Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrinsic air stability mechanisms of two-dimensional transition metal dichalcogenide surfaces: basal versus edge oxidation

Layered transition metal dichalcogenides (TMDs) are being considered as a promising alternative channel material in ultra-thin and low power nanoelectronics, due to the significant tunability of their electronic properties via mechanisms such as mechanical strain, control of the material thickness, application of an external field, impurities, doping, alloying, or altering the substrate nature. Initially, monolayer TMDs as counterparts to graphene captured the attention of the scientific community owing to their semiconductor nature with sizable band gaps. However, certain physical and chemical properties of TMDs, such as their oxygen reactivity and stability in air need to be more completely understood in order to crystallize the promising superior performance of TMD-based electronic devices. Here, a comparative analysis of the stability of various TMDs (MX2: M=Mo, W; X=S, Se) in air is performed using density-functional theory (DFT) as well as x-ray photoelectron spectroscopy (XPS). We find that the surface chemistry of the basal plane of sulfides and selenides is relatively stable in air although for completely different reasons, which can be explained by investigating oxygen dissociative adsorption kinetics and thermodynamics. On the contrary, the edge of MX2 nanoribbons shows strong driving forces towards O2 dissociation and chemisorption. Our combined theoretical and experimental investigation reveals that the air stability of TMDs should not be placed in the same footing that other 2D materials, like graphene. Thus, this work highlights the importance of having controlled oxygen environment during crystal exfoliation/growth and defect passivation in order to provide high quality uniform materials for TMD-based device fabrication.
Sb nanoparticles uniformly dispersed in 1-D N-doped porous carbon as anodes for Li-ion and Na-ion batteries

Sb nanoparticles encapsulated in 1-D N-doped porous carbon (denoted as Sb/NPC) have been fabricated by an in situ nanoconfined replacement reaction between SbCl3 and the intermediate Ni/NPC, in which Ni/NPC was obtained by annealing the hydrothermally synthesized nickel–nitrilotriacetic acid (Ni–NTA) precursor in an argon atmosphere. The Sb nanoparticles with a size of 10–20 nm were uniformly encapsulated in the 1-D N-doped porous carbon scaffolds. When the Sb/NPC composite was applied as an anode material in the batteries, it exhibited a high reversible capacity of 556 mA h g−1 at 200 mA g−1 after 100 cycles for Li-ion batteries (LIBs) and a reversible capacity of 400.9 mA h g−1 at 100 mA g−1 after 100 cycles for Na-ion batteries (NIBs). Such enhanced electrochemical performance of the designed Sb/NPC can be attributed to the synergistic effect between uniformly dispersed Sb nanoparticles and the 1-D N-doped porous carbon matrices.
Staying or leaving? Patterns and determinants of Italian researchers’ migration

This article aims to highlight the dynamics underlying Italian researchers’ migration patterns over the last decade. Building on data gathered through an international study (MORE 3), the analysis focuses on identifying perceptions of working conditions, career prospect and confidence in the national Research and Innovation (R&I) system by Italian researchers in Italy and abroad. It provides a comparative assessment of researchers’ satisfaction with regards to their R&I environment in and outside Italy, across different fields of study and career stages. Results show that Italian researchers working abroad have a faster career progression than researchers in the Italian system and provide evidence of a low confidence of Italian researchers regarding career prospect in their own country. These findings are interpreted as major determinants of the decision to emigrate and develop an academic career abroad. Implications for future science policy in Italy are discussed.
Batch and fixed bed column investigations of the sorptive removal of cesium ions from aqueous solutions using modified graphene-alginate nanocompositebeads

ABSTRACT Cesium radioisotopes are among the majors that are presented in liquid radioactive waste causing long-term environmental threats. The mandatory treatment of these streams is regenerative goal in which adsorption techniques are focal. Calcium alginate/graphene-sodium dodycyl sulfate (CA/GR-SDS) nanocomposite beads were synthesized/characterized and their sorption properties toward were evaluated. Beads were of amorphous nature and the essential components were detected by FT-IR. Batch and fixed-bed column studies were explored. The highest sorbed amounts were acquired within the 1st- 30 min of contact time. The pseudo 2nd-order model gave the best fitting of the experimental kinetic data. Simple thermodynamic models have been applied to the isotherm sorption data and the relevant thermodynamic parameters were determined from the graphical presentation of these models. Increasing temperature gave lower quantities of sorption capacities. The estimated thermodynamic parameters disclosed the exothermic spontaneous ease of all sorption processes where negative and quantities were gained. Curves of breakthrough from CA/GR-SDS were constructed at varied bed depths (2.0, 4.0, and 8.0 cm) and flow rates (1.0 and 2.0 mL/min). Increasing the bed depth to 8.0 cm, slower exhaustion time was observed (15.5 h). Capacities and performances of beds were increased from 24.85 to 214.46 mg/g and from 13.67 to 29.89%, respectively, by increasing bed depths from 2.0 to 8.0 cm. A fast exhaustion time were observed with increasing the flow rate to 2.0 mL/min (1.17 h).
Countering Misinformation and Fake News Through Inoculation and Prebunking

