Miracle-dz/UniFAR-FTUs huggingface dataset:
Earth and Planetary Science Letters

We investigate the initiation phase of the 2014 M w 8.1 Iquique earthquake in northern Chile. In particular, we focus on the month preceding the mainshock, a time period known to exhibit an intensiﬁcation of the seismic and aseismic activity in the region. The goal is to estimate the time-evolution and partitioning of seismic and aseismic slip during the preparatory phase of the mainshock. To do so, we develop a Bayesian inversion scheme to infer the spatio-temporal evolution of pre-slip from position time-series along with the corresponding uncertainty. To extract the aseismic component to the pre-seismic motion, we correct geodetic observations from the displacement induced by foreshocks. We ﬁnd that aseismic slip accounts for ∼ 80 percents of the slip budget. That aseismic slip takes the form of a slow-slip events occurring between 20 to 5 days before the future mainshock. This time-evolution is not consistent with self-accelerating fault slip, a model that is often invoked to explain earthquake nucleation. Instead, the slow-slip event seems to have interacted with the foreshock sequence such that the foreshocks contributed to the arrest of aseismic slip. In addition, we observe some evidence of late self-accelerating slip, but associated with large uncertainties, making it diﬃcult to assess its reliability from our observations alone. © 2022 Elsevier B
Single-carrier 2.5-Tb/s transmission using CSRZ-OTDM with 8×4 digital calibrator

We demonstrate a 224-GBaud CSRZ-OTDM optical transmitter achieving net bit rates of 2.59 Tb/s/ λ back-to-back and 2.52 Tb/s/ λ after 80-km SSMF transmission. An 8×4 digital calibrator effectively compensates for spurious distortions. ©2023 The Author(s)
Firm performance impacts of digitally enabled supply chain integration capabilities

Best practice exemplars suggest that digital platforms play a critical role in managing supply chain activities and partnerships that generate performance gains for firms. However, there is limited academic investigation on how and why information technology can create performance gains for firms in a supply chain management (SCM) context. Grant's (1996) theoretical notion of higher-order capabilities and a hierarchy of capabilities has been used in recent information systems research by Barua et al. (2004), Sambamurthy et al. (2003), and Mithas et al. (2004) to reframe the conversation from the direct performance impacts of IT resources and investments to how and why IT shapes higher-order process capabilities that create performance gains for firms. We draw on the emerging IT-enabled organizational capabilities perspective to suggest that firms that develop IT infrastructure integration for SCM and leverage it to create a higher-order supply chain integration capability generate significant and sustainable performance gains. A research model is developed to investigate the hierarchy of IT-related capabilities and their impact on firm performance. Data were collected from 110 supply chain and logistics managers in manufacturing and retail organizations. Our results suggest that integrated IT infrastructures enable firms to develop the higher-order capability of supply chain process integration. This capability enables firms to unbundle information flows from physical flows, and to share information with their supply chain partners to create information-based approaches for superior demand planning, for the staging and movement of physical products, and for streamlining voluminous and complex financial work processes. Furthermore, IT-enabled supply chain integration capability results in significant and sustained firm performance gains, especially in operational excellence and revenue growth. Managerial initiatives should be directed at developing an integrated IT infrastructure and leveraging it to create process capabilities for the integration of resource flows between a firm and its supply chain partners.
SoK: Security of Programmable Logic Controllers

Billions of people rely on essential utility and manufacturing infrastructures such as water treatment plants, energy management, and food production. Our dependence on reliable infrastructures makes them valuable targets for cyberattacks. One of the prime targets for adversaries attacking physical infrastructures are Programmable Logic Controllers (PLCs) because they connect the cyber and physical worlds. In this study, we conduct the first comprehensive systematization of knowledge that explores the security of PLCs: We present an in-depth analysis of PLC attacks and defenses and discover trends in the security of PLCs from the last 17 years of research. We introduce a novel threat taxonomy for PLCs and Industrial Control Systems (ICS). Finally, we identify and point out research gaps that, if left ignored, could lead to new catastrophic attacks against critical infrastructures.
High-Performance Work Systems in the Australian Higher Education Sector: A Critical Review and Future Research Agenda

The advocates of the configurational perspective view high-performance work systems (HPWS) as a complementary bundle of strategically driven and contextually specified human resource management practices that leads to employee and organisational performance through positive attitudinal outcomes. A study of the contemporary context could better configure the HPWS bundle for any industry undergoing significant transitions. Australia's higher education (HE) sector has observed significant changes since 2009 that have potentially redefined how human resource (HR) management practices interact and counteract within the system. No study to date has explored these changes and their impact on the HPWS configurations in the Australian HE industry. This study explores the changes in the Australian HE sector in recent years and identifies their strategic HR implications through a systematic review of the literature. The result will benefit the key decision-makers to configure the bundle of HPWS by confirming the external and internal fit within the transitional context of the Australian HE sector. Future researchers can use the proposed framework to design empirical studies in similar contexts.
Air–sea fluxes of greenhouse gases and oxygen in the northern Benguela Current region during upwelling events

