Miracle-dz/UniFAR-FTUs huggingface dataset:
USE OF CONTROL SPECIMENS IN FREEZING AND THAWING TESTING OF CONCRETE. TECHNICAL NOTE

The ability to assess a concrete's freezing and thawing durability is important for long-term evaluations of mix designs and of in-situ concrete. This technical note reviews ASTM C 666, Procedure A (American Society for Testing and Materials: Test Method for Resistance of Concrete to Rapid Freezing and Thawing), which was designed to provide an indication of the potential freezing and thawing durability of concrete in a freezing and thawing environment. Frost resistance of the concrete is based on a specified number of freeze-thaw cycles compared to the initial condition of the specimens. The principal objective of the investigation was to determine whether the use of control specimens improved interpretation of test data. The control specimens allow the effects of the deterioration process to be separated from the changes in the internal structure due to the hydration process as measured by the transverse frequency. Control specimen use provides a continuous reference for the test spcimens, giving a before and after picture for visual assessment.
Content-aware transmission with delay threshold in heterogeneous networks

With the popularity of smart devices, content based internet services are growing rapidly. Different from real-time services, the end-to-end delay requirements of the contents are much less stringent. In this paper, we consider the delay-tolerant content-aware delivery in two-tier heterogeneous wireless networks. Taking transmit power consumption into account, we propose a new transmission framework by pushing users from macrocells to small cells at the cost of tolerable delay. We model the tolerable delay of content delivery in a stochastic way by considering users' interests. In this model, we adopt a progressively decreasing interest function which treats the delay as its argument. A modified Black-Scholes model is adopted to model the interest function. Thus, there exists a tradeoff between users' experience and power consumption. We consider power efficiency under a certain level of quality of experience (QoE) to handle this tradeoff. A content-aware transmission scheme with the optimal power efficiency is proposed. Simulation results show that under the maximal power efficiency criterion, about 18% of power consumption is reduced while about 90% of users' interests is preserved.
Profiting from Regulation: An Event Study of the European Carbon Market

Tradable permit regulations have recently been implemented for climate change policy in many countries. One of the first mandatory markets was the EU Emission Trading System, whose first phase ran from 2005-07. Unlike taxes, permits expose firms to volatility in regulatory costs, but are typically accompanied by property rights in the form of grandfathered permits. In this paper, we examine the effect of this type of environmental regulation on profits. In particular, changes in permit prices affect: (1) the direct and indirect input costs, (2) output revenue, and (3) the carbon permit asset value. Depending on abatement costs, output price sensitivity, and permit allocation, these effects may vary considerably across industries and firms. We run an event study of the carbon price crash on April 25, 2006 by examining the daily stock returns for 90 stocks from carbon intensive industries and approximately 600 stocks in the broad EUROSTOXX index. In general, firms in industries that tended to be either carbon intensive, or electricity intensive, but not involved in international trade, were hurt by the decline in permit prices. In industries that were known to be net short of permits, the cleanest firms saw the largest declines in share value. In industries known to be long in permits, firms granted the largest allocations were most harmed.
Evolutionary Insights Based on SNP Haplotypes of Red Pericarp, Grain Size and Starch Synthase Genes in Wild and Cultivated Rice

