Miracle-dz/UniFAR-FTUs huggingface dataset:
Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning

Transductive zero-shot learning is designed to recognize unseen categories by aligning both visual and semantic information in a joint embedding space. Four types of domain biases exist in Transductive ZSL, i.e., visual bias and semantic bias in two domains, and two visual-semantic biases exist in the seen and unseen domains. However, the existing work has only focused on specific components of these topics, leading to severe semantic ambiguity during knowledge transfer. To solve this problem, we propose a novel attribute-induced bias eliminating (AIBE) module for Transductive ZSL. Specifically, for the visual bias between the two domains, the mean-teacher module is first used to bridge the visual representation discrepancy between the two domains using unsupervised learning and unlabeled images. Then, an attentional graph attribute embedding process is proposed to reduce the semantic bias between seen and unseen categories using a graph operation to describe the semantic relationship between categories. To reduce semantic-visual bias in the seen domain, we align the visual center of each category with the corresponding semantic attributes instead of with the individual visual data point, which preserves the semantic relationship in the embedding space. Finally, for the semantic-visual bias in the unseen domain, an unseen semantic alignment constraint is designed to align visual and semantic space using an unsupervised process. The evaluations on several benchmarks demonstrate the effectiveness of the proposed method, e.g., 82.8%/75.5%, 97.1%/82.5%, and 73.2%/52.1% for Conventional/Generalized ZSL settings for CUB, AwA2, and SUN datasets, respectively.
Description of self-reported fluid intake and its effects on body weight, symptoms, quality of life and physical capacity in patients with stable chronic heart failure.

AIM To describe the self-reported fluid intake and its effects on body weight, signs and symptoms of heart failure, quality of life, physical capacity and thirst, in patients with stabilised chronic heart failure. BACKGROUND Patients with chronic heart failure are often recommended a fluid restriction of 1.5 l/day but there is no evidence in the literature for this recommendation and little is known about the fluid intake consequences. DESIGN Crossover study. METHODS Chronic heart failure patients, clinically stabilised after an unstable state, were randomised to a 32-week cross-over study assessing the clinical importance of fluid prescription. In a secondary analysis of 63 patients, efficacy variables were analysed in relation to the self-reported median fluid intake of 19 ml/kg body weight/day. RESULTS The mean fluid intake was 16 ml/kg/day in the below-median group and 24 ml/kg/day in the above-median group. No between-group differences were found in change in body weight, signs and symptoms, diuretic use, quality of life or physical capacity. However, the above-median group significantly decreased sense of thirst and difficulties to adhere to the fluid prescription compared with the below-median group. CONCLUSION In clinically stabilised chronic heart failure patients on optimal pharmacological treatment, a larger fluid intake was associated with decreasing thirst without any measurable negative effects on signs and symptoms of heart failure, diuretic use or physical capacity. Thus, a more liberal fluid intake may be advisable in chronic heart failure patients who have been stabilised after an initial unstable clinical state. RELEVANCE TO CLINICAL PRACTICE Nurses involved in the care for patients with heart failure known how troublesome thirst can be and how difficult it can be to follow a restricted fluid intake. This study indicates that it is possible to reassess and recommend a less strict fluid intake in stabilised patients with chronic heart failure.
Topology optimization for optical microlithography with partially coherent illumination

This article revisits a topology optimization design approach for micro‐manufacturing and extends it to optical microlithography with partially coherent illumination. The solution is based on a combination of two technologies, the topology optimization and the proximity error correction in microlithography/nanolithography. The key steps include (i) modeling the physical inputs of the fabrication process, including the ultraviolet light illumination source and the mask, as the design variables in optimization and (ii) applying physical filtering and heaviside projection for topology optimization, which corresponds to the aerial image formulation and the pattern development processes, respectively. The proposed approach results in an effective source and a binary design mask, which can be sent directly to fabrication without additional post‐processing steps for proximity error correction. Meanwhile, the performance of the device is optimized and robust with respect to process variations, such as dose/photo‐resist variations and lens defocus. A compliant micro‐gripper design example is considered to demonstrate the applicability of this approach. Copyright © 2016 John Wiley & Sons, Ltd.
How the Self Became a Problem: A Psychological Review of Historical Research

