Miracle-dz/UniFAR-FTUs huggingface dataset:
How Good Are Embodied And Disembodied Idea Flows In Bridging Income Gaps And Idea Gaps

This paper empirically evaluates the relative importance of embodied versus disembodied idea flows in explaining income gaps and idea gaps. Trade is used as a measure of embodied idea flows and telephone call traffic a measure of disembodied flows. Since both trade and telephone traffic may be endogenous, this paper uses the geographic, linguistic, and colonial components of trade and telephone traffic as instruments to identify their effects on income and total factor productivity (TFP). The results provide little support for the embodied object models when both trade and telephone traffic are included in the regressions. Telephone traffic has a quantitatively much large effect on income per worker and TFP than trade.
Constrained ECG compression using best adapted wavelet packet bases

The main goal of any electrocardiogram (ECG) compression algorithm is to reduce the bit rate while keeping the signal distortion at a clinically acceptable level. Percentage root mean square difference (PRD), the commonly used figure of merit, does not directly reveal whether the clinically significant ECG waveform information is preserved or not. We present the results of a study of ECG compression using an upper bound on the PRD. This bound is based on the initial performance of the algorithm and could be specified by the clinician after correlating the quality of the compressed versions of the ECG and the resulting PRD.
Comparison of CP and IP Techniques for Data Transfer Planning

Planning of data transfers becomes an interesting problem when bandwidth of a requested traffic is comparable to a capacity of available networks. This type of problem is solved within CoUniverse framework supporting interactive high-quality media distribution for collaborative environments.The CoUniverse contains two alternative planning modules which comparison is the subject of this work. While a constraint programming solver was improved over the years, a new integer programming solver has been introduced recently. Current intent is a parallel development of both solvers and their improvement based on experiences with both methodologies.
Environmental Factors Shaping the Community Structure of Ammonia-Oxidizing Bacteria and Archaea in Sugarcane Field Soil

The effects of environmental factors such as pH and nutrient content on the ecology of ammonia-oxidizing bacteria (AOB) and archaea (AOA) in soil has been extensively studied using experimental fields. However, how these environmental factors intricately influence the community structure of AOB and AOA in soil from farmers’ fields is unclear. In the present study, the abundance and diversity of AOB and AOA in soils collected from farmers’ sugarcane fields were investigated using quantitative PCR and barcoded pyrosequencing targeting the ammonia monooxygenase alpha subunit (amoA) gene. The abundances of AOB and AOA amoA genes were estimated to be in the range of 1.8 × 105–9.2 × 106 and 1.7 × 106–5.3 × 107 gene copies g dry soil−1, respectively. The abundance of both AOB and AOA positively correlated with the potential nitrification rate. The dominant sequence reads of AOB and AOA were placed in Nitrosospira-related and Nitrososphaera-related clusters in all soils, respectively, which varied at the level of their sub-clusters in each soil. The relationship between these ammonia-oxidizing community structures and soil pH was shown to be significant by the Mantel test. The relative abundances of the OTU1 of Nitrosospira cluster 3 and Nitrososphaera subcluster 7.1 negatively correlated with soil pH. These results indicated that soil pH was the most important factor shaping the AOB and AOA community structures, and that certain subclusters of AOB and AOA adapted to and dominated the acidic soil of agricultural sugarcane fields.
SEQUENTIAL KERNEL ESTIMATION OF A MULTIVARIATE REGRESSION FUNCTION

This paper presents a sequential estimation procedure for an unknown multivariate regression function. Observed regressors and noises of the model are supposed to be dependent and form sequences of dependent vectors and numbers respectively. Two types of estimators are considered. Both estimators are constructed on the basis of Nadaraya‐Watson kernel estimators. First, sequential estimators with given bias and mean square error are defined. According to the sequential approach the duration of observations is a special stopping time. Then on the basis of these estimators, truncated sequential estimators of a regression function are constructed on a time interval of a fixed length. At the same time the variance of these estimators is also bounded by a non-asymptotic bound. Together with finite-sample, asymptotic properties of the presented estimators are investigated. It is shown, in particular, that by the appropriately chosen bandwidths both estimators have optimal (as compared to the case of independent data) rates of convergence.
What Behaviors Are Important for Successful Weight Maintenance?

