Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian analysis of predictive Non-Homogeneous hidden Markov models using Polya-Gamma data augmentation

We consider Non-Homogeneous Hidden Markov Models (NHHMMs) for forecasting univariate time series. We introduce two state NHHMMs where the time series are modeled via different predictive regression models for each state. Also, the time-varying transition probabilities depend on exogenous variables through a logistic function. In a hidden Markov setting, inference for logistic regression coefficients becomes complicated and in some cases impossible due to convergence issues. To address this problem, we use a new latent variable scheme, that utilizes the P\'{o}lya-Gamma class of distributions, introduced by \citet{Po13}. Given an available set of predictors, we allow for model uncertainty regarding the predictors that affect the series both linearly -- in the mean -- and non-linearly -- in the transition matrix. Predictor selection and inference on the model parameters are based on a MCMC scheme with reversible jump steps. Single-step and multiple-steps-ahead predictions are obtained based on the most probable model, median probability model or a Bayesian Model Averaging (BMA) approach. Simulation experiments, as well as an empirical study on real financial data, illustrate the performance of our algorithm in various setups, in terms of mixing properties, model selection and predictive ability.
Attribute-Based Encryption

Attribute-based encryption (ABE) is a type of public key encryption that allows users to encrypt and decrypt messages based on user attributes. For instance, one can encrypt a message to any user satisfying the boolean formula (“crypto conference attendee” AND “PhD student”) OR “IACR member”. One drawback is that encryption and key generation computational costs scale with the complexity of the access policy or number of attributes. In practice, this makes encryption and user key generation a possible bottleneck for some applications. To address this problem, we develop new techniques for ABE that split the computation for these algorithms into two phases: a preparation phase that does the vast majority of the work to encrypt a message or create a secret key before it knows the message or the attribute list/access control policy that will be used (or even the size of the list or policy). A second phase can then rapidly assemble an ABE ciphertext or key when the specifics become known. This concept is sometimes called “online/offline” encryption when only the message is unknown during the preparation phase; we note that the addition of unknown attribute lists and access policies makes ABE significantly more challenging. One motivating application for this technology is mobile devices: the preparation work can be performed while the phone is plugged into a power source, then it can later rapidly perform ABE operations on the move without significantly draining the battery.
Thinking inside the Box: Differential Fault Localization for SDN Control Plane

The control plane of Software-Defined Networking (SDN) is the key component that oversees and manages networks. However, involving design or logic flaws in its policy enforcement and network control is inevitable, which can cause it to behave incorrectly and induce network anomalies. Unfortunately, existing approaches mainly focus on policy verification or fault troubleshooting with little fault localization capability for repairing these flaws in production environments. In this paper, we present FALCON, the first FAult Localization tool for SDN CONtrol plane. We design a novel causal inference mechanism based on differential checking, which symmetrically compares two system behaviors with similar processes and identifies the causality in related code execution paths with concrete contexts to explain why a fault happened in the SDN network. Our main contributions include 1) a lightweight rule-based dynamic tracing mechanism for recording system behaviors of the SDN control plane, 2) a context-aware modeling mechanism for modeling these behaviors, and 3) a differential checking mechanism for localizing controller faults according to formulated symptoms. Our evaluation shows that FALCON is capable of localizing faults in SDN control plane with low overhead on performance.
A phylogenetic analysis of Brycon and Henochilus (Characiformes, Characidae, Bryconinae) based on the mitochondrial gene 16S rRNA

The genus Brycon, the largest subunit of the Bryconinae, has 42 valid species distributed from southern Mexico to the La Plata River in Argentina. Henochilus is a monotypic genus, comprising a single species (H. wheatlandii) found in the upper Rio Doce basin. In the present study, partial sequences of the mitochondrial gene 16S were obtained for fifteen species of Brycon and for Henochilus wheatlandii. The results showed that the genus Brycon is paraphyletic, since Henochilus is the sister-group of B. ferox and B. insignis. The most basal species analyzed were the trans-Andean species B. henni, B. petrosus, and B. chagrensis.
Quantitative Determination of Some Parameters in the Tennant Method and Its Application to Sustainability: A Case Study of the Yarkand River, Xinjiang, China

Analysis of basic eco-environmental water requirements (BEEWRs) along inland rivers characterized by extreme aridity can provide a theoretical basis for sustaining riverine ecosystems stressed by increasingly dry conditions and human activity. In the past, analyzing the ecological base flow as determined by the Tennant method was the predominant method used to calculate the BEEWR of a river. However, some parameter values within this method are determined subjectively, increasing uncertainty in the estimated values. In this paper, quantitative methods for these subjectively determined parameters are proposed and used to analyze the BEEWR of the Yarkand River, Xinjiang, China. The results demonstrate that: (1) the flood and non-flood seasons of a river can be delineated by analyzing the increase rate of monthly runoff as compared to the monthly runoff of the previous month; (2) the ecological base flow standard in the Tennant method can be more quantitatively determined by comparing the BEEWR for each ecological base flow standard to the annual average river loss, where the BEEWR must exceed the annual average river loss; and (3) BEEWRs of other up- and downstream river reaches can be obtained using the formula “BEEWR in the next downstream section equals the BEEWR in the last section minus the river loss between these two sections”.
Near‐Eye Display and Tracking Technologies for Virtual and Augmented Reality

