gebhart/patrepeval huggingface dataset:
A Cross-Language State Sharing and Mapping Approach to Bilingual (Mandarin–English) TTS (2009)

We propose a hidden Markov model (HMM)-based bilingual (Mandarin and English) text-to-speech (TTS) system to synthesize natural speech for given bilingual text. A simple baseline system consisting of two independent monolingual HMM synthesizers is built first from corresponding Mandarin and English data recorded by a bilingual speaker. A new, mixed language TTS is then constructed by asking language-independent and language-specific questions for sharing HMM states across the two languages in decision-tree based clustering. By sharing states, the new system has a smaller footprint than the baseline system. Speech synthesized by the new system sounds very similar to the baseline for non-mixed, Mandarin or English, monolingual sentences but much better for mixed-language sentences. This higher quality of mixed-language output is confirmed by a preference score, 60.2% to 39.8%, in a subjective listening test. A cross-language state mapping algorithm is further proposed for cross-language synthesis when only monolingual (English) recorded data from a source language speaker is available. Mandarin speech is then synthesized with the HMM model parameters in the nearest neighbor leaf nodes of the English decision tree. The nearest neighbor is measured with the Kullback-Leibler divergence (KLD) and mappings between leaf nodes in the decision trees of the source and target languages are established via the speech data recorded by a different, bilingual speaker. High voice (speaker) similarity is preserved in the synthesized target language sentences by using the recording of a source language from a monolingual speaker. Perceptual test results conducted on synthesized Mandarin speech show 1) high intelligibility which is confirmed by a Chinese character transcription accuracy of 92.1% and 2) decent speech quality with an average MOS score of 3.1.
Characterizing in vivo loss of virulence of an HN878 Mycobacterium tuberculosis isolate from a genetic duplication event (2022)

The increase of global cases of drug resistant (DR) Mycobacterium tuberculosis (M.tb) is a serious problem for the tuberculosis research community and the goals to END TB by 2030. Due to the need for advancing and screening next generation therapeutics and vaccines, we aimed to design preclinical DR models of Beijing lineage M.tb HN878 strain in different mouse backgrounds. We found escalating sensitivities of morbidity due to low dose aerosol challenge (50-100 bacilli) in CB6F1, C57BL/6 and SWR mice, respectively. We also observed that pulmonary bacterial burden at morbidity endpoints correlated inversely with survival over time between mouse strains. Interestingly, with in vitro passaging and in the process of selecting individual DR mutant colonies, we observed a significant decrease in in vivo HN878 strain virulence, which correlated with the acquisition of a large genetic duplication. We confirmed that low passage infection stocks with no or low prevalence of the duplication, including stocks directly acquired from the BEI resources biorepository, retained virulence, measured by morbidity over time. These data help confirm previous reports and emphasize the importance of monitoring virulence and stock fidelity.
Patient factors influencing a delay in diagnosis in pediatric spinal cord tumors. (2022)

The diagnosis of pediatric spinal cord tumor is frequently delayed due to the presence of non-specific symptoms. We investigated the factors influencing the delay between the first symptom presentation and the diagnosis for pediatric spinal cord tumor. We retrospectively analyzed 31 patients of age <20 years (18 men, 13 women) who underwent surgery for spinal cord tumor at a single center during 1998-2018. We extracted the relevant data on patients' symptoms, affected spinal location (cervical: C1-7, thoracic: T1-T12, and lumbosacral: L1-S), and tumor anatomical location (extradural, intradural extramedullary, and intramedullary tumor) that could potentially affect the duration of symptom presentation prior to the diagnosis. The most common symptom presented in the patients was pain (n = 22, 71.0 %). Motor symptoms such as paralysis was associated with early diagnosis (P = 0.039). The duration of symptoms prior to diagnosis was found to be significantly longer in patients with spinal tumor in the lumbar-sacral region than in those with the involvement of the cervical and thoracic regions (2.1 ± 1.7 months vs 13.6 ± 12.1 months; P = 0.006 and 2.9 ± 2.2 months vs 13.6 ± 12.1 months; P = 0.012, respectively). Our study results demonstrated that pain was the most common symptom in the examined patients, although it did not affect the delay in diagnosis, whereas the presentation of motor symptoms was helpful in the diagnosis of pediatric spinal cord tumor and the diagnosis could be delayed in lumbar-sacral spinal tumors.
An adaptative game loop architecture with automatic distribution of tasks between CPU and GPU (2009)

