Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of Perforin Gene for Early Development of Nephrons in Olive Flounder (Paralichthys olivaceus)

The innate immune system is the only defense weapon that invertebrates have, and it is the fundamental defense mechanism for fish. The innate immune response is important in newly hatched flounders because it is closely involved in the initial feeding phase, which is why it is essential for survival during the juvenile period. The expression analysis of genes involved in the innate immune response in the olive flounder (Paralichthys olivaceus) in the days after hatching is incomplete. Therefore, we have begun to examine the expression patterns of genes specifically induced during the development of the innate immune system in newly hatched flounders. Microscopic observation showed that pronephron formation corresponded with the expression of perforin-encoding gene. These results suggest that perforin plays a vital role in the innate immunity of the kidney during developmental stages. Perforin expression was strong at the start of the development of the innate immune response, and continued throughout all the development stages. Our findings have important implications with respect to perforin’s biological role and the evolution of the first defense mechanisms in olive flounder. Further studies are required to elucidate the perforin-mediated innate immunity response and to decipher the functional role of perforin in developmental stages.
Annual cycles of organochlorine pesticide enantiomers in Arctic air suggest changing sources and pathways

Abstract. Air samples collected during 1994–2000 at the Canadian Arctic air monitoring station Alert (82°30' N, 62°20' W) were analysed by enantiospecific gas chromatography–mass spectrometry for α-hexachlorocyclohexane (α-HCH), trans-chlordane (TC) and cis-chlordane (CC). Results were expressed as enantiomer fractions (EF = peak areas of (+)/[(+) + (−)] enantiomers), where EFs = 0.5, 0.5 indicate racemic composition, and preferential depletion of (+) and (−) enantiomers, respectively. Long-term average EFs were close to racemic values for α -HCH (0.504 ± 0.004, n = 197) and CC (0.505 ± 0.004, n = 162), and deviated farther from racemic for TC (0.470 ± 0.013, n = 165). Digital filtration analysis revealed annual cycles of lower α-HCH EFs in summer–fall and higher EFs in winter–spring. These cycles suggest volatilization of partially degraded α-HCH with EF 0.5 during the cold season. The contribution of sea-volatilized α-HCH was only 11% at Alert, vs. 32% at Resolute Bay (74.68° N, 94.90° W) in 1999. EFs of TC also followed annual cycles of lower and higher values in the warm and cold seasons. These were in phase with low and high cycles of the TC/CC ratio (expressed as FTC = TC/(TC+CC)), which suggests greater contribution of microbially "weathered" TC in summer–fall versus winter–spring. CC was closer to racemic than TC and displayed seasonal cycles only in 1997–1998. EF profiles are likely to change with rising contribution of secondary emission sources, weathering of residues in the environment, and loss of ice cover in the Arctic. Enantiomer-specific analysis could provide added forensic capability to air monitoring programs.
Impulse purchasing: a qualitative exploration of the phenomenon

This paper reviews the literature on unplanned purchasing and impulse purchasing in particular. Various definitions and explanations of the phenomena are examined. Because impulse purchasing may often be deemed socially undesirable, it is argued that a qualitative research approach is particularly appropriate in order to gain maximum insight. A study employing enabling techniques (including self scripts, laddering and pyramiding) demonstrated that interviewees were remarkably consistent in their descriptions of the impulse purchase experience. There were, however, variations of the behaviour which might form the basis of a classification scheme. Most studies have only focused on retail impulse buying. This study explored the subject across both retail and direct buying contexts.
Fast DASH bootstrap

Adaptive HTTP Streaming has become a widespread technology for delivering video to the end users. However, this technology usually suffers from various latencies, requiring an initial delay before playback. This is problematic for low delay or interactive applications, such as gaming or live event webcasting. A long initial waiting time is perceived by most users as bad quality, or even non-working content. In this paper, we review the causes of initial delays in MPEG-DASH and common strategies used to reduce this latency. We propose a new method based on HTTP/1.1 and compatible with existing infrastructures for the initial setup of an MPEG-DASH session. We compare our proposal to several existing approaches based on HTTP/1.x and on the HTTP/2 server push technique. Our experimental results show that 2 RTTs can be avoided and that the total downloaded size is reduced by 25% when using HTTP/1.1 and by 20% in HTTP/2 with similar latency.
Lessons learned from designing the MONTIUM - a coarse-grained reconfigurable processing tile

In this paper we describe in retrospective the main results of a four year project, called Chameleon. As part of this project we developed a coarse-grained reconfigurable core for DSP algorithms in wireless devices denoted MONTIUM. After presenting the main achievements within this project we present the lessons learned from this project.
Auditor tenure and rotation

