Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks

Deep neural networks suffer from over-fitting and catastrophic forgetting when trained with small data. One natural remedy for this problem is data augmentation, which has been recently shown to be effective. However, previous works either assume that intra-class variances can always be generalized to new classes, or employ naive generation methods to hallucinate finite examples without modeling their latent distributions. In this work, we propose Covariance-Preserving Adversarial Augmentation Networks to overcome existing limits of low-shot learning. Specifically, a novel Generative Adversarial Network is designed to model the latent distribution of each novel class given its related base counterparts. Since direct estimation of novel classes can be inductively biased, we explicitly preserve covariance information as the `variability' of base examples during the generation process. Empirical results show that our model can generate realistic yet diverse examples, leading to substantial improvements on the ImageNet benchmark over the state of the art.
Acoustic characteristics of healthy voices of adults: from young to middle age.

PURPOSE Characterize voices of adult individuals without vocal complaints and verify the effect of gender and age with the use of acoustic measures. METHODS One-hundred and seventy-six voice recordings belonging to adults between 19 and 59 years old, divided into four age groups, for decade, recorded in a database were analyzed. All voices analyzed were classified with no deviation in vocal quality. Acoustic analysis of the parameters was performed: Fundamental Frequency (sustained vowel and connected speech), Jitter, Shimmer and Noise-to-Harmonic Ratio through Multi Dimension Voice Program (KayPentax) software. The effect of gender, age and possible interactions were verified through the Factorial Anova test. When necessary, post hoc was performed with the Least Significant Difference test. RESULTS There were changes in the voice as a function of age, with a decrease in the Fundamental Frequency in the vowel and connected speech modalities in women and in the Fundamental Frequency of the speech in men. In men, an increase in shimmer measure was observed with the advancing age. Differences between genders were found in the measures of Fundamental Frequency, Jitter and Noise to Harmonic Ratio. CONCLUSION Vocal changes due to advancing age can be identified acoustically at the end of adulthood, and in women, these changes can be marked previously to the menopausal period.
Density Based Multisensor Data Fusion for Multiapplication Wireless Sensor Networks

The trend in the design of wireless sensor networks (WSNs) has recently shifted from an application-specific approach to a virtualization and resource-sharing view. Current WSNs allow the sensing and communication infrastructure to be shared among multiple applications thus optimizing the use of resources. However, as the number of applications sharing the WSN infrastructure grows, storing and analyzing requirements of all applications at the network level becomes unfeasible. To tackle this challenge, in this paper we proposed a multisensor data fusion method that requires no knowledge of the application specific requirements. For performing the analysis of the data, in our proposal we leverage concepts of the area of pattern recognition to create abstract sensors based on intervals in the monitored data. Considering that sensed data have a measuring range, given by their maximum and minimum values, our proposed methods group the data samples in abstract sensors based on density and peaks on the dataset. Both real and simulated experiments have shown that our proposal is accurate and reduce energy consumption.
The Impact of Gender Variance on Adolescents’ Wellbeing: Does the School Context Matter?

ABSTRACT Schools are often heteronormative environments, negatively influencing the wellbeing of LGB students. Less is known about the impact on gender-variant adolescents. Hence, this study investigates the wellbeing of gender-variant students—as evidenced by their gender (a)typicality and pressure for gender conformity— in different school cultures—as evidenced by the level of traditional gender role attitudes and homonegativity. We examine these context-dependent associations in a sample of 4987 Flemish students, who were questioned three times in 2012–2014. Multilevel regression analyses show that both gender-typical and atypical adolescents feel worse in heteronormative than inclusive schools. Furthermore, the social acceptance of boys seems to be more conditional on gender-conformity in heteronormative than inclusive schools. Overall, inclusive schools ensure higher wellbeing for all students (regardless of sex or gender variance), and student–teacher relationships seem central in explaining these school differences. Implications for school policy as well as research considering heteronormativity and gender-variance are discussed.
A Coarse-to-fine Pyramidal Model for Person Re-identification via Multi-Loss Dynamic Training

Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other. However, due to the inevitable challenging scenarios, current detection models often output inaccurate bounding boxes yet, which inevitably worsen the performance of these Re-ID algorithms. In this paper, to relax the requirement, we propose a novel coarse-to-fine pyramid model that not only incorporates local and global information, but also integrates the gradual cues between them. The pyramid model is able to match the cues at different scales and then search for the correct image of the same identity even when the image pair are not aligned. In addition, in order to learn discriminative identity representation, we explore a dynamic training scheme to seamlessly unify two losses and extract appropriate shared information between them. Experimental results clearly demonstrate that the proposed method achieves the state-of-the-art results on three datasets and it is worth noting that our approach exceeds the current best method by 9.5% on the most challenging dataset CUHK03.
Evaluation and correlation of oxidative stress and haemato-biochemical observations in horses with natural patent and latent trypanosomosis in Punjab state of India

The haemato-biochemical indices and oxidative stress markers in horses naturally infected with Trypanosoma evansi were evaluated by analyzing the level of these parameters between T. evansi infected (microscopically positive patent group and PCR positive latent group) and infection free horses. To compare the hemato-biochemical indices and oxidative stress indicators, horses were divided into three categories based on diagnostic test employed and positive results obtained. These included Romanowsky stained slide positive group (Group I; n = 6), PCR positive group (group II; n = 28) and negative control group (group III, n = 30), revealing parasitologically positive patent, molecular positive latent and disease free status of horses. A significant reductions in total ery-throcytes count (TEC, P = 0.01), haemoglobin (Hb, P = 0.01) and packed cell volume (PCV, P = 0.04) was noticed both in group I and group II while significant neutrophilia and lymphocytopenia was observed in group I when compared to negative control group. Substantial increase in creatinine (CRTN, P = 0.032) and gamma glutamyl transferase (GGT, P = 0.012) in group I while significant decrease in glucose (GLU, P = 0.04) and iron (Fe, P = 0.01) were noticed in both group I and group II in comparison to group III. A significant difference in lipid peroxides (LPO, P = 0.01) with highest level in patent group I (15.33 ± 0.53) followed by PCR positive latent group (14.09 ± 1.66) indicates higher lipid peroxidation in erythrocytes and oxidative stress in decreasing order when compared with infection free control horses (9.83 ± 0.97). Catalase (CAT, P = 0.01) was significantly lower in para-sitological (0.82 ± 0.14) and molecular positive cases (1.27 ± 0.35) in comparison to control group (3.43 ± 0.96). The levels of su-peroxide dismutase (SOD, P = 0.01), reduced glutathione (GSH, P = 0.01) and ferric reducing antioxidant power (FRAP, P = 0.01) were significantly lower in parasito-molecular positive cases as compared to infection free control horses. An inverse correlation of RBC count with LPO and GSH and a direct correlation with catalase, SOD and FRAP was revealed. Overall, the observed substantial decreases in the oxidative parameters like catalase CAT, SOD, GSH and FRAP activities with remarkably elevated levels of LPO indicate high exposure of erythrocytes to oxidative damage in T.evansi infected horses.
Hyperinsulinemia is associated with increasing insulin secretion but not with decreasing insulin clearance in an age‐related metabolic dysfunction mice model