ABSTRACT There has been increasing concern with the growing infusion of misinformation, or “fake news”, into public discourse and politics in many western democracies. Our article first briefly reviews the current state of the literature on conventional countermeasures to misinformation. We then explore proactive measures to prevent misinformation from finding traction in the first place that is based on the psychological theory of “inoculation”. Inoculation rests on the idea that if people are forewarned that they might be misinformed and are exposed to weakened examples of the ways in which they might be misled, they will become more immune to misinformation. We review a number of techniques that can boost people’s resilience to misinformation, ranging from general warnings to more specific instructions about misleading (rhetorical) techniques. We show that based on the available evidence, inoculation appears to be a promising avenue to help protect people from misinformation and “fake news”.
Mycobiome transplant increases resistance to Austropuccinia psidii in an endangered Hawaiian plant

The accelerated global movement of plant pathogens has become a substantial threat to rare and endangered plants. While application of synthetic pesticides on endangered plants is often necessary to control disease in greenhouse settings, these chemical treatments degrade the leaf microbiome. This reduction in diversity can eliminate foliar microbes that are essential for pathogen resistance, making plant hosts more susceptible to disease once out-planted in the wild. Beneficial microbes that naturally occur in plant tissue are a resource that is quickly gaining traction as a viable means to increase plant fitness and pathogen resistance in both agricultural and wild habitats. This is of particular interest for threatened and endangered wild plant populations with limited genetic variation where breeding for resistance is not possible. In this experiment we test the effectiveness of microbial inoculations to inhibit the fungal pathogen, Austropuccinia psidii, that is currently threatening the critically endangered Hawaiian Eugenia koolauensis with extinction. Using molecular and culture-based methods, we characterize foliar fungal communities of Myrtaceous hosts resistant to A. psidii and introduced these diverse fungi into the microbiome of E. koolauensis leaves. Our results indicate that transplanting an intact mycobiome community is more effective at reducing foliar disease resistance when compared to single fungal species inoculums. These findings demonstrate the potential of whole microbiome transplants as a powerful tool to inducing disease resistance and enhancing plant health within a conservation context.
Title: MDA5 score--A Novel Lung Computed Tomography Scoring Method for Anti-Melanoma Differentiation-associated Gene 5-positive Dermatomyositis

Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease. This study aimed to develop a novel pulmonary CT visual scoring method for assessing the prognosis of the disease, and an artificial intelligence (AI) algorithm-based analysis and an idiopathic pulmonary fibrosis (IPF)-based scoring were conducted as comparators. A prospective cohort of hospitalized patients with MDA5+ DM-ILD was analyzed. Since most fatalities occur within the first half year of the disease course, the primary outcome was the six-month all-cause mortality since the time of admission. A ground glass opacity (GGO) and consolidation-weighted CT visual scoring model for MDA5+ DM-ILD, namely ‘MDA5 score’, was then developed with C-index values of 0.80 (95%CI 0.75–0.86) in the derivation dataset (n = 116) and 0.84 (95%CI 0.71–0.97) in the validation dataset (n = 57), respectively. While, the AI algorithm-based analysis, namely ‘AI score’, yielded C-index 0.78 (95%CI 0.72–0.84) for the derivation dataset and 0.77 (95%CI 0.64–0.90) for the validation dataset. These findings suggest that the newly derived ‘MDA5 score’ may serve as an applicable prognostic predictor for MDA5+ DM-ILD and facilitate further clinical trial design. The AI based CT quantitative analysis provided a promising solution for ILD evaluation.
Evaluation of Quartz Reduction by Coal Cleaning for Thermal Utilization of an Indian Coal

ABSTRACT In Indian coals, quartz is abundantly found and its proportion usually varies from 5–20% by weight. Beneficiation of high-ash thermal coals of India has become the prerequisite for improving the overall economics and efficiency of power generation. A detailed survey of literature reveals that no systematic work has been done of beneficiated coal for Indian coals with respect to quartz, as also for correlation with abrasion. Therefore, to understand this effect different sizes of crushed coal were subjected to float-sink treatment at specific gravities in the range of 1.30– 1.80. This study highlights the systematic method of measuring crystalline silica (α-quartz) in bulk coal samples using NIST-SRM 1878a as a calibration standard with more accuracy by FT-IR as well as distribution of quartz in various screen sizes, float-and-sink fractions, for both the feed and clean coal. The results show that there is a linear relationship between ash % and quartz % with respect to specific gravity for all screen sizes. Characterization of the feed and clean coal with respect to quartz was also done using XRD, SEM, and XRF spectroscopic techniques to evaluate the reduction behavior of quartz during the coal-cleaning process.
Analysis of Processes Information Flows and Items as Additional Design Factor in Cobit Framework

