Miracle-dz/UniFAR-FTUs huggingface dataset:
Society of Gynecologic Oncology Clinical Practice Statement Clinical Practice Statement Opioid Use in Gynecologic Oncology ; Balancing Ef fi cacy , Accessibility and Safety : An SGO Clinical Practice Statement 1

The problem of opioid misuse has been called an “epidemic” and a “public health crisis” [1]. Though efforts to regulate prescribing practices have focused on non-cancer pain, existing andproposed legislation could significantly impact oncology patients andproviders aswell. Opioids are first line therapy for all but mild cancer pain [2]. Historically the problem with cancer pain has been under treatment rather than overtreatment [3,4], and though existence of risk factors for opioidmisuse have been documented in patients with cancer, there is currently no direct evidence that prescription of opioids to patients with cancer has contributed to the national issue of opioid misuse [5]. In order to promote safety without compromising efficacy of pain control, it is paramount that gynecologic oncologists are aware of current guidelines and proposed legislation and work to address barriers to safe and effective opioid prescribing.
Catheter ablation of permanent atrial fibrillation: medium term results

Objective: To investigate the feasibility of catheter ablation as a treatment for symptomatic patients with longstanding permanent atrial fibrillation (AF). Methods: Radiofrequency ablation was applied to encircle all pulmonary veins (PVs) and create lines from the left inferior PV to the mitral valve, along the roof of the left atrium between the PVs, and along the tricuspid valve–inferior vena cava isthmus. A seven day Holter was recorded at discharge and at follow up to assess arrhythmia burden. If patients developed a symptomatic, sustained atrial arrhythmia a repeat ablation procedure was advised. Results: 42 patients underwent the procedure that took a mean of five hours with 50 minutes of fluoroscopy. After a median follow up of 8.4 months, 31 of 41 surviving patients (76%) were in sinus rhythm. Of these, 29 patients were no longer taking any antiarrhythmic drugs but 22 (52%) required more than one procedure. During follow up 49% experienced a sustained atrial tachycardia. Twenty six repeat procedures were performed. Maintenance of sinus rhythm after the first, second, or third procedure was 36% (15 of 42), 58% (11 of 19), and 71% (5 of 7), respectively. From a total of 68 procedures there were two serious complications (2.9%): a stroke from which a full recovery was made, and a PV stenosis. Conclusion: Catheter ablation can be used to cure longstanding permanent AF; however, there is a significant complication rate. Whether this is offset by a mortality benefit associated with sinus rhythm is unknown. Many patients will need more than one procedure to achieve success.
The role of motivation

During the ancient period in Greece, the role of the teacher was first introduced and teaching was considered an art form. Going to school and getting an education was something that only the richest people could afford. The role of a teacher or educator was considered the most important in the learning process, as they gave children invaluable knowledge and wisdom. However, educators were not the first educators. Wealthy residents of the area used slaves to take their children to school. They were considered experienced and wise, who passed on knowledge to the children who were led to school. This is how the word "teacher" came about. He is described as the "leader of the children". They guide students both academically and morally. Teaching methods are broader methods used to help learners achieve learning outcomes, and activities are the various ways in which these methods are implemented. Teaching methods help students to master the course content and learn how to apply content in specific contexts.
XML schema mappings

Relational schema mappings have been extensively studied in connection with data integration and exchange problems, but mappings between XML schemas have not received the same amount of attention. Our goal is to develop a theory of expressive XML schema mappings. Such mappings should be able to use various forms of navigation in a document, and specify conditions on data values. We develop a language for XML schema mappings, and concentrate on three types of problems: static analysis of mappings, their complexity, and their composition. We look at static analysis problems related to various flavors of consistency: for example, whether it is possible to map some document of a source schema into a document of the target schema, or whether all documents of a source schema can be mapped. We classify the complexity of these problems. We then move to the complexity of mappings themselves, i.e., recognizing pairs of documents such that one can be mapped into the other, and provide a classification based on sets of features used in mappings. Finally we look at composition of XML schema mappings. We study its complexity and show that it is harder to achieve closure under composition for XML than for relational mappings. Nevertheless, we find a robust class of XML schema mappings that have good complexity properties and are closed under composition.
Demographic and Structural Characteristics to Rationalize Link Formation in Online Social Networks

