Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive comment on “ Complex noise suppression and reconstruction of seismic reflection data from fault structures using Space Lagged Singular Spectral Analysis ” by R . K . Tiwari

disadvantages of domain conversion. We have also the presented the application of the method using the synthetic as well as real seismic data and demonstrated that how the artifact would arise in domain conversion. Thus, we strongly refute referee’s comment and state that the t-x domain processing of the data, which is used here, has an added advantage over the MSSA method. In addition to this, the spatial data series correlates more than the depth series on large scales as horizons from a constant depth owe approximately same properties.
Transcending toward Advanced 3D-Cell Culture Modalities: A Review about an Emerging Paradigm in Translational Oncology

Cancer is a disorder characterized by an uncontrollable overgrowth and a fast-moving spread of cells from a localized tissue to multiple organs of the body, reaching a metastatic state. Throughout years, complexity of cancer progression and invasion, high prevalence and incidence, as well as the high rise in treatment failure cases leading to a poor patient prognosis accounted for continuous experimental investigations on animals and cellular models, mainly with 2D- and 3D-cell culture. Nowadays, these research models are considered a main asset to reflect the physiological events in many cancer types in terms of cellular characteristics and features, replication and metastatic mechanisms, metabolic pathways, biomarkers expression, and chemotherapeutic agent resistance. In practice, based on research perspective and hypothesis, scientists aim to choose the best model to approach their understanding and to prove their hypothesis. Recently, 3D-cell models are seen to be highly incorporated as a crucial tool for reflecting the true cancer cell microenvironment in pharmacokinetic and pharmacodynamics studies, in addition to the intensity of anticancer drug response in pharmacogenomics trials. Hence, in this review, we shed light on the unique characteristics of 3D cells favoring its promising usage through a comparative approach with other research models, specifically 2D-cell culture. Plus, we will discuss the importance of 3D models as a direct reflector of the intrinsic cancer cell environment with the newest multiple methods and types available for 3D-cells implementation.
A Hydrogen Sensor for Liquid-Metal Breeding Blankets

In HCLL (Helium Cooled Lithium Lead) blanket for ITER fusion reactor, an efficient management operation of tritium is necessary, in order to minimize the release of tritium to the environment and to improve the economy of the overall balance of the reactor tritium inventory. In this context, optimization techniques for the measurement of tritium in the various stages of the fuel cycle of the reactor must be carried out in parallel with the research and development of processing systems for tritium. For example, the TES, Tritium Extraction System, is a critical system and the determination of the concentration of hydrogen isotopes is required for its correct design [1]. Therefore, the need of a fast and reliable sensor for the measurement of the tritium concentration in the liquid breeder is well established. For this application, a sensor based on the principle of tritium permeation in a capsule of suitable material seems to be, at least in principle, the easiest and most reliable one. Furthermore, many data on tritium permeability through different materials and their compatibility in an environment of liquid metal are available, thanks to the experimental studies performed for the selection of structural materials for blanket modules
Quercetin modulates age-induced changes in the transcript levels of some apoptosis related genes in the skeletal muscles of male rats

Adverse changes occur gradually in the skeletal muscles with age via continuous exposure to oxidative stress. Quercetin, a member of the flavonoids family, possesses anti-oxidative and radical-scavenging activities. Therefore, this study investigated the role of quercetin to modulate age-induced changes in the transcript levels of some apoptosis-related genes in rat’s gastrocnemius muscles, up to 15 months-old. Half of the rats at each age (1, 5, 10 and 15 months old) were given a vehicle and the other half was given 200 mg/kg quercetin for 2 weeks, respectively. With the increase of age, vehicle groups showed hyalinization of the muscle fibers and a decrease of the catalase and an increase of the malondialdehyde levels. Down-regulation of Bcl2 gene and up-regulation of both NF-κB and Bax genes were recorded. Interestingly, quercetin groups showed focal hyalinization of the muscle fibers at both 10th and 15th months old. An increase in the catalase and a decrease in malondialdehyde levels, up-regulation of Bcl2 gene and down-regulation of both NF-κB and Bax genes were recorded. In conclusion, quercetin minimized age-induced alteration in the morphological structure and the expression of the apoptosis-related genes via increasing the antioxidant defense in the gastrocnemius muscle.
Oxidized Ti3C2T x film-based high-performance flexible pressure sensors

