Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic and clinical benefits of radiofrequency ablation versus hysterectomy in patients suffering from menorrhagia: a retrospective analysis with German health claims data

Objective: To assess clinical and economic benefits of radiofrequency ablation (RFA) compared to hysterectomy when treating patients suffering from menorrhagia. Methods: Based on German health claims data, a retrospective, longitudinal, observational analysis was performed. Patients having continuously statutory health insurance coverage during the study and being coded for menorrhagia and a relevant treatment option were included in the analysis. The control group was created using propensity score matching. Results: We discovered that using RFA generates cost savings of €1844 during the quarter of performance. As direct costs during a 2-year follow-up show similar levels in both groups, these initial savings can be preserved. This is partly because even if more patients in the RFA group were re-coded for menorrhagia after initial therapy, just a small proportion of these patients required another surgical intervention. Conclusion: RFA should more often be considered a relevant treatment option both from an economic and a medical point of view.
Developing a new measure of small bowel peristalsis with dynamic MR: a proof of concept study

Background Small bowel peristalsis is a complex of many individual motion elements. Although each element of peristalsis can be measured there is no current global measure of peristalsis. Purpose To examine the feasibility of automated computerized assessment of global small bowel motility using simple computational methods. Material and Methods Coronal dynamic MR images were obtained from five healthy volunteers who had fasted for 9 h and drunk 1.5 L of water. Images were taken using single breath-hold and ECG triggering. Acquisitions were repeated at 10 and 20 min after an intramuscular injection of hyoscine butylbromide. Parametric maps were generated representing the mean change in signal amplitude (MSA) per voxel for each dynamic acquisition. Two observers independently assessed thresholding for optimal segmentation of small bowel from other sources of signal. Total voxel activity (TVA) for each study was calculated as a sum of MSA per slice and whole examination and TVA profiles were generated. Results Independent observations suggest that the automated segmentation method described usefully segments small bowel activity from other signal. Small bowel movement represented as TVA varied three-fold in the five volunteers and was inhibited by anti-muscarinic injection. Conclusion It is possible to develop a new measure, based on automated segmentation of mean signal amplitude changes, of small bowel peristalsis using dynamic MR.
Linking above‐ and belowground responses to global change at community and ecosystem scales

Cryptic belowground organisms are difficult to observe and their responses to global changes are not well understood. Nevertheless, there is reason to believe that interactions among above‐ and belowground communities may mediate ecosystem responses to global change. We used grassland mesocosms to manipulate the abundance of one important group of soil organisms, arbuscular mycorrhizal (AM) fungi, and to study community and ecosystem responses to CO2 and N enrichment. Responses of plants, AM fungi, phospholipid fatty acids and community‐level physiological profiles were measured after two growing seasons. Ecosystem responses were examined by measuring net primary production (NPP), evapotranspiration, total soil organic matter (SOM), and extractable mineral N. Structural equation modeling was used to examine the causal relationships among treatments and response variables. We found that while CO2 and N tended to directly impact ecosystem functions (evapotranspiration and NPP, respectively), AM fungi indirectly impacted ecosystem functions by influencing the community composition of plants and other root fungi, soil fungi and soil bacteria. We found that the mycotrophic status of the dominant plant species in the mesocosms determined whether the presence of AM fungi increased or decreased NPP. Mycotrophic grasses dominated the mesocosm communities during the first growing season, and the mycorrhizal treatments had the highest NPP. In contrast, nonmycotrophic forbs were dominant during the second growing season and the mycorrhizal treatments had the lowest NPP. The composition of the plant community strongly influenced soil N, and the community composition of soil organisms strongly influenced SOM accumulation in the mesocosms. These results show how linkages between above‐ and belowground communities can determine ecosystem responses to global change.
Inquiry and the social : an empirical study of the construction of knowledge in architectural designing

