Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference Gene Selection and Evaluation for Gene Expression Studies Using qRT-PCR in the White-Backed Planthopper, Sogatella furcifera (Hemiptera: Delphacidae)

Abstract The white-backed planthopper, Sogatella furcifera (Hemiptera, Delphacidae), is one of the most devastating rice pests. For a better control strategy, various genetic studies have been conducted using reverse-transcription quantitative real-time polymerase chain reaction (qRT-PCR). The appropriate application of qRT-PCR requires reliable endogenous controls; however, studies on this aspect of the white-backed planthopper are lacking. In the present study, nine commonly used reference genes, elongation factor 1-α (EF1-α), polyubiquitin (UB), ribosomal protein S18 (RPS18), actin 1 (ACT), α-1 tubulin (TUB), glyceraldehyde-3-phosphate (GAPDH), ribosomal protein L9 (RPL9), ribosomal protein L10 (RPL10), and 18S ribosomal RNA (18S), were evaluated by qRT-PCR for their expression stability under four different experimental conditions (different developmental stages, acquisition of Southern rice black-streaked dwarf virus (SRBSDV), different tissues, and different temperature stress). These results were analyzed using four software programs (geNorm, NormFinder, BestKeeper, and the delta Ct method) and a Web-based comprehensive tool RefFinder to compare and rank candidate reference genes. According to the results of RefFinder analysis, which integrates the abovementioned four software programs, TUB was ranked as the most suitable reference gene at different developmental stages and under different temperature stress, and GAPDH and RPL9 showed the highest stability for acquisition of SRBSDV and different tissues, respectively. These results will provide a solid foundation for future gene expression study on the white-backed planthopper, and also will give aids in establishing a standardized qRT-PCR procedure for other related insects.
Big Data Analytics: The Case of Social Security Administration

Public agencies are investing significant resources in big data analytics to mine valuable information, predict future outcomes, and make data-driven decisions. In order to foster a strong understanding of the opportunities and challenges associated with the adoption of big data analytics in the public sphere, we analyze various efforts undertaken by the United States Social Security Administration (SSA). The SSA, which is commonly referred to as the "face of the government", collects, manages, and curates large volumes of data to provide Social Security services to US citizens and beneficiaries living abroad. The agency has made great strides in the burgeoning big data space to improve administration and delivery of services. This has included: (1) improving its arcane legacy system, (2) developing employee and end-user capability, (3) implementing data management strategies and organizational architecture, (4) managing security and privacy issues, and (5) advocating for increased investment in big data analytics. Despite these efforts, the SSA is still in the early stages of developing capability in the domain of big data analytics. By outlining challenges and opportunities facing the SSA, we discuss policy implications and explore issues to consider when public agencies begin to develop their capacity to analyze big data.
Climate and Conflict: Whence the Weather?

Abstract Researchers have increasingly sought to identify the social repercussions of an evolving climate. Several influential studies claim that climate change is responsible for increases in conflict, while other research finds no such evidence. Relating human-caused changes in the climate to conflict poses a basic endogeneity problem, though: accepting that industrial activity is responsible for altering the climate implies that human agency is indirectly involved in the impact of the climate on conflict. Specifically, industrial activity is closely tied to climate change and to rising economic development, the latter generally being accepted as a determinant of reductions in conflict. In this letter, we discuss this endogeneity problem, outline possible shortcomings for empirical research if this problem is not addressed, and propose a research strategy that might eventually help to overcome it effectively.
First Case of Fulminant Sepsis Due to Wohlfahrtiimonas chitiniclastica

ABSTRACT We report the first case of fulminant sepsis due to Wohlfahrtiimonas chitiniclastica. This case is also the first one reported in South America. We emphasize the importance of recognizing bacteria that live in the larvae of a parasitic fly as the causative agent of severe infections in homeless patients.
Differences between smokers and non‐smokers in regional gray matter volumes: a voxel‐based morphometry study

Magnetic resonance imaging (MRI) studies showed a link between chronic smoking and structural brain abnormalities. To date, little is known about the long‐term effects of smoking on gray matter deficiencies. MRI study was carried for 44 smokers and 44 matched non‐smokers to assess gray matter volume differences between the two groups. Decreased gray matter volumes were found in left thalamus, medial frontal cortex and anterior cingulate of smokers in comparison to controls. This voxel‐based morphometry study is showing reduction of regional gray matter volume in smokers, which might better guide future research into the pathogenesis of chronic smoking.
Pure Intermediate Products, Factor Intensities and Technical Progress in the Theory of International Trade

