Miracle-dz/UniFAR-FTUs huggingface dataset:
Fight Poison with Poison: Detecting Backdoor Poison Samples via Decoupling Benign Correlations

Deep learning suffers from backdoor poisoning attacks. By injecting only a few poison samples into a training set, adversaries can easily embed stealthy backdoor into the trained models. In this work, we study poison samples detection for defending against backdoor poisoning attacks on deep neural networks (DNNs). A principled idea underlying prior arts on this problem is to utilize the backdoored models’ distinguishable behaviors on poison and clean populations to distinguish between these two different populations themselves and remove the identiﬁed poison . Typically, many prior arts build their detectors upon a latent separability assumption, which states that backdoored models trained on the poisoned dataset will learn separable latent representations for backdoor and clean samples. Although such separation behaviors empirically exist for many existing attacks, there is no control on the separability and the extent of separation can vary a lot across different poison strategies, datasets, as well as the training conﬁgurations of backdoored models. Worse still, recent adaptive poison strategies can greatly reduce the "distinguishable behaviors" and consequently render most prior arts less effective (or completely fail). We point out that these limitations directly come from the passive reliance on some distinguishable behaviors that are not controlled by defenders. To mitigate such limitations, in this work, we propose the idea of active defense — rather than passively assuming backdoored models will have certain distinguishable behaviors on poison and clean samples, we propose to actively enforce the trained models to behave differently on these two different populations. Speciﬁcally, we introduce confusion training as a concrete instance of active defense. Confusion training separates poison and clean populations by introducing another poisoning attack to the already poisoned dataset, which actively decouples the benign correlations and leave backdoor correlations the only learnable patterns — consequently, only backdoor poison samples can be ﬁtted, while clean samples are underﬁtted. In short, we literally invite a "defensive poison" in to ﬁght the original backdoor
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

Failure detection in automated image classification is a critical safeguard for clinical deployment. Detected failure cases can be referred to human assessment, ensuring patient safety in computer-aided clinical decision making. Despite its paramount importance, there is insufficient evidence about the ability of state-of-the-art confidence scoring methods to detect test-time failures of classification models in the context of medical imaging. This paper provides a reality check, establishing the performance of in-domain misclassification detection methods, benchmarking 9 widely used confidence scores on 6 medical imaging datasets with different imaging modalities, in multiclass and binary classification settings. Our experiments show that the problem of failure detection is far from being solved. We found that none of the benchmarked advanced methods proposed in the computer vision and machine learning literature can consistently outperform a simple softmax baseline, demonstrating that improved out-of-distribution detection or model calibration do not necessarily translate to improved in-domain misclassification detection. Our developed testbed facilitates future work in this important area
Accurate modeling and mitigation of overlapping signals and glitches in gravitational-wave data

The increasing sensitivity of gravitational-wave detectors has brought about an increase in the rate of astrophysical signal detections as well as the rate of “glitches”; transient and non-Gaussian detector noise. Temporal overlap of signals and glitches in the detector presents a challenge for inference analyses that typically assume the presence of only Gaussian detector noise. In this study we perform an extensive exploration of the eﬃcacy of a recently proposed method that models the glitch with sine-Gaussian wavelets while simultaneously modeling the signal with compact-binary waveform templates. We explore a wide range of glitch families and signal morphologies and demonstrate that the joint modeling of glitches and signals (with wavelets and templates respectively) can reliably separate the two. We ﬁnd that the glitches that most aﬀect parameter estimation are also the glitches that are well modeled by such wavelets due to their compact time-frequency signature. As a further test, we investigate the robustness of this analysis against waveform systematics like those arising from the exclusion of higher-order modes and spin-precession eﬀects. Our analysis provides an estimate of the signal parameters; the glitch waveform to be subtracted from the data; and an assessment of whether some detected excess power consists of a glitch, signal, or both. We analyze the low-signiﬁcance triggers (191225 215715 and 200114 020818) and ﬁnd that they are both consistent with glitches overlapping high-mass signals. D max , and the low-frequency cutoﬀ f low runs have a sampling rate of 2048Hz used a sampling rate of 1024 Hz (which precludes any possibility of tidal group analyses target overlapping data, though the exact center of the glitch might be shifted according to long- and short-term glitch behavior.
An exploratory investigation of teaching innovations and learning factors in a lean manufacturing systems engineering course

