Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud Work Bench -- Infrastructure-as-Code Based Cloud Benchmarking

In order to optimally deploy their applications, users of Infrastructure-as-a-Service clouds are required to evaluate the costs and performance of different combinations of cloud configurations to find out which combination provides the best service level for their specific application. Unfortunately, benchmarking cloud services is cumbersome and error-prone. In this paper, we propose an architecture and concrete implementation of a cloud benchmarking Web service, which fosters the definition of reusable and representative benchmarks. In distinction to existing work, our system is based on the notion of Infrastructure-as-Code, which is a state of the art concept to define IT infrastructure in a reproducible, well-defined, and testable way.
Simultaneous Localization and Mapping Using Invariant Natural Features

This paper presents a practical approach to solve mobile robot simultaneous localization and mapping (SLAM) problem using natural visual landmarks obtained from a monocular vision. The Rao-Blackwellised particle filter (RBPF) is used to extend the path posterior by sampling new poses that integrate the current observation. The landmark position estimation and update is implemented through extended Kalman filter (EKF). Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem. Single CCD camera tracks the 3D natural landmarks, which are structured with matching image features extracted through Scale Invariant Feature Transform (SIFT). The matching for highly distinctive SIFT features described with multi-dimension vector descriptor is implemented with a KD-Tree in the time cost of O(log2N). And the matches with large error are eliminated by epipolar line constraint approach. The dense metric maps of natural 3D point landmarks for indoor environments is constructed. Experiments on the robot Pioneer3 in our real indoor environment indicate superior performance.
Road extraction from high-resolution remotely sensed panchromatic image in different research scales

As a main factor of evaluating city development speed, road is one of the fast information updating element during city development. Road information extraction based on high-resolution remotely sensed images has very important significance because road affects city land use-cover change. Based on the synthetically analyzing all kinds of read extraction method from high-resolution remotely sensed images, this paper presents the road extraction method that firstly extracts parcel-units from the experimental image based on different scales, and then analyzes the parcel-units assisted by transcendental knowledge. This method can extract road information exactly by object-oriented method, and can acquire different-scale roads according to the user's requirement. At last this paper gives the road information extraction result analysis of the experiment sample.
Node of Ranvier disruption as a cause of neurological diseases

Dysfunction and/or disruption of nodes of Ranvier are now recognized as key contributors to the pathophysiology of various neurological diseases. One reason is that the excitable nodal axolemma contains a high density of Nav (voltage-gated Na+ channels) that are required for the rapid and efficient saltatory conduction of action potentials. Nodal physiology is disturbed by altered function, localization, and expression of voltage-gated ion channels clustered at nodes and juxtaparanodes, and by disrupted axon–glial interactions at paranodes. This paper reviews recent discoveries in molecular/cellular neuroscience, genetics, immunology, and neurology that highlight the critical roles of nodes of Ranvier in health and disease.
Prediction of Pollutant Emissions of Biomass Flames Through Digital Imaging, Contourlet Transform, and Support Vector Regression Modeling

This paper presents a method for the prediction of NOx emissions in a biomass combustion process through the combination of flame radical imaging, contourlet transform and Zernike moment (CTZM), and least squares support vector regression (LS-SVR) modeling. A novel feature extraction technique based on the CTZM algorithm is developed. The contourlet transform provides the multiscale decomposition for flame radical images and the selected operator based on Zernike moments is designed to provide the well-defined structure for the images. The resulted image features are a variable structure, which is originated from the CTZM. Finally, the variable features of the images of four flame radicals (OH*, CN*, CH*, and C*2) are defined. The relationship between the variable features of radical images and NOx emissions is established through radial basis function network modeling, SVR modeling, and the LS-SVR modeling. A comparison between the three modeling approaches shows that the LS-SVR model outperforms the other two methods in terms of root-mean-square error and mean relative error criteria. In addition, the structure of the image features has a significant impact on the performance of the prediction models. The test results obtained on a biomass-gas fired test rig show the effectiveness of the proposed technical approach for the prediction of NOx emissions.
Trend cluster based compression of geographically distributed data streams

In many real-time applications, such as wireless sensor network monitoring, traffic control or health monitoring systems, it is required to analyze continuous and unbounded geographically distributed streams of data (e.g. temperature or humidity measurements transmitted by sensors of weather stations). Storing and querying geo-referenced stream data poses specific challenges both in time (real-time processing) and in space (limited storage capacity). Summarization algorithms can be used to reduce the amount of data to be permanently stored into a data warehouse without losing information for further subsequent analysis. In this paper we present a framework in which data streams are seen as time-varying realizations of stochastic processes. Signal compression techniques, based on transformed domains, are applied and compared with a geometrical segmentation in terms of compression efficiency and accuracy in the subsequent reconstruction.
Glycosaminoglycan contribution to the structure-mechanical properties of the posterior sclera

