Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Risk of Re-identification of Patients from Hospital Prescription Records.

BACKGROUND Pharmacies often provide prescription records to private research firms, on the assumption that these records are de-identified (i.e., identifying information has been removed). However, concerns have been expressed about the potential that patients can be re-identified from such records. Recently, a large private research firm requested prescription records from the Children's Hospital of Eastern Ontario (CHEO), as part of a larger effort to develop a database of hospital prescription records across Canada. OBJECTIVE To evaluate the ability to re-identify patients from CHEO'S prescription records and to determine ways to appropriately de-identify the data if the risk was too high. METHODS The risk of re-identification was assessed for 18 months' worth of prescription data. De-identification algorithms were developed to reduce the risk to an acceptable level while maintaining the quality of the data. RESULTS The probability of patients being re-identified from the original variables and data set requested by the private research firm was deemed quite high. A new de-identified record layout was developed, which had an acceptable level of re-identification risk. The new approach involved replacing the admission and discharge dates with the quarter and year of admission and the length of stay in days, reporting the patient's age in weeks, and including only the first character of the patient's postal code. Additional requirements were included in the data-sharing agreement with the private research firm (e.g., audit requirements and a protocol for notification of a breach of privacy). CONCLUSIONS Without a formal analysis of the risk of re-identification, assurances of data anonymity may not be accurate. A formal risk analysis at one hospital produced a clinically relevant data set that also protects patient privacy and allows the hospital pharmacy to explicitly manage the risks of breach of patient privacy.
Spatio-temporal interaction with disease mapping.

Markov chain Monte Carlo methods are used to estimate mortality rates under a Bayesian hierarchical model. Spatial correlations are introduced to examine spatial effects relative to both regional and regional changes over time by groups. A special feature of the models is the inclusion of longitudinal variables which will describe temporal trends in mortality or incidences for different population groups. Disease maps are used to illustrate the role of different parameters in the model and pinpointing areas of interesting patterns. The methods are demonstrated by male cancer mortality data from the state of Missouri during 1973-1992. Of special interest will be the geographic variations in the trend of lung cancer mortality over the recent past. Marginal posterior distributions are used to examine effects due to spatial correlations and age difference in temporal trends. Numerical results from the Missouri data show that although spatial correlations exist, they do not have a large effect on the estimated mortality rates.
Cancer Immunotherapy Takes a Multi-Faceted Approach to Kick the Immune System into Gear

Cancer accounts for about every fourth death in the United States, with approximately 1,500 people dying each day as a result of this disease. Despite some progress in the last decades, these numbers alone undoubtedly demonstrate the urgent need for new and more efficient treatments. Immunotherapy aims to activate an efficient immune response against tumors or even prevent cancers from occurring in the first place. It is a growing field currently flourishing with several successful trials, some of which have led to the recent approval of new anti-cancer drugs by the Food and Drug Administration (FDA). This review addresses the manifold strategies that immunotherapy has taken in the past and discusses the most recent achievements in the field.
Influence of hepatic load from far-off dry period to early postpartum period on the first postpartum ovulation and accompanying subsequent fertility in dairy cows

The aim of the present study was to investigate nutritional and metabolic parameters during the dry and early postpartum periods of ovulatory and anovulatory cows, as well as their postpartum reproductive performance. Blood samples from 20 multiparous Holstein cows were collected once a week from the far-off dry period to 3 weeks postpartum. Early postpartum (0–3 weeks) ovulation was confirmed using plasma progesterone concentration profiles, and cows were considered ovulatory if they had resumed luteal activity by this point (n = 9), whereas cows that had not were considered anovulatory (n = 11). Data from the ovulatory and anovulatory cows were analyzed separately for the far-off dry period (7–4 weeks prepartum), the close-up dry period (3–1 weeks prepartum), and the early postpartum period (0–3 weeks). Serum gamma-glutamyl transpeptidase activity (far-off, P = 0.065; close-up, P = 0.051; and early postpartum, P = 0.030) and aspartate aminotransferase (close-up, P = 0.050 and early postpartum, P = 0.087) activities were higher in anovulatory than in ovulatory cows. The days open period was longer (P = 0.019) in anovulatory than in ovulatory cows, and the number of artificial inseminations per conception (P = 0.025) was greater. In conclusion, we found that continuously high gamma-glutamyl transpeptidase activities in serum, which may be induced by liver disorders, prevent subsequent ovulation and affect subsequent fertility, even if cows obtain sufficient ovulation-related energy and β-carotene.
Greedy learning of Markov network structure