Flexible pressure sensors are the basic building blocks for implementing electronic or tactile skin for robotics, wearable electronic and human-machine interactions. To achieve these potential applications, subtle pressure detection is required under a variety of conditions and is often limited by low sensitivity. Herein, we report an oxidized Ti3C2T x film with outstanding mechanical flexibility via vacuum filtration to assemble a novel flexible pressure sensor. Benefiting from the large deformation of the composite films, the prepared pressure sensor exhibits low detection limits of 8 Pa and fast response/recovery time of 70/20 ms, in addition to excellent cycling stability (10 000 cycles). These novel functions allow us to act as electronic skin to monitor human physiological activity in a personalized manner. Obviously, this good sensing characteristic can highlight the broad prospects of oxidized MXene-based pressure sensors for higher integration of flexible electronic devices.
First-principles study on hydrogen storage properties of Ti8C6 cluster

The geometric structure, energy gaps of molecular orbital and hydrogen absorb capacities of Ti8C6 clusters are investigated by first-principles based on density functional theory. The results show that the bond length of hydrogen molecules decrease and the Ti-H bond length of Ti8C6(H2)n clusters increase with the increase of hydrogen molecules adsorbed by Ti8C6 from 8 to 40. Moreover, the Ti8C6(H2)40 cluster not only exhibits strong stability according to energy gap analysis, but also absorbs 40 hydrogen molecules with gravimetric density of 15.05 wt%, which will be considered as a candidate material for hydrogen absorption.
Calculation of evaporation rates of all components in Ag-Pb-Sn ternary alloy in vacuum distillation using modified molecular interaction volume model

In this study, the activities of each component in Ag-Pb, Ag-Sn, Pb-Sn binary and Ag-Pb-Sn ternary alloy systems were predicted using molecular interaction volume model (MIVM), modified molecular interaction volume model (M-MIVM), Wilson equation and nonrandom two-liquid (NRTL) model, respectively. The average standard deviation and average relative deviation of these four models are also calculated. The results show that the prediction deviations of M-MIVM are smallest among four models, which indicates that M-MIVM is reliable for prediction of activity of these alloy systems. The volatilization coefficients (α) of Ag-Pb, Ag-Sn and Pb-Sn binary alloy systems were calculated based on M-MIVM. The results show that α Ag-Pb ≫ 1 and α Pb-Sn ≪ 1, which indicates that Pb will be enriched in the vapor phase while Ag (or Sn) in the liquid phase in vacuum distillation of Ag-Pb alloy (or Pb-Sn alloy). The values of α Ag-Sn were in the range from 0.1 to 10 which indicates that Ag-Sn alloy is difficult to be separated by vacuum distillation. The evaporation rates of each component in Ag-Pb, Ag-Sn, Pb-Sn and Ag-Pb-Sn alloy systems at 1173 K, 1273 K and 1373 K were calculated based on M-MIVM. The results indicate that the evaporation rate of Pb is in the order of magnitude 10−1 ∼ 101 in Ag-Pb, Pb-Sn and Ag-Pb-Sn alloy systems and it is 104 ∼ 106 times larger than that of Sn (or Ag). The evaporation rate of Pb in Pb-Sn alloy decreases with the addition of the third component Ag. This work provides a new method for the development of kinetics research and a theoretical guidance for industrial production in vacuum distillation.
Classification of arrester defects based on Naive Bayesian inference

Under the special environment of high temperature, high humidity and high salt, the development of the deterioration or latent defects of the arrester is accelerated. It is difficult to identify the abnormal state of arrester in special environment, only relying on the monitoring index of arrester. Therefore, this paper proposes a kind of lightning arrester defect recognition technology based on Naive Bayesian, which extracts the key features that affect the operation state of lightning arrester in special environment, and calculates the prior probability of training samples and the posterior probability of test samples through naive Bayesian algorithm, so as to identify the type of lightning arrester defects. The feasibility and correctness of the proposed method are analyzed and verified by the actual monitoring and detection data.
Research basis of muon imaging applied in reactor core monitoring

Muon imaging technology has been applied in many fields. The exploratory application of muon imaging technology after the Fukushima nuclear accident provides enlightenment for the application of nuclear core safety monitoring under serious accidents. In this paper, the muon imaging technology is introduced from the aspects of technical principle, muon detection technology, imaging algorithm and application, so as to provide ideas and methods for the application of muon imaging technology in nuclear core safety monitoring.
Study on the Soil Structure and Construction Technology of Large Span Double-Arch Tunnel Entrance

In the construction process of tunnel engineering, the construction of the entrance section is one of the crucial procedures. How to improve the construction efficiency and ensure the stability of the tunnel entrance section needs to be considered. Based on the project of a double-arch tunnel, this paper studies the construction techniques of the entrance of the urban double-arch tunnel with a large span. Based on the numerical simulation, it is proved that the construction of tunnel entrance by opening up a cross passage is feasible.
A novel industrial process fault monitoring method based on kernel robust non-negative matrix factorization