This article presents a new architecture to implement all game loop models for games and real-time applications that use the GPU as a mathematics and physics coprocessor, working in parallel processing mode with the CPU. The presented model applies automatic task distribution concepts. The architecture can apply a set of heuristics defined in Lua scripts in order to get acquainted with the best processor for handling a given task. The model applies the GPGPU (general-purpose computation on GPUs) paradigm. In this article we propose an architecture that acquires knowledge about the hardware by running tasks in each processor and, by studying their performance over time, finding the best processor for a group of tasks.
[Conduction aphasia and phonemic disorder]. (2001)

Conduction aphasia is usually described as a repetition impairment. Semiology or pathophysiology cannot be explained with this definition. We report a single case particularly demonstrative. The patient showed spontaneous speech, denomination, repetition and reading impairments. Main errors were phonemic paraphasia. No arthric disorder nor comprehension impairment was observed. Damage of supramarginalis gyrus and Wernicke's area was found. A cognitive analysis suggested that the phonological buffer and the working memory were impaired. Implication for rehabilitation, which included segmentation and semantisation associated to phonological training, is discussed. The course of the conduction aphasia was good and the patient was able to work again.
RETRACTED: Risk factors for symptoms of infection and microbial carriage among French medical students abroad (2020)

This study makes it possible to identify the leading infectious diseases linked to travel in a group of French medical students undertaking an internship abroad and the risk factors on which to base targeting students for reinforced pre-travel advice.
Total Synthesis of the Ristocetin Aglycon (2004)

The first total synthesis of the ristocetin aglycon is described employing a modular and highly convergent strategy. An effective 12-step (12% overall) synthesis of the ABCD ring system 3 from its amino acid subunits sequentially features an intramolecular aromatic nucleophilic substitution reaction for formation of the diaryl ether and closure of the 16-membered CD ring system (65%), a respectively diastereoselective (3:1, 86%) Suzuki coupling for installation of the AB biaryl linkage on which the atropisomer stereochemistry can be further thermally adjusted, and an effective macrolactamization (51%) for closure of the 12-membered AB ring system. A similarly effective 13-step (14% overall) synthesis of the 14-membered EFG ring system 4 was implemented employing a room-temperature intermolecular S(N)Ar reaction of an o-fluoronitroaromatic for formation of the FG diaryl ether (69%) and a key macrolactamization (92%) with formation of the amide linking residues 1 and 2. The two key fragments 3 and 4 were coupled, and the remaining 16-membered DE ring system was closed via diaryl ether formation to provide the ristocetin tetracyclic ring system (15 steps, 8% overall) enlisting an unusually facile (25 degrees C, 8 h, DMF, >/=95%) and diastereoselective (>/=15:1) aromatic nucleophilic substitution reaction that benefits from substrate preorganization.
Dynamic D2D Communication in 5G/6G Using a Distributed AI Framework (2022)

This paper focuses on D2D communication for 5G/6G in dynamic environments where the D2D network topology changes through time due to D2D Devices&#x2019; mobility. Specifically, we consider a scenario within the coverage area of a Base Station (BS) serving a number of User Devices (UEs), with variations in speed and direction causing changes in the D2D network topology, either via direct connections or via D2D single-hop or D2D Multi-hop paths. Based on this scenario, we formulate a problem aiming to maximise the total Spectral Efficiency (SE) whilst minimising the total Power Consumption (PC), by selecting the best transmission mode that the D2D devices will operate. In order to address the aforementioned problem, the Distributed Artificial Intelligence Solution (DAIS) plan proposed in our earlier work and designed for static environments is extended to consider the mobility (i.e., speed, direction and indirectly link distance change) of the D2D Device, targeting the dynamic creation of stable and efficient clusters and good backhauling links towards the gateway. The enhanced DAIS performance is comparatively evaluated in terms of SE and PC against selected variations in UE speed and direction, changes in the link Transmission Power (TP), and an increase in the number of Devices in the D2D network. Overall, the results obtained demonstrated superior performance of enhanced DAIS over all the other related investigated approaches (i.e., Distributed Sum Rate (DSR), Single Hop Relay Approach (SHRA), Distributed Random (DR)), in terms of Spectral Efficiency (SE) and Power Consumption (PC). Also, the ability of enhanced DAIS to react and adapt quickly and efficiently to D2D network topology changes, with reduced signalling overhead and control delay in responding to changes, shows that it is a well-poised approach to be used in a Dynamic D2D Environment.
Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound (2003)

