Miracle-dz/UniFAR-FTUs huggingface dataset:
A taxonomy, data set, and benchmark for detecting and classifying malevolent dialogue responses

Conversational interfaces are increasingly popular as a way of connecting people to information. With the increased generative capacity of corpus‐based conversational agents comes the need to classify and filter out malevolent responses that are inappropriate in terms of content and dialogue acts. Previous studies on the topic of detecting and classifying inappropriate content are mostly focused on a specific category of malevolence or on single sentences instead of an entire dialogue. We make three contributions to advance research on the malevolent dialogue response detection and classification (MDRDC) task. First, we define the task and present a hierarchical malevolent dialogue taxonomy. Second, we create a labeled multiturn dialogue data set and formulate the MDRDC task as a hierarchical classification task. Last, we apply state‐of‐the‐art text classification methods to the MDRDC task, and report on experiments aimed at assessing the performance of these approaches.
Prevalence and Clinical Correlates of COVID-19 Outbreak Among Health Care Workers in a Tertiary Level Hospital in Delhi

COVID-19 has been shown to spread rapidly among Healthcare Workers (HCWs) and there is an urgent need to find and implement various mitigation strategies for these individuals. In this study, we summarize the epidemiological characteristics of the COVID-19 outbreak among HCWs in a tertiary care hospital and compare various parameters and preventive measures taken by infected and uninfected subjects. A retrospective questionnaire and record-based analysis was carried out to evaluate the epidemiological and clinical parameters of the participants. Preventive strategies such as masking, hand hygiene and use of prophylactic agents were compared for infected and uninfected subjects. Appropriate statistical tests were applied wherever required. The average age of participants in the COVID-19 positive group was 35.9 years and 52.1% of the positive HCWs were symptomatic. Three of these subjects needed hospitalization and one required admission to an intensive care unit. The study found a protective role of full course of prophylactic hydroxychloroquine in treated subjects versus untreated controls (p = 0.021) and benefit of N95 masks over others (p&lt;0.001). Our results did not show any added protection with the use of other strategies (prophylactic vitamin C, D, zinc, betadine gargles, or other home remedies). We observed outbreak control with increased awareness, near universal testing, PPE provision, sanitation drive and promoting social distancing among HCWs. This study highlights the role of hydroxychloroquine prophylaxis, use of N95 mask and effect of early interventions in outbreak mitigation.
Deep Learning based Scene Agnostic Image Based Visual Servoing

In the era of autonomous navigation, visual servoing plays a pivotal role in tasks that involve vision, control, machine learning and embedded systems. Deep learning has evolved hand-in-hand with the advancements in various technical fields and has become a part and parcel in the current technological inventions. This thesis aims at improving the current state of research in Image Based visual servoing using deep learning architectures. The proposed pipelines make an attempt to carry out visual servoing in unforeseen environments thus making them scene agnostic. We also focus on developing an unsupervised control mechanism that forecasts into a fixed time-horizon and helps in achieving faster target driven visual navigation. We mainly put forward 2 architectures. In the first architecture(chapter 3), we propose a two-fold solution: (i) We consider optical flow as our visual features, which are predicted using a deep neural network. (ii) These flow features are then systematically integrated with depth estimates provided by another neural network using interaction matrix. We further present an extensive benchmark in a photo-realistic 3D simulation across diverse scenes to study the convergence and generalisation of visual servoing approaches. We show convergence for over 3m and 40 degrees while maintaining precise positioning of under 2cm and 1 degree on our challenging benchmark where the existing approaches that are unable to converge for majority of scenarios for over 1.5m and 20 degrees. Furthermore, we also evaluate our approach for a real scenario on an aerial robot. Our approach generalizes to novel scenarios producing precise and robust servoing performance for 6 degrees of freedom positioning tasks with even large camera transformations without any retraining or fine-tuning. In the second architecture(chapter 4), we present a Deep model predictive visual servoing framework (Deep MPC) that can achieve precise alignment with optimal trajectories and can generalize to novel environments. Our framework consists of a deep network for optical flow predictions, which are used along with a predictive model to forecast future optical flow. For generating an optimal set of
Data Preparation in Machine Learning for Condition-based Maintenance

