Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding of Information about Medicines Use among Parents of Pre-School Children in Serbia: Parental Pharmacotherapy Literacy Questionnaire (PTHL-SR)

Parental health literacy plays an important role in children’s health. Experiences from pharmacy practice show that is necessary to check if parents understand instructions about use of medicines for children. This study aimed to assess pharmacotherapy literacy of parents of pre-school children and to examine association of parental pharmacotherapy literacy level with parent’s socio-demographic characteristics. The study was cross-sectional, conducted among parents of pre-school children (1–7 years of age), in kindergartens in several municipalities of Belgrade, Serbia, during regular parents meetings, from May to October 2016. Functional health literacy was measured by the Serbian version of the Short Test of Functional Health Literacy in Adults (S-TOFHLA). Parental pharmacotherapy literacy was assessed with newly constructed PTHL-SR questionnaire with good psychometric characteristics (Parental pharmacotherapy literacy questionnaire—Serbian). Overall, 813 parents participated in the study, mostly females (81.30%), between 30 to 40 years of age (70.85%) with two children (56.70%). Almost all of our study participants (99%) had adequate health literacy as assessed by S-TOFHLA. Mean score on PTHL-SR was 72.83% (standard deviation was 13.37), with better results among females than males (72% of women were in the group of highest PTHL-SR results). Our study showed that many parents (76.5%) knew the appropriate usage of non-prescription medicine for children, 57.2% parents were able to correctly calculate the dose of oral syrup for a child, and only 43.3% were able to interpret non-prescription dosage information written on the package. The majority of parents (61.3%) would make a dosage to child based on age and not on their weight. Every fifth parent with adequate functional health literacy measured by S-TOFHLA test, achieved the lowest results measured by PTHL-SR. Higher performance of the PTHL-SR was significantly correlated with education (p < 0.001), female sex (p < 0.001), married parents and those living in common-law (p < 0.001), older parents (p < 0.05) and parents who have more children (p < 0.05), and are non-smokers (p < 0.05). These results provide evidence that limitations in understanding common information about use of medicines are widespread among parents of pre-school children and encourage efforts for further investigation. PTHL-SR questionnaire may be a useful tool for identification of parents who need more instructions and assistance from healthcare providers, above all in providing better communication, written or spoken at community pharmacy settings.
Pharmacokinetic/Pharmacodynamic Analysis of Isavuconazole Against Aspergillus spp. and Candida spp. in Healthy Subjects and Patients With Hepatic or Renal Impairment by Monte Carlo Simulation

The aim of this pharmacokinetic/pharmacodynamic (PK/PD) study is to evaluate the efficacy of various isavuconazole dosing regimens for healthy individuals and patients with hepatic or renal impairment against Aspergillus spp. and Candida spp. Monte Carlo simulations were conducted using pharmacokinetic (PK) parameters and pharmacodynamics (PD) data to determine the probabilities of target attainment and cumulative fractions of response in terms of area under the concentration curve/minimum inhibition concentration (AUC/MIC) targets of isavuconazole. A clinically recommended dosage regimen of isavuconazole (200 mg qd) obtained high cumulative fraction of response values of > 90% for all subjects against A. fumigatus, A. flavus, A. nidulans, A. terreus, A. versicolor, C. parapsilosis and C. tropicalis. For patients with mild or moderate hepatic impairment, the dosage should be halved only when treating invasive fungal infections caused by C. albicans, C. parapsilosis or C. tropicalis. However, dose adjustment is unlikely to be required in mild to severe renal impairment patients because all cumulative fraction of response values were similar to those of comparing with healthy subjects. Notably, all isavuconazole dosing regimens were not effective against C. glabrata and C. krusei in all subjects. These PK/PD‐based simulations rationalize and optimize the dosage regimens of isavuconazole for healthy individuals and patients with hepatic or renal impairment against Aspergillus spp. and Candida spp.
Novel Regulation of Integrin Trafficking by Rab11-FIP5 in Aggressive Prostate Cancer

