Miracle-dz/UniFAR-FTUs huggingface dataset:
Running Head : MORAL REMINDERS 1 Do Moral Reminders Shape Ethical Behaviour in the Workplace ?

Dishonesty in the workplace is a major concern faced by modern businesses. The present study suggests possibilities to tackle this problem by varying the wording of moral reminders and providing information about the people that are harmed by dishonesty. I tested the effect of written moral reminders worded in either an affirmative (“Please pay here if you took a snack”) or negative (“Please do not forget to pay if you took a snack”) way among 103 German offices that are regularly supplied with snack boxes and where employees purchase snacks by means of an honour system. Additionally, an image of the people harmed by dishonesty was attached to the snack boxes, depicting either a single or a group of individuals. The two types of messages and images were presented in combination as well as separately, resulting in eight betweensubject conditions. For each office I computed a difference score by subtracting the payment percentage of the baseline level (prior to the intervention) from the one following the intervention. Results showed that payment rates tended to increase following the affirmative vs. negative message, and when the image depicted a single vs. group of individuals. This study hints toward important practical and cost-effective implications for businesses to curb dishonesty in the workplace.
Phytochemical Investigation of the Aerial Part of Iraqi Convolvulus arvensis

Convolvulus arvensis is a species of bindweed that is rhizomatous and is in the morning glory family (Convolvulaceae) native to Europe and Asia. The plant is naturally grown in Iraq. The plant was reported to be used in traditional medicine from as early as 1730s. The Aerial parts of Convolvulus arvensis were macerated in 80% ethanol for 6 days. The concentrated extract was partitioned with n-hexane, chloroform, ethyl acetate- and n-butanol successively. The n-hexane and ethyl acetate, fractions were examined for the presence of phytochemicals by thin layer chromatography and high performance liquid chromatography and its steroid and flavonoid contents were investigated. Stigmasterol was isolated from n-hexane fraction and identified by liquid chromatography/mass spectroscopy. Rutin was isolated from the ethyl acetate fraction and identified by liquid chromatography/mass spectroscopy. The aim is to examine the phytochemical constituents of the aerial parts of Convolvulus arvensis, literature survey available so far revealed that there were no studies about the phytochemical investigation for Convolvulus arvensis in Iraq. Different chromatographic techniques like Thin Layer Chromatography and mass spectroscopy were used and the presence of Stigmasterol and Rutin in aerial parts of Convolvulus arvensis was indicated.
Method Development and Validation of Ethambutol in Human Plasma by Using LCMS/MS

The goal of this study was to develop and validate a sensitive, specific and reproducible LC-MS/MS method of Ethambutol in human plasma by using Diphenhydramine hydrochloride as an internal standard. At the same time, method was efficient in analyzing large number of plasma samples obtained for pharmacokinetic, bioavailability or bioequivalence studies after therapeutic doses of Ethambutol. Available online at http://www.urpjournals. com
BOOLEAN LOGIC WITH A FeNEURON

ABSTRACT In this paper an artificial neuron model, FeNeuron, is developed using a ferroelectric capacitor as its basic unit. This model is based on a well-known neuron model called the perceptron. The FeNeuron model uses the phenomenon of the hysteresis loop as an activation function. The Ferroelectric capacitor performs the output of the neuron. Results are shown with the simulation of Boolean functions by the FeNeuron to verify the capabilities of the new model.
Coordinated Protection Scheme Based on Virtual Impedance Control for Loop-Based Microgrids

