Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic Understanding and the Rational Design of Sinter-Resistant Heterogeneous Catalysts

The activity and selectivity of heterogeneous catalysts are strong functions of the morphology of the catalytic active phase, which governs both the density and type of active sites. To realize materials with the desired reactivity, cutting-edge catalysts are often the product of novel synthetic strategies and advanced computational studies. Combining these approaches allows for the prediction and fabrication of active motifs in a directed manner. However, catalyst active phases are ordinarily in the nanometer or atomic regime, and small morphological changes can result in large differences in catalytic properties. Given painstaking efforts to design and fabricate active materials at the nanoscale, it is essential that these engineered structures and superior catalytic properties are preserved during working conditions. The stability of a highly active catalyst morphology is crucial for long-term, sustained activity, especially for industrial applications. Unfortunately, catalyst sintering, or processes i.
Trusting behavior and depressive symptoms

Abstract Economic games have been shown to be an effective way to assess interpersonal impairment, which is associated with depression. Because trust is a key element in all social interaction, we tested whether trust, assessed with an economic game, is negatively associated with depressive symptoms. Participants (n = 163) took part in a distrust game and completed the Patient Health Questionnaire (PHQ-9), the Depression Anxiety and Stress Scales (DASS), and demographic questions. Multiple regression analysis estimated the relationship between the outcome of the distrust game and the cut-off scores of the PHQ-9, those of the DASS depression scale, and a depressive dichotomous score created using the cut-off scores from the PHQ-9 and the DASS depression subscale. The cut-off scores of the PHQ-9, the DASS depression scale, and the depressive dichotomous score separately predicted trust. The distrust game could be useful in further research into underlying mechanisms in interpersonal impairments and deficits in decision making in depression, which could lead to the development of interventions aimed at reducing the interpersonal impairments often associated with mental health.
Integrating emotive competencies in public affairs education

ABSTRACT Emotion is the “how” of NASPAA competencies related to leading and managing in a culturally-conscious manner. In this article, we describe the role of emotion in public service and we detail the mechanism by which emotion fosters a collective mind-set for effective public service leadership and cultural literacy. We indicate specifically where emotive competencies could be integrated into the foundational skills demanded of all graduates of accredited programs. We further argue that they should be integrated into MPA core curricula. This normative argument captures the ethics of emotional labor: To graduate students from MPA programs without emotive capacities is to leave them poorly equipped for the practice of public service and to do so would be unethical. To demonstrate what is possible in public affairs education, we turn to an example from the Government of India Civil Service Competency Dictionary for a framework of emotive competencies in human resource management.
Prediction of Stock Prices Using Statistical and Machine Learning Models: A Comparative Analysis

With the advent of machine learning, numerous approaches have been proposed to forecast stock prices. Various models have been developed to date such as Recurrent Neural Networks, Long Short-Term Memory, Convolutional Neural Network sliding window, etc., but were not accurate enough. Here, the aim is to predict the price of a stock and compare the results obtained using three major algorithms namely Kalman filters, XGBoost and ARIMA. Kalman filters are recursive and use a feedback mechanism to perform error correction. This correction makes them best suited for making accurate predictions as they can factor in the market volatility, whereas XGBoost is a promising technique for datasets that are nonlinear and can gather knowledge by detecting patterns and relationships in the data. XGBoost is also capable of capturing the time dependency of features efficiently. ARIMA refers to an Auto Regressive Integrated Moving Average model that has become very popular in recent times. It is mostly used on time series data and works by eliminating its stationarity. Finally, a hybrid model combining Kalman filters and XGBoostis discussed and a comparison of the results of each of the four models, are made to provide a better clarity for making investments by forecasting the price of a stock.
Implant‐bone‐interface: Reviewing the impact of titanium surface modifications on osteogenic processes in vitro and in vivo

Abstract Titanium is commonly and successfully used in dental and orthopedic implants. However, patients still have to face the risk of implant failure due to various reasons, such as implant loosening or infection. The risk of implant loosening can be countered by optimizing the osteointegration capacity of implant materials. Implant surface modifications for structuring, roughening and biological activation in favor for osteogenic differentiation have been vastly studied. A key factor for a successful stable long‐term integration is the initial cellular response to the implant material. Hence, cell–material interactions, which are dependent on the surface parameters, need to be considered in the implant design. Therefore, this review starts with an introduction to the basics of cell–material interactions as well as common surface modification techniques. Afterwards, recent research on the impact of osteogenic processes in vitro and vivo provoked by various surface modifications is reviewed and discussed, in order to give an update on currently applied and developing implant modification techniques for enhancing osteointegration.
Competing frames on social media: analysis of English and Farsi tweets on Iran plane crash

