Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between smoking, insulin resistance and β‐cell function in a North‐western First Nation

Aims Aboriginal peoples have a high prevalence of smoking and are at major risk for diabetes. The role of insulin resistance vs. compromised β‐cell function in the link between smoking and glycaemic disease is not clear. This study tested whether relations between insulin resistance and β‐cell function differ between current smokers, former smokers and non‐smokers, and if having diabetes modifies smoking‐related effects.
On the Undecidability of Probabilistic Planning and Infinite-Horizon Partially Observable Markov Decision Problems

We investigate the computability of problems in probabilistic planning and partially observable infinite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic finite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there exists a plan with success probability exceeding a desirable threshold. Analogous policy-existence problems for partially observable infinite-horizon Markov decision processes under discounted and undiscounted total reward models, average-reward models, and state-avoidance models are all shown to be undecidable. The results apply to corresponding approximation problems as well.
Liposome bupivacaine (EXPAREL®) for extended pain relief in patients undergoing ileostomy reversal at a single institution with a fast-track discharge protocol: an IMPROVE Phase IV health economics trial

Background Postoperative opioid use following ileostomy reversal procedures contributes to postoperative ileus. We assessed the impact of a liposome bupivacaine-based, opioid-sparing multimodal analgesia regimen versus a standard opioid-based analgesia regimen on postsurgical opioid use. We also assessed health economic outcomes in patients undergoing ileostomy reversal at our institution, which employs an enhanced recovery discharge protocol. Methods In this single-center, open-label study, patients undergoing ileostomy reversal received postsurgical pain therapy via multimodal analgesia that included a single intraoperative administration of liposome bupivacaine or opioid-based patient-controlled analgesia (PCA) with intravenous morphine or hydromorphone. Rescue analgesia (intravenous [IV] opioids and/or oral opioid + acetaminophen) was available to all patients. Primary efficacy measures included postsurgical opioid use, hospital length of stay (LOS), and hospitalization costs. Secondary measures included: time to first rescue opioid use; patient satisfaction with analgesia; additional medical intervention; and opioid-related adverse events. Results Forty-three patients were enrolled and met eligibility criteria (IV opioid PCA group = 20; liposome bupivacaine-based multimodal analgesia group = 23). Postsurgical opioid use was significantly less in the multimodal analgesia group compared with the IV opioid PCA group (mean [standard deviation]: 38 mg [46 mg] versus 68 mg [47 mg]; P = 0.004). Postsurgical LOS between-group differences (median: 3.0 days versus 3.8 days) and geometric mean hospitalization costs (US $6,611 versus US$6,790) favored the multimodal analgesic group but did not achieve statistical significance. Median time to first opioid use was 1.1 hours versus 0.7 hours in the multimodal analgesia and IV opioid PCA groups, respectively; P = 0.035. Two patients in the multimodal analgesia group and one in the IV opioid PCA group experienced opioid-related adverse events. Conclusion A liposome bupivacaine-based multimodal analgesic regimen reduced postoperative opioid consumption in patients undergoing ileostomy reversal under a fast-track discharge protocol. A reduction of 21% in LOS (0.8 days) was noted which, although not statistically significant, may be considered clinically meaningful given the already aggressive fast-track discharge program.
Over-the-Air Implementation of Uplink NOMA

Though the concept of non-orthogonal multiple access (NOMA) was proposed several years ago, the performance of uplink NOMA has only been verified in theory, but not in practice. This paper presents an over-the-air implementation of a uplink NOMA system, while providing solutions to most common practical problems, i.e., carrier frequency offset (CFO) synchronization, time synchronization, and channel estimation. The implemented CFO synchronization method adopts the primary synchronization signal (PSS) of LTE. Also, we design a novel preamble for each uplink user, and it is appended to every frame before it is transmitted through the air. This preamble will be used for time synchronization and channel estimation at the BS. Also, a low-complexity, iterative linear minimum mean squared error (LMMSE) detector has been implemented for multi- user decoding. The paper also validates the proposed architecture numerically, as well as experimentally.
Learning Similarities for Rigid and Non-rigid Object Detection

In this paper, we propose an optimization method for estimating the parameters that typically appear in graph-theoretical formulations of the matching problem for object detection. Although several methods have been proposed to optimize parameters for graph matching in a way to promote correct correspondences and to restrict wrong ones, our approach is novel in the sense that it aims at improving performance in the more general task of object detection. In our formulation, similarity functions are adjusted so as to increase the overall similarity among a reference model and the observed target, and at the same time reduce the similarity among reference and "non-target" objects. We evaluate the proposed method in two challenging scenarios, namely object detection using data captured with a Kinect sensor in a real environment, and intrinsic metric learning for deformable shapes, demonstrating substantial improvements in both settings.
CVS: a Correlation-Verification based Smoothing technique on information retrieval and term clustering