Virtual and augmented reality (VR/AR) are expected to revolutionise entertainment, healthcare, communication and the manufacturing industries among many others. Near‐eye displays are an enabling vessel for VR/AR applications, which have to tackle many challenges related to ergonomics, comfort, visual quality and natural interaction. These challenges are related to the core elements of these near‐eye display hardware and tracking technologies. In this state‐of‐the‐art report, we investigate the background theory of perception and vision as well as the latest advancements in display engineering and tracking technologies. We begin our discussion by describing the basics of light and image formation. Later, we recount principles of visual perception by relating to the human visual system. We provide two structured overviews on state‐of‐the‐art near‐eye display and tracking technologies involved in such near‐eye displays. We conclude by outlining unresolved research questions to inspire the next generation of researchers.
Extraction and molecular detection of viral dsRNA from different infected plants

Extraction of viral double stranded RNA (dsRNA) from infected plants is helpful in identification of the viruses involved in infection. To date, there have been several methods developed to isolate dsRNA; however, type of the plant and virus is determinative in extraction efficiency. In this study we extracted dsRNA from different woody and herbaceous plants through a modified method which reduces the costs and time of extraction procedure. This method is based on different affinity of nucleic acids for the cellulose CF-11 in1X STE (Sodium chloride Tris EDTA) buffer containing 16 % ethanol. There is no phenol treatment or mini columns used in the isolation procedure. Extracted dsRNAs were identified by ribonuclease treatment and RT-PCR (Reverse Transcriptase-Polymerase Chain Reaction). We have applied the procedure on five different hosts representing Amaranthaceae, Vitaceae, Fabaceae and Rosaceae infected with four different viruses representing Secoviridae and Bromoviridae.
Simple Calculation Model of Combined Cycle Unit Under Off-Design Conditions

The modeling of the combined cycle unit is often limited by the lack of characteristic curve and operating data. This paper provided a simple off-design model of combined cycle unit, which was based on theoretical derivation and experimental data. The simulation results showed that the model could reflect the characteristics of gas cycle components and realize the calculation of off-design conditions. The calculation error of heat transfer of HRSG and output of steam turbine under pure coagulation the condition was less than 0.5%.
Analysis of Customer Satisfaction Factors on e-Commerce Payment System Methods in Indonesia

e-Commerce companies are currently competing to make it easier for customers to make transactions with a variety of payment system methods that have been provided and developed. The research aims to find out the factors that influence customer satisfaction in using the payment system method. The variables used in the study are service, comfort, speed, convenience, benefits, active use and security in conducting transactions. The results of the study concluded what factors influence satisfaction to develop a payment system method. The research model and questionnaire use a modified research model of the successful information system model DeLone and McLane and technology acceptance by Tella (2012) and in analyzing the results of the questionnaire, researchers used descriptive statistics and Structural Equation Model (SEM) analysis using AMOS V.26. The results of the management of these data the researchers concluded that there is one variable that is perceived comfort does not significantly affect satisfaction. Results of this study are expected to provide a reference that can be used by digital business people, particularly financial technology or e-commerce companies in improving services in applying the Payment System Method by factors that influence the level of customer satisfaction to maintain customer loyalty to the company.
High-Power Microwave Generation Through Distributed Optical Amplification Into a Photodiode Array on an Open Indium Phosphide Platform

High power handling is crucial to the performance of microwave photonic systems. Taking a fabless research approach, the high-power performance of the photodiodes on an open indium phosphide photonic integration platform is characterized experimentally. For improved power handling two travelling wave structures are presented. Open-ended operation at reduced bandwidth penalty, but with a potential gain in output microwave power of 6 dB is considered, analysing the effect of aperiodic loading and stub reflections. The single photo diode is found to have 1-dB compression of 5 dBm with 20 mA and −8 dBm with 10 mA at 1 GHz and 30 GHz respectively. For a 4-branch distributed photodiode array these numbers are improved to 16 dBm with 58 mA and −1 dBm with 45 mA, again at 1 GHz and 30 GHz respectively. Further the power conversion efficiency of the photodiodes is improved almost by a factor of four from 2.8% to 10.6% at 1 GHz, and the effect of included amplification on the efficiency is analysed. The limitations of the design is analysed through comparison of simulations with measurements and a discussion of the possible improvements and scaling of the method is given.
Investigation Into New Parameter About Dielectric Oil Flow Affecting The Melting Process In EDM 12

