Miracle-dz/UniFAR-FTUs huggingface dataset:
An advanced smart management system for electric vehicle recharge

Recent studies about climate change are mandating a drastic reduction of green house gas (GHG) emissions. Solutions include the utilization of renewable energy sources (e.g., wind, solar energy) and the increased utilization of hybrid and electric vehicles (EVs). In this scenario ICT can play a significant role by fostering the smart utilization of current energy and transportation infrastructures (smart grid and smart cities). This paper presents a new ICT infrastructure to enable the intelligent exploitation of distributed energy resources in order to minimize the EV charging times while optimizing the efficiency of the electrical infrastructure. The proposed system is based on a distributed communication infrastructure (both wired and wireless) aimed at collecting/emitting bidirectional energy dispatching opportunities for electric vehicles. The envisaged system seamlessly interconnects emerging self-organizing wireless technologies (i.e., VANETs and Wireless Mesh Networks), with legacy wired communication technologies, to guarantee a fast rollout of the EV charging service with minimum investments in communication infrastructures. The performance of the proposed solution is evaluated in terms of its sustainability by analyzing the quality of the charging service as perceived by the users, and the capability of the charging infrastructure to meet the charging requests in a timely manner.
Relationship between quality of life and clinical status in asthma: a factor analysis

Many studies have shown that correlation between clinical asthma status and asthma-specific quality of life is only weak to moderate. However, this relationship has never been explored to determine whether the weakness is due to noise of measurement or whether quality of life is a distinct component of asthma health status. With a database from three clinical trials (n=763), factor analysis was used to explore the relationships between quality of life, measured by the Asthma Quality of Life Questionnaire (AQLQ), and conventional measures of asthma clinical status (symptoms, airway calibre and rescue β2‐agonist use). The analysis revealed that although patients with severe, poorly controlled asthma tend to have worse quality of life than milder, well-controlled patients, overall asthma health status has four components (factors): asthma-specific quality of life; airway calibre; daytime symptoms and daytime β2‐agonist use, and night-time symptoms and night-time β2‐agonist use. The clean loading of all 21 outcomes onto four distinct and clinically identifiable factors suggests that, although some weakness of correlation between clinical indices and quality of life may be due to noise of measurement, it is mainly attributable to asthma health status being composed of distinct components.
Superimposed Pilots Based Secure Communications for a System with Multiple Antenna Arrays

In this paper, we investigate secure communications by introducing superimposed pilots for multiple antenna system. The superimposed pilots enable the trellis-based joint channel tracking and data detection for the user of interest. Further, by adjusting the power ratio between the data symbol and superimposed pilot symbol, the secure capacity region can be established. The user of interest can appropriately select the Forward Error Correction (FEC) code rate, to prevent any possible eavesdropping. In this paper, we present the achievable secure capacity region for multiple antenna system, and verify it via Monte Carlo simulation as well.
Feature Selection Pitfalls and Music Classification

Previous work has employed an approach to the evaluation of wrapper feature selection methods that may overstate their ability to improve classification accuracy, because of a phenomenon akin to overfitting. This paper discusses this phenomenon in the context of recent work in machine learning, demonstrates that previous work in MIR has indeed exaggerated the efficacy of feature selection for music classification, and presents new testing providing a more realistic analysis of feature selection’s impact on music classification accuracy.
Human arm estimation using convex features in depth images

Human arm estimation is very important for HCI and human pose estimation, but it remains a challenging problem due to complex environments, various poses, etc. In this paper, an efficient and robust method is presented to estimate human arms from depth images. Firstly, three convex features are explored from depth images for lower/upper arm detection, including convex degree feature (CDF), convex region feature (CRF), and U-type depth feature (UDF). With these effective features, secondly, the upper arm and lower arm candidates are accurately and quickly detected in a parallel and complementary way. Finally, the full arm is estimated based on depth continuity and human configuration constraint. Experiments on lots of test images demonstrate the robustness and efficacy of this approach.
Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

MOTIVATION Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease-phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease-manifestation (D-M) pairs (one specific type of disease-phenotype relationship) from the wide body of published biomedical literature. DATA AND METHODS Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M-specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. RESULTS In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. CONCLUSIONS The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. AVAILABILITY http://nlp.case. edu/public/data/DMPatternUMLS/
Trends in Substance Abuse Preceding Stroke Among Young Adults: A Population-Based Study