In this article, historical evidence pertaining to self hood is reviewed. A scheme of stages is delineated, according to which the modern self and its uncertainties have evolved. The historical data are then reviewed in connection with the following four major problems regarding the self: knowing and conceptualizing the self; defining or creating the self; understanding one's potential and fulfilling it; and relating the single self to society.
Sensitive troponin assay predicts outcome in syncope

Aims To assess whether plasma troponin concentration measured by a sensitive assay can predict 1-month and 1-year serious outcome, or all-cause death in patients presenting with syncope to the emergency department (ED). Methods Prospective cohort study of admitted adult patients presenting to the ED after an episode of syncope who had plasma troponin measured 12 h after syncope using the ARCHITECT STAT sensitive troponin I assay (Abbott Diagnostics). Primary endpoints were the composite endpoint of serious outcome or all-cause death at 1 month and 1 year. Results Between 1 March 2007 and 22 July 2008, 338 of 528 patients admitted from the ED with syncope had plasma troponin concentrations determined. Troponin concentrations were above the limit of detection in 261 (77%) patients. Patients numbering 120 (36%) had a troponin concentration ≥0.03 ng/ml (99th percentile of normal reference population), and 66 (20%) had concentrations ≥0.05 ng/ml (local diagnostic threshold for myocardial infarction). The proportion of patients with a composite serious outcome increased across patients stratified into quintiles based on peak troponin concentration at 1 month (0%, 9%, 13%, 26%, 70%) and at 1 year (10%, 22%, 26%, 52%, 85%). Conclusions The majority of patients admitted from the ED with syncope have detectable plasma troponin concentrations. Peak troponin concentration was associated with increasing risk of serious outcome and death, and this risk increases with higher troponin concentrations. Troponin may have a future role in the risk stratification of patients with syncope.
Acid Etching does not Improve CoCrMo Implant Osseointegration in a Canine Implant Model

Induction of bone ingrowth by topographical changes to implant surfaces is an attractive concept. Topographical modifications achieved by acid etching are potentially applicable to complex 3D surfaces. Using clinically relevant implant models, we explored the effect of wet etching porous bead-coated CoCrMo. The study was designed as two paired animal experiments with 10 dogs. Each dog received four implants; one in each medial femoral condyle (loaded 0.75-mm-gap model) and one in each proximal tibia (press-fit). The implants were observed for 6 weeks and were evaluated by biomechanical pushout tests and histomorphometry. We found that wet etching porous bead-coated CoCrMo implants failed to improve implant performance. Moreover, a tendency towards increased fibrous tissue formation, decreased new bone formation, and decreased mechanical fixation was observed. Surface topography on implants is able to stimulate bone-forming cells, but the clinical performance of an implant surface perhaps relies more on 3D geometrical structure and biocompatibility. Caution should be exercised regarding the results of wet etching of porous bead-coated CoCrMo and there is a need for more preclinical trials.
Comparison of PCR, Isoenzyme Analysis, and Antigen Detection for Diagnosis of Entamoeba histolyticaInfection

