Miracle-dz/UniFAR-FTUs huggingface dataset:
A WordNet-Based Near-Synonyms and Similar-Looking Word Learning System

Near-Synonyms and Similar-Looking (NSSL) words can create confusion for English as Foreign Language Learners as a result of a type of lexical error that often occurs when they confuse similar-looking words that are near synonyms to have the same meaning. Particularly, this may occur if the similar-looking words have the same translated meaning. This study proposes a method to find these NSSL words and designed three experiments to investigate whether NSSL matching exercises could increase Chinese EFL learners' awareness of NSSL words. Three primary findings arose from the study. First, a performance evaluation of the experiment showed good results and determined that the method extracted suitable NSSL words whose meaning EFL learners may confuse. Secondly, the analysis results of the evaluation of Computer Assisted Language Learning (CALL) software showed that this system is practical for language learning, but lacks authenticity. Thirdly, a total of ninety-two Chinese students participated in this study and the findings indicated that students increased awareness of NSSL words and improved in ability of NSSL word distinction while still maintaining the knowledge one month after they had completed the matching exercises. Additionally, students’ feedback expressed that they had benefited from discovery learning and that they thought it was not difficult to discover the differences among NSSL words. Further research might extend the method proposed in this study to distracter choice of automatic question generation.
Low‐SDS Blue native PAGE

SDS normally is strictly avoided during Blue native (BN) PAGE because it leads to disassembly of protein complexes and unfolding of proteins. Here, we report a modified BN‐PAGE procedure, which is based on low‐SDS treatment of biological samples prior to native gel electrophoresis. Using mitochondrial OXPHOS complexes from Arabidopsis as a model system, low SDS concentrations are shown to partially dissect protein complexes in a very defined and reproducible way. If combined with 2‐D BN/SDS‐PAGE, generated subcomplexes and their subunits can be systematically investigated, allowing insights into the internal architecture of protein complexes. Furthermore, a 3‐D BN/low‐SDS BN/SDS‐PAGE system is introduced to facilitate structural analysis of individual protein complexes without their previous purification.
Dead-End Driven Learning

The paper evaluates the effectiveness of learning for speeding up the solution of constraint satisfaction problems. It extends previous work (Dechter 1990) by introducing a new and powerful variant of learning and by presenting an extensive empirical study on much larger and more difficult problem instances. Our results show that learning can speed up backjumping when using either a fixed or dynamic variable ordering. However, the improvement with a dynamic variable ordering is not as great, and for some classes of problems learning is helpful only when a limit is placed on the size of new constraints learned.
Context Moderates Priming Effects on Financial Risk Taking

Previous research has shown that risk preferences are sensitive to the financial domain in which they are framed. In the present paper, we explore whether the effect of negative priming on risk taking is moderated by financial context. A total of 120 participants completed questionnaires, where risky choices were framed in six different financial scenarios. Half of the participants were allocated to a negative priming condition. Negative priming reduced risk-seeking behaviour compared to a neutral condition. However, this effect was confined to non-experiential scenarios (i.e., gamble to win, possibility to lose), and not to ‘real world’ financial products (e.g., pension provision). The results call into question the generalisability of priming effects on different financial contexts.
Towards New Antifolates Targeting Eukaryotic Opportunistic Infections

ABSTRACT Trimethoprim, an antifolate commonly prescribed in combination with sulfamethoxazole, potently inhibits several prokaryotic species of dihydrofolate reductase (DHFR). However, several eukaryotic pathogenic organisms are resistant to trimethoprim, preventing its effective use as a therapeutic for those infections. We have been building a program to reengineer trimethoprim to more potently and selectively inhibit eukaryotic species of DHFR as a viable strategy for new drug discovery targeting several opportunistic pathogens. We have developed a series of compounds that exhibit potent and selective inhibition of DHFR from the parasitic protozoa Cryptosporidium and Toxoplasma as well as the fungus Candida glabrata. A comparison of the structures of DHFR from the fungal species Candida glabrata and Pneumocystis suggests that the compounds may also potently inhibit Pneumocystis DHFR.
Doxazosin, an α-1-adrenergic-receptor Antagonist, for Nightmares in Patients with Posttraumatic Stress Disorder and/or Borderline Personality Disorder: a Chart Review

