Miracle-dz/UniFAR-FTUs huggingface dataset:
The spoken web search task at MediaEval 2012

In this paper, we describe the “Spoken Web Search” Task, which was held as part of the 2012 MediaEval benchmark evaluation campaign. The purpose of this task was to perform audio search with audio input in four languages, with very few resources being available. Continuing in the spirit of the 2011 SpokenWeb Search Task, which used speech from four Indian languages, the 2012 data was taken from the LWAZI corpus, to provide even more diversity and allow for a task that will allow both zero resource “pattern matching” approaches and “speech recognition” based approaches to participate. In this paper, we summarize the results from several independent systems, developed by nine teams, analyze their performance, and provide directions for future research.
STUDY OF VARIOUS FACTORS AFFECTING PERFORMANCE OF MULTI-CORE PROCESSORS

Advances in Integrated Circuit processing allow for more microprocessor design options. As Chip Multiprocessor system (CMP) become the predominant topology for leading microprocessors, critical components of the system are now integrated on a single chip. This enables sharing of computation resources that was not previously possible. In addition the virtualization of these computation resources exposes the system to a mix of diverse and competing workloads. On chip Cache memory is a resource of primary concern as it can be dominant in controlling overall throughput. This Paper presents analysis of various parameters affecting the performance of Multi-core Architectures like varying the number of cores, changes L2 cache size, further we have varied directory size from 64 to 2048 entries on a 4 node, 8 node 16 node and 64 node Chip multiprocessor which in turn presents an open area of research on multicore processors with private/shared last level cache as the future trend seems to be towards tiled architecture executing multiple parallel applications with optimized silicon area utilization and excellent performance.
Prognostic and clinicopathological significance of S100A14 expression in cancer patients

Abstract Background: The prognostic significance of S100A14 for survival of cancer patients remains controversial. Therefore, we conducted this meta-analysis to explore the association between S100A14 expression and cancer prognosis. Method: Eligible studies were identified by searching the online databases Pubmed and EMBASE up to August 2018. Odds ratios (ORs) with 95% confidence intervals (CIs) severed as the summarized statistics for clinicopathological assessments and hazard ratios (HRs) with 95% CIs were calculated to clarify the correlation between S100A14 expression and prognosis of different cancers. Results: A total of 11 studies with 1651 cancer patients were enrolled. The results indicated that S100A14 expression was not significantly associated with overall survival (OS) in total various cancers (HR = 1.54, 95% CI:0.89–2.67, P = .121). Further subgroup analysis stratified by tumor type showed that elevated S100A14 expression was associated with poor OS in breast cancer (HR = 3.66, 95% CI: 1.75–7.62, P < .001) and in ovarian cancer patients (HR = 3.78, 95%CI: 1.63–8.73, P = .002). Interestingly, high S100A14 expression was correlated with poor tumor differentiation (OR = 2.51, 95% CI: 1.52–4.13, P < .001). However, there were no significant correlations between S100A14 expression and other clinicopathologic characteristics. Begg funnel plot and Egger test showed that no publication bias was detected. Conclusions: Our meta-analysis suggests that S100A14 overexpression might be a predictive biomarker for poor prognosis in patients with breast cancer and ovarian cancer. Large-scale studies are required to confirm these results.
Assessment of patients’ psychological state and self-efficacy associated with postoperative constipation after thoracolumbar fracture surgery

Objective We aimed to explore the relationship among the duration of constipation at 30 days after thoracolumbar fracture surgery, self-efficacy, and anxiety or depression in patients with constipation after thoracolumbar fracture surgery. Methods In this descriptive correlational study, 108 patients with thoracolumbar fracture undergoing pedicle screw fixation surgery were recruited from January 2015 to May 2017 in our hospital. From the day of surgery, we conducted a 1-month follow-up investigation. We evaluated the pattern of defecation, stool consistency, and incidence of defecation-related problems using a structured interview. Clinical data were obtained using a patient intake form, and we applied the Health Behavior Self-Efficacy Scale (HBSES), and Hospital Anxiety and Depression Scale (HADS). Results Approximately 83.3% of patients experienced postoperative constipation, and most exhibited normal defecation by postoperative day 13. Self-efficacy and anxiety and depression were graded at a medium level in most patients. The average HBSES score was 74.39 ± 11.08, and the mean HADS score was 7.97 ± 4.08. The duration of postoperative constipation was negatively correlated with self-efficacy and positively associated with anxiety or depression. Conclusions Self-efficacy, anxiety, and depression are important sociopsychological factors associated with the duration of postoperative constipation.
Randomized Placebo‐/Sham‐Controlled Trials of Spinal Cord Stimulation: A Systematic Review and Methodological Appraisal