Abstract. Ground-based atmospheric observations of CO2, δ(O2∕N2), N2O, and CH4 were used to make estimates of the air–sea fluxes of these species from the Lüderitz and Walvis Bay upwelling cells in the northern Benguela region, during upwelling events. Average flux densities (±1σ) were 0.65±0.4 µmol m−2 s−1 for CO2, -5.1±2.5 µmol m−2 s−1 for O2 (as APO), 0.61±0.5 nmol m−2 s−1 for N2O, and 4.8±6.3 nmol m−2 s−1 for CH4. A comparison of our top-down (i.e., inferred from atmospheric anomalies) flux estimates with shipboard-based measurements showed that the two approaches agreed within ±55 % on average, though the degree of agreement varied by species and was best for CO2. Since the top-down method overestimated the flux density relative to the shipboard-based approach for all species, we also present flux density estimates that have been tuned to best match the shipboard fluxes. During the study, upwelling events were sources of CO2, N2O, and CH4 to the atmosphere. N2O fluxes were fairly low, in accordance with previous work suggesting that the evasion of this gas from the Benguela is smaller than for other eastern boundary upwelling systems (EBUS). Conversely, CH4 release was quite high for the marine environment, a result that supports studies that indicated a large sedimentary source of CH4 in the Walvis Bay area. These results demonstrate the suitability of atmospheric time series for characterizing the temporal variability of upwelling events and their influence on the overall marine greenhouse gas (GHG) emissions from the northern Benguela region.
Conflict Management Styles as Predictors of Organizational Commitment in University Teachers

Academicians need to learn and practice constructive conflict management by using appropriate and effective conflict management styles (McKibben, 2017). The present study investigated the impact of conflict handling strategies in building commitment with their institutions among university teachers by employing a cross-sectional research. The participants included 400 university teachers ( M age = 38, SD = 8.74) serving both in public and private sector institutions situated in Punjab and Federal Capital Islamabad by employing purposive sampling strategy. Their opinion was sought by administering Rahim Organizational Conflict Inventory (Rahim, 1983) and Organizational Commitment Questionnaire (Jaros, 2007) and the data collection period was of one year. The findings revealed that teachers scoring higher on integrating, obliging, and compromising tend to have a stronger commitment to their organizations. A hierarchical regression analysis showed that integrating style strongly predicted teachers’ commitment to their organizations. The styles to dominate and avoid conflict based situations turned out to be non-significant predictors of organizational commitment. The study has important implications for teaching faculty of universities in handling their conflicts with chairpersons of academic departments.
A comparative analysis of methodologies for database schema integration

One of the fundamental principles of the database approach is that a database allows a nonredundant, unified representation of all data managed in an organization. This is achieved only when methodologies are available to support integration across organizational and application boundaries. Methodologies for database design usually perform the design activity by separately producing several schemas, representing parts of the application, which are subsequently merged. Database schema integration is the activity of integrating the schemas of existing or proposed databases into a global, unified schema. The aim of the paper is to provide first a unifying framework for the problem of schema integration, then a comparative review of the work done thus far in this area. Such a framework, with the associated analysis of the existing approaches, provides a basis for identifying strengths and weaknesses of individual methodologies, as well as general guidelines for future improvements and extensions.
Enhancing Productivity in Rice-Based Cropping Systems

In India, the rice-based cropping system is a major food production system with rice as the first food crop. The cereal-based cropping system is low-yielding and highly nutrient exhaustive resulting in the declining of soil fertility. Summer/pre kharif fallowing leaves on the land fallow for entire season and production of the cropping system is declined. Hence, crops that can improve the fertility status should be included in the cropping system. Development of short duration thermal insensitive rice varieties has encouraged multiple cropping involving a wide range of crops. Diversification of rice-based cropping systems with inclusion of pulses/legumes and oilseeds in summer fallows is one of the options for horizontal expansion, as they are known to improve soil organic matter through biological nitrogen fixation, root exudates, leaf shedding and higher below ground biomass. The strategy for higher yields in the cropping system should be formulated using the combined application of organics, inorganics and biofertilizers coupled with the inclusion of crops in summer fallows for sustainable yields and preservation of soil health.
: Hepatoprotective activity of Artocarpus heterophyllus Lam. leaf petiole through antioxidant

