Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of survivorship care plans in the United States: associations with survivorship care.

BACKGROUND Survivorship care plans (SCPs), including a treatment summary and follow-up plan, intend to promote coordination of posttreatment cancer care; yet, little is known about the provision of these documents by oncologists to primary care physicians (PCPs). This study compared self-reported oncologist provision and PCP receipt of treatment summaries and follow-up plans, characterized oncologists who reported consistent provision of these documents to PCPs, and examined associations between PCP receipt of these documents and survivorship care. METHODS A nationally representative sample of medical oncologists (n = 1130) and PCPs (n = 1020) were surveyed regarding follow-up care for breast and colon cancer survivors. All statistical tests were two-sided. Multivariable regression models identified factors associated with oncologist provision of treatment summaries and SCPs to PCPs (always/almost always vs less frequent). RESULTS Nearly half of oncologists reported always/almost always providing treatment summaries, whereas 20.2% reported always/almost always providing SCPs (treatment summary + follow-up plan). Approximately one-third of PCPs indicated always/almost always receiving treatment summaries; 13.4% reported always/almost always receiving SCPs. Oncologists who reported training in late- and long-term effects of cancer and use of electronic medical records were more likely to report SCP provision (P < .05). PCP receipt of SCPs was associated with better PCP-reported care coordination, physician-physician communication, and confidence in survivorship care knowledge compared to receipt of neither treatment summaries nor SCPs (P < .05). CONCLUSIONS Providing SCPs to PCPs may enhance survivorship care coordination, physician-physician communication, and PCP confidence. However, considerable progress will be necessary to achieve implementation of sharing SCPs among oncologists and PCPs.
A Break in the Brake Mechanism in Diabetes

The importance of insulin and glucagon as fine regulators of glycemic excursions is well established (1). Alterations in gastric emptying are generally not considered important contributors to postprandial hyperglycemia until late complications of diabetes such as gastroparesis have occurred (2,3). It is now emerging that the rate of gastric emptying may be a major determinant of postprandial glycemic excursions in healthy subjects, as well as in type 1 and type 2 diabetic patients (4). Gastroparesis is a relatively rare complication that occurs late in diabetes because of irreversible intestinal nerve damage (4); it must be distinguished from the physiological inhibitory effects of acute hyperglycemia on gastric motility (5,6). The latter has been proposed as a defense mechanism existing to minimize postprandial hyperglycemia by reducing the rate of efflux of glucose into the circulation from the gut (7). This may be of special importance for people with type 1 diabetes who have a reduced ability to delay gastric emptying in response to hyperglycemia (8). Cross-sectional studies suggest that an inverse relationship between the rate of gastric emptying and blood glucose concentration also exists in type 2 diabetic patients (4) and, thus, that similar regulatory mechanisms may exist in both conditions. ### Extrinsic pathway. Normally, the rate of gastric emptying is tightly regulated as a result of neural and hormonal feedback triggered by the interaction of nutrients within the small intestine known as the ileal break mechanism or “extrinsic pathway” of control. This feedback is caloric-load dependent, relates to the length of small intestine exposed to nutrient, and regulates the overall rate of emptying to about 2–3 kcal/min (9,10). When food reaches the intestine, L- and K-cells in the distal small bowel are stimulated to produce glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP), respectively, both of …
Automatic In-vivo Evolution of Kernel Policies for Better Performance

Today's monolithic kernels often implement a small, fixed set of policies such as disk I/O scheduling policies, while exposing many parameters to let users select a policy or adjust the specific setting of the policy. Ideally, the parameters exposed should be flexible enough for users to tune for good performance, but in practice, users lack domain knowledge of the parameters and are often stuck with bad, default parameter settings. We present EOS, a system that bridges the knowledge gap between kernel developers and users by automatically evolving the policies and parameters in vivo on users' real, production workloads. It provides a simple policy specification API for kernel developers to programmatically describe how the policies and parameters should be tuned, a policy cache to make in-vivo tuning easy and fast by memorizing good parameter settings for past workloads, and a hierarchical search engine to effectively search the parameter space. Evaluation of EOS on four main Linux subsystems shows that it is easy to use and effectively improves each subsystem's performance.
A Novel Uneven Clustering Algorithm Based on Ant Colony Optimization for Wireless Sensor Networks

