Miracle-dz/UniFAR-FTUs huggingface dataset:
How Do Time Limits Affect Our Psychotherapies? A Literature Review

The application of time limits (i.e. restricting the amount of sessions before the beginning of psychotherapy) has become ingrained in psychotherapy research and in the context of managed care, mostly due to pragmatic and economic reasons. However, little is know on how this technique interferes with the psychotherapeutic process. Although several theorists have considered the possible advantages and drawbacks of the technique, research explaining these mechanisms is scattered. By conducting this review, we strived to answer two questions: (1) Does a time limit alter the psychotherapeutic process? And (2) In what way? In doing so, this study aspires to grant more insight into the mechanisms of time limited psychotherapy and aimes to contribute to a first understanding of the dynamics of a time restricted therapy process. We searched for articles in the databases of Web of Science and Pubmed. Our review identified 28 studies that provide empirical grounds to explain processes involved when applying a time limit to psychotherapy. Qualitative research suggests that a time limit exerts pressure on the therapy process and creates an expectancy effect, which can have both positive and negative consequences. Additionally, time limits can be associated to therapists taking on a more directive role in therapy. Results show that a time limit is anything but a neutral intervention; it is a technique that complexly interacts with therapy processes on multiple grounds. Further research is vital to determine which environment is appropriate for its application.
Cryptomnesia: Delineating inadvertent plagiarism.

Cryptomnesia, or inadvertent plagiarism, was experimentally examined in three investigations. Subjects were required to generate category exemplars, alternating with 3 other subjects in Experiments 1 and 2 or with a standardized, written list in Experiment 3. After this generation stage, subjects attempted to recall those items which they had just generated and an equal number of completely new items from each category. Plagiarism of others' generated responses occurred in all three tasks (generation, recall own, and recall new) in each experiment, despite instructions to avoid such intrusions. The amount of plagiarism was greater under more complex generation sequences and for items produced from orthographic relative to semantic categories. The most likely source of plagiarized responses was the person who had responded just before the subject in the generation sequence. Directions for future research are discussed. The topic of plagiarism is of universal interest to scholar/ teachers because of occasional incidents encountered either with colleagues or students. Although intentional plagiarism is clearly an anathema to all professionals, there are situations where duplication occurs inadvertently. This uninlentional plagiarism, or cryptomnesia, is the focus of the present article. In the technical definition, cryptomnesia is ". the presence of phenomena in normal consciousness which objectively are memories, but subjectively are not recognized as such. " (Taylor, 1965, p. 1111). Cryptomnesia refers to generating a word, an idea, a song, or a solution to a problem, with the belief that it is either totally original, or at least original within the present context. In actuality, the item is not original, but one which has been produced by someone else (or even oneself) at some earlier time. A number of anecdotal discussions of cryptomnesia exist. Some of these recount public scandals where prominent individuals such as Nietzsche (Jung, 1905/1957) and Helen Keller (Bowers & Hilgard, 1986) have been accused of copying portions of other person's works. Freud (1901/1960) related that when he was developing his theory on original bisexuality, Fliess (a friend and professional colleague) reminded Freud that he had given Freud the idea several years earlier. At that time, Freud rejected his claim but later recalled the earlier incident.
Convergence in the bilingual lexicon: A pre-registered replication study

We successfully replicated the finding of a converged naming pa! ern in bilinguals consistent with a moderate version of the one-pa! ern hypothesis. The par"ally merged naming pa! erns of the bilinguals were found to form a compromise between the naming pa! erns of both their languages. Convergence in the bilingual lexicon: a pre-registered replication study Anne White 1 , Barbara Malt 2 , Gert Storms 1
Randomized Concurrent Set Union and Generalized Wake-Up

We consider the disjoint set union problem in the asynchronous shared memory multiprocessor computation model. We design a randomized algorithm that performs at most O(log n) work per operation (with high probability), and performs at most O(m #8226; (α(n, m/(np)) + log(np/m + 1)) total work in expectation for a problem instance with m operations on n elements solved by p processes. Our algorithm is the first to have work bounds that grow sublinearly with p against an adversarial scheduler. We use Jayanti's Wake Up problem and our newly defined Generalized Wake Up problem to prove several lower bounds on concurrent set union. We show an Ω(log min {n,p}) expected work lower bound on the cost of any single operation on a set union algorithm. This shows that our single-operation upper bound is optimal across all algorithms when p = nΩ(1). Furthermore, we identify a class of "symmetric algorithms'' that captures the complexities of all the known algorithms for the disjoint set union problem, and prove an Ω(m•(α(n, m(np)) + log(np/m + 1))) expected total work lower bound on algorithms of this class, thereby showing that our algorithm has optimal total work complexity for this class. Finally, we prove that any randomized algorithm, symmetric or not, cannot breach an Ω(m •(α(n, m/n) + log log(np/m + 1))) expected total work lower bound.
Domain Generalization via Multidomain Discriminant Analysis

