Miracle-dz/UniFAR-FTUs huggingface dataset:
Secondary Metabolites from Penicillium roqueforti, A Starter for the Production of Gorgonzola Cheese

The presence of mold in food, although necessary for production, can involve the presence of secondary metabolites, which are sometimes toxic. Penicillium roqueforti is a common saprophytic fungus but it is also the essential fungus used in the production of Roquefort cheese and other varieties of blue cheese containing internal mold. The study was conducted on industrial batches of Penicillium roqueforti starters used in the production of the Gorgonzola cheese, with the aim to verify the production of secondary metabolites. Nine Penicillium roqueforti strains were tested. The presence of roquefortine C, PR toxin and mycophenolic acid was tested first in vitro, then on bread-like substrate and lastly in vivo in nine cheese samples produced with the same starters and ready to market. In vitro, only Penicillium out of nine produced roquefortine C, four starters showed mycophenolic acid production, while no significant amounts of PR toxin were detected. In the samples grown on bread-like substrate, Penicillium did not produce secondary metabolites, likewise with each cheese samples tested. To protect consumers’ health and safety, the presence of mycotoxins needs to be verified in food which is widely consumed, above all for products protected by the protected denomination of origin (DOP) label (i.e. a certificate guaranteeing the geographic origin of the product), such as Gorgonzola cheese.
Dynamic scenes reconstruction based on foreground and background splitting

In recent years, several approaches have been proposed to reconstruct static scenes. However, there exists rarely method for dynamic scenes. In this paper, we propose an approach to reconstruct dynamic scenes using only a moving depth sensor. The main idea is to reconstruct the moving foreground objects and static background scenes respectively. An iterative closest point (ICP) algorithm is used for obtaining the current camera pose. The foreground and background splitting is achieved by processing failed tracking points. We introduce an efficient filter and morphological operations to handle these points. Finally, foreground and background models are reconstructed separately using the split depth data and the calculated camera pose. Experimental results demonstrate that our method has fast and robust performance in reconstructing complex dynamic scenes.
A tail-sharing WFST composition algorithm for large vocabulary speech recognition

This paper presents an algorithm for approximating minimization in the context of the weighted finite-state transducers approach to large vocabulary speech recognition. The algorithm is designed for the integration of the lexicon with the language model and performs composition, determinization and pushing in one step. Furthermore, it uses tail-sharing in order to approximate minimization. Our results show that it is a good approximation to explicit minimization, with the added advantage that it can be used "on-the-fly" in a dynamic decoder.
Spatially aware tangible display interaction in a tabletop environment

One limiting factor of digital tabletops is that interaction is usually restricted to a single 2D surface. I propose to extend this interaction space to the 3D space above the table by using spatially aware handheld displays. Utilizing the spatial position and orientation of such tangible displays provides an additional dimension of interaction that allows users to interact with complex information spaces in a more direct and natural way. The simultaneous use of multiple tangible displays explicitly supports collaborative work. My research includes the identification of basic interaction principles, the design and implementation of a technical framework, and the development and evaluation of interactive systems demonstrating the benefits of tangible displays for different application domains.
The Temporal Dynamics of Scene Processing: A Multifaceted EEG Investigation

Abstract Our remarkable ability to process complex visual scenes is supported by a network of scene-selective cortical regions. Despite growing knowledge about the scene representation in these regions, much less is known about the temporal dynamics with which these representations emerge. We conducted two experiments aimed at identifying and characterizing the earliest markers of scene-specific processing. In the first experiment, human participants viewed images of scenes, faces, and everyday objects while event-related potentials (ERPs) were recorded. We found that the first ERP component to evince a significantly stronger response to scenes than the other categories was the P2, peaking ∼220 ms after stimulus onset. To establish that the P2 component reflects scene-specific processing, in the second experiment, we recorded ERPs while the participants viewed diverse real-world scenes spanning the following three global scene properties: spatial expanse (open/closed), relative distance (near/far), and naturalness (man-made/natural). We found that P2 amplitude was sensitive to these scene properties at both the categorical level, distinguishing between open and closed natural scenes, as well as at the single-image level, reflecting both computationally derived scene statistics and behavioral ratings of naturalness and spatial expanse. Together, these results establish the P2 as an ERP marker for scene processing, and demonstrate that scene-specific global information is available in the neural response as early as 220 ms.
Algorithms for stochastic optimization with expectation constraints

