Miracle-dz/UniFAR-FTUs huggingface dataset:
Zap: Making Predictions Based on Online User Behavior

This paper introduces Zap, a generic machine learning pipeline for making predictions based on online user behavior. Zap combines well known techniques for processing sequential data with more obscure techniques such as Bloom filters, bucketing, and model calibration into an end-to-end solution. The pipeline creates website- and task-specific models without knowing anything about the structure of the website. It is designed to minimize the amount of website-specific code, which is realized by factoring all website-specific logic into example generators. New example generators can typically be written up in a few lines of code.
Learning Hybrid Sparsity Prior for Image Restoration: Where Deep Learning Meets Sparse Coding

State-of-the-art approaches toward image restoration can be classified into model-based and learning-based. The former - best represented by sparse coding techniques - strive to exploit intrinsic prior knowledge about the unknown high-resolution images; while the latter - popularized by recently developed deep learning techniques - leverage external image prior from some training dataset. It is natural to explore their middle ground and pursue a hybrid image prior capable of achieving the best in both worlds. In this paper, we propose a systematic approach of achieving this goal called Structured Analysis Sparse Coding (SASC). Specifically, a structured sparse prior is learned from extrinsic training data via a deep convolutional neural network (in a similar way to previous learning-based approaches); meantime another structured sparse prior is internally estimated from the input observation image (similar to previous model-based approaches). Two structured sparse priors will then be combined to produce a hybrid prior incorporating the knowledge from both domains. To manage the computational complexity, we have developed a novel framework of implementing hybrid structured sparse coding processes by deep convolutional neural networks. Experimental results show that the proposed hybrid image restoration method performs comparably with and often better than the current state-of-the-art techniques.
Effect of γ-Aminobutyric Acid–Chitosan Nanoparticles on Glucose Homeostasis in Mice

Diabetes mellitus is the most common endocrine disease worldwide; hyperglycemia is a hallmark of this disease. To alleviate the pain caused by diabetes, developing and utilizing effective diabetic drugs to maintain or recover the function of the residual β-cells is an attractive therapeutic approach. γ-aminobutyric acid (GABA) has been shown to have such effects, but it is easy to have reduced GABA activity under physiological conditions. In the present study, GABA–chitosan nanoparticles (GABA–CS NPs) were prepared, and glucose homeostasis, pancreatic β-cell protection, and anti-inflammatory effects of GABA–CS NPs were investigated in vivo. The results showed that blood glucose levels and IL-1β levels in the GABA–CS NP-administered group were both significantly lower, whereas the PDX1 expression was significantly higher than that of the impaired group (p < 0.01). This indicates that GABA–CS NPs can efficiently maintain glucose homeostasis, protect β-cells, and inhibit inflammation. These nanoparticles have the potential to be applied for future diabetes theranostics.
Prevention of Surgical Site Infections: A Systematic Review of Cost Analyses in the Use of Prophylactic Antibiotics

Introduction: The preoperative phase is an important period in which to prevent surgical site infections (SSIs). Prophylactic antibiotic use helps to reduce SSI rates, leading to reductions in hospitalization time and cost. In clinical practice, besides effectiveness and safety, the selection of prophylactic antibiotic agents should also consider the evidence with regard to costs and microbiological results. This review assessed the current research related to the use of antibiotics for SSI prophylaxis from an economic perspective and the underlying epidemiology of microbiological findings. Methods: A literature search was carried out through PubMed and Embase databases from 1 January 2006 to 31 August 2017. The relevant studies which reported the use of prophylactic antibiotics, SSI rates, and costs were included for analysis. The causing pathogens for SSIs were categorized by sites of the surgery. The quality of reporting on each included study was assessed with the “Consensus on Health Economic Criteria” (CHEC). Results: We identified 20 eligible full-text studies that met our inclusion criteria, which were subsequently assessed, studies had in a reporting quality scored on the CHEC list averaging 13.03 (8–18.5). Of the included studies, 14 were trial-based studies, and the others were model-based studies. The SSI rates ranged from 0 to 71.1% with costs amounting to US$480-22,130. Twenty-four bacteria were identified as causative agents of SSIs. Gram negatives were the dominant causes of SSIs especially in general surgery, neurosurgery, cardiothoracic surgery, and obstetric cesarean sections. Conclusions: Varying results were reported in the studies reviewed. Yet, information from both trial-based and model-based costing studies could be considered in the clinical implementation of proper and efficient use of prophylactic antibiotics to prevent SSIs and antimicrobial resistance.
Semi-Mechanism-Based Pharmacodynamic Model for the Anti-Inflammatory Effect of Baicalein in LPS-Stimulated RAW264.7 Macrophages