Abstract Objective: Centrally active α-1-adrenergic-receptor antagonists such as prazosin are effective in the treatment of nightmares in patients with posttraumatic stress disorder (PTSD). A pharmacological alternative is doxazosin, which has a longer half-life and fewer side effects. However, doxazosin is currently being used without solid empirical evidence. Furthermore, no study so far has assessed the effects of α-1-antagonists on nightmares in patients with borderline personality disorder (BPD). We retrospectively assessed the effectiveness of doxazosin on nightmares in PTSD and BPD. Method: A retrospective chart review of patients treated with doxazosin for trauma-associated nightmares in our clinic was performed. As in previous prazosin studies, the B2 score of the Clinician-Administered PTSD Scale (CAPS) was used as the primary outcome measure. Furthermore, the Pittsburgh Sleep Quality Index-Addendum for PTSD (PSQI-A) and sleep logs were analyzed. Results: We identified 51 patients with PTSD and/or BPD (mean age 35.7 years, 92.3% women) who received doxazosin for nightmares. Of these, 46 patients continued doxazosin over a 4-week period and 31 patients over a 12-week period. Within the 12-week period, doxazosin treatment significantly reduced nightmares regardless of PTSD/BPD. 25 percent of patients treated for 12 weeks had full remission of nightmares. PSQI-A scores indicated that additional trauma-associated sleep symptoms improved over 12 weeks. Furthermore, recuperation of sleep improved with doxazosin within the first 4 weeks of treatment. Conclusion: Doxazosin might improve trauma associated nightmares and more general sleep parameters in patients with PTSD and BPD. Randomized controlled trials are warranted.
A compact low-power vertical filter for very-high-frequency applications

A design approach for realising a low-power/low-voltage current-mode filter operating around 1 GHz region is presented. The key element of the filter is the biquadratic filter inherently implemented from a conventional regulated cascode structure. By vertically stacking these biquads, a high-order very-high-frequency filter can be realised with very-low power consumption. For demonstration, a 4/sup th/ order Chebyshev filter operating at the cutoff frequency of 1 GHz is implemented. Under 2.4 V supply voltage, the simulation results indicate that the filter exhibits 42.4 dB spurious-free dynamic range (SFDR), 44.9 dB 1%-THD dynamic range and 710 /spl mu/W power consumption.
A Refinement-Tree Based Partitioning Method for Adaptively Refined Grids

An adaptive multigrid method solves an elliptic partial differential equation (PDE) by beginning with a very coarse grid and cycling through phases of adaptive refinement of the grid and multigrid solution of the linear system of equations resulting from discretization of the PDE on the adaptive grid. In a parallel adaptive multigrid method, the adaptive refinement phase can cause the load balance over the processors to become unequal. If the load is too unbalanced, the grid must be repartitioned and redistributed before continuing with the solution phase. An important part of a parallel adaptive multigrid method is the method for determining this partition. In this context, it must not only produce equal sized sets to balance the load and minimize cut edges to reduce communication, but must also be very fast to not dominate the computation time of fast multigrid, and must produce similar partitions for the refinement of a grid to reduce redistribution costs. In this paper we present the K-way Refinement Tree (RTK) partitioning method, a new method for partitioning grids that were created by adaptive refinement. The method uses a weighted tree representation of the refinement process that created the grid. A traversal of the tree sums the weights of the nodes. A second traversal of the tree places subtrees into sets to quickly determine equallyweighted connected partitions.
On the complexity of solving a bivariate polynomial system