The origin and domestication of rice has been a subject of considerable debate in the post-genomic era. Rice varieties have been categorized based on isozyme and DNA markers into two broad cultivar groups, Indica and Japonica. Among other well-known cultivar groups Aus varieties are closer to Indica and Aromatic varieties including Basmati are closer to Japonica, while deep-water rice varieties share kinship to both Indica and Japonica cultivar groups. Here, we analyzed haplotype networks and phylogenetic relationships in a diverse set of genotypes including Indian Oryza nivara/Oryza rufipogon wild rice accessions and representative varieties of four rice cultivar groups based on pericarp color (Rc), grain size (GS3) and eight different starch synthase genes (GBSSI, SSSI, SSIIa, SSIIb, SSIIIa, SSIIIb, SSIVa, and SSIVb). Aus cultivars appear to have the most ancient origin as they shared the maximum number of haplotypes with the wild rice populations, while Indica, Japonica and Aromatic cultivar groups showed varying phylogenetic origins of these genes. Starch synthase genes showed higher variability in cultivated rice than wild rice populations, suggesting diversified selection during and after domestication. O. nivara/O. rufipogon wild rice accessions belonging to different sub-populations shared common haplotypes for all the 10 genes analyzed. Our results support polyphyletic origin of cultivated rice with a complex pattern of migration of domestication alleles from wild to different rice cultivar groups. The findings provide novel insights into evolutionary and domestication history of rice and will help utilization of wild rice germplasm for genetic improvement of rice cultivars.
Promoting Success in the Introduction of Health Information Systems

The significant number of publications describing unsuccessful cases in the introduction of health information systems makes it advisable to analyze the factors that may be contributing to such failures. However, the very notion of success is not equally assumed in all publications. Based in a literature review, the authors argue that the introduction of systems must be based in an eclectic combination of knowledge fields, adopting methodologies that strengthen the role of organizational culture and human resources in this project, as a whole. On the other hand, the authors argue that the introduction of systems should be oriented by a previously defined matrix of factors, against which the success can be measured.
Clinical decision making and the expected value of information

Background The results of the HOPE study, a randomized clinical trial, provide strong evidence that 1) ramipril prevents the composite outcome of cardiovascular death, myocardial infarction or stroke in patients who are at high risk of a cardiovascular event and 2) ramipril is cost-effective at a threshold willingness-to-pay of $10 000 to prevent an event of the composite outcome. In this report the concept of the expected value of information is used to determine if the information provided by the HOPE study is sufficient for decision making in the US and Canada. Methods and results Using the cost-effectiveness data from a clinical trial, or from a meta-analysis of several trials, one can determine, based on the number of future patients that would benefit from the health technology under investigation, the expected value of sample information (EVSI) of a future trial as a function of proposed sample size. If the EVSI exceeds the cost for any particular sample size then the current information is insufficient for decision making and a future trial is indicated. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then there is sufficient information for decision making and no future trial is required. Using the data from the HOPE study these concepts are applied for various assumptions regarding the fixed and variable cost of a future trial and the number of patients who would benefit from ramipril. Conclusions Expected value of information methods provide a decision-analytic alternative to the standard likelihood methods for assessing the evidence provided by cost-effectiveness data from randomized clinical trials. Clinical Trials 2007; 4: 279—285. http://ctj.sagepub. com
Highly Active Combination of BRD4 Antagonist and Histone Deacetylase Inhibitor against Human Acute Myelogenous Leukemia Cells

The bromodomain and extra-terminal (BET) protein family members, including BRD4, bind to acetylated lysines on histones and regulate the expression of important oncogenes, for example, c-MYC and BCL2. Here, we demonstrate the sensitizing effects of the histone hyperacetylation-inducing pan–histone deacetylase (HDAC) inhibitor panobinostat on human acute myelogenous leukemia (AML) blast progenitor cells (BPC) to the BET protein antagonist JQ1. Treatment with JQ1, but not its inactive enantiomer (R-JQ1), was highly lethal against AML BPCs expressing mutant NPM1c+ with or without coexpression of FLT3-ITD or AML expressing mixed lineage leukemia fusion oncoprotein. JQ1 treatment reduced binding of BRD4 and RNA polymerase II to the DNA of c-MYC and BCL2 and reduced their levels in the AML cells. Cotreatment with JQ1 and the HDAC inhibitor panobinostat synergistically induced apoptosis of the AML BPCs, but not of normal CD34+ hematopoietic progenitor cells. This was associated with greater attenuation of c-MYC and BCL2, while increasing p21, BIM, and cleaved PARP levels in the AML BPCs. Cotreatment with JQ1 and panobinostat significantly improved the survival of the NOD/SCID mice engrafted with OCI-AML3 or MOLM13 cells (P < 0.01). These findings highlight cotreatment with a BRD4 antagonist and an HDAC inhibitor as a potentially efficacious therapy of AML. Mol Cancer Ther; 13(5); 1142–54. ©2014 AACR.
Low-Light Image Enhancement Using Adaptive Digital Pixel Binning