A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.
Computer Analysis of Sequence Data (1994)

DNA sequencing methodology was developed in the late 1970s (1,2) and has become one of the most widely used techniques in molecular biology. The amount of DNA sequencing performed worldwide has increased exponentially each year and this trend will almost certainly continue for the next few years at least. The importance of this technique is underlined by the volume of research funds now being channelled into genome sequencing projects, and by the large sums of money being invested in the development of automated sequencers and sequence analysis systems.
A Linearity-Enhanced Compact Series-Type Doherty Amplifier Suitable for CDMA Handset Applications (2007)

A high-linearity series-type Doherty amplifier that does not use bulky 3 dB quadrature hybrid coupler is developed for mobile handset applications. A predistorter is employed at the input to improve the ACPR performance at the high-power region, which effectively extends maximum linear power range. For size and stability considerations, the phasing circuits between the carrier and peak amplifiers have been realized using high-pass T-networks. The series-type Doherty amplifier of this work shows PAE's of 18% and 42.8% at 16 dBm and 28 dBm, while meeting the IS-95A ACPR requirement of -42 dBc
Functional Data Analysis of Dynamic PET Data (2018)

One application of positron emission tomography (PET), a nuclear imaging technique, in neuroscience involves in vivo estimation of the density of various proteins (often, neuroreceptors) in the brain. PET scanning begins with the injection of a radiolabeled tracer that binds preferentially to the target protein; tracer molecules are then continuously delivered to the brain via the bloodstream. By detecting the radioactive decay of the tracer over time, dynamic PET data are constructed to reflect the concentration of the target protein in the brain at each time. The fundamental problem in the analysis of dynamic PET data involves estimating the impulse response function (IRF), which is necessary for describing the binding behavior of the injected radiotracer. Virtually all existing methods have three common aspects: summarizing the entire IRF with a single scalar measure; modeling each subject separately; and the imposition of parametric restrictions on the IRF. In contrast, we propose a functional data analytic approach that regards each subject's IRF as the basic analysis unit, models multiple subjects simultaneously, and estimates the IRF nonparametrically. We pose our model as a linear mixed effect model in which population level fixed effects and subject-specific random effects are expanded using a <i>B</i>-spline basis. Shrinkage and roughness penalties are incorporated in the model to enforce identifiability and smoothness of the estimated curves, respectively, while monotonicity and non-negativity constraints impose biological information on estimates. We illustrate this approach by applying it to clinical PET data with subjects belonging to three diagnosic groups. We explore differences among groups by means of pointwise confidence intervals of the estimated mean curves based on bootstrap samples.
Direct Fabrication of Joints based on Direct Metal Laser Sintering in Aluminum and Titanium Alloys (2014)

Application of direct metal laser sintering for manufacturing three-dimensional objects represents one of the promising directions for the industries. Through this technology is possible to create an object with desired shape and material properties in order to meet a variety of applications. However, most reported applications are for static parts. There are only limited reports about direct rapid fabrication of mechanisms that could be considered as the core subsystems for many machine and robotic designs. So the main purposes of this study are the investigation and application of direct metal laser sintering (DMLS) in fabricating non-assembly mechanisms systems in AlSi10Mg and Ti6Al4 V alloys.
New Insight into Integrated Reservoir Management using Top-Down, Intelligent Reservoir Modeling Technique; Application to a Giant and Complex Oil Field in the Middle East (2010)

