Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing the applicability of reinforcement learning to autonomous control

With data-efficient reinforcement learning (RL) methods impressive results could be achieved, e.g., in the context of gas turbine control. However, in practice the application of RL still requires much human intervention, which hinders the application of RL to autonomous control. This thesis addresses some of the remaining problems, particularly regarding the reliability of the policy generation process. The thesis first discusses RL problems with discrete state and action spaces. In that context, often an MDP is estimated from observations. It is described how to incorporate the estimators’ uncertainties into the policy generation process. This information can then be used to reduce the risk of obtaining a poor policy due to flawed MDP estimates. Moreover, it is discussed how to use the knowledge of uncertainty for efficient exploration and the assessment of policy quality without requiring the policy’s execution. The thesis then moves on to continuous state problems and focuses on methods based on fitted Q-iteration (FQI), particularly neural fitted Q-iteration (NFQ). Although NFQ has proven to be very data-efficient, it is not as reliable as required for autonomous control. The thesis proposes to use ensembles to increase reliability. Several ways of ensemble usage in an NFQ context are discussed and evaluated on a number of benchmark domains. It shows that in all considered domains with ensembles good policies can be produced more reliably. Next, policy assessment in continuous domains is discussed. The thesis proposes to use fitted policy evaluation (FPE), an adaptation of FQI to policy evaluation, combined with a different function approximator and/or different dataset to obtain a measure for policy quality. Results of experiments show that extra-tree FPE, applied to policies generated by NFQ, produces value functions that can well be used to reason about the true policy quality. Finally, the thesis combines ensembles and policy assessment to derive methods that can deal with changing environments. The major contribution is the evolving ensemble. The policy of the evolving ensemble changes slowly as new policies are added and old policies removed. It turns out that the evolving ensemble approaches work considerably better than simpler approaches like single policies learned with recent observations or simple ensembles.
The Primordial Gravitational Wave Background in String Cosmology

We find the spectrum P(w)dw of the gravitational wave background produced in the early universe in string theory. We work in the framework of String Driven Cosmology, whose scale factors are computed with the low-energy effective string equations as well as selfconsistent solutions of General Relativity with a gas of strings as source. The scale factor evolution is described by an early string driven inflationary stage with an instantaneous transition to a radiation dominated stage and successive matter dominated stage. This is an expanding string cosmology always running on positive proper cosmic time. A careful treatment of the scale factor evolution and involved transitions is made. A full prediction on the power spectrum of gravitational waves without any free-parameters is given. We study and show explicitly the effect of the dilaton field, characteristic to this kind of cosmologies. We compute the spectrum for the same evolution description with three differents approachs. Some features of gravitational wave spectra, as peaks and asymptotic behaviours, are found direct consequences of the dilaton involved and not only of the scale factor evolution. A comparative analysis of different treatments, solutions and compatibility with observational bounds or detection perspectives is made.
Design and evaluation of electrical machine for parallel hybrid drive for heavy vehicles

This paper focuses on the electromagnetic design and experimental evaluation of a (insert) permanent magnet synchronous machine (IPMSM) for hybrid commercial heavy vehicle applications. The machine specifications are based on drive cycle simulations with a set of target vehicles and drive cycles. The goals for the machine design are to fulfil the specification including a wide constant power range and an overload capability, all to be realized in the strictly limited space in the vehicle. The torque speed characteristics are shown for the designed machine including the temperature dependence, winding arrangement, etc. The prototype is built and experimentally verified. The comparison shows that the design considerations in the modelling match the measured results.
CHEMOMETRIC-BASED ELECTRONIC NOSE APPLICATION TO PORK OIL AND OLIVE OIL USING THE ODOR PATTERN CLASSIFICATIONS

A chemometric-based electronic nose has designed for analyzing pork oil and olive oil using the odor pattern classifications. The electronic nose (e-nose) built from a combination of several chemical sensors derived from a semiconductor. The data retrieval was done by vaporizing the sample, then being captured by the sensor and identified by the electronic nose (e-nose). The output data from the electronic nose is the voltage released by each sensor. The analyzed samples were 100% olive oil, 100% pork oil and a combination of olive oil and pork oil with a ratio of 50%: 50%. The result of pattern classification using linear discriminant analysis (LDA) method shows that each sample is clustered well with the percentage of first discriminant function value is 87,9% and second discriminant function is 12,1%.
Scalability and Total Recall with Fast CoveringLSH

