kawasaki disease (KD) is pediatric systemic vasculitis with the classic complication of coronary artery aneurysm (CAA). It is the leading cause of acquired cardiovascular diseases in children. Some severe cases present with multi-organ involvement or neurological dysfunction. To identify the role of the glutamate receptor, ionotropic, N-methyl-d-aspartate 3A (GRIN3A) in KD, we investigated genetic variations in GRIN3A in a Taiwanese cohort of 262 KD patients (76 with and 186 without CAA complications). We used univariate and multivariate regression analyses to identify the associations between clinical characteristics and GRIN3A genetic variations in KD. According to univariate regression analysis, CAA formation in KD was significantly associated with fever duration (p < 0.0001), first Intravenous immunoglobulin (IVIG) used (days after day one of fever) (p < 0.0001), and the GRIN3A (rs7849782) genetic variant (p < 0.001). KD patients with GG+GC genotype showed a lower rate of developing CAA (GG+GC genotype: odds ratio = 0.26; 95% CI = 0.14–0.46). Significant associations were identified between KD with CAA complication and the GRIN3A (rs7849782) genetic variant by using multivariate regression analysis. Specifically, significant correlations were observed between KD with CAA complications and the presence of GG+GC genotypes for the GRIN3A rs7849782 single-nucleotide polymorphism (full model: odds ratio = 0.25; 95% CI = 0.14–0.46). Our results suggest that a polymorphism of the GRIN3A gene may play a role in KD pathogenesis.
Draft Genome Sequence of a Taxonomically Unique Acinetobacter Clinical Strain with Proteolytic and Hemolytic Activities

ABSTRACT Acinetobacter sp. strain A47, which has been recovered from several soft tissue samples from a patient undergoing reconstructive surgery due to a traumatic amputation, was categorized as a taxonomically unique bacterial strain. The molecular analysis based on three housekeeping protein-coding genes (16S rRNA, rpoB, and gyrB) showed that strain A47 does not belong to any of the hitherto known taxa and may represent a previously undescribed Acinetobacter species.
Readability Enhancement of Low Light Videos Based on Discrete Wavelet Transform

In this paper, we propose readability enhancement of low light videos based on discrete wavelet transform (DWT). Captured videos under the low light condition have a narrow dynamic range (low contrast) with a dark tone as well as are highly corrupted by noise. We achieve both contrast enhancement and noise reduction in low light videos using wavelet coefficients. First, we perform normalization to stretch a dynamic range of an image. Then, we decompose the image into high-pass and low-pass sub-bands using DWT. Next, we perform de-noising and weak edge enhancement in the high-pass sub-bands (LH, HL, HH) and contrast enhancement in the low-pass sub-band (LL). Finally, we conduct color correction to compensate for color distortions caused by contrast enhancement. Experimental results demonstrate that the proposed method outperforms state-of-the-art ones in contrast enhancement, noise reduction, and color reproduction in terms of both subjective and objective evaluations.
In-hospital and long-term mortality in infective endocarditis in injecting drug users compared to non-drug users: A retrospective study of 192 episodes

In a retrospective study, in-hospital and long-term mortality for patients with infective endocarditis (IE) was analysed. The study was conducted at a department of infectious diseases in Stockholm, Sweden. Mortality was compared between injecting drug users (IDUs) and patients without drug abuse (non-IDUs). 192 episodes of IE from 1995 to 2000 were analysed, 60 in IDUs and 135 in non-IDUs, median follow-up 4.4 y. Episodes were classified using the Duke criteria: 145 definite and 47 possible. Of 53 definite episodes in IDUs, 55% were right-sided IE and 43% left-sided IE (including combined left- and right-sided). Surgical treatment was used in 34/145 definite episodes, all being left-sided IE. The in-hospital mortality was 14/145 (9.6%). There was no difference in in-hospital mortality between patient groups with left-sided IE. The IDU patients with left-sided IE had a higher long-term mortality with the increased mortality rate explained by late deaths in the surgically treated IDUs. Treatment results for IDUs with right-sided IE were good with no in-hospital mortality, no relapses and no increase in long-term mortality. This difference in prognosis between left-sided and right-sided IE in IDUs makes high quality echocardiography important to identify patients with left-sided IE and worse prognosis.
Solving Imperfect Information Games Using Decomposition

