Miracle-dz/UniFAR-FTUs huggingface dataset:
KINETIC AND EQUILIBRIUM ISOTHERM OF PESTICIDES (ATRAZINE) ADSORPTION UNTO ACTIVATED CARBON OF CALABASH ( LAGENARIA SICERARIA)

The adsorption of pesticides (Atrazine) from water onto activated carbon prepared from calabash was investigated. The kinetic and equilibrium study was carried out, and data obtained showed that time duration, the concentration of the solution, the dosage of activated carbon and the pH of the solution greatly influenced the adsorption process. The adsorption kinetic study of the pesticide was done using various models. The result best fits pseudo-second-order using the coefficient regression value (0.9922) and intraparticle diffusion. Equilibrium isotherm data were analysed using the Langmuir isotherm model and Freundlich isotherm model. The result of the regression value provided Freundlich isotherm as the best fit to the experimental data, indicating the presence of heterogeneous layer sorption from the regression value of 0.7294. This study suggested that the activated carbon of calabash as a low-cost material is suitable for the adsorption of pesticides from water. Hence it could be applied as a cheap and effective material in removing pesticides in water bodies or industrial waste before disposal.
Some results on reducibilty for unitary groups and local Asai L-functions.

Let Fbe a/? -adic field ofcharacteristic zero and let Fbe the algebraicclosure off. In [20], Shahidi describes the relationship of the poles of certain Langlands L-functions attached to representations of GL(n, F), to the theory of twisted endoscopy. Here we carry out this program for the generalized Asai L-function attached to a representation of GL(n, E), where E/F is a quadratic extension. The problem is equivalent to certain reducibility questions for unitary groups.
Edinburgh Research Explorer The THISL SDR System at TREC-8

This paper describes the participation of the THISL group at the TREC-8 Spoken Document Retrieval (SDR) track. The THISL SDR system consists of the realtime version of the A BBOT large vocabulary speech recognition system and the THISL IR text retrieval system. The TREC-8 evaluation assessed SDR performance on a corpus of 500 hours of broadcast news material collected over a ﬁve month period. The main test condition involved retrieval of stories deﬁned by manual segmentation of the corpus in which non-news material, such as commercials, were excluded. An optional test condition required required retrieval of the same stories from the unsegmented audio stream. The THISL SDR sys-tem participated at both test conditions. The results show that a system such as THISL can produce respectable information retrieval performance on a realistically-sized corpus of unsegmented audio material.
Numerical Modelling Of a Rectangular Shell-And-Tube Heat Exchanger

- Numerical simulations have been carried out to investigate the turbulent flows and coupled conductive/convective heat transfers in a glycol to water shell-and-tube heat exchanger (one shell, one tube and six passes). The refrigerant (glycol) flows in the tube, and a secondary fluid (water) flows in the shell. The k-ω SST model is used to close the system of equations in the turbulent regime. The present model is first favorably compared and validated against experimental and numerical data available in the literature . It is then extended to consider the shell-and-tube configuration with a rectangular shell. Its thermo-hydraulic performances in the tube side are quantified for Reynolds numbers ranging from 1.03  10³ to 1.47  10 5 . The performance of the heat exchanger is then enhanced by introducing baffles in the shell. The results are finally compared and discussed in terms of three global performance metrics.
Constraint-based Modeling of Smart Grid Services in ICT-Reliant Power Systems

—The future Information and Communication Technology (ICT) infrastructure in distribution grids requires a significant network and computational resources for potentially running all so-called Smart Grid Services (SGS). The insufficient infrastructure may create network and computational conges-tions and resource shortages, which can lead to e.g., delayed critical messages in the power system and thus affect the power system stability. This paper presents a model for the configuration of SGSs with consideration of the underlying ICT infrastructure as a constraint satisfaction problem. This model is studied in a nominal and overvoltage scenario. The resulting over-constrained problem in the second scenario is relaxed by SGS data-rate reduction, SGS migration or SGS distribution. We show that an over-constrained problem can be relaxed with our proposed strategies.
Zooplankton community succession and trophic links during a mesocosm experiment in the coastal upwelling off Callao Bay (Peru)

