Miracle-dz/UniFAR-FTUs huggingface dataset:
ADM — a dialog manager

ADM is a system for developing user interfaces. We call it a dialog manager; it is similar to what others call a “User Interface Management System” [8]. Although ADM is still being developed, it has been used to construct several applications. A dialog manager divides an application into an “interaction handler,” which interacts with the user, and an “underlying application,” which processes user commands and data. With ADM the application designer writes the underlying application in a conventional programming language and defines the interface between interaction handler and underlying application in terms of “tasks,” things the user can do, and “states,” sets of tasks that are active at one time. The user interface designer defines the interaction handler in terms of “presentation techniques,” which present tasks to the user, and “structuring techniques,” which describe screen layout. Design decisions made for ADM include using a precompiled, declarative dialog description, a flexible division between interaction handler and underlying application, allowing either interaction handler or underlying application to maintain control, and the inclusion of help and error support.
The impact of thin trading on day-of-the-week effect: Evidence from the United Arab Emirates

Purpose - The purpose of this study is to examine the impact of thin trading on the day-of-the-week effect in the emerging equity markets of the United Arab Emirates (UAE). Researchers have stated that emerging markets are typically characterized by low liquidity, thin trading and possibly less well-informed investors with access to unreliable information and considerable volatility. It is well known that thin trading can affect the results of empirical studies on patterns of equity markets by introducing a serious bias into the results. Design/methodology/approach - This study applies a stochastic dominance approach to detect the day-of-the-week effect. The reason for utilizing this approach is that the parametric tests are not strictly appropriate for assets with non-normally distributed returns. In fact, stochastic dominance is a useful tool for making comparisons among distributions without relying on parametric assumptions. Findings - The findings indicate that there is day-of-the-week effect in published daily prices, while daily effect vanishes when data are corrected to remove any measurement bias arising from thin trading. The stochastic dominance results show that the day-of-the-week effect in the UAE equity markets is not present when we correct raw data for thin and infrequent trading. Originality/value - There has been no research in the literature testing the day-of-the-week effect on the emerging financial markets in the UAE. The study provides empirical evidence on their degree of market efficiency. If the day-of-the-week effect exists, this means that the Abu Dhabi Securities Markets and the Dubai Financial Markets are inefficient. These results will help investors to develop a good investment strategy
Value-At-Risk Forecast Using Copulas : An Empirical Approach in Brazilian Stock Market

Through empirical research is identified that the hypothesis of normal distribution of returns is no longer observed while verifying the existence of heavy tails and asymmetries in the distribution. Thus, the article has aimed empirically apply copula models using techniques of realized volatility (HAR) with high-frequency data and perform the calculation of Value at Risk for different periods. The results show that HAR models copula exhibited superior performance with respect to EWMA and GARCH in intervals of time greater than five minutes.
NATools - A statistical Word Aligner Workbench

This document presents the TerminUM project and the work done in its statistical word aligner workbench (NATools). It shows a variety of alignment methods for parallel corpora and discusses the resulting terminological dictionaries and their use: evaluation of sentence translations; construction of a multi-level navigation system for linguistic studies or statistical translations
Understanding and designing business process modelling for emergency plan

Thereafter the Fukushima setback, different resolutions are on-going to improved arrangements among agencies responsible for the safety of such facilities and jointly developed reasonable precautions that will mitigate future calamities. This paper accomplished to recognize and represent suggested business processes for the Malaysian Nuclear Power Generating Program (NPP) based on Alter's Work System Theory (WST). The work system method often considered as effective in describing the organizational system such as NPP. This method applied to frame and understands the user requirements within the business case of NPP. As a result, the business process was determined in respect of the emergency plan accordingly. This case study analytically processed by adopting qualitative grounding processes. These processes involved coding interpretation which providing structural analysis of the suggested system requirements in a form of business process modelling. This analysis comprising process fabrication using member checking technique and workflow driven approach, which then transformed into business process simulation in the future.
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TA cloning is one of the simplest and most efficient methods for the cloning of PCR products. The procedure exploits the terminal transferase activity of certain thermophilic DNA polymerases, including Thermus aquaticus (Taq) polymerase. Taq polymerase has non-template dependent activity which preferentially adds a single adenosine to the 3'-ends of a double stranded DNA molecule, and thus most of the molecules PCR amplified by Taq polymerase possess single 3'-A overhangs. The use of a linearized “T-vector” which has single 3'-T overhangs on both ends allows direct, high-efficiency cloning of PCR products, facilitated by complementarity between the PCR product 3'-A overhangs and vector 3'-T overhangs. The TA cloning method can be easily modified so that the same T-vector can be used to clone any double-stranded DNA fragment, including PCR products amplified by any DNA polymerase, as well as all bluntand sticky-ended DNA species. This technique is especially useful when compatible restriction sites are not available for the subcloning of DNA fragments from one vector to another. Directional cloning is made possible by appropriate hemi-phosphorylation of both the T-vectors and the inserts. With a single T-vector at hand, any DNA fragment can be cloned without compromising the cloning efficiency. The universal TA cloning method is thus both convenient and labor-saving.
An active-clamping single-stage DC-AC flyback converter