This article reviews global practices on auditor rotation and discusses the pros and cons of mandatory rotation. While many studies have examined auditor tenure and rotation, I argue that the literature has not yet answered the question as to whether mandatory rotation is desirable. The reason for this impasse is that there are major obstacles preventing us from doing research that can be used as a meaningful input to policy-making. I conclude with two suggestions that would help resolve this problem.
Chromosome Imbalance as a Driver of Sex Disparity in Disease

It has long been recognized that men and women exhibit different risks for diverse disorders ranging from metabolic to autoimmune diseases. However, the underlying causes of these disparities remain obscure. Analysis of patients with chromosomal abnormalities, including Turner syndrome (45X) and Klinefelter syndrome (47XXY), has highlighted the importance of X-linked gene dosage as a contributing factor for disease susceptibility. Escape from X-inactivation and X-linked imprinting can result in transcriptional differences between normal men and women as well as in patients with sex chromosome abnormalities. Animal models support a role for X-linked gene dosage in disease with O-linked N-acetylglucosamine transferase (OGT) emerging as a prime candidate for a pleiotropic effector. OGT encodes a highly regulated nutrient-sensing epigenetic modifier with established links to immunity, metabolism and development.
Association networks in time series data mining

We discuss a new method of time series data mining using moving approximation (MAP) transform and association measures based on MAP. MAP transform replaces time series values by slope values of lines approximating time series data in sliding window. An effective method of MAP transform calculation for time series with fixed time step is proposed. Based on MAP, a measure of local trend associations between time series is introduced. This measure is invariant under independent linear transformations of time series. Measure of local trend associations defines association function depending on the size of sliding window for each pare of considered time series. Based on association function, different association measures may be considered to measure local trend associations or global trend associations between time series. The methods of application of association measure to construction of association network of time series are discussed and illustrated on examples of synthetic and financial time series databases. Association networks give information about relationships between time dynamics of elements of systems given by time series databases.
CSHARP : Coherence and SHaring Aware Replacement Policies for Parallel Applications

Parallel applications are becoming mainstream and architectural techniques for multicores that target these applications are the need of the hour. Sharing of data by multiple threads and issues due to data coherence are unique to parallel applications. We propose CSHARP, a hardware framework that brings coherence and sharing awareness to any shared last level cache replacement policy. We use the degree of sharing of cache lines and the information present in coherence vectors to make replacement decisions. We apply CSHARP to a state-of-the-art cache replacement policy called TA-DRRIP to show its effectiveness. Our experiments on four core simulated system show that applying CSHARP on TADRRIP gives an extra 10% reduction in miss-rate at the LLC. Compared to LRU policy, CSHARP on TA-DRRIP shows a 18% miss-rate reduction and a 7% performance boost. We also show the scalability of our proposal by studying the hardware overhead and performance on a 8-core system. Keywords-Last-Level Cache, Replacement algorithm, Parallel Applications
Addressing Resource Fragmentation in Grids through Network-Aware Meta-scheduling in Advance

Grids are made of heterogeneous computing resources geographically dispersed where providing Quality of Service (QoS) is a challenging task. One way of enhancing the QoS perceived by users is by performing scheduling of jobs in advance, since reservations of resources are not always possible. This way, it becomes more likely that the appropriate resources are available to run the job when needed. One drawback of this scenario is that fragmentation appears as a well known effect in job allocations into resources and becomes the cause for poor resource utilization. So, a new technique has been developed to tackle fragmentation problems, which consists of rescheduling already scheduled tasks. To this end, some heuristics are implemented to calculate the intervals to be replanned and to select the jobs involved in the process. Moreover, another heuristic is implemented to put rescheduled jobs as close together as possible to minimize the fragmentation. This technique has been tested using a real test bed.
Identification and expression of troponin T, a new marker on the surface of cultured tumor endothelial cells by aptamer ligand

The identification of a specific biomarker involves the development of new clinical diagnostic tools, and an in‐depth understanding of the disease at the molecular level. When new blood vessels form in tumor cells, endothelial cell production is induced, a process that plays a key role in disease progression and metastasis to distinct organs for solid tumor types. The present study reports on the identification of a new biomarker on primary cultured mouse tumor endothelial cells (mTECs) using our recently developed high‐affinity DNA aptamer AraHH001 (Kd = 43 nmol/L) assisted proteomics approach. We applied a strategy involving aptamer‐facilitated biomarker discovery. Biotin‐tagged AraHH001 was incubated with lysates of mTECs and the aptamer‐proteins were then conjugated with streptavidin magnetic beads. Finally, the bound proteins were separated by sodiumdodecyl sulfate polyacrylamide gel electrophoresis (SDS‐PAGE) with silver staining. We identified troponin T via matrix assisted laser desorption ionization‐time of flight (MALDI‐TOF) mass spectrometry, the molecular target of aptamer AraHH001, and its presence was confirmed by measuring mRNA, protein levels, western blot, immunostaining, a gel shift assay of AraHH001 with troponin T. We first report here on the discovery of troponin T on mTECs, a promising and interesting diagnostic tool in the development of antiangiogenic therapy techniques the involves the targeting of the tumor vasculature.
Higher-Order Demand-Driven Program Analysis ( draft )