Electrical discharge machining (EDM) is one of the most useful machining methods and widely used especially in a mold manufacturing field. EDM is a thermal process that is caused by discharged plasma generated between a tool electrode and a workpiece. The heat flux from plasma melts a part of workpiece [1], and then a portion of melted workpiece is removed from the workpiece body by several effects [2]-[5] such as super heating [4], [5]. In usual EDM, the tool electrode and the workpiece are submerged in dielectric oil during the machining process. The effects of machining conditions on machining characteristics, such as material removal rate, surface roughness, and tool electrode wear, have been well studied so far. However, the influence of dielectric oil between tool electrode and workpiece on machining process has not been fully understood. In this study, focusing on the melting process of EDM, a new parameter, named flow conductance, about the oil flow between tool electrode and workpiece was derived from hydrodynamical point of view to investigate the effect of dielectric oil on the process. As a result, the fact that the flow conductance affects the melt volume of workpiece became clear.
Genetic structure of Platanus mexicana var. mexicana (Platanaceae) in southern Mexico

Platanus mexicana is a typical species of the tropical cloud forest with a complex biogeographical history. High adaptive radiation and interspecific hybridization have been reported for this species, leading to high genetic variability and low differentiation. However, previous studies have shown that populations in the southern part of the species’ distribution in Mexico show different patterns. Therefore, this research aimed at characterizing the genetic structure of three Platanus mexicana populations in southern Mexico. The results revealed significant differences between the populations in Oaxaca, Veracruz and Chiapas (FST = 0.235 ± 0.08), whereas there was evidence of gene flow between the two northwestern populations (Nm = 1.5). Bayesian analysis of allele frequencies showed high selection pressure in Veracruz. Furthermore, the alleles that shifted away from the neutral model were overrepresented in Chiapas. The Oaxaca population had the highest genetic variability values (He = 0.25; P = 68.7), whereas the Chiapas Mexican Journal of Biotechnology 2020, 5(2):120-134 Journal homepage:www.mexjbiotechnol. com ISSN:2448-6590
Two-stage Quantizer with Huffman Coding Based on G . 711 Standard

This paper considers the implementation of Huffman coder for coding of segments of the quantizer based on the G.711 standard. The signal quality obtained with the two-stage quantizer satisfies and overreaches the quality value defined by the G.712 standard, while the implementation of Huffman coder leads to reduction of the average bit rate for 1.25 bit/sample compared to the fixed rate G.711 quantizer. This enables a high quality speech transmission over the channel with less occupancy of its bandwidth. Streszczenie. W artykule analizowano zastosowanie kodera Huffmana do kodowania kwantyzera bazującego na standardzie G.711. Jakość sygnału otrzymana z dwustopniowego kwantyzera jest satysfakcjonująca przewyższając wymagania zdefiniowane przez standard G.712. (Dwustopniowy kwantyzer bazujący na kodowaniu Huffmana pracujący w standardzie G.711).
Innovating access to the nurse-led hepatitis C clinic using co-production

Background Many reasons for missed appointments are given by people who inject drugs and it is suggested that one solution cannot solve this complex issue (Poll et al., 2017). Increasingly, nurses and other health professionals are expected to actively involve patients and service users in developing innovative, effective and accessible services. This project used co-production as the approach to address this challenge. Aims This paper describes how a co-production method was used to develop accessible nurse-led hepatitis C virus services for people who inject drugs. Methods Using research evidence from a study conducted by the lead author as a starting point, a series of co-production workshops were run using creative co-design methods to identify the barriers to engagement with clinics. Potential solutions were then co-produced. Results The solutions included myth-busting posters, peer-support, a mobile clinic van and the offer of incentives and enablers (travel costs or a reward for attendance). Conclusions The service-development project illustrates how, with the right methods, it is possible to successfully engage with hard-to-access groups to co-produce innovative solutions for an important clinical challenge.
Growth and Mortality of Sillago sihama (Forsskål) from Karachi Coast, Pakistan

Length frequency data of silver sillago, Sillago sihama (Forsskål) were collected and measured from the fisherman catches using beach seines and handlines, at random, during 2012 from the Karachi coast of Pakistan. In this study, 1846 fish individuals (male and female combined) were collected ranging from 10 to 24 cm with dominant individuals ranged 12 to 16 cm (total length). Weight ranging was measured from 9 to 110 g. The above length-frequency data were analysed for the estimation of growth and mortality parameters. The power coefficient b of length-weight, the relationship was estimated at 2.9177. The estimated von Bertalanffy growth, function parameters of 25.20 cm (L∞) and 1.00 year -1 (K) were calculated by ELEFAN method equipped on FiSAT computer package. With length-converted catch curve analysis, the total mortality rate (Z) and its 95% confidence interval were 2.42 (2.174-2.669) year. The natural mortality rate (M) was 1.84 year -1 calculated with Pauly’s equation (the annual average seawater temperature was 27°C). Original Research Article Therefore, the fishing mortality rate was F/Z=0.239 which is less than biological reference point (0.5), S. sihama was exploited at managed.
Does HER 2 status influence locoregional failure rates in breast cancer patients treated with mastectomy for pT 1 – 2 pN 0 disease ?

Does HER2 status influence locoregional failure rates in breast cancer patients treated with mastectomy for pT1–2pN0 disease? W. Kwan*, A. J. Al-Tourah, C. Speers, R. Woods, H. Kennecke & I. A. Olivotto Radiation Therapy Program, Fraser Valley Centre; Systemic Therapy Program, Fraser Valley Centre; Breast Cancer Outcomes Unit; Systemic Therapy Program, Vancouver Centre and Radiation Therapy Program, Vancouver Island Centre, BC Cancer Agency, British Columbia, Canada
Theoretical and Experimental Determination of Proppant Crushing Rate and Fracture Conductivity

Proppant is an important material for hydraulic fracturing that impacts the production and production cost of oil and gas wells. The key properties of proppant are crushing rate and fracture conductivity. The most common way to evaluate the key properties of proppant is physical testing, but this method is time-consuming and costly, and it may result in different results under the same experimental conditions. This paper presents a method for calculating proppant crushing rate and fracture conductivity, which are obtained by combining a series of simple and economical laboratory experiments with a significant amount of numerical calculations under various experimental conditions. First, the arrangement of proppant particles was simulated, and the location of particles was determined with the Monte Carlo method, the optimization model, and search algorithm in this process. Second, by mechanical analysis of proppant particles, a mathematical model of force was established, and the singular-value decomposition (SVD) method was used to calculate the force of each particle. Third, the crushing rate of proppant particles was calculated under irregular conditions using mathematical statistics. The Kozeny–Carman equation was improved on to establish a fracture conductivity model. Finally, the average fracture conductivity was calculated on the basis of the simulation results. The calculated fracture conductivity is consistent with the experimental results, which verifies the accuracy of the model.
Determination of bioavailable iron in noncontaminated Slovak soils by flame atomic absorption spectrometry

A method for the extraction of bioavailable iron from soils from various parts of Slovakia using a buffered diethylenetriaminepentaacetic acid (DTPA) solution was utilized. The extractant consists of 0.005 mol dm−3 DTPA, 0.1 mol dm−3 CaCl2, and 0.1 mol dm−3 triethanolamine with pH of 7.3. DTPA was selected as the chelating agent because it can effectively extract micronutrient metal, iron. Distribution of iron in the horizons of various types of soils with respect to bioavailable iron was evaluated. The bioavailable iron in the extracts was determined by flame atomic absorption spectrometry. The calibration standards were prepared in the same surroundings as the extracts. Comparing to the average of 2.7–3.7 % total iron contents in Slovak soils, the available amounts of iron represent in average only very small amounts, approximately 0.3 % in comparison to total amounts.
Ensemble of ARIMA: combining parametric and bootstrapping technique for traffic flow prediction

There are numerous studies on traffic volume prediction, using either non-parametric or parametric methods. The main shortcoming of parametric methods is low prediction accuracy. Non-parametric methods show higher prediction accuracy, but they are criticised due to lack of support from theory. The innovation of this paper is to combine bootstrap with the conventional parametric ARIMA model with the aim of improving prediction accuracy while maintaining theory adherence. The outcome of this process is an ensemble of ARIMA models (E-ARIMA) where each model is developed using a random subsample of data. The validity of the proposed model is examined by comparing E-ARIMA with ARIMA and Long Short-Term Memory (LSTM) as representatives for parametric and non-parametric methods respectively. One year of traffic count data on four main arterial roads in Sydney, Australia is used for calibration and validation purposes. The results suggest that creating an ensemble of models improves prediction accuracy.
NO NO Roseland ওেয় ^ Pullman , এবং Riverdale আট ক $ াথিলক প $ ািরশ সম ` েয়

In this research we propose to use ontology to improve the performance of an EBMT system for low-resource language pair. The EBMT architecture use chunk-string templates (CSTs) and unknown word translation mechanism. CSTs consist of a chunk in source-language, a string in target-language, and word alignment in-formation. For unknown word translation, we used WordNet hypernym tree and English-Bengali dictionary. CSTs improved the wide-coverage by 57 points and quality by 48.81 points in human evaluation. Currently 64.29% of the test-set translations by the system were acceptable. The combined solutions of CSTs and unknown words generated 67.85% acceptable translations from the test-set. Un-known words mechanism improved translation quality by 3.56 points in human evaluation.