The recent availability of paraesthesia/sensation free spinal cord stimulation (SCS) modalities allow the design of clinical trials of SCS using placebo/sham controls and blinding of patients, clinicians, and researchers. The aims of this study were to: 1) systematically review the current evidence base of randomized controlled trials (RCTs) of SCS placebo/sham trials and 2) to undertake a methodological critique of their methods. Based on this critique, we developed a checklist for the design and reporting of future RCTs of SCS.
Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

The pace of on‐going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid‐DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process‐based models, are able to involve an intermediate number of well‐chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid‐DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid‐DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.
The role of miR156 in rejuvenation in Arabidopsis thaliana.

The plant life cycle can be divided into three major phases (juvenile, adult, and reproductive) after seed germination, based on morphological and physiological differences. In contrast to juvenile plants, adult plants are capable of transitioning to the reproductive phase by responding to diverse floral induction signals (Bäurle and Dean 2006). Juvenile plants also differ from adult plants in terms of leaf morphology and regenerative capacity (Yu et al. 2015). This article is protected by copyright. All rights reserved.
PASSENGER COUNTING TECHNOLOGIES AND PROCEDURES

This synthesis will be of interest to transit agency general managers, their planning and scheduling, operations and maintenance, computer services, and budget and finance staffs, as well as to technology providers. It summarizes information from selected transit agencies about benefits and problems associated with each passenger counting technology, as reported by current users. It also presents advice for agencies considering each technology. Issues considered deal with data collection methodology, data processing, end uses of ridership data, organizational responsibilities, and resource requirements.
A taxonomic revision of the genus Arcynopteryx Klapalek, 1904 Plecoptera, Perlodidae

Four known Arcynopteryx species are redescribed from the types and newly acquired material. Illustrations of the male andfemale genitalia, head and pronotal patterns and eggs are used to support species descriptions. Dictyopteryx compacta (McLachlan, 1872) is transferred to Skwala Ricker, 1943 with the valid name Skwala compacta (McLachlan, 1872) comb. nov., and S. pusilla (Klapalek, 1912) is placed as a junior synonym of that species. For genus Arcynopteryx type species is fixed(under Article 70.3 of the Code) as Arcynopteryx dichroa (McLachlan, 1872), misidentified as Arcynopteryx compacta (McLachlan, 1872) in the original designation by Klapalek (1912).
Viral Vectors for Gene Therapy of Genetic Diseases: Challenges and Prospects

Viruses naturally possess specialized molecular mechanisms to efficiently transfer their genetic materials into the infected cells. Viral vectors can be used to modify specific cell type or tissue and can be directed to express therapeutic genes. These unique abilities made them desirable for engineering viral vectors to deliver the therapeutic genes. The efficient delivery of therapeutic genes and correct gene expression are important for clinically relevant gene therapy. The most commonly used viral vectors are derived from retroviruses, adenoviruses, and adeno associated viruses (AAV). Gene therapy has a turbulent history because of failure of the first clinical trial. Jesse Gelsinger [1] who was suffering from a partial deficiency of ornithine trans carbamyalse (OTC), took part in a gene therapy clinical trial at the University of Pennsylvania, Philadelphia. Due to immune responses caused by a high dose of adenoviral vector containing OTC, Gelsinger died four days later because of multi-organ failure [1]. In another clinical trial conducted in France and UK, among twenty X-linked severe combined immunodeficiency disease (X-SCID) patients, 19 were successfully cured their immunodeficiency by retroviral vector containing IL-2RG (γc). Four of the treated patients developed T cell leukemia because the gamma retrovirus integrated in/near the proto-oncogenes that turned the gene on. But the patients were successfully treated with chemotherapy and in complete remission [2].
Controlling your connected car