Energy-Efficient Uneven Clustering (EEUC) algorithm is a novel algorithm which can balance energy cost among cluster headers and extend network’s general survival time effectively. However, EEUC needs to do cluster header election every round, and fails to take network’s reliability and real-time issues into account. This paper presents a novel uneven cluster-based routing protocol for Wireless Sensor Networks: Ant Colony Optimization based Uneven Clustering (ACOUC) algorithm. ACOUC changes EEUC’s periodical and random election model, optimizes and maintains network’s routing on employ of an ant colony algorithm based on its characteristics of self-organization, self-adaptation and dynamic optimization. Simulation results on OPNET show that ACOUC is better than EEUC in energy efficiency, reliability and real-time performance.
Privacy-Preserving Multimedia Big Data Aggregation in Large-Scale Wireless Sensor Networks

To preserve the privacy of multimedia big data and achieve the efficient data aggregation in wireless multimedia sensor networks (WMSNs), a distributed compressed sensing--based privacy-preserving data aggregation (DCSPDA) approach is proposed in this article. First, in this approach, the original multimedia sensor data are compressed and measured by distributed compressed sensing (DCS) and the compressed data measurements are uploaded to the sink, by which the inherent characteristics between sensor data can be obtained. Second, the original multimedia data are jointly recovered and the common and innovation sparse components are obtained through solving the optimization problem and linear equations at the sink. Third, through least squares support vector machine (LSSVM) learning of the sparse components, the sparse position configuration can be determined and disseminated for each node to conduct the privacy-preserving data configuration. After receiving the configuration message, original multimedia sensor data are accordingly customized, compressed, and measured by the common measurement matrix, aggregated at the cluster heads, and transmitted to the sink. Finally, the aggregated multimedia sensor data are recovered by the sink according to the data configuration to achieve the privacy-preserving data aggregation and transmission. Our comparative simulation results validate the efficiency and scalability of DCSPDA and demonstrate that the proposed approach can effectively reduce the communication overheads and provide reliable privacy-preserving with low computational complexity for WMSNs.
Protein secondary structure prediction using an evolutionary computation method and clustering

In this paper, we evaluated the performance of an evolutionary-based protein secondary structure (PSS) prediction model which uses the information of amino acid sequences extracted by a clustering technique. The dimension of the classifier's inputs is reduced using a k-means clustering method on sequence segments. The proposed PSS classifier is based on a Genetic Programming (GP) approach that uses IF rules for a multi-target classifier. The GP classifier is evaluated by using protein sequences and the sequence information obtained from the k-means clustering. The GP prediction model's performance is compared with those of feed-forward artificial neural networks (ANNs) and support vector machines (SVMs). The prediction methods are examined with two protein datasets RS126 and CB513. The performance of the three classification models are measured according to Q3 and segment overlap (SOV) scores. The prediction models which use clustered data result in average 2% higher prediction accuracy than those using sequence data. In addition, the experimental results indicate the GP model's prediction scores are in average 3% higher than those of the ANN and SVMs models when amino acid sequences or clustered information are explored.
Bilingual innovations: Experimental evidence offers clues regarding the psycholinguistics of language change*

Sustained interaction between a bilingual's two languages can be a first step toward diachronic language change. We describe two investigations that explore this by examining how bilinguals process innovative syntactic structures in their first language. In the first investigation, a sentence recall/sentence matching task, bilinguals and monolinguals exhibited differences in their tolerance of expressions of induced motion, which vary in acceptability between the two languages (Portuguese and English). In the second investigation, a priming methodology was employed to induce bilinguals to produce in their first language (Spanish) innovative constructions modeled on the second language (English), using materials where the alternation is shared between the two languages (voice, reciprocal) or not (dative). The two investigations provide a window into how languages interact in bilinguals, inducing tolerance of ungrammaticality which, we will argue, could lead to long-term novel representations in the linguistic competence repositories.
LA ALEXITIMIA: ENTRE LA ANGUSTIA Y EL GOCE Alexithymia: between anguish and enjoyment