This paper proposes an active clamping dc-ac flyback converter suitable to be used as a microinverter in renewable energy applications. The main features of the topology are the relatively low component count, high-frequency isolation, voltage step-up capability and zero voltage switching. The active clamping allows to recover most of the energy stored in the flyback's inductor leakage inductance and thus an improvement on the system efficiency is achieved. A 500 W, 50 kHz, 70 V input voltage and 127 Vrms output voltage prototype was built and the experimental results validate the theoretical analysis and the feasibility of the proposed converter.
Application of Additive Mass Method in the Compaction Quality Measurement of over Coarse-Grained Soils

The compaction quality of over coarse-grained soils is one of the most important indexes in the high-fill project quality management, but it is difficult to ascertain the compaction quality of over coarse-grained soils today. The traditional methods for compaction quality measurement of over coarse- grained soils have their limitation and applicability, so it is difficult to meet the demand of the compaction quality control in large-scale constructions. In certain western mountainous high-fill airport, the nondestructive test method of additive mass is applied for the first time in airport constructions. Through twenty group test results, the empirical formula between soil rigidity and dry density is established: rhod =0.0034k +1.69. The testing results indicate that it is not only rapid, portable, non-destructive and precise, but also suitable for density measurement of over coarse-grained soils. It has proved that the additive mass method is very effective and promising for its application in project quality management in the future.
Neurotrophin-4/5 (NT-4/5) and brain-derived neurotrophic factor (BDNF) act at later stages of cerebellar granule cell differentiation

The developing cerebellum expresses genes which encode for both neurotrophins and their receptors. The present study was designed to determine at what stages during cerebellar granule cell neurogenesis neurotrophin family molecules may act. We report here that in purified, well-characterized granule cell cultures (Gao et al., 1991; 1992), none of the neurotrophins stimulated proliferation of granule cell precursors or rescued phenotypic defect of mutant weaver granule cell precursors in the initiation of neuronal differentiation. However, neurotrophin-4/5 (NT-4/5) and BDNF, but not neurotrophin-3 (NT-3) or NGF, promoted neurite extension and survival of differentiated cerebellar granule cells. Both of these effects were blocked by the specific inhibitor for Trk tyrosine kinases, K-252a. NT-4/5 and BDNF also enhanced neurite extension by weaver granule cells which were rescued by wild-type granule cells during differentiation. Moreover, TrkB immunohistochemistry performed on sections of the developing wildtype and weaver cerebella revealed that only differentiated granule cells, but not the precursor cells, make high levels of TrkB receptor. These findings together suggest that NT-4/5 and BDNF promote the maturation and maintenance of differentiated granule cells, effects which are downstream to the weaver gene. Since no additive effects were seen with the combination of NT-4/5 and BDNF, it seems likely that the two neurotrophins activate the same receptor trkB for signal transduction.
Profiling Inflammatory Responses with Microfluidic Immunoblotting

Rapid profiling of signaling pathways has been a long sought after goal in biological sciences and clinical medicine. To understand these signaling pathways, their protein components must be profiled. The protein components of signaling pathways are typically profiled with protein immunoblotting. Protein immunoblotting is a powerful technique but has several limitations including the large sample requirements, high amounts of antibody, and limitations in assay throughput. To overcome some of these limitations, we have designed a microfluidic protein immunoblotting device to profile multiple signaling pathways simultaneously. We show the utility of this approach by profiling inflammatory signaling pathways (NFκB, JAK-STAT, and MAPK) in cell models and human samples. The microfluidic immunoblotting device can profile proteins and protein modifications with 5380-fold less antibody compared to traditional protein immunoblotting. Additionally, this microfluidic device interfaces with commonly available immunoblotting equipment, has the ability to multiplex, and is compatible with several protein detection methodologies. We anticipate that this microfluidic device will complement existing techniques and is well suited for life science applications.
A dynamically trained neural network for machine vision applications