Artocarpus heterophyllus Lam. is the common jackfruit tree belongs to family Moraceae. The protective role of leaf petiole part of the plant was investigated in experimental hepatotoxicity. Antioxidant enzyme activity was investigated in acetaminophen intoxicated rat liver treated with methanol extract of Artocarpus heterophyllus . Phytochemical analysis and the antioxidant property of successive hexane, ethyl acetate and methanol extracts of Artocarpus heterophyllus showed highest activity with methanol extract ( Artocarpus heterophyllus ). Superoxide dismutase, catalase (antioxidant enzymes) and glutathione showed significant increase in rats with oral administration of Artocarpus heterophyllus compared to the acetaminophen treated group. The degree of hepatoprotection was assessed by the activity of aspartate amino transferase, alanine aminotransferase, alkaline phosphatase, lactate dehydrogenase and gamma glutamyl transpeptidase. A dose dependant protective effect of Artocarpus heterophyllus (200 mg/kg body weight, 400 mg/kg body weight) against acetaminophen-induced hepatotoxicity in albino rats was identified. Histopathological evaluation of the liver confirmed the hepatoprotective function of methanol extract of Artocarpus heterophyllus as evident in biochemical evaluations. The results of the present study suggest the potential use of leaf petiole of Artocarpus heterophyllus in the treatment of liver disease due to its ability to protect as an antioxidant.
Fisher Vectors for Fine-Grained Visual Categorization

The bag-of-visual-words (BOV) is certainly the most popular image representation to date and it has been shown to yield good results in various problems including Fine-Grained Visual Categorization (FGVC) [3, 4]. Our contribution is to show that the Fisher Vector (FV) – which describes an image by its deviation from an “average” model – is an excellent alternative to the BOV for the FGVC problem. In this extended abstract we ﬁrst provide a brief introduction to the FV. We then present theoretical as well as practical motivations for using the FV for FGVC. We ﬁnally provide experimental results on four ImageNet subsets: fungus, ungulate, vehicle and ImageNet10K. Compared to [4] which uses spatial pyramid (SP) BOV representations, we report signiﬁcantly higher classiﬁcation accuracies. For instance, on ImageNet10K we report 16.7% vs 6.4% top-1 accuracy (a 160% relative improvement).
Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation within Factor Graphs

The factor graph framework is a convenient modeling technique for robotic state estimation and sensor fusion where states are represented as nodes and measurements are modeled as factors. In designing a sensor fusion framework using factor graphs for legged robots, one often has access to visual, inertial, encoders, and contact sensors. While visualinertial odometry has been studied extensively in this framework, the addition of a preintegrated contact factor for legged robots has been proposed recently. In this work, to cope with the problem of switching contact frames which was not addressed previously, we propose a hybrid contact preintegration that does not require the addition of frequently broken contact factors into the estimation factor graph. This paper presents a novel method for preintegrating contact information through an arbitrary number of contact switches. The proposed hybrid modeling approach reduces the number of required variables in the nonlinear optimization problem by only requiring new states to be added alongside camera or selected keyframes. This method is evaluated using real experimental data collected from a Cassie-series robot where the trajectory of the robot produced by a motion capture system is used as a proxy for ground truth data. The evaluation shows that inclusion of the proposed preintegrated hybrid contact factor alongside visualinertial navigation systems improves robustness to vision failure as well as the estimation accuracy for legged robots while its generalization makes it more accessible for legged platforms.
A countrywide multi-ethnic assessment of local communities’ perception of climate change in Benin (West Africa)

Climate change poses significant challenges to biodiversity, food security, water availability and health, especially in Africa. Research within local communities can lead to a better understanding of the observed changes in climate, and help to find more appropriate strategies for dealing with them. A number of studies have been carried out in West Africa, but most focus on Sahelian countries and all focus on a single area with one or two ethnic groups. Therefore, to determine whether a countrywide multi-ethnic assessment could provide more accurate information, we studied perceptions of climate change in local communities in Benin. Two focus groups (men and women) were carried out in nine villages. Local farmers and herders were asked about the changes in climate they have observed, the effects of these changes, and how they have adapted to them. Observed changes in climate followed a latitudinal trend, and were in agreement with available climatic studies. Some of the observed changes in climate had not been reported before for this latitude in West Africa. The effects of these climatic changes and the adaptive strategies used differed between areas and ethnic groups. Some adaptive strategies were only used by some ethnic groups. We found that the main obstacles preventing communities from adopting new strategies were unavailability of credit, lack of improved seeds and insufficient information. The findings support the conclusion that country-level multi-ethnic assessments provide key information for both climate change research and policy development.
COLLECTON: DATA AND