Locality-sensitive hashing (LSH) has emerged as the dominant algorithmic technique for similarity search with strong performance guarantees in high-dimensional spaces. A drawback of traditional LSH schemes is that they may have false negatives, i.e., the recall is less than 100%. This limits the applicability of LSH in settings requiring precise performance guarantees. Building on the recent theoretical "CoveringLSH" construction that eliminates false negatives, we propose a fast and practical covering LSH scheme for Hamming space called Fast CoveringLSH (fcLSH). Inheriting the design benefits of CoveringLSH our method avoids false negatives and always reports all near neighbors. Compared to CoveringLSH we achieve an asymptotic improvement to the hash function computation time from O(dL) to O(d + (LlogL), where d is the dimensionality of data and L is the number of hash tables. Our experiments on synthetic and real-world data sets demonstrate that fcLSH is comparable (and often superior) to traditional hashing-based approaches for search radius up to 20 in high-dimensional Hamming space.
Exceptional events classification in the Portuguese quality of electricity supply regulation

This paper addresses the concept of the classification of exceptional events (EE) introduced, in 2013, during the revision of the Portuguese quality of electricity supply code. An exceptional event is classified as such by the Portuguese national regulatory authority after a request from the network operator. The request must include a detailed description of the incident and the collected evidence, in order to prove that the four cumulative criteria for the classification as exceptional event are satisfied. The procedure for the classification of exceptional events was applied to requests submitted in 2014 by the main Portuguese distribution system operator.
Use of pulsed-field gel electrophoresis for detecting differences in Staphylococcus aureus strain populations between dairy herds with different cattle importation practices

The hypothesis tested was that dairy herds which import cattle for replacement or expansion have a higher prevalence of Staphylococcus aureus mastitis and a greater number of new Staphylococcus aureus strains enter their herds than closed herds. Fifteen commercial dairy herds were divided into four groups based on cattle importation practices. Composite foremilk samples were collected at 4-monthly intervals for 1 year from all lactating cattle. Additionally, foremilk samples were collected from cattle at parturition and skin swabs were taken from the udder of primiparous heifers. All samples were cultured for Staphylococcus aureus and isolates were strain-typed using pulsed-field gel electrophoresis. Herds that purchased replacement heifers had a higher prevalence of Staphylococcus aureus mastitis than herds that purchased lactating cattle for expansion (P = 0.02). Herds that purchased replacement heifers had more total strains of Staphylococcus aureus (P = 0.01) and more new strains (P = 0.04) enter the herd than closed herds.
Online Non-Preemptive Scheduling in a Resource Augmentation Model Based on Duality

Resource augmentation is a well-established model for analyzing algorithms, particularly in the online setting. It has been successfully used for providing theoretical evidence for several heuris-tics in scheduling with good performance in practice. According to this model, the algorithm is applied to a more powerful environment than that of the adversary. Several types of resource augmentation for scheduling problems have been proposed up to now, including speed augmentation , machine augmentation and more recently rejection. In this paper, we present a framework that unifies the various types of resource augmentation. Moreover, it allows generalize the notion of resource augmentation for other types of resources. Our framework is based on mathematical programming and it consists of extending the domain of feasible solutions for the algorithm with respect to the domain of the adversary. This, in turn allows the natural concept of duality for mathematical programming to be used as a tool for the analysis of the algorithm's performance. As an illustration of the above ideas, we apply this framework and we propose a primal-dual algorithm for the online scheduling problem of minimizing the total weighted flow time of jobs on unrelated machines when the preemption of jobs is not allowed. This is a well representative problem for which no online algorithm with performance guarantee is known. Specifically, a strong lower bound of Ω(√ n) exists even for the offline unweighted version of the problem on a single machine. In this paper, we first show a strong negative result even when speed augmentation is used in the online setting. Then, using the generalized framework for resource augmentation and by combining speed augmentation and rejection, we present an (1+ s)-speed O(
Modeling of Network Traffic

Traffic models are at the heart of any performance evaluation of telecommunication networks. An accurate estimation of network performance is critical for the success of broadband networks, which need to guarantee acceptable quality of service (QoS) to the users. A good traffic model should be accurate enough to capture the statistical characteristics of actual traffic, and at the same time should be computationally efficient. Recent analysis of network traffic reveals the presence of long-range dependence (LRD), a statistical property which traditional traffic models cannot capture. This report discusses modeling of traffic with both short-range and long-range dependent models. The relatively new field of multifractal modeling has also been explored. Keywords—Network Traffic, Short Range and Long Range Dependence, Self Similarity, Wavelets, Point Processes, Multifractals .
Cellular Imaging of Inflammation after Experimental Spinal Cord Injury