This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.
Atlas-based registration parameters in segmenting sub-cortical regions from brain MRI-images

Multi-atlas segmentation has been proved to perform well in segmenting sub-cortical structures from images. In this work, we study different components of multi-atlas segmentation and propose new techniques to improve the segmentation accuracy. We found that the use of gradient information in addition to standard normalised mutual information increases the registration accuracy. We also studied different techniques to select atlases in the multi-atlas segmentation. In addition, the expectation maximisation algorithm was used to combinemulti-atlas and intensity model information. The average similarity index obtained for six subcortical structures was 0.84.
Indentation Fracture Toughness of Sintered Silicon Carbide in the Palmqvist Crack Regime

This paper reports on the fracture toughness of a sintered dense {alpha}-SIC estimated by the Vickers indentation microfracture method in the low-load Palmqvist crack regime. It was observed that the use of simultaneously Vickers hardnesses does not yield reliable fracture toughness values, nor does application of the median-crack -derived equation. It is necessary to utilize a load-independent, crack-free hardness value with this toughness estimation method.
Hidden conditional random fields for phone classification

In this paper, we show the novel application of hidden conditional random fields (HCRFs) – conditional random fields with hidden state sequences – for modeling speech. Hidden state sequences are critical for modeling the non-stationarity of speech signals. We show that HCRFs can easily be trained using the simple direct optimization technique of stochastic gradient descent. We present the results on the TIMIT phone classification task and show that HCRFs outperforms comparable ML and CML/MMI trained HMMs. In fact, HCRF results on this task are the best single classifier results known to us. We note that the HCRF framework is easily extensible to recognition since it is a state and label sequence modeling technique. We also note that HCRFs have the ability to handle complex features without any change in training procedure.
High-bandwidth data dissemination for large-scale distributed systems

This article focuses on the multireceiver data dissemination problem. Initially, IP multicast formed the basis for efficiently supporting such distribution. More recently, overlay networks have emerged to support point-to-multipoint communication. Both techniques focus on constructing trees rooted at the source to distribute content among all interested receivers. We argue, however, that trees have two fundamental limitations for data dissemination. First, since all data comes from a single parent, participants must often continuously probe in search of a parent with an acceptable level of bandwidth. Second, due to packet losses and failures, available bandwidth is monotonically decreasing down the tree. To address these limitations, we present Bullet, a data dissemination mesh that takes advantage of the computational and storage capabilities of end hosts to create a distribution structure where a node receives data in parallel from multiple peers. For the mesh to deliver improved bandwidth and reliability, we need to solve several key problems: (i) disseminating disjoint data over the mesh, (ii) locating missing content, (iii) finding who to peer with (peering strategy), (iv) retrieving data at the right rate from all peers (flow control), and (v) recovering from failures and adapting to dynamically changing network conditions. Additionally, the system should be self-adjusting and should have few user-adjustable parameter settings. We describe our approach to addressing all of these problems in a working, deployed system across the Internet. Bullet outperforms state-of-the-art systems, including BitTorrent, by 25-70% and exhibits strong performance and reliability in a range of deployment settings. In addition, we find that, relative to tree-based solutions, Bullet reduces the need to perform expensive bandwidth probing.
Efficacy and safety of memantine in patients with moderate-to-severe Alzheimer's disease: results of a pooled analysis of two randomized, double-blind, placebo-controlled trials in Japan