This paper presents how we enhanced the accessibility and utility of historical linguistic data in the project Bullinger Digital . The project involved the transformation of 3,100 letters, primarily available as scanned PDFs, into a dynamic, fully digital format. The expanded digital collection now includes 12,000 letters, 3,100 edited, 5,400 transcribed
An Ethical Study of Generative AI from the Actor-Network Theory Perspective

The widespread use of Generative Artificial Intelligence in the innovation and generation of communication content is mainly due to its exceptional creative ability, operational efficiency, and compatibility with diverse industries. Nevertheless, this has also sparked ethical problems, such as unauthorized access to data, biased decision-making by algorithms, and criminal use of generated content. In order to tackle the security vulnerabilities linked to Generative Artificial Intelligence, we analyze ChatGPT as a case study within the framework of Actor-Network Theory. We have discovered a total of nine actors, including both human and non-human creatures. We examine the actors and processes of translation involved in the ethical issues related to ChatGPT and analyze the key players involved in the emergence of moral issues. The objective is to explore the origins of the ethical issues that arise with Generative Artificial Intelligence and provide a particular perspective on the governance of Generative Artificial Intelligence.
Romanian Diacritics Restoration Using Recurrent Neural Networks

Diacritics restoration is a mandatory step for adequately processing Romanian texts, and not a trivial one, as you generally need context in order to properly restore a character. Most previous methods which were experimented for Romanian restoration of diacritics do not use neural networks. Among those that do, there are no solutions specifically optimized for this particular language (i.e., they were generally designed to work on many different languages). Therefore we propose a novel neural architecture based on recurrent neural networks that can attend information at different levels of abstractions in order to restore diacritics.
Flexible Spatio-Temporal Energy-Efficient Runtime Management

Heterogeneous multi-core architectures, such as Arm’s big.LITTLE and DynamIQ, feature multiple core types with the same ISA but varied performance-energy characteristics. These are increasingly adopted in embedded systems as they enable dynamic application mapping, balancing performance with energy efficiency. While Hybrid Application Mapping (HAM) approaches have gained popularity in systems running dynamic workloads, most solutions yield spatial mappings and neglect application migrations in output schedules, substantially limiting the solution space. This work introduces STEM and FFEMS, two algorithms utilizing the temporal aspect with job reconfigurations to generate “flexible” spatio-temporal mappings. STEM leverages Memetic Algorithms (MAs), while FFEMS uses fast greedy heuristics. Our evaluation on two heterogeneous multi-core platform models demonstrates that the flexible structure of the spatio-temporal mappings significantly improves the schedulability. On workloads from automotive and multimedia domains, STEM finds the most energy-efficient solutions, but its large overhead makes it unsuitable for use in runtime systems. In contrast, FFEMS exhibits an outstanding balance between performance and runtime overhead: Given similar runtime overhead as MMKP-MDF, the state-of-the-art approach, FFEMS schedules up to 16% more test cases. Its “tail-switch” optimization further improves energy efficiency, though with increased overhead, which is still acceptable within runtime systems.
Building hybrid machine translation systems by using an EBMT preprocessor to create partial translations

This paper presents a hybrid machine translation framework based on a preprocessor that translates fragments of the input text by using example-based machine translation techniques. The preprocessor resembles a translation memory with named-entity and chunk generalization, and generates a high quality partial translation that is then completed by the main translation engine, which can be either rule-based (RBMT) or statistical (SMT). Results are reported for both RBMT and SMT hybridization as well as the preprocessor on its own, showing the effectiveness of our approach.
A Macroeconomic Model with Financially Constrained Producers and Intermediaries

We evaluate the quantitative effects of macroprudential policy. To do so, we solve a general equilibrium model with three types of agents and a government. Borrowerentrepreneurs produce output financed with long-term debt issued by financial intermediaries, subject to a leverage constraint. Intermediaries fund these loans combining deposits and their own equity, and are subject to a regulatory capital constraint. Savers provide funding to banks and to the government. Both entrepreneurs and banks make optimal default decisions. The government issues debt to finance budget deficits and to pay for bank rescue operations. We solve for macroeconomic quantities, the price of capital, the yield on safe bonds, and the credit spread. We study how financial and non-financial recessions differ, show that high credit spreads forecasts future declines in economic activity, and study macro-prudential policies. Policies that limit corporate leverage and financial leverage reduce welfare. Their benefits for financial and macro-economic stability are outweighed by the costs from a smaller-sized economy. The two types of macroprudential policies have different implications for the wealth distribution. JEL: G12, G15, F31.