Domain generalization (DG) aims to incorporate knowledge from multiple source domains into a single model that could generalize well on unseen target domains. This problem is ubiquitous in practice since the distributions of the target data may rarely be identical to those of the source data. In this paper, we propose Multidomain Discriminant Analysis (MDA) to address DG of classification tasks in general situations. MDA learns a domain-invariant feature transformation that aims to achieve appealing properties, including a minimal divergence among domains within each class, a maximal separability among classes, and overall maximal compactness of all classes. Furthermore, we provide the bounds on excess risk and generalization error by learning theory analysis. Comprehensive experiments on synthetic and real benchmark datasets demonstrate the effectiveness of MDA.
Reviewing Theories of Adolescent Substance Use: Organizing Pieces in the Puzzle

This article reviews 14 multivariate theories of experimental substance use (e.g., alcohol and marijuana use) among adolescents, including those theories that emphasize (a) substance-specific cognitions, (b) social learning processes, (c) commitment to conventional values and attachment to families, and (d) intrapersonal processes. Important similarities and differences among these theories are addressed, as are the conceptual boundaries of each theory. In an attempt to integrate existing theories, a framework is proposed that organizes their central constructs into 3 distinct types of influence (viz., social, attitudinal, and intrapersonal) and 3 distinct levels of influence (viz., proximal, distal, and ultimate). Implications for future theory development are discussed.
Categorical phoneme labeling in children with dyslexia does not depend on stimulus duration

It is established that individuals with dyslexia are less consistent at auditory phoneme categorization than typical readers. One hypothesis attributes these differences in phoneme labeling to differences in auditory cue integration over time, suggesting that the performance of individuals with dyslexia would improve with longer exposure to informative phonetic cues. Here, the relationship between phoneme labeling and reading ability was investigated while manipulating the duration of steady-state auditory information available in a consonant-vowel syllable. Children with dyslexia obtained no more benefit from longer cues than did children with typical reading skills, suggesting that poor task performance is not explained by deficits in temporal integration or temporal sampling.
Expanding the Soy Moratorium to Brazil’s Cerrado

Expanding the Soy Moratorium to the Cerrado biome would prevent the direct conversion of 3.6 million ha of intact Cerrado to soy. The Cerrado biome in Brazil is a tropical savanna and an important global biodiversity hot spot. Today, only a fraction of its original area remains undisturbed, and this habitat is at risk of conversion to agriculture, especially to soybeans. Here, we present the first quantitative analysis of expanding the Soy Moratorium (SoyM) from the Brazilian Amazon to the Cerrado biome. The SoyM expansion to the Cerrado would prevent the direct conversion of 3.6 million ha of native vegetation to soybeans by 2050. Nationally, this would require a reduction in soybean area of approximately 2%. Relative risk of future native vegetation conversion for soybeans would be driven by the Brazilian domestic market, China, and the European Union. We conclude that, to preserve the Cerrado’s biodiversity and ecosystem services, urgent action is required, including a zero native vegetation conversion agreement such as the SoyM.
Bootstrapping Public Blockchains Without a Trusted Setup

We propose a protocol that allows the participants of a permissionless decentralized system to agree on a set of identities in the presence of a computationally-bounded Byzantine adversary. Our protocol guarantees that the fraction of identities belonging to the adversary in the set of identities is at most equal to the total computational hash power of the adversary. We significantly improve on the existing state-of-the-art in the following four ways. First, our algorithm runs in expected O(1) rounds, in contrast to previous results which require O(log n/log log n) rounds, where n is the number of initial nodes in the system. Second, we require each node to solve just one computational puzzle, whereas previous algorithms require O(log n/log log n) puzzles per node. Third, our algorithm sends only O(n) bits per node in expectation, whereas previous algorithms send O( (log2 n/log log n)) bits in expectation. Finally, in contrast to past results, our algorithm handles dynamic joining and leaving of nodes.
Clients' perceptions of helpful experiences in counseling

The question of what clients experience as helpful in counseling was examined via concept mapping, a methodological approach combining qualitative and quantitative strategies. The purpose of the study was to clarify the scope and interrelations among elements of the retrospective experience of helpfulness among 36 clients who had completed counseling after an average of 11 sessions. Five thematic clusters consistent with previous research were identified: Counselor Facilitative Interpersonal Style, Counselor Interventions, Generating Client Resources, New Perspectives, and Client Self-Disclosure. Four new thematic clusters were also identified: Emotional Relief, Gaining Knowledge, Accessibility, and Client Resolutions. The structure of the concept map generated by the participants in this study was found to be consistent with an integrative, pantheoretical model of the counseling process.
Problem-dependent Regret Bounds for Online Learning with Feedback Graphs

