Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeted advertising using BLE beacon

Although cameras are commonly used to achieve customer's attributes in the field of advertising, improving the precision of these consumer features just by imagery has been a great challenge. This paper proposes a new targeted advertising method experimentally accommodated to digital signage systems by using Bluetooth Low Energy (BLE) beacons. The paper provides a design of this new advertising method implemented on an iPhone and Raspberry Pi 3, along with the experimental evaluations of the acquired attributes and psychological resistance of the targeted advertising method.
Fitting the data from embryo implantation prediction: Learning from label proportions

Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for embryo selection. In this study, a dataset of 330 consecutive cycles (and associated embryos) carried out by the Unit of Assisted Reproduction of the Hospital Donostia (Spain) throughout 18 months has been analyzed. The problem of the embryo selection has been modeled by a novel weakly supervised paradigm, learning from label proportions, which considers all the available data, including embryos whose fate cannot be certainly established. Furthermore, all the collected features, describing cycles and embryos, have been considered in a multi-variate data analysis. Our integral solution has been successfully tested. Experimental results show that the proposed technique consistently outperforms an equivalent approach based on standard supervised classification. Embryos in this study were selected for transference according to the criteria of the Spanish Association for Reproduction Biology Studies. Obtained classification models outperform these criteria, specifically reordering medium-quality embryos.
Efficacy and safety of flexibly dosed brexpiprazole for the adjunctive treatment of major depressive disorder: a randomized, active-referenced, placebo-controlled study

Abstract Objective: To assess the efficacy, safety, and tolerability of brexpiprazole as adjunctive treatment in adults with major depressive disorder (MDD) and an inadequate response to prior antidepressant treatment (ADT). Methods: Patients with a current major depressive episode after prior treatment with 1−3 ADTs entered an 8- or 10-week prospective treatment phase in which they received double-blind placebo adjunct to open-label ADT. Inadequate responders were randomized (2:2:1) to brexpiprazole 2−3 mg/day, placebo, or quetiapine extended-release (XR) 150−300 mg/day, adjunct to the same ADT, for 6 weeks. The primary efficacy endpoint was the change from baseline (randomization) to week 6 in Montgomery−Åsberg Depression Rating Scale (MADRS) total score. The key secondary efficacy endpoint was the change in Sheehan Disability Scale (SDS) mean score. Results: Adjunctive brexpiprazole showed a greater improvement in MADRS total score than adjunctive placebo (least squares mean difference [95% confidence interval] = −1.48 [−2.56, −0.39]; p = .0078), whereas adjunctive quetiapine XR did not separate from placebo (−0.30 [−1.63, 1.04]; p = .66). Adjunctive brexpiprazole failed to separate from placebo on the SDS mean score (−0.23 [−0.52, 0.07]; p = .13), but did improve functioning on two of the three SDS items (family life and social life). The most frequent treatment-emergent adverse events in patients receiving brexpiprazole were akathisia (6.1%), somnolence (5.6%), and headache (5.6%). Conclusions: Adjunctive brexpiprazole 2−3 mg/day improved symptoms of depression compared with adjunctive placebo in patients with MDD and an inadequate response to ADTs, and was well tolerated with no unexpected side effects.
Ancestral Reconstruction