Markov Random Fields (MRFs), a.k. a. Graphical Models, serve as popular models for networks in the social and biological sciences, as well as communications and signal processing. A central problem is one of structure learning or model selection: given samples from the MRF, determine the graph structure of the underlying distribution. When the MRF is not Gaussian (e.g. the Ising model) and contains cycles, structure learning is known to be NP hard even with infinite samples. Existing approaches typically focus either on specific parametric classes of models, or on the sub-class of graphs with bounded degree; the complexity of many of these methods grows quickly in the degree bound. We develop a simple new ‘greedy’ algorithm for learning the structure of graphical models of discrete random variables. It learns the Markov neighborhood of a node by sequentially adding to it the node that produces the highest reduction in conditional entropy. We provide a general sufficient condition for exact structure recovery (under conditions on the degree/girth/correlation decay), and study its sample and computational complexity. We then consider its implications for the Ising model, for which we establish a self-contained condition for exact structure recovery.
Including Students with Visual Difficulty within Higher Education: Necessary Steps

ABSTRACT The aim of this research study was to investigate the inclusion of students with disabilities studying in Turkish universities. Students with visual difficulty were selected as a case from 24 different universities. A survey with seven dimensions was administered to 73 students, and 12 students were interviewed. Survey and interview findings revealed both progress and, to a larger extent, dissatisfaction with (i) the physical and psychosocial environment of universities; (ii) the way diversity and disability were viewed; (iii) the way support was planned and delivered; (iv) the level and quality of communication and collaboration; (v) the teaching and learning processes; and (vi) the way higher education policy was made and implemented. Findings highlight the need for prioritizing university cultures that are inclusive of students with diverse backgrounds and translation of the inclusiveness into effective practice of providing pedagogical and material support to these students.
Protection against Diarrhea Associated with Giardia intestinalis Is Lost with Multi-Nutrient Supplementation: A Study in Tanzanian Children

Background Asymptomatic carriage of Giardia intestinalis is highly prevalent among children in developing countries, and evidence regarding its role as a diarrhea-causing agent in these settings is controversial. Impaired linear growth and cognition have been associated with giardiasis, presumably mediated by malabsorption of nutrients. In a prospective cohort study, we aim to compare diarrhea rates in pre-school children with and without Giardia infection. Because the study was conducted in the context of an intervention trial assessing the effects of multi-nutrients on morbidity, we also assessed how supplementation influenced the relationship between Giardia and diarrhoea rates, and to what extent Giardia modifies the intervention effect on nutritional status. Methods and Findings Data were collected in the context of a randomized placebo-controlled efficacy trial with 2×2 factorial design assessing the effects of zinc and/or multi-micronutrients on morbidity (n = 612; height-for-age z-score <−1.5 SD). Outcomes measures were episodes of diarrhea (any reported, or with ≥3 stools in the last 24 h) and fever without localizing signs, as detected with health-facility based surveillance. Giardia was detected in stool by enzyme-linked immunosorbent assay. Among children who did not receive multi-nutrients, asymptomatic Giardia infection at baseline was associated with a substantial reduction in the rate of diarrhea (HR 0.32; 0.15–0.66) and fever without localizing signs (HR 0.56; 0.36–0.87), whereas no such effect was observed among children who received multi-nutrients (p-values for interaction 0.03 for both outcomes). This interaction was independent of age, HAZ-scores and distance to the research dispensary. There was no evidence that Giardia modified the intervention effect on nutritional status. Conclusion Although causality of the Giardia-associated reduction in morbidity cannot be established, multi-nutrient supplementation results in a loss of this protection and thus seems to influence the proliferation or virulence of Giardia or associated intestinal pathogens.
Coarse frequency-offset acquisition via subcarrier differential detection for OFDM communications

An effective frequency-offset acquisition technique based on differential detection (DD) for wireless orthogonal frequency-division multiplexing communication is investigated. By exploiting differentially coherent detection involving coherent cross-correlation extraction and subsequent DD, data-aided frequency acquisition assisted by frequency-domain pseudonoise matched filters reduces probabilities of false alarm and miss over a propagation channel with a sufficiently wide coherence bandwidth. Furthermore, the proposed technique uses the inherent frequency diversity with maximum ratio combining and exploits subcarrier-level differential operation and subsequent coherent cross-correlation accumulation. To realize the subcarrier-level DD approach proposed here, the in-lock sequence must be modified by taking self-interference caused by Rayleigh fading into account, and the out-of-lock sequence must be remodeled by means of the discrete Wiener process. Statistical analysis and extensive computer simulation verifies the superiority of the proposed technique
Measurement and Simulation of the Energy Consumption of a WLAN Interface

The energy efficiency of a wireless network interface is a major design issue since mobile devices are often constrained by the battery. The work presented here follows the question which parameter of a WLAN interface can be adjusted to improve energy efficiency.We measured the power consumption of a WLAN interface for various operational modes and parameter settings for a non-impaired Radio Frequency (RF) channel and derived the energy consumed to transmit one bit of payload. The power consumption values were used to parameterize a simulation model of the WLAN interface which was in turn used to investigate the influence of parameters like RF power level, packet size, and data rate on the energy efficiency in case the radio channel becomes worse. Additionally, an analytical energy consumption model for a simple case is presented. Our results indicate, that control of the RF power level and data rate adaption have the highest impact on the energy efficiency.
Ionization of atomic hydrogen and He+ by slow antiprotons