We study the complexity of computing the real solutions of a bivariate polynomial system using the recently presented algorithm Bisolve [2]. Bisolve is an elimination method which, in a first step, projects the solutions of a system onto the x- and y-axes and, then, selects the actual solutions from the so induced candidate set. However, unlike similar algorithms, Bisolve requires no genericity assumption on the input, and there is no need for any kind of coordinate transformation. Furthermore, extensive benchmarks as presented in [2] confirm that the algorithm is highly practical, that is, a corresponding C++ implementation in Cgal outperforms state of the art approaches by a large factor. In this paper, we focus on the theoretical complexity of Bisolve. For two polynomials f, g ∈ Z[x, y] of total degree at most n with integer coefficients bounded by 2τ, we show that Bisolve computes isolating boxes for all real solutions of the system f = g = 0 using O(n8 + n7τ) bit operations, thereby improving the previous record bound for the same task by several magnitudes.
Automated tree detection and density calculation using unmanned aerial vehicles

Growth monitoring in tree plantation farms plays a crucial role in taking necessary actions from early stages to improve harvesting efficiency. Unmanned aerial vehicles (UAVs) provide a fast and efficient way to acquire data from large farms with difficult access. We propose a novel end-to-end system composed of multiple stages to identify areas where seeds have not grown as expected in young tree farms. The system acquires data from UAV flights to generate georeferenced orthophoto images. Next, local binary patterns, distance transform, and watershed segmentation methods are applied on images to detect trees. Finally, tree density distributions are calculated in the granularity of approximately 90 m2 tiles. We assessed the system performance by comparing detection results against a ground truth set of over 50000 trees from 16 orthophoto images for two tree species. The median deviation was 2 trees per tile for both species, where the median tree count was 14 and 9 per tile, respectively.
Production , Manufacturing and Logistics Vendor evaluation with performance variability : A max – min approach

The importance of incorporating multi-dimensional information into vendor evaluation is well established in the literature. Over the years, several multi-criteria techniques have been proposed for effective evaluation and selection of vendors. However, these models have not considered performance variability measures in evaluating alternative vendors. It is critical for the buyer to derive and incorporate such type of measures into the evaluation process because it provides for a more accurate portrayal of vendor s performance. This paper fills this gap by proposing a max–min productivity based approach that derives vendor performance variability measures, which are then utilized in a nonparametric statistical technique in identifying vendor groups for effective selection. The primary advantage of this technique is that it provides the buyer with effective alternative choices within a vendor group. Thus, allowing the buyer to base the final decision on other intangible factors that could not be incorporated into the analysis. The model application is demonstrated through a previously reported dataset from a pharmaceutical company. 2002 Elsevier Science B.V. All rights reserved.
Albumin: Pathophysiologic basis of its role in the treatment of cirrhosis and its complications

Since the introduction of human serum albumin as a plasma expander in the 1940s, considerable research has allowed a better understanding of its biochemical properties and potential clinical benefits. Albumin has a complex structure, which is responsible for a variety of biological functions. In disease, the albumin molecule is susceptible to modifications that may alter its biological activity. During the last decades, different methods to measure albumin function have been developed. Recent studies have shown that not only albumin concentration but also albumin function is reduced in liver failure. This observation led to the concept of effective albumin concentration, which represents the fact that plasma albumin concentration does not reflect its function. Indeed, in liver disease albumin function is several times less than its concentration. In patients with cirrhosis, albumin infusion reduces mortality in patients with spontaneous bacterial peritonitis and improves outcome following large volume paracentesis. In combination with vasoconstrictors, albumin is useful in the management of patients with hepatorenal syndrome. Its role is being investigated in a large number of indications, which rely on its volume and nonvolume expansion functions such as stroke, severe sepsis, Alzheimer's disease, malaria, burns, and ovarian hyperstimulation syndrome. This review explores the above concepts, reviews the available evidence for the use of albumin in liver diseases, defines therapeutic limitations, and explores the challenges that should be addressed in future research. (Hepatology 2013;58:1836–1846)
Altered distributions of Gemini of coiled bodies and mitochondria in motor neurons of TDP-43 transgenic mice