The topic of this thesis is enforcing privacy on telematics data that is being transmitted from the cars to third parties. Telematics data is information about the state of the car which is being sent towards a third party. Privacy has become an issue for car drivers the last couple of years. Related research has only shown the issue, but never proposed a solution to the problem. In this thesis, we have researched how a higher level of privacy (compared to the current level) can be enforced using cryptographic techniques. Typically, very little actions have been taken to protect the privacy of the user. Based on the security and privacy issues in the context of Connected Cars, we identified technical requirements from which we constructed a cryptographic solution. We have given an overview of the possible architectures to communicate between the car and a third party which resulted in a list of advantages and disadvantages per type of communication. By using cryptographic techniques, such as homomorphic cryptography, we were able to eliminate a lot of disadvantages. The Semi-Trusted Third Party architecture is chosen as the best option in the context of our thesis. Based on that architecture, we have provided sequence diagrams for the relevant scenarios, which should give the reader a clear understanding of the information flow. This includes the steps involved in storing the data, requesting delegated keys and aggregating data for a third party. This all contributed to defining technical requirements for a cryptographic solution. We proposed a modification of two existing cryptographic systems that enables the aggregation of multiple individual messages. To accomplish this, these cryptographic systems use homomorphic cryptography without revealing individual messages. However, important is that the proposed solution should not limit the functionality. For instance, it should still be able for the car owner to view his individual messages. This would, for instance, allow the car owner to view the current location of the car in case it gets stolen. In this thesis, we have analyzed to what extent the security and privacy requirements are being satisfied by the proposed cryptographic solutions. Although we have only tested our proposed solution on a modern CPU, we have compared the CPU with the microcontrollers in the car by using a general benchmark performance called Dhrystone. In order to do so, we have made a proof-of-concept implementation and researched the execution time for key generation, encryption and decryption. Furthermore, we have analyzed the theoretical complexity of both proposed cryptographic solutions and based on that made an estimation on how well the cryptographic solutions would perform on a car. The outcome of this thesis is a cryptographic solution that increases the privacy of the user, while it does not limit the functionality required by the user or the involved third party. Moreover, we show that the proposed cryptographic system has an acceptable performance for an application in Connected Cars. Controlling your Connected Car v
Chemosensory basis of feeding and oviposition behaviour in herbivorous insects: a glance at the periphery

Recent advances in our understanding of the relationship between chemosensory and behavioural responses to phytochemicals come from a number of studies on ovipositional and food selection behaviour of flies, butterflies, moths and beetles. Establishing input‐output relationships has provided insight into the way in which the activity of chemoreceptors is translated into host‐plant selection behaviour. This was achieved for both the qualitative contrast acceptance/rejection and for quantifiable preference hierarchies. By now it is clear that the subtlety of coding the complex phytochemical profiles offered by potential host plants relies on across‐fibre patterns or ensemble‐firing of taste neurons. Progress along these lines depends on unravelling processing pathways in the central nervous system, still a largely unexplored area in herbivorous insects. Increased interest can be noted for the mechanisms operating during the most peripheral events of chemoreception: the interaction of phytochemical and chemoreceptor, determining the specificity of recognition. Evidence for ‘peripheral integration’ has accumulated. Deterrent receptors have an especially puzzling nature. Although such cells respond to a wide array of structurally diverse secondary plant metabolites, their sensitivity profile differs between closely related species. To what extent membrane‐bound receptor molecules are involved and what degree of specificity is conferred by these, is largely unknown. Sensitivity to a certain group or class of compounds is determined by single genes in several cases. This allows for a scenario in which single gene mutations affect stimulus‐receptor interactions, which might concurrently affect host‐plant selection behaviour.
Operating system management of shared caches on multicore processors

Our thesis is that operating systems should manage the on-chip shared caches of multicore processors for the purposes of achieving performance gains. Consequently, this dissertation demonstrates how the operating system can profitably manage these shared caches. Two shared-cache management principles are investigated: (1) promoting shared use of the shared cache, demonstrated by an automated online thread clustering technique, and (2) providing cache space isolation, demonstrated by a software-based cache partitioning technique. In support of providing isolation, cache provisioning is also investigated, demonstrated by an automated online technique called RapidMRC. We show how these software-based techniques are feasible on existing multicore systems with the help of their hardware performance monitoring units and their associated hardware performance counters. On a 2-chip IBM POWER5 multicore system, promoting sharing reduced processor pipeline stalls caused by cross-chip cache accesses by up to 70%, resulting in performance improvements of up to 7%. On a larger 8-chip IBM POWER5+ multicore system, the potential for up to 14% performance improvement was measured. Providing isolation improved performance by up to 50%, using an exhaustive offline search method to determine optimal partition size. On the other hand, up to 27% performance improvement was extracted from the corresponding workload using an automated online approximation technique, made possible by RapidMRC.
Case-Specific Random Forests

Random forest (RF) methodology is a nonparametric methodology for prediction problems. A standard way to use RFs includes generating a global RF to predict all test cases of interest. In this article, we propose growing different RFs specific to different test cases, namely case-specific random forests (CSRFs). In contrast to the bagging procedure in the building of standard RFs, the CSRF algorithm takes weighted bootstrap resamples to create individual trees, where we assign large weights to the training cases in close proximity to the test case of interest a priori. Tuning methods are discussed to avoid overfitting issues. Both simulation and real data examples show that the weighted bootstrap resampling used in CSRF construction can improve predictions for specific cases. We also propose a new case-specific variable importance (CSVI) measure as a way to compare the relative predictor variable importance for predicting a particular case. It is possible that the idea of building a predictor case-specifically can be generalized in other areas.
EVOLUTION OF GENERALISTS AND SPECIALISTS IN SPATIALLY HETEROGENEOUS ENVIRONMENTS