Industrial processes are characterized by large amounts of nonlinear and noisy data, which pose a critical challenge to the accuracy and rapidity of fault detection. In this paper, an industrial process fault monitoring method based on kernel robust non-negative matrix factorization is proposed. This method uses the kernel technique to map the nonlinear data to high-dimensional linear space, where the local features of the sample will be extracted by the non-negative matrix factorization (NMF) method. However, noise signals will inevitably be mixed. Therefore, a sparse error matrix is introduced to isolate fault and noise information. Finally, a new monitoring statistics and a fault detection framework are constructed. On the TE platform, the algorithm proposed in this paper is compared with kernel principal component analysis and kernel NMF methods in nonlinear experiments and robustness experiments through two performance indicators: fault detection rate and fault delay. The results prove the effectiveness of the algorithm in this paper.
NLP for SDGs: Measuring Corporate Alignment with the Sustainable Development Goals

This article uses advanced natural language processing (NLP) methods to identify companies that are aligned with the UN Sustainable Development Goals (SDGs) based on the text in their sustainability disclosures. Using the Corporate Social Responsibility (CSR) reports of Russell 1000 companies between 2010–2019, we apply a logistic classifier, support vector machines (SVM), and a fully-connected neural network to predict alignment with the SDGs. Specifically, we use word embeddings to augment dictionary-based input features, as well as the embeddings as features themselves, based on Word2Vec and Doc2Vec models to classify companies’ alignment with the SDGs over time. Notably, the Doc2Vec embedding inputs to the SVM classifier result in high average accuracy of above 80% for predicting alignment.
The Effects of Usury Ceilings on Consumers Welfare: Evidence from the Microcredit Market in Colombia

Interest rate caps, also called usury ceilings, are a widely used policy tool to protect consumers from excessive charges by loan providers. However, they are often cited as a barrier for the advancement of financial inclusion, as they may reduce the incentives to provide loans to lower-income borrowers and and to invest in branching networks, particularly in remote and isolated locations. In this paper, I exploit a change in the usury ceiling applied to micro-loans in Colombia to understand the effects of this policy across geographic markets. To quantify the welfare implications of this policy, I structurally estimate a demand and supply model that incorporates the changes in size and composition of the potential market caused by this policy change, in a context where the distribution of branching networks has a crucial role in the optimal pricing strategies of loan providers. I find that the policy generated an increase in consumer surplus at the national level that is explained by greater credit availability for riskier borrowers and the expansion of branching networks in areas that were previously under-served. A counterfactual exercise reveals that the welfare gains associated to this policy depend greatly on additional investment in branching networks, as the opening of new branches in some locations is needed to compensate the consumer welfare loss associated with the subsequent increase in interest rates after the relaxation of the ceiling. <br>
Mining for Favors: The Impact of Political Influence on Regulatory Enforcement

Regulatory capture can generate significant social and economic costs, particularly<br>in dangerous occupations. In this article I evaluate whether political influence has<br>allowed firms to systematically evade safety and health regulations using data from one<br>of the country’s most dangerous occupations—mining. Using an instrument to capture<br>exogenous variation in political influence decisions, I show that when mining firms use<br>influence, they reduce their expected non-compliance costs by 30 percent, but report a<br>40 percent increase in death rates. Importantly, the largest benefit comes during the<br>adjudicative stage meant to be isolated from political influence.
Tracking Weekly State-Level Economic Conditions

Abstract This paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.
Causality Analysis between the Energy Consumption and Economic Growth in South Asia: An Evidence from Bangladesh

The objective of this study is to explore the causality between electricity use and economic growth of Bangladesh. By using the unit root and granger causality tests from 1971 to 2016, this study finds that energy consumption causes GDP growth in Bangladesh. However, our empirical findings indicate that GDP growth does not causes energy consumption indicating that there is an uni-directional causality between these two variables. The policy implication of the result is that Bangladesh need to pay special attention to utilize the energy consumption and identifying the alternative sources of energy generation in order to promote our economic growth.
Financial Development, Firm Growth, and Aggregate Productivity Divergence in Europe

Since the information and communications technology revolution, productivity growth in Southern European countries has been substantially lower than in developed European countries. I document that Spanish firms have lower productivity growth, lower intangible capital growth, and lower leverage than German firms. The disparity is larger among smaller firms. I build a model featuring endogenous firm productivity growth through innovation investment and size-dependent financial frictions to rationalize these findings. The model finds that financial frictions account for 11% of the aggregate productivity growth difference in the data. The model mechanism and predictions are also supported by evidence in other European countries.
Analytical Potential Energy Function for the Ground State X^{1} Sigma^+ of LaCl