: Using Machine Learning (ML) prediction to achieve a successful, cost-effective, Condition-Based Maintenance (CBM) strategy has become very attractive in the context of Industry 4.0. In other fields, it is well known that in order to benefit from the prediction capability of ML algorithms, the data preparation phase must be well conducted. Thus, the objective of this paper is to investigate the effect of data preparation on the ML prediction accuracy of Gas Turbines (GTs) performance decay. First a data cleaning technique for robust Linear Regression imputation is proposed based on the Mixed Integer Linear Programming. Then, experiments are conducted to compare the effect of commonly used data cleaning, normalization and reduction techniques on the ML prediction accuracy. Results revealed that the best prediction accuracy of GTs decay, found with the k-Nearest Neighbors ML algorithm, considerately deteriorate when changing the data preparation steps and/or techniques. This study has shown that, for effective CBM application in industry, there is a need to develop a systematic methodology for design and selection of adequate data preparation steps and techniques with the proposed ML algorithms.
Unravelling the Nexus Between CEO Characteristics and Financial Performance in Pakistani Listed Firms

Abdul Rehman, Ji Cheng Jun, Alam Rehman, Muhammad Zeeshan, Muhammad Adeel, Kashif Saleem, Shams Ur Rehman, College of Business Administration, Liaoning Technical University, Liaoning province, XingCheng, 125105, China, Professor at College of Business Administration, Liaoning Technical University, Liaoning province, XingCheng, 125105, China, Faculty of Management Sciences, National University of Modern Languages; Islamabad, Pakistan, College of Business Administration, Liaoning Technical University, Liaoning province, XingCheng, 125105, China, *Corresponding Author, Assistant professor Qurtuba University Science and Information Technology D I khan, Assistant Professor Northern University Nowshera, Pakistan, Email: rehman51jb@gmail.com, jichengjun@126.com, amrehman@numl.edu. pk, abobakarmzk1@gmail.com, Muhammad.adeel@qurtuba.edu. pk, kashifsaleem9212@gmail.com, Shams.mahsud@gmail.com
The Synergistic Combination of Cisplatin and Piperine Induces Apoptosis in MCF-7 Cell Line

Background: Piperine is a natural compound obtained from the Piper nigrum that exhibits anti-proliferative and anti-cancer activity in cancer cell lines. We analyzed the cytotoxic effect of piperine combined with cisplatin compound in the human MCF-7 breast cancer cell line and the underlying mechanism. Methods: The present in vitro study was performed on MCF-7 cell line in Jahrom University of Medical Sciences between, Jahrom, Iran from 2016 to 2017. Cultured MCF-7 cells were seeded into four groups: a control group (untreated group), a group treated with cisplatin, a group treated with piperine and a group treated with cisplatin and piperine. Cell viability was analyzed using the MTT assay method. Flow c-ytometric analysis was investigated for apoptosis. The mRNA and protein expression of the apoptotic regulators p53, Bcl-2, Bax, caspase 3 and caspase 9 were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting analysis. Results: Piperine (20 and 30 μM) in combination with cisplatin (5, 10 and 15 μM) for 24 h synergistically inhibited cell viability of MCF-7 breast cancer cells more than piperine and cisplatin used alone. Synergistic anti-breast cancer activities cisplatin (5 μM) and piperine (20 μM) were via inducing apoptosis. Piperine (20 μM) and cisplatin (5 μM) for 24 h induce apoptosis strongly through reduction of Bcl-2 and increase of caspase 3, p53, caspase 9, and Bax. Conclusion: Piperine in combination with cisplatin could trigger p53-mediated apoptosis more effective than cisplatin alone in MCF-7 breast cancer cells, reducing the toxic dose of cisplatin used in cancer chemotherapy.
Gender, Poverty, and Well-Being in Indonesia: MAMPU Background Assessment