ABSTRACT This study conducted content analysis and word co-occurrence network analysis of tweets about the Ukraine plane crash in Iran in 2020 to analyse differences between English tweets and Farsi tweets in framing and discussing the major international event. Results from our computational analysis and human coding of the tweets show important differences and similarities between English tweets and Farsi tweets in terms of prominent frames and frequently co-occurring word pairs, and topic areas discussed. People offered different diagnostic and prognostic perspectives on the crash. In both English and Farsi tweets, ‘UkrainePlaneCrash’ was frequently paired with ‘Iran’ and ‘Ukraine’. The most prominent frame in both English and Farsi tweets was diagnostic frame. In terms of collection action frame, there were statistically significant differences between English and Farsi tweets. While the second most prominent frame in Farsi tweets was motivational frame, prognostic frame was the second most prominent frame in English tweets.
Different water and nitrogen fertilizer rates effects on growth and development of spinach

ABSTRACT Water and nitrogen (N) nutrition are two key factors affecting nutrient absorption growth and biomass production of vegetables. However, less information is available to the interaction between water utilization and nitrogen use efficiency in vegetable production. In this study, a combination of three water levels and three nitrogen fertilizer rates was applied to optimize water and nitrogen application in field experiments. Plant traits, biomass production, and allocation were determined. The fresh and dry weight of leaf, stem, and root significantly decreased when irrigation water was short. Total aboveground biomass decreased in response to deficit irrigation. Leaf chlorophyll concentrations decreased when nitrogen fertilizer reduced. The leaf area was highest when spinach was grown under 170 kg ha−1 of nitrogen fertilizer and 70–80% of field capacity. These results suggested that spinach could be planted with good growth and quality by implementing effective water and nitrogen managements.
Serum Neutrophil Gelatinase-Associated Lipocalin and Iron Status in Predialysis Chronic Kidney Disease at Zagazig University

Background: The burden of chronic kidney disease (CKD) is substantial. Anemia is a common feature of CKD. Objective: The aim was to predict about iron status by serum neutrophil gelatinase-associated lipocalin (NGAL) levels and role of serum NGAL as biomarker of iron deficiency in CKD patients. Patients and Methods: A prospective, case-control comparative study that was conducted at Nephrology Outpatient Clinic and Internal Medicine Department, Zagazig University Hospitals. Seventy two participants were divided into two groups: Group I included 36 participants with no chronic kidney disease and group II that included 36 chronic kidney disease patients. Laboratory investigations included iron parameters and serum NGAL levels were measured Results: S. Iron, TIBC, S. Ferritin and calculated T. sat” were statistically analyzed and showed that there was a statistical significant difference between the two studied groups. NGAL level was higher in CKD group than in the non-CKD group. A significant positive correlation between serum NGAL and T sat & serum ferritin and there was a significant negative correlation between NGAL and eGFR, HB and serum iron. Conclusion: Patients had significantly higher NGAL levels when compared to controls and this means that it had an important role in iron metabolism in those patients. There was statistically significant direct correlation between serum NGAL levels and serum ferritin levels and T. sat and inverse correlation with iron. Serum NGAL could be a good biomarker for iron status in CKD patients but not better than the ordinary used methods “serum ferritin and T. sat”.
A fresh start in ambersnail (Gastropoda: Succineidae) taxonomy: finding a foothold using a widespread species of Oxyloma

The ambersnails (Succineidae), found nearly worldwide, are considered a very challenging group to classify and identify with even genus-level identifications requiring dissection. In this study, we use mitochondrial and nuclear DNA markers, shell morphometrics, and anatomical dissection to examine fresh material collected from the type localities of two nominal species in Oxyloma (Neoxyloma). We conclude from these evidence that Oxyloma salleanum (L. Pfeiffer, 1850) and Oxyloma effusum (L. Pfeiffer, 1853) are conspecific, and accordingly reduce O. effusum to the status of junior synonymy. We present a redescription of O. salleanum.
A DEA Approach towards to the Evaluation of IoT Applications in Intelligent Ports