Quantitative genetic models are used to investigate the evolution of generalists and specialists in a coarse‐grained environment with two habitat types when there are costs attached to being a generalist. The outcomes for soft and hard selection models are qualitatively different. Under soft selection (e.g., for juvenile or male‐reproductive traits) the population evolves towards the single peak in the adaptive landscape. At equilibrium, the population mean phenotype is a compromise between the reaction that would be optimal in both habitats and the reaction with the lowest cost. Furthermore, the equilibrium is closer to the optimal phenotype in the most frequent habitat, or the habitat in which selection on the focal trait is stronger. A specialist genotype always has a lower fitness than a generalist, even when the costs are high.
Enhanced wavelength-dependent surface tension of liquid-vapour interfaces

Due to the simultaneous presence of bulk-like and interfacial fluctuations the understanding of the structure of liquid-vapour interfaces poses a long-lasting and ongoing challenge for experiments, theory, and simulations. We provide a new analysis of this topic by combining high-quality simulation data for Lennard-Jones fluids with an unambiguous definition of the wave-number–dependent surface tension based on the two-point correlation function of the fluid. Upon raising the temperature, develops a maximum at short wavelengths. We compare these results with predictions from density functional theory. Our analysis has repercussions for the interpretation of grazing-incidence small-angle X-ray scattering (GISAXS) at liquid interfaces.
Quasistatic computing environments

Modern compiler optimizations can be roughly characterized as Static or Dynamic. Static optimizations are often limited by a lack of knowledge of run-time program behavior. Dynamic optimizations seek to circumvent this problem by delaying instruction bindings until run-time values are known. Much of the analysis for dynamic optimizations must be performed statically as any run-time analysis is in the critical path of the program and reduces the benefit of the optimized code. A model of Quasistatic computation addresses this difficulty by including compilation as an integral part of a program's lifetime. Run-time feedback from previous program executions are used during compile-time analysis to produce speculative optimizations based on expected run-time values. Additionally, expensive off-line analysis can be performed without impacting run-time performance. Quasistatic applications may continually adapt to changing data sets and environments. This thesis introduce a systems framework for enabling quasistatic computation and explores implications of quasistatic computing environments. Thesis Supervisor: Thomas F. Knight Title: Senior Research Scientist
Functional Context Network of T2DM

Type-2 diabetes mellitus (T2DM) is a complex disease with multiple causes covering several functional entities of the metabolism. Environmental factors contribute to the pathogenesis of the disease – most notably nutrition and weight of the organism. The identification of disease genes is the driving power of many research projects. In a previous paper (Rasche et al. 2008) we presented a method that integrates results from different T2DM related studies and identifies candidate genes with high disease relevance. This chapter is designated to elaborate on our work from a network based perspective. Network biology is a promising field that can shed light on interrelations between disease genes and from disease genes to their functional neighborhood. We use network-based tools to advance from a single-gene analysis towards a subnet, a functional module, of disease genes. Proteins are gene products that are associated with particular molecular functions. Molecular functions are interpreted as activities that can be performed by individual proteins following the definitions introduced by the Gene Ontology Consortium (Ashburner et al. 2000). Examples of molecular functions are catalytic activity, transporter activity or binding. Additionally, a biological process is accomplished by one or more ordered assemblies of molecular functions (Ashburner et al. 2000). Proteins physically interact with each other in order to carry out a biological function. A biological function is related to the term biological process. A signal transduction cascade whose biological function is to transmit information from a receptor to a transcription factor is a succession of protein-protein interactions (PPIs). Both the molecular function of a protein and the biological function in which it is involved are best deduced by studying the environment where it operates in. To this end, scientists pursue the ambitious goal of assembling all PPIs in an organism – the interactome – to elucidate how proteins work together and promote individual biological processes and eventually the complete cellular machinery. Today, mainly two methods are used to detect PPIs: Yeast two-hybrid screens (Fields & Sternglanz 1994) and affinity purification (Pandey & Mann 2000). These large-scale technologies provide vast numbers of interactions but have high false positive rates. Additionally, such experiments only reflect one environmental condition and not the dynamics of interactions between different phyiological states leading to high false negative rates. Regarding the current size of the human interactome, we have only a draft of the complete set of interactions. However, looking at the course of construction (fig. 1) so far and bearing in mind new quality standards we are continuously moving towards the completion of a