The laminin-binding integrins, α3β1 and α6β1, are needed for tumor metastasis and their surface expression is regulated by endocytic recycling. β1 integrins share the Rab11 recycling machinery, but the trafficking of α3β1 and α6β1 are distinct by an unknown mechanism. Using a mouse PDX tumor model containing human metastatic prostate cancer, Rab11 family interacting protein 5 (Rab11-FIP5) was identified as a lead candidate for α6β1 trafficking. Rab11-FIP5 and its membrane-binding domain were required for α6β1 recycling, without affecting the other laminin-binding integrin (i.e., α3β1) or unrelated membrane receptors like CD44, transferrin receptor, or E-cadherin. Depletion of Rab11-FIP5 resulted in the intracellular accumulation of α6β1 in the Rab11 recycling compartment, loss of cell migration on laminin, and an unexpected loss of α6β1 recycling in cell–cell locations. Taken together, these data demonstrate that α6β1 is distinct from α3β1 via Rab11-FIP5 recycling and recycles in an unexpected cell–cell location. Implications: Rab11-FIP5–dependent α6β1 integrin recycling may be selectively targeted to limit migration of prostate cancer cells into laminin-rich tissues. Mol Cancer Res; 16(8); 1319–31. ©2018 AACR.
Effects of Topology Knowledge and Relay Depth on Asynchronous Consensus

Consider a point-to-point message-passing network. We are interested in the asynchronous crash-tolerant consensus problem in incomplete networks. We study the feasibility and efficiency of approximate consensus under different restrictions on topology knowledge and the relay depth, i.e., the maximum number of hops any message can be relayed. These two constraints are common in large-scale networks, and are used to avoid memory overload and network congestion respectively. Specifically, for different values of integers k, k , we consider that each node knows all its neighbors of at most k-hop distance (k-hop topology knowledge), and the relay depth is k . We consider both directed and undirected graphs. More concretely, we answer the following main question in asynchronous systems: What is a tight condition on the underlying communication graphs for achieving approximate consensus if each node has only a k-hop topology knowledge and relay depth k? To prove that the necessary conditions presented in the paper are also sufficient, we have developed algorithms that achieve consensus in graphs satisfying those conditions: -The first class of algorithms requires k-hop topology knowledge and relay depth k. Unlike prior algorithms, these algorithms do not flood the network, and each node does not need the full topology knowledge. We show how the convergence time and the message complexity of those algorithms is affected by k, providing the respective upper bounds. -The second set of algorithms requires only one-hop neighborhood knowledge, i.e., immediate incoming and outgoing neighbors, but needs to flood the network (i.e., relay depth is n, where n is the number of nodes). One result that may be of independent interest is a topology discovery mechanism to learn and "estimate" the topology in asynchronous directed networks with crash faults.
Integrin α4β7 switches its ligand specificity via distinct conformer-specific activation

Chemokine (C-C motif) ligand 25 (CCL25) and C-X-C motif chemokine 10 (CXCL10) induce the ligand-specific activation of integrin &agr;4&bgr;7 to mediate the selective adhesion of lymphocytes to mucosal vascular addressin cell adhesion molecule-1 (MAdCAM-1) or vascular cell adhesion molecule-1 (VCAM-1). However, the mechanism underlying the selective binding of different ligands by &agr;4&bgr;7 remains obscure. In this study, we demonstrate that CCL25 and CXCL10 induce distinct active conformers of &agr;4&bgr;7 with a high affinity for either MAdCAM-1 or VCAM-1. Single-cell force measurements show that CCL25 increases the affinity of &agr;4&bgr;7 for MAdCAM-1 but decreases its affinity for VCAM-1, whereas CXCL10 has the opposite effect. Structurally, CCL25 induces a more extended active conformation of &agr;4&bgr;7 compared with CXCL10-activated integrin. These two distinct intermediate open &agr;4&bgr;7 conformers selectively bind to MAdCAM-1 or VCAM-1 by distinguishing their immunoglobulin domain 2. Notably, Mn2+ fully opens &agr;4&bgr;7 with a high affinity for both ligands. Thus, integrin &agr;4&bgr;7 adopts different active conformations to switch its ligand-binding specificity.
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport

Generative Adversarial Networks (GANs) are one of the most practical methods for learning data distributions. A popular GAN formulation is based on the use of Wasserstein distance as a metric between probability distributions. Unfortunately, minimizing the Wasserstein distance between the data distribution and the generative model distribution is a computationally challenging problem as its objective is non-convex, non-smooth, and even hard to compute. In this work, we show that obtaining gradient information of the smoothed Wasserstein GAN formulation, which is based on regularized Optimal Transport (OT), is computationally effortless and hence one can apply first order optimization methods to minimize this objective. Consequently, we establish theoretical convergence guarantee to stationarity for a proposed class of GAN optimization algorithms. Unlike the original non-smooth formulation, our algorithm only requires solving the discriminator to approximate optimality. We apply our method to learning MNIST digits as well as CIFAR-10 images. Our experiments show that our method is computationally efficient and generates images comparable to the state of the art algorithms given the same architecture and computational power.
Reinforcement Learning for Solving the Vehicle Routing Problem

We present an end-to-end framework for solving the Vehicle Routing Problem (VRP) using reinforcement learning. In this approach, we train a single model that finds near-optimal solutions for problem instances sampled from a given distribution, only by observing the reward signals and following feasibility rules. Our model represents a parameterized stochastic policy, and by applying a policy gradient algorithm to optimize its parameters, the trained model produces the solution as a sequence of consecutive actions in real time, without the need to re-train for every new problem instance. On capacitated VRP, our approach outperforms classical heuristics and Google's OR-Tools on medium-sized instances in solution quality with comparable computation time (after training). We demonstrate how our approach can handle problems with split delivery and explore the effect of such deliveries on the solution quality. Our proposed framework can be applied to other variants of the VRP such as the stochastic VRP, and has the potential to be applied more generally to combinatorial optimization problems.
The Influence of Different Kinds of Incentives on Decision-Making and Cognitive Control in Adolescent Development: A Review of Behavioral and Neuroscientific Studies

A number of recent hypothetical models on adolescent development take a dual-systems perspective and propose an imbalance in the maturation of neural systems underlying reward-driven and control-related behavior. In particular, such models suggest that the relative dominance of the early emerging subcortical reward system over the later emerging prefrontal-guided control system leads to higher risk-taking and sensation-seeking behavior in mid-adolescents. Here, we will review recent empirical evidence from behavioral and neuroscientific studies examining interactions between these systems and showing that empirical evidence in support for the view of a higher sensitivity to rewards in mid-adolescents is rather mixed. One possible explanation for this may be the use of different kinds and amounts of incentives across studies. We will therefore include developmental studies comparing the differential influence of primary and secondary incentives, as well as those investigating within the class of secondary incentives the effects of monetary, cognitive, or social incentives. We hypothesized that the value of receiving sweets or sours, winning or losing small or large amounts of money, and being accepted or rejected from a peer group may also changes across development, and thereby might modulate age differences in decision-making and cognitive control. Our review revealed that although developmental studies directly comparing different kinds of incentives are rather scarce, results of various studies rather consistently showed only minor age differences in the impact of incentives on the behavioral level. In tendency, adolescents were more sensitive to higher amounts of incentives and larger uncertainty of receiving them, as well as to social incentives such as the presence of peers observing them. Electrophysiological studies showed that processing efficiency was enhanced during anticipation of incentives and receiving them, irrespective of incentive type. Again, we found no strong evidence for interactions with age across studies. Finally, functional brain imaging studies revealed evidence for overlapping brain regions activated during processing of primary and secondary incentives, as well as social and non-social incentives. Adolescents recruited similar reward-related and control-related brain regions as adults did, but to a different degree. Implications for future research will be discussed.
Molecular Mechanisms Underlying Abscisic Acid/Gibberellin Balance in the Control of Seed Dormancy and Germination in Cereals