Background and Purpose— Approximately 5% of strokes occur in adults aged 18 to 44 years. Substance abuse is a prevalent risk factor for stroke in young adults. We sought to identify trends in substance abuse detection among stroke patients. Methods— Using a population-based design, we sought to identify all patients aged 18 to 54 years experiencing a stroke (ischemic or hemorrhagic) in the Greater Cincinnati and Northern Kentucky Study region during 1993 to 1994, 1999, and 2005. Demographic and clinical characteristics and substance use data were obtained retrospectively from chart review and adjudicated by physicians. Results— The number of young patients identified with a stroke increased from 1993 to 1994 (297) to 2005 (501). Blacks (61% vs 51%; P<0.02) and men (61% vs 47%; P<0.002) reported substance abuse (current smoking, alcohol, or illegal drug use) more frequently than did whites and women. Overall use of substances increased across study periods, 45% in 1993 versus 62% in 2005 (P=0.003). The trend was significant for illegal drug use (3.8% in 1993 vs 19.8% in 2005) and ever smoking (49% in 1993 vs 66% in 2005). Documentation of both cocaine and marijuana use increased over time. In 2005, half of young adults with a stroke were current smokers, and 1 in 5 abused illegal drugs. Conclusions— Substance abuse is common in young adults experiencing a stroke. The observed increase in substance abuse is contributing to the increased incidence of stroke in young adults. Patients aged younger than 55 years who experience a stroke should be routinely screened and counseled regarding substance abuse.
Why the Theremin Fell By the Wayside

The theremin was the first major electronic musical instrument. Players cause the theremin to produce sound without contact at all by manipulating electromagnetic fields with their hands. This unique design often sparks interest in those that learn about it, but despite this fact, the theremin has remained in relative obscurity since its invention. This paper discusses the history of the theremin and explains why it failed to gain widespread adoption, drawing on research in the growing field of
Testing and Fault Diagnosis of Time-Interleaved S? Modulators Using Checksums

Mismatch of components in a time-interleaved ADC (TIADC) is a major problem which can significantly degrade the performance, even with a 0.5% mismatch. This paper describes a new technique which uses checksums for diagnosing the mismatch of components among sub-ADCs in a TIADC. In our checksum formulation, a transition matrix is used to represent the transition relationship between the current state and the next state of modulators, while another matrix is used to represent the states of a TIADCs, where the state of a sub-ADC is presented in a column vector. We have applied the checksum technique to a TIADC which contains two 1-bit fifth-order ΣΔ modulators with matched resistances and capacitances, and demonstrated that the checksums successfully detect and locate mismatches.
Why it's quick to be square: modelling new and existing hierarchical menu designs

We consider different hierarchical menu and toolbar-like interface designs from a theoretical perspective and show how a model based on visual search time, pointing time, decision time and expertise development can assist in understanding and predicting interaction performance. Three hierarchical menus designs are modelled -- a traditional pull-down menu, a pie menu and a novel Square Menu with its items arranged in a grid -- and the predictions are validated in an empirical study. The model correctly predicts the relative performance of the designs -- both the eventual dominance of Square Menus compared to traditional and pie designs and a performance crossover as users gain experience. Our work shows the value of modelling in HCI design, provides new insights about performance with different hierarchical menu designs, and demonstrates a new high-performance menu type.
Just the Numbers: An Investigation of Contextualization of Problems for Novice Programmers

Contextualization of problems is widely studied in mathematics education. In computer science it is taken for granted that authentic, contextualized programming assignments will increase student interest and therefore enhance performance in programming assignments. This paper examines whether contextualization is, in fact, beneficial for students. We present a study that compares novice programmers' ability to code a solution given two versions of a problem. One version is contextualized, the other is non-contextualized, using "just the numbers. " The results presented indicate that there is no difference in success rates for the two types of programming assignments.
Comparative Phylogenomics of Pathogenic and Non-Pathogenic Mycobacterium