Recent years have seen tremendous growth of many online social networks such as Facebook, Linked In and My Space. People connect to each other through these networks forming large social communities providing researchers rich datasets to understand, model and predict social interactions and behaviors. New contacts in these networks can be formed either due to an individual's demographic profile such as age group, gender, geographic location or due to network's structural dynamics such as triadic closure and preferential attachment, or a combination of both demographic and structural characteristics. A number of network generation models have been proposed in the last decade to explain the structure, evolution and processes taking place in different types of networks, and notably social networks. Network generation models studied in the literature primarily consider structural properties, and in some cases an individual's demographic profile in the formation of new social contacts. These models do not present a mechanism to combine both structural and demographic characteristics for the formation of new links. In this paper, we propose a new network generation algorithm which incorporates both these characteristics to model growth of a network. We use different publicly available Facebook datasets as benchmarks to demonstrate the correctness of the proposed network generation model.
Phosphorylation of splicing factor SF1 on Ser20 by cGMP‐dependent protein kinase regulates spliceosome assembly

Splicing factor 1 (SF1) functions at early stages of pre‐mRNA splicing and contributes to splice site recognition by interacting with the essential splicing factor U2AF65 and binding to the intron branch site. We have identified an 80 kDa substrate of cGMP‐dependent protein kinase‐I (PKG‐I) isolated from rat brain, which is identical to SF1. PKG phosphorylates SF1 at Ser20, which inhibits the SF1–U2AF65 interaction leading to a block of pre‐spliceosome assembly. Mutation of Ser20 to Ala or Thr also inhibits the interaction with U2AF65, indicating that Ser20 is essential for binding. SF1 is phosphorylated in vitro by PKG, but not by cAMP‐dependent protein kinase A (PKA). Phosphorylation of SF1 also occurs in cultured neuronal cells and is increased on Ser20 in response to a cGMP analogue. These results suggest a new role for PKG in mammalian pre‐mRNA splicing by regulating in a phosphorylation‐dependent manner the association of SF1 with U2AF65 and spliceosome assembly.
The role of data mining in turning bio-data into Bioinformation

Editorial: The explosion of high throughput data generation technologies have added tremendous volumes of data to the already huge collections found in digital form. This is particularly true in Biology. In the near future higher throughput technologies will only exacerbate this raw data overload situation. The explosive growth in raw data volume generates the need for new techniques and tools that can intelligently and automatically transform the data into useful information and knowledge. One of the central tenets of all information theories is that “the higher the data volume, the lower the information (and knowledge) level”. This can be referred to as the “Data Overload, Information Underload” (DO/IU) problem. The DO/IU problem exists in most fields, not just in Biology. It has been pointed out by experts in almost all fields that involve voluminous data.
Coordination of Agri-Food Chain with Revenue-Sharing Contract under Stochastic Output and Stochastic Demand

Due to the effects of uncertain factors such as seasonal weather and plant/animal diseases, the output of agricultural production is uncertain given certain agricultural inputs. This paper addresses the issue of coordinating agri-food chain with perishable goods by revenue-sharing (RS) contract when both output and demand are random. Following a RS contract, a supplier decides on agricultural input (e) and deliveries all goods with a price (ω) lower than unit production cost to the retailer while a retailer decides on the retail price (p) and return 1–Φ share (percentage) of its revenue to the supplier. For such a contract, the necessary condition of coordinating the chain is that the expected revenue function is concave. Under the channel coordination, the relationship between RS contract parameters ω and Φ as well as the range of Φ are given. For both output and demand random factor with uniform distribution, the concavity of the expected revenue function is presented. A numerical example illustrates the correctness of our analysis. The results of numerical example show that RS contract is able to coordinate the agri-food chain when the expected revenue function is concave. The results also show that the optimal decisions of p and e are closely related to the demand price elasticity and the range of Φ is widened when the expected output increases.
University of Groningen Visualization of Generalized Voronoi Diagrams

Voronoi diagrams are an important data structure in computer science. However well studied mathematically, understanding such diagrams for different metrics, orders, and site shapes is a complex task. We propose a new method to visualize k-order diagrams and give an efficient adaptive implementation for this method. The algorithm is easy to customize for different metrics and site shapes. Its real-time performance makes it suitable for interactive planning and analysis of complex Voronoi configurations in 2D. We illustrate the method for different combinations of metrics and site shapes.
Narrative Variations in a Virtual Storyteller Conference

Research on storytelling over the last 100 years has distinguished at least two levels of narrative representation (1) story, or fabula; and (2) discourse, or sujhet. We use this distinction to create Fabula Tales, a computational framework for a virtual storyteller that can tell the same story in different ways through the implementation of general narratological variations, such as varying direct vs. indirect speech, character voice (style), point of view, and focalization. A strength of our computational framework is that it is based on very general methods for re-using existing story content, either from fables or from personal narratives collected from blogs. We first explain how a simple annotation tool allows naı́ve annotators to easily create a deep representation of fabula called a story intention graph, and show how we use this representation to generate story tellings automatically. Then we present results of two studies testing our narratological parameters, and showing that different tellings affect the reader’s perception of the story and characters.
Depressive symptoms and cognitive control in a mixed antisaccade task: Specific effects of depressive rumination

