Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluations of Hash Distributed A* in Optimal Sequence Alignment

Hash Distributed A* (HDA*) is a parallel A* algorithm that is proven to be effective in optimal sequential planning with unit edge costs. HDA* leverages the Zobrist function to almost uniformly distribute and schedule work among processors. This paper evaluates the performance of HDA* in optimal sequence alignment. We observe that with a large number of CPU cores HDA* suffers from an increase of search overhead caused by reexpansions of states in the closed list due to nonuniform edge costs in this domain. We therefore present a new work distribution strategy limiting processors to distribute work, thus increasing the possibility of detecting such duplicate search effort. We evaluate the performance of this approach on a cluster of multi-core machines and show that the approach scales well up to 384 CPU cores.
Comparative study of curcumin and curcumin formulated in a solid dispersion: Evaluation of their antigenotoxic effects

Abstract Curcumin (CMN) is the principal active component derived from the rhizome of Curcuma longa (Curcuma longa L.). It is a liposoluble polyphenolic compound that possesses great therapeutic potential. Its clinical application is, however, limited by the low concentrations detected following oral administration. One key strategy for improving the solubility and bioavailability of poorly water-soluble drugs is solid dispersion, though it is not known whether this technique might influence the pharmacological effects of CMN. Thus, in this study, we aimed to evaluate the antioxidant and antigenotoxic effects of CMN formulated in a solid dispersion (CMN SD) compared to unmodified CMN delivered to Wistar rats. Cisplatin (cDDP) was used as the damage-inducing agent in these evaluations. The comet assay results showed that CMN SD was not able to reduce the formation of cDDP-DNA crosslinks, but it decreased the formation of micronuclei induced by cDDP and attenuated cDDP-induced oxidative stress. Furthermore, at a dose of 50 mg/kg b.w. both CMN SD and unmodified CMN increased the expression of Tp53 mRNA. Our results showed that CMN SD did not alter the antigenotoxic effects observed for unmodified CMN and showed effects similar to those of unmodified CMN for all of the parameters evaluated. In conclusion, CMN SD maintained the protective effects of unmodified CMN with the advantage of being chemically water soluble, with maximization of absorption in the gastrointestinal tract. Thus, the optimization of the physical and chemical properties of CMN SD may increase the potential for the therapeutic use of curcumin.
Query sense disambiguation leveraging large scale user behavioral data

Term ambiguity - the challenge of having multiple potential meanings for a keyword or phrase - can be a major problem for search engines. Contextual information is essential for word sense disambiguation, but search queries are often limited to very few keywords, making the available textual context needed for disambiguation minimal or non-existent. In this paper we propose a novel system to identify and resolve term ambiguity in search queries using large-scale user behavioral data. The proposed system demonstrates that, despite the lack of context in most keyword queries, multiple potential senses of a keyword or phrase within a search query can be accurately identified, disambiguated, and expressed in order to maximize the likelihood of fulfilling a user's information need. The proposed system overcomes the immediate lack of context by leveraging large-scale user behavioral data from historical query logs. Unlike traditional word sense disambiguation methods that rely on knowledge sources or available textual corpora, our system is language-agnostic, is able to easily handle domain-specific terms and meanings, and is automatically generated so that it does not grow out of date or require manual updating as ambiguous terms emerge or undergo a shift in meaning. The system has been implemented using the Hadoop eco-system and integrated within CareerBuilder's semantic search engine.
The Efficiency of UK General Insurance Companies Professor Stephen Diacon Worshipful Company of Insurers Professor of Insurance Management

This paper explores the efficiency of UK specialist and composite insurers transacting general insurance business. The concept of efficiency concerns an insurer’s ability to produce a given set of outputs (such as premiums and investment income) via the use of inputs such as administrative and sales staff and financial capital. An insurer is said to be technically efficient if it cannot reduce its resource usage without some corresponding reduction in outputs, given the current state of production technology in the industry. An exploration of the value-based technical efficiency of UK general insurers is undertaken by comparing the relative performance of 431 general insurers licensed in six European countries using data from Standard & Poor’s Eurothesys database. The data has been made available on a (roughly) comparable basis as a result of the EU insurance Accounts Directive which only came fully into operation in 1996. The study uses the variable returns to scale formulation of the well-known data envelopment analysis to identify the locally-efficient and inefficient insurers within each country. A comparison is then undertaken for all insurers after adjusting for the impact of their local efficiency. The results for 1999 (the latest year of available data) indicate that UK general and composite insurance companies have the potential to be among the most efficient in Europe. On average, after adjusting for local inefficiencies, UK insurers demonstrate an average efficiency score of around 77% which is substantially higher than the corresponding average figures for France (67%), Germany (70%), Italy (56%), The Netherlands (69%) and Switzerland (66%). However there is also evidence that many UK companies are not currently realising their potential for efficiency improvements in comparison with their European counterparts.
Modeling and Analysis of the Lane-Changing Execution in Longitudinal Direction