Purpose. To examine behavioral factors related to successful weight maintenance. Methods. Subjects were 90 middle-aged participants who attended a weight loss program and were followed for one year. The subjects were classified into either successful weight maintainers (maintained a weight loss of 5% or more from their initial weight for one year) (SWM) or unsuccessful weight maintainers (USWM), and weight control practice, stress, obstacles, support, and self-efficacy during the program and follow-up period were compared. Results. SWM had mean loss of 12% from their initial weight during the program. They showed a greater improvement in their regularity of eating, walked more, and felt less stress regarding their increased physical activity than the USWM. During the follow-up period, significantly more SWM participants had self-efficacy (for measuring weight, practicing dietary objective, and assessing the practice and keeping records), actually kept records and measured weight more than the USWM participants. In contrast, more USWM participants felt stress about measuring weight. Conclusion. In addition to a substantial initial weight loss due to an increased amount of physical activity, having a higher self-efficacy and consistently keeping records of one's activities, as well as regularly weighing themselves, may be important for successful weight maintenance.
Quantum Interaction Approach in Cognition, Artificial Intelligence and Robotics

The mathematical formalism of quantum mechanics has been successfully employed in the last years to model situations in which the use of classical structures gives rise to problematical situations, and where typically quantum effects, such as 'contextuality' and 'entanglement', have been recognized. This 'Quantum Interaction Approach' is briefly reviewed in this paper focusing, in particular, on the quantum models that have been elaborated to describe how concepts combine in cognitive science, and on the ensuing identification of a quantum structure in human thought. We point out that these results provide interesting insights toward the development of a unified theory for meaning and knowledge formalization and representation. Then, we analyze the technological aspects and implications of our approach, and a particular attention is devoted to the connections with symbolic artificial intelligence, quantum computation and robotics.
3D CV Descriptor on Parallel Heterogeneous Platforms

Embedded three-dimensional (3D) Computer Vision (CV) is considered a technology enabler for future consumer applications, attracting a wide interest in academia and industry. However, 3D CV processing is a computation-intensive task. Its high computational cost is directly related to the processing of 3D point clouds, with the 3D descriptor computation representing one of the main bottlenecks. Understanding the main computational challenges of 3D CV applications, as well as the key characteristics, enabling features, and limitations of current computing platforms, is clearly strategic to identify the directions of evolution for future embedded processing systems targeting 3D CV. In this work, an innovative and complex 3D descriptor (called SHOT) has been ported on a high-end and an embedded computing platform. The high-end system is composed by a high-performance Intel CPU coupled with a Nvidia GPU. The embedded platform is, instead, composed by an ARM-based processor, coupled with the STHORM accelerator. STHORM is a many-core low-power accelerator developed by ST Microelectronics, featuring up to 64 computational units. The SHOT descriptor has been parallelized using the OpenCL programming model for both platforms. Finally, we have performed an in-depth performance comparison and analysis between general-purpose processors and accelerators in both high-end and embedded domains, discussing and highlighting the main differences in the Hardware/Software (HW/SW) design methodologies and approaches between high-end and embedded systems targeting 3D CV applications.
Defensome against Toxic Diatom Aldehydes in the Sea Urchin Paracentrotus lividus

Many diatom species produce polyunsaturated aldehydes, such as decadienal, which compromise embryonic and larval development in benthic organisms. Here newly fertilized Paracentrotus lividus sea urchins were exposed to low concentration of decadienal and the expression levels of sixteen genes, implicated in a broad range of functional responses, were followed by Real Time qPCR in order to identify potential decadienal targets. We show that at low decadienal concentrations the sea urchin Paracentrotus lividus places in motion different classes of genes to defend itself against this toxic aldehyde, activating hsp60 and two proteases, hat and BP10, at the blastula stage and hsp56 and several other genes (14-3-3ε, p38 MAPK, MTase, and GS) at the prism stage. At this latter stage all genes involved in skeletogenesis (Nec, uni, SM50 and SM30) were also down-expressed, following developmental abnormalities that mainly affected skeleton morphogenesis. Moreover, sea urchin embryos treated with increasing concentrations of decadienal revealed a dose-dependent response of activated target genes. Finally, we suggest that this orchestrated defense system against decadienal represents part of the chemical defensome of P. lividus affording protection from environmental toxicants.
Low expression of leptin and its association with breast cancer: A transcriptomic study

The incidence of breast cancer is alarmingly increasing worldwide and also among Saudi women. Obesity is linked with an increased cancer risk and studies have also revealed that leptin may be involved in breast tumorigenesis particularly among obese women. Numerous transcriptomic studies have been carried out worldwide; however, molecular studies among breast cancer patients of diverse ethnic groups from the Arabian Peninsula are scarce. In the present study, whole transcriptome analysis of 45 surgically resected breast tumors from Saudi Arabian female patients was carried out. Expression data were analyzed, and molecular networks and canonical pathways were identified. We identified 1,159 differentially expressed genes using p-value with a false discovery rate <0.05 and a fold-change >2 as a cut-off. Using ingenuity pathway analysis tool, we identified many canonical pathways that were implicated in breast cancer for the first time. Notably, along with other lipid metabolism molecules, leptin (LEP) was one of the most downregulated genes (fold cut-off, −7.03) with significant differences between the breast cancer and the control groups (p<0.0001) and was further confirmed in all the samples using qPCR. Transcriptomic profiling of breast cancer from a Saudi female population revealed downregulation of LEP. Molecular pathway analysis demonstrated the role of LEP and other associated molecules of the lipid metabolism pathway. Involvement of leptin and lipid metabolism in breast cancer was highlighted. The majority of cases presented were of late stage, stressing the need to educate individuals concerning early diagnostic testing and the life-style risk factors for breast cancer such as unhealthy diet and obesity.
Proapoptotic and Antiproliferative Effects of Thymus caramanicus on Human Breast Cancer Cell Line (MCF-7) and Its Interaction with Anticancer Drug Vincristine

