Miracle-dz/UniFAR-FTUs huggingface dataset:
Interscan Displacement-Induced Variance in PET Activation Data Is Excluded by a Scan-Specific Attenuation Correction

In PET activation studies, linear changes in regional cerebral blood flow may be caused by subject interscan displacements rather than by changes in cognitive state. The aim of this study was to investigate the impact of these artifacts and to assess whether they can be removed by applying a scan-specific calculated attenuation correction (CAC) instead of the default measured attenuation correction (MAC). Two independent data sets were analyzed, one with large (data I) and one with small (data II) interscan displacements. After attenuation correction (CAC or MAC), data were analyzed using SPM99. Interscan displacement parameters (IDP), obtained during scan realignment, were included as additional regressors in the General Linear Model and their impact was assessed by variance statistics revealing the affected brain volume. For data I, this volume reduced dramatically from 579 to 12 cm(3) (approximately 50-fold) at P(uncorr) </= 0.001 and from 100 to 0 cm(3) at P(corr) </= 0.05 when CAC was applied instead of MAC. Surprisingly, for data II, applying CAC instead of MAC still resulted in a substantial (approximately 10-fold) reduction of the affected volume from 23 to 2 cm(3) at P(uncorr) </= 0.001. We conclude that interscan displacement-induced variance can be prevented by applying a (realigned attenuation correction scan (e.g., CAC). With MAC data, introducing IDP covariates is not an alternative since they model only this variance. Even in data with minor interscan displacements, applying a (realigned attenuation correction method (e.g., CAC) is superior to a nonaligned MAC with IDP covariates.
RID-TWIN: An end-to-end pipeline for automatic face de-identification in videos

Face de-identification in videos is a challenging task in the domain of computer vision, primarily used in privacy-preserving applications. Despite the considerable progress achieved through generative vision models, there remain multiple challenges in the latest approaches. They lack a comprehensive discussion and evaluation of aspects such as realism, temporal coherence, and preservation of non-identifiable features. In our work, we propose RID-Twin: a novel pipeline that leverages the state-of-the-art generative models, and decouples identity from motion to perform automatic face de-identification in videos. We investigate the task from a holistic point of view and discuss how our approach addresses the pertinent existing challenges in this domain. We evaluate the performance of our methodology on the widely employed VoxCeleb2 dataset, and also a custom dataset designed to accommodate the limitations of certain behavioral variations absent in the VoxCeleb2 dataset. We discuss the implications and advantages of our work and suggest directions for future research.
FOLLOWING THE ACTION

Live sports blogging is a relatively new form of journalism in wide and frequent use by media companies but has received little attention from the academy. This article outlines a study that explored the belief and value system behind live sports blogging to establish whether shifts were taking place within the professional ideology of sports journalism. In-depth, semi-structured interviews were conducted with 10 live sports bloggers in the United Kingdom. The study found that live bloggers retained core journalistic values and beliefs of balancing objectivity and subjectivity, immediacy, providing a public service and editorial autonomy. However, live blogging's challenges of immediacy, interactivity and shifting consumption patterns have led to a reimagining of what these concepts mean and the skills and competences required. Live bloggers perceived their role as community builders and mediators of discussion as well as information providers, and this represents a new openness and inclusivity within the occupational base. Participants did not regard these changes to be a dumbing down of standards but rather a paradigm shift towards flattening hierarchies between journalist and audience. The findings suggest live bloggers have shown a greater willingness to adapt than previous research into the migration of sports journalists to digital platforms has found.
Immune system-dependent and -independent replication of the scrapie agent

Using the severe combined immunodeficiency (SCID) mouse model, we investigated the requirement of the immune system for the development of scrapie after peripheral inoculation. A total of 33% of SCID mice, all but one immunologically reconstituted SCID mice (93%), and all CB17 control mice developed the disease. PrPres was detectable in the brains of all diseased animals and in the spleens of reconstituted SCID and CB17 control mice but not of the diseased non-immunologically reconstituted SCID mice. The immune system appears to be a primary target in the pathogenesis of scrapie, but direct spread to the central nervous system from the peritoneum via visceral nerve fibers can probably also occur.
Visual analytics of text streams through multiple dynamic frequency matrices

We propose a Visual Analytics tool that supports situation awareness and exploration tasks for text streams. To reach this goal, we design our own data model to encode streaming text in multiple dynamic frequency matrices, handling multiple aspects of data. Our visualizations are composed first of two dynamic Theme Rivers. They allow real time exploration of all the aspects extracted from texts stored in both, short-term and long-term buffers. In addition, we visualize the geographical location of messages on a map. We use these visualizations, enhanced by efficient user interaction mechanisms, to answer the questions of the third mini-challenge of 2014 VAST Challenge. As a result we identify several challenging issues that we will investigate in future work.
How Useful Are the Concepts “Innate” and “Adaptation” for Explaining Human Development