Ancestral reconstruction is the extrapolation back in time from measured characteristics of individuals (or populations) to their common ancestors. It is an important application of phylogenetics, the reconstruction and study of the evolutionary relationships among individuals, populations, or species to their ancestors. In the context of biology, ancestral reconstruction can be used to recover different kinds of ancestral character states, including the genetic sequence (ancestral sequence reconstruction), the amino acid sequence of a protein, the composition of a genome (e.g., gene order), a measurable characteristic of an organism (phenotype), and the geographic range of an ancestral population or species (ancestral range reconstruction). Nonbiological applications include the reconstruction of the vocabulary or phonemes of ancient languages [1] and cultural characteristics of ancient societies such as oral traditions [2] or marriage practices [3]. Ancestral reconstruction relies on a sufficiently realistic model of evolution to accurately recover ancestral states. No matter how well the model approximates the actual evolutionary history, however, one's ability to accurately reconstruct an ancestor deteriorates with increasing evolutionary time between that ancestor and its observed descendants. Additionally, more realistic models of evolution are inevitably more complex and difficult to calculate. Progress in the field of ancestral reconstruction has relied heavily on the exponential growth of computing power and the concomitant development of efficient computational algorithms (e.g., a dynamic programming algorithm for the joint maximum likelihood [ML] reconstruction of ancestral sequences [4]). Methods of ancestral reconstruction are often applied to a given phylogenetic tree that has already been inferred from the same data. While convenient, this approach has the disadvantage that its results are contingent on the accuracy of a single phylogenetic tree. In contrast, some researchers advocate a more computationally intensive Bayesian approach that accounts for uncertainty in tree reconstruction by evaluating ancestral reconstructions over many trees [5].
A Fast Non-Smooth Nonnegative Matrix Factorization for Learning Sparse Representation

Nonnegative matrix factorization (NMF) is a hot topic in machine learning and data processing. Recently, a constrained version, non-smooth NMF (NsNMF), shows a great potential in learning meaningful sparse representation of the observed data. However, it suffers from a slow linear convergence rate, discouraging its applications to large-scale data representation. In this paper, a fast NsNMF (FNsNMF) algorithm is proposed to speed up NsNMF. In the proposed method, it first shows that the cost function of the derived sub-problem is convex and the corresponding gradient is Lipschitz continuous. Then, the optimization to this function is replaced by solving a proximal function, which is designed based on the Lipschitz constant and can be solved through utilizing a constructed fast convergent sequence. Due to the usage of the proximal function and its efficient optimization, our method can achieve a nonlinear convergence rate, much faster than NsNMF. Simulations in both computer generated data and the real-world data show the advantages of our algorithm over the compared methods.
Transformer‐coupled π‐network differential CMOS oscillator circuit topology

This paper reports a novel oscillator circuit topology based on a transformer‐coupled π‐network. As a case study, the proposed oscillator topology has been designed and studied for 60 GHz applications in the frame of the emerging fifth generation wireless communications. The analytical expression of the oscillation frequency is derived and validated through circuit simulations. The root‐locus analysis shows that oscillations occur only at that resonant frequency of the LC tank. Moreover, a closed‐form expression for the quality factor (Q) of the LC tank is derived which shows the enhancement of the equivalent quality factor of the LC tank due to the transformer‐coupling. Last, a phase noise analysis is reported and the analytical expressions of phase noise due to flicker and thermal noise sources are derived and validated by the results obtained through SpectreRF simulations in the Cadence design environment with a 28 nm CMOS process design kit commercially available. Copyright © 2016 John Wiley & Sons, Ltd.
A bioassay for true metabolizable energy in feedingstuffs.

In 12 experiments with S.C. W.L. roosters it was shown that for each of 12 feedingstuffs there was a linear relationship between feed input and the amount of energy voided as excreta. In the 24 h. period, following 21 hr. of starvation, roosters receiving no feed excreted 4.07 kcal. /kg. of body weight. When dextrose was fed the energy voided as excreta did not increase with dextrose input; consequently, the true metabolizable energy (T.M.E.) value of dextrose is its gross energy value. The T.M. E. values were not affected by the level of feed input and appeared to be additive. A simple, rapid assay for T.M. E. was developed, based on gross energy assays of the test feed and of excreta voided over 24 hr. by roosters force fed the test feed and other starved over the same period.
Dried plasma: state of the science and recent developments