Thymus caramanicus Jalas is one of the species of thymus that grows in the wild in different regions of Iran. Traditionally, leaves of this plant are used in the treatment of diabetes, arthritis, and cancerous situation. Therefore, the present study was designed to investigate the selective cytotoxic and antiproliferative properties of Thymus caramanicus extract (TCE). MCF-7 human breast cancer cells were used in this study. Cytotoxicity of the extract was determined using MTT and neutral red assays. Biochemical markers of apoptosis (caspase 3, Bax, and Bcl-2) and cell proliferation (cyclin D1) were evaluated by immunoblotting. Vincristine was used as anticancer control drug in extract combination therapy. The data showed that incubation of cells with TCE (200 and 250 μg/mL) significantly increased cell damage, activated caspase 3 and Bax/Bcl2 ratio. In addition, cyclin D1 was significantly decreased in TCE-treated cells. Furthermore, concomitant treatment of cells with extract and anticancer drug produced a significant cytotoxic effect as compared to extract or drugs alone. In conclusion, thymus extract has a potential proapoptotic/antiproliferative property against human breast cancer cells and its combination with chemotherapeutic agent vincristine may induce cell death effectively and be a potent modality to treat this type of cancer.
Prevalence, Semiology, and Risk Factors of Epilepsy in Alzheimer's Disease: An Ambulatory EEG Study.

BACKGROUND Alzheimer's disease (AD) is the primary cause of cognitive decline. A growing body of evidence suggests that AD patients have a higher risk to develop epileptic seizures; however, results are contradictory due to different methodological approaches of previous studies. OBJECTIVE We aimed to identify the prevalence, semiology, and risk factors of epilepsy in AD using long-term EEG. METHODS We selected forty-two AD patients and examined them using 24-hour ambulatory EEG. Neurological and epileptological data were collected with retro- and prospective methods. We analyzed the semiology of the identified seizures and the possible risk factors using logistic regression analysis. RESULTS We identified seizures confirmed by EEG in 24%. The majority of the seizures were aware focal (72%) without any motor activity (55%). We found epileptiform discharges without seizures in 28%. Patients with seizures and only with epileptic EEG activity showed similar clinical and demographical features. Higher education (OR:1.8) and lower Addenbrooke Examination Score (OR: 0.9) were identified as risk factors of epilepsy. Increase of 0.1 point in the Verbal-Language/Orientation-Memory ratio (VLOM) was associated with higher epilepsy risk as well (OR:2.9). CONCLUSION Epilepsy is a frequent comorbidity of AD. Since most of the seizures are aware non-motor focal seizures, sensitive EEG techniques are required for precise diagnosis of epilepsy. Long-term ambulatory EEG is a safe and well-tolerated option. Epileptiform EEG in AD signals the presence of concomitant epilepsy. Clinicians have to pay attention to comorbid epilepsy in dementia patients with high education, with high VLOM ratio and severe stage.
Hybrid Model of Least Squares Handover Algorithms in Wireless Networks

An adaptive handover algorithm for wireless communication systems is addressed in this paper. Moving from the Generalized Extended Least Square handover algorithm proposed in N. Benvenuto et al. (2002), we model the handover mechanism as a hybrid system, and we include it in a dynamic optimization problem which is solved through the use of a trellis diagram. The objective function takes into account the parameters that influence the handover mechanism. The optimal solution of the program allows to evaluate performance of the handover in terms of the probability of handover and probability of outage.
Insights from Neurodevelopmental Disorders