Background: With the increase in the aging population, there is a pressing need to provide effective treatment options for individuals with Alzheimer's disease (AD). Memantine is an N-methyl-D-aspartate receptor antagonist used to treat AD in > 80 countries worldwide, and studies in the USA and Europe have shown it to be effective in improving language deficits; however, there are currently no data on language improvements in Japanese patients treated with memantine. Objectives: To clarify the efficacy and safety of memantine in Japanese outpatients with moderate to severe AD, using a pooled analysis of two multicenter randomized placebo-controlled trials, a phase 2 dose-finding study and a phase 3 study. Results: The final analysis comprised 633 patients (318 receiving memantine and 315 placebo). Memantine produced better outcomes in terms of Severe Impairment Battery-Japanese version, Clinician's Interview-Based Impression of Change plus-Japanese version, Behavioral Pathology in AD Rating Scale, and language scores, versus placebo. The overall incidence of adverse events and adverse reactions was similar between groups. Conclusion: In this pooled analysis of Japanese patients, memantine achieved better outcomes than placebo in terms of cognition, including attention, praxis, visuospatial ability and language, and behavioral and psychological symptoms, including activity disturbances and aggressiveness.
A robustness metric for cascading failures by targeted attacks in power networks

Cascading failures are the main reason blackouts occur in power networks. The economic cost of such failures is in the order of tens of billion dollars annually. In a power network, the cascading failure phenomenon is related to both topological properties (number and types of buses, density of transmission lines and interconnection of components) and flow dynamics (load distribution and loading level). Existing studies most often focus on network topology, and not on flow dynamics. This paper proposes a new metric to assess power network robustness with respect to cascading failures, in particular for cascading effects due to line overloads and caused by targeted attacks. The metric takes both the effect of topological features and the effect of flow dynamics on network robustness into account, using an entropy-based approach. Experimental verification shows that the proposed robustness metric quantifies a power grid robustness with respect to cascading failures.
Cardiac Autonomic Responses during Exercise and Post-exercise Recovery Using Heart Rate Variability and Systolic Time Intervals—A Review

Cardiac parasympathetic activity may be non-invasively investigated using heart rate variability (HRV), although HRV is not widely accepted to reflect sympathetic activity. Instead, cardiac sympathetic activity may be investigated using systolic time intervals (STI), such as the pre-ejection period. Although these autonomic indices are typically measured during rest, the “reactivity hypothesis” suggests that investigating responses to a stressor (e.g., exercise) may be a valuable monitoring approach in clinical and high-performance settings. However, when interpreting these indices it is important to consider how the exercise dose itself (i.e., intensity, duration, and modality) may influence the response. Therefore, the purpose of this investigation was to review the literature regarding how the exercise dosage influences these autonomic indices during exercise and acute post-exercise recovery. There are substantial methodological variations throughout the literature regarding HRV responses to exercise, in terms of exercise protocols and HRV analysis techniques. Exercise intensity is the primary factor influencing HRV, with a greater intensity eliciting a lower HRV during exercise up to moderate-high intensity, with minimal change observed as intensity is increased further. Post-exercise, a greater preceding intensity is associated with a slower HRV recovery, although the dose-response remains unclear. A longer exercise duration has been reported to elicit a lower HRV only during low-moderate intensity and when accompanied by cardiovascular drift, while a small number of studies have reported conflicting results regarding whether a longer duration delays HRV recovery. “Modality” has been defined multiple ways, with limited evidence suggesting exercise of a greater muscle mass and/or energy expenditure may delay HRV recovery. STI responses during exercise and recovery have seldom been reported, although limited data suggests that intensity is a key determining factor. Concurrent monitoring of HRV and STI may be a valuable non-invasive approach to investigate autonomic stress reactivity; however, this integrative approach has not yet been applied with regards to exercise stressors.
Semigroup and prefix computations on improved generalized mesh-connected computers with multiple buses