Adaptationist thinking has played an important role in the life sciences, especially since the neo-Darwinian modern synthesis of Darwinian natural selection and Mendelian genetics that occurred in the 1930s. Adaptationist approaches focus on what a phenotype ‘‘is for’’ by reasoning about what particular adaptive problem it might have solved in an ancestral environment. This in turn leads to hypotheses regarding the manner in which the phenotype in question may have enhanced reproductive success. In the past 20 years or so, largely through the work of evolutionary psychologists, adaptationist explanation has become more common in psychology. During this same period of time, core knowledge explanations of human development have also increased in popularity. Such researchers conceive of the core capacities for which they marshal empirical evidence as the products of natural selection and, therefore, adaptations. In this article, I briefly describe these two approaches to human development and place their adaptationist programs in a historical context. I then describe recent developments that complicate adaptationist and innatist claims and briefly discuss the possibility of an alternative evolutionary meta-theory. In a general sense, evolutionary psychology can be understood as the study of the effect of evolutionary change on psychological development. It is sometimes capitalized as Evolutionary Psychology to single out the so-called Santa Barbara school of evolutionary psychology associated primarily with the theorizing of Tooby and Cosmides, but also Pinker, Buss and a few others [e.g., Buss, 1995; Pinker, 2003; Tooby & Cosmides, 1992]. Although my goal in this necessarily brief article is to discuss adaptationism more generally, I focus on evolutionary psychology because it lays out the basic assumptions that are in play when psychologists claim that a given phenotype is the result of an adaptation and is, accordingly, in some sense innate. In broad strokes, evolutionary psychology explains currently adaptive behavior – and sometimes maladaptive behavior through relying on mismatch arguments between our ancestral and modern environment – in terms of specific cognitive adaptations that are the product of the differential reproductive successes of our hominid ancestors. It is explicitly adaptationist because it explains human development by attempting to
‘Thinking Before Acting’ or ‘Acting Before Thinking’: Antecedents of Individual Action Propensity in Work Situations

We introduce the concept of ‘individual action propensity’ to examine the approach of individuals towards solving situations for which they lack knowledge and/or experience about what to do. We focus on a naturally contrasting pair of responses: ‘thinking before acting’ or ‘acting before thinking’, and associate low action propensity with thinking one's way into understanding how to act, and high action propensity with acting one's way into understanding such situations. We build on regulatory mode theory – with its dimensions of locomotion and assessment and the trade-off between speed and accuracy – to examine individual characteristics as predictors of individual action propensity. We find that individual action propensity is associated with being a woman, having fewer years of formal education, not relying on help-seeking behaviours, and having a positive attitude towards spontaneity. Our findings shed light on why individuals take action, or not, and provide implications for research on organizational action propensity.
Short-Term Effects of a Web-Based Guided Self-Help Intervention for Employees With Depressive Symptoms: Randomized Controlled Trial

BACKGROUND Depressive disorders are highly prevalent in the working population and are associated with excessive costs. The evidence for effective worker-directed interventions for employees with depressive symptoms is limited. Treating employees with depressive symptoms before sick leave via the Internet could be beneficial and cost saving. OBJECTIVE In this study, we developed and tested the effectiveness of a Web-based guided self-help course for employees with depressive symptoms. We report on the posttreatment effectiveness of the intervention. METHODS This study is a two-arm randomized controlled trial comparing a Web-based guided self-help course to care as usual (CAU). We recruited employees from 6 different companies via the companies' intranet and posters. The main inclusion criterion was elevated depressive symptoms as measured by a score of ≥16 on the Center for Epidemiological Studies Depression scale (CES-D). The intervention (Happy@Work) was based on problem-solving treatment and cognitive therapy and consisted of 6 weekly lessons. Participants were asked to submit their weekly assignment via the website after completion. They subsequently received feedback from a coach via the website. Self-report questionnaires on depressive symptoms (CES-D; primary outcome), anxiety measured by the Hospital Anxiety and Depression Scale (HADS), burnout measured by the Maslach Burnout Inventory (MBI), and work performance measured by the Health and Work Performance Questionnaire (HPQ; secondary outcomes) were completed at baseline and at posttreatment. RESULTS A total of 231 employees were randomized to either the intervention group (n=116) or CAU (n=115). The posttreatment assessment was completed by 171 (74.0%) participants. Both the intervention and the CAU group showed significant improvements in the primary outcome of depressive symptoms, but no differences between the conditions was found (d=0.16, 95% CI -0.10 to 0.41, P=.29). Significant but small effects in favor of the intervention group were found for anxiety symptoms (d=0.16, 95% CI -0.09 to 0.42, P=.04) and exhaustion (d=0.17, 95% CI -0.09 to 0.43, P=.02). CONCLUSIONS This study showed that a Web-based guided self-help course for employees with depressive symptoms was not more effective in reducing depressive symptoms among employees than CAU. Large improvements in depressive symptoms in the CAU group were unforeseen and potential explanations are discussed.
On the Limitations of Greedy Mechanism Design for Truthful Combinatorial Auctions