Twin and family studies have demonstrated that most cognitive traits are moderately to highly heritable. Neurodevelopmental disorders such as dyslexia, autism, and specific language impairment (SLI) also show strong genetic influence. Nevertheless, it has proved difficult for researchers to identify genes that would explain substantial amounts of variance in cognitive traits or disorders. Although this observation may seem paradoxical, it fits with a multifactorial model of how complex human traits are influencedbynumerousgenesthatinteractwithoneanother,andwiththeenvironment, to produce a specific phenotype. Such a model can also explain why genetic influences on cognition have not vanished in the course of human evolution. Recent linkage and association studies of SLI and dyslexia are reviewed to illustrate these points. The role of nonheritable genetic mutations (sporadic copy number variants) in causing autism is also discussed. Finally, research on phenotypic correlates of allelic variation in the genes ASPM and microcephalin is considered; initial interest in these as genes for brain size or intelligence has been dampened by a failure to find phenotypic differences in people with different versions of these genes. There is a current vogue for investigators to include measures of allelic variants in studies of cognition and cognitive disorders. It is important to be aware that the effect sizes associated with these variants are typically small and hard to detect without extremely large sample sizes.
Sudden stratospheric warmings seen in MINOS deep underground muon data

The rate of high energy cosmic ray muons as measured underground is shown to be strongly correlated with upper‐air temperatures during short‐term atmospheric (10‐day) events. The effects are seen by correlating data from the MINOS underground detector and temperatures from the European Centre for Medium Range Weather Forecasts during the winter periods from 2003–2007. This effect provides an independent technique for the measurement of meteorological conditions and presents a unique opportunity to measure both short and long‐term changes in this important part of the atmosphere.
Adaptation Based on Generalized Discrepancy

We present a new algorithm for domain adaptation improving upon a discrepancy minimization algorithm, (DM), previously shown to outperform a number of algorithms for this problem. Unlike many previously proposed solutions for domain adaptation, our algorithm does not consist of a fixed reweighting of the losses over the training sample. Instead, the reweighting depends on the hypothesis sought. The algorithm is derived from a less conservative notion of discrepancy than the DM algorithm called generalized discrepancy. We present a detailed description of our algorithm and show that it can be formulated as a convex optimization problem. We also give a detailed theoretical analysis of its learning guarantees which helps us select its parameters. Finally, we report the results of experiments demonstrating that it improves upon discrepancy minimization in several tasks.
Beyond average: potential for measurement of short telomeres

The length of telomeres, and in particular the abundance of short telomeres, has been proposed as a biomarker of aging and of general health status. A wide variety of studies show the association of short telomeres with age related pathologies and cancer, as well as with lifespan and mortality. These facts highlight the importance of measuring telomere length in human populations and by using reliable methods to uncover the association between telomere length and human disease. This review discusses the advantages and drawbacks of current telomere length measurement methods. Most of these methods provide mean telomere length values per cell or per sample and very few of them are able to measure the abundance of short telomeres, which are the ones indicative of telomere dysfunction. The information provided by each method and their suitability for different studies is discussed here.
The use of phrase-level prosodic information in lexical segmentation: evidence from word-spotting experiments in Korean.

This study investigated the role of phrase-level prosodic boundary information in word segmentation in Korean with two word-spotting experiments. In experiment 1, it was found that intonational cues alone helped listeners with lexical segmentation. Listeners paid more attention to local intonational cues (.H#L.) across the prosodic boundary than the intonational information within a prosodic phrase. The results imply that intonation patterns with high frequency are used, though not exclusively, in lexical segmentation. In experiment 2, final lengthening was added to see how multiple prosodic cues influence lexical segmentation. The results showed that listeners did not necessarily benefit from the presence of both intonational and final lengthening cues: Their performance was improved only when intonational information contained infrequent tonal patterns for boundary marking, showing only partially cumulative effects of prosodic cues. When the intonational information was optimal (frequent) for boundary marking, however, poorer performance was observed with final lengthening. This is arguably because the phrase-initial segmental allophonic cues for the accentual phrase were not matched with the prosodic cues for the intonational phrase. It is proposed that the asymmetrical use of multiple cues was due to interaction between prosodic and segmental information that are computed in parallel in lexical segmentation.
Prospects for dark energy evolution: a frequentist multi-probe approach

A major quest in cosmology is to understand the nature of dark energy. It is now well known that the use of several cosmological probes is required to break the underlying degeneracies on cosmological parameters. In this paper, we present a method based on a frequentist approach that combines probes without any prior constraints. As one application, the current supernovae type Ia and cosmic microwave background data are analyzed with an evolving dark energy component, and our results are first compared to other analyses. We emphasize the consequences of implementing the dark energy perturbations for an equation of state that varies with time. We then simulate the expectations of different future projects. The constraints from weak lensing surveys on the measurement of dark energy evolution are combined with the measurements from the cosmic microwave background and type Ia supernovae. We present the impacts for mid-term and long-term surveys and confirm that the combination with weak lensing is very powerful in breaking parameter degeneracies. A second generation of experiments is, however, required to achieve a 0.1 error on the parameters describing the evolution of dark energy.