Miracle-dz/UniFAR-FTUs huggingface dataset:
1 1 N ov 2 01 3 Robust Beamforming for Secure Communication in Systems with Wireless Information and Power Transfer

This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wi reless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdropp ers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers ar e able to harvest energy from radio frequency signals. Our des ign advocates the dual use of both artificial noise and energy sig nals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulat ed as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal genera tion for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state inform ation (CSI) of the potential eavesdroppers and no CSI of the passiv e eavesdroppers are available at the transmitter. Besides, t he problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-t ointerference-plus-noise ratio (SINR) at the desired recei ver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers;and minimum required heterogeneous amounts of power transferr ed to the idle legitimate receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex determi nistic constraint. Then, a semi-definite programming (SDP) relaxa tion approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complex ity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate a close-t o-optimal performance achieved by the proposed schemes and significan t transmit power savings by optimization of the artificial noise and energy signal generation.
Environmentally Friendly Polymer Blends Based on Post-Consumer Glycol-Modified Poly(Ethylene Terephthalate) (PET-G) Foils and Poly(Ethylene 2,5-Furanoate) (PEF): Preparation and Characterization

Environmentally friendly polymer blends between post-consumer PET-G and bio-based poly(ethylene 2,5 furanoate) (PEF) have been prepared. The PET-G granules were obtained from the post-consumer glycol-modified poly(ethylene terephthalate) PET-G foils from Nicrometal S.A. as a result of materials recycling. PEF was synthesized from dimethyl furan-2,5-dicarboxylate and 1,2-ethylene glycol (BioUltra) by a two-stage melt polycondensation process. According to the calculations followed by Hoy’s method, one has studied the miscibility of the components in the blend. The molecular structure of PET-G/PEF blends was analyzed by Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, while the morphology of the blends was determined by Scanning Electron Microscopy (SEM). To evaluate phase transition temperatures, as well as the thermal effects in PET-G/PEF blends, Differential Scanning Calorimetry (DSC), Dynamic Mechanical Thermal Analysis (DMTA), and Thermogravimetric Analysis (TGA), were performed. Tensile tests revealed that along with an increase in the amount of PEF, an increase in Young’s modulus was observed. Besides, the existence of interfacial interactions between polymers, especially in the case of PET-G/PEF 80/20, enabling the PET-G chains to form a network structure with the PEF by reacting with their functional groups, allows observation of a synergistic effect in the improvement of thermal stability and water absorption.
Pregnancy outcomes in women with inflammatory bowel disease: a large community-based study from Northern California.

BACKGROUND & AIMS The aim of this study was to determine whether pregnancy outcomes differ between women with and without inflammatory bowel disease (IBD) and to determine what risk factors adversely affect outcomes. METHODS We conducted a cohort study of all pregnant women within the Northern California Kaiser Permanente membership between the years 1995 and 2002. We abstracted the records of all pregnancies in women with IBD (exposed cohort) and a random sample of pregnancies from age-matched women without IBD (unexposed cohort) and evaluated risk factors for spontaneous abortion, complications of pregnancy, and adverse newborn events. RESULTS A total of 461 pregnant women with IBD were matched to 493 unexposed pregnant women. Women with IBD were more likely to have an adverse conception outcome (odds ratio, 1.65; 95% confidence interval, 1.09-2.48), an adverse pregnancy outcome (odds ratio, 1.54; 95% confidence interval, 1.00-2.38), or a pregnancy complication (odds ratio, 1.78; 95% confidence interval, 1.13-2.81); however, the difference between the 2 groups in adverse newborn outcomes was not statistically significant (odds ratio, 1.89; 95% confidence interval, 0.98-3.69). Independent predictors of an adverse outcome included a diagnosis of IBD, a history of surgery for IBD, and non-Caucasian ethnicity. Severity of disease and medical treatments were not associated with an adverse outcome. CONCLUSIONS Women with IBD are more likely to have an adverse outcome related to pregnancy. Disease activity and medical treatment did not predict adverse outcomes in a large, nonreferral population.
Promoting unsupervised walking in women with fibromyalgia: a randomized controlled trial

