Miracle-dz/UniFAR-FTUs huggingface dataset:
HMM-Based Hierarchical Unit Selection Combining Kullback-Leibler Divergence with Likelihood Criterion

This paper presents a hidden Markov model (HMM) based unit selection method using hierarchical units under statistical criterion. In our previous work we tried to use frame sized speech segments and maximum likelihood criterion to improve the performance of traditional concatenative synthesis system using phone sized units and cost function criterion. In this paper, hierarchical units which consist of phone level units and frame level units are adopted to achieve better balance between the coverage rate of candidate unit and the number of concatenation points during synthesis. Besides, Kullback-Leibler divergence (KLD) between candidate and target phoneme HMMs is introduced as a part of the final criterion for unit selection. The listening result proves that these two approaches can improve the performance of synthetic speech effectively.
Calretinin-Periglomerular Interneurons in Mice Olfactory Bulb: Cells of Few Words

Within the olfactory bulb (OB), periglomerular (PG) cells consist of various types of interneurons, generally classified by their chemical properties such as neurotransmitter and calcium binding proteins. Calretinin (CR) characterizes morphologically and functionally the more numerous and one of the less known subpopulation of PG cells in the OB. Using of transgenic mice expressing eGFP under the CR promoter, we have tried to obtain the first functional characterization of these cells. Electrophysiological recordings were made in these cells using the patch-clamp technique in thin slices. Using ion substitution methods and specific blockers, we dissected the main voltage-dependent conductances present, obtaining a complete kinetic description for each of them. The more peculiar property of these cells from the electrophysiological point of view is the presence only of a single K-current, A-type – there is no trace of delayed rectifier or of Ca-dependent K-current. Other currents identified, isolated and fully characterized are a fast sodium current, a small L-type calcium current, and an inward rectifier, h-type cationic current. As a consequence of the peculiar complement of voltage-dependent conductances present in these cells, and in particular the absence of delayed-rectifier potassium currents, under the functional point of view these cells present two interesting properties. First, in response to prolonged depolarisations, after the inactivation of the A-current these cells behave as a purely ohmic elements, showing no outward rectification. Second, the CR cells studied can respond only with a single action potential to excitatory inputs; since they send inhibitory synapses to projection neurones, they seem to be designed to inhibit responses of the main neurones to isolated, random excitatory signals, rapidly losing their vetoing effect in response to more structured, repetitive excitatory signals. We propose that a possible role for these rather untalkative interneurons in the intense exchange of messages within the OB might be that of improving the signal-to-noise ratio in the first stages of the olfactory information processing.
Texture Mapping with Vector Graphics: A Nested Mipmapping Solution

Texture mapping with vector graphics, rather than raster graphics generates better rendering quality. This paper discusses a fully developed approach of texture mapping 3D objects with vector graphics. First, the vector graphics is rendered to generate the corresponding raster graphics, which is temporarily stored in the back framebuffer. Then, using the newly generated raster graphics, a pyramid of mipmap (LOD) images are dynamically generated and maintained. Finally, a “nested dynamic mipmapping” mechanism is applied to pick the right image to achieve the best resolution during rendering. VTexturer, was developed to test and evaluate the proposed approach. The system runs on the regular PCs with the MS Windows operating system, and is capable of using vector graphics in . wmf or . emf format to texture map grid or TIN based 3D objects. The experimental results show that our approach maintains good rendering performance and yields very satisfied results.
An improved algorithm for symbol segmentation of mathematical formula images

Due to the complex species, the changing dimensions and 2D nesting structure of mathematical formula symbols, the accuracy of symbol segmentation still cannot meet the actual needs. Projection is only suitable for simple mathematical formula without subscript and hierarchy. This paper presents a kind of improved algorithm based on the connected domain for symbol segmentation of mathematical formula images. At first, the image of mathematical formula is pre-processed, including gray scale processing, adaptive median filter, image thinning and other operations. Then the segmentation of mathematical formula image is studied and a segmentation method based on improved connected domain presented. This method makes full use of the inherent connected features of the symbols to obtain connected domain, then combine them according to the structural characteristics of symbols, finally achieves a precise character segmentation effect on segmenting the mathematical formula symbols with complex 2D nesting structure.
The Economics of the Supreme Court's Decision On Forward Looking Costs

In May 2002, the Supreme Court upheld the rules promulgated by the Federal Communications Commission (FCC) to implement provisions in the Telecommunications Act of 1996 (the Act) regarding mandatory resale of the components of local telephone networks. This article explains the background of the forward-looking pricing rules adopted by the FCC, the economic rational for their use, and the implications of the Court's ruling for the future of local telecommunications competition.
Theoretical Analysis of RF-DC Conversion Efficiency for Class-F Rectifiers

