Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mobile Phone–Based Telemonitoring Program for Heart Failure Patients After an Incidence of Acute Decompensation (Medly-AID): Protocol for a Randomized Controlled Trial

Background Patients with heart failure (HF) are at the highest risk for hospital readmissions during the first few weeks after discharge when patients are transitioning from hospital to home. Telemonitoring (TM) for HF management has been found to reduce mortality risk and hospital readmissions if implemented appropriately; however, the impact of TM targeted for patients recently discharged from hospital, for whom TM might have the biggest benefit, is still unknown. Medly, a mobile phone–based TM system that is currently being used as a standard of care for HF at a large Canadian hospital, may be an effective tool for the management of HF in patients recently discharged from hospital. Objective The objective of the Medly-After an Incidence of acute Decompensation (Medly-AID) trial is to determine the effect of Medly on the self-care and quality of life of patients with HF who have been recently discharged from hospital after an HF-related decompensation. Methods A multisite multimethod randomized controlled trial (RCT) will be conducted at 2 academic hospitals and at least one community hospital to evaluate the impact of Medly-enabled HF management on the outcomes of patients with HF who had been hospitalized for HF-related decompensation and discharged during the 2 weeks before recruitment. The trial will include 144 participants with HF (74 in each control and intervention groups). Control patients will receive standard of care, whereas patients in the intervention group will receive standard of care and Medly. Specifically, patients in the intervention group will record daily weight, blood pressure, and heart rate and answer symptom-related questions via the Medly app. Medly will generate automated patient self-care messages such as to adjust diuretic medications, based on the rules-based algorithm personalized to the individual patient, and send real-time alerts to their health care providers as necessary. All patients will be followed for 3 months. Primary outcome measures are self-care and quality of life as measured through the validated questionnaires Self-Care of Heart Failure Index, EQ-5D-5L, and the Kansas City Cardiomyopathy Questionnaire-12. Secondary outcome measures for this study include cost of health care services used and health outcomes. Results Patient recruitment began in November 2018 at the Sunnybrook Health Sciences Centre, with a total of 35 participants recruited by July 30, 2019 (17 in the intervention group and 18 in the control group). The final analysis is expected to occur in the fall of 2020. Conclusions This RCT will be the first to assess the effectiveness of the Medly TM system for use following discharge from hospital after a HF-related decompensation. Trial Registration ClinicalTrials.gov NCT03358303; https://clinicaltrials.gov/ct2/show/NCT03358303 International Registered Report Identifier (IRRID) DERR1-10.2196/15753
An advanced in vitro model to assess glaucoma onset.

Glaucoma is the second leading cause of blindness worldwide. Currently glaucoma treatments aim to lower IOP by decreasing aqueous humor production or increasing aqueous humor outflow through pharmacological approaches or trabeculectomy. However, the lack of effective cure requires new therapeutic strategies. In this regard, we compared the biological responses of a three-dimensional trabecular meshwork (TM) model with or w/o perfusion bi oreactor technology to better understand the early molecular changes induced by prolonged oxidative stress condition. Therefore, we obtained standard 3D cultures from the embedment of TM cells in Matrigel and they were cultured both under static and dynamic conditions. In this regard, we demonstrated that the constant medium nutrients supply, conferred by perfusion bioreactor, improved the adaptive behavior to chronic oxidative stress of 3D TM cultures via offsetting pathway activation.
Through-wall Imaging of Conductors by Transverse Electric Wave Illumination

ABSTRACT A novel method for through-wall imaging (TWI) illuminated by the transverse electric (TE) waves is presented. Most microwave inverse scattering algorithms developed are for transverse magnetic (TM) wave illumination in which vector problem can be simplified to a scalar one, which less works have been reported on the more complicated TE case. In the TE case, the presence of polarization charges makes the inverse problem more nonlinear. This paper uses the self-adaptive dynamic differential evolution (SADDE) algorithm to recover the shapes of the two dimensional conducting cylinders by TE plane wave illumination. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equation is derived and the imaging problem is reformulated into optimization problem. The SADDE algorithm is employed to find out the global extreme solution of the object function. Numerical results show that the shapes of the conductor are well reconstructed. In addition, the effect of Gaussian noise on the reconstruction is investigated.
HMC: Model Checking for Hardware Memory Models