ABSTRACT The objective of this study is to test the efficacy of a group motivational plus implementation intentions intervention in promoting adherence to an unsupervised walking program recommended for fibromyalgia, compared to an implementation intentions condition and to an active control condition. A triple-blind, randomized, longitudinal study with measures at baseline, short (seven weeks post-intervention), mid (12 weeks) and long-term (36 weeks) is performed. Data are analyzed using multilevel longitudinal growth curve two-level modelling. Participants are 157 women with fibromyalgia. In the short-term, adherence to the minimum and to the standard walking program (primary outcome measures) is explained by time (both p <.001), motivational plus implementation intentions intervention (both p <.001) and by their interaction (both p <.001). Regarding the secondary outcomes, only physical function is explained by time (p <.001), motivational plus implementation intentions intervention (p <.05) and by their interaction (p <.05). Motivational plus implementation intentions intervention achieve the promotion of walking as an exercise in the short-term; furthermore, physical function of the women in this condition is better than in the other two intervention groups, which is a relevant outcome from a rehabilitation point of view. However, more studies are needed to maintain the exercise at mid and long-term.
Control Strategy to Eliminate Impact of Voltage Measurement Errors on Grid Current Performance of Three-Phase Grid-Connected Inverters

This study proposes an advanced current control strategy for three-phase grid-connected inverters to reject the impact of the dc offsets and scaling errors in the grid voltage measurement on the grid current performance. The proposed current controller designed in the synchronous (<italic>d-q</italic>) reference frame is developed with a proportional integral (PI) plus three vector PI controllers. The PI controller regulates the fundamental current to follow its reference, meanwhile, three vector PI controllers tuned at the fundamental grid frequency (<inline-formula> <tex-math notation="LaTeX">${\omega _s}$</tex-math></inline-formula>), <inline-formula><tex-math notation="LaTeX"> $2{\omega _s}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$6{\omega _s}$</tex-math> </inline-formula> are employed to eliminate the dc, unbalance, harmonic components in the grid current. As a result, the three-phase grid currents are controlled to be balanced, sinusoidal, and extremely low dc component despite the presence of the dc offset and scaling errors in the grid voltage measurement and distorted grid voltage conditions. The main advantage of the proposed control scheme is that it is developed without the need of additional hardware circuit, dc extraction, and harmonic detection scheme so that it can be integrated into the existing grid-connected inverter system without extra cost. The effectiveness of the suggested solution is verified by experimental results under various grid voltage conditions and the grid voltage measurement errors.
Racism in European Health Care: Structural Violence and Beyond

Research shows how racism can negatively affect access to health care and treatment. However, limited theoretical research exists on conceptualizing racism in health care. In this article, we use structural violence as a theoretical tool to understand how racism as an institutionalized social structure is enacted in subtle ways and how the “violence” built into forms of social organization is rendered invisible through repetition and routinization. We draw on interviews with health care users from three European countries, namely, Sweden, Germany, and Portugal to demonstrate how two interrelated processes of unequal access to resources and inequalities in power can lead to the silencing of suffering and erosion of dignity, respectively. The strength of this article lies in illuminating the mechanisms of subtle racism that damages individuals and leads to loss of trust in health care. It is imperative to address these issues to ensure a responsive and equal health care for all users.
Isolation and characterization of Halobacterium salinarum from saline lakes in Iran

Introduction and objective: Extremely halophilic Archaea belonging to the order Halobacteriales had been isolated from various hyper saline environments such as the Dead Sea, the Great Salt Lake, Sabkhas Lake, and natural or artificial Salterns. The main aim of this study was to isolate and characterize Halobacterium salinarum strains from samples of saline soils and lake water collected from four distinct regions of Iran. Materials and methods: Saline soil samples and lake water samples were collected from different zones of Iran including a high salinity lake in Qom and Fars and also Seawater of Oromiea Lake and Persian Gulf. For isolation of H. salinarum from collected samples, Halobacterium salinarum medium were used. Isolates were identified by biochemical tests such as motility and morphological features, then identification confirmed by molecular characterization. Optimum NaCl requirement, pH and temperature were determined. Results: The obtained results showed two isolates were motile, rod, Gram-negative, oxidase and catalase positive, with red pigmentation which grew in the presence of 25% NaCl. Isolates could hydrolyze casein and gelatin. The result of molecular characterization showed that two strains were H. salinarum. Basic local alignment search tool (BLAST) analysis showed 99% homology between these strains and H. salinarum strain R1. Conclusion: In this investigation we succeeded to isolate and identify H. salinarum in Iran saline ecosystems. There is a large diversity among halophilic bacteria in Iran ecosystems and isolation of H. salinarum from saline lakes will provide better information about halophilic bacteria in Iran ecosystems.
Soft versus Hard Interference Cancellation in MMSE OSIC MIMO Detector: A Comparative Study

There are two schemes to perform interference cancellation in soft-out minimum mean square error (MMSE) ordering successive interference cancellation (OSIC) detector for channel coded multiple-input multiple-output (MIMO) system, i.e., soft interference cancellation (SIC) and maximal likelihood (ML) hard decision based interference cancellation (HDIC). In this paper, we investigated these two schemes. At first, we discussed the basic principles of soft-output MMSE OSIC MIMO detector and proposed a reduced-complexity implementation. Then, based on the post-detection effective signal-to-interference and noise ratio (SINR) of MMSE filter at each detection stage, these two schemes are compared analytically. Finally, extensive simulations are performed to validate the analysis. The results show that the SIC based soft-output MMSE OSIC MIMO detector is superior to HDIC based one and all of them are much better than the MMSE detector and conventional MMSE OSIC detector, which assumes perfect interference cancellation.
Implementation of an adaptive, model free, learning controller on the Atlas robot