This paper considers the problem of minimizing an expectation function over a closed convex set, coupled with an expectation constraint on either decision variables or problem parameters. We first present a new stochastic approximation (SA) type algorithm, namely the cooperative SA (CSA), to handle problems with the expectation constraint on devision variables. We show that this algorithm exhibits the optimal ${\cal O}(1/\sqrt{N})$ rate of convergence, in terms of both optimality gap and constraint violation, when the objective and constraint functions are generally convex, where $N$ denotes the number of iterations. Moreover, we show that this rate of convergence can be improved to ${\cal O}(1/N)$ if the objective and constraint functions are strongly convex. We then present a variant of CSA, namely the cooperative stochastic parameter approximation (CSPA) algorithm, to deal with the situation when the expectation constraint is defined over problem parameters and show that it exhibits similar optimal rate of convergence to CSA. It is worth noting that CSA and CSPA are primal methods which do not require the iterations on the dual space and/or the estimation on the size of the dual variables. To the best of our knowledge, this is the first time that such optimal SA methods for solving expectation constrained stochastic optimization are presented in the literature.
The Central Role of the State in the Governance of Sport and the Olympic Movement in Tunisia, from 1956 to the Present Day

Abstract This paper examines the relationship between sport and the Tunisian state, focusing on the issues of governance and regulation. Identified are three periods: from independence to the coup d’état (20 March 1956–7 November 1987), where sport was a component of national identity; Ben Ali’s regime taking control of the Olympic Movement, 1987–2011; and Post-2011, which witnessed attempts to achieve democracy. Descriptions of the situation in each of the three periods are followed by analyses of sports policies (objectives, resources, and results), legislation, turning points, and tensions.
Performance vigilance task and sleepiness in patients with sleep-disordered breathing

Altered vigilance performance has been documented in patients with sleep-related breathing disorders (SRBDs). Sleep fragmentation, sleepiness, respiratory disturbances and nocturnal hypoxaemia have been suggested as the pathogenesis of these deficits, yet it remains difficult to find a good correlation between performance deficits and the above factors. In the present study, which performance measure better characterised SRBD patients and the main factors implicated in these disturbances were examined. The study group consisted of 152 patients and 45 controls, all examined using a performance vigilance task and subjective sleepiness assessment. Speed and accuracy in the psychomotor vigilance task (PVT) were measured in patients and controls. Objective daytime sleepiness was assessed in the patient group using the maintenance of wakefulness test. In comparison with controls, PVT accuracy rather than speed seems to be affected in SRBD patients, with lapses and false responses significantly greater in patients with more severe objective sleepiness and higher apnoea/hypopnoea index. Although slowing and increased variability in reaction time were associated with shorter sleep latency in the maintenance of wakefulness test, subjective sleepiness, sleep fragmentation, nocturnal hypoxaemia and apnoea/hypopnoea index influenced mainly PVT accuracy. It is concluded that vigilance impairment, sleep fragmentation and severity of disease may partially and differentially contribute to the diurnal performance consequences found in sleep-related breathing disorders. Since the psychomotor vigilance task worsening is more marked in accuracy that in speed, measurement of lapses and false responses would better characterise the degree of diurnal impairment in these patients.
ATPG for fault diagnosis on analog electrical networks using evolutionary techniques