Human life expectancy is increasing faster lately and, consequently, the number of patients with age‐related diseases such as type 2 diabetes (T2D) is rising every year. Cases of hyperinsulinemia have been extensively reported in elderly subjects and this alteration in blood insulin concentration is postulated to be a cause of insulin resistance, which in some cases triggers T2D onset. Thus, it is important to know the underlying mechanisms of age‐dependent hyperinsulinemia to find new strategies to prevent T2D in elderly subjects. Two processes control blood insulin concentration: Insulin secretion by the endocrine portion of the pancreas and insulin clearance, which occurs mainly in the liver by the action of the insulin‐degrading enzyme (IDE). Here, we demonstrated that 10‐month‐old mice (old) display increased body and fat pad weight, compared with 3‐month‐old mice (control), and these alterations were accompanied by glucose and insulin intolerance. We also confirm hyperinsulinemia in the old mice, which was related to increased insulin secretion but not to reduced insulin clearance. Although no changes in insulin clearance were observed, IDE activity was lower in the liver of old compared with the control mice. However, this decreased IDE activity was compensated by increased expression of IDE protein in the liver, thus explaining the similar insulin clearance observed in both groups. In conclusion, at the beginning of aging, 10‐month‐old mice do not display any alterations in insulin clearance. Therefore, hyperinsulinemia is initiated primarily due to a higher insulin secretion in the age‐related metabolic dysfunction in mice.
Automated gonioscopy photography for iridocorneal angle grading

Purpose: The aim of this study is to assess the agreement between manual and automated gonioscopy for iridocorneal angle opening. Methods: The research is a cross-sectional observational study. Manual and automated gonioscopy were performed to consecutive patients in a glaucoma clinic. Iridocorneal angle opening grading was performed according to Shaffer’s classification. Automated gonioscopy was performed with NGS-1 automated gonioscope (NIDEK Co., Gamagori, Japan). The automated gonio-photos were graded by two independent observers. Agreement between automated and manual gonioscopy and also among raters was ascertained by Fleiss’ kappa statistic and comparison of area under curve. Results: In total, 88 eyes of 47 subjects were analysed. Mean age was 63 ± 10 years. Twenty eyes (22.7%) were excluded from grading due to poor quality images. Angle closure was detected in 23.4% with dynamic gonioscopy in comparison with 4.3% using automated image grading. The agreement for angle closure diagnosis between dynamic and automated gonioscopy was low (κ = 0.09 ± 0.10; p = 0.18). The area under curve for detecting eyes with angle closure showed poor accuracy between automated and manual methods (area under curve: 0.53 ± 0.05, 95% confidence interval: 0.44–0.62). There was modest inter-rater agreement for angle opening assessment of automated images with Fleiss’ kappa of 0.17 (95% confidence interval: 0.035–0.238). Conclusion: Manual and automated gonioscopy showed only slight agreement for the assessment of iridocorneal angle opening status. Further improvements of the NGS-1 automated gonioscopy and technique are desired for widespread use in a real-life setting.
A Learning Approach to Wireless Information and Power Transfer Signal and System Design

The end-to-end learning of Simultaneous Wireless Information and Power Transfer (SWIPT) over a noisy channel is studied. Adopting a nonlinear model for the Energy Harvester (EH) at the receiver, a joint optimization of the transmitter and the receiver is implemented using Neural Network (NN)-based autoencoders. Modulation constellations for different levels of "power" and "information rate" demands at the receiver are obtained. The numerically optimized signal constellations are inline with the previous theoretical results. In particular, it is observed that as the receiver power demand increases, all but one of the modulation symbols are concentrated around the origin and the other symbol is shot away from the origin.
Brain-to-brain synchronization of the expectation of cooperation behavior: A fNIRS hyperscanning study

Expectation of cooperation (hereafter EOC) plays an important role in social dilemmas. In the present study, participant dyads performed an improved prisoner's dilemma game, with their prefrontal cortex and inferior frontal gyrus recorded via the functional near-infrared spectroscopy (fNIRS) hyperscanning technique. Inter brain results indicated significant inter-brain neural synchronization (INS) across participant pairs' inferior frontal gyrus (IFG) in high-powered incentives and defective expectation. Furthermore, the agreeableness proved to be a predictor of cooperative expectation in the inter brain frame. These results may revealed the inter-brain underlying substrate of EOC in social dilemmas and indicated the involvement of the mentalizing network and human mirror neuron system network in social dilemmas.
Clients’ experiences of one‐to‐one low‐intensity interventions for common mental health problems: An interpretative phenomenological analysis

