Miracle-dz/UniFAR-FTUs huggingface dataset:
What do cultural neuroscience findings mean?

Cultural neuroscience has documented factors that affect biological and psychological processes that reciprocally shape beliefs and norms shared by groups of individuals. Here we highlight open questions regarding the stability versus malleability of these findings across time, environments, and cultural settings. By borrowing points from population neuroscience (Falk et al., in Proc Natl Acad Sci 110:17615–17622, 2013) and neurogenetics (Bogdan et al., in Mol Psychiatry 18:288–299, 2012), we highlight considerations for research on the development of differences in brain structure and function, particularly in the context of cultural variation. These points highlight the need to better understand gene by culture interactions; in particular, the potential role of ancestry, and the role the brain likely plays as a mechanism through which gene by culture interactions affect behavior. Moreover, we highlight the need to consider development in the interaction of culture and biology. We also highlight methodological challenges as neuroscience is brought to the population level including the importance of sampling and experimental equivalence across groups and cultures. In total, this discussion is aimed at fostering new advances in the young field of cultural neuroscience and highlighting ways in which cultural neuroscience can inform a broader understanding of the development of differences in complex behaviors. L. W. Hyde (&) Department of Psychology, Center for Human Growth and Development, Institute for Social Research, University of Michigan, Ann Arbor, USA e-mail: lukehyde@umich.edu S. Tompson Department of Psychology, University of Michigan, Ann Arbor, USA J. D. Creswell Department of Psychology, Carnegie Mellon University, Pittsburgh, USA E. B. Falk Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA 123 Cult. Brain DOI 10.1007/s40167-014-0024-6
Allan deviation tells the binding properties in single-molecule sensing with whispering-gallery-mode optical microcavities

We propose a scheme of exploring the kinetic properties of the receptor-ligand binding process by means of the frequency stability measurement of a whispering-gallery-mode optical microcavity. In this scheme, the probe beam is directly locked to the microcavity and the time resolution of the sensing detection is determined by the feedback loop response time 10 μs, which is much shorter than the current limit of about 20 ms. The receptor-ligand interactions are entirely mapped onto the probe light frequency and can be recovered through the analysis of its Allan deviation. As a result, one can investigate a chemical and biological reaction at the single-molecule level without the need for resolving the occurrence and duration of individual binding events. We numerically study this sensing scheme based on a practical optoplasmonic platform, where several gold nanorods are adsorbed onto the surface of a spherical microcavity that is located in the aqueous environment. The microsphere has a typical radius of 40 μm and quality factor of 106 (finesse of 2.6 × 103) at the wavelength of 785 nm. This powerful scheme may extend single-molecule sensing to the kinetic regime of the biochemical reactions.
An Investigation of the Effect of Perceived Risk on Repurchase Intention in Online Vacation Purchases An Investigation of the Effect of Perceived Risk on Repurchase Intention in Online Vacation Purchases

Consumers may abandon their subsequent online purchase intentions due to the risks they perceive in their first online purchases. For this reason, this study aims to determine types of risk which consumers perceive during online purchase and their effect in online repurchase intention. Academic staff in the colleges and faculties of tourism in Turkey was selected as the population, and a survey form was sent to them via e-mail. Finally, the number of available survey form completed by the participants was 129. Data was analysed using correlation and simple linear regression analysis using IBM SPSS 20.0 software program. Research findings indicate that participants were influenced by financial risks, privacy and source risks, performance risks as well as social, physical and psychological risks. Furthermore, consumers feel that being comfortable when booking a vacation online is an antecedent of repurchase intention. Finally, significant and negative relationship was found between perceived risk and repurchase intention during online vacation purchase.
Inner Nuclear Membrane Asi Ubiquitin Ligase Catalytic Subunits Asi1p and Asi3p, but not Asi2p, confer resistance to aminoglycoside hygromycin B in Saccharomyces cerevisiae

The heterotrimeric Asi ubiquitin ligase (encoded by ASI1, ASI2, and ASI3) mediates protein degradation in the inner nuclear membrane in Saccharomyces cerevisiae. Asi1p and Asi3p possess catalytic domains, while Asi2p functions as an adaptor for a subset of Asi substrates. We hypothesized the Asi complex is an important mediator of protein quality control, and we predicted that Asi would be required for optimal growth in conditions associated with elevated abundance of aberrant proteins. Loss of Asi1p or Asi3p, but not Asi2p, sensitized yeast to hygromycin B, which promotes translational infidelity by distorting the ribosome A site. Surprisingly, loss of quality control ubiquitin ligase Hul5p did not sensitize yeast to hygromycin B. Our results are consistent with a prominent role for an Asi subcomplex that includes Asi1p and Asi3p (but not Asi2p) in protein quality control.
SCIENTISM AND THE INDEPENDENCE OF EPISTEMOLOGY