Abstract. The Humboldt Current Upwelling System (HCS) is the most productive eastern boundary upwelling system (EBUS) in terms of fishery yield on the planet. EBUSs are considered hotspots of climate change with predicted expansion of mesopelagic oxygen minimum zones (OMZs) and related changes in the frequency and intensity of upwelling of nutrient-rich, low-oxygen deep water. To increase our mechanistic understanding of how upwelling impacts plankton communities and trophic links, we investigated mesozooplankton community succession and gut fluorescence, fatty acid and elemental compositions (C, N, O, P), and stable isotope (δ13C, δ15N) ratios of dominant mesozooplankton and microzooplankton representatives in a mesocosm setup off Callao (Peru) after simulated upwelling with OMZ water from two different locations and different N:P signatures (moderate and extreme treatments). An oxycline between 5 and 15 m with hypoxic conditions (<50 µmol L−1) below ∼10 m persisted in the mesocosms throughout the experiment. No treatment effects were determined for the measured parameters, but differences in nutrient concentrations established through OMZ water additions were only minor. Copepods and polychaete larvae dominated in terms of abundance and biomass. Development and reproduction of the dominant copepod genera Paracalanus sp. , Hemicyclops sp. , Acartia sp. , and Oncaea sp. were hindered as evident from accumulation of adult copepodids but largely missing nauplii. Failed hatching of nauplii in the hypoxic bottom layer of the mesocosms and poor nutritional condition of copepods suggested from very low gut fluorescence and fatty acid compositions most likely explain the retarded copepod development. Correlation analysis revealed no particular trophic relations between dominant copepods and phytoplankton groups. Possibly, particulate organic matter with a relatively high C:N ratio was a major diet of copepods. C:N ratios of copepods and polychaetes ranged 4.8–5.8 and 4.2–4.3, respectively. δ15N was comparatively high (∼13 ‰–17 ‰), potentially because the injected OMZ source water was enriched in δ15N as a result of anoxic conditions. Elemental ratios of dinoflagellates deviated strongly from the Redfield ratio. We conclude that opportunistic feeding of copepods may have played an important role in the pelagic food web. Overall, projected changes in the frequency and intensity of upwelling hypoxic waters may make a huge difference for copepod reproduction and may be further enhanced by varying N:P ratios of upwelled OMZ water masses.
CPS-Based Smart Manufacturing: Integration of Sawing and Punching for Aluminum Profile

The work aims to put forward an intelligent manufacturing based on CPS (Cyber-Physical Systems), in order to realize the goal of digitization, networking, high efficiency and fewer people in the integrated sawing and punching production of aluminum profile, improve product quality, and promote the intelligent transformation and upgrading of enterprises. In this paper, firstly by building a smart industry with three-tier architecture: physical devices, network and applications, we proposed a solution based on CPS for aluminum profile production. This solution allows the smart factory to be integrated with other systems, and industrial data information coming from different kinds of industrial control system to be collected together, so as to integrate, exchange and share multi-source heterogeneous data in a closed-loop system. Then, aiming at the sawing machine, we analyze the quality of production process based on data association rule, then we find and control the key factors which cause quality fluctuation, so as to improve the quality in the production process of sawing machine. Then, we use OEE (Overall Equipment Effectiveness) method to calculate the production efficiency and do the experiment. the experimental results are used to verify whether the efficiency of the proposed system and the practicability satisfy the requirements. Finally, the production line capacity efficiency increased by 48.5% and product qualification rate was 99%
Comparison of clinical efficacy and satisfaction of Tiotropium via Respimat® administration with and without a spacer in patient with Chronic Obstructive Pulmonary Disease: A randomized control trial

Objective: This study assessed the delivery of tiotropium via Respimat ® in addition to standard care of treatment among chronic obstructive pulmonary disease (COPD) patients. We study the efficacy, clinical outcome of handling inhaler device, rate of exacerbation and frequency of hospital admission of tiotropium via Respimat® with and without the use of a spacer (AeroChamber ® ). Methods: Randomised, open-label study of COPD patients which was randomised into two groups: spacer or non-spacer groups using tiotropium via Respimat ® . Treatment with their pre-existing inhalers continued. Subjects were assessed at weeks 0, and 8 for forced expiratory volume in 1 second (FEV1), COPD assessment tool (CAT), St. George's Respiratory Questionnaire (SGRQ), and satisfaction questionnaire. Results: We enrolled 96 subjects: 49 in the spacer group and 47 in the non-spacer group. The mean predicted FEV1 in spacer group was 54.48% at baseline and 57.5l% at week 8: p=0.011. In the non-spacer groups, FEV 1 was 54.48% at baseline and 59.20% with a mean increment of 4.72 in both groups: p=0.002. There were no difference of exacerbation rates and hospital admission between both groups. At baseline, mean CAT score in the spacer group was 14.01 which improved to 9.80 (p<0.001) and 14.01 to 8.80 (p<0.001) in the non-spacer group. SGRQ total score reduced in both groups with mean difference of 3.1 (p<0.001) and 3.7: (p<0.001) at weeks 0 to 8. Conclusion: There was no difference between exacerbation and hospital admissions between both groups. There was no difference in FEV1, CAT and SQRQ score using Tiotropium via Respimat ® with or without a spacer. Respimat Ⓡ inhaler technique, FEV1, CAT, SGRQ satisfaction and quality of life.
Robust adaptation of the train speed for energy saving under punctuality and security constraints

: Controlling energy consumption has turned to be an important challenge of the 21 st century and par-ticularly in the railway world since the transport sector constitutes one of the largest consumers. For this reason, the railway companies pay close attention to their energy consumption and seek to reduce it. Recently, this objective has become even more crucial because of the growing demand stemming from the increase of the train frequency, as well as their speed. To achieve this consumption reduction, three levers can be activated: modify the rolling environment, the vehicle characteristics, or its speed profile. The present work focuses on the optimization of the speed profile. This latter must fulfill a number of constraints. First it has to respect the speed limitation on the track to assure the passengers’ security; the involved constraints are called the security constraints . Second the train has to arrive in the train station at a certain time and a specific position with an appropriate speed; these are called the punctuality constraints . Third, the passengers should not be subjected to violent accelerations or jolts; these conditions are regrouped in the comfort constraints . Consequently, the mathematical problem consists in an optimization problem under deterministic non-linear constraints . However, the speed profile is driven by the longitudinal behavior of the train on the track. The optimization supposes thus to construct a precise model to describe the train longitudinal dynamics and its energy consumption. But the mechanical system includes quantities that are more
ORDERED CHOICE PROBABILITIES IN RANDOM UTILITY MODELS

We prove a general identity which states that any element of a tuple (ordered set) can be obtained as an alternating binomial weighted sum of rst elements of some sub-tuples. The identity is then applied within the random utility models framework where any alternative's ordered choice probability (the probability that it has a given rank) is expressed with respect to standard best choice probabilities. The logit and the logsum formulas are extended to their ordered choice counterparts. In a symmetric case, we compare for the probit and the logit, the surplus loss due to the withdrawal of a product with the damage due to the loss of a rank.
influence slip planes in the through

Understanding the ingredients (APIs), in particular insight into the relationships between crystal structure and the thermodynamics of polymorph stability, is vital for the production of more stable drugs and better therapeutics, and for the economics of the pharmaceutical industry in general. In this paper, we report a detailed study of the structure-property relationships among the polymorphs of the model API, Sulfamerazine. Detailed experimental characterization using synchrotron radiation is complemented with computational modelling of the lattice-dynamics and mechanical properties, to study the origin of differences in millability and to investigate the thermodynamics of the phase equilibria. Good agreement is observed between calculated phonon density of states curves and mid-infrared and Raman spectra. The presence of slip planes, evident in the low-frequency lattice vibrations, explains the higher millability of Form I compared to Form II. Energy/volume curves for the three polymorphs, together with the temperature dependence of the thermodynamic free energy computed from the phonon frequencies, explains why Form II converts to Form I at high temperature, whereas Form III is a rare polymorph which is difficult to isolate. Moreover, the combined experimental and theoretical approach employed here should be generally applicable to the study of other systems which exhibit polymorphism, potentially helping to deliver better, more active forms of drugs at lower costs.
Determinants of External Debt Accumulation in Turkey: Evidence from an ARDL Bound Test Approach

External debt is one of the most important problems for underdeveloped countries and emerging markets like Turkey. External debt and its refinancing remain the main challenges for Turkey over the last decades. The purpose of this study is to examine the impact of interest rates, savings, exchange rates and budget deficits on external debt in Turkey through the Autoregressive Distributed Lag (ARDL) bounds testing approach developed by Pesaran, Shin and Smith. The ARDL test has many advantages over the other time series methods. The dependent variable is the ratio of external debt to GDP. The explanatory variables are the exchange rate, interest rate, savings rate and the budget deficit. The results reveal that those variables have significant effect on the accumulation of external debt both in the short and the long runs. To improve this outlook, many structural reforms are required to increase domestic savings and competitiveness and boost potential output.
Tensile strength and dimensional variances in parts manufactured by sla 3D printing

: With the rise of additive manufacturing (AM) technologies, a numerous limitations in conventional manufacturing have been circumvented. Additive manufacturing uses layer-by-layer fabrication of three-dimensional physical models directly from a computer-aided design (CAD) model. The CAD design is transformed into horizontal cross-section layers that are stacked together in physical space until the physical model is completed. This process can be used to directly manufacture tools for injection molding or for any other technology that requires a specific cavity shape to produce a part. This is referred to as Rapid Tooling (RT) and one of the up and coming AM technologies is the resin based stereolithography (SLA). An increasing number of companies are starting to develop desktop machines that utilize this technology and their low cost and high speed changes the design workflow. As a printing technology, SLA creates parts with a smooth surface finish which is ideal for applications such as investment casting for developing jewelry or rapid tooling for injection molding. The development of rapid tools using SLA usually requires more rigid materials which can withstand higher temperatures and stresses and part models that need to have more accurate dimensions in order for a precise part to be produced from that specific tool. Even though models created by SLA have more isotropic characteristics compared to other 3D printing technologies, there are still some variations linked to the process parameters. This paper covers how orientation of the model on the build plate impacts the part accuracy and the tensile strength of the models. The effects of different post-processing procedures after SLA printing are also taken into consideration, since most resins need to be UV cured after 3D printing in order to achieve maximum mechanical strength. This paper gives designers and engineers better understanding on the final properties of the models and the tolerances that have to be taken into consideration when designing parts intended to be manufactured via SLA 3D printing.
Development of Road Transport Logistic Infrastructure and Air Pollution in the Visegrad Group Countries