The presence of the inverter distributed generations in the power systems can bring about incoordination in the protection system performance while enjoying various advantages. In this paper, a suitable solution, independent of relay settings, is presented in order to solve the protection problems of inverter island microgrids with circular arrangement. The presence of distributed inverter generation sources causes a change in the direction and amplitude of the fault current at the microgrid level. This problem is more visible in microgrids with circular arrangement. Therefore, conventional protection schemes that consider a single path and a high fault current level compared to load current may be problematic. An important factor for the proper design of a protective system for microgrids is the contribution of the injecting fault current of the inverter sources. In this paper, a protection strategy based on the inverter control of sources is presented and ordinary overcurrent relays with the same characteristic curve are used. When a short circuit fault occurs in the microgrid, an adaptive current limiting strategy is applied using the virtual impedance loop. In this case, the share of fault current of each source is controlled according to the position of the fault, and sources closer to the fault produce a larger fault current. Therefore, the current passing through the protective equipment is closer to the fault than other equipment in the micro grid. And without the need for making connection between protective equipment, the protective coordination is guaranteed.
STUDIES ON Fusarium oxysporum DISEASES OF SWEET BASIL PLANTS IN ISMAILIA GOVERNORATE

Basil plant is one of the most popular medicinally herbs. Vascular wilt disease caused by Fusarium oxysporum is considering one of the most important diseases on basil in Egypt. Fusarium oxysporum isolates were isolated from all diseased plants showing symptoms of leaf yellowing, stunting, wilted foliage and root rots. All tested isolates of the fungus were found to be pathogenic for basil plants with different degrees. Pathogenicity test with representative isolates indicated that the causal agent is F. oxysporum that causes damping off, wilt, crown and root rot on basil seedlings and plants, where, isolate No.(2) showed more virulent. Under greenhouse conditions and artificial infestation, basil cultivars were differed in their susceptibility to infection by the fungus. Double flowers basil cv. showed more resistant for the disease symptoms, followed by Red leaves cv. Two techniques, vegetative or mycelial compatibility grouping and SDS (PAGE) fingerprinting, were showed differences between Fusarium isolates. Bio-Zeid bioproducts was more effective against Fusarium disease incidence. Also, seed dressing by combining of Vitavax-200 and Rizolex-T showed significant effects in controlling the disease incidence and produced the highest value of healthy plants.
Multi-perspective analysis of D4D fine resolution data

Nowadays, huge amounts of movement data describing changes of spatial positions of discrete mobile objects are collected by means of contemporary tracking technologies such as GPS, RFID, and positions within mobile phone call records. Automatically collected movement data are semantically poor as they basically consist of object identifiers, coordinates in space, and time stamps. Despite that, valuable information about the objects and their movement behavior, as well as about the space and time in which they move can be gained even from such basic movement data by means of analysis [1]. Movement can be viewed as consisting of continuous paths in space and time [2], also called trajectories, or as a composition of various spatial events [3]. Movement data can be aggregated in space, enabling identification of interesting places and studying their activity characteristics, and by time intervals, enabling similarity analysis of situations comprising different time intervals as well as detection of extraordinary events. In this study, we consider the D4D fine resolution call data records (CDR) set of Ivory Coast [4] from multiple perspectives. To set the scope we first evaluate the properties of the data that restrict potentially applicable movement data analysis methods (Section 2). A first analysis step is to study spatio-temporal patterns of calling activities at multiple resolutions of time. To this end we apply spatio-temporal aggregations by antennas, counting number of calls per day (Section 3) and per hour (Section 4). To further identify different kinds of activity neighborhoods and to study their spatial distribution we then characterize antennas by feature vectors of hourly activities within a week and cluster them by similarity of the feature vectors (Section 5). In order to identify peak events – i.e., time intervals during which extraordinarily large number of people made calls in one location simultaneously we compare time series comprising counts of distinct phone users per time interval and antenna (Section 6). This procedure allows us to identify large-scale events that, possibly, happened in the country. We use trajectories of mobile phone subscribers for reconstructing flows between major towns and between activity regions of the country (Section 7). Finally, we make an attempt at semantic interpretation of individuals’ personal places, such as home and work locations, based on these user trajectories (Section 8). We conclude this paper with a short discussion on the results and possible directions for further work.
The USTC-NELSLIP Systems for CHiME-6 Challenge