Lane changing is a common driving behavior in traffic, and the algorithm of lane-changing maneuver is an indispensable part of the design of autonomous vehicle control and adaptive cruise control. Although extensive research studies focused on modeling drivers' decision mechanism, lane-changing execution (LCE) happening after the lane-changing decision has not attracted much attention, which has a significant impact on driving safety and traffic simulation results. This paper attempts to replicate the real LCE behavior by proposing new LCE models. Depending on whether the lag vehicle on the target lane is considered in an LCE or not, two types of lane-changing execution are defined, namely, the cooperative LCE (CLCE) and the forced LCE (FLCE). The real vehicle trajectory data, i.e., the NGSIM data, are applied to train and test the proposed models. The results illustrate that the proposed models have good performance in replicating the CLCE and FLCE behavior and outperform the first LCE model proposed by Moridpour et al. Furthermore, when drivers decide to conduct a lane-changing execution, their considerations of the vehicles on the target lane have happened, and their considerations of the vehicles on the current lane decrease sharply during the LCE. In addition, the driver generally pays more attention to the preceding vehicle than to the lag vehicle on the target lane in an LCE.
Using Real-Options Valuation Methods for a Biotechnology Firm

Many firms in the biotechnology industry have significant valuations despite having no product revenue because their products are in early stages of development. In the past ten to fifteen years investors have bid up the stock prices of firms showing promise of developing a blockbuster drug. Using the decision-tree and binomial-lattice methods we compare the value of a biotechnology firm to the sum of the values of its drug development projects. We compare our computed values of Agouron to actual market values at selected points in time during the development of Viracept, a drug used to treat HIV-positive patients. Values for Agouron were also found using a binomial lattice with the addition of a growth option, which was added because the development of an initial new molecular entity (NME) is similar to purchasing a call option on the value of a subsequent NME.
Early postnatal ozone exposure alters rat nodose and jugular sensory neuron development

Sensory neurons originating in nodose and jugular ganglia that innervate airway epithelium (airway neurons) play a role in inflammation observed following exposure to inhaled environmental irritants such as ozone (O3). Airway neurons can mediate airway inflammation through the release of the neuropeptide substance P (SP). While susceptibility to airway irritants is increased in early life, the developmental dynamics of afferent airway neurons are not well characterized. The hypothesis of this study was that airway neuron number might increase with increasing age, and that an acute, early postnatal O3 exposure might increase both the number of sensory airway neurons as well as the number SP-containing airway neurons. Studies using Fischer 344 rat pups were conducted to determine if age or acute O3 exposure might alter airway neuron number. Airway neurons in nodose and jugular ganglia were retrogradely labeled, removed, dissociated, and counted by means of a novel technique employing flow cytometry. In Study 1, neuron counts were conducted on postnatal days (PD) 6, 10, 15, 21, and 28. Numbers of total and airway neurons increased significantly between PD6 and PD10, then generally stabilized. In Study 2, animals were exposed to O3 (2 ppm) or filtered air (FA) on PD5 and neurons were counted on PD10, 15, 21, and 28. O3-exposed animals displayed significantly less total neurons on PD21 than FA controls. This study shows that age-related changes in neuron number occur, and that an acute, early postnatal O3 exposure significantly alters sensory neuron development.
Research on DDoS Filtering Algorithm Based on Bloom Filter WhiteList

With the DDoS (distributed denial of service) traffic which was implemented using depleted bandwidth is filtered by routers in high speed network, it is impossible for the victim to work on the individual level of on-going traffic flows. The scheme establishes the source and destination IP address database by observing the normal traffic and storages it in a Bloom Filter table. The Netflow statistics is mainly used to allocate the weights for traffic routing by routers. A new algorithm is thus proposed to get efficiently maximum throughput by the traffic filtering, and its feasibility and validity have been verified in real network circumstances. The algorithm shows its advantages that it just occupies a small part of resources. Moreover, it can optimize the network traffic simultaneously with defending against DDoS attack, thus eliminating efficiently the global burst of traffic arising from normal traffic so as to improve greatly the efficiency of servers.
Pattern-recognition arm prosthesis: a historical perspective-a final report.