As information volume in enterprise systems and in the Web grows rapidly, how to accurately retrieve information is an important research area. Several corpus based smoothing techniques have been proposed to address the data sparsity and synonym problems faced by information retrieval systems. Such smoothing techniques are often unable to discover and utilize the correlations among terms.We propose CVS, a Correlation-Verification based Smoothing method, that considers co-occurrence information in smoothing. Strongly correlated terms in a document are identified by their co-occurrence frequencies in the document. To avoid missing correlated terms with low co-occurrence frequencies but specific to the theme of the document, the joint distributions of terms in the document are compared with those in the corpus for statistical significance.A common approach to apply corpus based smoothing techniques to information retrieval is by refining the vector representations of documents. This paper investigates the effects of corpus based smoothing on information retrieval by query expansion using term clusters generated from a term clustering process. The results can also be viewed in light of the effects of smoothing on clustering.Empirical studies show that our approach outperforms previous corpus based smoothing techniques. It improves retrieval effectiveness by 14.6%. The results demonstrate that corpus based smoothing can be used for query expansion by term clustering.
Bayesian Generalized Kernel Mixed Models

We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a reproducing kernel. We place a mixture of a point-mass distribution and Silverman's g-prior on the regression vector of a generalized kernel model (GKM). This mixture prior allows a fraction of the components of the regression vector to be zero. Thus, it serves for sparse modeling and is useful for Bayesian computation. In particular, we exploit data augmentation methodology to develop a Markov chain Monte Carlo (MCMC) algorithm in which the reversible jump method is used for model selection and a Bayesian model averaging method is used for posterior prediction. When the feature basis expansion in the reproducing kernel Hilbert space is treated as a stochastic process, this approach can be related to the Karhunen-Loeve expansion of a Gaussian process (GP). Thus, our sparse modeling framework leads to a flexible approximation method for GPs.
Atoms of Mind: The "Ghost in the Machine" Materializes

1. The Quest. - 2. Thinking About Thinking. - 3. Kinds of Mind. - 4. Carriers and Repositories of Thought. - 5. Specific Thought Mechanisms & Examples. - 6. Global Interactions. - 7. On the Nature of Consciousness. - 8. Theories of Consciousness. - 9. Conclusions.
A spectral model for multimodal redshift estimation

We present a physically inspired model for the problem of redshift estimation. Typically, redshift estimation has been treated as a regression problem that takes as input magnitudes and maps them to a single target redshift. In this work we acknowledge the fact that observed magnitudes may actually admit multiple plausible redshifts, i.e. the distribution of redshifts explaining the observed magnitudes (or colours) is multimodal. Hence, employing one of the standard regression models, as is typically done, is insufficient for this kind of problem, as most models implement either one-to-one or many-to-one mappings. The observed multimodality of solutions is a direct consequence of (a) the variety of physical mechanisms that give rise to the observations, (b) the limited number of measurements available and (c) the presence of noise in photometric measurements. Our proposed solution consists in formulating a model from first principles capable of generating spectra. The generated spectra are integrated over filter curves to produce magnitudes which are then matched to the observed magnitudes. The resulting model naturally expresses a multimodal posterior over possible redshifts, includes measurement uncertainty (e.g. missing values) and is shown to perform favourably on a real dataset.
Splenic sepsis in sickle cell disease

We describe two patients with sickle cell disease (SCD) who developed infections situated in the spleen. One patient had a splenic abscess and there was strong clinical evidence for an infected splenic infarct in the second patient. SCD predisposes to splenic infection because of functional hyposplenism, defective phagocyte function and splenic infarction. Splenic infections can occur in patients who might be considered to have an absent spleen and the diagnosis of splenic abscess should be considered in individuals with SCD who present with fever and abdominal pain.
Frequency reconfigurable hourglass shaped microstrip antenna

A compact hourglass shaped microstrip antenna having frequency reconfiguring ability from 2.362 GHz to 2.525 GHz range is proposed. A varactor diode is used in the gap between the two segments of ground plane in order to achieve frequency agility. By varying the capacitance of the varactor diode, six operating frequencies 2.395 GHz, 2.435 GHz, 2.445 GHz, 2.455 GHz, 2.47 GHz and 2.495 GHz are achieved with impedance bandwidth of 2.92%, 2.42%, 2.46%, 2.40%, 2.45%, 2.45% and 2.44% respectively. The antenna exhibits stable omnidirectional radiation patterns with realized gain varying from 2.55 dB-1.05 dB for all the bands. These features make the antenna suitable for different wireless application standards like Wi-Fi (2.412 GHz-2.483 GHz), Bluetooth (2.402 GHz-2.48 GHz), WiMax (2.3 GHz-2.4 GHz) etc. The proposed antenna has compact dimensions of 0. 44λ×0. 25λ×0. 013λ at 2.4 GHz frequency which is suitable for many handheld devices.
Diversification and phylogeographic structure in widespread Azteca plant‐ants from the northern Neotropics