This technical report describes our submission to the 6th CHiME Challenge. The submitted systems for CHiME-6 cover both the multiple-array speech recognition track and multiple-array diarization and recognition track. For each track, the re-sults corresponded to Category A and Category B are reported. The main technique points of our submission include the deep learning based iterative speech separation, training data augmentation via different versions of the ofﬁcial training data, SNR-based array selection, front-end model fusion, acoustic model fusion. Tested on the development and eval test set, our best system takes the ﬁrst place among all submitted systems in both two tasks of track 1.
Using Non-Pharmaceutical Interventions and High Isolation of Asymptomatic Carriers to Contain the Spread of SARS-CoV-2 in Nursing Homes

Objective. Using a pandemic influenza model modified for COVID-19, this study investigated the degree of control over pre-symptomatic transmission that common non-pharmaceutical interventions (NPIs) would require to reduce the spread in long-term care facilities. Methods. We created a stochastic compartmental SEIR model with Poisson-distributed transition states that compared the effect of R0, common NPIs, and isolation rates of pre-symptomatic carriers primarily on attack rate, peak cases, and timing in a 200-resident nursing home. Model sensitivity was assessed with 1st order Sobol' indices. Results. The most rigorous NPIs decreased the peak number of infections by 4.3 and delayed the peak by 9.7 days in the absence of pre-symptomatic controls. Reductions in attack rate were not likely, even with rigorous application of all defined NPIs, unless pre-symptomatic carriers were identified and isolated at rates exceeding 76%. Attack rate was most sensitive to the pre-symptomatic isolation rate (Sobol' index > 0.7) and secondarily to R0. Conclusions. Common NPIs delayed and reduced epidemic peaks. Reducing attack rates ultimately required efficient isolation of pre-symptomatic cases, including rapid antigen tests on a nearly daily basis. This must be accounted for in testing and contact tracing plans for group living settings.
Assessing Environmental Impacts of Wastewater Treatment Alternatives for Small-Scale Communities

The effluents of wastewater treatment plants in small sized communities of less than 2000 population equivalent (PE), which are discharged into sensitive receiving water environments, must receive “appropriate treatment” according to the EU Urban Wastewater Treatment Directive. Appropriate treatment depends on the quality objectives of the receiving waters as well as the relevant provisions of the member states. In this study, wastewater treatment options, such as vegetated land treatment (VLT), constructed wetlands (CW), and activated sludge treatment (AST), by which effluents are discharged to sensitive and less sensitive areas are evaluated by the life cycle assessment (LCA) approach. For this purpose, data related to energy usage, land requirement, raw material consumption, and released emissions from the life phases were collected with an inventory study and the environmental impacts were assessed by using SimaPro 7.1 LCA software. The results obtained from the assessments were compared with each other, which indicated that for small-scale communities VLT and CW are the most environmentally friendly wastewater treatment option.
Investigation of Droplet Impingement onto Wet Walls Based on Simulation Using Particle Method

In order to investigate the mitigation effect brought by the water film, liquid droplet impingement (LDI) on a wet rigid wall has been simulated using the moving particle semi-implicit (MPS) method. Propagation of the shock waves has been well resolved. High peak pressures that appear at the contact edge in the dry-wall impingement are mitigated or even eliminated by the water film. Furthermore, the magnitude of the average pressure load is reduced by the water film. Effects of the flow conditions, including the thickness of the water film, droplet velocity, droplet diameter, and impinging angle, have been investigated through a parametric study. Based on the parametric study, a correlation for the maximum average pressure is devised as [Ptilde] = f1 + f2 Ṽ, where f1 = a + be−pδ + (1 - a - b)e−qδ and f 2 = ce−pδ + (κ - c)e−qδ . The coefficients are a = 0:240, b = 0:213, c = 3:50, p = 3:70, and q = 36:0. The valid parameter ranges of the correlation are 0 ≤ δ ≤ 1:0 and 1/15 ≤ Ṽ ≤ 1/5. In the oblique impingement, the normal velocity to the wall determines the pressure load. The shear stress is found playing a minor role in the overall mechanical load in the wet-wall impingement.
The Impact of Capital Tax Competition on Public Input Provision in the Presence of Intersectoral Substitutability and Interindustry Factor Mobility