We explore a novel approach to higher-order program analysis that brings ideas of on-demand lookup from first-order CFL-reachability program analyses to higher-order programs. The analysis needs to produce only a control-flow graph; it can derive all other information including values of variables directly from the graph. Several challenges had to be overcome, including how to build the control-flow graph on-the-fly and how to deal with nonlocal variables in functions. The resulting analysis is flowand context-sensitive with a provable polynomial-time bound. The analysis is formalized and proved correct and terminating, and an initial implementation is described. 1998 ACM Subject Classification F.3. 2. Semantics of Programming Languages
A Telerehabilitation Framework for Lower-Limb Functional Recovery

Wearable devices are driving the development of post-surgery rehabilitation procedures, also helping in reducing the recovery time and social costs. This paper presents a real-time monitoring framework aimed at supporting telerehabilitation sessions for lower-limbs functional recovery. The presented framework supports patients during the execution of rehabilitation exercises by monitoring the limb movements through a set of low-cost wearable sensors and providing them with multi-modal bio-feedback to enhance the quality of the performed actions. The system also assists the therapist in the definition of exercises tailored to the patient and enables the collection of historical data in cloud-based services for monitoring the effects of therapies and further analysis.
Detection of Masses from Mammograms Using Mass shape Pattern

The purpose of this study was to develop a new method for automated mass detection in digital mammographic images using mass shape pattern. Masses were detected using a two steps process. First, the pixels in the mammogram images were scanned in 8 directions, and regions of interest (ROI) were identified using various thresholds. Then, a mass shape pattern was used to categorize the ROI as true masses or non-masses based on their morphologies. Each pixel of a ROI was scanned with a mass shape pattern to determine whether there was a shape (part of a ROI) similar to the mass in the shape pattern. The similarity was controlled using two thresholds. If a shape was detected, then the coordinates of the shape were recorded as part of a true mass. To test the system’s efficiency, we applied this process to 52 mammogram images from the Mammographic Image Analysis Society (MIAS) database. Three hundred and thirty-two ROI were identified using the ROI specification methods. These ROI were classified using three mass shape pattern whose diameters were 10, 20 and 30 pixels. The results of this experiment showed that using the mass shape pattern with these diameters achieved sensitivities of 93%, 90% and 81% with 1.3, 0.7 and 0.33 false positives per image respectively. These results indicate that the detection performance of this shape pattern based algorithm is satisfactory, and may improve the performance of computer-aided analysis of mammographic images and early diagnosis of mammographic masses.
Strategic IT Alignment: A Model for Competitive Advantage

This study examines how and why strategic IT alignment can be used to create competitive advantage and to what extent information intensity affects this process. A model is tested to examine how and why strategic IT alignment can produce enhanced organizational knowledge that yields competitive advantage. The model differentiates between alignment between the business plan and IT plan (BP-ITP alignment) and alignment between the IT plan and business plan (ITP-BP alignment). Results support six of the eight hypotheses and conclude that information intensity is an important antecedent to strategic IT alignment, that strategic IT alignment is best explained by multiple constructs which operationalize both process and content measures, and that ITP-BP, but not BP-ITP, alignment is significantly related to the use of IT for competitive advantage.
Thinking Well of African Americans: Measuring Complimentary Stereotypes and Negative Prejudice

Racial prejudice toward African Americans has been largely measured and researched in terms of negative and hostile attitudes. However, there is considerable research to suggest the prevalence of evaluatively positive beliefs about Blacks (e.g., as athletic). A measure of Complimentary Stereotypes and Negative Prejudice (CSNP) is validated through exploratory and confirmatory factor analyses across 6 samples (N = 4,404). The 30-item CSNP consists of 2 subscales. The Complimentary Stereotypes (CS) scale measures evaluatively favorable stereotypes of Blacks in domains of athleticism, musical and rhythmic ability, and social/sexual competence. The Negative Prejudice (NP) scale corresponds with traditional hostile attitudes related to the inferiority of Blacks, opposition to race-related policies, and aversion to interracial contact. The CSNP subscales demonstrated appropriate convergent and discriminant validity with other measures of prejudice, and 2 additional studies supported the validity of CS and NP in evaluating positive and negative subgroups of African Americans.
Barriers to Adoption of Methane Digester Technology on California Dairies