Seed dormancy is an adaptive trait that does not allow the germination of an intact viable seed under favorable environmental conditions. Non-dormant seeds or seeds with low level of dormancy can germinate readily under optimal environmental conditions, and such a trait leads to preharvest sprouting, germination of seeds on the mother plant prior to harvest, which significantly reduces the yield and quality of cereal crops. High level of dormancy, on the other hand, may lead to non-uniform germination and seedling establishment. Therefore, intermediate dormancy is considered to be a desirable trait as it prevents the problems of sprouting and allows uniformity of postharvest germination of seeds. Induction, maintenance, and release of seed dormancy are complex physiological processes that are influenced by a wide range of endogenous and environmental factors. Plant hormones, mainly abscisic acid (ABA) and gibberellin (GA), are the major endogenous factors that act antagonistically in the control of seed dormancy and germination; ABA positively regulates the induction and maintenance of dormancy, while GA enhances germination. Significant progress has been made in recent years in the elucidation of molecular mechanisms regulating ABA/GA balance and thereby dormancy and germination in cereal seeds, and this review summarizes the current state of knowledge on the topic.
Genomic and in Situ Analyses Reveal the Micropruina spp. as Abundant Fermentative Glycogen Accumulating Organisms in Enhanced Biological Phosphorus Removal Systems

Enhanced biological phosphorus removal (EBPR) involves the cycling of biomass through carbon-rich (feast) and carbon-deficient (famine) conditions, promoting the activity of polyphosphate accumulating organisms (PAOs). However, several alternate metabolic strategies, without polyphosphate storage, are possessed by other organisms, which can compete with the PAO for carbon at the potential expense of EBPR efficiency. The most studied are the glycogen accumulating organisms (GAOs), which utilize aerobically stored glycogen to energize anaerobic substrate uptake and storage. In full-scale systems the Micropruina spp. are among the most abundant of the proposed GAO, yet little is known about their ecophysiology. In the current study, genomic and metabolomic studies were performed on Micropruina glycogenica str. Lg2T and compared to the in situ physiology of members of the genus in EBPR plants using state-of-the-art single cell techniques. The Micropruina spp. were observed to take up carbon, including sugars and amino acids, under anaerobic conditions, which were partly fermented to lactic acid, acetate, propionate, and ethanol, and partly stored as glycogen for potential aerobic use. Fermentation was not directly demonstrated for the abundant members of the genus in situ, but was strongly supported by the confirmation of anaerobic uptake of carbon and glycogen storage in the absence of detectable polyhydroxyalkanoates or polyphosphate reserves. This physiology is markedly different from the classical GAO model. The amount of carbon stored by fermentative organisms has potentially important implications for phosphorus removal – as they compete for substrates with the Tetrasphaera PAO and stored carbon is not made available to the “Candidatus Accumulibacter” PAO under anaerobic conditions. This study shows that the current models of the competition between PAO and GAO are too simplistic and may need to be revised to take into account the impact of potential carbon storage by fermentative organisms.
Verification of wafer-level calibration accuracy at cryogenic temperatures

This article presents the results of accuracy verification of wafer level calibration at cryogenic temperatures based on coplanar calibration standards. For the first time, the electrical characteristics of commercially available coplanar calibration lines were extracted at the temperature of liquid helium. It was demonstrated that the temperature dependent variation of the characteristic impedance of the tested lines is within ±1% tolerance of the nominal value of 50 Ω for a temperature range from room temperature down to 4 K Finally, the accuracy of the LRM+ calibration method at cryogenic temperatures was verified by definition of the worst case error bounds for the measurement of passive devices and compared to the reference NIST multiline TRL.
A Parameterized Linear Magnetic Equivalent Circuit for Analysis and Design of Radial Flux Magnetic Gears–Part II: Evaluation

