Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation-based modeling for advanced targeted marketing

Fingerhut Business Intelligence (BI) has a long and successful history of building statistical models to predict consumer behavior. The models constructed are typically segmentation-based models in which the target audience is split into subpopulations (i.e., customer segments) and individually tailored statistical models are then developed for each segment. Such models are commonly employed in the direct-mail industry; however, segmentation is often performed on an ad-hoc basis without directly considering how segmentation affects the accuracy of the resulting segment models. Fingerhut BI approached IBM Research with the problem of how to build segmentation-based models more effectively so as to maximize predictive accuracy. The IBM Advanced Targeted Marketing-Single EventsTM (IBM ATM-SETM) solution is the result of IBM Research and Fingerhut BI directing their efforts jointly towards solving this problem. This paper presents an evaluation of ATM-SE's modeling capabilities using data from Fingerhut's catalog mailings.
A comparative study of constrained and unconstrained approaches for segmentation of speech signal

In this work, we compare different approaches for speech segmentation, of which some are constrained and the remaining are unconstrained by phone transcript. A high accuracy speech segmentation can be obtained by approaches constrained by phone transcript such as HMM forced-alignment when exact phone transcript is known. But such approaches have to adjust with canonical phone transcript ,a sexact phone transcript is tough to obtain. Our experiments on TIMIT corpus demonstrate that ANN and HMM phone-loop based unconstrained approaches, perform better than HMM forced-alignment based approach constrained by canonical phone transcript. Finally a detailed error analysis of these approaches is reported. Index Terms: HMM, Group-Delay, ANN, Speech Segmentation.
A Compositional Method for Verifying Software Transactional Memory Implementations

We present a compositional method for verifying software transactional memory (STM) implementations and its application to the Bartok STM. The method consists of two parts. The first is a generic, manual proof of serializability at the algorithm level for lazy-invalidate, write-in-place STM’s. The proof relies on three properties of program executions that the STM must ensure. The second part consists of proving that the Bartok STM implementation guarantees these properties and thus refines the algorithmlevel description. We present a novel technique for expressing the properties required of the STM implementation as assertions in sequential programs that model certain interference scenarios. This is a key benefit, as it allows these properties to be checked using sequential program verification tools. Using our method, the Spec# language and the Boogie verification tool, we were able to detect an omission in the published pseudo-code for the STM implementation and “challenge bugs” extracted from earlier versions of the STM. We were also able to prove correct the most recent version of the implementation.
Analysis of a Genetic Isolate: The Case of Carloforte (Italy)

Abstract We reviewed data collected during several studies concerning the genetic isolate of Carloforte (Sardinia, Italy) and analyzed new data on Y-chromosome markers. Carloforte is also a language island, where people still speak Tabarchino, an archaic form of Ligurian dialect. Demographic data indicate that, in the early years of its history, the Carloforte population was characterized by a high degree of endogamy and consanguinity rates that started to decrease around 1850, when marriages with Sardinian people began to occur more frequently. Cultural factors, mainly language, account for the high endogamy. Genetic data from classical markers, mtDNA, and Y-chromosome markers confirmed the strong isolation of the Carloforte population, which appears significantly different from the neighboring population of Sardinia. Analysis of mtDNA emphasizes the crucial aspect of sampling strategy—two different samplings of the same population (one based on founder surnames; the other one based on grandparents' criterion) gave different results. Founder surnames sampling is not affected by recent events, and therefore it better describes the ancestral population, whereas, grandparents' criterion sampling gives a picture of the present population, shaped by more recent events, such as migration and gene flow. This review further supports the notion that a comprehensive approach, including a detailed knowledge of the history of the population and the collection of different samplings, is essential in anthropology for reconstructing past and recent events that contributed to establishing the present genetic structure of the population. Likewise, it is essential in medical genetics to identify genes involved in complex diseases. An ideal scenario is offered by a genetic isolate with a recent, and well-documented, history, such as Carloforte, that can be a paradigm for this type of investigation.
Cancer Risk in Patients With Inflammatory Systemic Autoimmune Rheumatic Diseases

