Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast and Scalable Algorithm for Detection of Structural Breaks in Big VAR Models

Abstract Many real time series datasets exhibit structural changes over time. A popular model for capturing their temporal dependence is that of vector autoregressions (VAR), which can accommodate structural changes through time evolving transition matrices. The problem then becomes to both estimate the (unknown) number of structural break points, together with the VAR model parameters. An additional challenge emerges in the presence of very large datasets, namely on how to accomplish these two objectives in a computational efficient manner. In this article, we propose a novel procedure which leverages a block segmentation scheme (BSS) that reduces the number of model parameters to be estimated through a regularized least-square criterion. Specifically, BSS examines appropriately defined blocks of the available data, which when combined with a fused lasso-based estimation criterion, leads to significant computational gains without compromising on the statistical accuracy in identifying the number and location of the structural breaks. This procedure is further coupled with new local and exhaustive search steps to consistently estimate the number and relative location of the break points. The procedure is scalable to big high-dimensional time series datasets with a computational complexity that can achieve , where n is the length of the time series (sample size), compared to an exhaustive procedure that requires steps. Extensive numerical work on synthetic data supports the theoretical findings and illustrates the attractive properties of the procedure. Finally, an application to a neuroscience dataset exhibits its usefulness in applications. Supplementary files for this article are available online.
Ultrasound assisted synthesis of thiazolidine thiones containing 1,2,3-triazoles using Cu/TiO2

Oxidised copper nanoparticles on TiO 2 have been found to effectively catalyze the multicomponent synthesis of 1,4-disubstituted 1,2,3-triazoles in water under both conventional heating and ultrasonic irradiation conditions. The Cu/TiO 2 nanocatalyst is easy to prepare, very versatile and recyclable. Following the optimized conditions, an array of 1,2,3-triazoles containing thiazolidine-2-thiones were synthesized from 5-iodomethylthiazolidine-2-thiones, sodium azide
Phenological Classification Using Deep Learning and the Sentinel-2 Satellite to Identify Priority Afforestation Sites in North Korea

The role of forests to sequester carbon is considered an important strategy for mitigating climate change and achieving net zero emissions. However, forests in North Korea have continued to be cleared since the 1990s due to the lack of food and energy resources. Deforestation in this country has not been accurately classified nor consistently reported because of the characteristics of small patches. This study precisely determined the area of deforested land in North Korea through the vegetation phenological classification using high-resolution satellite imagery and deep learning algorithms. Effective afforestation target sites in North Korea were identified with priority grade. The U-Net deep learning algorithm and time-series Sentinel-2 satellite images were applied to phenological classification; the results reflected the small patch-like characteristics of deforestation in North Korea. Based on the phenological classification, the land cover of the country was classified with an accuracy of 84.6%; this included 2.6 million ha of unstocked forest and reclaimed forest. Sites for afforestation were prioritized into five grades based on deforested characteristics, altitude and slope. Forest area is expanded and the forest ecosystem is restored through successful afforestation, this may improve the overall ecosystem services in North Korea. In the long term, it will be possible to contribute to carbon neutrality and greenhouse gas reduction on the Korean Peninsula level through optimal afforestation by using these outcomes.
Like father, like son: explicating parental influence on adult children’s public sector preference

Abstract Research on how parents influence their children’s public sector preference is becoming more plentiful; unfortunately, these studies do not include the analysis of cultural contexts. In this study based in Taiwan, elements of Confucian ideology, which encompass submission to authority and male dominance, are proposed as the main sources of this parental influence. First, parents directly transmit values, such as public service motivation (PSM) as well as security and growth values, to their children and subsequently shape their sector preferences. Second, parents’ opinions and expectations about whether or not their children should consider a public service career in turn affects children’s own public sector preference. Statistical results from the parent–child dyadic data support both value transmission and parental expectation mechanisms. Additional analysis shows that the father’s influence is stronger than that of the mother.
Conceptual Framework for the Service-Oriented Management of Construction Labor Resource

Abstract In spite of the considerable research on construction labor management, labor resource availability remains a challenge for China’s construction projects. The reason is the separation between contractors and laborers caused by the main labor resource utilization method, namely, labor subcontracting rather than direct recruitment. Service-oriented concept and technology are introduced by multiple industries for the management and optimal allocation of distributed resources, and have the potential to solve the problem of labor resource availability faced by China’s construction industry. However, insufficient conceptual understanding impedes implementation. Accordingly, this research extends the service-oriented concept to construction labor and proposes a conceptual framework for explanation, thereby contributing to the body of knowledge. In this framework, a service-oriented labor resource management model called labor-as-a-service is covered and described from three aspects: organizational relationship, managerial process, and technical framework. A strengths, weaknesses, opportunities, and threats analysis is conducted to preliminarily investigate the potential of the proposed framework. Results show that the conceptual framework suits China’s conditions and has the potential to improve labor resource management.
The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees

Big data is rapidly being seen as a new frontier for improving organizational performance. However, it is still in its early phases of implementation in developing countries’ healthcare organizations. As data-driven insights become critical competitive advantages, it is critical to ascertain which elements influence an organization’s decision to adopt big data. The aim of this study is to propose and empirically test a theoretical framework based on technology–organization–environment (TOE) factors to identify the level of readiness of big data adoption in developing countries’ healthcare organizations. The framework empirically tested 302 Malaysian healthcare employees. The structural equation modeling was used to analyze the collected data. The results of the study demonstrated that technology, organization, and environment factors can significantly contribute towards big data adoption in healthcare organizations. However, the complexity of technology factors has shown less support for the notion. For technology practitioners, this study showed how to enhance big data adoption in healthcare organizations through TOE factors.
Assessing Future Drought Conditions over the Iberian Peninsula: The Impact of Using Different Periods to Compute the SPEI

Future drought-hazard assessments using standardized indices depend on the period used to calibrate the probability distributions. This appears to be particularly important in a changing climate with significant trends in drought-related variables. This study explores the effect of using different approaches to project droughts, with a focus on changes in drought characteristics (frequency, duration, time spent in drought, and spatial extent), estimated with a calibration period covering recent past and future conditions (self-calibrated indices), and another one that only applies recent-past records (relative indices). The analysis focused on the Iberian Peninsula (IP), a hot-spot region where climate projections indicate significant changes by the end of this century. To do this, a EURO-CORDEX multi-model ensemble under RCP8.5 was used to calculate the Standardized Precipitation-Evapotranspiration Index (SPEI) at both 3- and 12-month timescales. The results suggest that projections of drought characteristics strongly depend on the period used to calibrate the SPEI, particularly at a 12-month timescale. Overall, differences were larger for the near future when relative indices indicated more severe droughts. For the distant future, changes were more similar, although self-calibrated indices revealed more frequent and longer-lasting droughts and the relative ones a drought worsening associated with extremely prolonged drought events.
Morphological variation in Bessera (Asparagaceae: Brodiaeoideae) allows for the recognition of two new species

Bessera (Asparagaceae: Brodiaeoideae) is a genus endemic to Mexico. It currently has two described species: B. elegans with a wide geographic distribution from Durango and Sinaloa in the Sierra Madre Occidental, across the Transmexican Volcanic Belt to Oaxaca in the Sierra Madre del Sur, and B. tuitensis which is endemic to the Sierra del Cuale in Jalisco. Most of the morphological variation in Bessera occurs in western Mexico. We measured ten morphological characters for 280 plants from 21 populations, including B. tuitensis, to answer the following questions: Can Moore’s Group B of B. elegans be recognized as a different species? Are the newly included B. elegans s. l. populations from Colima different from B. elegans s. str. , and from B. elegans s. l. (Moore’s group B)? Is there a significant relationship between morphological variation and climate variables for these species? The statistical analyses (ANOVA, MANOVA, and discriminant analysis) allowed us to recognize two new Bessera species, described here as B. elegantissima and B. ramirezii. Additionally, we provide a morphological key for Bessera, illustrations, a distribution map, and photographs of all the species.
Relationship between Rubisco activase and Rubisco contents in transgenic rice plants with overproduced or decreased Rubisco content

ABSTRACT Overproduction of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco; E.C. 4.1.1.39) in rice did not necessarily improve photosynthesis. The reason for this was that a partial deactivation of Rubisco occurred in RBCS-overexpressed rice plants. Since a negative correlation between the amounts of Rubisco activase (RCA) and Rubisco has been reported for plants with overproduced or decreased RCA, the possibility that RCA content declines in RBCS-overexpressed rice plants was considered. The relationship between RCA and Rubisco contents was examined in RBCS-overexpressed and RBCS-antisense rice plants. Whereas the ratio of RCA to Rubisco contents in RBCS-antisense plants increased three- to fourfold as compared with that of the wild-type levels, this ratio decreased 60–70% of the wild-type levels in RBCS-overexpressed rice plants. Thus, an apparent trade-off between the amounts of RCA and Rubisco was observed in RBCS-transgenic rice plants. However, the amounts of several Calvin–Benson cycle enzymes changed in a similar manner to that of RCA in both types of RBCS-transgenic rice plants. When the relationships between the amounts of these enzymes, including RCA, and those of total leaf-N minus Rubisco-N and trichloroacetic acid (TCA)-soluble N were examined, there were no differences between them irrespective of genotypes. These results indicate that the negative correlation between the amounts of RCA and Rubisco in RBCS-transgenic rice plants is the result of a change in N allocation to Rubisco in transgenic rice plants rather than a trade-off. Such a negative correlation was also found for other Calvin–Benson cycle enzymes. In addition, since the amounts of these Calvin–Benson cycle enzymes and RCA were highly correlated with their mRNA levels irrespective of genotype, it is suggested that changes in the amounts of these proteins are regulated at their transcript levels by a change in N allocation to Rubisco.
Populism, Religion, and Social Media in Central America

