Miracle-dz/UniFAR-FTUs huggingface dataset:
The case of the banking, food and beverages and hotel industries

Introduction Corporate social reporting (CSR) is “the process of communicating the social and environmental effects of organizations’ economic actions to particular interest groups within society and to society at large” (Gray et al., 1987, p. ix). Although CSR has been the subject of substantial academic research for more than two decades, the CSR literature is dominated by empirical studies in the industrialized countries of Western Europe, the USA and Australia. Even international comparative studies of CSR have focused on analyses of the differences and similarities of CSR practices in these countries only (e.g. Ernst and Ernst, 1978; Guthrie and Parker, 1990). It is dangerous to generalize the results of these studies to less developed countries as the stage of economic development is likely to be an important factor affecting CSR practices. Moreover, cultural and national differences are likely to affect accounting practices in general and CSR practices in particular (Mathews, 1993; Perera and Mathews, 1990). Though some improvements have been made (e.g. Chow and Wong-Boren, 1987; Singh and Ahuja, 1983; Teoh and Thong, 1984), there is still a relative paucity of empirical studies on CSR practices in developing and newly industrialized countries. Another shortcoming of existing studies is that with few exceptions (e.g. Gray et al., 1995; Guthrie and Parker, 1989; Hogner, 1982), most of the studies are cross-sectional in nature. As such, it is not possible to trace the development of CSR practices, except by reviewing the literature over time. The purpose of this study is to address the above mentioned imbalances through an examination of corporate social disclosures by Singapore companies in three industries over a ten-year period from 1986 to 1995. Under the strong leadership of the Government, