Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of a Chemostat Model with Variable Yield Coefficient and Substrate Inhibition: Contois Growth Kinetics

We analyze the steady-state operation of a generalized reactor model that encompasses a continuous flow bioreactor and an idealized continuous flow membrane reactor as limiting cases. The biochemical reaction kinetics is governed by a Contois growth model subject to noncompetitive substrate inhibition with a variable substrate yield coefficient. The steady-state performance of the reactor is predicted and stability of the steady-state solutions as a function of dimensionless residence time reported. Our results identified two cases of practical interest. The first feature corresponds to the case where solutions to both no-washout and washout conditions are bistable. The second feature identifies the parameter region in which periodic solutions can occur when the yield coefficient is not constant. Both these features are often undesirable in practical applications and must be avoided. Scaling of the model equations reveals that both the second-bifurcation parameters are functions of the influent concentration. Our results predict how the reactor behavior varies as a function of influent concentration and identify the range of influent concentrations where the reactor displays neither periodic nor bistable behavior.
An Extensive Literature Review and New Proposal on Optimal Capacitor Placement in Distribution Systems

The main goal of power utilities is to supply reliable and quality power to the end-users and fulfill their total demands at all possible locations. Most of the loads are connected in the distribution systems are inductive. The excessive reactive power demand over the distribution network causes tremendous reactive power losses and changes the voltage profile, hence the system's reliability. Shunt Capacitor Bank (SCB) is widely used in the distribution system for reactive power support, voltage profile, and system performance improvement. But there are some challenges to employ SCB in the distribution network; among them, ensuring the most optimum location and size is a big challenge to get the maximum benefits. Some existing techniques showed better loss reduction but needed either larger SCBs sizes or cause improper node voltage. In this research study, the first section provides an extensive literature review of optimal SCBs placement and sizing. Later on, a new technique called Combinatorial Method has been developed for sizing and sitting of optimal Shunt Capacitors to reduce the distribution loss significantly. The developed method was tested for different case studies using Indian practical 22-bus and IEEE-69-bus network. The results were compared with DSA, Fuzzy GA, and TLBO method and found better distribution feeder loss minimization and voltage profile improvement.
Use of Power Transform Mixing Ratios as Hydrometeor Control Variables for Direct Assimilation of Radar Reflectivity in GSI En3DVar and Tests with Five Convective Storm Cases

When directly assimilating radar data within a variational framework using hydrometeor mixing ratios (q) as control variables (CVq), the gradient of the cost function becomes extremely large when background mixing ratio is close to zero. This significantly slows down minimization convergence and makes the assimilation of radial velocity and other observations ineffective because of the dominance of reflectivity observation term in the cost function gradient. Using logarithmic hydrometeor mixing ratios as control variables (CVlogq) can alleviate the problem but the high nonlinearity of logarithmic transformation can introduce spurious analysis increments into mixing ratios. In this study, power transform of hydrometeors is proposed to form new control variables (CVpq) where the nonlinearity of transformation can be adjusted by tuning exponent or power parameter p. The performance of assimilating radar data using CVpq is compared with those using CVq and CVlogq for the analyses and forecasts of five convective storm cases from spring of 2017. Results show that CVpq with p = 0.4 (CVpq0.4) gives the best reflectivity forecasts in terms of root mean square error and equitable threat score. Furthermore, CVpq0.4 has faster convergence of cost function minimization than CVq and produces less spurious analysis increment than CVlogq. Compared to CVq and CVlogq, CVpq0.4 have better skills of 0-3h composite reflectivity forecasts, and the updraft helicity tracks for the 16 May 2017 Texas and Oklahoma tornado outbreak case are more consistent with observations when using CVpq0.4.
Longitudinal Dispersion Coefficient in Natural Streams in Slovakia