This paper addresses the stochastic multi-armed bandit problem with an undirected feed-back graph. We devise a UCB-based al-gorithm, UCB-NE, to provide a problem-dependent regret bound that depends on a clique covering. Our algorithm obtains regret which provably scales linearly with the clique covering number. Additionally, we provide problem-dependent regret bounds for a Thompson Sampling-based algorithm, TS-N, where again the bounds are linear in the clique covering number. Finally, we present experimental results to see how UCB-NE, TS-N, and a few related algorithms perform practically.
Remagnetization of Marcellus Formation in the Plateau Province of the Appalachian Basin

An integrated paleomagnetic, magnetic fabric, and petrographic study of two cores (EC: oriented; DB: unoriented) in the Devonian Marcellus Formation from the Plateau Province (PA) indicates the presence of chemical remanent magnetizations (CRMs) and extensive diagenetic alteration. Anisotropy of magnetic susceptibility results indicate a predominately oblate fabric. Some specimens contain a prolate fabric that is interpreted as diagenetically altered. A well-developed viscous magnetization, possibly contaminated by a drilling induced component, is not present in either core, and cannot be used for orientation. An intermediate temperature component with steep down inclinations (ITN) is removed in both cores below ~ 300°C. Specimens in DB also contain a component with steep up inclinations (ITR) that is removed between 300 and 440°C. The ITN is interpreted to reside in magnetite and/or possibly pyrrhotite, and the ITR resides in magnetite. The ITN could be a reversal of ITR, acquired in the Cretaceous to Cenozoic based on a comparison with the expected inclinations. Alternatively, the ITN could be a contaminated by a Brunhes viscous magnetization. Specimens from both cores contain a characteristic remanent magnetization (ChRM) with shallow inclinations that is removed by 500°C in DB and 460°C in EC, and is interpreted to reside in magnetite. The DB ChRM has an inclination of -9.0°, which corresponds to a range of ages between 310-225 Ma based on the expected inclinations. The ChRM in EC has streaked declinations, which may have been caused by core barrel rotation. Shallow inclinations (- 3.7°) in this core suggest a range of acquisition from 305-230 Ma. Rock magnetic data are consistent with the presence of magnetite but provide conflicting evidence for pyrrhotite. The ChRM in DB is interpreted as a CRM whereas the ChRM in EC could be thermoviscous in origin. Diagenetic studies indicate a complex paragenesis with authigenic minerals such as barite, sphalerite, baroque dolomite, and sylvite suggestive of alteration by external fluids. The presence of the CRM in highly altered zones suggests it is related to alteration by external fluids, although its presence in other facies suggests that burial diagenetic processes could also be a cause of remagnetization.
On judging and being judged accurately in zero-acquaintance situations.

This research examined the role of personality, nonverbal skills, and gender as moderators ofjudging and being judged accurately in zero-acquaintance situations. Unacquainted participants, assembled in groups, completed a battery of personality tests, took 2 audiovisual tests (the Profile of Nonverbal Sensitivity [PONS] and the Interpersonal Perception Task [IPT]) intended to assess decoding skills and then rated themselves and every other person in the group on a set of personality dimensions. Results indicated that more sociable and extraverted participants tended to be more legible, that is, were judged more accurately. Participants who were more accurate judges tended to be less sociable and performed better on tests of decoding accuracy. Performance on the PONS predicted accuracy ofjudgment for men, whereas performance on the IPT predicted accuracy of judgment for women. On the whole, results suggest that some important and theoretically relevant moderators of accuracy in the zero-acquaintance situation have been identified.
Efficient aggregated deliveries with strong guarantees in event-based distributed systems

Wilkin, Gregory Aaron PhD. , Purdue University, December 2015. Efficient Aggregated Deliveries with Strong Guarantees in Event-based Distributed Systems. Major Professor: Patrick Eugster. A popular approach to designing large scale distributed systems is to follow an eventbased approach. In an event-based approach, a set of software components interact by producing and consuming events. The event-based model allows for the decoupling of software components, allowing distributed systems to scale to a large number of components. Event correlation allows for higher order reasoning of events by constructing complex events from single, consumable events. In many cases, event correlation applications rely on centralized setups or broker overlay networks. In the case of centralized setups, the guarantees for complex event delivery are stronger, however, centralized setups create performance bottlenecks and single points of failure. With broker overlays, the performance and fault tolerance are improved but at the cost of weaker guarantees. The goal of this dissertation is to develop an efficient middleware for event correlation while still providing strong guarantees. First, we show what is necessary for strong guarantees in asynchronous distributed event-based systems that perform event correlation. Secondly, we provide the main deliverable of this dissertation: a generic middleware system, FAIDECS, which utilizes event types to efficiently correlate individually multicast events while providing strong guarantees for asynchronous event-based distributed systems. We then provide semantic alternatives to those provided in FAIDECS, showing what strong guarantees are able to be provided given certain operators.
UrbanEdge: deep learning empowered edge computing for urban IoT time series prediction