In this paper, an analytical model for the Class-F rectifier RF-dc conversion efficiency is presented. This model analyzes each kind of diode power losses in the rectifier due to the diode series resistor, junction capacitor, built-in potential, and breakdown voltage based on the time-domain diode voltage and current waveforms. The model provides a simple calculation routine to determine the threshold input power at which the peak reverse voltage across the diode starts to exceed the diode breakdown voltage and cause the diode efficiency to decrease. Two sets of closed-form equations are derived to calculate the Class-F rectifier efficiency in the input power region where the input power is either smaller or larger than the determined threshold input power, respectively. The implementation of a MATLAB code for the model calculation is also presented. Using this tool, the diode efficiency in Class-F rectifiers of different diode parameters can be easily determined, which provides a useful guideline for the optimal diode selection in various applications. The calculated diode efficiency using this model is compared with the Class-F rectifier ADS simulation at different load conditions, and all the results agree well with the model. To verify the model at different frequencies, two Class-F rectifiers working at 900 MHz and 5.8 GHz, respectively, are designed with the highest measured efficiency of 80.4% for the 900-MHz rectifier and 79.5% for the 5.8-GHz rectifier. Both of the measurement results agree well with the model prediction, which further verified the accuracy of the proposed model.
Technologies on establishing earthquake site communication network based on wireless mesh network

The earthquake site communication technologies are very important for the post-earthquake emergency and rescue work, with high requirements for convenient setup and stable data transmission. According to the real requirements, methods to establish the earthquake site communication network based on wireless mesh network (WMN) are proposed in this paper. A WMN is a special type of wireless ad hoc network and supports various wireless protocols. Some key issues (architecture, capacity, radio techniques, scalability, security, etc.) of WMN are discussed. On the basis of summarizing different applications supported by WMNs, an earthquake site communication network based on WMN is established. In such an application, various Wi-Fi clients are connected together and consequently facilitate the earthquake site rescue work. The methods are proved feasible and meaningful for real earthquake emergency and rescue work.
Community Detection Using Spectral Clustering on Sparse Geosocial Data

In this article we identify social communities among gang members in the Hollenbeck policing district in Los Angeles, based on sparse observations of a combination of social interactions and geographic locations of the individuals. This information, coming from Los Angeles Police Department (LAPD) Field Interview cards, is used to construct a similarity graph for the individuals. We use spectral clustering to identify clusters in the graph, corresponding to communities in Hollenbeck, and compare these with the LAPD's knowledge of the individuals' gang membership. We discuss different ways of encoding the geosocial information using a graph structure and the influence on the resulting clusterings. Finally we analyze the robustness of this technique with respect to noisy and incomplete data, thereby providing suggestions about the relative importance of quantity versus quality of collected data.
A metaBUS-enabled meta-analysis of career satisfaction

Purpose In this study, the authors revisit the meta-analytic correlates of career satisfaction and demonstrate the use of metaBUS – a database repository of meta-analytic effect sizes and related information from the field of applied psychology. The purpose of this paper is to extend prior meta-analytic research on the topic of career satisfaction and compare the results from the metaBUS-enabled meta-analysis, with the results from meta-analyses that do not build on the repository. Design/methodology/approach A multilevel meta-analysis was conducted on all correlates available in the metaBUS database and the approach was described in a step-by-step fashion. Findings The demonstration reiterated some of the findings of prior meta-analyses, but also revealed considerable incongruity between the sample taken from the metaBUS database and the meta-analytic sample from studies that relied on non-metaBUS-based literature searches. Nevertheless, the results are similar in terms of the directions of the effects and the relative sizes of the effects. Research limitations/implications The paper demonstrates the use of the metaBUS database. In addition, results suggest that meta-analyses on career satisfaction might have suffered from sample selection issues, but further research is required in order to establish the source of the sample selection incongruence. Originality/value This is the first step-by-step demonstration of the use of metaBUS specifically for meta-analyses.
Success Evaluation and Measures in Software Process Improvement

Purpose: Investigate and examine industry practice with regards to evaluation of process improvement, identification of measures and methods for success evaluations. The main reasoning is to use empirical data from industry, data from academia and research as input for suggesting proposals for improvement and discussion new avenues for future research in a field not addressed by e.g. traditional investment theory or marketing research. Method: Interviews were used and several data sources were elicited to gather empirical data. Literature surveys complemented this. Ultimately a triangulation approach was adopted to gradually and continuously compare and identify the chasms between academia and the reality and needs of industry. Results: The results can be described in three parts. First, there is a empirical investigation showing what measures and models are used in industry. These are discussed and put against literature (the academic view) in both the software engineering field, but relevant research is also scrutinized in business management field, e.g. investment theory. The second contribution is the concrete proposal of three methods for evaluating process improvement success. The first two of these are actually useable and take notice of the limitations identified in industry through the empirical investigation, i.e. no assumptions and theoretical models are presented in the first part of the proposal. The second part of the proposal is designed to present an outlook of the overall potential, provoking a discussion and ultimately leading out to a conclusion of future research needed in the field.
Investing in Development: Six High-Performing, High-Poverty Schools Implement the Massachusetts Teacher Evaluation Policy