We study mechanisms for the combinatorial auction (CA) problem, in which m objects are sold to rational agents and the goal is to maximize social welfare. Of particular interest is the special case of s-CAs, where agents are interested in sets of size at most s, for which a simple greedy algorithm obtains an s + 1 approximation, but no polynomial time deterministic truthful mechanism is known to attain an approximation ratio better than O(m/√log m). We view this not only as an extreme gap between the power of greedy auctions and truthful greedy auctions, but also as exemplifying the gap between the known power of truthful and non-truthful polynomial time deterministic algorithms. We associate the notion of greediness with a broad class of algorithms, known as priority algorithms, which encapsulate many natural auction methods. This motivates us to ask: how well can a truthful greedy algorithm approximate the optimal social welfare for CA problems? We show that no truthful greedy priority algorithm can obtain an approximation to the CA problem that is sublinear in m, even for s-CAs with s ≥ 2. Our inapproximations are independent of any time constraints on the mechanism and are purely a consequence of the greedy-type restriction. We conclude that any truthful combinatorial auction mechanism with a non-trivial approximation factor must fall outside the scope of many natural auction methods.
A Proposal of a Workflow-based CBR for Interventional CDSS - Application to Transcatheter Aortic Valve Implantation (TAVI)

A Clinical Decision Support System (CDSS) is an interactive software designed to assist physicians, and other health professionals, with health decision-making tasks through an inference process that associates observations with conclusions supported by objective and expert knowledge on a specific application domain. As complexity of surgical processes arises, there is a demand from the clinicians to extend the capabilities from a pure research database towards a clinically integrated decision support system. The work presented in this paper details a proposal of a CDSS designed to to assess clinicians during interventions by retrieving and reusing past similar cases. Following an operative workflow, the designed software will use a Case-Based Reasoning (CBR) methodology to retrieve similar past cases from a case base to give case-specific advice at any particular point of the process, specially during preoperative and intraoperative stages. The proposal intends to develop a monitoring mechanism capable to recognize relevant data to every stage in the intervention workflow. Thus, measures and observations generated during the intervention will be used to retrieve the most similar cases occurred in previous occasions. The paper proposes an example application of the CBR strategy, where it is adapted to a recent complex minimally invasive intervention which is receiving growing attention lately, the Transcatheter Aortic Valve Implantation (TAVI).
A common framework for the analysis of complex motion? Standstill and capture illusions

A series of illusions was created by presenting stimuli, which consisted of two overlapping surfaces each defined by textures of independent visual features (i.e., modulation of luminance, color, depth, etc.). When presented concurrently with a stationary 2-D luminance texture, observers often fail to perceive the motion of an overlapping stereoscopically defined depth-texture. This illusory motion standstill arises due to a failure to represent two independent surfaces (one for luminance and one for depth textures) and motion transparency (the ability to perceive motion of both surfaces simultaneously). Instead the stimulus is represented as a single non-transparent surface taking on the stationary nature of the luminance-defined texture. By contrast, if it is the 2D-luminance defined texture that is in motion, observers often perceive the stationary depth texture as also moving. In this latter case, the failure to represent the motion transparency of the two textures gives rise to illusionary motion capture. Our past work demonstrated that the illusions of motion standstill and motion capture can occur for depth-textures that are rotating, or expanding / contracting, or else spiraling. Here I extend these findings to include stereo-shearing. More importantly, it is the motion (or lack thereof) of the luminance texture that determines how the motion of the depth will be perceived. This observation is strongly in favor of a single pathway for complex motion that operates on luminance-defines texture motion signals only. In addition, these complex motion illusions arise with chromatically-defined textures with smooth transitions between their colors. This suggests that in respect to color motion perception the complex motions' pathway is only able to accurately process signals from isoluminant colored textures with sharp transitions between colors, and/or moving at high speeds, which is conceivable if it relies on inputs from a hypothetical dual opponent color pathway.
Inferring Community Structure in Healthcare Forums