This paper analyzes how presidential candidates Fabricio Alvarado and Nayib Bukele used Facebook during the elections in Costa Rica (2018) and El Salvador (2019) respectively to develop a particular style of communication that blended populist elements and religious discourse. This style of communication extended traditional modes of populism that have prevailed in Latin America since the turn of the century (emphasizing the notion of the hero who comes to rescue “the people”) but expressed them in an explicitly religious way (stressing the role of a “messiah” who comes to alter the established political order). We conducted both content and multimodal discourse analyses of 838 posts made by these candidates on Facebook during their respective electoral campaigns. We argue that the study of these campaigns would be incomplete without accounting for the relationship between populism, religion, and social media. While populism gave political validity to religious discourse, a religious imaginary provided populism with charismatic and messianic authority. This populist/religious reason found an ideal expression in Facebook and, simultaneously, was resignified by this platform's affordances. In this way, we assess how fundamentalist Christianity has become a legitimating force of knowledge and politics in the context of epistemic tensions that shape contemporary Latin-American societies.
Regional differences in hourly rainfall characteristics over the southeastern extension of the Tibetan Plateau

The southeastern extension of the Tibetan Plateau (SETP) is distributed by the typical longitudinal mountains and has unique climate characteristics and significant regional differences. The diurnal cycles of rainfall amount, frequency, and intensity over the SETP in the warm seasons (May–September) were investigated using high‐density hourly station rainfall data and the possible mechanisms were discussed by analysing the ERA5 reanalysis and satellite data. The largest amounts of rainfall appeared on the southern and western margins of the SETP, and the rainfall amount was relatively small at the higher elevations of the SETP. Located at the southern margins of the SETP, the adjacent western (Reg_W) and eastern (Reg_E) regions presented a similar rainfall amount, frequency, and intensity, but the diurnal features of the two regions were quite different. The rainfall amount, frequency, and intensity had dominant peaks in the late afternoon in Reg_W, while in the early morning in Reg_E. A secondary peak in the early morning can be found in Reg_W. The diurnal features of the two regions were closely related with the low‐level atmospheric conditions and the distribution of clouds. The enhanced convergence of the anomalous southerly winds and sufficient water vapour after midnight contributed to the nocturnal rainfall at the southern edge of the SETP. In the afternoon, the lower surface air temperature and more stable stratification in Reg_E, as compared with Reg_W, were relatively unfavourable for the occurrence of afternoon convection.
An internal supplemental action measurement to increase the gap of action values and reduce the sensitivity to overestimation error

ABSTRACT Reinforcement learning holds considerable promise to help address sequential decision-making problems, in which Q-learning is one of the most used algorithms. However, Q-learning suffers from overestimation errors, especially when action values in the same state are similar. To reduce such damages, we introduce an internal supplemental action measurement based on the variation of the expected state values between a state transition, which can measure the action causing the state transition. For the reason that the internal supplemental action measurement can increase or decrease the action values according to the action performance, it can increase the gap of the action values, thus reducing the sensitivity to the overestimation error. The experimental results in the Markov chain and the video games demonstrate the performance advantage of applying the internal supplemental action measurement, in which the mean evaluating scores with the internal supplemental action measurement are 131.6% in SpaceInvaders, 187.9% in Seaquest, and 176.6% in Asterix respectively of that without the internal supplemental action measurement.
Does Consumer Innovativeness Matter in Electrified Vehicle? The Moderation Role of Consumer Involvement

Abstract Electrified vehicles have become a solution to greenhouse gas emissions. However, the diffusion of this sustainable transportation is slow, and consumer innovativeness is suggested to have a weak predictive power on electrified vehicle adoption. The aim of this study was to understand how consumer innovativeness and involvement may affect customers’ electrified vehicle purchase behavior. The results indicate that consumer innovativeness has less ability to predict electrified vehicle adoption. This finding offers insights for the formulation of marketing strategies on facilitating electrified vehicle adoption, which should focus on highly involved consumers with a high level of consumer innovativeness. This study highlights the importance of the role of personality traits and supports the proposition that of distinction between consumer innovativeness and involvement. This study focuses on the role of personality traits on consumers’ actual electrified vehicle adoption behavior rather than purchase intention.
SWAT modeling of hydrology, sediment and nutrients from the Grand River, Ontario

