Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-Learning with Hessian Free Approach in Deep Neural Nets Training

Meta-learning is a promising method to achieve efficient training method towards deep neural net and has been attracting increases interests in recent years. But most of the current methods are still not capable to train complex neuron net model with long-time training process. In this paper, a novel second-order meta-optimizer, named Meta-learning with Hessian-Free(MLHF) approach, is proposed based on the Hessian-Free approach. Two recurrent neural networks are established to generate the damping and the precondition matrix of this Hessian-Free framework. A series of techniques to meta-train the MLHF towards stable and reinforce the meta-training of this optimizer, including the gradient calculation of $H$. Numerical experiments on deep convolution neural nets, including CUDA-convnet and ResNet18(v2), with datasets of CIFAR10 and ILSVRC2012, indicate that the MLHF shows good and continuous training performance during the whole long-time training process, i.e., both the rapid-decreasing early stage and the steadily-deceasing later stage, and so is a promising meta-learning framework towards elevating the training efficiency in real-world deep neural nets.
Assessing a mobile-based deep learning model for plant disease surveillance

Convolutional neural network models (CNNs) have made major advances in computer vision tasks in the last five years. Given the challenge in collecting real world datasets, most studies report performance metrics based on available research datasets. In scenarios where CNNs are to be deployed on images or videos from mobile devices, models are presented with new challenges due to lighting, angle, and camera specifications, which are not accounted for in research datasets. It is essential for assessment to also be conducted on real world datasets if such models are to be reliably integrated with products and services in society. Plant disease datasets can be used to test CNNs in real time and gain insight into real world performance. We train a CNN object detection model to identify foliar symptoms of diseases (or lack thereof) in cassava (Manihot esculenta Crantz). We then deploy the model on a mobile app and test its performance on mobile images and video of 720 diseased leaflets in an agricultural field in Tanzania. Within each disease category we test two levels of severity of symptoms - mild and pronounced, to assess the model performance for early detection of symptoms. In both severities we see a decrease in the F-1 score for real world images and video. The F-1 score dropped by 32% for pronounced symptoms in real world images (the closest data to the training data) due to a drop in model recall. If the potential of smartphone CNNs are to be realized our data suggest it is crucial to consider tuning precision and recall performance in order to achieve the desired performance in real world settings. In addition, the varied performance related to different input data (image or video) is an important consideration for the design of CNNs in real world applications.
Evaluation of an Intensive Interdisciplinary Pain Treatment Based on Acceptance and Commitment Therapy for Adolescents With Chronic Pain and Their Parents: A Nonrandomized Clinical Trial

Objective Parental factors are central in the development and maintenance of chronic pain in youths. Only a handful of studies have investigated the impact of psychological treatments for pediatric chronic pain on parental factors, and the relationships between changes in parental and adolescent factors. In the current study, we evaluated the effects of an intensive interdisciplinary pain treatment (IIPT) program based on Acceptance and Commitment Therapy (ACT) for adolescents with chronic pain, on adolescent and parental variables, and the relationship between parental psychological flexibility and adolescent pain acceptance. Methods Adolescents (N = 164) with chronic pain were included, with a mean age of 15.5 years, and completed the 3-week treatment with an accompanying parent (N = 164). Linear mixed-effects models were used to analyze change over time (from pretreatment to 3-month follow-up) on parent (depression, health-related quality of life and parent psychological flexibility) and adolescent (physical, social and emotional functioning, and adolescent pain acceptance) variables. Additionally, linear mixed-effects models were used to analyze the relationship between parent psychological flexibility and adolescent pain acceptance. Results Results illustrated significant improvements over time in depressive symptoms and levels of psychological flexibility in parents. Excluding social development, adolescents improved significantly in all assessed aspects of functioning and pain acceptance. Additionally, changes in parent psychological flexibility were significantly associated with changes in adolescent pain acceptance. Conclusions Results indicated that treatment had positive effects for parents and adolescents, and a significant positive relationship between changes in parent psychological flexibility and adolescent pain acceptance was found.
Use of Moulage to Evaluate Student Assessment of Skin in an Objective Structured Clinical Examination