The use of models for simulation of pollution in the stream is encountering the lack of information on the size of the mixing dispersion coefficient, either in the longitudinal or transverse direction. The value of the coefficient can influence the outcome of the calculations or simulations of leaking substances into the flow. Therefore, accurate determination of the values of this coefficient is an important part in solving the problems of pollution transport in the stream. In general, we can use the values of the mixing coefficients referred in the literature (approximate table values), or estimated using approximate empirical relationships, or determine them on the basis of field measurements. In our field investigation, we have focused on the longitudinal dispersion coefficient determination based on experimental saline experiments in various small streams in Slovakia. Model of the pollution dispersion in rivers SIRENIE was used to estimate the dispersion coefficient.
TELOCATE: A Wireless GIS for Crime Control in E-Policing

: - Effective crime control requires accurate prediction for decision making in crime-control planning. In addition, the system should provide for the collection, organization and retrieval of a variety of data. Multiple types of data such as text (criminal data, property data, gang information, case information), graphic (photographs of criminals, pictures of crime scenes) and geographic (crime locations, details of the area) need to be accessed when and where they are needed, especially in time-critical situations. TELOCATE is a system that addresses these problems and provides integrated data and can be accessed by using wireless equipment such as Personal Digital Assistants (PDAs). This paper presents a design and implementation of a system using open source software such as Minnesota Map Server, PHP, PostgreSQL and PostGIS to provide crime information for police and citizens. User evaluations of the system allowed us to study the impact of TELOCATE on performance in crime control.
Practice of Epidemiology Measurement of Telomere Length for Longitudinal Analysis: Implications of Assay Precision

Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Vol. 190, No. 7 https://doi.org/10.1093/aje/kwab025 Advance Access publication: February 10, 2021
Visual Categorization: Basic v Super/Sub-ordinate levels

It is widely accepted in the domain of cognitive sciences that there exist hierarchies in categorization – three levels are often posited: super-ordinate, basic and subordinate. Rosch and her colleagues showed in the 1970s that out of these the basic level is accessed first. Recent studies, however, have pointed to evidence that in a rapid visual processing task super-ordinate categories are accessed most rapidly. In this computational study I simulate the hierarchy of categorization using an object recognition classifier. A bag-of-features model is used for feature extraction from object images, followed by k-means clustering to implement categorization. Results show that super-ordinate categories are indeed favoured over basic and subordinate ones. The role of expertise in determining the categories is also studied.
University of Birmingham Defining and Evaluating Context for Wearable Computers

Deﬁning ‘context’ has proved to be a non-trivial problem for research in context-awareness. In this paper we address two questions: what features of activity are required to deﬁne context? and does the use of context-awareness measurably improve user performance? The ﬁrst question was addressed by a study of everyday activities, using a Photo Diary method to arrive at a set of Context Identiﬁers. We feel that it is important to discover what features of activity are needed in order to describe context. Two user trials were carried out to address the second question. We conclude that the use of context improves user task proﬁciency. r 2004
Escaping the McNamara Fallacy: Towards more Impactful Recommender Systems Research

Recommender systems are among today’s most successful application areas of artificial intelligence. However, in the recommender systems research community, we have fallen prey to a McNamara fallacy to a worrying extent: In the majority of our research efforts, we rely almost exclusively on computational measures such as prediction accuracy, which are easier to make than applying other evaluation methods. However, it remains unclear whether small improvements in terms of such computational measures matter greatly and whether they lead us to better systems in practice. A paradigm shift in terms of our research culture and goals is therefore needed. We can no longer focus exclusively on abstract computational measures but must direct our attention to research questions that are more relevant and have more impact in the real world. In this work, we review the various ways of how recommender systems may create value; how they, positively or negatively, impact consumers, businesses, and the society; and how we can measure the resulting effects. Through our analyses, we identify a number of research gaps and propose ways of broadening and improving our methodology in a way that leads us to more impactful research in our field.
Board Composition, ‘Grey Directors’ and the Incidences of Corporate Failure in the UK