Naturalists seek continuity between epistemology and science. Critics argue this illegitimately expands science into epistemology and commits the 'fallacy' of scientism. Must naturalists commit this 'fallacy'? I defend a conception of naturalized epistemology which upholds the non-identity of epistemic ends, norms, and concepts with scientific evidential ends, norms, and concepts. I argue it enables naturalists to avoid three leading scientistic 'fallacies': dogmatism, one dimensionalism, and granting science an epistemic monopoly. Naturalists seek continuity between epistemology and science so that epis? temology may be conducted within science, as part of science.1 They propose creating such continuity by extending the epistemology of the sciences (e.g., their a posteriori methods, styles of explanation, and sub? stantive findings) into the epistemology of epistemology.2 Critics, however, oppose naturalism on the grounds that it illegitimately expands science into epistemology and commits the 'fallacy' of scientism. Naturalism forsakes traditional features of our epistemic practices such as their normative-evaluative component and role as independent critic of science. It creates a sterile, one dimensional epistemology which grants science monopoly over what counts as evidence, knowledge and correct method. In order to avoid these shortcomings, critics maintain episte? mology must remain an autonomous, extra-scientific affair employing sui generis, a priori methods and evidence. I argue that naturalism need not commit the 'fallacy' of scientism. Sec? tion 1 explains how naturalists' calls for continuity between science and epistemology are ambiguous. Some yield what I call strong continuity, others, weak continuity. After sketching some general features of weak continuity naturalism, Section 2 proposes an anthropological approach to meta-epistemological matters. Adopting this approach, Section 3 hypoth? esizes a conception of epistemology which conceives the epistemic point of view in terms of acquiring truth and avoiding error. Section 4 then conceives epistemic notions in terms of these ends. It adopts a reliabilist theory of justification which fits the meta-epistemological specifications of weak continuity. I call the combined view weak continuity reliabilism. Lastly, after exploring scientism, Section 5 argues that weak continuity Erkenntnis 43: 1-27,1995. 1995 Kluwer Academic Publishers. Printed in the Netherlands. This content downloaded from 130.56. 64.29 on Mon, 25 May 2020 12:18:14 UTC All use subject to https://about.jstor. org/terms
Did a Successful Fight Against the Covid-19 Pandemic Come at a Cost? Impacts of the Outbreak on Employment Outcomes in Vietnam

Vietnam is widely praised for its successful fight against the COVID-19 pandemic. The country has had an extremely low mortality rate of 35 deaths to date (out of a population of approximately 100 million) and currently has no community transmission. We offer the first study that examines the effects of the COVID-19-induced lockdown on various employment outcomes for Vietnam. We employ difference-in-differences econometric models to estimate the causal effects of the lockdown, using rich individual-level data from the quarterly Labor Force Surveys. We find that the lockdown increases the unemployment rate, the temporary layoff rate, and decreases the quality of employment. It also reduces workers' numbers of working hours and their monthly incomes and wages. Our estimation results remain robust to different model specifications and estimation samples. Further heterogeneity analysis suggests that the effects vary across education levels and occupation sectors but are similar across regions or provinces with different lockdown durations.
Trend Drift Discovery for Individual Highway Drivers through Ensemble Learning

Inter-city transportation plays an important role in modern smart cities, and has accumulated massive spatio-temporal data from various sensors in IoT (Internet of things). Current travel characteristics and future trends of highway traffic are valuable for traffic guidance and personalized service. As a routine domain analysis, trend drift discovery for highway drivers faces challenges in processing efficiency and predictive accuracy. Sensitive privacy of business data has to be considered, executive latency on huge data is hard to guarantee, and correlation among spatio-temporal characteristics cannot be fully employed. In this paper, a travel-characteristic based method is proposed to discover the potential drift of payment identity for individual highway drivers. Considering time, space, subjective preference and objective property, monthly travel characteristics are modeled on toll data from highway toll stations, and predictive error for those trends can be reduced dramatically through gradient boosting classification technology. With real-world data of one Chinese provincial highway, extensive experiments show that our method has second-level in executive latency with more than 85% F1-score for predictive accuracy.
Detecting Redundancy in Electronic Medical Records Using Clinical BERT