The goal of this research was to analyze the barriers to adoption of methane digesters on California dairies. Methane digesters have long existed as a technology in the dairy industry, both in the United States and abroad. Much research has been done to attest to the viability and economic sustainability of methane digesters; however in 2014, there were 26 dairies in California that have methane digesters installed, and of these, only 17 of those were still in operation, according to the USEPA AgStar Anaerobic Digester Database. Hence, the question remains, as to why this technology has not been widely adopted at the farm level. Of the 12 interviews conducted, four were with dairies which housed operational digesters. Four more assessed dairies where digesters were no longer operational and an additional four were conducted with dairies that were considering implementing this technology. Results from the interviews were analyzed using qualitative methods to categorize and interpret the textual data collected. The study found a low level of understanding or competence in the amount of training and technical support necessary for dairy farmers in the installation, operation and long-term maintenance of methane digesters. The study identified initial costs of implementing combined with low negotiated energy prices and changing emissions regulations were among the main reasons for a lack of adoption in California. In addition, the study found geographic location and changing emissions regulations were main factors in the success or failure of this technology. Furthermore, the studies observed those dairies with a third party management contract were the most successful with their digester systems. Most participants of this study view the widespread adoption at the farm level as unlikely at this time. Obispo, for all their help and support in the completion of this study. Thanks to my committee chair, Dr. Wayne Howard, who gave the idea, inspiration and unfailing support for this most interesting and progressive topic. insides and constructive analysis of the issues surrounding this topic. Thanks to my family and friends for their support and enthusiasm over the years in aiding me along the path to completion, and to my very understanding and gracious husband.
Grouping Multivariate Time Series : A Case Study

We present a case study to demonstrate a process for grouping massive multivariate time series based on nonp arametric statistical summaries aided by information visualization. We want a method that allows us to quickly find approximate groups in time series, both to identify typical aggregate be haviors and to find aberrant outliers. We use simple statistical summaries to capture the temporal nature and variability of the time series, as well as the interaction between the various multivariate components. Each individual time series is mapped to a fixed-length vector of summaries. T he summary vectors are then clustered using any fast clusterin g algorithm like -means. Appropriate information visualization techniques are used at every stage to guide the analyst. Beca use the method is nonparametric, it is customizable and flexible , and it generalizes easily. When choosing the statistical summa ries, we can incorporate domain knowledge that may enhance the clust ering. We demonstrate with a massive real life telecommunicat ions application.
Discriminative Slot Detection Using Kernel Methods

Most traditional information extraction approaches are generative models that assume events exist in text in certain patterns and these patterns can be regenerated in various ways. These assumptions limited the syntactic clues being considered for finding an event and confined these approaches to a particular syntactic level. This paper presents a discriminative framework based on kernel SVMs that takes into account different levels of syntactic information and automatically identifies the appropriate clues. Kernels are used to represent certain levels of syntactic structure and can be combined in principled ways as input for an SVM. We will show that by combining a low level sequence kernel with a high level kernel on a GLARF dependency graph, the new approach outperformed a good rule-based system on slot filler detection for MUC-6.
MPPT Controller Design Using Fuzzy-BBBC Method

Maximum power point tracking is considered to be an efficiency improving method applicable to the solar arrays. In this paper, Fuzzy-Big Bang-Big Crunch algorithm is applied in tracking of maximum power point. Simulation has been done in both MATLAB software where comparison made between Fuzzy-Big Bang and Fuzzy algorithm-alone. It has shown that in various temperatures and irradiations, optimized duty cycle achieved by proposed method is closer than fuzzy logic method to the values previously expressed in the referred source. Using those calculated values, the maximum error in Fuzzy-Big Bang method is only 0.0028 where fuzzy logic shows 0.0088. That is, the maximum error is reduced by 6.67% also efficiency of the system with Fuzzy-Big Bang algorithm is 5% improved in comparison with the Fuzzy method. The tracking system will quickly adapt itself even in rapidly environmental changes.
A New Thalamic Pathway of Vibrissal Information Modulated by the Motor Cortex

Three ascending pathways of information processing have been identified so far in the vibrissal system of rodents. In the ventral posterior medial nucleus of the thalamus, two of these pathways convey information through the core and tail of barrel-associated structures, called barreloids. The other pathway transits through the posterior group nucleus. The present study provides anatomical and electrophysiological evidence for the existence of an additional pathway that passes through the head of the barreloids. This pathway arises from multiwhisker-responsive cells in the principal trigeminal nucleus and differs from the classic lemniscal pathway, in that constituent thalamic cells have multiwhisker receptive field and receive corticothalamic input from lamina 6 of the vibrissa motor cortex. It is suggested that this pathway might be involved in relaying signals encoding phase of whisker motion during free whisking.