We studied how six high-performing, high-poverty schools in one large Massachusetts city implemented the state’s new teacher evaluation policy. The sample includes traditional, turnaround, restart, and charter schools, each of which had received the state’s highest accountability rating. We sought to learn how these successful schools approached teacher evaluation, including classroom observations, feedback, and summative ratings. We interviewed 142 teachers and administrators and analyzed data using sensemaking theory, which considers how individuals’ knowledge and beliefs, the context in which they work, and the policy stimuli they encounter affect implementation. All schools prioritized the goal of developing their teachers over holding them accountable. The spillover effects of additional policies affected how these schools approached implementation.
The effect of the various doses of atorvastatin on renal tubular cells; an experimental study

Background Recent retrospective observational studies suggest that high-potency statin therapy might increase the risk of acute kidney injury, however data on this subject is scares. Objectives This study, was designed to investigate the renal tubular cell effect of different doses of atorvastatin to detect the possible aggravation of renal function or morphology of the kidney. Materials and Methods In this experimental study 24 male Wistar rats were designated into 4 equal groups and treated as follows. Control group received phosphate buffer as the vehicle of atorvastatin for 7 days. Groups 1, II and III received atorvastatin at doses of 10, 50 and 150 mg/kg daily for 7 days, then on the day 8, all rats were anesthetized using ketamine and the blood samples were collected for evaluation of creatinine (Cr) and blood urea nitrogen (BUN) levels and then all rats were sacrificed, then the animals’ kidneys were dissected out and histopathological studies were performed. Results Mean (±SD) of scores of injury to renal tubular cells in control group was 4.2 ± 2.2 and in groups I, II and III were 6.44 ± 4.9, 15.4 ± 8.5 and 25.8 ± 12.7 respectively. Group III which received 150 mg/kg/day of atorvastatin had significant renal damage in comparison to control group (P < 0.001). There was no significant difference of renal injury score between control group with groups of I and II. Conclusions In the present study we found, atorvastatin with a dose of 150 mg/kg/day for 7 days was nephrotoxic for rats, while lower doses at 10 mg/kg/day or 50 mg/kg/day for 7 days were not accompanied by renal injury. These findings imply further attention to the administration of higher doses of atorvastatin in clinical conditions.
Lack of TEK Gene Mutation in Patients with Cutaneomucosal Venous Malformations from the North-Western Region of Algeria

Background. Venous malformations (VM) result from an error in vascular morphogenesis. The first gene suspected in their development is the TEK gene (tyrosine kinase, endothelial). Mutations of this gene have been identified in several Belgian families with a dominant form of the disease. Therefore, we investigated whether mutations in this TEK gene could explain the MV development in patients of families from Tlemcen region (north-western Algeria). Methods. Genomic DNA was extracted from leucocytes of ten patients. The search for mutations in all the 23 exons and in the 5′ and 3′ intronic sequences flanking the TEK gene was performed using PCR amplification and direct sequencing of amplified genomic DNA. Additionally, a search for somatic mutations of the gene TEK was performed on a biopsy of the venous malformation from one of the ten eligible patients. Results. The sequencing of the 23 exons of the TEK gene revealed neither germinal mutation in our ten patients nor somatic mutation in the tissue of the biopsy. Conclusion. The absence of mutation in the TEK gene in the population studied suggests that the TEK gene is not necessarily involved in the onset of VM; its association with these malformations may differ from one population to another.
Long-Term Crime Desistance and Recidivism Patterns—Evidence from the Essex County Convicted Felon Study