A dynamically trained neural network is proposed in this paper proper for adapting the network performance to non stationary image or video inputs. The scheme includes, on one hand, a retrieval mechanism which selects the most appropriate network from the system memory and, on the other hand, a weight perturbation procedurewhich adapts the network weights to the current condition. If no suitable network exists in memory, new weights and network structure are created and then stored for future use. Experimental results are provided indicating the good performance of the proposed system to computer and machine vision applications.
Sherlock Holmes goes Cyber Deception Detection on the Basis of Actions

In work very relevant to national defense and homeland security, this paper describes software that detects deception on the basis of actions. This is in sharp contrast with present approaches that detect deception based on physiological factors, as well as on verbal and nonverbal cues. Our approach attempts to model agents and their actions. This is achieved in a logic programming framework using a theory of agents, a theory of actions, and a theory of reasoning with respect to time. As a test case, a children’s mystery is analyzed and implemented. The software correctly reasons about who the potential suspects are, and ultimately, correctly identifies the chief culprit. Further, it can correctly introspect with regard to previously held beliefs.
Recommendations on generic names competing for use in Leotiomycetes (Ascomycota)

In advancing to one scientific name for fungi, this paper treats genera competing for use in the phylogenetically defined class Leotiomycetes except for genera of Erysiphales. Two groups traditionally included in the so-called “inoperculate discomycetes” have been excluded from this class and are also not included here, specifically Geoglossomycetes and Orbiliomycetes. A recommendation is made about the generic name to use in cases in which two or more generic names are synonyms or taxonomically congruent along with the rationale for the recommendation. In some cases the recommended generic name does not have priority or is based on an asexual type species, thus needs to be protected and ultimately approved according to Art. 57.2 of the International Code of Nomenclature for algae, fungi and plants (ICN). A table is presented listing all competing generic names and their type species noting the recommended generic name. New combinations are introduced for the oldest epithet in the recommended genus including Ascocalyx berenice, Ascoconidium purpurascens, Ascocoryne albida, A. trichophora, Blumeriella filipendulae, B. ceanothi, Botrytis arachidis, B. fritillariae-pallidoflori, Calloria urticae, Calycellina aspera, Dematioscypha delicata, Dermea abietinum, D. boycei, D. stellata, Diplocarpon alpestre, D. fragariae, Godroniopsis peckii, Grovesinia moricola, Heterosphaera sublineolata, Hyphodiscus brachyconium, H. brevicollaris, H. luxurians, Leptotrochila campanulae, Monilinia polystroma, Neofabraea actinidae, N. citricarpa, N. vagabunda, Oculimacula aestiva, O. anguioides, Pezicula brunnea, P. californiae, P. cornina, P. diversispora, P. ericae, P. melanogena, P. querciphila, P. radicicola, P. rhizophila, Phialocephala piceae, Pilidium lythri, Rhabdocline laricis, Streptotinia streptothrix, Symphyosirinia parasitica, S. rosea, Unguiculariopsis caespitosa, and Vibrissea laxa.
Arbitrary Code Injection through Self-propagating Worms in Von Neumann Architecture Devices

Malicious code (or malware) is defined as a software designed to execute attacks on software systems and fulfill the harmful intents of an attacker. As lightweight embedded devices become more ubiquitous and increasingly networked, they present a new and very disturbing target for malware developers. In this paper, we demonstrate how to execute malware on wireless sensor nodes that are based on the Von Neumann architecture. We achieve this by exploiting a buffer overflow vulnerability to smash the call stack and intrude a remote node over the radio channel. By breaking the malware into multiple packets, the attacker can inject arbitrarily long malicious code to the node and completely take control of it. Then we proceed to show how the malware can be crafted to become a self-replicating worm that broadcasts itself and infects the network in a hop-by-hop manner. To our knowledge, this is the first instance of a self-propagating worm that provides a detailed analysis along with instructions in order to execute arbitrary malicious code. We also provide a complete implementation of our attack, measure its effectiveness in terms of time taken for the worm to propagate to the entire sensor network and, finally, suggest possible countermeasures.
Robust one-Tube Ω-PCR Strategy Accelerates Precise Sequence Modification of Plasmids for Functional Genomics

Functional genomics requires vector construction for protein expression and functional characterization of target genes; therefore, a simple, flexible and low-cost molecular manipulation strategy will be highly advantageous for genomics approaches. Here, we describe a Ω-PCR strategy that enables multiple types of sequence modification, including precise insertion, deletion and substitution, in any position of a circular plasmid. Ω-PCR is based on an overlap extension site-directed mutagenesis technique, and is named for its characteristic Ω-shaped secondary structure during PCR. Ω-PCR can be performed either in two steps, or in one tube in combination with exonuclease I treatment. These strategies have wide applications for protein engineering, gene function analysis and in vitro gene splicing.
Three-dimensional digital beamforming for near-field wideband acoustic imaging