AbstractThe aim of this study was to determine whether inflammation is related to cancer development, and whether the incidence of cancer is increased and occurs in a site-specific manner in patients with systemic autoimmune rheumatic diseases (SARDs). This study included a nationwide dynamic cohort of patients with various newly diagnosed SARDs from 1997 to 2010 with follow-up until 2012.This study included 75,123 patients with SARDs. During 562,870 person-years of follow-up, 2844 patients developed cancer. Between 1997 and 2010, the highest number of newly diagnosed SARDs cases were rheumatoid arthritis (n = 35,182), followed by systemic lupus erythematosus (SLE, n = 15,623), Sjögren syndrome (n = 11,998), Kawasaki disease (n = 3469), inflammatory bowel disease (n = 2853), scleroderma (n = 1814), Behçet disease (n = 1620), dermatomyositis (n = 1119), polymyositis (n = 811), and vasculitis other than Kawasaki disease (n = 644). A significant standardized incidence ratio (SIR) of overall cancer was observed for patients with SLE (1.41; 95% confidence interval [CI], 1.28–1.56), Sjögren syndrome (1.19; 95% CI, 1.08–1.30), scleroderma (1.27; 95% CI, 1.02–1.59), dermatomyositis (4.79; 95% CI, 4.01–5.73), polymyositis (1.47; 95% CI, 1.05–2.06), vasculitis excluding Kawasaki disease (1.75; 95% CI, 1.20–2.55), and Kawasaki disease (2.88; 95% CI, 1.60–5.20). Overall, patients with most SARDs had a significantly higher risk of inflammation-associated site-specific cancers and hematologic malignancies.This study confirms that autoimmunity is associated with site-specific and hematological malignancies and provides clinical evidence of an association between inflammation and subsequent site-specific cancer development. These findings support the importance of inflammation in site-specific organ system carcinogenesis.
Binary-Coded Monitoring of a Behavioral Sequence by Cells in the Pre-Supplementary Motor Area

To regulate the temporal structure of a series of behavioral sequences involving multiple actions, it is essential to monitor the progress of the entire behavioral process. To identify the involvement of three cortical motor areas in monitoring behavioral sequences, we examined neuronal activity while monkeys sequentially performed a series of motor tasks in accordance with a predetermined behavioral schedule that included a numerical structure. We found that neurons in the pre-supplementary motor area exhibited activity that appeared to monitor the performance of the behavioral trials in a binary-coded manner. One-half of the activity represented odd-numbered trials within a behavioral sequence, whereas the other one-half represented even-numbered trials. Such neuronal activity, resembling the operation of binary counting elements widely used for constructing artificial computing devices, was rare in the supplementary motor area or in the primary motor cortex.
Sparse cooperative Q-learning

Learning in multiagent systems suffers from the fact that both the state and the action space scale exponentially with the number of agents. In this paper we are interested in using Q-learning to learn the coordinated actions of a group of cooperative agents, using a sparse representation of the joint state-action space of the agents. We first examine a compact representation in which the agents need to explicitly coordinate their actions only in a predefined set of states. Next, we use a coordination-graph approach in which we represent the Q-values by value rules that specify the coordination dependencies of the agents at particular states. We show how Q-learning can be efficiently applied to learn a coordinated policy for the agents in the above framework. We demonstrate the proposed method on the predator-prey domain, and we compare it with other related multiagent Q-learning methods.
Gamifying an online approach for promoting game development Learning and contest: An experience report

A big challenge of virtual learning environments is to guarantee engagement and keep students motivated to use it. In this context, gamification techniques are being explored to adapt game elements to teaching and Learning in Virtual Environments (VLE) with the objective of make the VLEs more engaging and attractive for students. The gamification engages, encourages and promotes greater interaction between students, enabling growth of learning. In this context, this article presents the gamification results of a virtual learning environment for online programming teaching and competition of digital games. At the end, results showed that the gamification achieves greater engagement of users in relation to the higher frequency of use of the VLE, larger views of video lessons and a greater number of completed challenges, bringing some other advantages such as the environment that became more competitive, fun and friendly for students.
Glypican‐3: a marker and a therapeutic target in hepatocellular carcinoma

Glypican‐3 (GPC3) is a member of the glypican family. Glypicans are proteoglycans that are attached to the cell surface by a glycosyl‐phosphatidylinositol anchor. They regulate the signaling activity of several growth factors, including Wnts. This regulation is based on the ability of glypicans to stimulate or inhibit the interaction of these growth factors with their respective signaling receptors. It has been clearly established that whereas GPC3 is expressed by most hepatocellular carcinomas (HCCs), this glypican is not detected in normal and cirrhotic liver, or in benign hepatic lesions. Consequently, immunostaining of liver biopsies for GPC3 is currently being used by clinical pathologists to confirm HCC diagnosis when the malignant nature of the lesion is difficult to establish. In addition to being a marker of HCC, GPC3 plays a role in the progression of the disease. GPC3 promotes the growth of HCC by stimulating canonical Wnt signaling. It has been proposed that this stimulation is based on the ability of GPC3 to increase the binding of Wnt to its signaling receptor, Frizzled. Two therapeutic approaches for HCC that target GPC3 are currently being tested in phase II clinical trials. One of them is based on the use of a humanized GPC3 monoclonal antibody that inhibits the in vivo growth of HCC xenografts by inducing antibody‐dependent cellular cytotoxicity. The second approach employs a vaccine that consists of two GPC3‐derived peptides that induce cytotoxic T lymphocytes against these peptides. Targeting of GPC3 might offer a new tool for the treatment of HCC.
Managing travel demand: Location recommendation for system efficiency based on mobile phone data