We study the ionization of H(1s), He+(1s) and He+(2s) by antiprotons in the energy range from 0.1 to 500 keV. We adopt a semiclassical single centre close-coupling approach in which the wavefunction for the electron is expanded in a B-spline basis centred on the nucleus of the atom/ion. Comparison is made with existing theoretical calculations and available experimental data. The results are encouraging.
An in-Depth Survey of Visible Light Communication Based Positioning Systems

While visible light communication (VLC) has become the candidate for the wireless technology of the 21st century due to its inherent advantages, VLC based positioning also has a great chance of becoming the standard approach to positioning. Within the last few years, many studies on VLC based positioning have been published, but there are not many survey works in this field. In this paper, an in-depth survey of VLC based positioning systems is provided. More than 100 papers ranging from pioneering papers to the state-of-the-art in the field were collected and classified based on the positioning algorithms, the types of receivers, and the multiplexing techniques. In addition, current issues and research trends in VLC based positioning are discussed.
Feeding and Fasting Signals Converge on the LKB1-SIK3 Pathway to Regulate Lipid Metabolism in Drosophila

LKB1 plays important roles in governing energy homeostasis by regulating AMP-activated protein kinase (AMPK) and other AMPK-related kinases, including the salt-inducible kinases (SIKs). However, the roles and regulation of LKB1 in lipid metabolism are poorly understood. Here we show that Drosophila LKB1 mutants display decreased lipid storage and increased gene expression of brummer, the Drosophila homolog of adipose triglyceride lipase (ATGL). These phenotypes are consistent with those of SIK3 mutants and are rescued by expression of constitutively active SIK3 in the fat body, suggesting that SIK3 is a key downstream kinase of LKB1. Using genetic and biochemical analyses, we identify HDAC4, a class IIa histone deacetylase, as a lipolytic target of the LKB1-SIK3 pathway. Interestingly, we found that the LKB1-SIK3-HDAC4 signaling axis is modulated by dietary conditions. In short-term fasting, the adipokinetic hormone (AKH) pathway, related to the mammalian glucagon pathway, inhibits the kinase activity of LKB1 as shown by decreased SIK3 Thr196 phosphorylation, and consequently induces HDAC4 nuclear localization and brummer gene expression. However, under prolonged fasting conditions, AKH-independent signaling decreases the activity of the LKB1-SIK3 pathway to induce lipolytic responses. We also identify that the Drosophila insulin-like peptides (DILPs) pathway, related to mammalian insulin pathway, regulates SIK3 activity in feeding conditions independently of increasing LKB1 kinase activity. Overall, these data suggest that fasting stimuli specifically control the kinase activity of LKB1 and establish the LKB1-SIK3 pathway as a converging point between feeding and fasting signals to control lipid homeostasis in Drosophila.
Towards Active Tracking of Beating Heart Motion in the Presence of Arrhythmia for Robotic Assisted Beating Heart Surgery

In robotic assisted beating heart surgery, the control architecture for heart motion tracking has stringent requirements in terms of bandwidth of the motion that needs to be tracked. In order to achieve sufficient tracking accuracy, feed-forward control algorithms, which rely on estimations of upcoming heart motion, have been proposed in the literature. However, performance of these feed-forward motion control algorithms under heart rhythm variations is an important concern. In their past work, the authors have demonstrated the effectiveness of a receding horizon model predictive control-based algorithm, which used generalized adaptive predictors, under constant and slowly varying heart rate conditions. This paper extends these studies to the case when the heart motion statistics change abruptly and significantly, such as during arrhythmias. A feasibility study is carried out to assess the motion tracking capabilities of the adaptive algorithms in the occurrence of arrhythmia during beating heart surgery. Specifically, the tracking performance of the algorithms is evaluated on prerecorded motion data, which is collected in vivo and includes heart rhythm irregularities. The algorithms are tested using both simulations and bench experiments on a three degree-of-freedom robotic test bed. They are also compared with a position-plus-derivative controller as well as a receding horizon model predictive controller that employs an extended Kalman filter algorithm for predicting future heart motion.
Comparing beamforming and holography in a homogeneous 2-D scenario

A formal rigorous comparison of the Beamforming and Holographic Imaging techniques are carried out in this paper against a common scenario that enables an analytic description of the scattering phenomenon. This comparison is particularly useful in the area of microwave breast cancer imaging applications, where detection techniques are normally limited to diverse datasets and radar configurations. The comparison is performed in terms of the geometrical characteristics of the point spread function (PSF) which is the image of a point scatterer as seen by the imaging systems. An accurate analysis of each algorithm is carried out in terms of critical parameters such as the operating frequency range and the number of scatterers. This formal analytical approach enables a rigorous performance comparison of these techniques.
Techniques for Interdomain Traffic Engineering