Semantic Textual Similarity (STS) computes the degree of semantic equivalence between text snippets. STS is used in various natural language processing tasks, including detecting redundant information in texts. Although STS tasks have been widely studied in the general English domain, there exists very few resources for STS tasks in the clinical domain. The methods used for general domain STS tasks might not work well in the clinical domain because of variability of natural language expressions, and clinical domain expressions are diﬀerent from general domain expressions. We present a Clinical BERT-based model for redundancy detection in clinical texts. Our experiments show that domain-speci(cid:12)c BERT improves performance of the model.
The Incremental Shuttle Walk Testing (ISWT) in Patients with Pulmonary Hypertension (PH): Assessment of Safety According to W.H.O. Functional Class and Etiology

Purpose: The 6 minute walk test used to evaluate patients with PH has many limitations. The ISWT, an automated progressively incremental and more physically demanding exercise test, has been useful to assess exercise tolerance in patients with severe COPD. Its application in patients with PH and particularly, pulmonary arterial hypertension (PAH) raises the concern of eliciting cardiovascular complications during testing. We wished to evaluate the safety of ISWT in patients with PH. Methods: A retrospective review was performed on patients with RHC-confirmed PH who had undergone outpatient ISWT, predominantly those with W.H. O. FC II and III. Eighty-four ISWTs from 46 patients were assessed according to W.H. O. functional class (FC), echocardiogram, minute distances walked, pulse oximetry, BORG dyspnea scores and fatigue, blood pressure, heart rate and adverse events. Results: A total of 21 adverse events were reported from the 84 ISWT performed as follows: Two patients angina, 1 worsening dyspnea, 12 locomotor difficulties including leg and joint pain, and 6 lightheadedness. There were no deaths or sustained adverse events after the ISWT. There were no documented episodes of syncope or tachyarrhythmia’s even in patients with right ventricular dysfunction. Conclusions: Performance of ISWT appears to be safe in stable outpatients with PH and right-sided heart disease as an assessment of the functional capacity in the PH population and should be included in future clinical trials to assess whether it may provide a meaningful assessment of patient exercise tolerance. Its limitations are similar to those shared by the 6 minute walk and include locomotor difficulties.
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning

Modern statistical applications often involve minimizing an objective function that may be nonsmooth and/or nonconvex. This paper focuses on a broad Bregman-surrogate algorithm framework including the local linear approximation, mirror descent, iterative thresholding, DC programming and many others as particular instances. The recharacterization via generalized Bregman functions enables us to construct suitable error measures and establish global convergence rates for nonconvex and nonsmooth objectives in possibly high dimensions. For sparse learning problems with a composite objective, under some regularity conditions, the obtained estimators as the surrogate's fixed points, though not necessarily local minimizers, enjoy provable statistical guarantees, and the sequence of iterates can be shown to approach the statistical truth within the desired accuracy geometrically fast. The paper also studies how to design adaptive momentum based accelerations without assuming convexity or smoothness by carefully controlling stepsize and relaxation parameters.
The effect of aquatic training on static and semi-dynamic balance of patients with chronic ischemic stroke: A randomized clinical trial

Objectives This study aims to investigate the effect of six-week aquatic exercise on the static and semi-dynamic balance of male patients with chronic ischemic stroke (CIS). Patients and methods This randomized clinical trial (RCT) included a total of 36 male CIS patients (mean age 60.2±6.7 years; range, 40 to 70 years) between January 2015 and January 2017. The patients were randomly divided into three groups consisting of 12 patients in each group: (i) exercising in shallow water, (ii) exercising in deep water, and (iii) control group. Training sessions were held three days a week for six weeks, and the control group did not participate in these sessions. The balance of the patients was checked using the Biodex balance system in two stages. Results There was no significant difference between the two intervention groups (shallow and deep) in terms of the balance assessment post-test (p>0.05), yet there was a statistically significant difference between the two intervention groups (shallow and deep) with the control group in terms of the semi-dynamic balance (total) score, (p<0.05); the semi-dynamic balance (total) of the two intervention groups (shallow and deep) was higher than that of the control group (p<0.05). Conclusion Our study results indicate that exercise in both depths is a suitable solution to improve balance, particularly semi-dynamic balance (total) in male CIS patients. Accordingly, aquatic training has a positive effect on balance in male stroke patients and we can prescribe this protocol as a useful remedy for these patients.
Improving Concept Representations for Short Text Classiﬁcation

Short text classiﬁcation is a challenging task in Natural Language Processing (NLP). Compared with documents, short texts are more sparse and ambiguous due to lack of context. In order to overcome this diﬃ-culty, recent work tends to take an approach of combining neural language models with external linguistic resources such as knowledge bases. In this kind of approaches, concepts obtained from a knowledge base are usually mapped to an implicit space and represented as a vector. However, how to eﬀectively represent concepts in a neural language model is not well studied yet. Hence, in this study, we construct several formulae for concept embedding and compare them in a short text classiﬁcation task. Our experimental results show that utilizing proper concept embeddings can slightly improve the performance of short text classiﬁcation.
Authentication encryption scheme using leopard and chaotic tent map algorithm for smart grid