There is an unmistakable correlation between income and women’s status: when countries are richer, women fare better. Women in richer countries have more education, fewer children, healthier and safer pregnancies, more say in politics and policy making, and contribute a greater share of earned income to their households. This correlation is shown in Figure 1, which graphs per capita gross national income (on the horizontal axis) against the UNDP’s gender inequality index (on the vertical axis). 1 The figure makes it clear that Indonesia is no outlier – it lags developed countries in both income and gender equality. In recent years, however, Indonesia has made significant progress in poverty reduction and economic development. At the same time, much needs to be done to meet the government’s stated goal of an 8 percent poverty rate by 2014. Given the stark pattern in Figure 1, this raises an important question: is gender inequity simply an outcome of poverty that will disappear with economic growth, or does gender inequity cause poverty, making it an important barrier to growth? The answer to this question nuanced. As Duflo (2011) points out in her review of the literature, economic growth does seem to reduce gender inequity, but growth is not enough to rectify imbalances between men and women. On the other hand, there is a well established body of evidence demonstrating that empowering women can improve certain economic outcomes, especially in terms of nutrition and child health. But empowering women is not enough to solve all development ills. In other words, gender inequity is both an outcome of poverty and a barrier to economic growth, but the nature
GaitCube: Deep Data Cube Learning for Human Recognition With Millimeter-Wave Radio

Monitoring and identifying gait has recently emerged as a promising solution candidate for unobtrusive human recognition. In order to enable ubiquitous and reliable application, a gait recognition system must be robust to environment changes and easy to use without requiring too much user cooperation and recalibration, while maintaining high accuracy, which is often not satisfied in conventional approaches. In this article, we present <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {GaitCube}$ </tex-math></inline-formula>, a high-accuracy gait recognition system with the minimal training requirement using a single commodity millimeter-wave (mmWave) radio. To reduce the training overhead, we propose <italic>gait data cube</italic>, a novel 3-D joint-feature representation of micro-Doppler and micro-range signatures over time that can comprehensively embody the physical relevant features of one’s gait. With a pipeline of signal processing, <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {GaitCube}$ </tex-math></inline-formula> can automatically detect and segment human walking and effectively extract the <italic>gait data cubes</italic>. We implement and evaluate <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {GaitCube}$ </tex-math></inline-formula> through experiments conducted at six different locations in a typical indoor space with ten subjects over a month, resulting in >50000 gait instances. The results show that <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {GaitCube}$ </tex-math></inline-formula> achieves an accuracy of 96.1% with a single gait cycle using one receive antenna, and the accuracy increases to 98.3% when combining all the receive antennas. Further, it achieves an average recognition accuracy of 79.1% for testing over different times and unseen locations by using only 2 min of training data collected in a single location, enabling a practical and ubiquitous gait-based identification.
Dynamic Response of Parallel Overlapped Tunnel under Seismic Loading by Shaking Table Tests

Potential earthquake-induced damage to overlapped tunnels probably occurs during the operation and maintenance of mountain tunnel engineering, especially in the seismically active zone. This study investigated the dynamic response and the failure characteristics of the parallel overlapped tunnel under seismic loadings by employing shaking table tests. The failure mode of the parallel overlapped tunnels was analyzed through macroscopic test phenomena. The dynamic responses of the surrounding rock and tunnel lining were evaluated by acceleration and dynamic strain, respectively. In particular, wavelet packets were used to investigate the spectrum characteristics of the tunnel structure in depth. The failure process of the model can be divided into three stages. The upper-span and the under-crossing tunnels showed different failure characteristics. Additionally, the lining damage on the outer surface of the tunnel mainly occurred on the right side arch waist and the left side wall, whereas the lining damage on the inner surface of the tunnel mainly appeared on the crown and invert. Wavelet packet energy results showed that the energy characteristic distributions of the upper-span and the under-crossing tunnels were not consistent. Specifically, the energy eigenvalues of the crown of the upper-span tunnel and the invert of the under-crossing tunnel were the largest, which should be considered to be the weak parts in the seismic design.
A Prognostic Model of Gastrointestinal Diffuse Large B Cell Lymphoma

