Miracle-dz/UniFAR-FTUs huggingface dataset:
A Semi-Parametric Bayesian Generalized Least Squares Estimator

In this paper we propose a semi-parametric Bayesian Generalized Least Squares estimator. In a generic setting where each error is a vector, the parametric Generalized Least Square estimator maintains the assumption that each error vector has the same distributional parameters. In reality, however, errors are likely to be heterogeneous regarding their distributions. To cope with such heterogeneity, a Dirichlet process prior is introduced for the distributional parameters of the errors, leading to the error distribution being a mixture of a variable number of normal distributions. Our method let the number of normal components be data driven. Semi-parametric Bayesian estimators for two specific cases are then presented: the Seemingly Unrelated Regression for equation systems and the Random Effects Model for panel data. We design a series of simulation experiments to explore the performance of our estimators. The results demonstrate that our estimators obtain smaller posterior standard deviations and mean squared errors than the Bayesian estimators using a parametric mixture of normal distributions or a normal distribution. We then apply our semi-parametric Bayesian estimators for equation systems and panel data models to empirical data.
eMentor: An Informal, Semi-Structured Online Intercollegiate Mentorship Experience

Mentorship is perceived as vital to attracting, training, and retaining nursing faculty members and to maintaining high-quality education programs (Nowell, White, Mrklas & Norris, 2015). Access to faculty mentors is a critical issue in nurse practitioner programs.  For the mentor, giving back to the profession is an enormous benefit while availability of time and developing a successful experience can be challenging.
ASSESSMENT OF SEASONAL AND ALTITUDINAL VARIATION IN POPULATION DENSITY AND BIOMASS OF BEETLES (COLEOPTERA) IN NANDA DEVI BIOSPHERE RESERVE, WESTERN HIMALAYA, INDIA

Insects are among the creator of the biological foundation for all terrestrial ecosystems. They cycle nutrients, pollinate plants, disperse seeds, and maintain soil structure, fertility, biological controller, and major food source for other animals (Majer 1987). Soil insects are essential for the maintenance of healthy and productive agricultural ecosystems (Cock et al. 2012). Among the insects, the Coleoptera (beetles and weevils) is the largest order in the class Insecta. It's estimated that about 15,500 species belonging to 104 families of 03 suborders of Coleoptera are recorded from India, constitutes about 5% of the world Coleoptera fauna (Sengupta & Pal 1998). The economic importances of various beetles are well known. More than 300 species in India are noted as pests of field crops, forest trees, timbers, and various stored products. Beetles have considerable ecological and biological importance in natural control of many crop pests and decomposition of plant and animal debris. Scavengers and wood-boring beetles are useful as decomposers and recyclers of organic nutrients. Predatory species, such as lady beetles, are important biological control agents of aphids and scale insects.
Evaluating the fidelity of a novel part-task trainer for emergency front of neck access training

In 2015, the British Difficult Airway Society (DAS) revised its guidelines for managing an unanticipated difficult airway, recommending surgical cricothyroidotomy as the new standard emergency front of neck access (FONA). 1 In the UK, the 4th National Audit Project of the Royal College of Anaesthetists recommended anaesthetists to undergo frequent FONA training using simulation.2 Fidelity in simulation has physical, functional and psychological components,3 and we feel that the Crico-Trainer (Frova; VMB Medical, Newcastle, UK), currently used in our department, could be improved. A prestudy survey (n=15) of attending (consultant) anaesthetists identified ‘ideal manikin qualities’. This confirmed that important features were high-fidelity feel of: tissue (80.0%), scalpel incision (86.7%) and surface (80.0%). The ability to intubate (60.0%), haemorrhage (46.7%) and mimic an impalpable cricothyroid membrane (46.7%) were also considered important. The Frova was deemed to lack realistic tissue planes (80.0%), component feel (66.7%) and haemorrhage (46.7%). The aim of this study was to develop and evaluate our own trainer, focusing on improved fidelity. We designed and constructed our part-task trainer (figure 1) using a wooden base, proprietary reusable plastic ‘larynx/trachea’ and a novel disposable ‘neck tissue’ prosthesis, which feels realistic and bleeds when cut. The neck was fabricated from a viscoelastic polymer (Akton; Action Products, Leek, UK) coated in acrylic paint (Daler-Rowney, Bracknell, UK) and …
Sentiment Analysis and Polarity Detection of Tweets through R Programming on Bengaluru Traffic, India