Decomposition, i.e. independently analyzing possible subgames, has proven to be an essential principle for effective decision-making in perfect information games. However, in imperfect information games, decomposition has proven to be problematic. To date, all proposed techniques for decomposition in imperfect information games have abandoned theoretical guarantees. This work presents the first technique for decomposing an imperfect information game into subgames that can be solved independently, while retaining optimality guarantees on the full-game solution. We can use this technique to construct theoretically justified algorithms that make better use of information available at run-time, overcome memory or disk limitations at run-time, or make a time/space trade-off to overcome memory or disk limitations while solving a game. In particular, we present an algorithm for subgame solving which guarantees performance in the whole game, in contrast to existing methods which may have unbounded error. In addition, we present an offline game solving algorithm, CFR-D, which can produce a Nash equilibrium for a game that is larger than available storage.
Speeding up the virtual light sources algorithm

The classical virtual light sources algorithm enables us to reuse complete shooting paths at the cost of a single shadow ray per pixel, thus it can solve the rendering equation efficiently. This paper proposes two techniques to speed up this algorithm. Since the tracing of the shadow rays is rather computation-intensive, it seems to be reasonable to trace them only where it is necessary. Firstly, the proposed method evaluates the contribution of the virtual sources without taking care of the visibility factor. Then, for each of these partially evaluated samples, we only complete the evaluation (by tracing the shadow ray), if the sample can have a significant effect on the result. Since the contributions can be computed independently of the visibility tests, we can utilize the computing power of the graphics card to increase performance. Namely, we shall discuss how the partially evaluated samples can be obtained quickly by the graphics card without increasing the load of the CPU.
A 2.4-Gsample/s DVFS FFT Processor for MIMO OFDM Communication Systems

This paper presents a new dynamic voltage and frequency scaling (DVFS) FFT processor for MIMO OFDM applications. By the proposed multimode multipath-delay-feedback (MMDF) architecture, our FFT processor can process 1-8-stream 256-point FFTs or a high-speed 256-point FFT in two processing domains at minimum clock frequency for DVFS operations. A parallelized radix-24 FFT algorithm is also employed to save the power consumption and hardware cost of complex multipliers. Furthermore, a novel open-loop voltage detection and scaling (OLVDS) mechanism is proposed for fast and robust voltage management. With these schemes, the proposed FFT processor can operate at adequate voltage/frequency under different configurations to support the power-aware feature. A test chip of the proposed FFT processor has been fabricated using UMC 90 nm single-poly nine-metal CMOS process with a core area of 1.88 times1.88 mm2 . The SQNR performance of this FFT chip is over 35.8 dB for QPSK/16-QAM modulation. Power dissipation of 2.4 Gsample/s 256-point FFT computations is about 119.7 mW at 0.85 V. Depending on the operation mode, power can be saved by 18%-43% with voltage scaling in TT corner.
A Hygroscopic Sensor Electrode for Fast Stabilized Non-Contact ECG Signal Acquisition

A capacitive electrocardiography (cECG) technique using a non-invasive ECG measuring technology that does not require direct contact between the sensor and the skin has attracted much interest. The system encounters several challenges when the sensor electrode and subject’s skin are weakly coupled. Because there is no direct physical contact between the subject and any grounding point, there is no discharge path for the built-up electrostatic charge. Subsequently, the electrostatic charge build-up can temporarily contaminate the ECG signal from being clearly visible; a stabilization period (3–15 min) is required for the measurement of a clean, stable ECG signal at low humidity levels (below 55% relative humidity). Therefore, to obtain a clear ECG signal without noise and to reduce the ECG signal stabilization time to within 2 min in a dry ambient environment, we have developed a fabric electrode with embedded polymer (FEEP). The designed hygroscopic FEEP has an embedded superabsorbent polymer layer. The principle of FEEP as a conductive electrode is to provide humidity to the capacitive coupling to ensure strong coupling and to allow for the measurement of a stable, clear biomedical signal. The evaluation results show that hygroscopic FEEP is capable of rapidly measuring high-accuracy ECG signals with a higher SNR ratio.
Electroporation-based delivery of cell-penetrating peptide conjugates of peptide nucleic acids for antisense inhibition of intracellular bacteria.