Network operators must have control over the flow of traffic into, out of, and across their networks. However, the Border Gateway Protocol (BGP) does not facilitate common traffic engineering tasks, such as balancing load across multiple links to a neighboring AS or directing traffic to a different neighbor. Solving these problems is difficult because the number of possible changes to routing policies is too large to exhaustively test all possibilities, some changes in routing policy can have an unpredictable effect on the flow of traffic, and the BGP decision process implemented by router vendors limits an operator’s control over path selection. We analyze routing and traffic data from the AT&T backbone to identify ways to use BGP policy for traffic engineering tasks. First, we show how certain BGP policy changes can move traffic in a predictable fashion, despite limited knowledge about the routing policies in neighboring AS’s. Then, we show how operators can gain greater flexibility by relaxing some steps in the BGP decision process and ensuring that neighboring AS’s send consistent advertisements at each peering location. Finally, we show that an operator can manipulate traffic efficiently by changing the routes for a small number of prefixes (or groups of related prefixes) that consistently receive a large amount of traffic. These results can help operators accomplish common traffic engineering tasks using existing BGP features.
Social rejection shares somatosensory representations with physical pain

How similar are the experiences of social rejection and physical pain? Extant research suggests that a network of brain regions that support the affective but not the sensory components of physical pain underlie both experiences. Here we demonstrate that when rejection is powerfully elicited—by having people who recently experienced an unwanted break-up view a photograph of their ex-partner as they think about being rejected—areas that support the sensory components of physical pain (secondary somatosensory cortex; dorsal posterior insula) become active. We demonstrate the overlap between social rejection and physical pain in these areas by comparing both conditions in the same individuals using functional MRI. We further demonstrate the specificity of the secondary somatosensory cortex and dorsal posterior insula activity to physical pain by comparing activated locations in our study with a database of over 500 published studies. Activation in these regions was highly diagnostic of physical pain, with positive predictive values up to 88%. These results give new meaning to the idea that rejection “hurts. ” They demonstrate that rejection and physical pain are similar not only in that they are both distressing—they share a common somatosensory representation as well.
Leader endorsement in social dilemmas: Comparing the instrumental and relational perspectives.

This chapter examines the role of leadership in overcoming social dilemmas within groups. First, based on prior theorising and research we present two alternative perspectives on leader endorsement in social dilemmas, an instrumental and a relational perspective. Next, we systematically compare these perspectives in a series of experiments investigating leadership in social dilemmas created within small groups in the laboratory. The results of our studies suggest that when their personal identity is salient, group members more strongly endorse leaders who are perceived to be instrumental in solving the freerider problem. In contrast, when a social identity is salient, members more strongly endorse leaders who fulfil their relational needs. Based on these findings we propose a differential needs model of leader endorsement in social dilemmas.
Downregulation of miR-101 contributes to epithelial-mesenchymal transition in cisplatin resistance of NSCLC cells by targeting ROCK2

Chemoresistance and epithelial-mesenchymal transition (EMT) in cancer are linked phenomena. EMT contributes to chemoresistance, however, little is known about whether chemotherapy can induce EMT in cancer cells. Here, we found that miR-101 expression was downregulated in cisplatin-resistant non-small cell lung cancer (NSCLC) cells. Restoration of miR-101 expression inhibited EMT and increased the sensitivity of cisplatin-resistant NSCLC cells to cisplatin in vitro by targeting ROCK2. Furthermore, ROCK2 protein level was inversely correlated with miR-101 level in NSCLC tissue samples. Kaplan-Meier analysis revealed that low miR-101 expression in NSCLC was correlated with poor survival time. In summary, our results provide novel mechanistic insights into the role of miR-101/ROCK2 signaling in the cisplatin resistance of NSCLC cells. Targeting of miR-101 is a potential therapeutic approach for NSCLC.
Probabilistic short-term wind power forecasting based on kernel density estimators

Short-term wind power forecasting tools have been developed for some time. The majority of such tools usually provide single-valued (spot) predictions. Such predictions are however often not adequate when the aim is decision-making under uncertainty. In that case there is a clear requirement by end-users to have additional information on the uncertainty of the predictions for performing efficiently functions such as reserves estimation, unit commitment, trading in electricity markets, a.o. In this paper, we propose a method for producing the complete predictive probability density function (PDF) for each time step of the prediction horizon based on the kernel density estimation technique. The performance of the proposed approach is demonstrated using real data from several wind farms. Comparisons to state-of-the-art methods from both outside and inside the wind power forecasting community are presented illustrating the performances of the proposed method.