ABSTRACT The diagnosis of amebiasis by microscopic identification of the parasite in stool is insensitive and unable to distinguish the invasive parasite Entamoeba histolytica from the commensal parasite E. dispar. In this study, we have tested a PCR technique for the detection of E. histolytica and compared it with isoenzyme analysis and the TechLab E. histolytica-specific antigen detection test. The nested-PCR test we used is based on amplification of the small subunit rRNA gene ofE. histolytica and E. dispar followed by restriction digest analysis of the PCR product. Single stool samples were obtained from 98 patients from Dhaka, Bangladesh, with diarrhea: 88 patients diagnosed by microscopy and/or culture with E. histolytica and/or E. dispar infection and 10 patients without infection. Isoenzyme analysis identified 53 of the infections as E. histolytica and 28 as E. dispar. PCR and isoenzyme identification of E. histolytica agreed in 96% (51 of 53) of amebic cultures. PCR forE. histolytica was negative in all 10 samples that were negative for E. histolytica by isoenzyme and antigen detection. PCR and antigen detection had comparable sensitivities when performed directly on fresh stool specimens, identifying 87% (46 of 53) and 85% (45 of 53), respectively, of E. histolyticainfections identified by isoenzyme analysis. The correlation of results by antigen detection and PCR for identification of E. histolytica in stool was 93% (45 of 48 cases). Mixed infections with E. histolytica and E. dispar were detected by PCR in 14% (12 of 88) of cases. In conclusion, all three techniques for specific identification of E. histolytica in fresh stool showed excellent correlation. Only the TechLab E. histolytica antigen detection test was both rapid and technically simple.
Content-aware Neural Hashing for Cold-start Recommendation

Content-aware recommendation approaches are essential for providing meaningful recommendations for new (i.e.,cold-start) items in a recommender system. We present a content-aware neural hashing-based collaborative filtering approach (NeuHash-CF), which generates binary hash codes for users and items, such that the highly efficient Hamming distance can be used for estimating user-item relevance. NeuHash-CF is modelled as an autoencoder architecture, consisting of two joint hashing components for generating user and item hash codes. Inspired from semantic hashing, the item hashing component generates a hash code directly from an item's content information (i.e., it generates cold-start and seen item hash codes in the same manner). This contrasts existing state-of-the-art models, which treat the two item cases separately. The user hash codes are generated directly based on user id, through learning a user embedding matrix. We show experimentally that NeuHash-CF significantly outperforms state-of-the-art baselines by up to 12% NDCG and 13% MRR in cold-start recommendation settings, and up to 4% in both NDCG and MRR in standard settings where all items are present while training. Our approach uses 2-4x shorter hash codes, while obtaining the same or better performance compared to the state of the art, thus consequently also enabling a notable storage reduction.
Critical and excess current through an open quantum dot: Temperature and magnetic-field dependence

We present measurements of temperature and magnetic-field dependence of the critical current and excess current in a carbon nanotube Josephson quantum dot junction. The junction is fabricated in a controlled environment which allows for extraction of the full critical current. The measurements are performed in the open quantum dot regime and fitted to theory with good qualitative agreement. We also show how to extract level spacing, level broadening, and charging energy of an open quantum dot from a bias spectroscopy plot.
Effect of soil roughness on backscattered P-band radar signal over bare soil

In this paper, the potential use of P-band radar signal for the estimation of soil roughness parameters is analyzed. The Integral Equation Model (IEM) is used to study the sensitivity of backscattered P-band signal to soil surface parameters. A new roughness parameter referred to as Zp, combining the root mean square surface height and the correlation length, is proposed to describe the behavior of P-band radar signal as a function of soil roughness. The IEM model is validated using real data covering a large range of roughness values, derived from experimental airborne P-band SAR campaigns made over agricultural fields. Discrepancies between the measurements and simulations led to the analysis of the influence of low frequency roughness structures on backscattering simulations. The analysis of the behavior of P-band radar signal as a function of multi-scale soil roughness (micro topography and large roughness structures) reveals the complexity of using P-band data for the analysis of bare surface soil parameters.
Analysis of Secondary Structure Predictions of Dengue Virus Type 2 NS2B/NS3 Against Crystal Structure to Evaluate the Predictive Power of theIn Silico Methods

