Miracle-dz/UniFAR-FTUs huggingface dataset:
The Sustainability of Biofuels: Limits of the Meta-Standard Approach

This paper examines the European Union (EU) biofuels and bioliquids sustainability scheme. It argues that the ‘meta-standard’ approach adopted in the EU sustainability scheme is an innovative addition to the EU’s environmental governance toolkit. From a global governance perspective, the EU meta-standard will aid the process of streamlining the proliferation of certification schemes and harmonizing global standards. This will reduce transaction costs for biofuels producers and promote the growth of a sustainable biofuels industry. However, given the close resemblance between the heavy reliance on auditors in the sustainability scheme and that placed on designated operational entities (DOEs) in the Clean Development Mechanism (CDM), this paper argues that the same problems that threaten the integrity of the CDM verification process are likely to emerge in the EU sustainability scheme. It is therefore necessary to reevaluate the wisdom of extensive reliance on voluntary schemes to perform environmental monitoring functions.
Trade-Offs in a Google Distance and a WordNet Hybrid for QoS-Enabled Web Services Composition

This paper proposes a hybrid approach in using Google Distance and WordNet together in a new method for the semantic similarity matching stage of web services discovery. We provide comparisons, using services recall and precision metrics, between our hybrid approach and our earlier lightweight Google Distance-based approach for web services discovery. Our performance evaluation demonstrates the trade-offs between the Google Distance only approach and a WordNet-assisted Google Distance hybrid approach for similarity matching in the web services discovery phase. Further, the impact of both approaches on QoS-enabled web service composition is described for 7 representative web transactions in the Travel domain.
Screening vaccine formulations for biological activity using fresh human whole blood

Understanding the relevant biological activity of any pharmaceutical formulation destined for human use is crucial. For vaccine-based formulations, activity must reflect the expected immune response, while for non-vaccine therapeutic agents, such as monoclonal antibodies, a lack of immune response to the formulation is desired. During early formulation development, various biochemical and biophysical characteristics can be monitored in a high-throughput screening (HTS) format. However, it remains impractical and arguably unethical to screen samples in this way for immunological functionality in animal models. Furthermore, data for immunological functionality lag formulation design by months, making it cumbersome to relate back to formulations in real-time. It is also likely that animal testing may not accurately reflect the response in humans. For a more effective formulation screen, a human whole blood (hWB) approach can be used to assess immunological functionality. The functional activity relates directly to the human immune response to a complete formulation (adjuvant/antigen) and includes adjuvant response, antigen response, adjuvant-modulated antigen response, stability, and potentially safety. The following commentary discusses the hWB approach as a valuable new tool to de-risk manufacture, formulation design, and clinical progression.
The Danish Civil Registration System. A cohort of eight million persons.

BACKGROUND The Danish Civil Registration System (CRS) was established in 1968, where all persons alive and living in Denmark were registered. Among many other variables, it includes individual information on personal identification number, gender, date of birth, place of birth, place of residence, citizenship, continuously updated information on vital status, and the identity of parents and spouses. METHODS To evaluate the quality and completeness of the information recorded on persons in the CRS, we considered all persons registered on November 4, 2005, i.e. all persons who were alive and resident in Denmark at least one day from April 2, 1968 to November 4, 2005, or in Greenland from May 1, 1972 to November 4, 2005. RESULTS A total of 8,176,097 persons were registered. On November 4, 2005, 5,427,687 (66.4%) were alive and resident in Denmark, 56,920 (0.7%) were alive and resident in Greenland, 2,141,373 (26.2%) were dead, 21,160 (0.3%) had disappeared, and 528,957 (6.5%) had emigrated. Among persons born in Denmark 1960 or later the CRS contains complete information on maternal identity. Among persons born in Denmark 1970 or later the CRS contains complete information on paternal identity. Among women born in Denmark April 1935 or later the CRS contains complete information on all their children. Among males born in Denmark April 1945 or later the CRS contains complete information on all their children. The CRS contains complete information on: a) immigrations and emigrations from 1971 onwards, b) permanent residence in a Danish municipality from 1971 onwards, c) permanent residence in a municipality in Greenland from May 1972 onwards, and d) full address in Denmark from 1977 onwards. CONCLUSION Data from the CRS is an important research tool in epidemiological research, which enables Danish researchers to carry out representative population-based studies on e.g. the potential clustering of disease and death in families and the potential association between residence and disease and death.
Link Mining: A Computer Vision and Pattern Mining Approach