Objectives Common mental health disorders such as depression and anxiety are highly prevalent and carry significant health care and economic burdens. The UK's improving access to psychological therapies (IAPT) initiative was developed as a cost‐effective way of reducing the pernicious effects of these disorders. IAPT interventions, such as guided self‐help, have been subjected to considerable quantitative evaluation. However, there has been minimal investigation into clients’ experiences of the one‐to‐one low‐intensity interventions (LIIs), which form a key component of IAPT service provision. Qualitative exploration could provide rich data regarding experiences of psychological change and factors affecting therapeutic experiences. This will enable informative, client led insights into how low‐intensity therapy can be improved. Methods Interpretative phenomenological analysis of eight semi‐structured interviews was used to develop an idiosyncratic understanding of clients’ experiences of one‐to‐one LIIs following entry into a randomized control trial (RCT). Results Four superordinate themes were identified from clients’ accounts: goals and expectations of therapy, beneficial aspects of therapy, non‐beneficial aspects of therapy, and the experience of psychological change. A heuristic model of interrelationships between factors is proposed. Conclusions Both therapeutic techniques and relationships contribute to beneficial therapeutic experiences. The results reported here can be used to inform practice by harnessing the most beneficial aspects of therapy, such as developing adaptive therapeutic approaches to clients’ clinical needs and facilitating idiosyncratic processes of psychological change. Due to limited qualitative research in this area, further research should be conducted in different service settings to assess differences and similarities in clients’ experiences. Practitioner points Therapists who adapted to clients’ individual needs were perceived as more effective than those who did not. Effective therapeutic experiences were exemplified by a personal therapeutic approach, enough time to discuss issues and normalizing client's experiences. Clients develop idiosyncratic models of change which should be encouraged by therapists over and above clinical models.
Reciprocal Regulation of AMPK/SNF1 and Protein Acetylation

Adenosine monophosphate (AMP)-activated protein kinase (AMPK) serves as an energy sensor and master regulator of metabolism. In general, AMPK inhibits anabolism to minimize energy consumption and activates catabolism to increase ATP production. One of the mechanisms employed by AMPK to regulate metabolism is protein acetylation. AMPK regulates protein acetylation by at least five distinct mechanisms. First, AMPK phosphorylates and inhibits acetyl-CoA carboxylase (ACC) and thus regulates acetyl-CoA homeostasis. Since acetyl-CoA is a substrate for all lysine acetyltransferases (KATs), AMPK affects the activity of KATs by regulating the cellular level of acetyl-CoA. Second, AMPK activates histone deacetylases (HDACs) sirtuins by increasing the cellular concentration of NAD+, a cofactor of sirtuins. Third, AMPK inhibits class I and II HDACs by upregulating hepatic synthesis of α-hydroxybutyrate, a natural inhibitor of HDACs. Fourth, AMPK induces translocation of HDACs 4 and 5 from the nucleus to the cytoplasm and thus increases histone acetylation in the nucleus. Fifth, AMPK directly phosphorylates and downregulates p300 KAT. On the other hand, protein acetylation regulates AMPK activity. Sirtuin SIRT1-mediated deacetylation of liver kinase B1 (LKB1), an upstream kinase of AMPK, activates LKB1 and AMPK. AMPK phosphorylates and inactivates ACC, thus increasing acetyl-CoA level and promoting LKB1 acetylation and inhibition. In yeast cells, acetylation of Sip2p, one of the regulatory β-subunits of the SNF1 complex, results in inhibition of SNF1. This results in activation of ACC and reduced cellular level of acetyl-CoA, which promotes deacetylation of Sip2p and activation of SNF1. Thus, in both yeast and mammalian cells, AMPK/SNF1 regulate protein acetylation and are themselves regulated by protein acetylation.
Food Perceptions and Dietary Changes for Chronic Condition Management in Rural Peru: Insights for Health Promotion