The ability to visualize the cellular inflammatory responses after experimental spinal cord injury (SCI) was investigated using a clinical 1.5-T magnetic resonance imaging scanner, a custom-built, high-strength gradient coil insert, a 3-D fast imaging employing steady-state acquisition (FIESTA) imaging sequence and a superparamagnetic iron oxide (SPIO) contrast agent. An “active labeling” approach was used, with SPIO administered intravenously at different time points following SCI. Our results show that this strategy can be used to visualize clusters of iron-labeled cells associated with the inflammatory response in SCI. Of particular importance for this application was the finding that in FIESTA images hemorrhage does not cause signal loss. In T2-weighted spin echo or T2*-weighted gradient-echo images, which are more commonly used to detect signal loss associated with SPIO, the signal loss associated with hemorrhage interferes with the detection of iron-induced signal loss. FIESTA, therefore, allowed us to discriminate between iron associated with blood products in hemorrhage that occurs in acute SCI and the iron associated with SPIO-labeled cells accumulating in the injured cord.
Two-Year Monitoring of Water Samples from Dam of Iskar and the Black Sea, Bulgaria, by Molecular Analysis: Focus on Mycobacterium spp.

The coast of the Bulgarian Black Sea is a popular summer holiday destination. The Dam of Iskar is the largest artificial dam in Bulgaria, with a capacity of 675 million m3. It is the main source of tap water for the capital Sofia and for irrigating the surrounding valley. There is a close relationship between the quality of aquatic ecosystems and human health as many infections are waterborne. Rapid molecular methods for the analysis of highly pathogenic bacteria have been developed for monitoring quality. Mycobacterial species can be isolated from waste, surface, recreational, ground and tap waters and human pathogenicity of nontuberculose mycobacteria (NTM) is well recognized. The objective of our study was to perform molecular analysis for key-pathogens, with a focus on mycobacteria, in water samples collected from the Black Sea and the Dam of Iskar. In a two year period, 38 water samples were collected—24 from the Dam of Iskar and 14 from the Black Sea coastal zone. Fifty liter water samples were concentrated by ultrafiltration. Molecular analysis for 15 pathogens, including all species of genus Mycobacterium was performed. Our results showed presence of Vibrio spp. in the Black Sea. Rotavirus A was also identified in four samples from the Dam of Iskar. Toxigenic Escherichia coli was present in both locations, based on markers for stx1 and stx2 genes. No detectable amounts of Cryptosporidium were detected in either location using immunomagnetic separation and fluorescence microscopy. Furthermore, mass spectrometry analyses did not detect key cyanobacterial toxins. On the basis of the results obtained we can conclude that for the period 2012–2014 no Mycobacterium species were present in the water samples. During the study period no cases of waterborne infections were reported.
Non-motor symptoms profile and burden in drug naïve versus long-term Parkinson's disease patients.

BACKGROUND Recent studies have demonstrated that, contrary to common perception non-motor symptoms (NMS) occur and may dominate early and untreated stage of Parkinson's disease (PD). OBJECTIVE The aim of this ongoing study was to describe the overall NMS profile and burden in drug naïve PD patients (DNPD) compared to a group of long-term PD patients (LTPD, disease duration ≥15 years). METHODS Cross sectional UK data from a multicenter (16 sites) collaboration were obtained and specifically NMS dataset from validated scales were analysed in DNPD and LTPD patients. The NMS scale (NMSS) was used as the primary outcome variable. RESULTS Out of a current database of 468 PD patients, 57 were DNPD (58% males, mean age 64.8 years, median Hoehn and Yahr stage 1) and 25 were LTPD (44%, mean age 67.6 years, median Hoehn and Yahr stage 3). DNPD patients had a significantly lower (p = 0.001) NMSS score (mean 45.5, range 1-150) compared to the LTPD patients (mean 74.0, range 6-155), but 26.3% had severe and 19.3% had very severe burden of NMSS using NMSS cutoff scores. In comparison, 20.0% of the LTPD patients had severe and 60.0% very severe burden of NMS (p = 0.003). CONCLUSIONS NMS are common in DNPD patients and over 45% may have severe to very severe burden of NMS, which is a key determinant of quality of life. In LTPD patients not only the burden of "very severe" NMS is significantly higher, but there are also differences in the profile of expression of NMS.
Delay of vaccinia virus-induced apoptosis in nonpermissive Chinese hamster ovary cells by the cowpox virus CHOhr and adenovirus E1B 19K genes