The sclera is the white outer shell and main load-bearing tissue of the eye. It resists the intraocular pressure, therefore maintaining the shape of the eye, and protects the more fragile intraocular structures, such as the retina, from external forces. Alterations to the scleral mechanical properties can lead to the initiation and development of ocular pathologies such as myopia, often characterized by an axial elongation of the globe, or glaucoma, where the transmission of the visual information to the brain is impaired by a detrimental mechanical environment at the optic nerve head, at the back of the eye. While studies reported alterations in the mechanical properties of the posterior sclera of glaucomatous and myopic eyes, others measured alterations in the tissue microstructure, including the glycosaminoglycan (GAG) content. The contribution of collagen and elastin to the mechanical behavior of connective tissues is well known and consistent among tissues. However, the mechanical role of GAGs is tissue-dependent and has never been studied in the sclera. Therefore, this work aims to investigate the contributions of GAGs to the structure and mechanical properties of the posterior sclera, as well as their possible mechanical role in glaucoma ii
Adaptive Shared Control of a Brain-Actuated Simulated Wheelchair

The use of shared control techniques has a profound impact on the performance of a robotic assistant controlled by human brain signals. However, this shared control usually provides assistance to the user in a constant and identical manner each time. Creating an adaptive level of assistance, thereby complementing the user's capabilities at any moment, would be more appropriate. The better the user can do by himself, the less assistance he receives from the shared control system; and vice versa. In order to do this, we need to be able to detect when and in what way the user needs assistance. An appropriate assisting behaviour would then be activated for the time the user requires help, thereby adapting the level of assistance to the specific situation. This paper presents such a system, helping a brain-computer interface (BCI) subject perform goal-directed navigation of a simulated wheelchair in an adaptive manner. Whenever the subject has more difficulties in driving the wheelchair, more assistance will be given. Experimental results of two subjects show that this adaptive shared control increases the task performance. Also, it shows that a subject with a lower BCI performance has more need for extra assistance in difficult situations, such as manoeuvring in a narrow corridor.
From Weber to Kafka: Political Activism and the Emergence of an Inefficient Bureaucracy

A well functioning bureaucracy can promote prosperity, as advocated by Max Weber. But when bureaucracy gets jammed, it causes stagnation, as described by Franz Kafka. We propose a dynamic theory of the interaction between the production of laws and the efficiency of bureaucracy. When bureaucracy is inefficient the effects of politicians legislative acts are hard to assess. Therefore, incompetent politicians have strong incentives to pass laws to acquire the reputation of skill-full reformers. But too many, often contradictory reforms can in turn lead to a collapse in bureaucratic fficiency. This interaction leads to the existence of both Weberian and Kafkian steady states. A temporary surge in political instability, a strong pressure for reforms by the public, and the appointment of short-lived technocratic governments can determine a permanent shift towards the Kafkian nightmare steady state. Using micro-data for Italy, we provide evidence consistent with one key prediction of the theory: the relative supply of laws by incompetent politicians increases when legislatures are expected to be short.
DNA enzymes as potential therapeutics: towards clinical application of 10-23 DNAzymes

Introduction: Ongoing studies on the inhibition of gene expression at the mRNA level have identified several types of specific inhibitors such as antisense oligonucleotides, small interfering RNA, ribozymes and DNAzymes (Dz). After its discovery in 1997, the 10-23 Dz (which can cleave RNA efficiently and site-specifically, has flexible design, is independent from cell mechanisms, does not require expensive chemical modifications for effective use in vivo) has been employed to downregulate a range of therapeutically important genes. Recently, 10-23 Dzs have taken their first steps into clinical trials. Areas covered: This review focuses predominantly on Dz applications as potential antiviral, antibacterial, anti-cancer and anti-inflammatory agents as well as for the treatment of cardiovascular disease and diseases of CNS, summarizing results of their clinical trials up to the present day. Expert opinion: In comparison with antisense oligonucleotides and small interfering RNAs, Dzs do not usually show off-target effects due to their high specificity and lack of immunogenicity in vivo. As more results of clinical trials carried out so far are gradually becoming available, Dzs may turn out to be safe and well-tolerated therapeutics in humans. Therefore, there is a good chance that we may witness a deoxyribozyme drug reaching the clinic in the near future.
Phrenology between anthropology and neurology in a nineteenth-century collection of skulls

The University of Padua has many legends about its cultural heritage. One of these concerns a collection of eight skulls still preserved in the Hall of Medicine at Bo Palace, near the old anatomy theatre built in 1545. It is said that some famous professors of the University donated their bodies to medical science, and the skulls were from these bodies. From multidisciplinary research, both historical and anthropological, we have discovered that Francesco Cortese, Professor of Medicine and Rector of the University, started this personal collection of colleagues’ skulls, although they had not donated their bodies to science, so that he could make his own detailed phrenology study.
Estimating evolutionary parameters when viability selection is operating