The early transfusion of plasma is important to ensure optimal survival of patients with traumatic hemorrhage. In military and remote or austere civilian settings, it may be impossible to move patients to hospital facilities within the first few hours of injury. A dried plasma product with reduced logistical requirements is needed to enable plasma transfusion where medically needed, instead of only where freezers and other equipment are available. First developed in the 1930s, pooled lyophilized plasma was widely used by British and American forces in WWII and the Korean War. Historical dried plasma products solved the logistical problem but were abandoned because of disease transmission. Modern methods to improve blood safety have made it possible to produce safe and effective dried plasma. Dried plasma products are available in France, Germany, South Africa, and a limited number of other countries. However, no product is available in the US. Promising products are in development that employ different methods of drying, pathogen reduction, pooling, packaging, and other approaches. Although challenges exist, the in vitro and in vivo data suggest that these products have great potential to be safe and effective. The history, state of the science, and recent developments in dried plasma are reviewed.
Mining Container Image Repositories for Software Configuration and Beyond

This paper introduces the idea of mining container image repositories for configuration and other deployment information of software systems. Unlike traditional software repositories (e.g., source code repositories and app stores), image repositories encapsulate the entire execution ecosystem for running target software, including its configurations, dependent libraries and components, and OS-level utilities, which contributes to a wealth of data and information. We showcase the opportunities based on concrete software engineering tasks that can benefit from mining image repositories. To facilitate future mining efforts, we summarize the challenges of analyzing image repositories and the approaches that can address these challenges. We hope that this paper will stimulate exciting research agenda of mining this emerging type of software repositories.
Quarantine versus pathogen‐reduced plasma‐coagulation factor content and rotational thromboelastometry coagulation

Different types of fresh‐frozen plasma (FFP) exist, and the concentrations of plasma proteins vary between individuals and blood groups. Furthermore, processing may also influence the content. Quarantine‐stored plasma (qFFP) and plasma that was pathogen‐reduced using blood‐safety (Intercept) technology (piFFP) were analyzed regarding procoagulant and anticoagulant hemostasis proteins, including endogenous thrombin (thrombin‐generation) potential (ETP).
Estimating Risk Attitudes in Conventional and Artefactual Lab Experiments: The Importance of the Underlying Assumptions

Abstract In this paper we assess the importance of sample type in the estimation of risk preferences. We elicit and compare risk preferences from student subjects and subjects drawn from the general population, using the multiple price list method devised by Holt and Laury in their paper Risk Aversion and Incentive Effects (2002). We find evidence suggesting that under rank dependent utility, students exhibit approximately risk neutral preferences while subjects drawn from the general population exhibit risk loving preferences. However, when we assume an incorrect characterization of risk preferences, in particular we adopt the framework of expected utility theory, our estimation results lead to erroneous inferences. In this case, students are on average risk averse, while subjects drawn from the general population exhibit risk neutrality. Our results have implications for economic policy making under uncertainty.
Semi-supervised low-rank representation graph for pattern recognition

In this study, the authors propose a new semi-supervised low-rank representation graph for pattern recognition. A collection of samples is jointly coded by the recently developed low-rank representation (LRR), which better captures the global structure of data and implements more robust subspace segmentation from corrupted samples. By using the calculated LRR coefficients of both labelled and unlabelled samples as the graph weights, a low-rank representation graph is established in a parameter-free manner under the framework of semi-supervised learning. Some experiments are taken on the benchmark database to investigate the performance of the proposed method and the results show that it is superior to other related semi-supervised graphs.
Metallothionein Preserves Akt2 Activity and Cardiac Function via Inhibiting TRB3 in Diabetic Hearts