The literature on intermediate products in the context of international trade theory has been mainly confined to the traditional two-sector model in which allowance is made for interindustry flows between the two productive sectors. ' Although the incorporation of such flows has represented an improvement over the two-primary-factors only assumption, the emphasis placed on interindustry flows has resulted in the neglect of what may be called "pure" intermediate goods, that is, commodities which use primary factors in their production and are themselves solely utilized as inputs in producing the economy's final goods.2 The difference between the two models is far from trivial. Thus, for example, it has been shown by Vanek [11, 141-42] and Casas [3] that net and gross factor intensities always possess the same ranking in the presence of interindustry flows. From this, it follows that all the theorems which are expressed in terms of the ranking of the two final commodities' net labour-capital ratios, such as the Rybczynski theorem and the Stolper-Samuelson theorem, remain unscathed by the introduction of interindustry flows. Indeed, this has prompted Kemp [6, 148] to assert that the neglect of intermediate products in the earlier trade literature can be defended since all the results derived in their absence remain valid in their pres-
Programming abstractions for wireless multicasting in software-defined enterprise WLANs

The increasing demand for multimedia content and for live broadcasting is bringing renewed interest in multicast applications. In many cases, users access such streams using Wi-Fi networks. However, multicast over Wi-Fi poses several challenges including low-data rates and coexistence issues with regard to other unicast streams. Software Defined Networking (SDN) has recently emerged as a novel approach to network control and management. In this paper we present SDN@Play, a novel SDN-based solution for multicast rate-adaptation in Wi-Fi networks. The solution builds upon a new abstraction, named Transmission Policy which allows the SDN controller to reconfigure or replace a certain rate control policy if its optimal operating conditions are not met. An experimental evaluation carried out over a real-world testbed shows that this approach can deliver an improvement of up to 80% in terms of channel utilization compared to legacy 802.11 multicast. We release the entire implementation including the controller and the data-path under a permissive license for academic use.
Technical and scale efficiencies of meat goat farms in the USA

ABSTRACT This study determines i) scale and technical efficiencies, ii) marginal productive contributions for inputs and outputs and iii) efficiency drivers of meat goat farms in the USA. We estimate an input distance function (IDF) using a stochastic production frontier (SPF) technique. The average technical efficiency (TE) for the USA meat goat whole farm was 0.74. The operator education level, percentage of annual net farm income from the goat operation, regional differences and holding of an off farm job are the efficiency drivers of USA meat goat farms. We find increasing returns to scale (RTS) for USA meat goat farms. Our results suggest that USA meat goat farms can be scale efficient if their optimal size of operation is greater than approximately 64 goats or greater than 40 breeding does. Empirical Monte Carlo (MC) simulation techniques show the consistency of finite-sample properties for the input distance function.
'Early' mammalian myoblasts are resistant to phorbol ester-induced block of differentiation.

Mesenchymal cells were isolated from somites and limbs of mouse embryos at different developmental stages. When grown in tissue culture, some of the cells underwent muscle differentiation as indicated by synthesis of sarcomeric myosin, acetylcholine receptor and, in the case of limb cells, fusion into multinucleated myotubes. When the tumour promoter 12-O-tetradecanoyl phorbol 13-acetate (TPA) was added to these cultures, it caused differential effects, depending upon the age of the embryo from which cells were isolated. In cultures of somites or limb bud from embryos up to 12 days post coitum, TPA did not interfere with the appearance of differentiated muscle cells. When TPA was added to cultures from older embryos, it inhibited muscle differentiation with an efficiency which increased with the age of the embryo, reaching about 90% inhibition at 15 days. After this period, a new population of myogenic cells appeared in the limb, which were able to differentiate in the presence of TPA and represented the great majority of myoblasts after day 18 of embryonic development. The simplest interpretation of these data can be based on the existence of three major classes of myogenic cell precursors, which appear sequentially during muscle histogenesis: 'early' myoblasts, which appear resistant to tumour promoters; 'late' myoblasts, whose differentiation is inhibited by tumour promoters and 'satellite' cells which, like early myoblasts, show no sensitivity to TPA.
Tiba inhibition of in vitro organogenesis in excised tobacco leaf explants

SummaryTriiodobenzoic acid (TIBA), an anti-auxin, was found to inhibit both shoot and root formation in cultured excised leaf explants of tobacco (Nicotiana tabacum L.). The shoot formation (SF) medium used required only exogenous cytokinin (N6-benzyladenine) and the root formation (RF) medium required both auxin (indole-3-butyric acid) and cytokinin (kinetin). By transferring the explants from SF or RF media to SF or RF media with TIBA (4.0×10−5M), respectively or vice versa, at different times in culture, it was found that TIBA inhibition was at the time of meristemoid formation and after determination of organogenesis. This indicates that TIBA interfered with endogenous auxin involvement in organized cell division.
Association between quality of life of adolescents with type 1 diabetes and parents’ illness perception as evaluated by adolescents