TAR DNA-binding protein-43 (TDP-43), a DNA/RNA-binding protein involved in RNA transcription and splicing, has been associated with the pathophysiology of neurodegenerative diseases, including ALS. However, the function of TDP-43 in motor neurons remains undefined. Here we use both gain- and loss-of-function approaches to determine roles of TDP-43 in motor neurons. Mice expressing human TDP-43 in neurons exhibited growth retardation and premature death that are characterized by abnormal intranuclear inclusions composed of TDP-43 and fused in sarcoma/translocated in liposarcoma (FUS/TLS), and massive accumulation of mitochondria in TDP-43-negative cytoplasmic inclusions in motor neurons, lack of mitochondria in motor axon terminals, and immature neuromuscular junctions. Whereas an elevated level of TDP-43 disrupts the normal nuclear distribution of survival motor neuron (SMN)-associated Gemini of coiled bodies (GEMs) in motor neurons, its absence prevents the formation of GEMs in the nuclei of these cells. Moreover, transcriptome-wide deep sequencing analysis revealed that a decrease in abundance of neurofilament transcripts contributed to the reduction of caliber of motor axons in TDP-43 mice. In concert, our findings indicate that TDP-43 participates in pathways critical for motor neuron physiology, including those that regulate the normal distributions of SMN-associated GEMs in the nucleus and mitochondria in the cytoplasm.
Controlled Introduction of Defects to Delafossite Metals by Electron Irradiation

The delafossite metals PdCoO$_{2}$, PtCoO$_{2}$ and PdCrO$_{2}$ are among the highest conductivity materials known, with low temperature mean free paths of tens of microns in the best as-grown single crystals. A key question is whether these very low resistive scattering rates result from strongly suppressed backscattering due to special features of the electronic structure, or are a consequence of highly unusual levels of crystalline perfection. We report the results of experiments in which high energy electron irradiation was used to introduce point disorder to the Pd and Pt layers in which the conduction occurs. We obtain the cross-section for formation of Frenkel pairs in absolute units, and cross-check our analysis with first principles calculations of the relevant atomic displacement energies. We observe an increase of resistivity that is linear in defect density with a slope consistent with scattering in the unitary limit. Our results enable us to deduce that the as-grown crystals contain extremely low levels of in-plane defects of approximately $0.001\%$. This confirms that crystalline perfection is the most important factor in realizing the long mean free paths, and highlights how unusual these delafossite metals are in comparison with the vast majority of other multi-component oxides and alloys. We discuss the implications of our findings for future materials research.
Design error diagnosis and correction via test vector simulation

With the increase in the complexity of digital VLSI circuit design, logic design errors can occur during synthesis. In this paper, we present a test vector simulation-based approach for multiple design error diagnosis and correction. Diagnosis is performed through an implicit enumeration of the erroneous lines in an effort to avoid the exponential explosion of the error space as the number of errors increases. Resynthesis during correction is as little as possible so that most of the engineering effort invested in the design is preserved. Since both steps are based on test vector simulation, the proposed approach is applicable to circuits with no global binary decision diagram representation. Experiments on ISCAS'85 benchmark circuits exhibit the robustness and error resolution of the proposed methodology. Experiments also indicate that test vector simulation is indeed an attractive technique for multiple design error diagnosis and correction in digital VLSI circuits.
Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion‐weighted imaging and MRS