Cardiac insulin resistance is a key pathogenic factor for diabetic cardiomyopathy (DCM), but the mechanism remains largely unclear. We found that diabetic hearts exhibited decreased phosphorylation of total Akt and isoform Akt2 but not Akt1 in wild-type (WT) male FVB mice, which was accompanied by attenuation of Akt downstream glucose metabolic signal. All of these signal changes were not observed in metallothionein cardiac-specific transgenic (MT-TG) hearts. Furthermore, insulin-induced glucose metabolic signals were attenuated only in WT diabetic hearts. In addition, diabetic hearts exhibited increased Akt-negative regulator tribbles pseudokinase 3 (TRB3) expression only in WT mice, suggesting that MT may preserve Akt2 function via inhibiting TRB3. Moreover, MT prevented tert-butyl hydroperoxide (tBHP)–reduced insulin-stimulated Akt2 phosphorylation in MT-TG cardiomyocytes, which was abolished by specific silencing of Akt2. Specific silencing of TRB3 blocked tBHP inhibition of insulin-stimulated Akt2 phosphorylation in WT cardiomyocytes, whereas overexpression of TRB3 in MT-TG cardiomyocytes and hearts abolished MT preservation of insulin-stimulated Akt2 signals and MT prevention of DCM. Most importantly, supplementation of Zn to induce MT preserved cardiac Akt2 signals and prevented DCM. These results suggest that diabetes-inhibited cardiac Akt2 function via TRB3 upregulation leads to aberrant cardiac glucose metabolism. MT preservation of cardiac Akt2 function by inhibition of TRB3 prevents DCM.
A Galois connection between Turing jumps and limits

Limit computable functions can be characterized by Turing jumps on the input side or limits on the output side. As a monad of this pair of adjoint operations we obtain a problem that characterizes the low functions and dually to this another problem that characterizes the functions that are computable relative to the halting problem. Correspondingly, these two classes are the largest classes of functions that can be pre or post composed to limit computable functions without leaving the class of limit computable functions. We transfer these observations to the lattice of represented spaces where it leads to a formal Galois connection. We also formulate a version of this result for computable metric spaces. Limit computability and computability relative to the halting problem are notions that coincide for points and sequences, but even restricted to continuous functions the former class is strictly larger than the latter. On computable metric spaces we can characterize the functions that are computable relative to the halting problem as those functions that are limit computable with a modulus of continuity that is computable relative to the halting problem. As a consequence of this result we obtain, for instance, that Lipschitz continuous functions that are limit computable are automatically computable relative to the halting problem. We also discuss 1-generic points as the canonical points of continuity of limit computable functions, and we prove that restricted to these points limit computable functions are computable relative to the halting problem. Finally, we demonstrate how these results can be applied in computable analysis.
Web-based remote psychological intervention improves cancer treatment

Abstract Web-based-remote (WBR) intervention is a new approach that incorporates smart control technology and modern medicine to monitor patient compliance. It is based on computer control and communication technology. This study is to explore the benefits of WBR psychological intervention for cancer treatment. 128 patients diagnosed with cancer by Pathology Department of our hospital between 1 February 2013 and 1 August 2013 were included. Patients were randomly assigned to intervention and control group (n = 64). The Questionnaire-Core 30 (QLQ-C30) was used for the survey. Intervention group received WBR psychological intervention in addition to regular clinical follow-up care. Control group only received regular clinical follow-up care. The QLQ-C30 score was significantly better in the intervention group than the control group when the intervention and control groups were followed for three months. In conclusion, WBR psychological intervention substantially improves the quality of life in patients during cancer treatment.
Sociophonetics: The Role of Words, the Role of Context, and the Role of Words in Context

This paper synthesizes a wide range of literature from sociolinguistics and cognitive psychology, to argue for a central role for the "word" as a vehicle of language variation and change. Three crucially interlinked strands of research are reviewed-the role of context in associative learning, the word-level storage of phonetic and contextual detail, and the phonetic consequences of skewed distributions of words across different contexts. I argue that the human capacity for associative learning, combined with attention to fine-phonetic detail at the level of the word, plays a significant role in predicting a range of subtle but systematically robust observed socioindexical patterns in speech production and perception.
Predicting Circulatory Diseases from Psychosocial Safety Climate: A Prospective Cohort Study from Australia