This thesis is a study of inquiry. Drawing upon the work of American pragmatist John Dewey, this work seeks to contribute to our understanding of the construction of knowledge within the social system of communities of inquiry. The process of inquiry that is traced in this work is one effected in the course of architectural designing. An ethnographically informed study of an architectural masterplan project is used to illustrate Dewey’s ideas and how they’re played out in design practice. This thesis is understood to correspond with the growing interest of the students of organisational learning and knowledge management in knowledge creation and the underlying social processes. It is further seen as a response to the claim that the key processes of knowledge creation remain largely an enigma. Illuminating such processes is considered important for that they inform vital organisational practices such as innovation and change. Agreement has been established with Dewey that knowledge is not just an end in itself but a form of action, a medium of change and social transformation. The formation of knowledge, however, within the operation of inquiry is not a matter that “naturally” runs its course. The process of inquiry as studied both in theory and practice has shown just how much its results, which by definition constitute knowledge, are shaped by the institution and control of a problem. A problem is a social construct and the product of the purposeful selection and arrangement of pieces of information. Inquiry is therefore considered a process of controlled knowledge formation. That which counts as knowledge in the realm of social phenomena has been shown to be a matter not so much of agreement between actions and their consequences but agreement in terms of intellectual acceptance. What “satisfies” as a solution (such as the final masterplan) has therefore been shown to be not necessarily a question of its logical status.
Scalable Pattern-Matching via Dynamic Differentiated Distributed Detection (D4)

Pattern Matching (PM) over network packet flows for Network Intrusion Detection/Prevention System is becoming more and more performance sensitive due to the rapid progress of Internet applications in terms of data volumes. Meanwhile, modern multicore platforms are becoming performance competitive with traditional hardware solutions for PM. But due to the unbalance of network flow sizes, traditional flow- based data parallel processing/programming model can not fully exert multicore platforms' computing power and results in poor performance scalability. In this paper, a novel parallel inspection model, Dynamic Differentiated Distributed Detection (D4) is proposed. D4 deploys distributed parallel operations by adding one more dimension on workload partition/allocation. It proposes an effective and efficient scheme to pre-partition the pattern set in several candidate ways, called "Detection Modes", and let multiple candidate PM methods to handle the subsets, respectively; the most suitable Detection Mode would be selected specifically for each incoming flows at the run-time, and the workload would be dynamically allocated among multiple CPU cores. Experimental results on real-world pattern set and traffic traces show that D4 scales much better than traditional schemes by better balancing the load among the processors while avoiding unnecessary overheads.
Chaos criterion on some quadric polynomial maps and design for chaotic pseudorandom number generator

This paper sets up a chaos criterion on some quadric polynomial discrete maps (QPDM). Using the criterion obtains a kind of quadric polynomial discrete maps with chaotic dynamic behaviors. A chaotic pseudorandom number generator (CPNG) is designed based on a chaotic quadric polynomial discrete map. Using the FIPS 140-2 tests issued by the National Institute of Standard and Technology verifies the random properties of the binary number sequences generated by the CPNG. The results showed that all binary number sequences passed the tests. The confidence interval analysis showed that the binary number sequences have sound random properties
Exploration of continuous variability in collections of 3D shapes

As large public repositories of 3D shapes continue to grow, the amount of shape variability in such collections also increases, both in terms of the number of different classes of shapes, as well as the geometric variability of shapes within each class. While this gives users more choice for shape selection, it can be difficult to explore large collections and understand the range of variations amongst the shapes. Exploration is particularly challenging for public shape repositories, which are often only loosely tagged and contain neither point-based nor part-based correspondences. In this paper, we present a method for discovering and exploring continuous variability in a collection of 3D shapes without correspondences. Our method is based on a novel navigation interface that allows users to explore a collection of related shapes by deforming a base template shape through a set of intuitive deformation controls. We also help the user to select the most meaningful deformations using a novel technique for learning shape variability in terms of deformations of the template. Our technique assumes that the set of shapes lies near a low-dimensional manifold in a certain descriptor space, which allows us to avoid establishing correspondences between shapes, while being rotation and scaling invariant. We present results on several shape collections taken directly from public repositories.
Strategic Voting Over Strategic Proposals