Stateless Model Checking (SMC) is an effective technique for verifying safety properties of a concurrent program by systematically exploring all of its executions. While SMC has been extended to handle hardware memory models like x86-TSO, it does not adequately support models that allow load buffering behaviours, such as the POWER, ARMv7, ARMv8, and RISC-V models. Existing SMC tools either do not consider such behaviours in the name of efficiency, or do not scale so well due to the extra complexity induced by these behaviours. We present HMC, the first efficient SMC algorithm that can verify programs under all hardware memory models in a sound, complete, and optimal fashion. We implement HMC in a tool for C programs, and show that it outperforms the state-of-the-art tools that can handle similar memory models. We demonstrate the efficiency of HMC by verifying code currently employed in production.
Exploring the Impact of Dissolved Organic Carbon on Bluegill (Lepomis macrochirus) Behavior: Why Live Subjects are Important for Scientific Study

Global browning in aquatic systems is a phenomenon, augmented by anthropogenic climate change, that is caused by increasing concentrations of dissolved carbon, making bodies of water brown, decreasing visibility. Dissolved organic carbon (DOC) is a term used to describe the decomposed organic matter from plant and animal tissue that incorporates into bodies of water. Higher levels of DOC alter the absorbance of solar radiation and heat distribution throughout a water column. Organisms living in the water column, especially visual predators, may be impacted, potentially exhibiting altered behaviors to adapt to these variations in visibility and temperature. The objective of this study was to explore the effects of varying concentrations of DOC upon the aggressive and explorative behaviors of bluegill (Lepomis macrochirus) fish. Bluegill, caught from Bay Lake on the University of Notre Dame Environmental Research Center property, were kept in nine mesocosms containing three different concentrations of dissolved organic carbon. After an acclimation period of five weeks, two behavioral assays focusing on aggression and boldness/exploration were conducted upon each fish. I found that latency time was not significantly related to DOC concentration for both the aggression and boldness/exploration assays (p=0.4658 and p=0.2294, respectively). Due to minimal replication, these findings highlight a need for further studies both of bluegill as well as expansion to other fish species to determine the impacts of increasing DOC concentrations on fish behavior.
Next Steps for Human-Computer Integration

Human-Computer Integration (HInt) is an emerging paradigm in which computational and human systems are closely interwoven. Integrating computers with the human body is not new. however, we believe that with rapid technological advancements, increasing real-world deployments, and growing ethical and societal implications, it is critical to identify an agenda for future research. We present a set of challenges for HInt research, formulated over the course of a five-day workshop consisting of 29 experts who have designed, deployed and studied HInt systems. This agenda aims to guide researchers in a structured way towards a more coordinated and conscientious future of human-computer integration.
Ideal versions of the Bolzano-Weierstrass property

Let I, J be ideals on ? , we say that a space X has (I,J)-BW property if every sequence in X contains a J-converging subsequence indexed by an I-positive set. This is a common generalization ofBWlike properties types. By modifying some classic notions, we obtain some characterizations of (I,J)-BW property.
Rethinking Sanctions Efficiency evidence from 205 Cases of the u . S . Government enforcement actions against Business

The article revisits the issue of economic sanctions efficiency. It concentrates on changes in business behavior when it is affected by governmental enforcement actions. The empirical groundwork is composed of 205 cases of U.S. governmental investigations vis a vis business in 2009-2019. The article tests two major hypotheses. The first one is about the measure of rationality of business when it violates existing sanctions regulations. The second one is about changes in business behavior during and after the investigation. Descriptive statistics shows that violations are rather not planned in advance. Reckless behavior is much more frequent than willful one. However, the data confirm the hypothesis about the transformation of business behavior during and after the OFAC investigation. This is an indicator of the high efficiency of Ivan N. Timofeev, Ph.D. (Political Science) MGIMO University, Moscow, Russia Associate Professor; Russian International Affairs Council, Moscow, Russia
Bioluminescence resonance energy transfer (BRET) - based nanostructured biosensor for detection of glucose