Circulatory diseases (CDs) (including myocardial infarction, angina, stroke or hypertension) are among the leading causes of death in the world. In this paper, we explore for the first time the impact of a specific aspect of organizational climate, Psychosocial Safety Climate (PSC), on CDs. We used two waves of interview data from Australia, with an average lag of 5 years (excluding baseline CDs, final n = 1223). Logistic regression was conducted to estimate the prospective associations between PSC at baseline on incident CDs at follow-up. It was found that participants in low PSC environments were 59% more likely to develop new CD than those in high PSC environments. Logistic regression showed that high PSC at baseline predicts lower CD risk at follow-up (OR = 0.98, 95% CI 0.96–1.00) and this risk remained unchanged even after additional adjustment for known job design risk factors (effort reward imbalance and job strain). These results suggest that PSC is an independent risk factor for CDs in Australia. Beyond job design this study implicates organizational climate and prevailing management values regarding worker psychological health as the genesis of CDs.
Efficacy of High-Dose Vitamin D Supplements for Elite Athletes

Purpose Supplementation with dietary forms of vitamin D is commonplace in clinical medicine, elite athletic cohorts, and the general population, yet the response of all major vitamin D metabolites to high doses of vitamin D is poorly characterized. We aimed to identify the responses of all major vitamin D metabolites to moderate- and high-dose supplemental vitamin D3. Methods A repeated-measures design was implemented in which 46 elite professional European athletes were block randomized based on their basal 25[OH]D concentration into two treatment groups. Athletes received either 35,000 or 70,000 IU·wk−1 vitamin D3 for 12 wk, and 42 athletes completed the trial. Blood samples were collected for 18 wk to monitor the response to supplementation and withdrawal from supplementation. Results Both doses led to significant increases in serum 25[OH]D, and 1,25[OH]2D3. 70,000 IU·wk−1 also resulted in a significant increase of the metabolite 24,25[OH]2D at weeks 6 and 12 that persisted after supplementation withdrawal at week 18, despite a marked decrease in 1,25[OH]2D3. Intact parathyroid hormone was decreased in both groups by week 6 and remained suppressed throughout the trial. Conclusions High-dose vitamin D3 supplementation (70,000 IU·wk−1) may be detrimental for its intended purposes because of increased 24,25[OH]2D production. Rapid withdrawal from high-dose supplementation may inhibit the bioactivity of 1,25[OH]2D3 as a consequence of sustained increases in 24,25[OH]2D that persist as 25[OH]D and 1,25[OH]2D concentrations decrease. These data imply that lower doses of vitamin D3 ingested frequently may be most appropriate and gradual withdrawal from supplementation as opposed to rapid withdrawal may be favorable.
A controlled study comparing salivary osmolality, caries experience and caries risk in patients with cerebral palsy

Background Cerebral palsy (CP) is a permanent neurological disorder accompanied by secondary musculoskeletal masticatory disorder, with repercussion on chewing and deglutition functions. In these conditions, the liquids ingestion is compromised resulting in salivary osmolality alteration. The objective of this study was to compare salivary osmolality, caries experience and caries risk between normoreactive individuals and patients with CP. Material and Methods The participants were 4-20 years old: 52 patients with CP treated at a reference rehabilitation centre (study group, SG), and 52 normoreactive individuals (control group, CG). Saliva was collected for five minutes using cotton rolls. Following centrifugation, salivary osmolality was determined by freezing point depression osmometry. Evaluations included caries experience (DMFT index), and caries risk based on a caries-risk assessment tool (CAT). Descriptive and inferential statistics (Chi square and Student t tests) were used to compare the groups. Receiver operating characteristic (ROC) analyses were performed and the area under the ROC curve (Az) was calculated. The level of significance was set at 5%. Results The groups were homogeneous for sex (p=0.843) and age (p=0.128). In the SG, spastic type CP was the most prevalent (80.8%), and patients showed significantly higher salivary osmolality values compared with the CG (p<0.001). No significant differences in caries experience (p=0.159) or caries risk (p=0.297) were observed. ROC curve analysis determined a salivary osmolality cutoff point of >74 for the SG and >54 for the CG in the presence of dental caries. A significant correlation was verified between salivary osmolality and the DMFT index for the SG (p≤0.05). Conclusions Although patients with CP showed higher salivary osmolality values, higher caries experience and caries risk were not observed compared with normoreactive individuals. Key words:Cerebral palsy, osmolar concentration, dental caries, saliva.