Background The digestive tract is the most common site of extranodal involvement in diffuse large B cell lymphoma (DLBCL) and its prognostic evaluation is different from that of ordinary DLBCL. Currently, for gastrointestinal lymphoma, in addition to the Ann Arbor staging system, the Lugano and the TNM staging systems are commonly used. However, there is no effective prognostic model to identify poor prognosis in patients with localized gastrointestinal diffuse large B cell lymphoma (GI-DLBCL). Material/Methods This study included 82 patients with GI-DLBCL that had a median follow-up of 75 months, and developed a model (HLAMA) with 5 variables: hemoglobin, age, lactate dehydrogenase (LDH), serum albumin, and the maximum intra-abdominal lesion diameter (MIALD). The specific indicators are: HGB <105 g/L (2 points); LDH ≥300 U/L; age ≥75 years, ALB <38 g/L, MIALD ≥4 cm (each scoring 1 point). We also developed a simplified model, which includes only 3 variables (HGB, LDH, and age). Results HLAMA model and the simplified model both demonstrated good ability to predict prognosis of patients with GI-DLBCL (P<0.001), performing better than the IPI score as it could distinguish low-risk groups in relatively elderly patients (60–75 years old). Conclusions This study established a prognostic model for diffuse large B cell lymphoma of the gastrointestinal tract. Both the HLAMA model and its simplified version are similar to the IPI score, but could be considered better as they can provide a simpler and more accurate prognostic assessment in patients with GI-DLBCL. For patients with localized GI-DLBCL, our model could distinguish high-risk patients.
The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders

Training and using modern neural-network based latent-variable generative models (like Variational Autoencoders) often require simultaneously training a generative direction along with an inferential(encoding) direction, which approximates the posterior distribution over the latent variables. Thus, the question arises: how complex does the inferential model need to be, in order to be able to accurately model the posterior distribution of a given generative model? In this paper, we identify an important property of the generative map impacting the required size of the encoder. We show that if the generative map is"strongly invertible"(in a sense we suitably formalize), the inferential model need not be much more complex. Conversely, we prove that there exist non-invertible generative maps, for which the encoding direction needs to be exponentially larger (under standard assumptions in computational complexity). Importantly, we do not require the generative model to be layerwise invertible, which a lot of the related literature assumes and isn't satisfied by many architectures used in practice (e.g. convolution and pooling based networks). Thus, we provide theoretical support for the empirical wisdom that learning deep generative models is harder when data lies on a low-dimensional manifold.
COLLECTION, ISOLATION AND IDENTIFICATION OF PATHOGENIC BACTERIA FROM BLOOD CLINICAL SPECIMENS IN BAGHDAD

One hundred and five of clinical sample were collected from Central Teaching Hospital of paediatric and Medical city / Educational laboratory, from patients (Male, Female and infant) of age range between(≤ 1 day-70 year)during the period from17/10/2016 to 23/1/2017. Out of one hundred and five clinical samples were screened, only seventy isolates were collected in 17 identified as Staphylococcus aureus, 12 identified as Klebsiella pneumonia depending on cultural, microscopical and biochemical characteristics. The remaining isolates were identified as Staphylococcus spp. , E.coli and Acinetobacter baumannii, pseudomonas aeruginosa, Enterobacter spp and Proteus spp. Regarding to the patient gender, it was found that infants had a tendency to get infected more than males and female when 30 (28.57 %) of patients were males, 33 (31.42 %) females and 42 (40%) infant. Moreover, the age group ≤ 1year were most subjected to the infection of bloodstream infection.
Genital Human Papillomavirus Prevalence and Genotyping Among Males in Putuo District of Shanghai, China 2015–2019