Recent events in natural and man-made disasters have highlighted the limitation in man's ability to confine and mitigate damage in such scenarios. Therefore, there is an urgent need for robotic technology that can function in all environments and serve as a substitute to humans in disaster scenarios. This paper presents research efforts to advance walking technology of humanoid robots with application to the Boston Dynamics Atlas robot. The Atlas was designed as part of the DARPA Robotics Challenge (DRC). The paper contribution is in a model free, walking trajectory tracking controller that is tested using GAZEBO robotics simulator. Artificial neural networks are used to learn the robot's nonlinear dynamics on the fly using a neuroadaptive control algorithm. The learned nonlinear dynamics are utilized along with a filtered error signal to generate input torques to control the system. Results show that the ability to approximate the robot nonlinear dynamics allows for full-body control without the need of modeling such a complex system. This ability is what makes the control scheme utilized appealing for complex, real-life, robotic applications that occur in a non-laboratory setting.
Genomic sequence and expression profile of murine Bat1a and Nfkbil1

In humans, susceptibility to several immunopathologic diseases maps to a conserved block encompassing the polymorphic BAT1, NFKBIL1 (IKBL) and TNF genes in the central MHC. As a pre-requisite for studies of these genes in animal models, we characterized Bat1a and Nfkbil1 in inbred mice differing in their H2 haplotype. We identified two indels and nine single nucleotide polymorphisms (SNP) upstream of Nfkbil1, one indel, nine SNP upstream of Bat1a and a synonymous SNP in exon 2 of Bat1a. H2g7 and H2b mice yielded identical Bat1a and Nfkbil1 sequences. Real time PCR (RT-PCR) showed Bat1a was expressed in adult brain, heart, kidney, liver, lung, pancreas and spleen. Expression of Bat1a was higher in brain and liver of 15-day embryos compared to 1-day old mice and increased moderately in liver and lung of adult mice 2–4 h after LPS challenge. Nfkbil1 expression was low or undetetectable in all tissues and cell lines.
Non-parametric optimal design in dose finding studies.

We describe a non-parametric optimal design as a theoretical gold standard for dose finding studies. Its purpose is analogous to the Cramer-Rao bound for unbiased estimators, i.e. it provides a bound beyond which improvements are not generally possible. The bound applies to the class of non-parametric designs where the data are not assumed to be generated by any known parametric model. Whenever parametric assumptions really hold it may be possible to do better than the optimal non-parametric design. The goal is to be able to compare any potential dose finding scheme with the optimal non-parametric benchmark. This paper makes precise what is meant by optimal in this context and also why the procedure is described as non-parametric.
Hyperprolactinemia in antipsychotic-naive patients with first-episode psychosis

Background Hyperprolactinemia is frequent in patients with schizophrenic psychoses. It is usually regarded as an adverse effect of antipsychotics but has recently also been shown in patients without antipsychotic medication. Our objective was to test whether hyperprolactinemia occurs in antipsychotic-naive first-episode patients (FEPs). Method In the framework of the European First Episode Schizophrenia Trial (EUFEST), 249 out of 498 FEPs were eligible for this study, of whom 74 were antipsychotic naive. All patients were investigated regarding their serum prolactin levels with immunoassays standardized against the 3rd International Reference Standard 84/500. Results Twenty-nine (39%) of the 74 antipsychotic-naive patients showed hyperprolactinemia not explained by any other reason, 11 (50%) of 22 women and 18 (35%) of 52 men. Conclusions Hyperprolactinemia may be present in patients with schizophrenic psychoses independent of antipsychotic medication. It might be stress induced. As enhanced prolactin can increase dopamine release through a feedback mechanism, this could contribute to explaining how stress can trigger the outbreak of psychosis.
Association between Active Helicobacter pylori Infection and Glaucoma: A Systematic Review and Meta-Analysis