This paper proposes a method for automated test pattern generation for fault diagnosis on continuous-time analog electrical networks based on evolutionary techniques. The paper states a method for coding a generic algorithm, based on a given heuristic, that are able to generate a set of optimum frequencies capable of disclosing parametric faults. The method itself is generic, and not based on specific or ad hoc features at all.
Loss of 11p11 is a frequent and early event in sporadic nonfunctioning pancreatic neuroendocrine neoplasms

The pathogenesis of sporadic pancreatic neuroendocrine neoplasms (PNENs) is poorly understood. To gain insight into the genetic mechanisms underlying this tumor entity, we performed genome-wide screening of 16 surgical specimens from 15 patients with sporadic PNEN, combining G-band karyotyping and high resolution comparative genomic hybridization (HR-CGH). G-banding revealed abnormal karyotypes in 2 of 10 tumor samples analyzed. DNA copy number changes were detected in 13 samples, whereas three tumors showed a balanced genome. Gains were more frequent than losses in the nonfunctioning tumors (n=13). Common gains were scored at 5p12–13, 4q13–24, 5p15, 5q11–31, and 9q21–22. Common losses were scored at 11p11, 11p14–15, 11q23, 11p12–13, and 11q22. The average number of copy aberrations (ANCA index) was 12 for 13 nonfunctioning primary tumors, 4.8 for the nonfunctioning tumors with low Ki-67 (≥5%), 21.2 for the tumors with high Ki-67 (<5%), 2.5 for small tumors (<3.5 cm), and 17.8 for large tumors (≥3.5 cm). There was a statistically significant difference in the ANCA index between the groups defined by Ki-67 and tumor size. Nonfunctioning tumors with low Ki-67, no distant metastasis and small size had few aberrations detected by HR-CGH, but frequent loss of material from chromosomal band 11p11. The present study indicates the existence of distinct cytogenetic patterns in sporadic nonfunctioning PNEN. Loss of chromosomal band 11p11 might indicate a primary pathogenetic event in these tumors.
RETRACTED ARTICLE: Cloud Computing in Libraries and Higher Education: An Innovative User-Centric Quality of Service Model

ABSTRACTCloud computing has emerged as an effective system to support the implementation and growth of e-learning in the higher education sector, as well as in institutional libraries. This rising trend has attracted several service providers to the market in a very short span of time. Students and faculties associated with higher education are experiencing an increased need for the use of cloud computing services to aid development and enhancement of their knowledge base, and to help meet the requirement of constant access to the latest research data and electronic content. While accessing or providing such services, however, sufficient consideration and importance has not been attributed to the Quality of Service (QoS) provided and as experienced by the user, thus referenced as Quality of Experience (QoE), which plays an important role in making cloud computing applications more reliable and adaptable. Currently, no standard model exists that could effectively define the QoE parameters from the users’ p.
An Account of Transforms on A/G

In this article we summarize and describe the recently found transforms for theories of connections modulo gauge transformations associated with compact gauge groups. Specifically, we put into a coherent picture the so-called loop transform, the inverse loop transform, the coherent state transform and finally the Wick rotation transform which is the appropriate transform that incorporates the correct reality conditions of quantum gravity when formulated as a dynamical theory of connections while preserving the simple algebraic form of the Hamiltonian constraint.
Tuning the Feature Space using Support Vector Control

The fraction of training data chosen as support vectors gives us an ide of the complexity of the concept being modeled. Controlling the number of support v ectors and their relevance allows us to control the complexity of the concept learnt. In his paper we present a method to approximately control the fraction of suppor t vectors. We demonstrate it’s applicability to the tuning of the feature space where the proje cted data can be separated more effectively. We also outline other problems w here the same approach can be useful.
ARMin - Toward a six DoF upper limb rehabilitation robot

