Miracle-dz/UniFAR-FTUs huggingface dataset:
General developmental health in the VPA-rat model of autism

Autism is a neurodevelopmental condition diagnosed by impaired social interaction, abnormal communication and, stereotyped behaviors. While post-mortem and imaging studies have provided good insights into the neurobiological symptomology of autism, animal models can be used to study the neuroanatomical, neurophysiological and molecular mediators in more detail and in a more controlled environment. The valproic acid (VPA) rat model is an environmentally triggered model with strong construct and clinical validity. It is based on VPA teratogenicity in humans, where mothers who are medicated with VPA during early pregnancy show an increased risk for giving birth to an autistic child. In rats, early embryonic exposure, around the time of neural tube closure, leads to autism-like anatomical and behavioral abnormalities in the offspring. Considering the increasing use of the VPA rat model, we present our observations of the general health of Wistar dams treated with a single intraperitoneal injection of 500 or, 600 mg/kg VPA on embryonic day E12.5, as well as their male and female offspring, in comparison to saline-exposed controls. We report increased rates of complete fetal reabsorption after both VPA doses. VPA 500 mg/kg showed no effect on dam body weight during pregnancy or, on litter size. Offspring exposed to VPA 500 mg/kg showed smaller brain mass on postnatal days 1 (P1) and 14 (P14), in addition to abnormal nest seeking behavior at P10 in the olfactory discrimination test, relative to controls. We also report increased rates of physical malformations in the offspring, rare occurrences of chromodacryorrhea and, developmentally similar body mass gain. Further documentation of developmental health may guide sub-grouping of individuals in a way to better predict core symptom severity.
Sensorimotor Integration during Rubber Hand Illusion in Normal Subjects and Subjects with Parkinson’s Disease

Rubber hand illusion (RHI) measures visuo-tactile multisensory integration. Non-motor symptoms are well recognized in Parkinson’s disease (PD) and PD patients have impaired sensation and sensorimotor integration. We hypothesized that 1) RHI decreases sensorimotor integration in healthy subjects 2) PD patients show reduced RHI and less modulation of sensorimotor integration by RHI. We used transcranial magnetic stimulation to examine shortand long-latency afferent inhibition (SAI and LAI), which measures the influence of sensory input on the primary motor cortex (M1), and the posterior parietal cortex (PPC)-M1 interactions during RHI. In healthy subjects, we found reduced SAI and LAI during RHI, and stronger RHI correlated with greater inhibitory PPC-M1 interactions. PD patients showed normal RHI, but had no correlation between RHI strength and PPC-M1 interactions. Our results show that RHI modulates both early and late stages of sensorimotor integration in healthy subjects and this effect of RHI is altered in PD.
Risk Prediction Model Based on Improved AdaBoost Method for Cloud Users

Considering the problem how to protect the cloud services from being destroyed by cloud users, the risk- prediction model based on improved AdaBoost method is proposed. The risk prediction is regarded as two-class classifi- cation problem, and the risk of new cloud users could be predicted by the attributes of historical cloud users. In order to improve the result of predicted, AdaBoost method is adopted in this paper. The error rate of the last training is used to ad- just the sample distribution of the next training, which can make the next training have stronger ability of identification for the error-classified samples. At the same time the weight of each weak classifier is set. After all, the strong classifier is generated by combined the weak classifiers through voting, which can improve the overall result of classification. Con- sidering the wrongly-predicted cost, AdaBoost method is improved. The method of cost-sensitive is added into the model in order to minimal the misclassified-cost. Experiments show that the cost-sensitive AdaBoost method has better classifi- cation result than the traditional ones and it can predict the risk of the new cloud user effectively and protect the security of the cloud services.
A Stochastic Dominance Approach to Spanning

textabstractWe develop a Stochastic Dominance methodology to analyze if new assets expand the investment possibilities for rational nonsatiable and risk-averse investors. This methodology avoids the simplifying assumptions underlying the traditional mean-variance approach to spanning. The methodology is applied to analyze the stock market behavior of small firms in the month of January. Our findings suggest that the previously observed January effect is remarkably robust with respect to simplifying assumptions regarding the return distribution.
Genotyping of Human Lice Suggests Multiple Emergences of Body Lice from Local Head Louse Populations