The impact of competition for business capital on local public expenditure has been an important subject of the literature on capital tax competition. That literature argues that when a tax on mobile capital is imposed to finance local public expenditure, Iocal public service levels are set inefficiently low. The reason is that local govemments keep tax rates low to prevent capital outflows. As a result, Iocal tax revenue is insufficient to support efficient levels of pub2) lic services. While most of the studies in the literature focuses on public goods benefiting residents, there are several recent papers which analyze the impact of capital tax competition on the provision of public inputs into the production process. The analysis of public inputs is somewhat complex because such inputs directly increase the productivity of capital. This
Imitation Learning of Neural Spatio-Temporal Point Processes

We present a novel Neural Embedding Spatio-Temporal (NEST) point process model for spatio-temporal discrete event data and develop an efficient imitation learning (a type of reinforcement learning) based approach for model fitting. Despite the rapid development of one-dimensional temporal point processes for discrete event data, the study of spatial-temporal aspects of such data is relatively scarce. Our model captures complex spatio-temporal dependence between discrete events by carefully design a mixture of heterogeneous Gaussian diffusion kernels, whose parameters are parameterized by neural networks. This new kernel is the key that our model can capture intricate spatial dependence patterns and yet still lead to interpretable results as we examine maps of Gaussian diffusion kernel parameters. The imitation learning model fitting for the NEST is more robust than the maximum likelihood estimate. It directly measures the divergence between the empirical distributions between the training data and the model-generated data. Moreover, our imitation learning-based approach enjoys computational efficiency due to the explicit characterization of the reward function related to the likelihood function; furthermore, the likelihood function under our model enjoys tractable expression due to Gaussian kernel parameterization. Experiments based on real data show our method’s good performance relative to the state-of-the-art and the good interpretability of NEST’s result.
Variational quantum solver employing the PDS energy functional

Recently a new class of quantum algorithms that are based on the quantum computation of the connected moment expansion has been reported to find the ground and excited state energies. In particular, the Peeters-Devreese-Soldatov (PDS) formulation is found variational and bearing the potential for further combining with the existing variational quantum infrastructure. Here we find that the PDS formulation can be considered as a new energy functional of which the PDS energy gradient can be employed in a conventional variational quantum solver. In comparison with the usual variational quantum eigensolver (VQE) and the original static PDS approach, this new variational quantum solver offers an effective approach to navigate the dynamics to be free from getting trapped in the local minima that refer to different states, and achieve high accuracy at finding the ground state and its energy through the rotation of the trial wave function of modest quality, thus improves the accuracy and efficiency of the quantum simulation. We demonstrate the performance of the proposed variational quantum solver for toy models, H2 molecule, and strongly correlated planar H4 system in some challenging situations. In all the case studies, the proposed variational quantum approach outperforms the usual VQE and static PDS calculations even at the lowest order. We also discuss the limitations of the proposed approach and its preliminary execution for model Hamiltonian on the NISQ device.
Increased Performance Factor for the Best Clustering Algorithm

 Abstract — Clustering is the process of grouping objects into clusters such that the objects from the same clusters are similar and objects from different clusters are dissimilar. The relationship is often expressed as similarity or dissimilarity measurement and is calculated through distance function. some of the outlier detection techniques are distance based outlier detection distribution based outlier detection density based outlier detection and depth based outlier detection The goal of this paper is the detection of outliers with high accuracy and time efficiency. The methodology discussed here is able to save a large amount of time by selecting a small subset of suspicious transactions for manual inspection which includes most of the erroneous transactions.
Effect of Zinc Supplementation on Urea Hydrolysis in an In Vitro Fermentation Using Rumen Liquor