Driven by the development of world ' s technology, the concept of Internet of things (IoT) not only promotes the leapfrog development of global information technology, but also makes computer and communication technology realize further perfection. IoT technology enables the global sharing of network resources and the overall perception of information to achieve the goal of “ interconnection of all things together, ” which is the third wave of world ' s information industry development after the computer and Internet. Recently, the rapid expansion of IoT technology has made many conventional industries more intelligent. With the accelerated expansion of port traf ﬁ c, many conventional ports are facing the transformation of operation mode. They urgently need to improve the service quality of infrastructure, comprehensive processing capacity for information and the optimized allocation of resources of their related logistics parks. Therefore, from the aspects of intelligent supervision, intelligent service and technology security, this study constructs the data envelopment analysis (DEA) framework of factors in ﬂ uencing the intelligent transformation of international commercial ports with the application of IoT technology. This study hopes to help port managers to improve the operational performance through an intelligent cloud connection, and to transform conventional port to intelligent commercial port 4.0 as soon as possible.
Attitude Decoupling Control of Semifloating Space Robots Using Time-Delay Estimation and Supertwisting Control

Dynamic coupling is an inherent behavior of the space robot system, which seriously affects the motion accuracy of the system. This article focuses on how to guarantee the base attitude stability of semifloating space robots, from a control perspective—namely, the base attitude decoupling control. The quaternion representation of the system dynamics is derived to avoid the representation singularity of the Euler angles. In consideration of the complicated system dynamics and the limited computing ability of the on-board computer, an efficient decoupling controller is designed based on the time-delay estimation (TDE) and the supertwisting control (STC). Herein, for the proposed TDE-based STC (TDE-STC) scheme, TDE is used to decouple and linearize the nonlinear dynamics, and STC is a second-order sliding mode control algorithm which can compensate for the TDE error and drive the state variables to converge to the equilibrium point robustly in finite time. The model-free decoupling principle of TDE is clearly illustrated by comparison with the classical computed torque control. The global asymptotical stability analysis of the closed-loop system is proven using the Lyapunov theory and the linear matrix inequality theorem. Finally, several comparative simulation studies on a 3-D space robot system with consideration of joint friction, disturbances, and model uncertainties are conducted to verify the effectiveness of the proposed TDE-STC scheme. The corresponding results show that the TDE-STC scheme can achieve a high-accuracy attitude decoupling performance with both the model-free merits and the chatter-free merits.
Use of efficient microorganisms in agriculture

The interest in the use of microorganisms in agricultural practices has increased significantly in recent years, both in the promotion of plant growth and in the biological control of plant pests and diseases. This literature review work aimed to address information on the use of isolation, multiplication, use and storage methodologies for efficient microorganisms (Effective Microorganisms, EM) in agriculture. These microorganisms have important functions for their hosts, as they have symbiotic interactions with them, and are capable of protecting plants from attack by insects, diseases and herbivorous mammals through the production of toxins. The use of EM in agriculture aims to accelerate the natural composition of organic matter and promote the balance of microbial flora contributing to plant development. EMs are potential substitutes for chemical products, and can thus favor the preservation of the environment. They are collected from fertile forest soils through simple and inexpensive methodologies, consisting of a tool with potential to be used both by family farmers and on a small and large scale. They can be used in different ways, the main ones being in soil, plant, water and animals. The use of EM is an accessible and low-cost technique, in addition to being easy to prepare within the property itself, contributing to the sustainability of agricultural systems.
Un modelo de análisis político comparado para videojuegos de simulación de gobierno. Estudio de caso con 'Frostpunk', 'Tropico IV' y 'Civilization V'

In this paper we present a large-scale comparative analysis model for videogames in which the player manages the development of a political community, which we will call «government simulators». The model, built upon political-science literature and other analytical models for videogames, uses a set of operationalized variables to synthesize the components of the political system represented in games, as well as the structure of objectives and other elements that guide the player’s action, to finally compare them with a set of independent variables. The model will be tested by applying it to three famous government simulators that have received notable academic attention (Civilization V, Tropico IV and Frostpunk), to finally discuss its advantages and limitations.
Electron energy spectrum in the field‐ionized plasma