Peru is undergoing a nutrition transition and, at the country level, it faces a double burden of disease where several different conditions require dietary changes to maintain a healthy life and prevent complications. Through semistructured interviews in rural Peru with people affected by three infectious and noninfectious chronic conditions (type 2 diabetes, hypertension, and neurocysticercosis), their relatives, and focus group discussions with community members, we analyzed their perspectives on the value of food and the challenges of dietary changes due to medical diagnosis. The findings show the various ways in which people from rural northern Peru conceptualize good (buena alimentación) and bad (mala alimentación) food, and that food choices are based on life-long learning, experience, exposure, and availability. In the context of poverty, required changes are not only related to what people recognize as healthy food, such as fruits and vegetables, but also of work, family, trust, taste, as well as affordability and accessibility of foods. In this paper we discuss the complexity of introducing dietary changes in poor rural communities whose perspectives on food are poorly understood and rarely taken into consideration by health professionals when promoting behavior change.
Biocompatibility of common implantable sensor materials in a tumor xenograft model

Abstract Real‐time monitoring of tumor microenvironment parameters using an implanted biosensor could provide valuable information on the dynamic nature of a tumor's biology and its response to treatment. However, following implantation biosensors may lose functionality due to biofouling caused by the foreign body response (FBR). This study developed a novel tumor xenograft model to evaluate the potential of six biomaterials (silicon dioxide, silicon nitride, Parylene‐C, Nafion, biocompatible EPOTEK epoxy resin, and platinum) to trigger a FBR when implanted into a solid tumor. Biomaterials were chosen based on their use in the construction of a novel biosensor, designed to measure spatial and temporal changes in intra‐tumoral O2, and pH. None of the biomaterials had any detrimental effect on tumor growth or body weight of the murine host. Immunohistochemistry showed no significant changes in tumor necrosis, hypoxic cell number, proliferation, apoptosis, immune cell infiltration, or collagen deposition. The absence of biofouling supports the use of these materials in biosensors; future investigations in preclinical cancer models are required, with a view to eventual applications in humans. To our knowledge this is the first documented investigation of the effects of modern biomaterials, used in the production of implantable sensors, on tumor tissue after implantation. © 2018 The Authors. Journal of Biomedical Materials Research Part B: Applied Biomaterials published by Wiley Periodicals, Inc. J Biomed Mater Res Part B, 2018. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 1620–1633, 2019.
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

Recommendation is crucial in both academia and industry, and various techniques are proposed such as content-based collaborative filtering, matrix factorization, logistic regression, factorization machines, neural networks and multi-armed bandits. However, most of the previous studies suffer from two limitations: (1) considering the recommendation as a static procedure and ignoring the dynamic interactive nature between users and the recommender systems, (2) focusing on the immediate feedback of recommended items and neglecting the long-term rewards. To address the two limitations, in this paper we propose a novel recommendation framework based on deep reinforcement learning, called DRR. The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can consider both the dynamic adaptation and long-term rewards. Furthermore, a state representation module is incorporated into DRR, which can explicitly capture the interactions between items and users. Three instantiation structures are developed. Extensive experiments on four real-world datasets are conducted under both the offline and online evaluation settings. The experimental results demonstrate the proposed DRR method indeed outperforms the state-of-the-art competitors.
Power Consumption Model of a Circulating Wet Runner Pump

In this paper the power consumption model of a circulating wet runner pump is presented. Such a model provides several advantages since it can be used for example to detect issues during operation of the pump. For instance, dry running which might damage the bearings of the pump can be detected based on deviations between the measured power and the power predicted by the model. Furthermore, based on the power model the volume flow which passes the pump can be determined without a volume flow sensor and thus save costs. As the overall power consumption of the pump is influenced by different components such as electrical and friction losses, models of the individual components which have an influence on the power consumption are presented. Then, the components are combined to one overall power consumption model and the model parameters are identified by measurements. Finally, the model is validated by comparison of the dynamic behaviour of the model with the actual measured power consumption.