Two conflicting definitions of desistance exist in the criminology literature. The first definition is instantaneous desistance in which an offender simply chooses to end a criminal career instantaneously moving to a zero rate of offending (Blumstein et al., 1986). The second definition views desistance as a process by which the offending rate declines steadily over time to zero or to a point close to zero (Bushway et al., 2001; Laub and Sampson, 2001; Leblanc and Loeber, 1998). In this article, we capitalize on the underlying assumptions of several parametric survival distributions to gain a better understanding of which of these models best describes actual patterns of desistance. All models are examined using 18 years of follow-up data on a cohort of felony convicts in Essex County, NJ. Our analysis leads us to three conclusions. First, some people have already desisted at the beginning of the follow-up period, which is consistent with the notion of “instantaneous desistance. ” Second, a three-parameter model that allows for a turning point in the risk of recidivism followed by a long period of decline fits the data best. This conclusion suggests that for those offenders active at the start of the study period, the risk of recidivism is declining over time. However, we also find that a simpler two-group model fits the data almost as well and gains superiority in the later years of follow-up. This last point is particularly relevant as it suggests that the observed gradual decline in the hazard over time is a result of a compositional effect rather than of a pattern of individually declining hazards.
Exploiting Path Diversity for Thwarting Pollution Attacks in Named Data Networking

With information becoming a first-class citizen on the Internet, information-centric networking (ICN) is considered as a promising direction for the future Internet. Named data networking (NDN) is a prominent example of emerging ICN architectures. Unfortunately, NDN is vulnerable to various attacks targeting its in-network caching mechanism. In this paper, we focus on the false-locality pollution attack, in which an adversary repeatedly requests a number of unpopular data objects to waste the precious cache space on the NDN router and to reduce normal users' hit ratios. With simulation experiments, we show that such an attack can cause considerable damage to the NDN network. To detect and mitigate such an attack, we introduce an algorithm that exploits the diversity of the Interest traversing paths within an Internet service provider's point-of-presence network. We also propose inexpensive methodologies based on the probabilistic counting and Bloom filter techniques to implement the algorithm on an NDN router. The experimental results indicate that our proposed algorithm is effective in thwarting false-locality pollution. We also experiment with strategies that the adversary may utilize against our antipollution algorithm and demonstrate that such strategies are either ineffective or impractical in the real world.
A Molecularly Cloned, Live-Attenuated Japanese Encephalitis Vaccine SA14-14-2 Virus: A Conserved Single Amino Acid in the ij Hairpin of the Viral E Glycoprotein Determines Neurovirulence in Mice

Japanese encephalitis virus (JEV), a mosquito-borne flavivirus that causes fatal neurological disease in humans, is one of the most important emerging pathogens of public health significance. JEV represents the JE serogroup, which also includes West Nile, Murray Valley encephalitis, and St. Louis encephalitis viruses. Within this serogroup, JEV is a vaccine-preventable pathogen, but the molecular basis of its neurovirulence remains unknown. Here, we constructed an infectious cDNA of the most widely used live-attenuated JE vaccine, SA14-14-2, and rescued from the cDNA a molecularly cloned virus, SA14-14-2MCV, which displayed in vitro growth properties and in vivo attenuation phenotypes identical to those of its parent, SA14-14-2. To elucidate the molecular mechanism of neurovirulence, we selected three independent, highly neurovirulent variants (LD50, <1.5 PFU) from SA14-14-2MCV (LD50, >1.5×105 PFU) by serial intracerebral passage in mice. Complete genome sequence comparison revealed a total of eight point mutations, with a common single G1708→A substitution replacing a Gly with Glu at position 244 of the viral E glycoprotein. Using our infectious SA14-14-2 cDNA technology, we showed that this single Gly-to-Glu change at E-244 is sufficient to confer lethal neurovirulence in mice, including rapid development of viral spread and tissue inflammation in the central nervous system. Comprehensive site-directed mutagenesis of E-244, coupled with homology-based structure modeling, demonstrated a novel essential regulatory role in JEV neurovirulence for E-244, within the ij hairpin of the E dimerization domain. In both mouse and human neuronal cells, we further showed that the E-244 mutation altered JEV infectivity in vitro, in direct correlation with the level of neurovirulence in vivo, but had no significant impact on viral RNA replication. Our results provide a crucial step toward developing novel therapeutic and preventive strategies against JEV and possibly other encephalitic flaviviruses.
Supervised learning of bag‐of‐features shape descriptors using sparse coding

We present a method for supervised learning of shape descriptors for shape retrieval applications. Many content‐based shape retrieval approaches follow the bag‐of‐features (BoF) paradigm commonly used in text and image retrieval by first computing local shape descriptors, and then representing them in a ‘geometric dictionary’ using vector quantization. A major drawback of such approaches is that the dictionary is constructed in an unsupervised manner using clustering, unaware of the last stage of the process (pooling of the local descriptors into a BoF, and comparison of the latter using some metric). In this paper, we replace the clustering with dictionary learning, where every atom acts as a feature, followed by sparse coding and pooling to get the final BoF descriptor. Both the dictionary and the sparse codes can be learned in the supervised regime via bi‐level optimization using a task‐specific objective that promotes invariance desired in the specific application. We show significant performance improvement on several standard shape retrieval benchmarks.