The infection of vaccinia virus in Chinese hamster ovary (CHO) cells produces a rapid shutdown in protein synthesis, and the infection is abortive (R.R. Drillien, D. Spehner, and A. Kirn, Virology 111:488-499, 1978; D.E. Hruby, D.L. Lynn, R. Condit, and J.R. Kates, J. Gen. Virol. 47:485-488, 1980). Cowpox virus, which can productively infect CHO cells, had previously been shown to contain a host range gene, CHOhr, which confers on vaccinia virus the ability to replicate in CHO cells (D. Spehner, S. Gillard, R. Drillien, and A. Kirn, J. Virol. 62:1297-1304, 1988). We found that CHO cells underwent apoptosis when infected with vaccinia virus. The expression of the CHOhr gene in vaccinia virus allowed for the expression of late virus genes. CHOhr also delayed or prevented vaccinia virus-induced apoptosis in CHO cells such that there was sufficient time for replication of the virus before the cell died. The E1B 19K gene from adenovirus also delayed vaccinia virus-induced apoptosis; however, there was no detectable expression of late virus genes. Furthermore, E1B 19K also delayed cell death in CHO cells which had been productively infected with vaccinia virus. This study identifies a new antiapoptotic gene from cowpox virus, CHOhr, for which the protein contains an ankyrin-like repeat and shows no significant homology to other proteins. This work also indicates that an antiapoptotic gene from one virus family can delay cell death in an infection of a virus from a different family.
Adiabatic westward drift of Indian monsoon depressions

A large fraction of the rain received by continental India is produced by cyclonic vortices with outer radii of about 1000 km that are contained within the larger scale South Asian monsoon flow. The more intense occurrences of these vortices are called monsoon depressions; these consist of bottom‐heavy columns of relative vorticity that propagate to the northwest in time‐mean low‐level eastward flow. Previous studies have argued that this apparent upstream propagation is caused by dynamical lifting west of the vortex centre, with the resulting ascent producing vortex stretching that shifts the vortex to the west. Here, analysis of over 100 Indian monsoon depressions is used to show that low‐level vortex stretching has a spatial structure inconsistent with the observed propagation and is balanced by other terms in the low‐level vorticity budget. Instead, monsoon depressions are shown to consist of potential vorticity maxima that have peak amplitude in the middle troposphere and propagate westward by nonlinear, horizontal adiabatic advection (i.e. beta drift). The precipitating ascent in monsoon depressions makes a more minor contribution to the total storm motion and primarily acts to maintain the upright structure of the vortex. These results suggest a new view of Indian monsoon depressions as potential vorticity columns that propagate primarily by adiabatic dynamics.
Web information extraction using markov logic networks

In this paper, we consider the problem of extracting structured data from web pages taking into account both the content of individual attributes as well as the structure of pages and sites. We use Markov Logic Networks (MLNs) to capture both content and structural features in a single unified framework, and this enables us to perform more accurate inference. MLNs allow us to model a wide range of rich structural features like proximity, precedence, alignment, and contiguity, using first-order clauses. We show that inference in our information extraction scenario reduces to solving an instance of the maximum weight subgraph problem. We develop specialized procedures for solving the maximum subgraph variants that are far more efficient than previously proposed inference methods for MLNs that solve variants of MAX-SAT. Experiments with real-life datasets demonstrate the effectiveness of our MLN-based approach compared to existing state-of-the-art extraction methods.
Object-oriented techniques for distributed computation

Distributed applications are currently built by means of a wide spectrum of programming and design techniques. This spectrum spans various dimensions, such a technique’s dependency on languages, protocols, or software products, its adherence to some design or programming paradigm, the nature and complexity of its intended applications. This paper surveys some interesting object-oriented techniques. The survey groups them first of all according to their degree of dependency on particular protocols or languages: the main division is between general frameworks (such as CORBA) and Web-based systems (such as CGI scripts). The latter may be further categorized according to their requirements on browsers. Within this main scheme, the other relevant aspects are considered.
Studying Turbulence Using Doppler-broadened Lines: Velocity Coordinate Spectrum

We discuss a new technique for studying astrophysical turbulence that utilizes the statistics of Doppler-broadened spectral lines. The technique relates the power velocity coordinate spectrum (VCS), i.e., the spectrum of fluctuations measured along the velocity axis in position-position-velocity data cubes available from observations, to the underlying power spectra of the velocity/density fluctuations. Unlike the standard spatial spectra, which are a function of angular wavenumber, the VCS is a function of the velocity wavenumber kv ~ 1/v. We show that absorption affects the VCS to a higher degree for small kv and obtain the criteria for disregarding the absorption effects for turbulence studies at large kv. We consider the retrieval of turbulence spectra from observations for high and low spatial resolution observations and find that the VCS allows one to study turbulence even when the emitting turbulent volume is not spatially resolved. This opens interesting prospects for using the technique for extragalactic research. We show that, while thermal broadening interferes with the turbulence studies using the VCS, it is possible to separate thermal and nonthermal contributions. This allows a new way of determining the temperature of the interstellar gas using emission and absorption spectral lines.