ABSTRACT The use of collaborative activities and simulation sessions in engineering education has been explored previously. However, few studies have investigated the relationship of these types of teaching innovations with other learner characteristics, such as self-efficacy and background knowledge. This study explored the effects of collaborative activities and simulation sessions on learning and the relationships between self-efficacy beliefs, background knowledge, and learning. Data were collected from two different terms in an upper division engineering course entitled Lean Manufacturing Systems Engineering. Findings indicated that the impact of collaborative activities and simulation sessions appears to be different, depending on the concepts being taught. Simulation sessions were found to have a significant effect on self-efficacy beliefs, and background knowledge had a mixed effect on learning. Overall the results of this study highlight the complex set of relationships between classroom innovations, learner characteristics, and learning.
International Journal of Scientific Research in Science and Technology

291 Face Identification and Recognition Using AI Dr. A. Senthil Kumar1, R. Anusha2, K. Arshitha2, S. M. Zeelan Basha2, P. Lavanya2 1B.E. , M.E. , PGDVLSI. , DISM. , Ph.D. (IITR), PDF. (TUT.SA), Senior PDF. (VSD. TUV, EUROPE) Department of EEE, Principal, Sanskrithi school of engineering, Puttparthi, Andhra Pradesh, India 2Department of ECE, Sanskrithi School of Engineering, Puttparthi, , Andhra Pradesh, India
A Narrative Review on Biopsychosocial Predictors of Cognitive Impairment among Multiple Sclerosis Patients: Directions for Malaysia Studies

Cognitive impairment is the most disabling symptoms of Multiple Sclerosis (MS). Researchers have been studying factors that could predict cognitive impairment among MS patients hoping to alleviate its consequences and gather indicators of the disease progression. However, there were limited up-to-date articles that review the predictors of cognitive impairment among MS patients. In Malaysia, the topic about cognitive functioning in MS was absent. This review aims to identify and synthesize the research evidence concerning biopsychosocial variables on cognitive impairment among this population for future directions in Malaysia researches. A narrative review was performed by identifying research articles from year 2004 to 2019 through PubMed, EBSCOhost, Scopus and Google Scholar. Full-text articles meeting the selection criteria were included for qualitative synthesis. A total of 12 studies were included. Studies included in this paper found that age, course of disease and anxiety predicts cognitive functioning. Mixed results were found among variables such as gender, disability, fatigue, burden of lesion, depression and educational level. Stress was correlated with cognitive functioning but it was not a significant predictor. Although many factors were found to affect cognitive functioning among MS patients, evidence provided from this review indicates that their relationships might not be linear and direct.
ELECTRON CLOUD IN THE LHC

This article reports some highlights from the joint INFN/ARIES workshop ECLOUD’18. We focus on electron-cloud e ects in the LHC and at SuperKEKB, predictions for future machines like FCC-hh, HE-LHC and FCC-ee, models and parameters for the secondary-emission yield, recent trends in electron-cloud simulations, mitigation measures, and novel phenomena. Some workshop statistics and a brief outlook conclude the paper.
Investigating the Rationales Behind Student Engagement in Learning English at Ho Chi Minh City University of Food Industry

This paper aims to qualitatively investigate the factors that affect non-English major students' engagement in their EFL courses at the Ho Chi Minh City University of Food Industry. Regarding the literature, the paper firstly reviews the notion of engagement and its different dimensions then ends with an overview of the recent relevant studies. The data is collected and analyzed through group interviews. Finally, the results and findings will serve as a foundation for future studies which look at the strategies to raise non - English major students’ engagement in learning English at tertiary education in Vietnam.
AGE-RELATED CHANGES OF ARGINASE ACTIVITY AND NITRIC OXIDE LEVEL IN PHAGOCYTES AND THEIR MODULATION..