Abstract Children and adolescents account for half of all cases of type 1 diabetes, which is one of the most common pediatric chronic diseases. The disease’s effects and the treatment/disease-management protocols patients must follow can lead to a marked deterioration in quality of life, especially for adolescents. Patients’ illness perceptions have been shown to impact their quality of life, but do other people’s illness perceptions also have an effect? The present study addressed this question by investigating possible links between the quality of life of adolescent patients with type 1 diabetes and illness perceptions, measured in terms of the adolescents’ self-perceptions, parents’ self-perceptions, and the adolescents’ evaluations of their parents’ perceptions. We asked 41 adolescents (M = 13.9 years; SD = 1.9) who had been undergoing treatment for type 1 diabetes for at least a year (M = 6.6 years; SD = 3.7) to complete the Diabetes Quality of Life for Youth Questionnaire-Short Form (DQOLY-SF) and the Illness Perception Questionnaire-Revised (IPQ-R). They completed the IPQ-R twice, once to state their own opinions (self-report) and once to give their evaluations of their parents’ perceptions. At the same time, but in a different room, their parents (N = 47) completed the IPQ-R (self-report). Quality of life was predicted by gender (p < .05) and by the parents’ emotional representations (p < .01) and perceptions of consequences (p < .01) as evaluated by the adolescents. This new approach provides new insights into the impact of parents’ perceptions on the quality of life of adolescents with type 1 diabetes.
RCU-HTM: Combining RCU with HTM to Implement Highly Efficient Concurrent Binary Search Trees

In this paper we introduce RCU-HTM, a technique that combines Read-Copy-Update (RCU) with Hardware Transactional Memory (HTM) to implement highly efficient concurrent Binary Search Trees (BSTs). Similarly to RCU-based algorithms, we perform the modifications of the tree structure in private copies of the affected parts of the tree rather than in-place. This allows threads that traverse the tree to proceed without any synchronization and without being affected by concurrent modifications. The novelty of RCU-HTM lies at leveraging HTM to permit multiple updating threads to execute concurrently. After appropriately modifying the private copy, we execute an HTM transaction, which atomically validates that all the affected parts of the tree have remained unchanged since they've been read and, only if this validation is successful, installs the copy in the tree structure.We apply RCU-HTM on AVL and Red-Black balanced BSTs and compare theirperformance to state-of-the-art lock-based, non-blocking, RCU- and HTM-basedBSTs. Our experimental evaluation reveals that BSTs implemented with RCU-HTMachieve high performance, not only for read-only operations, but also for update operations. More specifically, our evaluation includes a diverse range of tree sizes and operation workloads and reveals that BSTs based on RCU-HTM outperform other alternatives by more than 18%, on average, on a multi-core server with 44 hardware threads.
Growth Effects of Education and Social Capital in the OECD Countries

This paper surveys the empirical literature on the growth effects of education and social capital. The main focus is on the cross-country evidence for the OECD countries, but the paper also briefly reviews evidence from labour economics, to clarify where empirical work on education using macro data may be relatively useful. It is argued that on balance, the recent cross-country evidence points to productivity benefits of education that are at least as large as those identified by labour economists. The paper also discusses the implications of this finding. Finally, the paper reviews the emerging literature on the benefits of social capital. Since this literature is still in its early days, policy conclusions are accordingly harder to find.
Mirror‐symmetrical populations of wide‐field amacrine cells of the macaque monkey retina

Retinas of macaque monkeys were immunostained for glycogen phosphorylase (glypho). Glypho was localized to regular and displaced amacrine cells. Their processes occupied two narrow strata within the inner plexiform layer (IPL). The labeling pattern is reminiscent of cholinergic amacrine cells; however, double immunostaining of the retinas for choline acetyltransferase and glypho revealed two different cell populations. Intracellular injection of DiI showed that glypho‐immunoreactive amacrine cells are wide‐field amacrine cells with straight, radially oriented, and sparsely branched dendrites. The density of the cells increased from ∼70/mm2 in the peripheral retina to ∼700/mm2 in the central retina. The regular glypho‐immunoreactive amacrine cells branch in sublamina 2 of the IPL, where they receive input from OFF‐cone bipolar cells. The displaced cells branch in sublamina 3/4 and receive input from ON‐cone bipolar cells. This suggests that the regular cells are OFF‐cells and the displaced cells are ON‐cells. The cells express γ‐aminobutyric acid (GABA)‐like immunoreactivity and receive glycinergic input through synapses expressing preferentially the glycine receptor α2 subunit. The close proximity of the dendritic strata of glypho‐immunoreactive amacrine cells, cholinergic amacrine cells, and direction‐selective ganglion cells suggests a possible role of the cells in the generation of direction‐selective light responses of the monkey retina. J. Comp. Neurol. 508:13–27, 2008. © 2008 Wiley‐Liss, Inc.
Logistic regression Gaussian mixture model and softmax discriminant classifier for epilepsy classification from EEG signals