This is Part II of a two part paper on the development of a parameterized linear magnetic equivalent circuit (MEC) for radial flux magnetic gears with surface permanent magnets. Part I describes the MEC implementation. This section, Part II, evaluates the MEC model's accuracy by comparing its results against those produced by a nonlinear finite-element analysis (FEA) model. Simulation results demonstrate that the linearity approximation does not prevent the MEC from accurately matching the torque and air-gap flux densities predicted by a nonlinear FEA model for three diverse magnetic gear base designs. The impacts of the MEC discretization parameters introduced in Part I are also investigated using the same base designs, and guidelines for those settings are developed. Additionally, single design parameter sweeps illustrate the MEC's ability to track these changes over most practical design ranges and reveal where the MEC's accuracy degrades due to the linearity approximation. Finally, the results of a 46,656 case parametric optimization study demonstrate the MEC's ability to match the nonlinear FEA model's torque predictions within a few percent over a wide range of designs while achieving average simulation speeds 44 to 271 times faster than those of the FEA model.
Subresolution Assist Feature Generation With Supervised Data Learning

Subresolution assist feature (SRAF) generation is a very important resolution enhancement technique to improve yield in modern semiconductor manufacturing process. Model-based and rule-based approaches are widely adopted in the semiconductor industry. The model-based SRAF generation can achieve a high accuracy but it is known to be time-consuming and it is hard to obtain consistent SRAFs on the same layout pattern configurations. The rule-based SRAF generation is highly technology dependent and it is becoming extremely difficult to render high-quality results in advanced technology nodes. This paper proposes supervised data learning techniques for fast yet consistent SRAF generation with high-quality results. We first propose the constrained concentric circle with area sampling scheme for feature extraction. Illumination source symmetry-based feature compaction technique is further invented to reduce the training data set size and achieve consistent SRAF predictions. Using accurate model-based SRAFs as training data, classification models based on logistic regression (LGR) and support vector machine are calibrated for SRAF predictions. Moreover, the probability maximum prediction is proposed to generate manufacturing-friendly SRAFs with a greedy simplification scheme. We compare support vector machine and LGR models by embedding into an entire mask optimization flow, where the support vector machine model obtains better lithographic performance. Experimental results demonstrate that, compared with the commercial Calibre tool, supervised data learning techniques for SRAF generation obtain significant speed up (>3X for a ${100~{ {{\mathrm{um}}} }^{2}}$ layout clip) and comparable lithographic performance in terms of edge placement error and process variation band.
Increased trauma activation is not equally beneficial for all elderly trauma patients

BACKGROUND Physiologic changes in the elderly lead to higher morbidity and mortality after injury. Increasing level of trauma activation has been proposed to improve geriatric outcomes, but the increased cost to the patient and stress to the hospital system are significant downsides. The purpose of this study was to identify the age at which an increase in activation status is beneficial. METHODS A retrospective review of trauma patients 70 years or older from October 1, 2011, to October 1, 2016, was performed. On October 1, 2013, a policy change increased the activation criteria to the highest level for patients 70 years or older with a significant mechanism of injury. Patients who presented prior to (PRE) were compared with those after the change (POST). Data collected included age, Injury Severity Score (ISS), length of stay (LOS), complications, and mortality. Primary outcome was mortality, and secondary outcome was LOS. Multivariable regressions controlled for age, ISS, injury mechanism, and number of complications. RESULTS A total of 4,341 patients met the inclusion criteria, 1,919 in PRE and 2,422 in POST. Mean age was 80.4 and 81 years in PRE and POST groups, respectively (p = 0.0155). Mean ISS values were 11.6 and 12.4 (p < 0.0001) for the PRE and POST groups. POST had more Level 1 activations (696 vs. 220, p < 0.0001). After controlling for age, ISS, mechanism of injury, and number of complications, mortality was significantly reduced in the POST group 77 years or older (odds ratio, 0.53; 95% confidence interval, 0.3–0.87) (Fig. 1). Hospital LOS was significantly reduced in the POST group age 78 years or older (regression coefficient, −0.55; 95% confidence interval, −1.09 to −0.01) (Fig. 2). CONCLUSIONS This study suggests geriatric trauma patients 77 years or older benefit from the highest level of trauma activation with shorter LOS and lower mortality. A focused approach to increasing activation level for elderly patients may decrease patient cost. LEVEL OF EVIDENCE Therapeutic/Care Management, level IV.