Growth in leisure travel has become increasingly significant economically, socially, and environmentally. However, flexible but uncoordinated travel behaviors exacerbate traffic congestion. Mobile phone records not only reveal human mobility patterns, but also enable us to manage travel demand for system efficiency. In this paper, we propose a location recommendation system that infers personal preferences while accounting for constraints imposed by road capacity in order to manage travel demand. We first infer unobserved preferences using a machine learning technique from phone records. We then formulate an optimization method to improve system efficiency. Coupling mobile phone data with traffic counts and road network infrastructures collected in Andorra, this study shows that uncoordinated travel behaviors lead to longer average travel delay, implying the opportunities in managing travel demand by collective decisions. The interplay between congestion relief and overall satisfied location preferences observed in extensive simulations indicate that moderate sacrifices of individual utility lead to significant travel time savings. Specifically, the results show that under full compliance rate, travel delay fell by 52% at a cost of 31% less satisfaction. Under 60% compliance rate, 41% travel delay is saved with a 17% reduction in satisfaction. This paper highlights the effectiveness of the synergy among collective behaviors in increasing system efficiency.
Search of Web Service Based on Community

With the rapid growth of web services, how to efficiently locate the desired web services has become a very important problem. We observe that under different contexts the descriptions of services vary in their level of semantic ambiguity. So the traditional keyword search is insufficient in the very small text fragments in web services, and semantic of the web services is not exploited. We describe the algorithms based on the complex networks for web services. Firstly with the communities discovered from the complex networks, services sharing the similar context could be clustered into same groups. Then by targeting the users' queries to the relevant group, utilize similarity metric in this group to search services. The experiment shows the approach can improve the accuracy of service search.
Mechanical ventilation in trauma

Purpose of review The purpose of this review is to evaluate new concepts in mechanical ventilation in trauma. We begin with the keystone of physiology prior to embarking on a discussion of several new modes of mechanical ventilation. We will discuss the use of noninvasive ventilation as a mode to prevent intubation and then go on to airway pressure release ventilation, high-frequency oscillatory ventilation, and computer-based, closed loop ventilation. Recent findings The importance of preventing further injury in mechanical ventilation lies at the heart of the introduction of several new strategies of mechanical ventilation. New modes of ventilation have been developed to provide lung recruitment and alveolar stabilization at the lowest possible pressure. Summary The old modes of continuous positive airway pressure and bilevel positive airway pressure have been actively introduced in clinical practice in the case of trauma patients. Used with proper pain management protocols, there has been a decrease in the incidence of intubation in blunt thoracic trauma. Airway pressure release ventilation has been gaining a role in the management of thoracic injury and may lead to less incidence of physiologic trauma to mechanically ventilated patients. High-frequency oscillatory ventilation has been shown to be effective in patient care by its ability to open and recruit the lung in trauma patients and in those with acute respiratory distress syndrome but it may not have a role in patients with inhalational injury. Closed loop ventilation is a technology that may better control major pulmonary parameters and lead to more rapid titration from the ventilator to spontaneous breathing.
Truthful Mechanisms for Message Dissemination via Device-to-Device Communications

Device-to-device (D2D) communications are not only featured by high spectral and energy efficiency, but also offer appealing benefits for applications, such as message dissemination, traffic offloading, and coverage expansion. In this paper, we consider a message dissemination scenario where a base station (BS) can direct message requests to be fulfilled by some source devices via D2D communications and thereby save the resource cost. Furthermore, a source device may be subject to a cost budget due to its limited resources. To minimize the overall cost or maximize the BS's cost saving from offloading, it is essential to properly assign the message request(s) for each source and decide the payment to incentivize participation. The request direction is an NP-hard problem, while the payment determination is also nontrivial. The payment should be sufficient to compensate for a source device's resource cost, and meanwhile, incentivize the source to truthfully declare its private cost and budget. Modeling the problem as a reverse auction, we develop both a deterministic mechanism and a randomized mechanism, which are truthful or truthful in expectation, respectively. Both mechanisms are individually rational and subject to a computational complexity lower than that of the well-known Vickrey–Clarke–Groves mechanism or its generalized version. While the deterministic mechanism performs well in an average sense, the randomized mechanism maintains an approximation guarantee for the worst case. Extensive numerical results demonstrate the effectiveness of the proposed mechanisms with various settings in the D2D content distribution scenario.
The Measurement of Learning Style: A Critique of Four Assessment Tools.