Purpose This study investigated the physician assistant (PA) student evaluation of skin and the use of moulage in an objective structured clinical examination (OSCE). Methods Clinical-year PA students participated in an OSCE, taking a history, completing a physical examination, and writing a focused clinical note. The standardized patient's history simulated a primary diagnosis of right-sided carpal tunnel syndrome and an incidental skin lesion consistent with melanoma, only if the student made an inquiry in this replication study. Faculty members' assessments of students' physical examinations were standardized using an agreed-upon rubric. Students completed an anonymous survey on the OSCE experience immediately following the activity. Results All students identified the primary diagnosis of carpal tunnel. Sixty-three percent of students verbalized examination of the skin; however, only 38% identified an atypical skin lesion in their clinical note documentation. Of those, only 33% of students referred the patient for biopsy. Most students believed that the use of moulage increased the realism of the standardized patient encounter. Sixty percent of students reported that they noticed a skin lesion but did not believe that it was part of the simulated experience. Conclusions Moulage increased the realism of the OSCE. This study found that the ability of a student to verbalize the evaluation of a particular body system did not necessarily mean that they adequately or correctly assessed that system upon physical examination. Implementation of an OSCE and use of moulage provided an opportunity to explicitly assess student performance related to evaluation and assessment of skin. It provided a mechanism for meaningful, formative feedback of students' performance.
Similar Inhibition of Dynamic Adhesion of Lymphocytes From IBD Patients to MAdCAM-1 by Vedolizumab and Etrolizumab-s.

Background Although anti-adhesion therapies are a novel mainstay in the treatment of inflammatory bowel diseases (IBDs), the mechanisms controlling integrin-dependent gut homing are poorly elucidated, and the available techniques for translational functional investigations are limited. Methods We used dynamic adhesion assays to study adhesion of CD4+ T cells, CD8+ T cells, CD19+ B cells, and granulocytes to the addressins MAdCAM-1, VCAM-1, and ICAM-1. The effects of vedolizumab, natalizumab, etrolizumab-s, anti-CD11a, and anti-CD18 antibodies were explored. Results Adhesion of peripheral blood leukocytes from IBD patients and control donors could be validly assessed, and integrin-mediated addressin adhesion could be specifically inhibited by anti-integrin antibodies. Numbers of adhering cells were partly, but not completely, related to integrin expression. Vedolizumab and etrolizumab-s resulted in similar reduction of adhesion to MAdCAM-1, and preliminary data proposed an association of dynamic adhesion to MAdCAM-1 with response to vedolizumab therapy. Conclusions Dynamic adhesion assays are an easy and broadly applicable method for IBD research that is useful for future translational studies and potentially also for supporting clinical treatment decisions. 10.1093/ibd/izy077_video1izy077_Video_15786486962001.
The YorkNRM Systems for Trilingual EDL Tasks at TAC KBP 2016

This paper describes the YorkNRM systems submitted to the Trilingual Entity Detection and Linking (EDL) track in 2016 TAC Knowledge Base Population (KBP) contests. Here, we have studied a novel approach for for trilingual entity discovery and mention detection (MD). Instead of treating NER as a sequence labelling problem, we propose to use a new lo-cal detection approach, which rely on the recent ﬁxed-size ordinally forgetting encoding (FOFE) method to fully encode each sentence fragment and its left/right contexts into a ﬁxed-size representation. Afterwards, a simple feedforward neural network is used to reject or predict entity label for each individual fragment. Moreover, we have used the entity linking system from another participating team USTC NELSLIP for entity linking and NIL clustering. Based on these techniques, we have submitted the results to both EDL1 and EDL2 evaluations.
Antibodies Against Chlamydia trachomatis and Ovarian Cancer Risk in Two Independent Populations