Background Genetic analyses of human lice have shown that the current taxonomic classification of head lice (Pediculus humanus capitis) and body lice (Pediculus humanus humanus) does not reflect their phylogenetic organization. Three phylotypes of head lice A, B and C exist but body lice have been observed only in phylotype A. Head and body lice have different behaviours and only the latter have been involved in outbreaks of infectious diseases including epidemic typhus, trench fever and louse borne recurrent fever. Recent studies suggest that body lice arose several times from head louse populations. Methods and Findings By introducing a new genotyping technique, sequencing variable intergenic spacers which were selected from louse genomic sequence, we were able to evaluate the genotypic distribution of 207 human lice. Sequence variation of two intergenic spacers, S2 and S5, discriminated the 207 lice into 148 genotypes and sequence variation of another two intergenic spacers, PM1 and PM2, discriminated 174 lice into 77 genotypes. Concatenation of the four intergenic spacers discriminated a panel of 97 lice into 96 genotypes. These intergenic spacer sequence types were relatively specific geographically, and enabled us to identify two clusters in France, one cluster in Central Africa (where a large body louse outbreak has been observed) and one cluster in Russia. Interestingly, head and body lice were not genetically differentiated. Conclusions We propose a hypothesis for the emergence of body lice, and suggest that humans with both low hygiene and head louse infestations provide an opportunity for head louse variants, able to ingest a larger blood meal (a required characteristic of body lice), to colonize clothing. If this hypothesis is ultimately supported, it would help to explain why poor human hygiene often coincides with outbreaks of body lice. Additionally, if head lice act as a reservoir for body lice, and that any social degradation in human populations may allow the formation of new populations of body lice, then head louse populations are potentially a greater threat to humans than previously assumed.
Change-Based Test Selection in the Presence of Developer Tests

Regression test selection (i.e., selecting a subset of a given regression test suite) is a problem that has been studied intensely over the last decade. However, with the increasing popularity of developer tests as the driver of the test process, more fine-grained solutions are in order. In this paper we investigate how method-level changes in the base-code can serve as a reliable indicator for identifying which tests need to be rerun. We validate the approach on two cases - PMD and Cruise Control - using mutation testing as a means to compare the selected subset against a "retest all" approach. Our results show that we are able to reach a sizable reduction of the complete test suite, yet with a comparable number of mutants killed by the reduced test suite.
Does Hysteresis Exist in Unemployment? New Findings from Fourteen Regions of the Czech Republic

The present study chose 14 regions of the Czech Republic as case studies to examine the existence of unemployment hysteresis. To carry out the empirical analysis, it used the SURADF test and the FADF test. The empirical findings from the ADF tests suggested that unemployment in all 14 regions could be described as a non-stationary process. However, the results obtained from the more powerful SURADF test and the non-linear FADF test indicated that the unemployment rates in nine regions could have a unit root in accordance with the hysteresis hypothesis. These regions are Prague-city (Praha), Plzen (Plzenský), Karlovy Vary (Karlovarský), Usti (Ustecký), Liberec (Liberecký), Hradec Kralove (Kralovohradecký), Pardubice (Pardubický), South Moravia (Jihomoravský) and Olomouc (Olomoucký). By contrast, unemployment in the remaining five regions, namely Central Bohemia (Stredoceský), South Bohemia (Jihoceský), Vysocina, Zlin (Zlinský) and Moravia-Silesia (Moravskoslezský), could be described as a stationary process in line with the natural rate hypothesis. This means that unemployment hysteresis was not found in these five regions.
FOX ( FOld eXtractor ) : A novel protein fold recognition method using iterative PSI-BLAST searches and structural alignments

We present a novel fold recognition method based on the combination of detailed sequence searches and structural information. Presently the protocol implements two different approaches to assign the correct fold to the target protein sequence: the first is based on database secondary structure search and the second is based on iterative database sequence search. In the first phase a secondary structure prediction of the target is performed and based on the ConSSPred [1] protocol. This prediction is used to search for hits against a database of known secondary structures extracted from PDB (using DSSP). The search is based on a two-step strategy: the first step is based on a Smith-Waterman local secondary structure similarity search with a specific substitution matrix optimized for secondary structure alignment [2]. The second is based on a global alignment based on SSEA [3] (Secondary Structure Element Alignment), as implemented in our program MANIFOLD [4], to refine the score and the alignment itself in the region extracted from the first step. At the end of the first phase a list of hits that share a similar secondary structure topology with the target sequence is extracted. The second phase is based on a modified protocol for scanning the sequence database called SENSER [5]. In the beginning of the second phase, BLASTP [6] is used to scan the target sequence against the NR database. These initial hits are clustered to reduce sequence bias and a seed alignment with 20 or fewer sequences generated. This step ensures that PSI-BLAST [7] can be jump-started with a more sensitive initial profile, increasing its sequence diversity. PSI-BLAST is run for four iterations (e-value inclusion threshold 10e-3) on the NR60 database of known sequences. NR60 is produced by applying the CD-HIT [8] algorithm to cluster the NR database at 60% sequence identity. Sequences producing NR60 hits with the query are assigned either to the significant sequence space (e-value <= 10e-3) or the trailing end (e-value <= 10) for further use. The profile is used to search the PDBAA database of sequences with known structure. If a significant PDBAA hit (e-value <= 10) is found, the protocol proceeds to the back-validation step (see below). If no significant hit is found, or the hit does not back-validate, a new PSI-BLAST search, using the above "4+1" protocol on NR and PDBAA, is started for the highest ranking sequence (i.e. lowest e-value) in the significant sequence space. …
A Molecular Basis of Analgesic Tolerance to Cannabinoids