The application of external power for the operation of artificial arms, hands, and hooks has intrigued inventors in and outside of prosthetics since the idea was first proposed, in Germany, shortly after World War I (1). Nothing much seems to have happened until Alderson (2) proposed the idea of an electric arm to the International Business Machines Corp . , about 1945 . He received financial support from both IBM and the Veterans Administration. Evaluation of the very ingenious and impressive models designed and fabricated by Alderson and his associates revealed that it was not possible for arm amputees to control the electrically actuated prostheses without conscious thought, an activity which, for all but the most severely disabled amputees, required a level of effort that exceeded the benefits received . And thus the research and development effort was directed toward "control " rather than "actuation . "
Divergence With Gene Flow in Anopheles funestus From the Sudan Savanna of Burkina Faso, West Africa

Anopheles funestus is a major vector of malaria across Africa. Understanding its complex and nonequilibrium population genetic structure is an important challenge that must be overcome before vector populations can be successfully perturbed for malaria control. Here we examine the role of chromosomal inversions in structuring genetic variation and facilitating divergence in Burkina Faso, West Africa, where two incipient species (chromosomal forms) of A. funestus, defined principally by rearrangements of chromosome 3R, have been hypothesized. Sampling across an ∼300-km east–west transect largely contained within the Sudan–Savanna ecoclimatic zone, we analyzed chromosomal inversions, 16 microsatellite loci distributed genomewide, and 834 bp of the mtDNA ND5 gene. Both molecular markers revealed high genetic diversity, nearly all of which was accounted for by within-population differences among individuals, owing to recent population expansion. Across the study area there was no correlation between genetic and geographic distance. Significant genetic differentiation found between chromosomal forms on the basis of microsatellites was not genomewide but could be explained by chromosome 3R alone on the basis of loci inside and near inversions. These data are not compatible with complete reproductive isolation but are consistent with differential introgression and sympatric divergence between the chromosomal forms, facilitated by chromosome 3R inversions.
Gait Recognition Using Radon Transform and Linear Discriminant Analysis

A new feature extraction process is proposed for gait representation and recognition. The new system is based on the Radon transform of binary silhouettes. For each gait sequence, the transformed silhouettes are used for the computation of a template. The set of all templates is subsequently subjected to linear discriminant analysis and subspace projection. In this manner, each gait sequence is described using a low-dimensional feature vector consisting of selected Radon template coefficients. Given a test feature vector, gait recognition and verification is achieved by appropriately comparing it to feature vectors in a reference gait database. By using the new system on the Gait Challenge database, very considerable improvements in recognition performance are seen in comparison to state-of-the-art methods for gait recognition
Fabrication and electric-field-dependent transport measurements of mesoscopic graphite devices

We have developed a unique micromechanical method to extract extremely thin graphite samples. Graphite crystallites with thicknesses ranging from 10 to 100nm and lateral size ∼2μm are extracted from bulk. Mesoscopic graphite devices are fabricated from these samples for electric field-dependent conductance measurements. Strong conductance modulation as a function of gate voltage is observed in the thinner crystallite devices. The temperature-dependent resistivity measurements show more boundary scattering contribution in the thinner graphite samples.
Cost-Efficient Processing of Continuous Extreme Queries over Distributed Data Streams

We address the problem of cost-efficient processing of continuous extreme queries (MAX or MIN) over distributed sliding window streams, and propose several methods for communication reduction and resource sharing among queries. Firstly, we develop an effective pruning technique to minimize the number of elements to be kept. It can be shown that on average only O(logN) key points need to be stored for exact answer of extreme query, where N is the number of points contained in the sliding window. Then we consider the distributed environment, where remote nodes delay the data transmission as late as possible, and adopt the pruning strategy to filter local stream tuples, which is quite efficient in communication reduction. An efficient algorithm called MCEQP is proposed in the coordinator node for continuously monitoring K queries with different sliding window widths, and the linklist-implemented instance of MCEQP can update all K results in O(M+K) time when a new tuple arrives, where M is the cardinality of key points set corresponding to the widest window. Theoretical analysis and experimental evidences show the efficiency of proposed approach both on storage/communication reduction and efficiency improvement.
MicroRefresh: Minimizing Refresh Overhead in DRAM Caches

DRAM memory systems require periodic recharging to avoid loss of data from leaky capacitors. These refresh operations consume energy and reduce the duration of time for which the DRAM banks are available to service memory requests. Higher DRAM density and 3D-stacking aggravate the refresh overheads, incurring even higher energy and performance costs. 3D-stacked DRAM and other emerging on-chip High Bandwidth Memory (HBM) technologies which are widely considered to be changing the landscape of memory hierarchy in future heterogeneous and many-core architectures could suffer significantly from refresh overheads. Such large on-chip memory, when used as a very large last-level cache, however, provides opportunities for addressing the refresh overheads. In this work, we propose MicroRefresh, a scheme for almost eliminating the refresh overhead in DRAM caches. MicroRefresh eliminates unwanted refresh of recently accessed DRAM pages; it takes advantage of the relative latency difference between on-chip and off-chip DRAM and achieves a fine balance of usage of system resources by aggressively opportunistically eliminating refresh of older DRAM pages. It tolerates any resulting increase in cache misses by leveraging the under-utilized main memory bandwidth. The resulting organization eliminates the energy and performance overhead of refresh operations in the DRAM cache to achieve overall performance and energy improvement. Across both 4-core and 8-core workloads, MicroRefresh eliminates 92% the refresh energy consumed in the baseline periodic refresh mechanism. Further this is accompanied by performance improvements of upto 10%, with average improvements of 3.9% and 3.4% in 4-core and 8-core respectively.
Verkehrsstaus rational betrachtet