Abstract This paper demonstrates the validity of a recently developed reservoir modeling technique called "Top-Down, Intelligent Reservoir Modeling" (will be referred to Top-Down Modeling for short). This new modeling technology integrates reservoir engineering analytical techniques with Artificial Intelligence &amp; Data Mining (AI&amp;DM) in order to arrive at an empirical, cohesive and spatiotemporally calibrated full field model. The model is used to predict reservoir performance in order to recommend field development strategies. One of the distinctive features of this technology is its data requirement for analysis. Although Top-Down Modeling can incorporate almost any type and amount of data that is available in the modeling process, it only requires monthly production rate and some well log data (porosity, initial water saturation and thickness) in order to start the analysis and provide a full field model. Presence and incorporation of other types of data such as core analysis, pressure data, reservoir characteristics and seismic data can and will increase the accuracy and validity of the developed model. In this work, we apply Top-Down Modeling to a large and complex Oil field in the Middle East that produces from a combination of clastic and carbonate formations. Production rates and well log data from 210 wells have been analyzed and imported into the Top-Down Modeling software to develop a new empirical reservoir model and make predictions on new well performance and potential infill locations. Results from Top-Down Modeling analyses are compared with results concluded from a comprehensive reservoir management study (that included use of large amount and various types of data and a commercial numerical reservoir simulator) performed by an IOC. Analytical reservoir engineering techniques used in the Top-Down Modeling presented in this study include production decline analysis, volumetric reserve and recovery factor estimations and are integrated with Voronoi graph theory, geostatistics, two-dimensional Fuzzy Pattern Recognition (FPR), and discrete, data driven predictive modeling. The resulting full field Top-Down Modeling is used to identify the distribution of the remaining reserves, sweet spots for infill locations and under-performer wells and also identify the locations in the reservoir where gas cap is formed. Furthermore, the fullfield model is used to predict new well’s performance.
Signaling TO Prevent SPIT (SPITSTOP) Reference Scenario (2008)

This memo discusses the need for standards that support SPam over
Internet Telephony (SPIT) prevention applications. After explaining
the general need for SPIT prevention applications the memo provides a
reference scenario for potential communication between entities that
may be involved in SPIT prevention. Within this scenario the need for
standardizing communication is analyzed for each pair of communicating
entities. The analysis is intended to serve as a starting point for
discussing the requirements for signaling standards as well as for
architectural considerations, that support SPIT prevention
applications. This memo is not intended to suggest any solution of
SPIT signaling issues. Such work, if necessary at all, should be
object of separate documents.
Meteor burst and other long distance high latitude propagation modes in the low VHF band (1994)

We have analysed the duty cycle from very high frequency polar cap and auroral paths in Greenland. We find that at 35 MHz and 45 MHz the path is often sustained by sporadic E-layers rather than by meteor scatter. At the higher frequencies of 65 MHz and 85 MHz we find that the path is generally dominated by meteor scatter modes. The diurnal, seasonal and geomagnetic variations of sporadic E have been examined and off line decision aid models have been derived to evaluate the magnitude of multiple mechanism propagation on the paths.
Reactive Ion Etching of InP using Hydrocarbons (2002)

This paper deals with the development of an etch recipe for the etching of InP by Reactive ion etching (RIE), a vital process step in the fabrication of microstructures. RIE is a dry etching scheme, wherin effective pattern transfer can be achieved due to its inherent anisotropic characteristics for certain process conditions. RIE is preferred to other dry etching schemes since it is simple, robust and is widely used in industry. The main aim of our research is to design micromechanically tunable optical filters for wavelength division multiplexing (WDM) systems. In this system, transmission takes place in the second and third optical communication window, namely in the region of zero material dispersion (1300 nm) and minimum attenuation (1550 nm) respectively. InP based devices are widely used for this application since they are compatible with the above mentioned WDM transmission wavelengths. The key properties investigated in this thesis were the material etch rate, the selectivity of the material with res to the mask, the side wall steepness and the surface morphology. The examined process parameters have been the rf-power, the flow rate, the pressure inside the chamber, the substrate temperature and the various ratios of gas combinations. Improved values of etch rate and selectivity have been achieved with respect to past results by optimizing the process conditions. Etch rates as high as 120 nm/min have been achieved using CH4 / H2 with infinite values of selectivity for certain process parameters. Measurements have also been made on InP samples using the scanning electron microscope and the atomic force microscope for determining the side wall steepness and the roughness of the etched surface. Side wall slopes close to 90° and surface roughnesses below 0.4 nm (rms) have been achieved. The earlier reported problems of polymer deposition on top of the mask was strongly suppressed. In addition measurements have been carried out on various samples to establish process stability, an absolute necessity for realis vel recipe.
An enantioselective approach to 2-alkyl substituted tetrahydroquinolines: total synthesis of (+)-angustureine (2015)

A simple and highly efficient synthetic approach to enantiopure 2-alkyl substituted tetrahydroquinoline <bold>1</bold> skeleton from aldehydes as starting materials and its application to the total synthesis of (+)-angustureine <bold>2</bold> is described.