Clinically, psychic participation is considered as a possible cause of psychosomatic diseases. However, those who proceed technically on the basis of purely clinical observations —without considering a cognitive rupture that allows the conceptualization of their actions— disregard the participation of subjectivity conceived by psychoanalysi s, whose theoretical corpus may contribute to a fittingly human rationale of phenomena unexplained by medical science. This work seeks to make such a contribution by articulating the psychoanalytic categories of anguish and enjoyment with the medical category called alexithymia.
Unintended Benefits Arising from Cell-Based Interventions for Neurological Conditions

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Prosody Modification on Mixed-Language Speech Synthesis

This paper proposes a method to generate natural prosody parameters in Chinese and English mixed-language speech synthesis system which is based on separate Chinese, English, and a small bilingual corpus. Prosodic assimilation of English words to Chinese contexts can be found by observing the bilingual corpus. The most obvious assimilation characteristics are the wider pitch range and the longer duration. A prosody modification model based on this observation is proposed to modify mono-lingual prosody parameters to adapt for mixed-lingual environment. Experiments have proved that more natural mixed-lingual prosody can be generated with our model.
Esense: communication through energy sensing

In this paper, we present Esense: a new paradigm of communication between devices that have fundamentally different physical layers. The same communication framework also works between devices that have the same physical layer, which are out of communication range but within carrier-sense range. Esense is based on sensing and interpreting energy profiles. While our ideas are generic enough to be applicable in a variety of contexts, we illustrate the usefulness of our ideas by presenting novel solutions to existing problems in three distinct research domains. As part of these solutions, we demonstrate the ability to communicate between devices that follow two different standards: IEEE 802.11 and 802.15. 4. We build an ``alphabet set'': a set of signature packet sizes which can be used for Esense. For this, we take a measurement based approach by considering WiFi traces from actual deployments. We then analyze the channel activity resulting from these traces and build an appropriate alphabet set for Esense communication. Our results show that we could potentially construct an alphabet of size as high as 100; such a large alphabet size promises efficient Esense communication. We also validate this alphabet set via a prototype implementation, and show that effective communication is indeed feasible even when both sides use different physical layers.
Subjective Mental Workload

Subjective workload is of increasing importance in user-machine systems, as the role of the human operator becomes less to control and more to monitor complex systems. This paper reviews the relationship between physical, cognitive, manual-control, and time-stress tasks and the subjective load experienced by an operator. The more important task variables are suggested, as are areas requiring research.
Improving augmented reality using recommender systems

With the rapid development of smart devices and wireless communication, especially with the pre-launch of Google Glass, augmented reality (AR) has received enormous attention recently. AR adds virtual objects into a user's real-world environment enabling live interaction in three dimensions. Limited by the small display of AR devices, content selection is one of the key issues to improve user experience. In this paper, we present an aggregated random walk algorithm incorporating personal preferences, location information, and temporal information in a layered graph. By adaptively changing the graph edge weight and computing the rank score, the proposed AR recommender system predicts users' preferences and provides the most relevant recommendations with aggregated information.
Effect of Pubertal Suppression on Linear Growth and Body Mass Index; a Two-Year Follow-Up in Girls with Genetic Short Stature and Rapidly Progressive Puberty

Objective: Gonadotropin-Releasing Hormone agonists (GnRHa) are used to improve the final adult height in short stature children. There are limited studies which address the potential side effect of these agents: excessive weight gain. We have followed girls with rapidly progressive puberty receiving GnRHa and results were focused on the effect of treatment on final height, weight and body mass index Methods: Thirty girls between 8.5 and 12 years with short stature and predicted adult height of less than 155 cm were enrolled in the study. All had rapidly progressive puberty. Weight and height measurements were done at the beginning of treatment, 6 and 12 months after starting and 6 and 12 months after the cessation of treatment. Bone age and stages of puberty were estimated at the beginning of treatment, after 12 months of starting and 12 months after the treatment was stopped. Findings : Predicted adult height (PAH) changes during treatment were not significant. There was no significant difference between final height and weight according to the body mass index (BMI), PAH or bone age. Conclusion: We conclude that girls with genetic short stature and rapidly progressive puberty will not benefit receiving a one-year course of GnRHa and there is no significant difference between the final height and final weigh among children according to BMI.
Contributions To Neuropsychological Assessment A Clinical Manual