Multiple sequence alignment was performed against eight proteases from the Flaviviridae family using ClustalW to illustrate conserved domains. Two sets of prediction approaches were applied and the results compared. Firstly, secondary structure prediction was performed using available structure prediction servers. The second approach made use of the information on the secondary structures extracted from structure prediction servers, threading techniques and DSSP database of some of the templates used in the threading techniques. Consensus on the one-dimensional secondary structure of Den2 protease was obtained from each approach and evaluated against data from the recently crystallised Den2 NS2B/NS3 obtained from the Protein Data Bank (PDB). Results indicated the second approach to show higher accuracy compared to the use of prediction servers only. Thus, it is plausible that this approach is applicable to the initial stage of structural studies of proteins with low amino acid sequence homology against other available proteins in the PDB.
High speed single phase SOGI-PLL with high resolution implementation on an FPGA

Every power converter needs a precise synchronization method to be able to connect to the utility grid. The synchronization impacts directly on the performance of the converter. Synchronization algorithms are often based on the well known Synchronous Reference Frame Phase Locked Loop (SRF-PLL). These are usually implemented in software on Digital signal Processors (DSP) or Microcontrollers and the maximum sample rate that can be achieved is limited by the hardware used. In this paper a simple and highly effective Field Programmable Gate Array (FPGA) implementation of a Phase Locked Loop (PLL) algorithm based on a Second Order Generalized Integrator PLL (SOGI-PLL) with a high sampling frequency of 500 kHz and 16 bit resolution is presented in detail. Design time is drastically reduced by the use of a fast-prototype high-level synthesis tool without the need of any Hardware Description Language (HDL) code. Both simulation and experimental results on a Xilinx FPGA show an excellent behavior even against severe distortion and frequency or phase steps in the input voltage.
Routing as a Bayesian Coalition Game in Smart Grid Neighborhood Area Networks: Learning Automata-based approach

Routing issues in the existing Smart Grid (SG) literature are focused on Home Area Networks (HANs), Neighborhood Area Networks (NANs), or Wide Area Networks (WANs). Among these, routing in NANs is the most challenging as it entails construction and maintenance of backhaul having various Mesh Routers (MRs). Wireless networks are generally used for communication between backhaul and centralized controller for power distribution. This triggers increased chances of congestion due to scarce resources of available bandwidth and number of channels. Keeping in view of the same, in this paper, we propose a new Efficient Routing Scheme (ERS) as a Bayesian Coalition Game (BCG). The solution strategy integrates the concepts of Learning Automata (LA) in NANs. LA are assumed to be the players in the game, which are deployed at the MRs in NANs. Coalition among the players of the game is scaffolded upon the concepts of Bayesian Networks. Each player in the game is allowed to move from one coalition to another depending upon the payoff function. Corresponding to each move of the player in the game, its action may be rewarded or penalized from the environment. Based upon reward/penalty from the environment, each player updates its action probability vector. The proposed scheme is evaluated with respect to various performance evaluation metrics such as load utilization factor, user satisfaction levels, delay and probability of transmission.
Tandem repeat of C/EBP binding sites mediates PPARγ2 gene transcription in glucocorticoid‐induced adipocyte differentiation

Bone marrow stromal stem cells differentiate into many different types of cells including osteoblasts and adipocytes. Long‐term glucocorticoid treatment decreases osteoblastic activity but increases adipocytes. We investigated the mechanism of glucocorticoid‐induced PPARγ2 transcription. Treatment of human bone marrow stromal cells with dexamethasone induced the differentiation of these cells into adipocytes as measured by oil‐red O staining, and Northern blot analysis showed that dexamethasone strongly induced PPARγ2 mRNA expression in cells cultured in adipocyte induction medium. Moreover, the mRNA of C/EBPδ, an adipocyte‐promoting transcription factor, was also induced by dexamethasone in the presence of induction medium. Gel mobility shift assays using purified GST‐C/EBPδ fusion protein showed that C/EBPδ specifically binds to a 40‐base pair DNA element from PPARγ2 promoter, which was found to contain a tandem repeat of C/EBP binding sites. Transfection studies in mouse mesenchymal C3H10T1/2 cells showed that it is the tandem repeat of the C/EBP binding site in PPARγ2 promoter region that regulates dexamethasone‐mediated PPARγ2 gene activation. We conclude that glucocorticoid‐induced adipogenesis from bone marrow stromal cells is mediated through a reaction cascade in which dexamethasone transcriptionally activates C/EBPδ; C/EBPδ then binds to PPARγ2 promoter and transactivates PPARγ2 gene expression. This activated master regulator, in turn, initiates the adipocyte differentiation. J. Cell. Biochem. 76:518–527, 2000. © 2000 Wiley‐Liss, Inc.
The Development and Application of a Process-oriented "Thermometer" of IT Business Value