Growing empirical evidence suggests that cognitive and affective problems in depression may be a reflection of cognitive control impairments. However, to date, the nature of such impairments is still poorly understood and further investigation of this topic is required to advance current knowledge on the underlying vulnerability factors for depression. Using a mixed antisaccade paradigm, the present study examined if depressive symptoms in general, and more specifically rumination, are related to impairments in cognitive control functions such as inhibition and switching. The results on antisaccade latency and error rates indicated that depressive symptoms in general were not related to impairments in inhibition and switching. However, rumination was associated with impaired inhibition such that high, compared to low, ruminators had slower antisaccade latencies. No group differences were observed on antisaccade error rates. Implications for understanding the underlying vulnerability factors for the development of depressive symptoms are discussed.
Motion Control and Dynamic Load Carrying Capacity of Mobile Robot via Nonlinear Optimal Feedback

In this paper, two methods are presented for solving closed loop optimal control problem and finding dynamic load carrying capacity (DLCC) for fixed and mobile manipulators. These control laws are based on the numerical solution to nonlinear Hamilton-Jacobi-Bellman (HJB) equation. First approach is the Successive Approximation (SA) for finding solution of HJB equation in the closed loop form and second approach is based on solving state-dependent Riccati equation (SDRE) that is an extension of algebraic Riccati equation for nonlinear systems. Afterward dynamic load carrying capacity of manipulators is computed using these controllers. The DLCC is calculated by considering tracking error and limits of torque’s joints. Finally, results are presented for two cases, a two-link planar manipulator mounted on a differentially driven mobile base and a 6DOF articulated manipulator (6R). The simulation results are verified with the experimental test for the 6R manipulator. The simulation and experimental results demonstrate that these methods are convenient for finding nonlinear optimal control laws in state feedback form and finding the maximum allowable load on a given trajectory.
A novel compression algorithm decision method for spark shuffle process

With the wide application of Spark big data platform, some problems in practical application are exposed, and one of the main problems is performance optimization. The Shuffle module of Spark is one of the core modules of Spark, and it is also an important module of some other distributed big data computing frameworks. The design of Shuffle module is the key factor that directly determines the performance of big data computing framework. The main optimization parameters of Shuffle process involve the CPU utilization, I/O literacy rate, network transmission rate, and one of these factors is likely to be the bottleneck during the execution of application. The network data transmission time consumption, I/O read and write time, and the CPU utilization are closely related with the size of the data processing. As a result, Spark provides compression configuration options and different compression algorithms for users to select. Different compression algorithms have different effects in compression rate and compression ratio, but the default configuration is usually selected by all users even though they run different applications, so the optimal configuration cannot be achieved. In order to achieve the optimal configuration of compression algorithm for the Shuffle process, one cost optimization model for Spark Shuffle process is proposed in this paper, which enables users to get the best compression configuration before application execution. The experimental results show that the prediction model for compression configuration has an accuracy of 58.3%, and the proposed cost optimization model can improve the performance by 48.9%.
Comprehensive Study on Injection Velocity Enhancement in Dopant-Segregated Schottky MOSFETs

The carrier transport in dopant-segregated Schottky (DSS) and conventional MOSFETs was thoroughly investigated in terms of carrier injection velocity, vinj. It was found that vinj enhancement associated with the velocity overshoot enhances the current drivability in DSS, in addition to the reduction of parasitic resistance. A physical-based model was newly developed to explain the velocity overshoot behavior and reproduced the experimental data very well. Moreover, a novel type of DSS FinFET to take full advantage of the velocity overshoot was proposed and demonstrated as a primary study
ProximityHat: a head-worn system for subtle sensory augmentation with tactile stimulation

In this paper we present the iterative design process of our wearable sensory substitution system ProximityHat, which uses pressure actuators around the head to convey spatial information. It was already shown that the sense of touch can be used to augment our perception of reality. Existing systems focus on vibration signals for information transfer, but this is unsuitable for constant stimulation in everyday use. Our system determines the distance to surrounding objects with ultrasonic sensors and maps this information to an inward pressure. It was evaluated in a study with 13 blindfolded subjects in orientation and navigation tasks. The users were able to discern at least three different absolute pressure levels with high certainty. Combined with the sensors, they could also use continuous values to navigate hallways and find doors. Most users had only a few collisions, but a small group of three individuals struggled more. We attribute this to the latency and resolution of the final prototype, which led to slow walking speed and will be addressed in future work.
Some Issues In Continuous - And Discrete - Response Contingent Valuation Studies