COBIT is a process-oriented IT governance framework. In 2019 version, the framework offers a significantly redesigned approach to prioritize processes and set process target capability levels. The design phase is very important to achieve governance system in future. Although there are several design factors defined in the design phase of COBIT 2019, these factors do not assess process suitability and value for the governance system. Thus, connections and continuity among processes are not taken into consideration enough. Therefore, the aim of the article is to suggest another design factor based on the interrelationships of processes in the COBIT framework represented by its information flows. The nature of the proposed innovation is described, and the analysis of process information flows and items is performed. The article also publishes several inconsistencies in COBIT 2019 documentation that have been identified in the process of research. The application of process information flows and items analysis has been illustrated in two case studies. We have identified new information that can be relevant to decision making in the design phase and discussed their importance for planned governance system. The results could help to improve the quality of the design phase by providing additional information about the context of the processes designed to ensure the governance system. Implications for Central European audience: The implications for senior managers in the Central European region will be beneficial. Optimization and effective use of information technologies is a prerequisite for achieving long-term competitiveness. COBIT is a best practice framework, and its implementation in companies is largely based on the specifics of each organization. Therefore, it is important to pay close attention to the implementation phase of the application of COBIT. Framework application positively supports the holistic approach to management, resource optimization, management based on responsibility and measurability. Today, these attributes of the organization's management are emphasized not only in Central Europe but in developed countries in general.
Machine learning methods for short-term probability of default: A comparison of classification, regression and ranking methods

Abstract Probability of default estimation via machine learning on historical data is widely studied in credit risk modeling. In this work, we investigated the use of machine learning for a finer-grained risk estimation task, namely spot factoring. Here, the goal is to estimate the likelihood that an invoice will be paid in an acceptable timeframe. In this case, risk is more related to the overdueness of an invoice. Based on this observation, we investigate three possible machine learning tasks for estimating this risk: binary classification for a predetermined overdue days cutoff; regression of the overdue days; and learning-to-rank which learns to optimize the risk-related ranking for the full range of instances. We model and evaluate these tasks using real-life spot factoring data. Finally, we perform a profit-driven evaluation that shows that regression models can lead to higher profits and better spread the risk than classification and ranking models for spot factoring.
Optimized design of a tungsten–copper functionally graded material monoblock for minimal von Mises stress meeting the material operational temperature window

Functionally graded materials (FGMs) are a means to remove discrete material interfaces which lead to high local stress concentrations, such as the tungsten–copper (W–Cu) interface of the current ITER monoblock design. This paper employs adjoint-based optimization methods to identify the highest potential reduction of stresses that could be reached with these materials, while ensuring that the local temperature does not exceed the material temperature operational window. The cheap sensitivity evaluation inherent to the adjoint approach enables the optimization of the detailed 3D material distribution. Furthermore, a novel optimization method based on an augmented Lagrangian formulation is proposed that allows accurate treatment of the material temperature window constraints. The temperature and stresses are modelled by the steady heat conduction and Navier’s equation, respectively. We compare the results of different optimization formulations, with cost functions based on the von Mises stress and corresponding yield criterion and considering different values of the stress free temperature. To assess the performance under off-design conditions, two optimized designs were chosen and compared to the ITER and flat tile (FT) design, which consists of a copper block protected by a tungsten layer on top. The optimized designs lead to a factor 2–4 decrease in maximal stress near the original W–Cu interface of the FT design and a factor 10 decrease in yield criterion measure near the cooling duct. Under off-design conditions, they realized a factor 2–10 decrease in yield criterion in the upper part of the monoblock. This confirms numerically that FGMs can lead to significant design improvements. Finally, the inclusion of the material temperature operation window constraints leads to a decrease of 30–55 vol% W compared to the unconstrained cases, thus profoundly influencing the final design. The stress free temperature was found to have a comparably weaker influence on the final design with differences of 5–30 vol% W.
Consumers'
 self‐construal
 : Measurement and relevance for social media communication success

To determine the relevance of consumers' self-construal in social media contexts, this study investigates its effects on social media success metrics, such as sharing behaviour, as well as its influence on the relationship between social media success and other drivers, such as endorsers' emotion displays or the communication source (user vs. company). Along with an in-depth review of consumers' self-construal, this article reports on two quantitative panel studies, which reveal that eight items are best suited to represent consumers' self-construal, using correlated dimensions of interdependent and independent self-construal. The main study affirms the relevance of consumers' self-construal and offers detailed insights. Consumers with a strong interdependent self-construal express more positive attitudes toward social media posts, and a smiling endorser positively influences attitudes toward the post, sharing behaviour, word of mouth, and purchase intention. In combination, a strong interdependent self-construal and smiling endorser produce even stronger effects for attitudes toward the post, purchase intention, and word of mouth. User-generated content outperforms company-generated content, independent of self-construal types. These findings have important implications for social media communication management and personality research.
Orthogonal frequency division multiplexing with index modulation by using multiple constellation sets