Bioluminescence resonance energy transfer (BRET) is a distance dependent, non-radiative energy transfer, which uses a bioluminescent protein to excite an acceptor through resonance energy transfer. In this thesis, BRET technology is incorporated into a sensor comprised of a recombinant protein and quantum dots. The recombinant protein, which includes the bioluminescent protein, Renilla luciferase (Rluc), is used as the donor molecule and cadmium tellurium quantum dots as the acceptor molecules. Separating the donor-acceptor pair is a recombinant protein, glucose binding protein, which changes conformation upon binding glucose and brings the pair closer together, thus allowing BRET to occur. Optimization of the BRET sensor was investigated by evaluating different ratios of the donor and acceptor, changes in the bioconjugation process, and different glucose concentrations. The intensity of bioluminescence is a function of the ratio between the quantum dots to protein, which ranges from 1:6 to 0.0156:1, EDC ratio to quantum dots, conjugation time, and concentration of glucose ranging from 2 μM to 0.1 M. In addition, the performance of the sensor on a solid substrate was evaluated. This sensor promises to offer an alternative to traditional blood glucose sensing. a alternative measuring blood glucose by utilizing A newly designed sensor using a technology known as bioluminescence resonance (BRET) developed with the hopes that sensing methods. BRET occurs when a light emitting transfers light another emitting protein. The second Testing of the that ratio of the protein to quantum dots be ideal. the sensor detect variations of glucose levels ranging between 2 µM to 0.1 M, which is sufficient to detect levels of glucose in both tear samples and blood samples. The sensor was also tested while deposited on a solid substrate. The results indicate the sensor may be promising as an alternative to traditional blood glucose sensing.
Evolving trends in biopolymer based drug delivery systems : An overview D Review

An efficient drug delivery system deals with the administration of a drug to its target site, to achieve the desired therapeutic effect. The drawbacks with conventional drug delivery systems had led to the search for efficient drug formulations and new routes of drug delivery. Modern day drug delivery systems focus on improving the efficacy of the drugs by modifying the carriers and increasing the bioavailability. Also the newly emerging drug delivery systems (DDS) tend to target the pharmacodynamics and pharmacokinetics of the pharmaceutical compound. Over the past few decades, biopolymer based drug delivery systems have been gaining attention. The use of biopolymers as drug carriers has been attributed to their biodegradability and their non-toxic nature. This review focuses on the different biopolymer based drug delivery systems used recently.
Exploring Best Arm with Top Reward-Cost Ratio in Stochastic Bandits

The best arm identification problem in multi-armed bandit model has been widely applied into many practical applications, such as spectrum sensing, online advertising, and cloud computing. Although lots of works have been devoted into this area, most of them do not consider the cost of pulling actions, i.e., a player has to pay some cost when she pulls an arm. Motivated by this, we study a ratio-based best arm identification problem, where each arm is associated with a random reward as well as a random cost. For any δ ∈ (0,1), with probability at least 1−δ, the player aims to find the optimal arm with the largest ratio of expected reward to expected cost using as few samplings as possible. To solve this problem, we propose three algorithms: 1) a genie-aided algorithm GA; 2) the successive elimination algorithm with unknown gaps SEUG; 3) the successive elimination algorithm with unknown gaps and variance information SEUG-V, where gaps denote the differences between the optimal arm and the suboptimal arms. We show that for all three algorithms, the sample complexities, i.e., the pulling times for all arms, grow logarithmically as $\frac{1}{\delta }$ increases. Moreover, compared to existing works, the running of our elimination-type algorithms is independent of the arm-related parameters, which is more practical. In addition, we also provide a fundamental lower bound for sample complexities of any algorithms under Bernoulli distributions, and show that the sample complexities of the proposed three algorithms match that of the lower bound in the sense of $\log \frac{1}{\delta }$. Finally, we validate our theoretical results through numerical experiments.
Imaging anaerobic methane oxidation at environs near Woods Hole