The issue of whether firms are receiving an adequate return on their investment in information technology (IT) continues to pervade managerial decision making. While productivity and other financial metrics are established hallmarks of IT investment evaluation, research has called for broader and richer metrics that can take into account the diversity of IT impacts. In this paper, we extend previous instrument development research to develop and test a process-oriented thermometer of IT business value using survey data based on executives’ perceptions of IT impacts at multiple points along the value chain. Consistent with earlier research, we find that our process measures are sensitive to differences in industry, firm size, and business strategy. Through additional analysis of post-implementation reviews of IT impacts in four firms, we find consistency of within-firm perceptual measures among teams of senior executives, highlighting the potential for our thermometer to gauge the level of IT impacts within a single firm. We conclude that process-oriented perceptual measures can offer new and useful insights into IT impacts, complementing what we already know from firm-level objective metrics.
Rating Prediction with Contextual Conditional Preferences

Exploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start system scenario, based on user interests model called contextual conditional preferences. We present results obtained with three publicly available data sets in comparison with several state-of-the-art baselines. We show that usage of contextual conditional preferences improves the prediction accuracy, even when all users have provided a few feedbacks, and hence small amount of data is available.
COVID-19: Social Media Sentiment Analysis on Reopening

The novel coronavirus (COVID-19) pandemic is the most talked topic in social media platforms in 2020. People are using social media such as Twitter to express their opinion and share information on a number of issues related to the COVID-19 in this stay at home order. In this paper, we investigate the sentiment and emotion of peoples in the United States on the subject of reopening. We choose the social media platform Twitter for our analysis and study the Tweets to discover the sentimental perspective, emotional perspective, and triggering words towards the reopening. During this COVID-19 pandemic, researchers have made some analysis on various social media dataset regarding lockdown and stay at home. However, in our analysis, we are particularly interested to analyse public sentiment on reopening. Our major finding is that when all states resorted to lockdown in March, people showed dominant emotion of fear, but as reopening starts people have less fear. While this may be true, due to this reopening phase daily positive cases are rising compared to the lockdown situation. Overall, people have a less negative sentiment towards the situation of reopening.
Method for using visible ocular vasculature for mobile biometrics

Securing personal information on handheld devices, especially smartphones, has gained a significant interest in recent years. Yet, most of the popular biometric modalities require additional hardware. To overcome this difficulty, the authors propose utilising the existing visible light cameras in mobile devices. Leveraging visible vascular patterns on whites of the eye, they develop a method for biometric authentication suitable for smartphones. They start their process by imaging and segmenting whites of the eyes, followed by image quality assessment. The authors' stage 1 matcher is a three-step process that entails extracting interest points [Harris-Stephens, features from accelerated segment test, and speeded up robust features (SURF)], building features (SURF and fast retina keypoint) around those points, and match score generation using random sample consensus-based registration. Stage 2 matcher uses registered Gabor phase filtered images to generate orientation of local binary pattern features for its correlation-based match metric. A fusion of stage 1 and stage 2 match scores is calculated for the final decision. Using a dataset of 226 users, the authors' results show equal error rates as low as 0.04% for long-term verification tests. The success of their framework is further validated on UBIRIS v1 database.