Some individuals die before a trait is measured or expressed (the invisible fraction), and some relevant traits are not measured in any individual (missing traits). This paper discusses how these concepts can be cast in terms of missing data problems from statistics. Using missing data theory, I show formally the conditions under which a valid evolutionary inference is possible when the invisible fraction and/or missing traits are ignored. These conditions are restrictive and unlikely to be met in even the most comprehensive long-term studies. When these conditions are not met, many selection and quantitative genetic parameters cannot be estimated accurately unless the missing data process is explicitly modelled. Surprisingly, this does not seem to have been attempted in evolutionary biology. In the case of the invisible fraction, viability selection and the missing data process are often intimately linked. In such cases, models used in survival analysis can be extended to provide a flexible and justified model of the missing data mechanism. Although missing traits pose a more difficult problem, important biological parameters can still be estimated without bias when appropriate techniques are used. This is in contrast to current methods which have large biases and poor precision. Generally, the quantitative genetic approach is shown to be superior to phenotypic studies of selection when invisible fractions or missing traits exist because part of the missing information can be recovered from relatives.
Regulation of the VHL/HIF-1 Pathway by DJ-1

DJ-1 (PARK7) is a gene linked to autosomal recessive Parkinson disease (PD). We showed previously that DJ-1 loss sensitizes neurons in models of PD and stroke. However, the biochemical mechanisms underlying this protective role are not completely clear. Here, we identify Von Hippel Lindau (VHL) protein as a critical DJ-1-interacting protein. We provide evidence that DJ-1 negatively regulates VHL ubiquitination activity of the α-subunit of hypoxia-inducible factor-1 (HIF-1α) by inhibiting HIF–VHL interaction. Consistent with this observation, DJ-1 deficiency leads to lowered HIF-1α levels in models of both hypoxia and oxidative stress, two stresses known to stabilize HIF-1α. We also demonstrate that HIF-1α accumulation rescues DJ-1-deficient neurons against 1-methyl-4-phenylpyridinium-induced toxicity. Interestingly, lymphoblast cells extracted from DJ-1-related PD patients show impaired HIF-1α stabilization when compared with normal individuals, indicating that the DJ-1–VHL link may also be relevant to a human context. Together, our findings delineate a model by which DJ-1 mediates neuronal survival by regulation of the VHL–HIF-1α pathway.
Psycho-emotional disorders in women after spontaneous abortion

Objective: To determine the frequency of women with spontaneous abortions that present psycho-emotional disorders. Design: Cross-sectional study using a face-to-face questionnaire. Setting: Postpartum area at a tertiary care referral hospital in Leon, Mexico. Participants: 210 postpartum women, divided into 105 women with spontaneous abortion, and 105 with eutocic deliveries (controls). Data collection: Women answered face-to-face the questionnaire Minnesota Multiphase Personality Inventory-2 (MMPI-2), applied one day after the abortion. Findings: the frequency of psycho-emotional disorders in women who presented abortion was (12.7%), which was higher compared with the controls (9.04%), P = 0.002, being significant the hysteria (6.6%), P = 0.021. Key conclusions: There is a higher frequency of psycho-emotional disorders in women who present an abortion, represented for hysteria. Implications for practice: It is recommended to supply psychological support to women who suffer a spontaneous abortion.
A Search for Trypanosoma brucei rhodesiense Diagnostic Antigens by Proteomic Screening and Targeted Cloning

Background The only available diagnostic method for East African trypanosomiasis is light microscopy of blood samples. A simple immunodiagnostic would greatly aid trypanosomiasis control. Methodology and Principal Findings To find trypanosome proteins that are specifically recognised by sera from human sleeping sickness patients, we have screened the Trypanosoma brucei brucei proteome by Western blotting. Using cytosolic, cytoskeletal and glycosomal fractions, we found that the vast majority of abundant trypanosome proteins is not specifically recognised by patient sera. We identified phosphoglycerate kinase (PGKC), heat shock protein (HSP70), and histones H2B and H3 as possible candidate diagnostic antigens. These proteins, plus paraflagellar rod protein 1, rhodesain (a cysteine protease), and an extracellular fragment of the Trypanosoma brucei nucleoside transporter TbNT10, were expressed in E. coli and tested for reactivity with patient and control sera. Only TbHSP70 was preferentially recognized by patient sera, but the sensitivity and specificity were insufficient for use of TbHSP70 alone as a diagnostic. Immunoprecipitation using a native protein extract revealed no specifically reacting proteins. Conclusions No abundant T. brucei soluble, glycosomal or cytoskeletal protein is likely to be useful in diagnosis. To find useful diagnostic antigens it will therefore be necessary to use more sophisticated proteomic methods, or to test a very large panel of candidate proteins.
Using Problem Solving Times and Expert Opinion to Detect Skills