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A fast algorithm for finding the confidence set of large collections of models

The paper proposes a new algorithm for finding the confidence set of a collection of forecasts or prediction models. Existing numerical implementations for finding the confidence set use an elimination approach where one starts with the full collection of models and successively eliminates the worst performing until the null of equal predictive ability is no longer rejected at a given confidence level. The intuition behind the proposed implementation lies in reversing the process: one starts with a collection of two models and as models are successively added to the collection both the model rankings and p-values are updated. The first benefit of this updating approach is a reduction of one polynomial order in both the time complexity and memory cost of finding the confidence set of a collection of M models, falling respectively from O (M3) to O (M2) and from O (M2) to O (M). This theoretical prediction is confirmed by a Monte Carlo benchmarking analysis of the algorithms. The second key benefit of the updating approach is that it intuitively allows for further models to be added at a later point in time, thus enabling collaborative efforts using the model confidence set procedure.
Hierarchical Frequency Control Scheme for Islanded Multi-Microgrids Operation

This paper presents a new hierarchical approach to deal with the problem of controlling frequency and active power generation of a medium voltage network comprising several mi- crogrids and distributed generation sources operated in islanded mode. The hierarchical approach described here should be cost effective and capable of dealing with large numbers of distributed microsources and performing tasks related to coordinated frequency control.
Local Aspects of The Triple Helix Model on The Example of Białystok

The cooperation of the three sectors included in the Triple Helix (TH), i.e. science, business and public administration is carried out in varied ways. The course of the relationship is not only affected by the sectors themselves but also by factors specific to the environment in which they operate. The article focuses on the local aspects of the TH model – actors who create it and give it a specific, individualized dimension. At the beginning of deliberations, the authors hypothesized that the formation of Białystok Science and Technology Park contributed to the intensification of cooperation between the three sectors in the city of Bialystok and the incubation of new innovative enterprises. The aim of the study was to determine the local TH model parameters in the City of Bialystok and evaluate the potential of individual actors. In Bialystok, public administration has highest potential within the local TH model. Due to the relatively high degree of integration and concentration of authority in the city it is much easier to carry out long-term innovation policy. The basic problem of business and science turns out to be a low degree of concentration, which hinders the diffusion of knowledge and reduces competitiveness. In Bialystok LGU is the moderator of cooperation between the three sectors – there is a etatistic model. The current local government intervention is supposed to lead to the independence of the two other spheres, through their innovation and increase in competitiveness.
What determines trust in international organizations? An empirical analysis for the IMF, the World Bank, and the WTO

So far no existing study has analyzed what determines people’s trust in the IMF, the World Bank, and the WTO even though – in the absence of democratic accountability – this is one of the few ways to assess the legitimacy of these institutions. This study is intended to fill this gap in the literature based on Eurobarometer survey data from the EU-15 countries. The estimation results suggest that individual characteristics (gender, international background, formal education level, personal income, ideological preferences, interest in politics, and exposure to media) as well as the extent of globalization influence trust in the three international organizations. The state of the economy only has a significant effect on trust in the WTO. Moreover, respondents’ attitudes towards globalization have a bearing on trust in all three international organizations. Survey items on individual knowledge and perceptions of the WTO allow us to test additional hypotheses that apply to this institution alone. We find that familiarity with the WTO fosters trust. Finally, beliefs that the EU is well-represented in the WTO, that the WTO has a good reputation and that it is a democratic and necessary institution increases repondents’ propensity to trust the WTO.
"Skeleton climbing": fast isosurfaces with fewer triangles

Skeleton climbing is an algorithm that builds triangulated isosurfaces in 3D grid data, more economically than marching cubes, and without the time penalty of current mesh decimation algorithms. Building the surface from its intersections with grid edges (1-skeleton), then faces (2-skeleton), then cubes (3-skeleton), treats the data in a uniform way; this allows a 25% reduction in the number of triangles produced, while still creating a true separating surface at similar speed.