The equilibrium geometry, harmonic frequency and dissociation energy of lanthanum monochloride have been calculated at B3LYP, MP2, QCISD(T) levels with energy-consistent relativistic effective core potentials. The possible electronic state and reasonable dissociation limit for the ground state are determined based on atomic and molecular reaction statics. Potential energy curve scans for the ground state X^{1} Sigma^+ have been carried out with B3LYP and QCISD(T) methods due to their better performance in bond energy calculations. We find the potential energy calculated with QCISD(T) method is about 0.5 eV larger than dissociation energy when the diatomic distance is as large as 0.8 nm. The problem that single-reference ab initio methods don't meet dissociation limit during calculations of lanthanide heavy-metal elements is analyzed. We propose the calculation scheme to derive analytical Murrell-Sorbie potential energy function and Dunham expansion at equilibrium position. Spectroscopic constants got by standard Dunham treatment are in good agreement with results of rotational analyses on spectroscopic experiments. The analytical function is of much realistic importance since it is possible to be applied to predict fine transitional structure and study reaction dynamic process.
The Impact of Artificial Intelligence on Skills at Work in Denmark

Based on a unique dataset on the use of artificial intelligence (AI) among employees in Denmark, we investigate within-job relationships between AI use and skill requirements. We show that the effects of AI are varied and depend on providing orders to humans versus providing information for further human handling and in which occupation it is used. AI may enhance or augment skills through, for example, the increased use of high-performance work practices, or it may simply increase work pace constraints and reduce employee autonomy. The results imply that the diffusion of AI can increase inequalities in the labour market by augmenting skills used in high-skill jobs while having relatively more adverse impacts on other jobs. We use additive noise modelling to establish the likely direction of causality in our results and find that the direction of causality is from AI use to skill requirements.
Comparing the Willingness to Pay for the Ecological Compensation and Recreation Value of the Urban Inland Rivers Based on CVM Method, a Case Study of Nanyang Urban Inland Rivers

Ecological restoration of urban inland rivers is of great importance for sustainable urban development. Ecological restoration of urban inland rivers can be carried out mainly in two aspects, on the one hand, the environmental ecology of urban inland rivers and on the other hand, the ecological aspect of recreation in urban inland rivers. In this study, the willingness to pay of 326 respondents within 2 km of the three inland rivers in Nanyang City was studied by CVM method. Two sets of double bounded dichotomous choice questions were designed to investigate the respondents' willingness to pay for environmental restoration and recreational restoration respectively, and the willingness to pay for environmental restoration was 9.13 RMB per person per month, and the willingness to pay for recreational restoration was 21.26 yuan per person per month. By comparing these two differences, we analyzed the influence of income level, educational background, environmental awareness, and recreational participation in willingness to pay. And based on the analysis results, targeted future policy recommendations and efforts for inland river restoration are proposed.
The Evolution of Financial Services in the Digital Age

This chapter provides an overview of how digital technologies are transforming the financial services landscape. We highlight the latest in digital financial product and service offerings related to payments and transfers, savings and investments, borrowing, and risk management. We then consider how digitalization is impacting the delivery of financial advice - including virtual advisors, robo- and hybrid advisors, and personal finance communities. While many of these digital innovations were underway prior to Covid-19, the pandemic accelerated the transition raising concerns that some individuals and families may be at risk of being excluded from financial services due to growing socioeconomic and digital divides. We look at barriers to access and usage and emphasize the need for digital financial literacy. Legal and regulatory challenges are also examined. Particular attention is given to recent efforts by regulatory and supervisory authorities to balance innovation and competition with consumer protection. The insights from this chapter provide a useful starting place for scholars and practitioners who are interested in exploring in greater detail how digital technologies are impacting the financial services industry. © 2022 Walter de Gruyter GmbH, Berlin/Boston.
Would I Lie to You? How Interaction with Chatbots Induces Dishonesty

Is dishonesty more prevalent in interaction with a machine as opposed to a human? We analyze this question using an innovative experimental setup involving the reporting of an unobserved payout-relevant random draw either to a chatbot or another human in a chat interaction while also varying the degree of agency. We find that reporting to a chatbot that is unable to demonstrate agency induces the lowest levels of honesty, whereas reporting to a human, which can demonstrate such agency, generates the highest levels of honesty. We identify a stronger role of social-image concerns and social norms when a person interacts with another human and show that subjects abstain from lying more when they have more time to reflect on their behavior. Our results have implications for designing efficient means of interaction between consumers and organizations in a variety of different contexts in the digital economy.