Various augmenting mechanisms have been proposed to enhance the communication efficiency of mesh-connected computers (MCCs). One major approach is to add nonconfigurable buses for improved broadcasting. A typical example is the mesh-connected computer with multiple buses (MMB). In this paper, we propose a new class of generalized MMBs, the improved generalized MMBs (IMMBs). Each processor in an IMMB is connected to exactly two buses. We show the power of IMMBs by considering semigroup and prefix computations. Specifically, we show that semigroup and prefix computations on N operands, and data broadcasting all take O(log N) time on IMMBs. This is the first O(log N) time algorithm for these problems on arrays with fixed broadcasting buses.
Capacitive Contact Imaging for Skin Measurements

Water in the skin, particularly in the outmost skin layer-the stratum corneum, plays a key role in the skin’s barrier functions as well as its cosmetic properties. However, the water distribution within the skin is not uniform, and to measure the water in the skin is very difficult. Although there are many skin hydration measurement instruments on the market, e.g. Corneometer (Courage+Khazaka electronic GmbH, Germany), DermaLab hydration probe (Cortex Technology, Denmark), MoistureMeter (Delfin Technologies, Finland), Moisture Checker (Scalar Corporation, Japan) and HydraTest (BeautyPro, UK) etc. their performances have left a lot to be desired. No technology can make accurate, absolute water content measurements, and no technology is imaging based.
The SARS coronavirus E protein interacts with the PALS1 and alters tight junction formation and epithelial morphogenesis

Intercellular tight junctions define epithelial apicobasal polarity and form a physical fence which protects underlying tissues from pathogen invasions. PALS1, a tight junction-associated protein, is a member of the CRUMBS3-PALS1-PATJ polarity complex, which is crucial for the establishment and maintenance of epithelial polarity in mammals. Here we report that the carboxy-terminal domain of the SARS-CoV E small envelope protein (E) binds to human PALS1. Using coimmunoprecipitation and pull-down assays, we show that E interacts with PALS1 in mammalian cells and further demonstrate that the last four carboxy-terminal amino acids of E form a novel PDZ-binding motif that binds to PALS1 PDZ domain. PALS1 redistributes to the ERGIC/Golgi region, where E accumulates, in SARS-CoV-infected Vero E6 cells. Ectopic expression of E in MDCKII epithelial cells significantly alters cyst morphogenesis and, furthermore, delays formation of tight junctions, affects polarity, and modifies the subcellular distribution of PALS1, in a PDZ-binding motif-dependent manner. We speculate that hijacking of PALS1 by SARS-CoV E plays a determinant role in the disruption of the lung epithelium in SARS patients.
A proteomic approach toward the selection of proteins with enhanced intrinsic conformational stability.

A detailed understanding of the molecular basis of protein folding and stability determinants partly relies on the study of proteins with enhanced conformational stability properties, such as those from thermophilic organisms. In this study, we set up a methodology aiming at identifying the subset of cytosolic hyperstable proteins using Sulfurispharea sp. , a hyperthermophilic archaeon, able to grow between 70 and 97 degrees C, as a model organism. We have thermally and chemically perturbed the cytosolic proteome as a function of time (up to 96 h incubation at 90 degrees C), and proceeded with analysis of the remaining proteins by combining one- and two-dimensional gel electrophoresis, liquid chromatography fractionation, and protein identification by N-terminal sequencing and mass spectrometry methods. In total, 14 proteins with enhanced stabilities which are involved in key cellular processes such as detoxification, nucleic acid processing, and energy metabolism were identified including a superoxide dismutase, a peroxiredoxin, and a ferredoxin. We demonstrate that these proteins are biologically active after extensive thermal treatment of the proteome. The relevance of these and other targets is discussed in terms of the organism's ecology. This work thus illustrates an experimental approach aimed at mining a proteome for hyperstable proteins, a valuable tool for target selection in protein stability and structural studies.