: This paper aims to retrieve data from twitter and pre-process the data into comprehensive particulars, and analyze the sentiments of tweets via providing scores to the tweets obtained on Bengaluru traffic with the help of opinion lexicon English, which has both negative and positive words, where these words are compared with collected data from the twitter. Simple naïve bayes algorithm is used to carry out experiment in r studio. Twitter users sentiments on the Bengaluru traffic is presented as the result through the R studio plots.
BREEDING AND GENETICS SYMPOSIUM: Breeding for resilience to heat stress effects in dairy ruminants. A comprehensive review1

Selection for heat tolerant (HT) animals in dairy production has been so far linked to estimation of declines in production using milk recording and meteorological information on the day of control using reaction norms. Results from these models show that there is a reasonable amount of genetic variability in the individual response to high heat loads, which makes feasible selection of HT animals at low costs. However, the antagonistic relationship between level of production and response to heat stress (HS) implies that selection for HT animals under this approach must be done with caution so that productivity is not damaged. Decomposition of the genetic variability in principal components (PC) can provide selection criteria independent of milk production level although biological interpretation of PC is difficult. Moreover, given that response to heat stress for each animal is estimated with very sparse information collected under different physiological and management circumstances, biased (normally underestimation) and lack of accuracy may be expected. Alternative phenotypic characterization of HT can come from the use of physiological traits, which have also shown moderate heritability. However, costs of a large scale implementation based on physiological characteristics has precluded its use. Another alternative is the use of biomarkers that define heat tolerance. A review of biomarkers of HS from more recent studies is provided. Of particular interest are milk biomarkers, which together with infrared spectra prediction equations can provide useful tools for genetic selection. In the ‘omics’ era, genomics, transcriptomics, proteomics and metabolomics have been already used to detect genes affecting HT. A review of findings in these areas is also provided. Except for the slick hair gene, there are no other genes for which variants have been clearly associated with HT. However, integration of omics information could help in pointing at knots of the HS control network and, in the end, to a panel of markers to be used in the selection of HT animals. Overall, HT is a complex phenomenon that requires integration of fine phenotypes and omics information to provide accurate tools for selection without damaging productivity. Technological developments to make on-farm implementation feasible and with greater insight into the key biomarkers and genes involved in HT are needed.
A RTIFICIAL N EURAL N ETWORK FOR E NERGETIC D YNAMIC C IRCUIT S IMULIZATIONS

— This paper provides the An Artificial Neural Network (ANN) is mathematical model that is presented for dynamic circuit Simulizations model. The ANN is used to learn modelling for dynamic circuit’s simulation, in modelling for circuit simulation, there are major applications that need to be distinguished because of their different requirements. The designs of artificial neural network model are constructed with layers of units
VoIP Security Threat Taxonomy and Privacy

-The number of users of VoIP services is increasingevery year. Consequently, VoIP systems get more attractive for attackers. This paper describes the implementation of a low interaction honeypot for monitoring illegal activities in VoIP environments. The honeypot operated during 92 days and collected 3502 events related to the SIP protocol. The analysis of the results allows understanding the modus operandi of the attacks targeted to VoIP infrastructures. These results may be used to improve defence mechanisms such as firewalls and intrusion detection systems.
Performance Analysis of Acknowledgement based Vector Routing and Epidemic Techniques in infrastructure less Opportunistic Networks

—Opportunistic networks are one of the most increasing evolutions of MANETs. In opportunistic networks the existence of a simultaneous path is not assumed to transmit a message between a source and a destination. In opportunistic networks, path connecting to the mobile nodes never exits, mobile nodes transmit messages with each other when they get opportunity to transmit. Furthermore, nodes are not supposed to possess or acquire any information about the network topology. Routes are built dynamically, while messages are route between the source and the destination, and anyone node can be selected as opportunistic network and node which pass message to neighbor node, only if it is likely to bring the message nearer to the final destination. These features make opportunistic networks a challenging and promising field of research. In this paper we describe approach for routing in opportunistic networks, rendering old traditional routing protocols unable to deliver messages between hosts. Thus, there is a need for a new technique to route through such networks. We propose composite approach which combines concepts of Epidemic Routing and Probabilistic routing techniques together with acknowledgement approach for better delivery. Our results show that composite routing protocol is able to provide better message delivery probability and less message delay.
Parallel Random Motion-Selective Rank Band Based Image Compression Using Hybrid Multi Wavelet Transform