Rapid hydrolysis of urea in the rumen is the principle cause for urea (ammonia) toxicity. Efforts were directed to retard urea hydrolysis by supplementing zinc at gradual levels viz, 0, 5.0,10.0, 15.0 and 20.0 pprn in one ml solution to 35 mg of urea in one ml solution, and in one ml distilled water with 40 ml buffered rumen liquor in 100 ml syringe fitted with butyl rubber cap and incubated at 39OC. The 35 mg of urea per 43ml of liquor in the in vitro batch culture is equivalent to toxic dose of 100 mg per 100ml of rumen liquor in adult cattle. The incubation was carried out in an anaerobic environment at pH of 6.8. Five replications were conducted twice, resulting in ten replications in each treatment. The residual urea retained in each tube at 0, 1, 2 and 3 hour intervals from the respective aliquot (1 ml) was measured at wavelength of 520 nm. Highest residual urea (P<0.01) was observed in 10 pprn zinc supplementation over the rest of the treatments imposed across incubating hours. The residual urea (mg/dL) at the end of 1,2 and 3 hours of incubation were 28.99f 1.04, 18.33f 0.04 and 15.45+ 0.18 respectively at 10 pprn of zinc compared to 18.95+ 0.38,10.00+ 0.16 and 7.48 + 0.12 in control (0 pprn). The result divulged that 10 pprn zinc was able to effectively retard the urea hydrolysis up to 3 hours, reflecting its effect on the extent of duration. Though the results demonstrated the superiority of 10 pprn zinc treatment over the rest of the treatments in retarding urea hydrolysis, yet another experiment was conducted to further improve the precision at a pH of 7.4 that is considered to be favorable environment for ammonia toxicity. The second trial was conducted following the same procedure except that of the level of zinc supplemented. In this experiment, zinc was supplemented at 0, 7.5, 10.0 and 12.5 pprn to 35 mg of urea with 40 ml of buffered rumen liquor incubated for 0,1,2 and 3 hours. The intial pH was brought to 7.4 by addition of a suitable quantity of soda bicarbonate to simulate a conducive environment for free ammonia production. The results of this experiment further strengthened the previous experiment's results with a significantly (P<0.01) higher residual urea in 10 pprn against the rest of the treatments. Thus it can be concluded that supplementation of 10 pprn zinc delayed the hydrolysis of urea.
Partitioning of o/p-Nitrophenols in the Presence of Hydrotropes in Aqueous Solutions

Abstract Partitioning of o/p-nitrophenols between organic solvents and water in the presence of hydrotropes such as sodium toluene sulfonate, sodium xylene sulfonate, and sodium cumene sulfonate, has been experimentally investigated and modelled in terms of co-aggregation of the hydrotrope and nitrophenols in aqueous solutions. The phenol-hydrotrope and hydrotrope-hydrotrope interactions are characterized by an aggregation model. The experimental data for a series of hydrotropes are further used to predict the partitioning behavior of p-nitrophenol in the presence of sodium butyl benzene sulfonate (Na-NBBS). The aggregation number of NaNBBS, (∼30) obtained from the partitioning data, matches well with that obtained by small angle neutron scattering.
CFD modeling of flow patterns and hydraulics of commercial‐scale sieve trays

A computational fluid dynamics (CFD) model was used to predict the flow patterns and hydraulics of a commercial-scale sieve tray. The model considers the 3-D two-phase flow of gas and liquid in which each phase is treated as an interpenetrating continuum having separate transport equations. Interaction between the two phases occurs via an interphase momentum transfer. For the CFD analysis, the commercial packages CFX5.4 and CFX4.4 of AEA Technology were employed. Velocity distributions, clear liquid height, froth height, and liquid holdup fraction in froth were predicted for various combinations of gas and liquid flow rates. Tray geometry and operating conditions were based on the experimental work that Solari and Bell carried out in a 1.22-m diameter air-water simulator in 1986 at Fractionation Research Inc. Predicted results were found to be in good agreement with the experimental data of these authors. The objective of the work was studying the extent to which CFD can be used as a prediction and design tool for industrial trays. The simulation results are such that CFD can be used as an invaluable tool in tray design and analysis.