In this article, a new transmission method named enhanced orthogonal frequency division multiplexing (E‐OFDM) is proposed to increase the spectral efficiency (SE) of the OFDM. The proposed method conveys information bits not only by the M‐ary symbols but also by the multiple different constellation sets. In the proposed method, we build the sub‐blocks by splitting the whole OFDM into pieces. Then, we use different constellation sets in each sub‐block and we assign the extra bits to them to increase the SE of the OFDM systems. Consequently, at the same modulation level, the proposed method has higher SE than the conventional OFDM system. The simulation results also show that the proposed method achieves better bit error rate (BER) performance than the conventional OFDM system with tolerable complexity. For example, the proposed method with a sub‐block size 2 doubles the SE of the conventional OFDM method with BPSK modulation, and also it has approximately 1.6 dB better BER performance than the conventional OFDM at BER =10−4. New constellation designs and receiver algorithm for the detection of additional bits are also presented.
Social environment and corporate payouts

We investigate if macro-level social capital, which captures the notions of trust and honesty, has any effects on corporate payout policy. We find that firms situated in U.S. states (or counties) with higher levels of social capital (SC) have higher dividend payouts (DP). These results survive a battery of robustness tests dealing with inference and various forms of endogeneity. We find that the positive SC-DP association is more prominent when monitoring is weak. We also find that the positive SC-DP association remains when we account for internal social capital, political corruption, federal and state income taxes, and other possible dividend clienteles such as in-state pension funds and pension-age populations. Our study contributes to the literatures that regional locations and social considerations constitute clienteles who affect important corporate strategic decisions such as corporate payouts.
Distributed economic model predictive control for operational safety of nonlinear processes

Achieving operational safety of chemical processes while operating them in an economically-optimal manner is a matter of great importance. Our recent work integrated process safety with process control by incorporating safety-based constraints within model predictive control (MPC) design; however, the safety-based MPC was developed with a centralized architecture, with the result that computation time limitations within a sampling period may reduce the effectiveness of such a controller design for promoting process safety. To address this potential practical limitation of the safety-based control design, in this work, we propose the integration of a distributed model predictive control architecture with Lyapunov-based economic model predictive control (LEMPC) formulated with safety-based constraints. We consider both iterative and sequential distributed control architectures, and the partitioning of inputs between the various optimization problems in the distributed structure based on their impact on process operational safety. Moreover, sufficient conditions that ensure feasibility and closed-loop stability of the iterative and sequential safety distributed LEMPC designs are given. A comparison between the proposed safety distributed EMPC controllers and the safety centralized EMPC is demonstrated via a chemical process example. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3404–3418, 2017
Nitrogen, Phosphorus, and Potassium Adsorption and Desorption Improvement and Soil Buffering Capacity Using Clinoptilolite Zeolite

The physical and chemical properties of clinoptilolite zeolite can be used to enhance soil nutrient availability for optimum crop use. Amending nitrogen, phosphorus, and potassium fertilizers with clinoptilolite zeolite could create a pool of negative charges to retain and release nutrients timely for crop use. Thus, we used clinoptilolite zeolite to enhance Typic Paleudults sorption (adsorption and desorption) of nitrogen, phosphorus, potassium, and this soil’s pH buffering capacity. The treatments evaluated were: (i) 250 g soil alone, (ii) 20 g clinoptilolite zeolite alone, (iii) 250 g soil + 20 g clinoptilolite zeolite, (iv) 250 g soil + 40 g clinoptilolite zeolite, and (v) 250 g soil + 60 g clinoptilolite zeolite. Clinoptilolite zeolite increased soil nitrogen and potassium adsorption, nitrogen desorption, and soil pH. Moreover, ability of the soil to resist drastic change in pH (pH buffering capacity) was improved. Additionally, phosphorus adsorption and desorption of phosphorus and potassium were reduced. Higher potassium adsorption with lower potassium desorption suggests that the clinoptilolite zeolite sorbs potassium effectively. The clinoptilolite zeolite nitrogen, phosphorus, and potassium contributed to the reduction in the adsorption these nutrients. The clinoptilolite zeolite improved nitrogen, phosphorus, and potassium availability and soil buffering capacity to prevent these nutrients from being fixed or lost through for example, leaching. Therefore, clinoptilolite zeolite application could contribute to improved use of nitrogen, phosphorus, and potassium fertilizers to prevent soil, air, and water pollution. Additionally, our intervention could improve nitrogen, phosphorus, and potassium use efficiency.