I want to begin with a caveat. I have no training in psychology, and my interest in the field is that of an amateur. Thus, the confidence with which I shall make statements about psychological facts is in inverse proportion to my expertise. My point of departure is the assumption that the most serious problem with contingent valuation (CV) methodology is hypothetical bias. Apart from introspection, the evidence for this assumption comes from two classic studies conducted by Richard Bishop and his colleagues at the University of Wisconsin. The first study by Bishop and Heberlein (1979) involved a survey of two random samples of individuals who had obtained permits to hunt ducks in the Horizon Zone of East Central Wisconsin. One sample group was asked the hypothetical question whether they would be willing to sell their permit for a specified sum of money (this sum differed among individuals). The other sample group was given a real opportunity to sell their permit for a specified sum of money; of 237 hunters surveyed, 105 actually sold their permits. Using a methodology which I discuss in a later section, Bishop and Heberlein estimated willingness-to-sell (WTS) functions from these two sets of data. From the fitted WTS functions, they derived an estimate of the expected selling price for an average individual which I denote C'. In Hanemann (1984), which is summarized in the third section, I propose two other measures of the average individuals' selling price which I denote C* and C. The results are: C' C* C+ Hypothetical sale $101 83.16 Real sale $ 63 31.02 114.22
A multivariate Bayesian model for embryonic growth

Most longitudinal growth curve models evaluate the evolution of each of the anthropometric measurements separately. When applied to a ‘reference population’, this exercise leads to univariate reference curves against which new individuals can be evaluated. However, growth should be evaluated in totality, that is, by evaluating all body characteristics jointly. Recently, Cole et al. suggested the Superimposition by Translation and Rotation (SITAR) model, which expresses individual growth curves by three subject‐specific parameters indicating their deviation from a flexible overall growth curve. This model allows the characterization of normal growth in a flexible though compact manner. In this paper, we generalize the SITAR model in a Bayesian way to multiple dimensions. The multivariate SITAR model allows us to create multivariate reference regions, which is advantageous for prediction. The usefulness of the model is illustrated on longitudinal measurements of embryonic growth obtained in the first semester of pregnancy, collected in the ongoing Rotterdam Predict study. Further, we demonstrate how the model can be used to find determinants of embryonic growth. Copyright © 2015 John Wiley & Sons, Ltd.
Long term uricosuric therapy in gout.

The effectiveness of long term uricosuric therapy was evaluated in sixty-four patients with primary gout. Serum uric acid was reduced to normal in half the patients; the majority manifested a urate diuresis. In seventeen of fifty patients with tophi, these lesions decreased in size. Acute gouty attacks were reduced to less than one per year in forty-five, patients; the chronic symptoms present in fifty-one patients improved in forty. , Effectiveness of therapy was categorized as good, moderate, and poor, with examples of illustrative cases.
Heterodimeric coiled-coil interactions of human GABAB receptor

Significance Human GABAB receptor transmits inhibitory signals in the brain. Defects in the receptor are linked to several neurological diseases, including epilepsy and spasticity. The GABAB receptor consists of two subunits, GABAB receptor 1 (GBR1) and GABAB receptor 2 (GBR2). GBR1 is trapped inside the cell because it contains an endoplasmic reticulum retention signal that targets the receptor to the intracellular compartment. This retention signal is masked by coiled-coil interaction between GBR1 and GBR2 when the two subunits associate. The crystal structure of a coiled-coil complex between the GABAB receptor subunits reveals the heterodimeric interaction that is responsible for facilitating the surface transport of the intact receptor. Metabotropic GABAB receptor is a G protein-coupled receptor that mediates inhibitory neurotransmission in the CNS. It functions as an obligatory heterodimer of GABAB receptor 1 (GBR1) and GABAB receptor 2 (GBR2) subunits. The association between GBR1 and GBR2 masks an endoplasmic reticulum (ER) retention signal in the cytoplasmic region of GBR1 and facilitates cell surface expression of both subunits. Here, we present, to our knowledge, the first crystal structure of an intracellular coiled-coil heterodimer of human GABAB receptor. We found that polar interactions buried within the hydrophobic core determine the specificity of heterodimer pairing. Disruption of the hydrophobic coiled-coil interface with single mutations in either subunit impairs surface expression of GBR1, confirming that the coiled-coil interaction is required to inactivate the adjacent ER retention signal of GBR1. The coiled-coil assembly buries an internalization motif of GBR1 at the heterodimer interface. The ER retention signal of GBR1 is not part of the core coiled-coil structure, suggesting that it is sterically shielded by GBR2 upon heterodimer formation.