Mycobacterium species are the source of a variety of infectious diseases in a range of hosts. Genome based methods are used to understand the adaptation of each pathogenic species to its unique niche. In this work, we report the comparison of pathogenic and non-pathogenic Mycobacterium genomes. Phylogenetic trees were constructed using sequence of core orthologs, gene content and gene order. It is found that the genome based methods can better resolve the inter-species evolutionary distances compared to the conventional 16S based tree. Phylogeny based on gene order highlights distinct evolutionary characteristics as compared to the methods based on sequence, as illustrated by the shift in the relative position of M. abscessus. This difference in gene order among the Mycobacterium species is further investigated using a detailed synteny analysis. It is found that while rearrangements between some Mycobacterium genomes are local within synteny blocks, few possess global rearrangements across the genomes. The study illustrates how a combination of different genome based methods is essential to build a robust phylogenetic relationship between closely related organisms.
Embarrassingly Parallel Sequential Markov-chain Monte Carlo for Large Sets of Time Series

Bayesian computation crucially relies on Markov chain Monte Carlo (MCMC) algorithms. In the case of massive data sets, running the Metropolis-Hastings sampler to draw from the posterior distribution becomes prohibitive due to the large number of likelihood terms that need to be calculated at each iteration. In order to perform Bayesian inference for a large set of time series, we consider an algorithm that combines 'divide and conquer" ideas previously used to design MCMC algorithms for big data with a sequential MCMC strategy. The performance of the method is illustrated using a large set of financial data.
Further properties of second-order multi-agent flocking under Olfati-Saber's algorithms

In this paper, we revisit the flocking control algorithms suggested by Olfati-Saber for the second-order multi-agent networks, in which the multi-agents are driven by the distributed algorithms installed on each and all agents that are based merely on local measurements of neighboring multi-agent position and velocity vectors. It has been shown that by under appropriate initial conditions about the agent positions and velocities, the concerned multi-agent systems eventually run into flocking formation, namely α-lattice, by means of the Olfati-Saber control algorithms. This paper is devoted to probe into additional features and properties under the same flocking algorithms. What is revealed further in this study includes: the average flocking trajectory, its controllability and geometrical facts, steady-state features and the modes of the structural dynamics. Moreover, possible inter-agent collision is verified via the variation-of-constant formula and the Gronwall inequality when the agents initially aggregate too densely. Numerical examples are sketched to illustrate the main results.
Platelet rich plasma (PRP) enhances anabolic gene expression patterns in flexor digitorum superficialis tendons

Platelet rich plasma (PRP) has recently been investigated for use in tissue regeneration studies that seek to utilize the numerous growth factors released from platelet α‐granules. This study examined gene expression patterns, DNA, and collagen content of equine flexor digitorum superficialis tendon (SDFT) explants cultured in media consisting of PRP and other blood products. Blood and bone marrow aspirate (BMA) were collected from horses and processed to obtain plasma, PRP, and platelet poor plasma (PPP). IGF‐I, TGF‐β1, and PDGF‐BB were quantified in all blood products using ELISA. Tendons were cultured in explant fashion with blood, plasma, PRP, PPP, or BMA at concentrations of 100%, 50%, or 10% in serum‐free DMEM with amino acids. Quantitative RT‐PCR for expression of collagen type I (COL1A1), collagen type III (COL3A1), cartilage oligomeric matrix protein (COMP), decorin, matrix metalloproteinase‐3 (MMP‐3), and matrix metalloproteinase‐13 (MMP‐13) was performed as were DNA and total soluble collagen assays. TGF‐β1 and PDGF‐BB concentrations were higher in PRP compared to all other blood products tested. Tendons cultured in 100% PRP showed enhanced gene expression of the matrix molecules COL1A1, COL3A1, and COMP with no concomitant increase in the catabolic molecules MMP‐3 and MMP‐13. These findings support in vivo investigation of PRP as an autogenous, patient‐side treatment for tendonitis. © 2006 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 25:230–240, 2007
Elastic, scalable and self-tuning data replication in the cloud-TM platform

Over the last years Cloud Computing has emerged as a disruptive paradigm for the future generation of IT services. Just as the electric grid revolutionized access to electricity one hundred years ago, freeing corporations from having to generate their own power and enabling them to concentrate on their business differentiators, cloud computing is hailed as revolutionizing IT, freeing corporations from large IT capital investments and enabling them to plug into extremely powerful computing resources over the network.
High School Students' Perceptions of the Relationship between Music and Math.