Prior research on â€œstrategic votingâ€ has reached the conclusion that unanimity rule is uniquely bad: it results in destruction of information, and hence makes voters worse off. We show that this conclusion depends critically on the assumption that the issue being voted on is exogenous, i.e., independent of the voting rule used. We depart from the existing literature by endogenizing the proposal that is put to a vote, and establish that under many circumstances unanimity rule makes voters better off. Moreover, in some cases unanimity rule also makes the proposing individual better off even when he has diametrically opposing preferences. In this case, unanimity is the Pareto dominant voting rule. Voters prefer unanimity rule because it induces the proposing individual to make a more attractive proposal. The proposing individual prefers unanimity rule because the acceptance probabilities for moderate proposals are higher.
Interventions to improve medication‐adherence after transplantation: a systematic review

Reports of interventions to improve adherence to medical regimens in solid organ transplant recipients are scarce. A systematic review identified 12 intervention studies. These studies focused on renal, heart, and liver transplant recipients. Five reports used randomized controlled trial (RCT) designs. Sample sizes varied between 18 and 110 subjects. The interventions are difficult to evaluate and categorize because of brief descriptions of intervention details. Of the 12 studies identified in this review, only five studies found a statistically significant improvement in at least one medication‐adherence outcome with the intervention. In general, most included a combination of patient‐focused cognitive/educational, counseling/behavioral, and psychologic/affective dimensions. Eight studies intervened at the healthcare provider, healthcare setting or healthcare system level, but showed a limited improvement in adherence. No single intervention proved to be superior at increasing medication‐adherence in organ transplantation, but a combination of interventions in a team approach for the chronic disease management of organ transplant patients may be effective in a long‐term perspective. In conclusion, finding the most effective combination of interventions to enhance adherence is vital. Utilizing an RCT design and adhering to the CONSORT guidelines can lead to higher quality studies and possibly more effective intervention studies to enhance medication‐adherence.
The Development of the Concept of Difficulty.

According to attributional analyses of the development of achieve ment motivation, developmental changes in achievement affect and overt achievement behavior can be explained as reflections of changes in the cognitive mediators of that behavior (Nicholls, 1978; Ruble, Parsons, & Ross, 1976; Weiner & Kun, in press). That is, changes in the way children interpret tasks and performance outcomes mediate changes in affective reactions and behavior. One of the more dramatic age-changes in achievement behavior occurs at about seven years. Below this age, almost all children prefer easy tasks when difficulty is communicated in the form of performance norms. Most older children, on the other hand select normatively diffi cult or intermediate level tasks (Veroff, 1969). This change has been explained in terms of the development of understanding that more difficult tasks require greater ability (Nicholls, 1978). Within the framework of attribution theory, a person's difficulty level preferences are held to reflect the attempt to demonstrate high ability while avoid ing demonstrating low ability (Kukla, 1978). People generally select tasks with intermediate subjective probabilities of success where the chances of demonstrating high rather than low ability appear optimum. Individuals with high self-concepts of ability will have inter mediate subjective probabilities of success on difficult tasks and prefer such tasks. Those with low self-concepts of ability will have inter mediate subjective probabilities of success on easy tasks and prefer easy tasks. For older children, norms not only provide a basis for estimating probabilities of success. They also indicate which tasks it is more impressive to succeed on: that is, those demanding more ability— the difficult ones. Thus, provided they perceive their ability on the relevant tasks as moderate or high, they will not choose easy tasks. Young children, on the other hand, do not understand that more nor matively difficult tasks demand greater ability. Consequently, they
Low Computational Color Secret Sharing Schemes with High Shares Quality Color Secret Sharing