Monitoring of the inhibition of TNF-α, IL-6, iNOS, and NO is used to effectively evaluate anti-inflammatory drugs. Baicalein was found to have good anti-inflammatory activities, but its detailed cellular pharmacodynamic events have not been expatiated by any other study. The inflammatory mediators, including TNF-α, IL-6, iNOS, and NO production in RAW264.7 macrophage induced by LPS, were measured. It was found that these data showed a sequential pattern on time and based on these points a cellular pharmacodynamic model was developed and tested. TNF-α and IL-6 were quantified by ELISA, NO was detected by Griess and iNOS expression was measured by Western blot. The pharmacodynamic model was developed using a NLME modeling program Monolix® 2016R1.1The results showed that baicalein quickly suppressed release of TNF-α in a concentration-dependent manner, and consequently causing the diminution of IL-6 and iNOS/NO. The pharmacodynamic model simulation successfully described the experimental data, supporting the hypothesis that IL-6 and iNOS /NO release after LPS stimulation is mediated by TNF-α rather than LPS directly. The pharmacodynamic model allowed a well understanding of the cellular pharmacodynamic mechanism of baicalein in the treatment of inflammatory diseases.
Tracking Elections: our experience during the presidential elections in Ecuador

The world's digital transformation has influenced not only the way we do business, but also the way we perform daily activities. In fact, the past Presidential elections in the United States as well as those in Great Britain (Brexit) and in Colombia (peace agreement referendum) are proof that social media play an important part in modern politics. In fact, this digital political field is filled by political movements and political candidates looking for popular support (number of followers), regular citizens' messages discussing social issues (trending topics flooding social media), or even political propaganda in favor or against politicians or political movements (advertisement). One of the issues with social media in this era is the presence of automatic accounts (bots) that artificially fill accounts with fake followers, create false trending topics, and share fake news or simply flood the net with propaganda. All this artificial information may influence people and sometimes may even censor people's real opinions undermining their freedom of speech. In this paper, we propose a methodology to track elections and a set of tools used to collect and analyze election data. In particular, this paper discusses our experiences during the Presidential Elections in Ecuador held in 2017. In fact, we show how all candidates prepared an online campaign in social media (Twitter) and how the political campaign altered a common follower rate subscription. We discuss that the high presence of followers during the period between the first and second round of elections may be altered by automatic accounts. Finally, we use bot detection systems and gathered more than 30,000 political motivated bots. In our data analysis, we show that these bots were mainly used for propaganda purposes in favor or against a particular candidate.
Resilient Feedback Controller Design For Linear Model of Power Grids

In this paper, a resilient controller is designed for the linear time-invariant (LTI) systems subject to attacks on the sensors and the actuators. A novel probabilistic attack model is proposed to capture vulnerabilities of the communication links from sensors to the controller and from the controller to actuators. The observer and the controller formulation under the attack are derived. Thereafter, By leveraging Lyapunov functional methods, it is shown that exponential mean-square stability of the system under the output feedback controller is guaranteed if a certain LMI is feasible. The simulation results show the effectiveness and applicability of the proposed controller design approach.
Modulation of bone morphogenetic protein activity by melatonin in ovarian steroidogenesis

Melatonin regulates circadian and seasonal rhythms and the activities of hormones and cytokines that are expressed in various tissues, including the ovary, in which melatonin receptors are expressed. In the ovary, follicular growth occurs as a result of complex interactions between pituitary gonadotropins and autocrine and paracrine factors, including bone morphogenetic proteins (BMPs) that are expressed in the ovary.
Effect of hip position and breathing pattern on abdominal muscle activation during curl-up variations

Recent studies have indicated that applying different breathing pattern and changes of extremity positions could be a useful way of performing challenging exercises that include coactivation of the abdominal muscles. The aim of this study was to investigate the effects of changes of breathing pattern and hip position on abdominal muscle activity during curl-up exercises. Surface electromyography responses of the rectus abdominis (RA), internal oblique (IO), external oblique (EO) muscles and rectus femoris (RF), and Borg rating of perceived exertion (Borg RPE) score were investigated during the curl up exercises. A total of 20 healthy, physically active male volunteers completed two hip positions (45° and 90° hip flexion) and three breath types (slow expiration, maximal inspiration, and maximal expiration) for curl-up variations. The curl-up with 90° of hip flexion significantly increased the muscular activities of IO, EO, RF, and Borg RPE score (P<0.05). The curl-up with maximal expiration significantly elevated the IO and EO activity, compared to other breathing conditions. There were no significant difference in RA activities (P>0.05). The present study showed both the hip position and breathing pattern affect abdominal muscle activities during the curl-up exercise, especially of the oblique muscles. Among the breathing patterns investigated herein, the curl-up with maximum expiration produced greater activation of the oblique muscles compared to slow expiration and maximum inspiration.
The effects of early-stage neurodevelopmental treatment on the growth of premature infants in neonatal intensive care unit