Background Reports of human papillomavirus (HPV) infection and genotype distribution in Chinese men are limited, and HPV vaccination has not yet been recommended for men in China. Material/Methods We retrospectively reviewed the prevalence and genotyping of male genital HPV. A total of 1227 male patients (aged 17 to 81 years) attending the dermatology and sexually transmitted disease clinics at Putuo District Center Hospital in Shanghai from 2015 to 2019 were included. Genital exfoliated specimens were obtained for detection and genotyping of 27 HPV types by Luminex-based multiplex assay. Results The prevalence of any HPV was 65.5% (804/1227). The rate of multiple infection was 25.8% (317/1227). The 5 main HPV types were 6 (32.0%), 11 (23.2%), 16 (5.6%), 43 (4.3%), and 59 (4.0%). Among all detected HPV genotypes, 65.5% (875/1336) were 9-valent HPV genotypes. No significant differences were observed in the detection rate of HPV infection over 5 years (P>0.05). Age groups ≤24 years (70.7%) and ≥55 years (72.9%) showed higher infection rates, and significant differences were detected in rates of low-risk HPV infection in different age-stratified groups (P<0.05). Prevalence of HPV infection among patients with warts (74.4%) was significantly higher than that of patients with other clinical characteristics (40.4%) and physical examination (63.6%). Conclusions Our study suggested that more than half of Chinese male patients have detectable HPV infections, and penis-genital and anogenital warts were the most common clinical manifestations. Moreover, the available 9-valent HPV vaccine covers the most frequently observed HPV types among men.
Does Analyst Coverage Promote or Impede Corporate Innovation: Evidence from an Emerging Market

How analyst coverage impacts firms’ innovation remains unknown ex ante. Information hypothesis predicts the positive direction while and performance pressure hypothesis predicts the negative direction. In this paper, we examine this question in the context of China. Our baseline result shows that companies covered by abundant analysts generate more innovation. We validate the robustness of the result in an instrumental regression design. This study sheds light on the determinant of innovation in emerging market.
CORRELATION BETWEEN EXPRESSION OF BCL-2, BAX & P53 AND HISTOLOGICAL ALTERATIONS IN BREAST CANCER OF EGYPTIAN PATIENTS

In Egypt, breast cancer represents approximately 33% of all female cancers and 29% of cancer cases treated at the National Cancer Institute. The present work aimed to determine the differences between normal breast tissue, fibroadenoma and invasive ductal carcinoma tissues using histopathological, histochemical (PAS reaction was used for demonstration of polysaccharides and mercury bromophenol blue method for demonstration of total proteins), immunohistochemical studies (using antibodies directed against ER, PR, p53, Bax and Bcl-2) as well as DNA fragmentation assay. Sixty female breast specimens were obtained from Pathology Department, National Cancer Institute, Cairo University from 2012 to 2014. A noticeable difference in the content of polysaccharides and proteins in the three studied groups (normal, fibroadenoma and invasive ductal carcinoma) was detected. Tumor specimens showed lowest polysaccharides and highest proteins content. Out of 40 invasive ductal carcinoma (IDC) cases, Bcl-2 expressed in 24 cases (60%) and Bax expressed in 16 cases (40%). Also, 30% and 40% of the IDC specimens showed positive ER and PR expression; respectively. Total optical density in IDC specimens was statistically increased due to fragmentation of DNA. It was concluded that normal breast tissues contained the highest polysaccharides contents, while fibroadenoma specimens showed moderate content and the lowest content was in IDC specimens. The total proteins in the invasive ductal carcinoma specimens showed significant increase compared with fibroadenoma and normal specimens. There was significant increase in Bcl-2, Bax and p53 expression in invasive ductal carcinoma. There was a marked decrease in ER expression in both fibroadenoma and invasive ductal carcinoma than normal breast. There was high DNA fragmentation in invasive ductal carcinoma.