An Autobahnknotenpunkten und -anschlussstellen entstehen mit zunehmender Verkehrsdichte regelmaessig Rueckstaus. Wenn der Kraftfahrzeugbestand und die Verkehrsleistung weiterhin stark ansteigen, waehrend die Netzdichte und Leistungsfaehigkeit der Bundesfernstrassen kaum zunehmen, sind Verkehrsstaus unvermeidlich. Die Bildung und Aufloesung von Fahrzeugstaus in Abhaengigkeit von der Verkehrsstaerke, Dichte, Kapazitaet und Geschwindigkeit wird auf der Grundlage des Fundamentaldiagramms und der Schockwellentheorie abgeleitet. Es zeigt sich, dass der individuelle Zeitverlust im Verkehrsstau unter normalen Bedingungen weniger als 15 Minuten betraegt. Steuerungsmassnahmen in Hauptverkehrszeiten sind daher vorrangig auf die Erhoehung der Dichte, Kontinuitaet und Sicherheit zu richten. Durch differenzierte Steuerung der Fahrzeuge nach Nutzergruppen, Einfuehrung von Strassenbenutzungsgebuehren und hoehere Auslastung der Strassenkapazitaet kann eine hoehere Effizienz des Verkehrs auf Fernstrassen erreicht werden.
Enriching in-IDE process information with fine-grained source code history

Current studies on software development either focus on the change history of source code from version-control systems or on an analysis of simplistic in-IDE events without context information. Each of these approaches contains valuable information that is unavailable in the other case. Our work proposes enriched event streams, a solution that combines the best of both worlds and provides a holistic view on the software development process. Enriched event streams not only capture developer activities in the IDE, but also specialized context information, such as source-code snapshots for change events. To enable the storage of such code snapshots in an analyzable format, we introduce a new intermediate representation called Simplified Syntax Trees (SSTs) and build CA□RET, a platform that offers reusable components to conveniently work with enriched event streams. We implement FEEDBAG++, an instrumentation for Visual Studio that collects enriched event streams with code snapshots in the form of SSTs. We share a dataset of enriched event streams captured from 58 users and representing 915 days of work. Additionally, to demonstrate usefulness, we present three research applications that have already made use of CA□RET and FEEDBAG++.
Robust dual-stage face recognition method using PCA and high-dimensional-LBP

In this paper, we propose a dual-stage face recognition method which utilized both holistic and local features-based recognition algorithms. In the first stage Principal Components Analysis (PCA) is utilized to recognize test image. If the confidence level test is passed, the recognition process will be terminated. Otherwise, the second stage where High Dimensional Local Binary Patterns (HDLBP) is employed will be pursued. The performance of this hybrid method is evaluated on CMU-PIE database, and we obtain improved recognition rate than PCA alone.
Language Reference

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Architectural Test Coverage for Component-Based Integration Testing

This paper introduces a component-based integration testing method with an architectural test coverage criteria. This method is suitable for systems that lack system documentation and is applicable during regression testing and deployment phase. This paper also presents the initial results of an empirical study that validates the proposed test coverage criteria against an existing method in terms of the test coverage using a test suite precision parameter. We also describe the test models used that are based on probabilistic deterministic finite automata which are used to represent gate usage profiles at run-time and test execution. These models facilitate the representation and validation of the gate protocol, test coverage measurement and monitoring of the test suite coverage of each gate.
MPI-IO/Gfarm: An Optimized Implementation of MPI-IO for the Gfarm File System

This paper proposes a design and implementation of an MPI-IO implementation of the Gfarm file system, called MPI-IO/Gfarm. The Gfarm file system is a global file system that federates the local storage of compute nodes among several clusters. It has a scale-out architecture designed to support distributed data-intensive computing. However Gfarm file system does not achieve scalable performance in the case of parallel writes to a single file, a typical file operation in MPI-IO. This paper proposes an optimization technique to improve the parallel write performance to a single file. In the evaluation, MPI-IO/Gfarm achieves scalable parallel I/O performance.