Secret image sharing, a technology of secret communication, transmits secret images by distributing camouflage images (shares) to a group of participants, where each camouflage image contains a part of secret images. Secret images can be reconstructed under the conditions of a sufficient number of shares gathered and processed using a revealing algorithm. In 2009, Tsai et al. proposed a novel secret image sharing scheme using exclusive-or operators, principal component analysis (PCA), and feed-forward (FF) neural networks. The performance of their scheme was better than that of more recently proposed schemes, however, PCA and FF neural networks are time-consuming technologies and secret images cannot be completely restored. In this paper, we proposed an improved secret image sharing scheme to solve these problems. Experimental results show that camouflage image qualities of the proposed method were 54.26 dB on average, which is higher than that of Tsai et al.¡¦s scheme. Meanwhile, hiding capacity of the proposed mechanism was 1.125 times larger than that of Tsai et al.¡¦s scheme. Additionally, results also contribute to the literature by illustrating that original secret images can be reversed.
MyD88 and Trif Target Beclin 1 to Trigger Autophagy in Macrophages*

The Toll-like receptors (TLR) play an instructive role in innate and adaptive immunity by recognizing specific molecular patterns from pathogens. Autophagy removes intracellular pathogens and participates in antigen presentation. Here, we demonstrate that not only TLR4, but also other TLR family members induce autophagy in macrophages, which is inhibited by MyD88, Trif, or Beclin 1 shRNA expression. MyD88 and Trif co-immunoprecipitate with Beclin 1, a key factor in autophagosome formation. TLR signaling enhances the interaction of MyD88 and Trif with Beclin 1, and reduces the binding of Beclin 1 to Bcl-2. These findings indicate TLR signaling via its adaptor proteins reduces the binding of Beclin 1 to Bcl-2 by recruiting Beclin 1 into the TLR-signaling complex leading to autophagy.
Mistore: A distributed storage system leveraging the DSL infrastructure of an ISP

Internet Service Providers (ISPs) furnishing cloud storage services usually rely on big data centers. These centralized architectures induce many drawbacks in terms of scalability, reliability, and high access latency as data centers are single points of failure and are not necessarily located close to the users. This paper introduces Mistore, a distributed storage system aiming to ensure data availability, durability, low access latency by leveraging the Digital Subscriber Line infrastructure of an ISP. Mistore uses the available storage resources of a large number of home gateways and points of presence for content storage and caching facilities. Mistore also targets data consistency by providing multiple types of consistency criteria on content and a versioning system. Mistore validation has been achieved through extensive simulations.
Cognitive, affective and behavioural characteristics of mothers with anxiety disorders in the context of child anxiety disorder

Parental emotional distress, particularly high maternal anxiety, is one of the most consistent predictors of child anxiety treatment outcome. In order to identify the cognitive, affective and behavioural parenting characteristics of mothers of children with anxiety disorders who themselves have an anxiety disorder, we assessed the expectations and appraisals of 88 mothers of anxious children (44 not anxious (NONANX) and 44 with a current anxiety disorder (ANX)) before and after interacting with their 7-12 year old children. There were no observed differences in anxiety and avoidance among children of ANX and NONANX mothers, but, compared to NONANX mothers, ANX mothers held more negative expectations and differed on observations of intrusiveness, expressed anxiety, warmth and the quality of the relationship. Associations were moderated by the degree to which children expressed anxiety during the tasks. Maternal reported negative emotions during the task significantly mediated the association between maternal anxiety status and the observed quality of the relationship. These findings suggest that maternal anxiety disorder is associated with reduced tolerance of children’ s negative emotions. This may interfere with the maintenance of a positive, supportive mother-child interaction under conditions of stress, and as such impede optimum treatment outcomes. The findings identify potential cognitive, affective and behavioural targets to improve treatment outcomes for children with anxiety disorders in the context of a current maternal anxiety disorder.
Influence of the menstrual cycle on sympathetic activity, baroreflex sensitivity, and vascular transduction in young women.