Background: Glaucoma is the second most common cause of blindness worldwide affecting almost 70 million individuals. Helicobacter pylori (H. pylori) is a widespread pathogen with systematic pathogenicity. This meta-analysis aimed to estimate the contradictory data regarding a potential association between active H. pylori infection and glaucoma. Materials and Methods: A research in MEDLINE/PubMed and Google Scholar was conducted and original studies investigating the relationship between H. pylori infection and glaucoma were included. Analysis was performed with random effects model. The main outcome was the odds ratio (OR) with 95% confidence intervals (CI) of H. pylori infection as a risk factor for glaucoma. A parallel analysis studied the role of active infection as indicated by histology and the titer of anti-H. pylori antibodies. For the anti-H. pylori antibody titers, weighted mean differences (WMD) were estimated between patients and controls. Results: Fifteen studies were included, with 2664 participants (872 patients with glaucoma and 1792 controls), divided into primary open-angle glaucoma (POAG), normal tension glaucoma (NTG) and pseudo-exfoliation glaucoma (PEG). The association between H. pylori infection and overall glaucoma was significant (OR = 2.08, CI 95% 1.48–2.93) with moderate heterogeneity (I2 = 61.54%). After stratification by glaucoma subtype, heterogeneity was eliminated in the NTG subgroup. Studies with healthy controls, and controls with anemia yielded very low or no heterogeneity, respectively. Gastric biopsy to document active H. pylori infection yielded the highest OR (5.4, CI: 3.17–9.2, p < 0.001) and null heterogeneity. For anti-H. pylori antibody titers, there was a significant difference in WMD between patients and controls (WMD 15.98 IU/mL; 95% CI: 4.09–27.87; p = 0.008); values were greater in glaucoma patients, with high heterogeneity (I2: 93.8%). Meta-regression analysis showed that mean age had a significant impact on glaucoma (p = 0.037). Conclusions: Active H. pylori infection may be associated with glaucoma with null heterogeneity, as, beyond histology, quantified by anti-H. pylori titers and increases with age.
SneakPeek: Interest Mining of Images based on User Interaction

Nowadays, eye tracking is the most used technology to detect areas of interest. This kind of technology requires specialized equipment recording user's eyes. In this paper, we propose SneakPeek, a different approach to detect areas of interest on images displayed in web pages based on the zooming and panning actions of the users through the image. We have validated our proposed solution with a group of test subjects that have performed a test in our on-line prototype. Being this the first iteration of the algorithm, we have found both good and bad results, depending on the type of image. In specific, SneakPeek works best with medium/big objects in medium/big sized images. The reason behind it is the limitation on detection when smartphone screens keep getting bigger and bigger. SneakPeek can be adapted to any website by simply adapting the controller interface for the specific case.
The Inhibitory Effect of Plant Extracts on Growth of the Foodborne Pathogen, Listeria monocytogenes

Listeria monocytogenes is a foodborne pathogen responsible for about 1600 illnesses each year in the United States (US) and about 2500 confirmed invasive human cases in European Union (EU) countries. Several technologies and antimicrobials are applied to control the presence of L. monocytogenes in food. Among these, the use of natural antimicrobials is preferred by consumers. This is due to their ability to inhibit the growth of foodborne pathogens but not prompt negative safety concerns. Among natural antimicrobials, plant extracts are used to inactivate L. monocytogenes. However, there is a large amount of these types of extracts, and their active compounds remain unexplored. The aim of this study was to evaluate the antibacterial activity against L. monocytogenes of about 800 plant extracts derived from plants native to different countries worldwide. The minimal inhibitory concentrations (MICs) were determined, and scanning electron microscopy (SEM) was used to verify how the plant extracts affected L. monocytogenes at the microscopic level. Results showed that 12 of the plant extracts had inhibitory activity against L. monocytogenes. Future applications of this study could include the use of these plant extracts as new preservatives to reduce the risk of growth of pathogens and contamination in the food industry from L. monocytogenes.
Efficient human-robot collaboration: When should a robot take initiative?

The promise of robots assisting humans in everyday tasks has led to a variety of research questions and challenges in human-robot collaboration. Here, we address the question of whether and when a robot should take initiative during joint human-robot task execution. We designed a robotic system capable of autonomously performing table-top manipulation tasks while monitoring the environmental state. Our system is able to predict future environmental states and the robot’s actions to reach them using a dynamic Bayesian network. To evaluate our system, we implemented three different initiative conditions to trigger the robot’s actions. Human-initiated help gives control of the robot action timing to the user; robot-initiated reactive help triggers robot assistance when it detects that the human needs help; robot-initiated proactive help makes the robot help whenever it can. We performed a user study (N=18) to compare the trigger mechanisms in terms of quality of interaction, system performance and perceived sociality of the robot. We found that people collaborate best with a proactive robot, yielding better team fluency and high subjective ratings. However, they prefer having control of when the robot should help, rather than working with a reactive robot that only helps when needed. We also found that participants gazed at the robot’s face more during the human-initiated help compared to the other conditions. This shows that asking for the robot’s help may lead to a more “social” interaction, without improving the quality of interaction or the system performance.