This work addresses the important problem of discovery and analysis of social networks and link between frequent people observed from surveillance video footage where large amount of video data is collected routinely. A computer vision approach has been applied for detecting and extracting people within a group using HAAR classifier. This technique allows us to recognizing people by doing similarity matching between training faces and unknown detected face image. Therefore it is required to obtain high resolution face images of people in order to extract intrinsic feature information of facial images used in detection of person’s faces. We present a novel frequent pattern mining based approach in the domain of frequent person detection i.e. apriori to solve frequent association problem between social networks obtained from low level task of face recognition. Our approach is illustrated with promising results from a fully integrated camera system. General Terms Data Mining, Frequent Pattern Mining, Social Network Analysis, Dynamic Social Network Analysis
Effect of Helicobacter pylori on metabolic syndrome parameters in diabetic patients

Aim: The aim of this study is to survey the effect of Helicobacter Pylori on metabolic syndrome parameters in diabetic patients. Background: Helicobacter pylori (HP) infection is the most common infection in developing countries. Some studies showed the association between HP infection and insulin resistance. Insulin resistance is a major mechanism in the development of metabolic syndrome (MetS) and it is said that MetS is more prevalent among HP infected subjects. Also, some studies have shown that MetS is common among patients with type 2 diabetes mellitus. In this study, we aimed to investigate the prevalence of MetS in diabetic patients and its association with HP. Methods: This cross-sectional study was carried out from May to December 2014 on 211 diabetic patients. For each patient, the following data were collected: age, gender, diabetes duration, weight, body mass index (BMI), waist circumference, blood pressure (BP), HDL, cholesterol, triglyceride (TG), total cholesterol, and HbA1c. The lipid profile was performed on fasting samples. Anti- HP IgG antibody was measured and serum titer >30AU/mL was considered positive. MetS was diagnosed by The National Cholesterol Education Program’s Adult Treatment Panel III report (NCEP-ATPIII) and IDF criteria. Results: Totally 139 patients (65.9%) were HP+ and 72 patients (34.1%) were HP-. Age, gender and diabetes duration were not significantly different in both groups. BMI was significantly lower in HP+ women (29.05±5.26 vs. 31.45±4.8, p=0.02). Although the waist circumference of men was not different between the two groups but it was significantly lower in HP+ women (102.04±12.37 vs. 97.3±10, p=0.03). Although BP and TG levels were not statistically different in HP+ and HP- patients, but HP+ patients had lower HDL level (p=0.037) which was due to lower HDL in men (58.2±26.6 vs. 72.48±28.1, p=0.012). The prevalence of MetS according to the IDF criteria among HP+ and HP- patients was 76.6% vs. 69.8% (p=0.27). Also, the prevalence of MetS according to NCEP-ATP III criteria among HP+ and HP- patients was 90.4% vs. 87.2% (p=0.5). Duration of diabetes did not affect the prevalence of metabolic syndrome among HP+ and HP- patients. Conclusion: It seems that HP infection increases the prevalence of metabolic syndrome through an increase in insulin resistance. According to NCEP-ATPIII criteria, the increase in the prevalence of metabolic syndrome in HP+ patients is almost significant, however more complete studies is recommended to investigate this relationship.
The rich and the poor in the EU and the Great Recession: evidence from a Panel Analysis

This paper proposes a theoretical framework of the factors affecting the gap between the rich and the poor in the European Union, and utilizes a twelve-year panel (2000-2012) of 27 countries to identify the short-term effects of the macroeconomic performance, the level of household income inequality, and the social protection expenditure, controlling for several structural factors of income disparities. It is assessed their impact on the bottom, median and top shares of household income; it is found a different effect of the three core determinants before the Great Recession and during the crisis years, and a different public commitment depending on the type of welfare regime.
Approximating the age of RF/analog circuits through re-characterization and statistical estimation

Counterfeit ICs have become an issue for semiconductor manufacturers due to impacts on their reputation and lost revenue. Counterfeit ICs are either products that are intentionally mislabeled or legitimate products that are extracted from electronic waste. The former is easier to detect whereas the latter is harder since they are identical to new devices but display degraded performance due to environmental and use stress conditions. Detecting counterfeit ICs that are extracted from electronic waste requires an approach that can approximate the age of manufactured devices based on their parameters. In this paper, we present a methodology that uses information on both fresh and aged ICs and tries to distinguish between the fresh and aged population based on an estimate of the age. Since analog devices age mainly due to their bias stress, input signals play less of a role. Hence, it is possible to use simulation models to approximate the aging process, which would give us access to a large population of aged devices. Using this information, we can construct a statistical model that approximates the age of a given circuit. We use a Low noise amplifier (LNA) and an NMOS LC oscillator to demonstrate that individual aged devices can be accurately classified using the proposed method.
Expression and Characterization of Recombinant Human-DerivedPneumocystis carinii Dihydrofolate Reductase