R. S. Dovhyi1,2, I. S. Nikolsky3, L. M. Skivka1 1Taras Shevchenko National University of Kyiv Educational and Scientific Center “Institute of Biology and Medicine” 2, Academician Glushkov Ave, Kyiv 03127, Ukraine e-mail: roman_dovhyi@univ.kiev. ua 2 Institute of Gerontology, AMS of Ukraine, 67, Vyshgorodska St., Kyiv 04114, Ukraine 3 State Institute of Genetic and Regenerative Medicine, NAMS of Ukraine 67, Vyshgorodska St., Kyiv 04114, Ukraine
Clinical Importance of Blood Drug Concentration of Oral Molecular Targeted Drugs for Renal Cell Carcinoma

-- Purpose: Therapeutic drug monitoring (TDM) is widely used in clinical practice to maximize drug efficacy and minimize toxicities. Currently, it is also practiced in the use of oral molecular targeted drugs. The objective of this study was to assess the clinical importance of measuring the systemic concentration of oral molecular targeted drugs used to treat renal cell carcinoma (RCC). Methods: The systemic concentrations of the oral molecular targeted drugs sorafenib, sunitinib, axitinib, pazopanib, and everolimus used for RCC were useful for therapeutic interventions, and clinical outcomes were evaluated retrospectively. Results: The interventional use of systemic drug concentration was confirmed in 26 of 87, and their categories are presented. The systemic concentration of sunitinib was useful in dose reduction and/or discontinuation (n = 10), dose escalation (n = 3), and adherence monitoring (n = 2). Nine of the 10 patients whose dose was reduced showed reduced adverse event. Two patients who were intervened in adherence monitor showed improved adherence. For axitinib, dose reduction and/or discontinuation (n = 1) and dose escalation (n = 6) were confirmed. For pazopanib, dose reduction and/or discontinuation (n = 1) and drug interaction detection (n = 1) were confirmed, both of them were confirmed to have reduced adverse events. For everolimus, dose reduction and/or discontinuation (n = 1) and drug interaction detection (n = 1) were confirmed, a patient with reduced dose recovered from adverse events. Interventions for sorafenib were not identified. Conclusions: This study demonstrated that systemic concentrations of oral molecular targeted drugs for RCC were considered to be clinically useful for dose adjustment, monitoring of treatment adherence, and the detection of drug interactions. Moreover, this information could be successfully used to guide individualized therapy to maximize the antitumor effects of these drugs.
Bringing agile practice to the classroom: Student voices of third-year major project implementation

Agile practices are the current trend in the software industry, so it is, therefore, pertinent that students not only learn but practise agile development in the learning environment. Adapting to a different approach such as agile practices in software systems development has been a challenge for both students and lecturing staff. This study examined the underlying challenges and experiences of students in using the agile approach to software development in a project course. A mixed-methods approach was followed with focus group interviews and a survey instrument used to determine the students’ experiences of the agile approach to software development. The results reflected an intention to use agile practices in future and enthusiasm in using agile practices in learning. In addition, it was found that more programming expertise was needed for some students without the requisite programming knowledge. These findings have implications for structuring courses more effectively for undergraduate modules.
Tunable square slot FSS EC modelling and optimisation