The Neotropical myrmecophytic tree Cordia alliodora hosts symbiotic Azteca ants in most of its widespread range. The taxonomy of the genus Azteca is notoriously difficult, which has frequently obscured species identity in ecological studies. We used sequence data from one mitochondrial and four nuclear loci to infer phylogenetic relationships, patterns of geographic distribution, and timing of diversification for 182 colonies of five C. alliodora‐dwelling Azteca species from Mexico to Colombia. All morphological species were recovered as monophyletic, but we identified at least five distinct genetic lineages within the most abundant and specialized species, Azteca pittieri. Mitochondrial and nuclear data were concordant at the species level, but not within species. Divergence time analyses estimated that C. alliodora‐dwelling Azteca shared a common ancestor approximately 10–22 million years ago, prior to the proposed arrival of the host tree in Middle America. Diversification in A. pittieri occurred in the Pleistocene and was not correlated with geographic distance, which suggests limited historical gene flow among geographically restricted populations. This contrasts with the previously reported lack of phylogeographic structure at this spatial scale in the host tree. Climatic niches, and particularly precipitation‐related variables, did not overlap between the sites occupied by northern and southern lineages of A. pittieri. Together, these results suggest that restricted gene flow among ant populations may facilitate local adaptation to environmental heterogeneity. Differences in population structure between the ants and their host trees may profoundly affect the evolutionary dynamics of this widespread ant–plant mutualism.
A data mining approach to financial time series modelling and forecasting

This paper describes one of the relatively new data mining techniques that can be used to forecast the foreign exchange time series process. The research aims to contribute to the development and application of such techniques by exposing them to difficult real-world (non-toy) data sets. The results reveal that the prediction of a Radial Basis Function Neural Network model for forecasting the daily $US/$NZ closing exchange rates is significantly better than the prediction of a traditional linear autoregressive model in both directional change and prediction of the exchange rate itself. We have also investigated the impact of the number of model inputs (model order), the number of hidden layer neurons and the size of training data set on prediction accuracy. In addition, we have explored how the three different methods for placement of Gaussian radial basis functions affect its predictive quality and singled out the best one. Copyright  2001 John Wiley & Sons, Ltd.
Solar PV and Battery Storage Integration using a New Configuration of a Three-Level NPC Inverter With Advanced Control Strategy

In this paper, a novel configuration of a three-level neutral-point-clamped (NPC) inverter that can integrate solar photovoltaic (PV) with battery storage in a grid-connected system is proposed. The strength of the proposed topology lies in a novel, extended unbalance three-level vector modulation technique that can generate the correct ac voltage under unbalanced dc voltage conditions. This paper presents the design philosophy of the proposed configuration and the theoretical framework of the proposed modulation technique. A new control algorithm for the proposed system is also presented in order to control the power delivery between the solar PV, battery, and grid, which simultaneously provides maximum power point tracking (MPPT) operation for the solar PV. The effectiveness of the proposed methodology is investigated by the simulation of several scenarios, including battery charging and discharging with different levels of solar irradiation. The proposed methodology and topology is further validated using an experimental setup in the laboratory.
Automating, monitoring, and control of an ICE based micro-CCHP system using LabVIEW and Android

A methodology to automate and control a small-scale combined heat and power system (micro-CHP) is proposed. The contribution of this design is to extend the original plant toward micro-CHP system modeling, thus allowing flexible and efficient system through graphical programming. The automation involves the synthesized system analysis; thereby, human intervention is reduced. It builds on LabVIEW™ software that takes the model architecture to monitor and control de plant. Measured signals and parameters (SQL database) managed by LabVIEW™ are used to issue remote control communication. An Android application was developed to communicate with the database. The integration methodology of automation, monitoring and control energy variables in real-time may be extended to study failures and possible improvements on micro-CHP systems.
Rethinking Resilience from Indigenous Perspectives

The notions of resilience that have emerged in developmental psychology and psychiatry in recent years require systematic rethinking to address the distinctive cultures, geographic and social settings, and histories of adversity of indigenous peoples. In Canada, the overriding social realities of indigenous peoples include their historical rootedness to a specific place (with traditional lands, communities, and transactions with the environment) and the profound displacements caused by colonization and subsequent loss of autonomy, political oppression, and bureaucratic control. We report observations from an ongoing collaborative project on resilience in Inuit, Métis, Mi'kmaq, and Mohawk communities that suggests the value of incorporating indigenous constructs in resilience research. These constructs are expressed through specific stories and metaphors grounded in local culture and language; however, they can be framed more generally in terms of processes that include: regulating emotion and supporting adaptation through relational, ecocentric, and cosmocentric concepts of self and personhood; revisioning collective history in ways that valorize collective identity; revitalizing language and culture as resources for narrative self-fashioning, social positioning, and healing; and renewing individual and collective agency through political activism, empowerment, and reconciliation. Each of these sources of resilience can be understood in dynamic terms as emerging from interactions between individuals, their communities, and the larger regional, national, and global systems that locate and sustain indigenous agency and identity. This social–ecological view of resilience has important implications for mental health promotion, policy, and clinical practice.
Swiss ball abdominal crunch with added elastic resistance is an effective alternative to training machines.