Early intervention and intensive therapy improve outcome of neuromuscular disorder rehabilitation. However, a major problem is posed by considerable controversy surrounding the most appropriate method of therapy and there are still insufficient data to identify clearly the benefits of different approaches. At the same time largely still non-patient-specific methods for diagnosis and therapy are currently being used. Evidence indicates that where patient is motivated and premeditates his movement, the recovery is more effective and intelligent machines allow a broad scope to investigate these conditions. The ARMin robot is designed to assist, enhance, evaluate, and document neurological and orthopedic rehabilitation. Model-based impedance control enables the patient's effort being taken into consideration by allowing the machine to comply with forces exerted by the patient. The interaction is enhanced through a multimodal display based on visual, auditory, and kinesthetic modalities
Revenue maximization in an optical router node - allocation of service windows

In this paper we study a revenue maximization problem for optical routing nodes. We model the routing node as a single server polling model with the aim to assign visit periods (service windows) to the different stations (ports) such that the mean profit per cycle is maximized. Under reasonable assumptions regarding retrial and dropping probabilities of packets the optimization problem becomes a separable concave resource allocation problem, which can be solved using existing algorithms.
Efficient mining of correlated sequential patterns based on null hypothesis

Frequent pattern mining has been a widely studied topic in the research area of data mining for more than a decade. However, pattern mining with real data sets is complicated - a huge number of co-occurrence patterns are usually generated, a majority of which are either redundant or uninformative. The true correlation relationships among data objects are buried deep among a large pile of useless information. To overcome this difficulty, mining correlations has been recognized as an important data mining task for its many advantages over mining frequent patterns. In this paper, we formally propose and define the task of mining frequent correlated sequential patterns from a sequential database. With this aim in mind, we re-examine various interestingness measures to select the appropriate one(s), which can disclose succinct relationships of sequential patterns. We then propose PSBSpan, an efficient mining algorithm based on the framework of the pattern-growth methodology which mines frequent correlated sequential patterns. Our experimental study on real datasets shows that our algorithm has outstanding performance in terms of both efficiency and effectiveness.
Role of Sarcoplasmic Reticulum Calcium in Development of Secondary Calcium Rise and Early Afterdepolarizations in Long QT Syndrome Rabbit Model

Background L-type calcium current reactivation plays an important role in development of early afterdepolarizations (EADs) and torsades de pointes (TdP). Secondary intracellular calcium (Cai) rise is associated with initiation of EADs. Objective To test whether inhibition of sarcoplasmic reticulum (SR) Ca2+ cycling suppresses secondary Cai rise and genesis of EADs. Methods Langendorff perfusion and dual voltage and Cai optical mapping were conducted in 10 rabbit hearts. Atrioventricular block (AVB) was created by radiofrequency ablation. After baseline studies, E4031, SR Ca2+ cycling inhibitors (ryanodine plus thapsigargin) and nifedipine were then administrated subsequently, and the protocols were repeated. Results At baseline, there was no spontaneous or pacing-induced TdP. After E4031 administration, action potential duration (APD) was significantly prolonged and the amplitude of secondary Cai rise was enhanced, and 7 (70%) rabbits developed spontaneous or pacing-induced TdP. In the presence of ryanodine plus thapsigargin, TdP inducibility was significantly reduced (2 hearts, 20%, p = 0.03). Although APD was significantly prolonged (from 298 ± 30 ms to 457 ± 75 ms at pacing cycle length of 1000 m, p = 0.007) by ryanodine plus thapsigargin, the secondary Cai rise was suppressed (from 8.8 ± 2.6% to 1.2 ± 0.9%, p = 0.02). Nifedipine inhibited TdP inducibility in all rabbit hearts. Conclusion In this AVB and long QT rabbit model, inhibition of SR Ca2+ cycyling reduces the inducibility of TdP. The mechanism might be suppression of secondary Cai rise and genesis of EADs.
Treatment of Colon and Lung Cancer Patients with ex Vivo Heat Shock Protein 70-Peptide-Activated, Autologous Natural Killer Cells