An equivalent circuit model for tunable square slot frequency selective surfaces (FSS) is proposed. Tuning is achieved with the inclusion of a discrete capacitance element, at key points within the FSS unit cell. The equivalent circuit model takes into account the FSS physical attributes. The performance of the proposed equivalent circuit model was evaluated against results obtained from appropriate electromagnetic simulations. Results demonstrate the validity of the proposed equivalent circuit model, in which good estimations of the frequency response of FSS structures were obtained. A RMSE value of 190 MHz was extracted from the complete parametric simulation set. The model was further validated against measurements performed on a tunable active FSS prototype inside an anechoic chamber. Tuning of the FSS was achieved by means of bias voltage to modify the varicaps capacitance value. A relatively good agreement was verified between equivalent circuit model, electromagnetic simulations and measurements. Finally, this work is sought to be a useful contribution to the literature on this topic, by improving on the elementary models of such FSS structures and be useful as a good and fast first approach to determine approximate FSS unit cell dimensions.
University of Birmingham A comprehensive review of mTOR-inhibiting pharmacotherapy for the treatment of non-infectious uveitis

Background : Non-infectious uveitis is a sight-threatening inflammatory disease that often necessitates prolonged use of high-dose corticosteroids, resulting in significant systemic side effects. There is a need for efficacious steroid-sparing immunomodulatory therapy for these patients, and the mTOR inhibitors (sirolimus and everolimus) may be contenders for this role. Methods : A comprehensive review of preclinical and clinical research on mTOR inhibitors for non-infectious uveitis was performed. Articles were identified by a search of MEDLINE (PubMed/OVID) and EMBASE (OVID) the terms ( uveitis OR non-infectious uveitis ) AND ( mTOR inhibitor OR sirolimus OR everolimus ). Assessment of study aims, methods, efficacy outcomes and adverse events was performed. Results : Seven pre-clinical and nine clinical studies were identified. One study in each group was on everolimus, the rest sirolimus. Preclinical studies have been performed in rabbit, rat, mouse and in-vitro models. Clinical studies range from comparative open-label trials to case reports, with reported clinical efficacy ranging from 40% to 100% depending on endpoint assessed. The overall rate of drug-related adverse events (such as ocular irritation, visual floaters, nausea and vomiting) was 0.640 events per patient-year with sirolimus, and 0.111 events per patient-year with everolimus. Conclusion : Published evidence suggests that sirolimus and everolimus may be useful in the management of non-infectious uveitis. Both appear to be well tolerated, especially when
Revision shunt for Budd-Chiari syndrome

controversial, the second is considered more compatible with the observed pathology in these tumors. Noteworthy is the presence of transition zones between the carcinomatous and neuroendocrine components, thus interweaving an intricate admixture of different cell types.It has been suggested that the histogenesis of endocrine cell carcinoma of the gallbladder is closely related to that of adenocarcinoma.Since there are very few reports on mixed gallbladder tumors, the clinical importance of morphological subtyping of this tumorhas not been yet established. Carcinomas of the extrahepatic biliary tract with pure or predominant exocrine differentiation have better prognosis as compared to carcinomas with neuroendocrine differentiation,the latter being associated with shorter survival time. The current case is being thus reported for its rarity in association of adenoendocrine carcinoma with primary sclerosingcholangitis and ulcerative colitis.
Evaluation of pregerminative treatments in gulupa

The genus Passiflora, commonly known as fruits of passion, includes numerous species, including gulupa (Passiflora edulis f. edulis), of nutracetic and economic importance, both for consumption in nature and for its agro-industrial applicability. This research was developed to evaluate the effects of various pre-germinative treatments on the germination of gulupa seeds from the municipality of Ramiriquí (Boyacá), such as: exposure to hydrogen peroxide (H2O2), hypochlorite of sodium (NaOCl), gibberellic acid (GA3), distilled water imbibition and stratification at 4 °C, in varying concentrations and exposure times (24 and 48 hours), using an experimental design completely random, with three repetitions of 50 seed each one. Statistical analysis showed significant differences between treatments, with H2O2 being 15% the most effective, with a germination percentage (PG) of 88% in exposed seeds for 48 hours. In the presence of NaOCl the percentages were lower 36 40%. GA3 at 100 ppm for 24 hours recorded 51% PG, at the other concentrations of this growth regulator and exposure times this value was lower. The use of H2O2 has not been reported as a treatment to induce germination in the genus Passiflora. These results can be applied for the treatment of seeds in plant species can be a viable, effective, economical and easily applicable alternative.
FACULTY OF INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING

This thesis details the design and implementation of a system that can find relevant and latent semantic topics from textual documents. The design of this system, named Topic Distiller, is inspired by research conducted on automatic keyphrase extraction and automatic topic labeling, and it employs entity linking and knowledge bases to reduce text documents to their semantic topics. The Topic Distiller is evaluated using methods and datasets used in information retrieval and automatic keyphrase extraction. On top of the common datasets used in the literature three additional datasets are created to evaluate the system. The evaluation reveals that the Topic Distiller is able to find relevant and latent topics from textual documents, beating the state-of-the-art automatic keyphrase methods in performance when used on news articles and social media posts.
UNIVERSITY OF RIJEKA FACULTY OF HUMANITIES AND SOCIAL SCIENCES DEPARTMENT OF ENGLISH

From the beginnings of human culture to the multimedia environment in which we live today, stories have been used as powerful socializing and pedagogical tools, providing communities with clear patterns of acceptable and abhorrent behavior through their heroes and villains. For this to be effective, it was necessary to code such characters in a way that was immediately understood by the story’s recipients. One such code is the characters’ language and how it is used to create a cultural model of particular character types. This thesis aims to examine the language of villains, its features and the way they interact in creating a recognizable villainous identity. To do this, a corpus of nine films produced by the Disney company in the decade between 1989 and 1999, a period known as the “Disney Renaissance” was examined. The study comprises two parts. Firstly, auditory analysis was conducted to examine one of the most salient ways in which language is manifested: the characters’ accents. Secondly, discourse analysis of the main villains’ language was conducted, with the intention of exploring how language is used to construct certain villainous identities, especially in regards to power or lack thereof. It was found that negatively coded characters tend to be visually and linguistically characterized as foreign, and are therefore more likely to speak in non-American accents. Furthermore, the villains’ language use revealed a dual nature with regards to power, with them presenting both a victimized and non-threatening, as well as an authoritative and powerful figure. Finally, some implications as well as potential for further research were
Prophylactic Zinc Administration Combined with Swimming Exercise Prevents Cognitive-Emotional Disturbances and Tissue Injury following a Transient Hypoxic-Ischemic Insult in the Rat

Exercise performance and zinc administration individually yield a protective effect on various neurodegenerative models, including ischemic brain injury. Therefore, this work was aimed at evaluating the combined effect of subacute prophylactic zinc administration and swimming exercise in a transient cerebral ischemia model. The prophylactic zinc administration (2.5 mg/kg of body weight) was provided every 24 h for four days before a 30 min common carotid artery occlusion (CCAO), and 24 h after reperfusion, the rats were subjected to swimming exercise in the Morris Water Maze (MWM). Learning was evaluated daily for five days, and memory on day 12 postreperfusion; anxiety or depression-like behavior was measured by the elevated plus maze and the motor activity by open-field test. Nitrites, lipid peroxidation, and the activity of superoxide dismutase (SOD) and catalase (CAT) were assessed in the temporoparietal cortex and hippocampus. The three nitric oxide (NO) synthase isoforms, chemokines, and their receptor levels were measured by ELISA. Nissl staining evaluated hippocampus cytoarchitecture and Iba-1 immunohistochemistry activated the microglia. Swimming exercise alone could not prevent ischemic damage but, combined with prophylactic zinc administration, reversed the cognitive deficit, decreased NOS and chemokine levels, prevented tissue damage, and increased Iba-1 (+) cell number. These results suggest that the subacute prophylactic zinc administration combined with swimming exercise, but not the individual treatment, prevents the ischemic damage on day 12 postreperfusion in the transient ischemia model.