BACKGROUND Pelvic inflammatory disease (PID) has been associated with ovarian cancer risk. To clarify the role of Chlamydia trachomatis and other infectious agents in the development of ovarian cancer, we evaluated the association of serologic markers with incident ovarian cancer using a staged approach in two independent populations. METHODS Studies included: 1) a case-control study in Poland (244 ovarian cancers/556 control subjects) and 2) a prospective nested case-control study in the PLCO Cancer Screening Trial (160 ovarian cancers/159 control subjects). Associations of serologic marker levels with ovarian cancer risk at diagnostic as well as higher thresholds, identified in Poland and independently evaluated in PLCO, were estimated using multivariable adjusted logistic regression. RESULTS In the Polish study, antibodies (based on laboratory cut-point) against the chlamydia plasmid-encoded Pgp3 protein (serological gold standard) were associated with increased ovarian cancer risk (adjusted odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.20 to 2.22); when a positive result was redefined at higher levels, ovarian cancer risk was increased (cut-point 2: OR = 2.00, 95% CI = 1.38 to 2.89; cut-point 3 [max OR]: OR = 2.19, 95% CI = 1.29 to 3.73). In the prospective PLCO study, Pgp3 antibodies were associated with elevated risk at the laboratory cut-point (OR = 1.43, 95% CI = 0.78 to 2.63) and more stringent cut-points (cut-point 2: OR = 2.25, 95% CI = 1.07 to 4.71); cut-point 3: OR = 2.53, 95% CI = 0.63 to 10.08). In both studies, antibodies against other infectious agents measured were not associated with risk. CONCLUSIONS In two independent populations, antibodies against prior/current C. trachomatis (Pgp3) were associated with a doubling in ovarian cancer risk, whereas markers of other infectious agents were unrelated. These findings lend support for an association between PID and ovarian cancer.
A Method to Directly Compute Synchronverter Parameters for Desired Dynamic Response

This paper proposes a method to directly compute controller parameter values in a synchronverter augmented with a so-called damping correction loop, and in so doing, achieve desired transient and steady-state response. The proposed approach is grounded in a reduced third-order system model that captures pertinent dynamic characteristics of the synchronverter active-power loop (APL), particularly those of the dominant mode. This reduced-order model helps to identify and explain a shortcoming in a previous parameter tuning method. Central to the proposed parameter computation method is to express APL parameters of the original system as closed-form functions of the poles of the reduced-order system. Since the reduced-order model retains dominant-mode dynamic behaviors of the original system, APL parameters can be directly computed according to specified APL dominant mode. Time-domain simulations are provided to validate the accuracy of the reduced-order model and the proposed direct-computation parameter tuning method.
Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking

Extraction from raw text to a knowledge base of entities and fine-grained types is often cast as prediction into a flat set of entity and type labels, neglecting the rich hierarchies over types and entities contained in curated ontologies. Previous attempts to incorporate hierarchical structure have yielded little benefit and are restricted to shallow ontologies. This paper presents new methods using real and complex bilinear mappings for integrating hierarchical information, yielding substantial improvement over flat predictions in entity linking and fine-grained entity typing, and achieving new state-of-the-art results for end-to-end models on the benchmark FIGER dataset. We also present two new human-annotated datasets containing wide and deep hierarchies which we will release to the community to encourage further research in this direction: MedMentions, a collection of PubMed abstracts in which 246k mentions have been mapped to the massive UMLS ontology; and TypeNet, which aligns Freebase types with the WordNet hierarchy to obtain nearly 2k entity types. In experiments on all three datasets we show substantial gains from hierarchy-aware training.
Cross-Cultural Differences in the Experience of Grandparent–Grandchild Relationships and Related Psychosocial Outcomes