BACKGROUND Our goal was to test sympathetic and cardiovagal baroreflex sensitivity and the transduction of sympathetic traffic into vascular resistance during the early follicular (EF) and midluteal (ML) phases of the menstrual cycle. METHODS AND RESULTS Sympathetic baroreflex sensitivity was assessed by lowering and raising blood pressure with intravenous bolus doses of sodium nitroprusside and phenylephrine. It was defined as the slope relating muscle sympathetic nerve activity (MSNA; determined by microneurography) and diastolic blood pressure. Cardiovagal baroreflex sensitivity was defined as the slope relating R-R interval and systolic blood pressure. Vascular transduction was evaluated during ischemic handgrip exercise and postexercise ischemia, and it was defined as the slope relating MSNA and calf vascular resistance (determined by plethysmography). Resting MSNA (EF, 1170+/-151 U/min; ML, 2252+/-251 U/min; P<0.001) and plasma norepinephrine levels (EF, 240+/-21 pg/mL; ML, 294+/-25 pg/mL; P=0. 025) were significantly higher in the ML than in the EF phase. Furthermore, sympathetic baroreflex sensitivity was greater during the ML than the EF phase in every subject (MSNA/diastolic blood pressure slopes: EF, -4.15; FL, -5.42; P=0.005). No significant differences in cardiovagal baroreflex sensitivity or vascular transduction were observed. CONCLUSIONS The present study suggests that the hormonal fluctuations that occur during the normal menstrual cycle may alter sympathetic outflow but not the transduction of sympathetic activity into vascular resistance.
Performance Comparison of CVD Grown Carbon Nanofiber Based on Single- and Multi-Layer Graphene Oxides in Melt-Compounded PA6.6 Nanocomposites

In the present study, newly design hybrid nanostructures were produced by growing long carbon nanofibers (CNF) on single- and multi-layer graphene oxide (GO) sheets in the presence of catalyst by chemical vapor deposition (CVD). Chemical composition analysis indicated the formation of Fe-C bonds by the deposition of carbon atoms on catalyst surface of Fe2O3 and increasing in C/O atomic ratio confirming CNF growing. These hybrid additives were distributed homogeneously through polyamide 6.6 (PA6.6) chains by high shear thermokinetic mixer in melt phase. Spectroscopic studies showed that the differences in the number of graphene layer in hybrid structures directly affected the crystalline behavior and dispersion state in polymer matrix. Flexural strength and flexural modulus of PA6.6 nanocomposites were improved up to 14.7% and 14% by the integration of 0.5 wt% CNF grown on multi-layer GO, respectively, whereas there was a significant loss in flexural properties of single-layer GO based nanocomposites. Also, the integration of 0.5 wt% multi-layer GO hybrid reinforcement in PA6.6 provided a significant increase in tensile modulus about 24%. Therefore, multi-layer GO with CNF increased the degree of crystallinity in nanocomposites by forming intercalated structure and acted as a nucleating agent causing the improvement in mechanical properties.
Detection of Encrypted Tunnels Across Network Boundaries

The use of covert application-layer tunnels to bypass security gateways has become quite popular in recent years. By encapsulating blocked or controlled protocols such as peer- to-peer, chat and e-mail into others allowed by the security policies, such as HTTP, SSH or even DNS, both legitimate and malicious users can effectively neutralize many security restrictions enforced at the network edge. Traditional firewalling techniques, based on Application Layer Gateways and even pattern-matching mechanisms are becoming practically useless as tunneling tools grow more sophisticated. In this paper we propose an effective solution to this problem based on a statistical traffic classification technique. Our mechanism relies on the creation of a statistical fingerprint of legitimate usage of a given protocol, such as regular remote interactive logins or secure copying activities. Such fingerprint can then be used to detect with high accuracy non-legitimate sessions, i.e., sessions that tunnel other protocols. Results from experiments conducted on a live network suggest that the technique can be very effective, even when the application layer protocol used as a tunnel is encrypted, such as in the case of SSH.