The aim of this study was to determine whether tumor size, MRS parameters and apparent diffusion coefficient (ADC) measurements could be applied to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Ninety patients with breast cancer (median size, 4.5 cm; range, 1.6–9.5 cm) were evaluated with single‐voxel 1H MRS and dynamic contrast‐enhanced MRI. Diffusion‐weighted imaging was performed in 41 of these patients using a 1.5‐T scanner before and after completion of NAC. Pre‐ and post‐treatment measurements and changes in tumor size, MRS parameters [absolute and normalized total choline‐containing compound (tCho) integral and tCho signal‐to‐noise ratio (SNR)] and ADCs in pCR versus non‐pCR were compared using the nonparametric Mann–Whitney test. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of each parameter. After NAC, 30 patients (33%) showed pCR and 60 (67%) showed non‐pCR. At pretreatment, ADC was the only significant parameter in differentiating between pCR and non‐pCR [(0.83 ± 0.05) × 10–3 versus (0.97 ± 0.14) × 10–3 mm2/s] (p = 0.014). Post‐treatment measurements after completion of NAC and changes in tumor size (both p < 0.001), MRS parameters (p = 0.027 and p = 0.020 for absolute tCho integral, p = 0.036 and p = 0.023 for normalized tCho integral, and p = 0.032 and p = 0.061 for tCho SNR) and ADC (p = 0.003 and p < 0.001) were significantly different between the pCR and non‐pCR groups, except for changes in tCho SNR. In ROC analysis, the areas under the ROC curve (AUCs) of 0.63–0.73 were obtained for tumor size and MRS parameters. AUCs for pre‐ and post‐treatment ADC and changes in ADC were 0.75, 0.80 and 0.96, respectively. The optimal cut‐off of the percentage change in ADC for predicting pCR was 40.7%, yielding 100% sensitivity and 91% specificity. Patients with pCR showed significantly lower pretreatment ADCs than those with non‐pCR. The change in ADC after NAC was the most accurate predictor of pCR. Copyright © 2012 John Wiley & Sons, Ltd.
The Splash 2 processor and applications

Splash 2 is an attached parallel processor in which the computing elements are user-programmable FPGA devices. The architecture of Splash 2 is designed to accelerate the solution of problems which exhibit at least modest amounts of temporal or data parallelism. Applications are developed by writing descriptions of algorithms in VHDL, which are then iteratively refined and debugged within a simulator. Once an application is determined to be functionally correct in simulation, it is compiled to a gate list and optimized by logic synthesis. The gate list is then mapped onto the FPGA architecture by automatic placement and routing tools to form a loadable FPGA object module. A C language library and a symbolic debugger comprise the execution environment. The Splash 2 system has been shown to be effective on a variety of applications, including text searching, sequence analysis, and image processing. <<ETX>>
Variable impedance control of a robot for cooperation with a human

Robots are expected to be human-friendly and to execute tasks in cooperation with humans. Control systems for such robots should be designed in order to adapt human characteristics. In this paper, a variable impedance control method for robot to cooperate with human is proposed. First, the human characteristics in a cooperative task between two humans are analyzed. It is confirmed that human characteristics can be expressed by a variable impedance model. Then, we make a robot and a human to execute a cooperative task. It is shown that the impedance parameters obtained in the experiment performed by two humans give the best characteristics to the robot for cooperation with the human.
Sensitivity and specificity should never be interpreted in isolation without consideration of other clinical utility metrics*

Abstract Objective: The purpose of this paper is to highlight the risks and pitfalls of interpreting sensitivity and specificity in isolation when evaluating the clinical utility of a new test/measure to predict a target behavior, disease, or condition. Method: This paper (a) provides a primer for a set of metrics that can be used to appropriately examine the clinical utility of a test/measure (i.e. test operating characteristics – TOC), and (b) provides a discussion regarding various interpretative considerations when using TOCs that supports the tenet of this paper. Conclusions: There are two primary conclusions. First, sensitivity and specificity should never be interpreted in isolation as a means for evaluating the clinical utility of a test/measure. When sensitivity and specificity are used in this manner, more often than not, this will result in erroneous and/or incomplete conclusions regarding the clinical utility of a new test/measure. Second, sensitivity and specificity values are important, but they must be interpreted in conjunction with other more relevant clinical utility metrics (e.g. positive predictive power and negative predictive power).