Abstract This study contributes to the debate by empirically examining the characteristics of board prior to failure and their relationships with the incidences of corporate failure. Specifically, this research splits board of directors into inside directors, grey directors and independent outside directors in the analyses. It has been found that the likelihood of corporate failure is negatively related to the percentage of non-executive directors. After categorizing non-executive directors as either independent outside directors or grey directors, there is no significant association between corporate failure and the percentage of independent outside directors. However, the results show that greater grey directors on the board, the lower probability of corporate failure. Additionally, corporate failure and leadership duality is not related. The findings might suggest that the role of grey directors is distinct from both inside directors and independent outside directors, and overemphasizing on the independence of board is not favorable to firm survival.
A Visuo-Haptic Guidance Interface for Mobile Collaborative Robotic Assistant (MOCA)

In this work, we propose a novel visuo-haptic guidance interface to enable mobile collaborative robots to follow human instructions in a way understandable by non-experts. The interface is composed of a haptic admittance module and a human visual tracking module. The haptic guidance enables an individual to guide the robot end-effector in the workspace to reach and grasp arbitrary items. The visual interface, on the other hand, uses a real-time human tracking system and enables autonomous and continuous navigation of the mobile robot towards the human, with the ability to avoid static and dynamic obstacles along its path. To ensure a safer human-robot interaction, the visual tracking goal is set outside of a certain area around the human body, entering which will switch robot behaviour to the haptic mode. The execution of the two modes is achieved by two different controllers, the mobile base admittance controller for the haptic guidance and the robot’s whole-body impedance controller, that enables physically coupled and controllable locomotion and manipulation. The proposed interface is validated experimentally, where a human-guided robot performs the loading and transportation of a heavy object in a cluttered workspace, illustrating the potential of the proposed Follow-Me interface in removing the external loading from the human body in this type of repetitive industrial tasks.
Virus Taxonomy The ICTV Report on Virus Classification and Taxon Nomenclature Nodaviridae Chapter Nodaviridae

The family Nodaviridae includes two genera, Alphanodavirus and Betanodavirus (Table 1.Nodaviridae). The family name derives from the Japanese village of Nodamura where Nodamura virus was first isolated from Culex tritaeniorhynchus mosquitos. Virions are non-enveloped and spherical in shape with icosahedral symmetry (T=3) and diameters ranging from 25–33 nm. The genome consists of two molecules of positive-sense ssRNA: RNA1 and RNA2. The virion capsid consists of 180 protein subunits arranged on a T=3 surface lattice. Alphanodaviruses infect insects whereas betanodaviruses are pathogens of fish.
DESIGN AND ANALYSIS OF BIDIRECTIONAL DC-DC CONVERTER FOR PHOTO VOLTAIC SYSTEM WITH ENERGY STORAGE MUKKALA VENKATA SIVA NAGA RAJU M.Tech, ST.MARY’S GROUP OF INSTITUTIONS GUNTUR CHEBROLU S M GAVASKAR MEDABALIMI Assistant professor, ST.MARY’S GROUP OF INSTITUTIONS GUNTUR CHEBROLU

This paper proposes a new isolated three-port bidirectional dc–dc converter. It contains an inductor– capacitor–inductor (LCL)-resonant circuit to achieve zero-current switching (ZCS) for the main switch. A new isolated three-port bidirectional dc–dc converter for simultaneous power management of multiple energy sources is proposed in this paper. The proposed converter has the advantage of using the least number of switches and soft switching for the main switch, which is realized by using an inductor–capacitor– inductor (LCL)-resonant circuit. The converter is capable of interfacing sources of different voltage– current characteristics with a load and/or a dc micro grid. The proposed converter is constructed for simultaneous power management of a photovoltaic (PV) panel, a rechargeable battery, and a load. Simulation results show that the proposed converter is capable of maximum power point tracking control for the PV panel, when there is solar radiation, and controlling the charge and discharge of the battery, when there is surplus energy and power deficiency with respect to the load, respectively. By using the simulation results we can analyze the proposed method.
Lecture Note on Deep Learning and Quantum Many-Body Computation

This note introduces deep learning from a computational quantum physicist’s perspective. The focus is on deep learning’s impacts to quantum many-body computation, and vice versa. The latest version of the note is at http://wangleiphy.github. io/. Please send comments, suggestions and corrections to the email address in below. ∗ wanglei@iphy.ac. cn
Computational investigation of pressure profiles in lipid bilayers with embedded proteins