The patient suffers from spontaneous seizures under a neurological condition termed epilepsy. Due to the severe disturbances happening in the electrical activity of the brain, the seizures occur. An epileptic seizure is simply a transient occurrence of symptoms because of excessive and abnormal neuronal firing of neurons in the brain. Due to the hypersynchronous and abnormal activity of neurons in the brain, epilepsy manifests itself in the form of seizures. The most disabling aspect and the characteristic feature of this disease are witnessed by the occurrence of seizures. It is quite difficult to identify the presence of epileptic activities in order to characterize and understand the spatio-temporal patterns. The automatic classification and detection procedure of seizures from Electroencephalography (EEG) signals is quite crucial for the localization and epileptic seizure activity classification. The seizures are typically non stationary and highly dynamic in nature so that the rhythmic activities cannot be easily interpreted. In this paper, a two level classification procedure is employed, firstly the risk of epilepsy is classified with Softmax Discriminant Classifier (SDC) and secondly it is further optimized and classified with Logistic Regression Gaussian Mixture Model (LRGMM) Classifier. Results show that a classification accuracy of about 93.38% is obtained when classified with SDC and a classification accuracy of about 97.91% is obtained with classified with LRGMM.
Supervised Link Prediction with Path Scores

Link prediction has long been a classic and fundamental topic in network analysis. The problem is basically about given a network, how can we infer the possible links that will be formed in the future, or which links are missing in the current record. Link prediction is important not only for understanding the dynamics of networks, but also for completing current networks. It has many applications in different areas, from automatic recommendation systems in social networks and e-commerce, to finding the interactions between cells or proteins in bioinformatics. [5] To predict potential or missing links in the network, attributes of nodes, edges and network topology give some clues. And machine learning (ML) based methods such as [1] make it easier to incorporate different measurements into one model. Supervised random walks (SRW) [2] combines ML methods with the graph algorithm PageRank to get a higher performance. In this project, we leverage the idea of ML methods and SRW to propose a new method for link prediction. Similar to SRW, our method also utilizes the graph information (the paths between two nodes) to train a link predicting model. But unlike SRW, it does not involve the high-cost and unscalable PageRank algorithm/update. Instead, we try to use a simpler way to extract features for each path and calculate a potential link score for two nodes directly. Experiments show that our method can train much faster than SRW with much smaller memory space, and meanwhile gets a similar performance as SRW. We review some related work in Section 2. Our model is elaborated in Section 3. The progress until this point including data preprocessing and preliminary experiments of baseline models are introduced in Section 4 and 5. Finally, we discuss future work and challenges in Section 6.
ARTICULATION-TESTING METHODS: CONSONANTAL DIFFERENTIATION WITH A CLOSED-RESPONSE SET.

The development and evaluation of a new speech‐intelligibility test suitable for routine use by operational personnel in determining the performance level of speech‐communication systems is described. The format used is similar to that described for a rhyme test but makes use of a closed‐response set. An experiment was performed to determine the general reliability of the test materials when administered to U.S. Air Force enlisted personnel under a wide range of signal‐to‐noise ratios. Testing of 18 listeners over a period of 30 days showed that repeated exposure to the materials did not change the levels of average response in any appreciable way. Analysis of the responses to individual phonetic elements shows that the test can be useful for diagnostic study as well as for over‐all evaluation of communication systems. Talker differences that appeared during the experiment and the statistical reliability and sensitivity of the materials are analyzed and discussed.
Towards an independent component model

Summary form only given. There is an increasing need for engineering models that provide better representation of a software application. Software manufacturers are hoping to make an application from the composition of several software components in a way very similar to the hardware components. However, applications are currently bounded to the traditional programming models and services provided by current operating systems. Although current component models support component based development, they are at the end governed by the legacy roles imposed by the operating systems. In this paper, we introduce the EZeus component object model (ECM). We show that ECM exhibits most of the component-based software engineering advantages. ECM is an independent component model that allows developers to craft applications purely out of components that interact efficiently. The components are not dependent on particular operating systems.