Clinical usage of cannabinoids in chronic pain states is limited by their central side effects and the pharmacodynamic tolerance that sets in after repeated dosage. Analgesic tolerance to cannabinoids in vivo could be caused by agonist-induced downregulation and intracellular trafficking of cannabinoid receptors, but little is known about the molecular mechanisms involved. We show here that the type 1 cannabinoid receptor (CB1) interacts physically with G-protein-associated sorting protein 1 (GASP1), a protein that sorts receptors in lysosomal compartments destined for degradation. CB1–GASP1 interaction was observed to be required for agonist-induced downregulation of CB1 in spinal neurons ex vivo as well as in vivo. Importantly, uncoupling CB1 from GASP1 in mice in vivo abrogated tolerance toward cannabinoid-induced analgesia. These results suggest that GASP1 is a key regulator of the fate of CB1 after agonist exposure in the nervous system and critically determines analgesic tolerance to cannabinoids.
Performance evaluation of an adaptive backoff scheme for WLAN

Summary In this paper, a simple self-adaptive contention window adjustment algorithm for 802.11 wireless local area networks (WLAN) is proposed and analyzed. Numerical results show that the new algorithm outperforms the standard 802.11 window adjustment algorithm. Compared with the standard and previously proposed enhancement algorithms, a salient feature of our algorithm is that it performs well in both heavy and light contention cases regardless of the packet sizes and physical versions. Moreover, the adaptive window adjustment algorithm is simpler than previously proposed schemes in that no live measurement of the WLAN traffic activity is needed. Copyright # 2004 John Wiley & Sons, Ltd.
Detection of Mycobacterium tuberculosis (MTB) in Fecal Specimens From Adults Diagnosed With Pulmonary Tuberculosis Using the Xpert MTB/Rifampicin Test

We performed a proof-of-concept study using the Xpert MTB/RIF test for the detection of Mycobacterium tuberculosis from fecal samples. The overall sensitivity was 85.7% (95% CI; 73.8 – 93.6%) and the specificity was 100% (95% CI; 86.2–100).
An LR substring parser for noncorrecting syntax error recovery

For a context-free grammar <italic>G</italic>, a construction is given to produce an LR parser that recognizes any substring of the language generated by <italic>G</italic>. The construction yields a conflict-free (deterministic) parser for the <italic>bounded context</italic> class of grammars (Floyd, 1964). The same construction yields either a left-to-right or right-to-left substring parser, as required to implement <italic>Non-correcting Syntax Error Recovery</italic> as proposed by Richter (1985). Experience in constructing a substring parser for Pascal is described.
Are we adequately preparing the next generation of physicians to prescribe exercise as prevention and treatment? Residents express the desire for more training in exercise prescription

Background Physical activity (PA) is a key intervention for chronic disease, yet few physicians provide exercise prescription (EP). EP is an important component in larger strategies of reducing non-communicable disease (NCD). Our objective was to assess Family Medicine Residents (FMR) knowledge, competence, and perspectives of EP to help inform future curriculum development. Methods A 49-item cross-sectional survey was administered to 396 University of British Columbia FMR. Residents’ EP knowledge, competence, attitudes/beliefs, current practices, personal physical activity levels, and perspectives of training were assessed using, primarily, a 7-point Likert scale. Results The response rate was 80.6% (319/396). After eliminating 25 that failed to meet the inclusion criteria, 294 were included in the final analysis. The majority 95.6% of FMR reported EP as important in their future practice, despite having low knowledge of the Canadian PA Guidelines (mean score 1.77/4), low self-reported competence prescribing exercise as prevention (mean score 13.35/21), and rating themselves “somewhat incompetent” prescribing exercise to patients with chronic disease (mean score 11.26/21). FMR believe PA is integral to their patients’ health (98.0%), sedentary behaviour is harmful (97.9%), and feel a responsibility to discuss PA with patients (99.7%). Few FMR (14.9%) perceived their training in EP as adequate and 91.0% desire more. Conclusions FMR report EP is important, yet do not perceive they are sufficiently prepared to provide EP. In future curricular development, medical educators should consider residents’ low knowledge, competence, perceived program support, and their expressed desire for more training in exercise prescription.
Collective control of multiple unicycle agents with non-identical constant speeds: Tracking control and performance limitation