In this article, the effect of ionization on the energy spectrum of electrons within the interaction of a laser pulse with hydrogen atoms is investigated using particle‐in‐cell simulation codes. The results show that the behaviour of electrons' energy distribution function in the field‐ionized plasma, which occurred due to the field ionization, compared with that in the pre‐plasma strongly depends on the pulse shape. For short rise‐time pulses (here 30 fs), due to the rapid enhancement of laser electric field, ionization occurs quickly, and as a result, there is not much difference in the electron energy in both the media. However, for pulses with rise time of 40 fs, in the pre‐plasma state, the electron population reaches higher energies compared with the field‐ionized plasma state. The main reason for this difference is the nonlinear wave breaking that happens earlier due to density inhomogeneity in the field‐ionized plasma. On the other hand, at longer rise‐time pulses (here 60 and 70 fs), electrons achieve higher energies in the field‐ionized plasma than those in the case of pre‐plasma. In this case, because of density fluctuations in the field‐ionized plasma, the Raman backscattered radiations are seeded by a strong initial noise at the earlier times and the Mendonca condition for chaos threshold is met sooner. Therefore, the electrons gain more energy through the stochastic mechanism that is in agreement with chaotic nature of the motion.
The boundary node method for multi‐robot multi‐goal path planning problems

In this paper, we investigate the multi‐goal path planning problem to find the shortest collision‐free path connecting a given set of goal points located in the robot working environment. This problem combines two sub‐problems: first, optimize the sequence of the goal points located in the free workspace; second, compute the shortest collision‐free path between goal points. In this study, a genetic algorithm is used to optimize the sequence of the goal points that the robot should visit. Once the sequence of the goal points is available, our developed method called Boundary Node Method (BNM) is applied to generate an initial collision‐free path between every pair of the sequenced goal points. Subsequently, an additional developed method called Path Enhancement Method (PEM) is used to find an optimal or near‐optimal path by reducing the overall initial path length. In the BNM, the robot and its immediate surroundings are simulated by a nine‐node quadrilateral element, where the centroid node represents the robot's position. The robot moves between goals with boundary nodes in the working environment depending on the boundary node's potential value. The potential value of each point in the working environment is calculated based on the proposed potential function. Additionally, this article investigates the multi‐goal path planning problem for multi‐robot systems, when each goal reached by several robots. Finally, simulations and experiments are performed on a real mobile robot to demonstrate the effectiveness of the developed methods.
Does non-profit commercialization help reduce social inequality? Revisiting the cross-subsidization hypothesis

ABSTRACT The non-profit sector has a long history of serving vulnerable people and promoting social equity. The growing reliance on commercial income in the non-profit sector has aroused wide concern about mission drift and the loss of identity. The cross-subsidization hypothesis is often used to justify non-profit commercialization, but this hypothesis has not been subject to many empirical tests. This study examines how non-profit hospitals’ commercial income affects their provision of community benefits. The results indicate that hospitals with more commercial income provide less unprofitable programmes to serve disadvantaged groups and reduce health disparities.
What have we learnt from the challenges of (semi-) automated requirements traceability? A discussion on blockchain applicability

Over the last 3 decades, researchers have attempted to shed light into the requirements traceability problem by introducing tracing tools, techniques, and methods with the vision of achieving ubiquitous traceability. Despite the technological advances, requirements traceability remains problematic for researchers and practitioners. This study aims to identify and investigate the main challenges in implementing (semi-)automated requirements traceability, as reported in the recent literature. A systematic literature review was carried out based on the guidelines for systematic literature reviews in software engineering, proposed by Kitchenham. We retrieved 4530 studies by searching five major bibliographic databases and selected 70 primary studies. These studies were analysed and classified according to the challenges they present and/or address. Twenty-one challenges were identified and were classified into five categories. Findings reveal that the most frequent challenges are technological challenges, in particular, low accuracy of traceability recovery methods. Findings also suggest that future research efforts should be devoted to the human facet of tracing, to explore traceability practices in organisational settings, and to develop traceability approaches that support agile and DevOps practices. Finally, it is recommended that researchers leverage blockchain technology as a suitable technical solution to ensure the trustworthiness of traceability information in interorganisational software projects.
A robust novel approach for dynamic energy management of smart grids in Wireless Sensor Networks

In our research work, we have implemented interval type 2 fuzzy logic model (IT2FL) applied to Smart grids in Wireless Sensor Networks (WSNs). The smart grids equipped with our technique are proficient to mainly react to various metrics like effective electricity cost and heat to continue end user’s thermic relaxation. Moreover the capabilities of WSNs to identify, examine and calculate various variables have been assessed to progress the restrictions of actual power control organizations for instance thermoregulators. We have taken Set-point weight, Time-Weights and Override flag as input to evaluate System output in weights and minutes. Efficacy of the recommended framework is made by means of statistical analysis and multiple linear regressions(MLR)