To generate volumetric acoustic images, a planar array of sensors is required to collect the signals coming from a 3-D scene. The method most frequently used to process the acquired signals is a digital beamforming algorithm. In general, due to the high number of sensors and beam signals, the computational load is prohibitive for real-time image generation. In this paper, the options for a frequency-domain implementation are discussed and an extension of the Chirp Zeta Transform beamforming is proposed that has been specifically devised to cope with the requirements of volumetric imaging. In particular, the process of wideband signals collected by a planar array and generated by a scene placed in both the near-field and the far-field is enabled with a computational load that is a few orders of magnitude lower than that of the traditional frequency-domain and time-domain beamforming implementations.
An Overview of Studies of the Low Non-Farming Wage Problem in the Rural Labor Market in Japan

The discussion of the low wage problem has a long history, and there are a huge number of studies even if we were to consider only those that pertain to non-farming wages. Therefore, it is hard to trace all the discussion that has taken place. The aim of this article is to give an overview of the studies on the low non-farming wage problem. In addition, this article also introduces, based on data from the newest study, a fresh and relevant discussion of the low wage problem as it stands today. An overview of the actual wage levels indicate that non-farming wages of males meet their family budgets in the urbanized region, but fall to half these levels in the farming-oriented region. The outline of our discussion indicates that the family factor was paid more attention to in order to explain the low wage levels in the later discussions; moreover, the latest study points out that the different family norms have bond with the wage difference.
Street Connectivity is Negatively Associated with Physical Activity in Canadian Youth

Street connectivity, defined as how well streets connect to one and other and the density of intersections, is positively associated with active transportation in adults. Our objective was to study the relation between street connectivity and physical activity in youth. Study participants consisted of 8,535 students in grades 6–10 from 180 schools across Canada who completed the 2006 Health Behaviour in School-aged Children (HBSC) survey. Street connectivity was measured in a 5 km circular buffer around these schools using established geographic information system measures. Physical activity performed outside of school hours was assessed by questionnaire, and multi-level regression analyses were used to estimate associations with street connectivity after controlling for several covariates. Compared to students living in the highest street connectivity quartile, those in the second (relative risk = 1.22, 95% confidence interval = 1.10–1.35), third (1.25, 1.13–1.37), and fourth (1.21, 1.09–1.34) quartiles were more likely to be physically active outside of school. In conclusion, youth in neighbourhoods with the most highly connected streets reported less physical activity outside of school than youth from neighbourhoods with less connected streets. Relationships between street connectivity and physical activity reported in this national study are in the opposite direction to those previously observed for active transportation in adult populations.
Overload Management in Data Stream Processing Systems with Latency Guarantees

Stream processing systems are becoming increasingly important to analyse real-time data generated by modern applications such as online social networks. Their main characteristic is to produce a continuous stream of fresh results as new data are being generated at real-time. Resource provisioning of stream processing systems is difficult due to time-varying workload data that induce unknown resource demands over time. Despite the development of scalable stream processing systems, which aim to provision for workload variations, there still exist cases where such systems face transient resource shortages. During overload, there is a lack of resources to process all incoming data in real-time; data accumulate in memory and their processing latency grows uncontrollably compromising the freshness of stream processing results. In this paper, we present a feedback control approach to design a nonlinear discrete-time controller that has no knowledge of the system to be controlled or the workload for the data and is still able to control the average tuple end-to-end latency in a single-node stream processing system. The results, of our evaluation on a prototype stream processing system, show that our method controls the average tuple end-to-end latency despite the time-varying workload demands and increasing number of queries.
Artificial neural network prediction of antisense oligodeoxynucleotide activity.

An mRNA transcript contains many potential antisense oligodeoxynucleotide target sites. Identification of the most efficacious targets remains an important and challenging problem. Building on separate work that revealed a strong correlation between the inclusion of short sequence motifs and the activity level of an oligo, we have developed a predictive artificial neural network system for mapping tetranucleotide motif content to antisense oligo activity. Trained for high-specificity prediction, the system has been cross-validated against a database of 348 oligos from the literature and a larger proprietary database of 908 oligos. In cross- validation tests the system identified effective oligos (i.e. oligos capable of reducing target mRNA expression to <25% that of the control) with 53% accuracy, in contrast to the <10% success rates commonly reported for trial-and-error oligo selection, suggesting a possible 5-fold reduction in the in vivo screening required to find an active oligo. We have implemented a web interface to a trained neural network. Given an RNA transcript as input, the system identifies the most likely oligo targets and provides estimates of the probabilities that oligos targeted against these sites will be effective.