This study examined grandchildren’s perceptions of the quality of their relationship with their grandmothers and how these perceptions relate to psychosocial outcomes. Eighty-two youth from Mexico and 99 youth from the United States aged between 13 and 16 participated. Results suggested that both cultures benefit in unique ways from positive relationship with their grandmothers. Yet, there were also differences in the relational experience of grandmother–grandchild relationships across cultures. Specifically, grandchildren in the U.S. sample reported higher relationship quality, relational competency, and self-efficacy than the grandchildren in the Mexico sample. Within the U.S. sample, relationship quality was associated with grandchildren’s relational competence, while in the Mexico sample, relationship quality was associated with self-efficacy. Limitations of the present study include restricted generalizability to other age groups and to grandfathers and that only one element of the grandparent–grandchild dyad was sampled. Longitudinal research will improve our understanding of the causal dynamics of grandparent–grandchild relationships.
Cue-reactivity in behavioral addictions: A meta-analysis and methodological considerations

Background and aims Recent research has applied cue-reactivity paradigms to behavioral addictions. The aim of the current meta-analysis is to systematically analyze the effects of learning-based cue-reactivity in behavioral addictions. Methods The current meta-analysis includes 18 studies (29 data sets, 510 participants) that have used a cue-reactivity paradigm in persons with gambling (eight studies), gaming (nine studies), or buying (one study) disorders. We compared subjective, peripheral physiological, electroencephal, and neural responses toward addiction-relevant cues in patients versus control participants and toward addiction-relevant cues versus control cues in patients. Results Persons with behavioral addictions showed higher cue-reactivity toward addiction-relevant cues compared with control participants: subjective cue-reactivity (d = 0.84, p = .01) and peripheral physiological and electroencephal measures of cue-reactivity (d = 0.61, p < .01). Increased neural activation was found in the caudate nucleus, inferior frontal gyrus, median cingulate cortex, subgenual cingulate, and precentral gyrus. Persons with gambling, gaming, or buying disorders also showed higher cue-reactivity toward addiction-relevant cues compared with control cues: subjective cue-reactivity (d = 0.39, p = .11) and peripheral physiological and electroencephal measures of cue-reactivity (d = 0.47, p = .05). Increased neural activation was found in the caudate nucleus, inferior frontal gyrus, angular gyrus, inferior network, and precuneus. Discussion and conclusions Cue-reactivity not only exists in substance-use disorders but also in gambling, gaming, and buying disorders. Future research should differentiate between cue-reactivity in addictive behaviors and cue-reactivity in functional excessive behaviors such as passions, hobbies, or professions.
Local Support Vector Machines: Formulation and Analysis

We provide a formulation for Local Support Vector Machines (LSVMs) that generalizes previous formulations, and brings out the explicit connections to local polynomial learning used in nonparametric estimation literature. We investigate the simplest type of LSVMs called Local Linear Support Vector Machines (LLSVMs). For the first time we establish conditions under which LLSVMs make Bayes consistent predictions at each test point $x_0$. We also establish rates at which the local risk of LLSVMs converges to the minimum value of expected local risk at each point $x_0$. Using stability arguments we establish generalization error bounds for LLSVMs.
Prevalence and Risk Factors for Hepatitis B Virus Infection in Roma and Non-Roma People in Slovakia

Prevalence of Hepatitis B is relatively low in developed European countries. However specific subpopulations may exist within each country with markedly different Hepatitis B burden. Roma minority is very numerous in Slovakia and their lifestyle is completely different to non-Roma population. The aim of this study is to map Hepatitis B prevalence in Roma and compare it to non-Roma population and to explore potential socio-economic and health related risk factors. Cross-sectional epidemiology study was performed in Slovakia that included randomly sampled Roma population and geographically corresponding random sampled non-Roma population. Comprehensive questionnaire about risk factors was administered and blood samples were drawn for Hepatitis B serology and virology tests. Altogether 855 participants were included. Global Hepatitis B surface Antigen (HBsAg) positivity rate was 7.7% (i.e., active Hepatitis B) and anti Hepatitis B core IgG antibody (antiHBcIgG) positivity rate was 34.6%. Roma population had significantly higher prevalence of Hepatitis B, both active chronic infection (12.4%; 95% Confidence Interval (CI) 9.58%–15.97% versus 2.8%; 95% CI 1.56%–4.91%; p < 0.0001) and antiHBcIgG positivity (52.8%; 95% CI 48.17%–57.44% versus 25.9%; 95% CI 12.56%–20.02%; p < 0.0001) Main risk factors for HBsAg positivity were Roma ethnicity, male sex and tattoo. Conclusion: There is a very high prevalence of Hepatitis B in Roma communities in Slovakia, with potential for grave medical consequences.
A Siting and Sizing Optimization Approach for PV–Battery–Diesel Hybrid Systems