The purpose of this study was to investigate the effects of early-stage neurodevelopmental treatment on the growth of premature infants in the neonatal intensive care unit. A total of 85 premature infants were included in this study. Infants with a birth weight of less than 2.5 kg and of 2.5 kg or higher were classified as premature infants with a high risk of growth delay and with a low risk of growth delay respectively. Of the 55 premature infants with a high risk of growth delay, 27 premature infants were placed in the intervention group and 28 were placed in the control group according to their hospitalization time. Thirty premature infants with a low risk of growth delay were included in the comparative group. The same general nursing care of the neonatal intensive care unit was provided to the intervention group, the control group, and the comparative group, but an additional neurodevelopmental treatment program was given only to the intervention group, for 15 min per session, 4 times a week, up to 40 weeks after conception. As growth indicators, the body weight and head circumference were measured before and 2 weeks after the intervention, and at 40 weeks after conception when the intervention was completed. The body weight and head circumference of the intervention group, which received the neurodevelopmental treatment, were significantly improved compared to the control group (P<0.05), but they were not significantly different from those of the comparative group. However, the body weight and head circumference of the control.
Sparse Signal Processing for Grant-Free Massive Connectivity: A Future Paradigm for Random Access Protocols in the Internet of Things

The next wave of wireless technologies will proliferate in connecting sensors, machines, and robots for myriad new applications, thereby creating the fabric for the Internet of Things (IoT). A generic scenario for IoT connectivity involves a massive number of machine-type connections, but in a typical application, only a small (unknown) subset of devices are active at any given instant; therefore, one of the key challenges of providing massive IoT connectivity is to detect the active devices first and then decode their data with low latency. This article advocates the usage of grant-free, rather than grantbased random access schemes to overcome the challenge of massive IoT access. Several key signal processing techniques that promote the performance of the grant-free strategies are outlined, with a primary focus on advanced compressed sensing techniques and their applications for the efficient detection of active devices. We argue that massive multiple-input, multiple-output (MIMO) is especially well suited for massive IoT connectivity because the device detection error can be driven to zero asymptotically in the limit as the number of antennas at the base station (BS) goes to infinity by using the multiplemeasurement vector (MMV) compressed sensing techniques. This article also provides a perspective on several related important techniques for massive access, such as embedding short messages onto the device-activity detection process and the coded random access.
Stoichio-Metagenomics of Ocean Waters: A Molecular Evolution Approach to Trace the Dynamics of Nitrogen Conservation in Natural Communities

Nitrogen is crucially limiting in ocean surface waters, and its availability varies substantially with coastal regions typically richer in nutrients than open oceans. In a biological stoichiometry framework, a parsimonious strategy of nitrogen allocation predicts nitrogen content of proteins to be lower in communities adapted to open ocean than to coastal regions. To test this hypothesis we have directly interrogated marine microbial communities, using a series of metagenomics datasets with a broad geographical distribution from the Global Ocean Sampling Expedition. Analyzing over 20 million proteins, we document a ubiquitous signal of nitrogen conservation in open ocean communities, both in membrane and non-membrane proteins. Efficient nitrogen allocation is expected to specifically target proteins that are expressed at high rate in response to nitrogen starvation. Furthermore, in order to preserve protein functional efficiency, economic nitrogen allocation is predicted to target primarily the least functionally constrained regions of proteins. Contrasting the NtcA-induced pathway, typically up-regulated in response to nitrogen starvation, with the arginine anabolic pathway, which is instead up-regulated in response to nitrogen abundance, we show how both these predictions are fulfilled. Using evolutionary rates as an informative proxy of functional constraints, we show that variation in nitrogen allocation between open ocean and coastal communities is primarily localized in the least functionally constrained regions of the genes triggered by NtcA. As expected, such a pattern is not detectable in the genes involved in the arginine anabolic pathway. These results directly link environmental nitrogen availability to different adaptive strategies of genome evolution, and emphasize the relevance of the material costs of evolutionary change in natural ecosystems.
Watching the Detectives: An Initial Report on an Industrial Experiment to Collaborate with the Empirical Software Engineering Research Community