This paper discusses collective control of multiple unicycle-type vehicles with nonholonomic constraints and non-identical constant speeds, with focus on the design of a tracking controller for a desired target's position and velocity. The tracking control task is divided into several sub-tasks. The group centroid is controlled to track a desired reference velocity, while the reference velocity is constructed with information from the target's position and velocity so that the group centroid can successfully track both the position and velocity of a target vehicle. In order to keep all the agents close to the centroid within a reasonable spacing, an additive spacing controller is devised. We also discuss in detail the performance limitation and trade-offs of the tracking control due to the constraint of non-identical and constant speeds in such a heterogeneous agent group.
Joint Decoding of Multiple-Description Network-Coded Data

This paper considers a transmission scheme combining multiple description coding (MDC) and network coding (NC). Our aim is to benefit from the property of MDC to provide progressive quality improvement with the number of received packets and from the efficient use of network resources provided by NC. MDC is performed either via frame expansion (NC-MDC-F) or via correlating transform (NC-MDC-T). With NC-MDC-F, when not enough NC have been received, reconstruction may be done via mixed integer quadratic programming (MIQP). With NC-MDC-T, the reconstruction involves simple Gaussian elimination. In both cases, a good robustness to missing NC packets is observed. When the number of missing packets is small, NC-MDC-F provides better SNR thanks to a reduction of a part of the quantization noise. The price to be paid is a decreased robustness to missing packets. When the number of lost packets increases, a reconstruction is still possible with NC-MDC-F for some packets, even if the number of missing packets is larger than $n-k$, the number of introduced redundancy packets. A typical application context is multicasting of multimedia contents with delay constraints. Users with very good channel conditions will benefit from the reception of redundant packets with NC-MDC-F, whereas these packets are useless with NC-MDC-T or with error-correcting NC.
Algorithms That Learn to Extract Information BBN: TIPSTER Phase III

All of BBN's research under the TIPSTER III program has focused on doing extraction by applying statistical models trained on annotated data, rather than by using programs that execute hand-written rules. Within the context of MUC-7, the SIFT system for extraction of template entities (TE) and template relations (TR) used a novel, integrated syntactic/semantic language model to extract sentence level information, and then synthesized information across sentences using in part a trained model for cross-sentence relations. At the named entity (NE) level as well, in both MET-1 and MUC-7, BBN employed a trained, HMM-based model.The results in these TIPSTER evaluations are evidence that such trained systems, even at their current level of development, can perform roughly on a par with those based on rules hand-tailored by experts. In addition, such trained systems have some significant advantages:• They can be easily ported to new domains by simply annotating fresh data. • The complex interactions that make rule-based systems difficult to develop and maintain can here be learned automatically from the training data.We believe that improved and extended versions of such trained models have the potential for significant further progress toward practical systems for information extraction.
Applying composite kernel to kernel-based nonparametric weighted feature extraction

In the recent researches show that nonparametric weighted feature extraction (NWFE) is a useful method for extracting hyperspectral image features. Kernel-based NWFE (KNWFE) is applying the kernel method to extend the more effective projected features in the feature space. It had been showed the performance of KNWFE is better than NWFE. In this study, we would apply a composite kernel function with spectral and spatial information to KNWFE, and hope this composite kernel to KNWFE can get a better performance than the spectral-based kernel function to KNWFE. In the experiment results show that the KNWFE with composite kernel, include the spectral and spatial information, outperforms the KNWFE with the only spectral based kernel function
Research Statement.docx

Information and Communications Technologies, despite being criticized for detracting from our social lives and communities, can often create and reinforce offline relationships. Companies like Meetup allow people to gather for group activities. Facebook connects high school friends for decades. My research focuses on how to support and enable similar communities in other contexts, including developing regions, crowdsourcing, and education.
Software Development in Small IT Firms: The Whitewater Method

Nearly 99% of all U.S. firms are small businesses and roughly half the private sector employees work for a small business. Yet surprisingly little research attention is given to IT and its role in small firms; neither from the small consumer nor producer perspective. This area is of increasing importance, as small firms struggle to grow and gain competitive advantage against the backdrop of rapid technological advancements. This paper looks at some of the more salient components of software usage and development gained from preliminary interviews with executives and IT workers at 3 small IT firms with the purpose of identifying how small firms address technology decisions related to the software they use and develop. Preliminary interviews have revealed that the development processes is distinctly different for small firms and the perspective from which they address key decisions in the development process is also different. In contrast to the traditional waterfall software development methodology we introduce the whitewater approach used by small IT developers.
Tupleware: A Distributed Tuple Space for Cluster Computing

This paper presents Tupleware, a cluster middleware which provides a distributed tuple space intended for use by computationally intensive scientific and numerical applications. It aims to add no extra burden to the application programmer due to the distribution of the tuple space, and uses a decentralised approach and intelligent tuple search and retrieval to provide a scalable and efficient execution environment. Tupleware is evaluated using two applications: a modified quicksort and an ocean model, which demonstrates good scalability and a low system overhead.