This paper proposes a new method to determine the sizing and siting of diesel generators (DGs), photovoltaic (PV) solar panels, and batteries for off-grid systems. In this work, the objective is to reduce the total system cost while fulfilling the load demand and maintaining the power quality of the system, among other constraints. This is achieved by employing a two-stage particle swarm optimization algorithm; the first for siting and sizing of the system and the second for its scheduling. Three case studies, namely only DGs, DGs + PV, and DGs + PV + batteries systems, based on the energy requirement of an Indonesian island are presented. In addition, real solar irradiance and temperature data are utilized together with a measured load profile. The results reveal that a system that relies only on DGs is not able to keep the system voltage within the tolerable range (from 0.95 to 1.05 p.u.), while yielding a lifetime cost of 104 million USD. The DGs + PV system requires a lower lifetime cost, 67 million USD. Nevertheless, the voltage of the system reaches values lower than 0.95 p.u. for certain nodes during night-time as the PV are not able to provide power. Finally, the DGs + PV + batteries system yields the lowest cost, 64 million USD, and is able to keep the values of the voltage within the desired range, as batteries can provide power when PV are not operating.
Personal sleep debt and daytime sleepiness mediate the relationship between sleep and mental health outcomes in young adults

Sleep duration and chronotype (i.e., morningness–eveningness) are associated with increased depression and anxiety risk, but differences in individual sleep need and lifestyle may mean these sleep parameters do not present the same risk across all individuals. This study explored the mediating role of sleep debt and daytime sleepiness in the relationship between sleep and mental health symptoms in young adults, a particularly vulnerable population.
The Low-Threshold Calcium Channel Cav3.2 Mediates Burst Firing of Mature Dentate Granule Cells

Abstract Mature granule cells are poorly excitable neurons that were recently shown to fire action potentials, preferentially in bursts. It is believed that the particularly pronounced short-term facilitation of mossy fiber synapses makes granule cell bursting a very effective means of properly transferring information to CA3. However, the mechanism underlying the unique bursting behavior of mature granule cells is currently unknown. Here, we show that Cav3.2 T-type channels at the axon initial segment are responsible for burst firing of mature granule cells in rats and mice. Accordingly, Cav3.2 knockout mice fire tonic spikes and exhibit impaired bursting, synaptic plasticity and dentate-to-CA3 communication. The data show that Cav3.2 channels are strong modulators of bursting and can be considered a critical molecular switch that enables effective information transfer from mature granule cells to the CA3 pyramids.
The Sound of Words Evokes Affective Brain Responses

The long history of poetry and the arts, as well as recent empirical results suggest that the way a word sounds (e.g., soft vs. harsh) can convey affective information related to emotional responses (e.g., pleasantness vs. harshness). However, the neural correlates of the affective potential of the sound of words remain unknown. In an fMRI study involving passive listening, we focused on the affective dimension of arousal and presented words organized in two discrete groups of sublexical (i.e., sound) arousal (high vs. low), while controlling for lexical (i.e., semantic) arousal. Words sounding high arousing, compared to their low arousing counterparts, resulted in an enhanced BOLD signal in bilateral posterior insula, the right auditory and premotor cortex, and the right supramarginal gyrus. This finding provides first evidence on the neural correlates of affectivity in the sound of words. Given the similarity of this neural network to that of nonverbal emotional expressions and affective prosody, our results support a unifying view that suggests a core neural network underlying any type of affective sound processing.