The distribution of surface tension within a lipid bilayer, also referred to as the lateral pressure profile, has been the subject of theoretical scrutiny recently due to its potential to radically alter the function of biomedically important membrane proteins. Experimental measurements of the pressure profile are still hard to come by, leaving first-principles all-atom calculations of the profile as an important investigative tool. We describe and validate an efficient implementation of pressure profile calculations in the molecular dynamics package NAMD, capable of distinguishing between internal, bonded and nonbonded contributions as well as those of selected atom groups. The new implementation can also be used in conjunction with Ewald summation for long-range electrostatics, improving the accuracy and reproducibility of the calculated profiles. We then describe results of the calculation of a pressure profile for a simple protein–lipid system consisting of melittin embedded in a DMPC bilayer. While the lateral pressure in the protein–lipid system is nearly the same as that of the bilayer alone, partitioning of the lateral pressure by atom type revealed substantial perturbation of the pressure profile and surface tension in an asymmetric manner.
Thin film nanocomposite embedded with polymethyl methacrylate modified multi-walled carbon nanotubes for CO2 removal

Over the past decades, carbon nanotubes (CNTs) have gained tremendous attention as nanofillers in nanocomposite membranes owing to their potential to improve the physical properties and gas separation performance. In this work, polyamide–ethylene oxide (PA–EO) thin film nanocomposite (TFN) membranes embedded with polymethyl methacrylate (PMMA) grafted multi-walled carbon nanotubes (MWNTs) were successfully fabricated. The TFNs were fabricated via an interfacial polymerization (IP) technique to allow the formation of a very thin selective skin. The effects of the incorporation of nanofiller within the coating and selective thin film layers on the membrane morphologies and gas separation performance have been highlighted. The TFN incorporating milled PMMA-MWNTs within its coating layer showed a 29% increment in CO2 permeance (70.5 gas permeation units (GPU)) with 47% and 9% enhancement in CO2/N2 and CO2/CH4 selectivity respectively compared to its thin film composite counterpart. While the improvement in gas separation performance can be primarily attributed to the presence of highly diffusive channels rendered by the CNTs, PMMA grafting is also believed to play an important role to ensure good nanofiller dispersion and good filler–polymer compatibility. Uncovering the construction of membrane fabrication could pave facile yet versatile ways for the development of effective membranes for greenhouse gas removal.
CS6476 Project: Enhanced Augmented Reality

The goal of this project is to devise a pipeline that can consistently (a) detect a blank flat surface in the scene and (b) project an advertisement image onto it without the use of predefined markers. We experimented with a number of well-known methods in the literature, including Shi-Tomasi corner detector [10], SIFT [5], SURF [1], FAST [8], ORB [9], and AKAZE [3] and found that by combining Shi-Tomasi corner detector and Lucas-Kanade [6] method of estimating optic flow, we can strike a good balance of accuracy and speed. Methods such as SIFT and ORB, though more accurate at times, do not take into account the motion from one frame to the next, thus requires computation of keypoints’ descriptors, which can be a bane to processing time. For example, on a Macbook Pro 13 inch (2018), without writing to an output video, ORB runs at 14 FPS, AKAZE at 2 FPS, while the Shi-Tomasi and Lucas-Kanade combination (hereinafter referred to as the algorithm or our algorithm) runs at a whopping 24 FPS. In the remaining of this report, we will discuss in more details about our algorithm, how it works and what are the results of applying this algorithm to different footage.
Heart ATP-Binding Cassette Protein A1 and G1, Peroxisome Proliferator- Activated Receptor-α and Liver X Receptors Genes Expression in Response to Intensive Treadmill Running and Red Crataegus pentaegyna (Sorkh valik) in Male Rats

extraction. Statistical analysis was performed using a two way ANOVA, and significance was accepted at P < 0.05. Results: Changes in ABCA1 and ABCG1 gene expression were not significant and a non-significant increase in PPAR- α and LXR genes expression were found in the trained rats and Sorkh valik-control group than in the control group. Conclusions: The findings indicate that training and Sorkh valik extraction solely were able to increase non-significantly all selected genes expression in rat heart. It seems that exercise with Sorkh valik supplementation trend to decrease mentioned genes expression.
Analysis of Pesticide Residues in Tomatoes and French Beans from Murang’a and Kiambu Counties, Kenya