BACKGROUND Swiss ball training is recommended as a low intensity modality to improve joint position, posture, balance, and neural feedback. However, proper training intensity is difficult to obtain during Swiss ball exercises whereas strengthening exercises on machines usually are performed to induce high level of muscle activation. PURPOSE To compare muscle activation as measured by electromyography (EMG) of global core and thigh muscles during abdominal crunches performed on Swiss ball with elastic resistance or on an isotonic training machine when normalized for training intensity. METHODS 42 untrained individuals (18 men and 24 women) aged 28-67 years participated in the study. EMG activity was measured in 13 muscles during 3 repetitions with a 10 RM load during both abdominal crunches on training ball with elastic resistance and in the same movement utilizing a training machine (seated crunch, Technogym, Cesena, Italy). The order of performance of the exercises was randomized, and EMG amplitude was normalized to maximum voluntary isometric contraction (MVIC) EMG. RESULTS When comparing between muscles, normalized EMG was highest in the rectus abdominis (P<0.01) and the external obliques (P<0.01). However, crunches on Swiss ball with elastic resistance showed higher activity of the rectus abdominis than crunches performed on the machine (104±3.8 vs 84±3.8% nEMG respectively, P<0.0001). By contrast, crunches performed on Swiss ball induced lower activity of the rectus femoris than crunches in training machine (27±3.7 vs 65±3.8% nEMG respectively, P<0.0001) Further, gender, age and musculoskeletal pain did not significantly influence the findings. CONCLUSION Crunches on a Swiss ball with added elastic resistance induces high rectus abdominis activity accompanied by low hip flexor activity which could be beneficial for individuals with low back pain. In opposition, the lower rectus abdominis activity and higher rectus femoris activity observed in machine warrant caution for individuals with lumbar pain. Importantly, both men and women, younger and elderly, and individuals with and without pain benefitted equally from the exercises.
Futures hedging using clusters with dynamic behavior of market fluctuation

In this study, a novel procedure of time series dynamic behaviors clustering is proposed to improve the accuracy of minimum -variance optimal hedge ratio (OHR) estimation for future hedging. The dynamic behaviors of market fluctuation are extracted by measurement of variances, covariance, price spread, and their first and second differences. The behaviors with similar patterns are clustered using a growing hierarchical self-organizing map (GHSOM). The observations for OHR estimation are collected based on the hierarchical cluster structure and processed by within-cluster resampling. The spots and futures of the Taiwan Weighted Index (TWI) are adopted to demonstrate that the futures hedge effectiveness can be significantly improved.
Efficacy of rifaximin versus lactulose for reducing the recurrence of overt hepatic encephalopathy and hopitalizations in cirrhosis.

UNLABELLED Both rifaximin and lactulose have been reported to be effective for maintenance of remission from hepatic encephalopathy (HE) in patients with cirrhosis. The aim of this study was to compare the efficacy of different treatment strategies for preventing recurrences and HE-related hospitalizations. MATERIALS AND METHODS Seventy-eight cirrhotic patients who recovered from HE were grouped according to one of the following therapies: rifaximin intermittently 14 days/month (RI- group), rifaximin 400 mg three times daily (RD-group) and lactulose 30 to 60 ml in 2 or 3 divided doses daily (L-group) for a 6-month period. The follow-up lasted 12 months. A Kaplan-Meier analysis was performed to determine the probability of developing recurrent overt HE episodes. The frequencies of HE- related hospitalizations in the three groups were evaluated comparatively. RESULTS Over a 12-month follow-up period, 10 (26.31 %) of 38 patients in the RI-group, 7 (25%) of 28 in the RD-group and 4 (33.33 %) of 12 in the L-group experienced recurrent bouts of HE, the differences not being significant. More L-group patients experienced more severe episodes of overt HE in spite of mild or moderate disease. In the rifaximin groups overt HE episodes were similarly frequent, and the severity of bouts was associated with Child-Pugh score. Fewer hospitalizations were reported in the rifaximin groups. CONCLUSIONS According to our data, rifaximin and lactulose are equally effective for the maintenance of remission from overt HE. However, rifaximin is superior for reducing the risk of HE-related hospitalization.