ABSTRACT Dihydrofolate reductase (DHFR) is the target of trimethoprim (TMP), which has been widely used in combination with sulfa drugs for treatment and prophylaxis of Pneumocystis cariniipneumonia. While the rat-derived P. carinii DHFR has been well characterized, kinetic studies of human-derived P. carinii DHFR, which differs from rat-derived P. carinii DHFR by 38% in amino acid sequence, have not been reported to date. Here we report on the expression and kinetic characterization of the recombinant human-derived P. carinii DHFR. The 618-bp coding sequence of the human-derivedP. carinii DHFR gene was expressed in Escherichia coli. As determined by sodium dodecyl sulfate-polyacrylamide gel eletrophoresis, the purified enzyme had a molecular mass of 25 kDa, consistent with that predicted from the DNA sequence. Kinetic analysis showed that the Km values for dihydrofolate and NADPH were 2.7 ± 0.3 and 14.0 ± 4.3 μM, respectively, which are similar to those reported for rat-derived P. carinii DHFR. Inhibition studies revealed that both TMP and pyrimethamine were poor inhibitors of human-derived P. carinii DHFR, withKi values of 0.28 ± 0.08 and 0.065 ± 0.005 μM, respectively, while trimetrexate and methotrexate were potent inhibitors, with Kivalues of 0.23 ± 0.03 and 0.016 ± 0.004 nM, respectively. The availability of purified recombinant enzyme in large quantities should facilitate the identification of antifolate inhibitors with greater potency and higher selectivity for human-derived P. cariniiDHFR.
Predictive model of the human muscle fatigue: application to repetitive push-pull tasks with light external load

Repetitive tasks in industrial works may contribute to health problems among operators, such as musculo–skeletal disorders, in part due to insufficient control of muscle fatigue. In this paper, a predictive model of fatigue is proposed for repetitive push/pull operations. Assumptions generally accepted in the literature are first explicitly set in this framework. Then, an earlier static fatigue model is recalled and extended to quasi–static situations. Specifically, the maximal torque that can be generated at a joint is not considered as constant, but instead varies over time accordingly to the operator's changing posture. The fatigue model is implemented with this new consideration and evaluated in a simulation of push/pull operation.
Route and Stopping Intent Prediction at Intersections From Car Fleet Data

In this paper, an approach is presented to predict the route and stopping intent of human-driven vehicles at urban intersections using a selection of distinctive features observed on the vehicle state (position, heading, acceleration, velocity). For potential future advanced driver assistance systems, this can facilitate the situation analysis and risk assessment at road intersections, helping to improve the protection of vulnerable road users. After extracting recorded driving data for nine intersections (featuring over 50 000 crossings) from a database, they are assigned to possible routes and transformed from a time-based representation to a distance-based one. Using random decision forests, the route intent can be predicted with a mean unweighted average recall (UAR) of 0.76 at 30 m before the relevant intersection center, the stopping intent prediction scores a mean UAR of 0.78.
Self-tuning of game scenarios through self-adaptative multi-agent systems

Les jeux video modernes deviennent de plus en plus complexes, tant par le nombre de regles qui les composent, que par le nombre d'entites artificielles qui y interagissent. D'un point de vue purement ludique, mais egalement en ayant des ambitions pedagogiques, les jeux doivent proposer aux joueurs des experiences qui correspondent a leurs niveaux de competences et a leurs capacites. La diversite au sein de la population de joueurs rend difficile, voire impossible, de proposer une experience qui aille a tout un chacun. Differents niveaux et differentes capacites de progression font que differents joueurs ont des besoins distincts. L'adaptation des jeux est proposee comme une solution pour palier ces difficultes. Cette these propose un ensemble de concepts afin que des concepteurs de jeux, ou des experts de differents domaines, puissent exprimer des objectifs pedagogiques ou ludiques, ainsi que des contraintes sur les experiences de jeu. La genericite de ces concepts les rend compatible avec une grande variete d'application, potentiellement hors du domaine du jeu video. Conjointement a ces concepts, nous proposons un systeme multi-agent concu pour modifier dynamiquement les parametres d'un moteur de jeu, afin que celui-ci satisfasse les objectifs definis par les experts ou les concepteurs. Le systeme est compose d'un ensemble d'agents autonomes, qui representent les concepts du domaine. Ils n'ont qu'une vue locale de leur environnement et ne connaissent pas la fonction globale du systeme. Ils ne cherchent qu'a resoudre cooperativement les probleme locaux qu'ils rencontrent. De l'organisation des agents emerge la fonctionnalite du systeme : l'adaptation de l'experience de jeu menant a la satisfaction des objectifs ainsi qu'au respect des contraintes. Nous avons conduit plusieurs experiences pour demontrer que le systeme passe l'echelle, et qu'il est resistant au bruit. Le paradigme avec lequel les objectifs doivent etre definis est utilise dans des contextes varies pour demontrer sa genericite. D'autres applications demontrent que le systeme est capable d'adapter une experience du joueur meme quand les conditions de jeu evoluent significativement au cours du temps.
Scenarios of Robot Assisted Play for Children with Cognitive and Physical Impairments