Context: Evidence-based practice within healthcare benefits from the Cochrane Collaboration providing trustworthy evidence that can be used to inform clinical decisions. Currently no equivalent resource exists for the practice of software engineering. With the ever increasing dependence of society upon software an analogue of the collaboration for the discipline of software engineering would appear to be of potentially significant societal benefit. Objectives: This study investigated attitudes of the empirical software engineering community, as exemplified by attendees at an research focused conference, to the hypothesis that an analogue of the Cochrane Collaboration would be beneficial. Method: An online survey was employed to capture opinions of participants in the EASE’16 conference on the hypothesis. During a presentation at the industrial track of the conference attendees (27) were invited to complete the survey. Subsequently all conference attendees (90) were provided with details of the survey, irrespective of whether they had attended the presentation or not. No closing date for the survey was specified. Results: In total 9 conference attendees completed the survey: of whom 7 had attended the industrial track presentation. These figures approximate to a response rate of 26% for those attending the presentation and exactly 10% for conference participants overall. This response rate is insufficient to enable statistical analysis of the data obtained through the survey. Trends are, however, evident in the rankings of the responses provided. These trends are consistent with opinions and observations volunteered by a diverse range of individuals active in software engineering and allied fields dating from 2014 to the present. Conclusions: At this time there is insufficient data to validate the hypothesis. Nevertheless experience, informal observation and opinion continues to accumulate to provide evidence in support of the validity of the hypothesis, albeit principally in anecdotal form.
Noisy Private Information Retrieval: On Separability of Channel Coding and Information Retrieval

We consider the problem of noisy private information retrieval (NPIR) from <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> non-communicating databases, each storing the same set of <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> messages. In this model, the answer strings are not returned through noiseless bit pipes, but rather through <italic>noisy</italic> memoryless channels. We aim at characterizing the PIR capacity for this model as a function of the statistical information measures of the noisy channels such as entropy and mutual information. We derive a general upper bound for the retrieval rate in the form of a max-min optimization. We use the achievable schemes for the PIR problem under asymmetric traffic constraints and random coding arguments to derive a general lower bound for the retrieval rate. The upper and lower bounds match for <inline-formula> <tex-math notation="LaTeX">$M=2$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$M=3$ </tex-math></inline-formula>, for any <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>, and any noisy channel. The lower and upper bounds show a separation between channel coding and retrieval scheme except for adapting the traffic ratio from the databases. We refer to this as <italic>almost separation</italic>. Next, we consider the private information retrieval problem from multiple access channels (MAC-PIR). In MAC-PIR, the database responses reach the user through a multiple access channel (MAC) that mixes the responses together in a stochastic way. We show that for the additive MAC and the conjunction/disjunction MAC, channel coding and retrieval scheme are <italic>inseparable</italic> unlike in NPIR. We show that the retrieval scheme depends on the properties of the MAC, in particular on the linearity aspect. For both cases, we provide schemes that achieve the full capacity without any loss due to the privacy constraint, which implies that the user can exploit the nature of the channel to improve privacy. Finally, we show that the full unconstrained capacity is not always attainable by determining the capacity of the selection channel.
Investigation of histology radius for dielectric characterisation of heterogeneous materials

Knowledge of the dielectric properties of biological tissues is fundamental in the design of novel electromagnetic-based medical devices. Tissue dielectric properties are typically measured using the open-ended coaxial probe technique, which is designed for homogeneous samples. Histological analysis may be conducted to associate the measured dielectric properties to different tissue types within heterogeneous samples. However, the histology radius (i.e., the radial extent of the tissue sample that undergoes histological analysis) has not been consistently defined in the literature; therefore, this parameter may be a source of error in dielectric data. For this reason, we investigate the histology radius of various heterogeneous samples. Dielectric measurements were conducted over the frequency range of 0.5 to 20 GHz on radially heterogeneous tissue-mimicking materials and biological tissues, with different dielectric properties and contrasts. The experimental results were validated with numerical simulations and indicate that: i) the histology radius does not exceed the probe radius; ii) the dielectric properties of radially heterogeneous tissues depend on the spatial distribution of each material within the histology radius; and iii) the bulk dielectric properties of concentric heterogeneous tissues highly depend on the properties of each constituent material within the histology radius. This study supports consistent identification of the histology radius and provides a basis for rigorous interpretation of the dielectric properties of heterogeneous tissues.