Construction of a mapping between educational content and skills is an important part of development of adaptive ed- ucational systems. This task is difficult, requires a domain expert, and any mistakes in the mapping may hinder the po- tential of an educational system. In this work we study tech- niques for improving a problem-skill mapping constructed by a domain expert using student data, particularly prob- lem solving times. We describe and compare different tech- niques for the task – a multidimensional model of problem solving times and supervised classification techniques. In the evaluation we focus on surveying situations where the combination of expert opinion with student data is most useful.
Reinforcement learning in robotics: A survey

Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors. Conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in reinforcement learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this article, we attempt to strengthen the links between the two research communities by providing a survey of work in reinforcement learning for behavior generation in robots. We highlight both key challenges in robot reinforcement learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our paper lies on the choice between model-based and model-free as well as between value-function-based and policy-search methods. By analyzing a simple problem in some detail we demonstrate how reinforcement learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.
Detection of Sentinel Lymph Nodes in Gynecologic Tumours by Planar Scintigraphy and SPECT/CT

Objective: Assess the role of planar lymphoscintigraphy and fusion imaging of SPECT/CT in sentinel lymph node (SLN) detection in patients with gynecologic tumours. Material and Methods: Planar scintigraphy and hybrid modality SPECT/CT were performed in 64 consecutive women with gynecologic tumours (mean age 53.6 with range 30-77 years): 36 pts with cervical cancer (Group A), 21 pts with endometrial cancer (Group B), 7 pts with vulvar carcinoma (Group C). Planar and SPECT/CT images were interpreted separately by two nuclear medicine physicians. Efficacy of these two techniques to image SLN were compared. Results: Planar scintigraphy did not image SLN in 7 patients (10.9%), SPECT/CT was negative in 4 patients (6.3%). In 35 (54.7%) patients the number of SLNs captured on SPECT/CT was higher than on planar imaging. Differences in detection of SLN between planar and SPECT/CT imaging in the group of all 64 patients are statistically significant (p<0.05). Three foci of uptake (1.7% from totally visible 177 foci on planar images) in 2 patients interpreted on planar images as hot LNs were found to be false positive non-nodal sites of uptake when further assessed on SPECT/CT. SPECT/CT showed the exact anatomical location of all visualised sentinel nodes. Conclusion: In some patients with gynecologic cancers SPECT/CT improves detection of sentinel lymph nodes. It can image nodes not visible on planar scintigrams, exclude false positive uptake and exactly localise pelvic and paraaortal SLNs. It improves anatomic localization of SLNs. Conflict of interest:None declared.
A new selection procedure for the optimal vehicle mass detection method depending on environmental parameters

The global sales volume of automobiles increased in the last years and electric vehicles and autonomous vehicles are main topics of the automobile industry. Many well-known automobile manufactures have already developed their own electric vehicles. Furthermore, the development of self-driving cars is content of many research projects and the first autonomous vehicles are already driving on the roads worldwide. These changes in the automobile sector lead to new challenges, especially the compliance of safety requirements. Therefore, the industry developed different driver assistance systems for the realization of an adaptive cruise control or trajectory planning. The goals of those systems are the enhancement of safety and comfort. The systems need many input parameters, like the distance to other cars or the current velocity. One important parameter is the current vehicle mass. Based on this, some existing systems and methods as well as different application examples are presented in this paper to clarify their necessity. The focus of this paper is on the presentation of a new selection procedure for the optimal vehicle mass detection method depending on environmental parameters and the advantages of this system in comparison to previous systems.
In Silico Mutational Analysis and Drug Interaction Studies of HIV Reverse Transcriptase

Human immunodeficiency virus is a retrovirus that causes acquired immunodeficiency syndrome, a condition in humans in which the immune system begins to fail, leading to life threatening opportunistic infections. Reverse transcriptase inhibitors are class of antiretroviral drugs used to treat HIV infection. RTIs inhibit activity of reverse transcriptase, a viral DNA polymerase enzyme that HIV needs to replace. Protein P04585|POL_HV1H2 Gag-Pol polyprotein - Human immunodeficiency virus type 1 (isolate HXB2 group M subtype B) (HIV-1) was docked with RTIs and thebfree energies of the docking complexes were analyzed. It was concluded that M184V mutations has least impact than that of other mutations and Y115F mutation has great impact on the drug interaction with Abcavir. This has to be correlated with the real effect on the patients. This serves a best model for evaluating the impact of mutations in changing the folding of protein and further its effect on the inhibition. This is shown by superimposing the wild type structures and mutant structures.