Summary Background: Detecting community structures in complex networks is a problem interesting to several domains. In healthcare, discovering communities may enhance the quality of web offerings for people with chronic diseases. Understanding the social dynamics and community attachments is key to predicting and influencing interaction and information flow to the right patients. Objectives: The goal of the study is to empirically assess the extent to which we can infer meaningful community structures from implicit networks of peer interaction in online healthcare forums. Methods: We used datasets from five online diabetes forums to design networks based on peer-interactions. A quality function based on user interaction similarity was used to assess the quality of the discovered communities to complement existing homophily measures. Results: Results show that we can infer meaningful communities by observing forum interactions. Closely similar users tended to co-appear in the top communities, suggesting the discovered communities are intuitive. The number of years since diagnosis was a significant factor for cohesiveness in some diabetes communities. Conclusion: Network analysis is a tool that can be useful in studying implicit networks that form in healthcare forums. Current analysis informs further work on predicting and influencing interaction, information flow and user interests that could be useful for personalizing medical social media.
Finding Co-occurring Text Phrases by Combining Sequence and Frequent Set Discovery

A signiicant amount of data resides in loosely structured text collections. The concept of text mining has recently been introduced in order to utilize these resources in data mining driven decision making. In our approach, we consider nding multi-term text phrases that tend to co-occur in the documents of a document collection. We combine and further develop two techniques, nding frequent sequences and nding frequent sets, and discuss their suitabil-ity for text mining. The process presented in this paper contains two major phases. In the rst phase, maximal frequent sequences are extracted from documents, i.e., such sequences of words that are frequent in the document collection and that are not contained in any other longer frequent sequence. A sequence is considered to be frequent if it appears in at least documents, when is a given frequency threshold. For instance, we may require the sequences to occur in at least 10 documents. In the second phase, co-occurrences of the maximal frequent sequences are found by discovering frequent sets of the sequences, i.e., which sequences tend to co-occur in several documents. We have implemented the methods and experimented with a news collection. The experiments reveal many characteristics of textual data, which aaect the further development and application of the methods.
A Novel Wavelet-Based Energy Detection for Compressive Spectrum Sensing

Wavelet transform has proved to be an attractive tool in terms of analyzing singularities and irregular structures, which can characterize irregular edges of signals. Thus, it is well motivated to apply the wavelet transform approach to wideband spectrum sensing. But the existing wavelet-based spectrum sensing schemes work under the assumption that the frequency response of the analog signal input at the sensing receiver is real. To make this method work for more types of signals, this paper develops a novel wavelet-based approach to compressive wide-band spectrum sensing. In the proposed scheme, the wide-band time domain signal is fed into a number of filters and the sub-Nyquist sampled outputs are utilized to detect the occupancy of spectrum via a wavelet-based edge detector. The filters' outputs are real and nonnegative, regardless of the style of the analog signal. Furthermore, through simply adding the measurement vectors at the fusion center, this scheme can be applied to the case of multiple cognitive radios (CRs), reducing the complexity compared with traditional joint recovery algorithms.
Copy Number Variation Analysis of Matched Ovarian Primary Tumors and Peritoneal Metastasis

Ovarian cancer is the most deadly gynecological cancer. The high rate of mortality is due to the large tumor burden with extensive metastatic lesion of the abdominal cavity. Despite initial chemosensitivity and improved surgical procedures, abdominal recurrence remains an issue and results in patients' poor prognosis. Transcriptomic and genetic studies have revealed significant genome pathologies in the primary tumors and yielded important information regarding carcinogenesis. There are, however, few studies on genetic alterations and their consequences in peritoneal metastatic tumors when compared to their matched ovarian primary tumors. We used high-density SNP arrays to investigate copy number variations in matched primary and metastatic ovarian cancer from 9 patients. Here we show that copy number variations acquired by ovarian tumors are significantly different between matched primary and metastatic tumors and these are likely due to different functional requirements. We show that these copy number variations clearly differentially affect specific pathways including the JAK/STAT and cytokine signaling pathways. While many have shown complex involvement of cytokines in the ovarian cancer environment we provide evidence that ovarian tumors have specific copy number variation differences in many of these genes.
A Survey of Single Database PIR: Techniques and Applications

In this paper we survey the notion of Single-Database Private Information Retrieval (PIR). The first Single-Database PIR was constructed in 1997 by Kushilevitz and Ostrovsky and since then Single-Database PIR has emerged as an important cryptographic primitive. For example, Single-Database PIR turned out to be intimately connected to collision-resistant hash functions, oblivious transfer and public-key encryptions with additional properties. In this survey, we give an overview of many of the constructions for Single-Database PIR (including an abstract construction based upon homomorphic encryption) and describe some of the connections of PIR to other primitives.