The revolution of smart city has led to rapid development and proliferation of Internet of Things (IoT) technologies, with the focus on transmitting raw sensory data into valuable knowledge. Meanwhile, the ubiquitous deployments of IoT are raising the importance of processing data in real-time at the edge of networks rather than in remote cloud data centers. Based on above, edge computing has been proposed to exploit the capabilities of edge devices in providing in-proximity computing services for various IoT applications. In this paper, we present UrbanEdge, a conceptual edge computing architecture empowered by deep learning for urban IoT time series prediction. We design a hierarchical architecture to process correlated IoT time series and illustrate the work-flow of UrbanEdge in data collection, data transmission and data processing. As a core component of UrbanEdge, a deep learning model is developed with attention-based recurrent neural networks. Composed with multiple processing layers, the deep learning model can extract feature representations from raw IoT data for monitoring and prediction. We evaluate the designed deep learning model of UrbanEdge on real-world datasets, evaluation results show that the UrbanEdge outperforms other baseline methods in time series prediction.
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging

There has recently been a concerted effort to derive mechanisms in vision and machine learning systems to offer uncertainty estimates of the predictions they make. Clearly, there are benefits to a system that is not only accurate but also has a sense for when it is not. Existing proposals center around Bayesian interpretations of modern deep architectures - these are effective but can often be computationally demanding. We show how classical ideas in the literature on exponential families on probabilistic networks provide an excellent starting point to derive uncertainty estimates in Gated Recurrent Units (GRU). Our proposal directly quantifies uncertainty deterministically, without the need for costly sampling-based estimation. We show that while uncertainty is quite useful by itself in computer vision and machine learning, we also demonstrate that it can play a key role in enabling statistical analysis with deep networks in neuroimaging studies with normative modeling methods. To our knowledge, this is the first result describing sampling-free uncertainty estimation for powerful sequential models such as GRUs.
Fault trees: Sensitivity of estimated failure probabilities to problem representation.

Abstract : Fault trees represent problem situations by organizing things that could go wrong into functional categories. Such trees are essential devices for analyzing and evaluating the fallibility of complex systems. They follow many different formats, sometimes by design, other times inadvertently. Major results were: people were quite insensitive to what had been left out of a fault tree, increasing the amount of detail for the tree as a whole or just for some of its branches produced small effects on perceptions, and the perceived importance of a particular branch was increased by presenting it in pieces (as two separate component branches). Aside from their relevance for the study of problem solving, such results may have important implications for how best to inform the public about technological risks and to involve it in policy decisions and how experts should perform fault-tree analyses of the risks from technological systems.
Excessive exosome release is the pathogenic pathway linking a lysosomal deficiency to generalized fibrosis

Abnormal release of exosomes carrying profibrotic signals by myofibroblasts leads to muscle fibrosis in a lysosomal disease. Lysosomal exocytosis is a ubiquitous process negatively regulated by neuraminidase 1 (NEU1), a sialidase mutated in the glycoprotein storage disease sialidosis. In Neu1−/− mice, excessive lysosomal exocytosis is at the basis of disease pathogenesis. Yet, the tissue-specific molecular consequences of this deregulated pathway are still unfolding. We now report that in muscle connective tissue, Neu1−/− fibroblasts have features of myofibroblasts and are proliferative, migratory, and exocytose large amounts of exosomes. These nanocarriers loaded with activated transforming growth factor–β and wingless-related integration site (WNT)/β-catenin signaling molecules propagate fibrotic signals to other cells, maintaining the tissue in a prolonged transitional status. Myofibroblast-derived exosomes fed to normal fibroblasts convert them into myofibroblasts, changing the recipient cells’ proliferative and migratory properties. These findings reveal an unexpected exosome-mediated signaling pathway downstream of NEU1 deficiency that propagates a fibrotic disease and could be implicated in idiopathic forms of fibrosis in humans.
Transesophageal Echocardiography During Cytoreductive Surgery with Hyperthermic Intraperitoneal Chemotherapy: A Novel Approach

Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is an extensive, lengthy procedure for patients with peritoneal metastases. It is associated with fairly high morbidity and mortality as compared with other non-vascular intra-abdominal surgeries. Fluid and hemodynamic management is challenging and not well established, particularly in patients with a low ejection fraction (EF). This case details the successful intraoperative anesthetic management of a patient with an ejection fraction of 20% undergoing CRS/HIPEC using the addition of intraoperative transesophageal echocardiography (TEE) as an adjunct to central venous pressure (CVP), urine output (UOP), and calculated stroke volume variation (SVV) for goal-directed resuscitation and blood pressure support.