: A Hybrid Multi Wavelet Transform (HMWT) based 2D magnetic resonance (MR) image compression method is proposed. The proposed work presents a novel MR image compression method using Parallel Random Band Selection Method and Motion-Selective Rank Algorithm (PRMRB). In the proposed method, 2D multispectral MR image is spectral decorrelated and temporal decorrelated in the first and second stage of intra and inter band correlation. From this process, the main spectral band component for analysis is selected. These components were given to Parallel Random Band Selection Method, where the registration of sequence of band components is done. In this approach, the spectral bands are treated independently, so there will be many sequences as the number of spectral bands. Motion-Selective Rank Algorithm will generate a multi spectral adaptive sub band wavelet transform filters known multi-directional filters , performs better in terms of motion estimation and compression efficiency, divided in to multi frames of temporal filtering generating HMWT. Throughout the experiments, the proposed novel HMWT shows good performance with the conventional methods.
of Information Compressive

Note that, as Bsp and Bsa are orthonormal, U is unitary, and, in particular, it is invertible with inverse UH. Therefore, if we were to have access to all the measurements 〈f, hj〉, for j ∈ [N ], then we could easily recover x according to x = UHy, where yj = 〈f, hj〉. However, we know that x is s-sparse, so it is plausible that this prior information can be used to recover it by using fewer than N samples. Concretely, let M = {t1, . , tm} ⊂ [N ] be the sampling pattern. We will study the conditions under which x can be recovered by solving the basis pursuit problem
DTCWT Based EEG Biomarker Detection and Classification for Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is the most common progressive neurodegenerative disorder reflecting the degeneration of upper and lower motor neurons. Motor neurons controls the communication between nervous system and muscles of the body. ALS results in the loss of voluntary control over muscular activities along with the inability to breathe and the maximum life expectancy of affected individual will be 3-5 years from the onset of symptoms. But the lifetime of affected people can be extended by early detection of disease. The usual methods for diagnosis are Electromyography (EMG), Nerve Conduction Study (NCS), Magnetic Resonance Imaging (MRI) and Magneto-encephalography (MEG). But some of these methods may erroneously result in neuropathy or myopathy instead of ALS and some do not provide any biomarker. EEG is comparatively least expensive method and it provides biomarker for ALS detection. ALS is always associated with fronto-temporal dementia (FTD). The spectral analysis of EEG will reveal the structural and functional connectivity alterations of the underlying neural network that occurs due to FTD and it can generate potential biomarkers for the early detection of ALS. A novel algorithm has been developed by exploiting the Dual Tree Complex Wavelet Transform (DTCWT) technique and it can overcome the short comes of existing methods for the analysis and feature extraction of EEG. Deterministic biomarkers were obtained from spectral analysis of EEG and the proposed algorithm provided 100% accuracy for all the test datasets.
Quality by Design (QbD)

Quality by Design (QbD) be a concept first outlined by quality expert Joseph M. Juran in publications, most notably Juran on Quality intentionally. Designing for quality and innovation is one among the three universal processes of the Juran Trilogy, during which Juran describes what's required to realize breakthroughs in new products, services, and processes. QbD could be a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and method management supported sound science and quality risk management (ICH Q8(R)) QbD suggests that coming up with and developing formulations and manufacturing processes to make sure predefined product quality. Product quality is ensured by staple testing, drug substance manufacturing, a fixed drug product manufacturing process, in-process material testing, and end product testing. If they meet the manufacturer’s proposed and FDA approved specifications or other standards like USP for drug substance or excipients, they can be used for the manufacturing of the products. The goal of a well-characterized method development effort is to develop a reliable method which will be demonstrated with a high degree of assurance to consistently produce data meeting predefined criteria when operated within defined boundaries. QbD are often applied to the event and evaluation of analytical methods. During method development, all potential factors (the inputs) and every one critical analytical responses (the outputs) are studied to work out the relationships.
Government objectives for broadband

I hope you enjoy our tenth Vodafone Policy Paper. Our aim in these papers is to provide a platform for leading experts to write on issues in public policy that are important to us at Vodafone. These are the people that we listen to, even if we do not always agree with them. These are their views, not ours. We think that they have important things to say that should be of interest to anybody concerned with good public policy.
MicroRNAs in nephrology; new concepts

Key point MicroRNAs play an important role in kidney physiology and pathology. In fact, targeting of abnormal miRNAs in patients is applicable for treatment of related disorders. It means that, administration of antagomirs as miRNA inhibitors could modulate the effect of miRNAs. Therefore it has therapeutic effect, but there is not sufficient data on the safety of these antisense oligonucleotide inhibitors. However, more studies in animal models and more clinical researches in this field are necessary. Citation: Hajian S. MicroRNAs in nephrology; new concepts Immunopathol Persa. 2018;4(1):e07. doi: 10.15171/ipp.2018. 07
Perception and Genuine Knowledge in Wang Yangming