CARD-FISH was performed to determine the presence of S-DAMO and NDAMO in the Cape Cod Area. Samples were taken from marine sediments at Trunk River and Great Sippewissett Salt Marsh for S-DAMO studies, while freshwater samples were collected from Cedar Swamp and the Cape Cod Aquifer for N-DAMO. Comparisons of the epifluorescence micrographs found at the marine sites indicate that ANME/SRB consortia are more prevalent at Great Sippewissett Salt Marsh and more free-living members of the ANME clades are found at Trunk River. On comparing Cedar Swamp and the Cape Cod Aquifer, it seems that the M. oxyfera at the Cape Cod Aquifer are in consortia with methanogenic archaea, and that those at Cedar Swamp are primarily free-living.
Diagnosis of recurrent glioma with SPECT and iodine-123-α-methyl tyrosine

UNLABELLED: Iodine-123-alpha-methyl tyrosine (IMT) allows the investigation of amino acid transport rate in brain neoplasms. It was the aim of this study to evaluate the potential of IMT-SPECT to diagnose the recurrence of gliomas after primary therapy. METHODS: Using a triple-headed SPECT camera, the cerebral uptake of IMT was determined in 27 patients 22 mo, on average, after surgical removal of a primary brain tumor. Eighteen patients had suffered from high-grade gliomas, and nine had suffered from low-grade tumors. Four patients were examined before and after surgical revision of a presumed tumor recurrence. A total of 31 studies were evaluated. The final diagnosis was based on prospective clinicopathological follow-up. Recurrence was diagnosed in 23 cases, with marked clinical deterioration occurring 3.1 mo, on average, after SPECT, and was confirmed by histopathology in 14 instances. Eight cases were free of recurrence, as evidenced by inconspicuous clinical follow-up, ranging from 6 mo to 17 mo after SPECT in seven cases, and by clinical course and histopathology in the remaining subject. RESULTS: Patients with recurrence had significantly higher ratios of IMT uptake in the tumor area to that in a background region than did patients without recurrence (2.27 +/- 0.59 compared to 1.47 +/- 0.29; p < 0.002). The best cutoff level of the IMT uptake ratio in the differentiation between recurrence and benign posttherapeutic lesion was 1.8. Using this study-specific discrimination threshold, the sensitivity and specificity of IMT-SPECT for detecting glioma recurrence were 18 of 23 (78%) and 8 of 8 (100%), respectively. The area under the binormal receiver operating characteristic curve, fitted to the data, was 0.90 +/- 0.06. CONCLUSION: Iodine-123-alpha-methyl tyrosine-SPECT is a promising new tool in the follow-up of patients with gliomas after primary therapy.
A "User-Knowledge-Product" Co-Creation Cyberspace Model for Product Innovation

To benefit from users’ co-creation knowledge in online communities, enterprises need effective methods to discover and manage co-creation users and knowledge as suggested in existing research. However, the existing methods still have their own limitations when analysing different relationships and networks. Therefore, first, this paper proposes a co-creation cyberspace super-network model for product innovation from a “user-knowledge-product” perspective to integrate the co-creation information of users, knowledge, and products. Second, to increase the accuracy of discovering, managing, and using the co-creation knowledge, three subnetworks including co-creation user network, co-creation knowledge network, and co-creation product network as well as the relationships among them are constructed and improved. Third, a well-known co-creation community in China is selected as a case to verify the feasibility and validity of the proposed model for enterprise’s product innovation. Three subnetworks and the mapping relationships among them are constructed and visualized based on the introduced User-Knowledge-Product Cyberspace model. The results from the case study validate the co-creation cyberspace constructed in this paper and provide enterprises with a comprehensive and detailed integration framework analysis model. Hence, the enterprises can use this model for user discovery, product innovation knowledge mining, and dynamic innovation knowledge basement and forecast hotspot trend in co-creation communities.
Inquiry-based learning put to test: long-term effects of the Swedish STC program