Poor Pesticide-handling practices during production of tomatoes and French beans pose adverse health and environmental effects. This study was conducted to determine the concentrations of pesticide residues in tomatoes and French beans grown and sold in Murang’a and Kiambu counties, Kenya. Samples were collected in farms and markets during the wet and dry seasons. Pesticide residues were extracted using the QuEChERS method and quantified using GC-MS/MS and LC-MS/MS. The recoveries of pesticides from spiked samples were within the acceptable range (70-120%) for quantitative pesticide residue methods. The concentration range of pesticides residues in tomatoes were: profenofos, <LOQ to 0.18 mg/Kg; omethoate, <LOQ to 0.03 mg/Kg; indoxacarb, <LOQ to 0.05 mg/Kg; chlorantraniliprole <LOQ to 0.11 mg/Kg; spirotetramat <LOQ to 0.01 mg/Kg; and metalaxyl < LOQ to 0.02 mg/Kg. The concentration range of pesticides residues in French beans were: imidacloprid <LOQ to 0.29 mg/Kg; chlorantraniliprole <LOQ to 0.37 mg/Kg; spirotetramat <LOQ to 0.01 mg/Kg; indoxacarb <LOQ to 0.05 mg/Kg; and metalaxyl <LOQ to 0.02 mg/Kg. The concentrations of pesticide residues in tomatoes and French beans were below the Maximum Residue Levels set by the Joint FAO/WHO Food Standards Programme and the European Union except for concentrations of omethoate in tomatoes, which were higher in 29% of analyzed samples. The presence of omethoate in tomatoes, whose use in vegetables is banned, suggests poor pesticide handling practices by some tomato farmers in the two counties.
Right-Censored Nonparametric Regression: A Comparative Simulation Study

This paper introduces the operating of the selection criteria for right-censored nonparametric regression using smoothing spline. In order to transform the response variable into a variable that contains the right-censorship, we used the KaplanMeier weights proposed by [1], and [2]. The major problem in smoothing spline method is to determine a smoothing parameter to obtain nonparametric estimates of the regression function. In this study, the mentioned parameter is chosen based on censored data by means of the criteria such as improved Akaike information criterion (AICc), Bayesian (or Schwarz) information criterion (BIC) and generalized crossvalidation (GCV). For this purpose, a Monte-Carlo simulation study is carried out to illustrate which selection criterion gives the best estimation for censored data.
Growth stimulation and enhanced invertase activity induced by salicylic acid in tea cuttings (Camellia sinensis L

Salicylic acid(SA) acts as an endogenous signal for the induction of systemic acquired resistance (SAR) in plants infected by pathogens. The application of SA promotes the SAR process and consequently could interfere on the growth of plants with such an increased resistance. The influence of SA application on the growth and invertase activity of one year old tea cuttings (Camellia sinensis L.) was investigated. Tea cuttings, grown on compost in a growth chamber, were sprinkled with Hoagland medium of SA every five days. After 28 days of growth, leaves were harvested and used for growth and total soluble sugar (TSS) measurements. Leaf invertase activity was measured spectrophotometrically . The data were analysed statistically. Very low dose of SA considerably enhanced the growth and carbohydrate metabolism of tea cuttings. Addition of 50 μM SA produced the most remarkable effects. There was a 2 fold significant increase (p<0.05) in leaf area, leaf fresh weight and leaf dry weight. Leaf TSS were also double by this treatment. Invertase activity in SA treated cuttings was higher than in control with a significant increase (x 3.4) for 50 μM SA (p<0.05). These results suggest that it will be profitable to experiment very low dose SA application at the field culture level for the improvement of tea cuttings’ plantation.