WangYangming (1472-1529) iswidely recognized as themost influential philosopher of theMing dynasty (1368-1644) and one of themost important philosophers in the whole tradition now called “Confucian”. His most celebrated doctrines concern the relationship between knowledge and virtuous action. Wang claimed that his predecessors had held that a person can act virtuously only if they first determine that their action will be virtuous by applying their knowledge of general moral laws to their predicament. Since on this picture, the person’s knowledge of these laws must precede their action (if it is to be virtuous), this view was associated with the slogan that knowledge comes first, and action later. Wang rejected this picture. According to him, virtuous action requires an important cognitive achievement, but the relevant cognitive achievement – which Wang called “genuine knowledge” (zhen zhi真知) – occurs simultaneouslywith virtuous action. Where his predecessors were associated with the slogan that knowledge comes first, Wang described his own viewwith the slogan, the “unity of knowledge and action” (知行合一). According toWang’s position, a person haswhat he called “genuine knowledge”when and only when they are acting virtuously. Wang’s reconceptualization of the connection between knowledge and virtuous action centered on his claim that there was an interesting cognitive achievement – genuine knowledge –which occurredwhen and onlywhen a personwas acting virtuously. To assess this claim – or even understand it – requires an understanding of what Wang meant by genuine knowledge. But if we turn to the literature onWang in European lan-
A Study of Partial Human Papillomavirus Genotyping in Support of the 2019 ASCCP Risk-Based Management Consensus Guidelines

Supplemental digital content is available in the text. Introduction The 2019 ASCCP Risk-Based Management Consensus Guidelines include recommendations for partial human papillomavirus (HPV) genotyping in management of abnormal cervical cancer screening results. The guidelines are based on matching estimates of cervical intraepithelial neoplasia (CIN) 3+ risk to consensus clinical action thresholds. In support of the guidelines, this analysis addresses the risks predicted by individual identification of HPV 16 and HPV 18. Methods Risk estimates were drawn from a subset of women in the Kaiser Permanente Northern California screening program, whose residual cervical specimens were HPV typed as part of the HPV Persistence and Progression study. We calculated risk of CIN 3+ to assess how identification of HPV 16, HPV 18, or 12 other “high-risk” HPV types would influence recommended clinical management of new abnormal screening results, taking into account current cytologic results and recent screening history. Immediate and/or 5-year risks of CIN 3+ were matched to clinical actions identified in the guidelines. Results Identification of HPV 16 at the first visit including HPV testing elevated immediate risk of diagnosing CIN 3+ sufficiently to mandate colposcopic referral even when cytology was Negative for Intraepithelial Lesions or Malignancy and to support a preference for treatment of cytologic high-grade squamous intraepithelial lesion. HPV 18 less clearly elevated CIN 3+ risk. Conclusions Identification of HPV 16 clearly mandated consideration in clinical management of new abnormal screening results. HPV 18 positivity must be considered as a special situation because of established disproportionate risk of invasive cancer. More detailed genotyping and use beyond initial management will be considered in guideline updates.
MicroRNA-322 regulates the growth, chemosensitivity, migration and invasion of breast cancer cells by targeting NF-kB1.

PURPOSE Breast cancer is one of the leading causes of mortality in women across the globe. Herein, the role and therapeutic implications of miR-322 were investigated in breast cancer. METHODS An array of breast cancer cell lines and a normal cell line were used in this study. The expression of miR-322 was determined by quantitative realtime polymerase chain reaction (qRT-PCR). Lipofectamine 2000 reagent was used to perform transfections and MTT assay was used to determine the cell viability. DAPI and annexin V/propidium iodide (PI) assays were used to detect apoptosis. Wound healing and transwell assays were used to monitor cell migration and invasion, respectively. Protein expression was determined by western blot analysis. RESULTS The expression of miR-322 was found to be remarkably suppressed in breast cancer cells. Overexpression of miR-322 led to considerable decline in the proliferation rate and colony formation of the MCF7 breast cancer cells due to induction of apoptosis. The overexpression of miR-322 caused a significant increase in Bax and decrease in Bcl-2 expression and also enhanced the sensitivity of MCF7 cells to cisplatin and decreased their migration and invasive potential. The TargetScan analysis showed NF-kB1 to be the target of miR-322. Additionally, NF-kB1 was remarkably upregulated in all the breast cancer cells. However, miR-322 overexpression resulted in depletion of NF-kB1 expression in MCF7 cells. Silencing of NF-kB1 also decreased the proliferation rate and colony formation of the MCF7 cells. CONCLUSION To conclude, miR-322 may exhibit therapeutic implications in breast cancer treatment and warrants further investigation.