Smart Grid (SG) has gain popularity due to reliability, efficiency, and sustainability. They transmit periodically collected reading. The reading contains very sensitive data such as personal information and geometric locations. Therefore, transmission and storage of data have many security challenges such as eavesdropping and tampering attacks. This proposes a novel authentication encryption scheme that provides confidentiality, integrity, and authentication of the data. To achieve these objectives, we have hybrid the LEOPARD and chaotic tent map algorithm. The LEOPARD algorithm provides confidentiality and the chaotic tent map algorithm gives the authentication tag to verify the data integrity and authentication. The algorithm is simulated in MATLAB. The experimental results show that the proposed algorithm provides better results as compared to the existing algorithms in terms of PSNR, execution time, and security.
Improving Distantly Supervised Relation Extraction via Textual Representation of Multi-hop Inference over Text

Distantly Supervised Relation Extraction (DS-RE) is a widely applied approach to collect relational facts from unstructured text, but often accompanies with the problem of fuzzy data. To alleviate this issue, existing approach uses multi-hop reasoning over text to facilitate the relation classiﬁcation. However, the method only represents the textual relation (e.g., the middle context between an entity pair) as a unit, rather than a textual sequence of words and so cannot utilize the semantic information (e.g., pretrained word embedding) of the textual relation for DS-RE. Therefore, in this work, we propose a new DS-RE model that represents the textual relation as a sequence of words and encodes the sequence with a world-level attention mechanism. Experimental results prove the effectiveness or the proposed model for DS-RE, because the proposed model achieves signiﬁcant and consistent improvement as compared with baselines, and obtains a competitive results with the state-of-the-art models on the NYT10 dataset.
LEADERS' PERSPECTIVE ON LEADER MEMBER EXCHANGE: A CONCEPTUAL REVIEW

Studies on the Leaders Member Exchange (LMX) have focused more on subordinates' perspective, even though a leader's perspective is equally important in creating a positive LMX. Leaders' personalities, leaders' wisdom, and leaders' emotion management are things every leader must know and have to build a positive LMX and achieve their leadership goals.
Effects of Functional Separation and Low Levels of Blood Alcohol on the Response to Automobile Rear-Signal Information

The experiment investigated the effects of functional separation of brake and turn-signals, and of low levels of alcohol intoxication on a driver's ability to detect and interpret rear-signal information presented on a model automobile in a laboratory setting. Twelve experienced drivers performed the laboratory task for one-hour sessions on five successive days. Three independent variables were examined in a randomized-block, factorial design. These consisted of two levels of model type, one with brake and turn-signals combined under the same lens, the other with brake and turn-signals under separate lenses, four levels of blood alcohol, . 00, . 02, . 05, and . 08%, and six levels of stimulus complexity, representing six types of rear-signal information. Response variables consisted of response errors and the latencies between the onset of the stimulus and both the onset of the response and the completion of the response. Results indicated that the response variables were not equally sensitive to the task and that performance was significantly affected by model type and stimulus complexity. Performance deteriorated with blood alcohol levels as low as . 05% on the combined model and 0.8% on the model that separated brake and turn-signal lights. Results are discussed in terms of the stimulus-identification/response-choice components of the task, and in terms of optimal coding methods for rear signals.
Immunological dysfunction persists for 8 months following initial mild-moderate SARS-CoV-2 infection

A proportion of patients surviving acute COVID-19 infection develop post-COVID syndrome (long COVID) encompassing physical and neuropsychiatric symptoms lasting longer than 12 weeks. Here we studied a prospective cohort of individuals with long COVID (the ADAPT study) compared to age/gender matched subjects without long COVID, healthy donors and individuals infected with other non-SARS CoV2 human coronaviruses (the ADAPT-C study). We found an elevated diffuse serum inflammatory cytokine profile in symptomatic long COVID subjects that was maintained at 8 months post-infection and was not observed in asymptomatic COVID-19 survivors. This inflammatory profile consisted of 15 cytokines that positively correlated; revealing an apparent diffuse, potentially coordinated, low level up regulation of a spectrum of immune and inflammatory mediators. In addition, we found an absence of subsets of un-activated naive T and B cells in peripheral blood of long COVID subjects, that did not reconstitute over time. In contrast, individual serum cytokines from the interferon I and III classes, T cell activation markers and plasma ACE2, while elevated in the serum of people previously infected with SARS-CoV-2 were not further elevated in subjects with long COVID symptoms. This work defines immunological parameters associated with long COVID and suggests future opportunities to prevention and treatment.