Road transport is a dominant branch of transport in majority of European countries, particularly in case of freight. Its common application results from availability of transport infrastructure and lower costs compared to other branches of transport. Unfortunately, road transport poses a serious threat to the natural environment due to emission of air pollution and noise. The research has shown that modern logistic transport infrastructure may significantly decrease the pression of transport on the environment. For this reason, the goal of this paper is to determine the level of a dynamic impact of transport infrastructure development on emission of pollution into the air, being a by-product of conventional fuels combustion in road transport in the Visegrad Group countries. The Granger causality relationship between road transport energy consumption, length of roads, number of cars and nitrogen oxides (NOx) emissions derived from road transport activity has been investigated for the Visegrad Group countries in the period of 1991-2015. Moreover, the response of the NO x emissions to changes in road transport infrastructure and energy consumption have also been examined using the impulse response functions and variance decomposition of prediction error in the framework of the vector autoregression models (VAR) methodology.
A comparison of performance between optimal neural networks and classical algorithms in active learning based text classification

Deep learning is often used in text classification tasks for its efficiency and proficiency in modelling nonlinear processes. However, using this type of machine learning takes more time and processing power than using shallow learning algorithms. This study aims to determine if a combination of shallow and deep learning techniques can be used in increasing the classification performance for automated systematic review software. Since deep learning networks excel at finding difficult connections, this study aims to find situations in which they outperform shallow networks. To find these situations, simulations were run on a prepared dataset using different classifiers, switching from shallow to deep networks. While at first results showed no improvement, continued exploratory research provided results that support the hypothesis, as situations were found in which the neural network outperforms the shallow network classifier. All data, code, and commands can be found at the following repositories:
Collaborative Artificial Neural Networks

Taking inspiration from the brain and to some extend human nature, this experiment seeks to reproduce the noticeable improvement tasks experience when performed collaboratively, in the context of working with Artificial Neural Networks. Parts of the brain, when stimulated by different stimuli, work together to reach better decisions and understanding. Groups of individuals having different view points and knowledge can collectively reach better conclusions by virtue of debating and deliberating. These are the processes I have attempted to emulate in my experiments by trying multiple collaboration techniques, networks and problems to find out if multiple agents combined produce noticeably improved results compared to them working separately. The name I coined for systems which combine the results of multiple agents by means of Artificial Neural Networks is the name shared by this thesis: "Collaborative Artificial Neural Networks" (CANN). The methods I came up with and will be presented in this paper are the following three: 1. Simple Collaboration Network (SCN), as the name suggests this is a very simple approach to modeling the system I envisioned; 2. Empathic Collaboration Network (ECN), an improved version of SCN which requires a larger model and more training but obtains better results; 3. Progressive Collaboration Network (PCN), a slightly more complex and ambitious method with which I reached some interesting but mixed initial results. The problems chosen to demonstrate the proof-of-concept were image classification using the ImageNet dataset as well as economic metrics prediction using historic US data. As far as I was able to research, the ideas and concepts presented here haven’t been tried before or there aren’t any easily found publications about them. As such I consider that the ideas presented here, experiments and their results posses a considerable amount of novelty. Key words— Collaborative Artificial Neural Networks, Feedforward Network, SCN, ECN, PCN, ImageNet
THE EFFECTIVENESS OF SIMULATION-BASED LEARNING FOR POLYTECHNIC LEVEL ENGINEERING STUDENTS

Simulation-based learning (SBL) has been widely used and accepted in the industry (think aircraft simulation for example). In education, computer simulations have been used in a wide variety of context, ranging from collaborative learning and skill needs learning to supporting differentiated learning. This study investigates the outcome of using SBL in Machining Technology, an engineering based subject at the polytechnic level by looking at two aspects: student learning and their motivation to learn. It is hypothesised that SBL, which provides learners with interactive experiences, will enhance student learning and motivation in content-heavy subjects. In the study, students in the control group received conventional instructions and workshop practice while the experimental group had conventional instructions, SBL sessions, followed by workshop practice. Both groups receive an equal amount of time on the subject. A post intervention test followed by a survey based on a framework of self-determination theory (SDT) was administered at the end of the study. Although the equal variance t-test indicates that students using SBL as an augmentation tool obtain better results, it was found that the students themselves were mostly exhibiting introjected regulatory behaviour.