While there is little doubt that engaging in musical or mathematical activities stimulates brain activity at high levels and that increased student involvement fosters a greater learning environment, questions remain about whether musical ability and mathematics performance are related. This study took a qualitative approach that allowed 24 high school students to share their direct experiences with music and mathematics, as well as their perceptions of how the two fields are related. Participants were divided into four groups based on school music participation and level of mathematic achievement. Using a multiple intelligence lens, this study addressed the following question: How do students perceive the fields of music and mathematics relating to each other? Interestingly, most of the students saw math as a foundation for musical ability, which suggest a different direction than most previous studies. The musical element of rhythm seemed to have the most mathematical connection. This implies several possibilities for educators, including encouraging students in both areas of study to recognize the connections between the two, if not particularly the influence of one over the other. Additionally, teachers in both fields may begin more collaborative efforts to support the learning in both content areas. Future studies include looking at the specific perceptions of students based on ethnicity, gender, and SES status, as well as exploring the motivation of students in both music and mathematics.
Intelligent Search Agents Using Web-Driven Natural-Language Explanatory Dialogs

T he World Wide Web’s accelerated growth has turned the Internet into an immense information space with diverse and often poorly organized content. Users are confronted with rapidly increasing amounts of information as epitomized by the term “information overload. ” While minimal training seems to provide the skills necessary for browsing individual Web sites, query-based searching and intersite navigation require more expertise.1 The efficient use of search engines such as AltaVista and Excite requires sophisticated knowledge. Investigations of the search behavior of both expert and novice Web users have several practical applications. A model of search behavior can serve as the basis for improving the interfaces and functionality of existing search systems. More sophisticated future systems can identify the varied needs of both experts and novice users. Also, help systems can benefit from a better understanding of users’ difficulties with the search process.2 Web user behavior has attracted some attention in the user modeling community. Tesa Lau and Eric Horvitz, for example, constructed Bayesian networks to model the successive queries that search engine users issue.3 These networks can augment the search engine logfile with manually assigned categories of presumed information goals to predict query modifications. Similarly, Ingrid Zukerman and colleagues proposed using Markov models to predict a Web user’s next request based on the timing and location of past requests.4 However, these studies do not address the user’s personal characteristics and level of expertise. Although traditional keyword-based information search systems can provide a first step for use in the overall search process, the challenge is to perform tasks more accurately and intelligently, applying a user’s knowledge—intentions, goals, and so on— to improve search capabilities with a minimum of interactions or exchanges. Those limitations can be partially overcome using the knowledge obtained from natural-language interactions between the user and the search engine. From the behavior point of view, our research proposes that user feedback in terms of (natural) dialog interactions can play a key role in reducing information overload and getting accurate information about what the user is searching for. This underlying linguistic knowledge could assist in making the search system more specific by restricting requirements and identifying the user’s intentions. Accordingly, we explore the generation of natural-language interactive dialogs for bibliographical searching on the Web to improve the searching and filtering process by minimizing user exchanges. A computational linguistics approach for Web-based cooperative dialogs focuses on the user’s requests by automatically generating languagedriven interactions that take into account the context, user feedback, and the initial search’s results.
DNA methylation of multiple promoter-associated CpG islands in adult acute lymphocytic leukemia.

PURPOSE Aberrant methylation of promoter-associated CpG islands is an epigenetic oncogenic mechanism. The objective of this study was to define the methylation characteristics of patients with acute lymphocytic leukemia (ALL). EXPERIMENTAL DESIGN Using bisulfite-PCR followed by restriction enzyme digestion (COBRA), we have analyzed the methylation status of 10 promoter-associated CpG islands in 80 untreated adult patients with ALL. RESULTS Mean methylation density of MDR1, THBS2, MYF3, ER, p15, THBS1, CD10, C-ABL, and p16 was 24.5%, 20.8%, 17.6%, 16.1%, 11.3%, 8.9%, 4.5%, 3.7%, and 1.3% respectively. p73 was methylated in 17 of 80 cases (21.2%). A total of 86.2% of the cases had methylation of at least one gene, and 42.5% of the cases had methylation of three or more genes. MDR1 methylation was inversely correlated with age (P = 0.01). CD10 methylation inversely correlated with CD10 expression (P = 0.0001). Methylation of MDR1 and THBS1 was inversely associated with the presence of the Philadelphia chromosome, whereas C-ABL methylation correlated with the presence of the p210 variant of the Philadelphia chromosome. In univariate analysis, methylation of THBS1 was associated with a favorable outcome (P = 0.02), whereas methylation of p73, p15, and C-ABL was associated with a trend toward worse prognosis. CONCLUSIONS Aberrant DNA methylation of promoter-associated CpG islands is very common in adult ALL and potentially defines subgroups with distinct clinical and biological characteristics.