We quantitatively evaluate the effects in grade 9 on content and process skills in sciences, from participation in the Swedish science and technology for children program, the NTA program. Students predominantly participate in this program during grades 1-6. Our outcome measures are scores and grades on nationwide tests, and course grades, in biology, chemistry and physics, 2009-2010. A nationally representative random sample of almost 16 000 test-taking students is coupled with multi-level information about the NTA, and background factors. Non-random selection into the program is addressed by propensity score analysis. The matched sample of pairs of NTA participants and non-participants, determined by the propensity scores, is quite well behaved, although there are significant, but small, differences for some of the matching covariates. We find significantly positive effects on test scores (average increase 16.4%) and test grades in physics, but not in biology and chemistry. No significant effects are found for course grades.
Analyzing Students' Synergistic Learning Processes in Physics and CT by Collaborative Discourse Analysis

: The introduction of computational modeling into science curricula has been shown to benefit students’ learning, however the synergistic learning processes that contribute to these benefits are not fully understood. We study students’ synergistic learning of physics and computational thinking (CT) through their actions and collaborative discourse as they develop computational models in a visual block-structured environment. We adopt a case study approach to analyze students synergistic learning processes related to stopping conditions, initialization, and debugging episodes. Our findings show a pattern of evolving sophistication in synergistic reasoning for model-building activities.
DRAIN: Deadlock Removal for Arbitrary Irregular Networks

Correctness is a first-order concern in the design of computer systems. For multiprocessors, a primary correctness concern is the deadlock-free operation of the network and its coherence protocol; furthermore, we must guarantee the continued correctness of the network in the face of increasing faults. Designing for deadlock freedom is expensive. Prior solutions either sacrifice performance or power efficiency to proactively avoid deadlocks or impose high hardware complexity to reactively resolve deadlocks as they occur. However, the precise confluence of events that lead to deadlocks is so rare that minimal resources and time should be spent to ensure deadlock freedom. To that end, we propose DRAIN, a subactive approach to remove potential deadlocks without needing to explicitly detect or avoid them. We simply let deadlocks happen and periodically drain (i.e., force the movement of) packets in the network that may be involved in a cyclic dependency. As deadlocks are a rare occurrence, draining can be performed infrequently and at low cost. Unlike prior solutions, DRAIN eliminates not only routing-level but also protocol-level deadlocks without the need for expensive virtual networks. DRAIN dramatically simplifies deadlock freedom for irregular topologies and networks that are prone to wear-related faults. Our evaluations show that on an average, DRAIN can save 26.73% packet latency compared to proactive deadlock-freedom schemes in the presence of faults while saving 77.6% power compared to reactive schemes.
Quantifying Tree Hydration Using Electromagnetic Sensors

An automated method of determining tree water status would enable tree fruit growers, foresters and arborists to reduce water consumption, reduce orchard maintenance costs and improve fruit quality. Automated measurements could also be used to irrigate based on need rather than on fixed schedules. Numerous automated approaches have been studied; all are difficult to implement. Electromagnetic sensors that measure volumetric water content can be inserted in tree trunks to determine relative changes in tree water status. We performed automated measurements of dielectric permittivity using four commercially available electromagnetic sensors in fruit tree trunks over the 2016 growing season. These sensors accurately measure the ratio of air and water in soils, but tree trunks have minimal air-filled porosity. The sensors do respond, however, to bound and unbound water and the relative change in the output of the sensors thus provides an indication of this ratio. Sapwood is the hydro-dynamically responsive component of trunk anatomy and is nearest the bark. Sensor response improved when the waveguides were exposed to a greater percentage of sapwood. Irrigation-induced increases of approximately 0.5 MPa in stem water potential were associated with 0.5 unit increases in dielectric permittivity. Electromagnetic sensors respond to bound water in trees and thus have the potential to indicate tree water status, especially when the sensor rods are in contact with sapwood. Sensor modifications and/or innovative installation techniques could enable automated measurements of tree water status that could be used to precision irrigate trees.