Purpose: The 14 amino acid sequence (aa450–463) TKDNNLLGRFELSG (TKD) of heat shock protein 70 (Hsp70) was identified as a tumor-selective recognition structure for natural killer (NK) cells. Incubation of peripheral blood lymphocyte cells with TKD plus low-dose interleukin 2 (IL-2) enhances the cytolytic activity of NK cells against Hsp70 membrane-positive tumors, in vitro and in vivo. These data encouraged us to test tolerability, feasibility, and safety of TKD-activated NK cells in a clinical Phase I trial. Experimental Design: Patients with metastatic colorectal cancer (n = 11) and non-small cell lung cancer (n = 1) who had failed standard therapies were enrolled. After ex vivo stimulation of autologous peripheral blood lymphocytes with Hsp70-peptide TKD (2 μg/ml) plus low-dose IL-2 (100 units/ml), TKD was removed by extensive washing, and activated cells were reinfused i.v. The procedure was repeated for up to six cycles, applying a dose escalation schedule in 4 patients. Results: The percentage of activated NK cells in the reinfused leukapheresis products ranged between 8 and 20% of total lymphocytes, corresponding to total NK cell counts of 0.1 up to 1.5 × 109. Apart from restless feeling in 1 patient and itching in 2 patients, no negative side effects were observed. Concomitant with an enhanced CD94 cell surface density, the cytolytic activity of NK cells against Hsp70 membrane-positive colon carcinoma cells was enhanced after TKD/IL-2 stimulation in 10 of 12 patients. Concerning tumor response, 1 patient was in stable disease during therapy by formal staging criteria and another patient showed stable disease in one metastases and progression in another. Conclusions: Reinfusion of Hsp70-activated autologous NK cells is safe. Immunological results warrant additional studies in patients with lower tumor burden.
Measuring Change in Social Communication Behaviors: Reliability, Validity, and Application

Measuring Change in Social Communication Behaviors: Reliability, Validity, and Application Rebecca Grzadzinski Purpose: The field of Autism Spectrum Disorder (ASD) intervention research is in need of treatment response measures that are sensitive to change and flexible enough to be used across studies. The Brief Observation of Social Communication Change (BOSCC) was developed to address this need. The purpose of this work is to examine the initial reliability and validity of the BOSCC in two samples of children with ASD. Method: In a sample of 56 children participating in ongoing early intervention, the primary objectives of Study 1 were to 1) determine items for inclusion in the BOSCC coding scheme, 2) explore the relationships among items using factor analysis, 3) assess inter-rater and test-retest reliability, and 4) explore change over time. Using a sample of school-age, minimally-verbal children, the primary objectives of Study 2 were to extend the results of Study 1 to a new sample to 1) assess BOSCC changes over time, 2) compare changes in BOSCC to clinician determinations of improvement, 3) examine the relationship between change in BOSCC scores with changes in baseline cognitive skills, adaptive functioning, and ASD severity, and 4) compare changes in BOSCC scores in children who did and did not change on other standard measures. Results: Study 1 revealed that the BOSCC has high to excellent inter-rater and test-retest reliability and shows convergent validity with measures of language and communication skills. The BOSCC Core total demonstrated statistically significant amounts of change over time while the ADOS Calibrated Severity Score over the same period did not. Results of Study 2 confirmed excellent inter-rater reliability but the BOSCC did not change significantly over time. Most children were identified by clinicians as improving in response to treatment. However, only 15% of children changed significantly on the BOSCC over 16 weeks of intervention. Limitations: Both studies had small samples of predominantly male, Caucasian children. When interpreting the results of these studies, it is important to consider the differences between samples, including the shorter time of treatment and more cognitively and language impaired children in Study 2. Conclusions: These studies are a first step in the development of a novel outcome measure for social-communication behaviors with applications to clinical trials and longitudinal studies. Future work should continue to explore the benefits and limitations of the BOSCC in larger independent samples.