ABSTRACT This paper addresses the issue of whether four of the learning styles instruments currently available are of sufficient psychometric quality to warrant their continued use either for research or educational purposes. Four instruments, which purport to measure learning styles, were selected for review. Criteria for selection were based in part on the frequency of references in the professional literature and discussions with several adult educators who have had considerable experience with the assessment of learning styles. The four instruments chosen were the Myers-Briggs Type Indicator, the Kolb Learning Style Inventory, Canfield's Learning Styles Inventory, and Gregorc's Style Delineator. The paper is divided into six sections. Following the first section, which introduces the study, each of the next four sections consists of a detailed critique of the four learning styles instruments selected for review. Each critique follows the same format and includes a description of (1) the practical features of the test, administration, scoring, and other considerations; (2) characteristics of the manual, including how information is reported and what test interpretation information is provided; (3) characteristics of the test including norms; reliability, validity, and its overall quality; and (4) a summary statement that focuses on the reviewer's personal decision regarding the use of the test. The paper closes with a listing of research questions that need to be explored and some suggestions for improving the measurement of learning styles. (KC)
Taqreer: A System for Spatio-temporal Analysis on Microblogs

Motivated by the wide popularity of microblog services (e.g., Twitter and Facebook) along with the sheer sizes of microblogs issued every second, this article introduces Taqreer as a scalable and efficient system for auto-generation of spatio-temporal analysis reports on microblogs. Taqreer is composed of two main modules: The Taghreed query engine, which is a scalable and efficient query processing engine for spatio-temporal keyword queries on microblogs and a Report Generation Tool, which receives the user analytic report request and divides it into a set of queries sent to the Taghreed engine, and a set of analysis tasks executed on top of the returned query answers. As of now, Taqreer is able to produce three analysis report types, namely comparative reports, categorical reports, and image gallery reports. Other report types will be added in the future.
Genome-Wide Association Study of Seed Dormancy and the Genomic Consequences of Improvement Footprints in Rice (Oryza sativa L.)

Seed dormancy is an important agronomic trait affecting grain yield and quality because of pre-harvest germination and is influenced by both environmental and genetic factors. However, our knowledge of the factors controlling seed dormancy remains limited. To better reveal the molecular mechanism underlying this trait, a genome-wide association study was conducted in an indica-only population consisting of 453 accessions genotyped using 5,291 SNPs. Nine known and new significant SNPs were identified on eight chromosomes. These lead SNPs explained 34.9% of the phenotypic variation, and four of them were designed as dCAPS markers in the hope of accelerating molecular breeding. Moreover, a total of 212 candidate genes was predicted and eight candidate genes showed plant tissue-specific expression in expression profile data from different public bioinformatics databases. In particular, LOC_Os03g10110, which had a maize homolog involved in embryo development, was identified as a candidate regulator for further biological function investigations. Additionally, a polymorphism information content ratio method was used to screen improvement footprints and 27 selective sweeps were identified, most of which harbored domestication-related genes. Further studies suggested that three significant SNPs were adjacent to the candidate selection signals, supporting the accuracy of our genome-wide association study (GWAS) results. These findings show that genome-wide screening for selective sweeps can be used to identify new improvement-related DNA regions, although the phenotypes are unknown. This study enhances our knowledge of the genetic variation in seed dormancy, and the new dormancy-associated SNPs will provide real benefits in molecular breeding.
Cognition and hopelessness in association with subsyndromal orthostatic hypotension.

BACKGROUND The move from lying to standing is typically associated with a variety of physiological and neurohumoral changes, most especially a slight increase in systolic blood pressure (SBP). Decreased efficacy of the various mechanisms that control orthostatic blood pressure (BP) regulation may result in lightheadedness, dizziness, syncope, and cerebral hypoperfusion. The lack of effective orthostatic BP regulation is a symptom for various problems, including fatigue, depression, anxiety, and reduced attention. METHODS This study examined men and women (N = 74) who were aged 30-75 years and asymptomatic for clinical orthostatic hypotension. RESULTS Relatively poor BP regulation in response to orthostasis was associated with decreased verbal memory, decreased concentration, and higher hopelessness scores. CONCLUSIONS Individuals who exhibited less effective SBP regulation even to a subsyndromal degree in response to an orthostatic challenge may be at increased risk for cognitive and affective problems. The relationship between orthostatic BP regulation is best described as curvilinear.