The Grand River watershed (GRW) is an important agricultural area in Southern Ontario. Land use has been modified by various human endeavors, altering hydrology and increasing export of sediment and nutrients. The objective of this study was to predict spatial and temporal patterns of hydrology, and export of sediment and nutrients from the GRW to Lake Erie using the Soil and Water Assessment Tool (SWAT) model. The Sequential Uncertainty FItting (SUFI2) program was used to calibrate and validate stream flow for years 2001–2010. Calibration and validation of the SWAT model for monthly stream flow at York indicated good model performance ( R 2 , NSE , and PBIAS = 0.64, 0.63 and 7.1 for calibration (2001–2005); = 0.82, 0.74 and 0.2, for validation (2006–2010)). The model was applied to predict sediment and nutrient export from the GRW into Lake Erie. Predicted loading at Dunnville (near the mouth) was 2.3 × 10 5 tonnes y −1 total suspended sediment, 7.9 × 10 3 tonnes y −1 TN, and 2.3 × 10 2 tonnes y −1 TP. This SWAT model can now be used to investigate the relative effects of best management practices, and to forecast effects of climate change, on sustainable water management, hydrology, and sediment and nutrient export to Lake Erie.
Implementing Strategic Sustainable Supply Chain Management

Despite increasing business interest in sustainability in general and in sustainable supply chain management (SSCM), the ability to increase suppliers’ ecological and social performance is generally insufficient for many companies. In this study, we outline an implementation process model for sustainable supply chain management. We do so by synthesizing insights from a review of the sustainable supply chain management and organizational learning literature and a case study with a company aspiring to become a global leader in sustainable lighting. By combining these insights, we find that successful implementation of sustainable supply chain management requires sustainability to be anchored in a company’s vision and integrated into all functions. We also argue that organizational learning, especially learning with external stakeholders such as suppliers, an operational definition of socioecological sustainability among stakeholders, and procedural support for the cocreation of strategic plans for change are vital for achieving a truly sustainable supply chain. This definition and cocreation allow for attention to be directed toward strategic ecological and social practices, along with the joint handling of tradeoffs and economic considerations among stakeholders. As we build a foundation for an SSCM implementation process model, we use a science-based framework for strategic sustainable development. We call for more action-based research to uncover the complex nature of sustainable supply chain management, as there are unique challenges and dynamic relationships in every supply chain.
An Arithmetical-like Theory of Hereditarily Finite Sets

This paper presents the (second-order) theory of hereditarily finite sets according to the usual pattern adopted in the presentation of the (second-order) theory of natural numbers. To this purpose, we consider three primitive concepts, together with four axioms, which are analogous to the usual Peano axioms. From them, we prove a homomorphism theorem, its converse, categoricity, and a kind of (semantical) completeness.
Effect of Ascophyllum nodosum Alga Application on Microgreens, Yield, and Yield Components in Oats Avena sativa L

This paper describes the influence of Ascophyllum nodosum algae on the seeds, microgreens, yield, and yield components of oat Avena sativa cv. Bingo. This article includes the results from three experiments. In one of the experiments, the oat seeds were soaked in a solution of demineralized water with dried comminuted and homogenized algae. For the FT–Raman spectra measurements, a spectrometer with an Nd:YAG laser, with a germanium detector, was used. The results obtained show that an excessively low as well as an excessively high alga concentration did not have an influence on the change in oat composition. Other algae concentrations that were used in these experiments caused significant chemical changes in the oat seeds. For the FT–Raman data, separation of the control from all the oat grains treated with different algae concentrations was possible. The aim of the pot experiment was to determine the effect of the application of algae (in different doses) on the A. sativa green mass of young plants (microgreens). The certified oat seeds, after being soaked in a solution with algae, were planted in the ground. For the chemometric analysis of the oat samples, a Fourier-transform infrared (FTIR) spectrometer device was used. The data were recorded with a viewing diamond with an attenuated total reflection (ATR) crystal plate. The FTIR spectra showed that soaking in an algae suspension affected the germination, general metabolism, and chemical composition of the oats. The use of algae did not change the lipid content of the plant. The three-year field experiment was established by introducing two factors: A. nodosum application (A) and a pre-sowing stimulation with a low-frequency magnetic field (S). The influence of experimental factors on the oat yield and its structure (yield structure components and yield components) was investigated. The beneficial effect of algae on oat yield was demonstrated by improved parameters such as the number and weight of the grains; however, under field conditions, the pre-sowing magnetic field stimulation of seeds did not have a beneficial effect. Various weather conditions also had a great influence on the yield. This study also considered the role of A. nodosum as a biostimulant in plants, and this showed potential under less favorable conditions.