Cell penetrating peptides (CPPs) have been used for a myriad of cellular delivery applications and were recently explored for delivery of antisense agents such as peptide nucleic acids (PNAs) for bacterial inhibition. Although these molecular systems (i.e. CPP-PNAs) have shown ability to inhibit growth of bacterial cultures in vitro, they show limited effectiveness in killing encapsulated intracellular bacteria in mammalian cells such as macrophages, presumably due to difficulty involved in the endosomal escape of the reagents. In this report, we show that electroporation delivery dramatically increases the bioavailability of CPP-PNAs to kill Salmonella enterica serovar Typhimurium LT2 inside macrophages. Electroporation delivers the molecules without involving endocytosis and greatly increases the antisense effect. The decrease in the average number of Salmonella per macrophage under a 1200 V cm(-1) and 5 ms pulse was a factor of 9 higher than that without electroporation (in an experiment with a multiplicity of infection of 2 : 1). Our results suggest that electroporation is an effective approach for a wide range of applications involving CPP-based delivery. The microfluidic format will allow convenient functional screening and testing of PNA-based reagents for antisense applications.
Non-stop monitoring and debugging on shared-memory multiprocessors

Monitoring and debugging parallel programs is a difficult activity. There are many situations where the traditional "stop the world, I want to get off" approach to debugging is simply unsuitable. Frequently, nonintrusive monitoring of the program execution is more productive in locating sources of error and also in monitoring "correct" programs for such purposes as performance measurement and tuning. This paper presents a number of space- and time-efficient tools and techniques to support nonintrusive, non-stop monitoring and debugging of parallel programs running on a shared-memory multiprocessor. The techniques include the use of spy tasks, circular history buffers, vectors of use bits, and data structure audits. Particular emphasis is placed on issues that pertain to parallel computing, such as dealing with concurrent execution, shared memory and data caches.
Primary Transgenic Bovine Cells and Their Rejuvenated Cloned Equivalents Show Transgene-Specific Epigenetic Differences

Cell-mediated transgenesis, based on somatic cell nuclear transfer (SCNT), provides the opportunity to shape the genetic make-up of cattle. Bovine primary fetal fibroblasts, commonly used cells for SCNT, have a limited lifespan, and complex genetic modifications that require sequential transfections can be challenging time and cost-wise. To overcome these limitations, SCNT is frequently used to rejuvenate the cell lines and restore exhausted growth potential. We have designed a construct to be used in a 2-step cassette exchange experiment. Our transgene contains a puromycin resistance marker gene and an enhanced green fluorescence protein (EGFP) expression cassette, both driven by a strong mammalian promoter, and flanked by loxP sites and sequences from the bovine β-casein locus. Several transgenic cell lines were generated by random insertion into primary bovine cell lines. Two of these original cell lines were rederived by SCNT and new primary cells, with the same genetic makeup as the original donors, were established. While the original cell lines were puromycin-resistant and had a characteristic EGFP expression profile, all rejuvenated cell lines were sensitive to puromycin, and displayed varied EGFP expression, indicative of various degrees of silencing. When the methylation states of individual CpG sites within the transgene were analyzed, a striking increase in transgene-specific methylation was observed in all rederived cell lines. The results indicate that original transgenic donor cells and their rejuvenated derivatives may not be equivalent and differ in the functionality of their transgene sequences.