This article presents a set of play scenarios for robot assisted play for children with disabilities. This work was developed as part of the pan-European IROMEC project that investigated how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play (with peers, carers/teachers, parents etc). The target user groups in the project were children with Mild Mental Retardation 1 , children with Severe Motor Impairment and children with Autism. The play scenarios were developed against specific educational and therapeutic objectives that were discussed with panels of experts (teachers therapists parents) in various countries, during several user panel meetings for each of the above mentioned target user groups. These objectives were classified with reference to the ICF-CY, the International Classification of Functioning – version for Children and Youth. The article presents a set of play scenarios, each with its relevant educational and therapeutic objectives in five key developmental areas (i.e sensory development, communication and interaction, cognitive development, motor development and social and emotional development). Although the play scenarios presented in this paper originally were developed for and tested with the above user groups and with the IROMEC robot, the play scenarios may be considered for use with other user groups or in other applications involving human-robot interaction and with other robotic toys. 1 The term Mental Retardation was replaced in the UK by the Disability Discrimination Act, with the term Learning Difficulties. However, as it is still being widely used in continental Europe, this was the term chosen to be used within the IROMEC project
Web document clustering approach using wordnet lexical categories and fuzzy clustering

Web mining is defined as applying data mining techniques to the content, structure, and usage of Web resources. The three areas of Web mining are commonly distinguished: content mining, structure mining, and usage mining. In all these areas, a wide range of general data mining techniques, in particular association rule discovery, clustering, classification, and sequence mining, are employed and developed further to reflect the specific structures of Web resources and the specific questions posed in Web mining. In this paper, we introduced a Web document clustering approach that uses WordNet lexical categories and fuzzy c-means algorithm to improve the performance of clustering problem for Web document. Experiments show that fuzzy c-means algorithm achieves great performance optimization with comparison with the recent algorithms for document clustering.
Using digital forensic readiness model to increase the forensic readiness of a computer system

Nowadays systems administrators are facing with huge challenges in securing and protecting information systems. Intrusions attempts are increasing and becoming more sophisticated by days leading to the common presumption that any information systems can be hacked into, no matter what level of security measures are being taken. Systems administrators are also relying heavily on security tools to secure their computer systems and security tools can be out-dated overtime. Therefore from digital forensics perspectives, preparing the systems in advance with the presumption that the information systems will be hacked, and taking all the necessary steps to ensure preservation of key evidences, can lead to successful legal prosecutions. The Authors proposed a simplified Digital Forensic Readiness Model as a framework that can be used to prepare any appropriate computer system forensically and increase its readiness at the same time.
Diffusion microscopic MRI of the mouse embryo: Protocol and practical implementation in the splotch mouse model

Advanced methodologies for visualizing novel tissue contrast are essential for phenotyping the ever‐increasing number of mutant mouse embryos being generated. Although diffusion microscopic MRI (μMRI) has been used to phenotype embryos, widespread routine use is limited by extended scanning times, and there is no established experimental procedure ensuring optimal data acquisition.
3-D dataset for Human Activity Recognition in video surveillance

We introduces a new 3-D video dataset to assess the performance of Human Activity Recognition system in indoor and outdoor environment. This dataset also help to check the performance of activity recognition algorithms against the effect of varying illumination, background and viewpoint. The available dataset for activity recognition are simple and most of them contain RGB information only as well as fewer complex and far away from real world general scenario. This dataset consist of RGB and depth information for all the activities performed under different illumination condition and viewpoint. This dataset includes ten activities performed by eleven subjects in four illumination condition and three viewpoints. Around one hundred and ten videos of one hour duration are recorded and annotated. We believe that the additional depth information provided will be useful for researcher in analyzing the performance of activity recognition algorithms for real time implementation. Large no of dataset are publicly available but most of them are less complex and consist of RGB data only. The proposed dataset is more complex and comprises of depth information along with RGB.
Equivalent optimal compensation problem in the delta domain for systems with white stochastic parameters

The equivalent representation in the delta domain of the digital optimal compensation problem is provided and computed in this article. This problem concerns finding digital optimal full and reduced-order output feedback controllers for linear time-varying and time-invariant systems with white stochastic parameters. It can subsequently be solved in the delta domain using the strengthened optimal projection equations that we recently formulated in this domain as well. If the sampling rate becomes high, stating and solving the problem in the delta domain becomes necessary because the conventional discrete-time problem formulation and solution become ill-conditioned. In this article, by means of several numerical examples and compensator implementations, we demonstrate this phenomenon. To compute and quantify the improved performance when the sampling rate becomes high, a new delta-domain algorithm is developed. This algorithm computes the performance of arbitrary digital compensators for linear systems with white stochastic parameters. The principle application concerns nonconservative robust digital perturbation feedback control of nonlinear systems with high sampling rates.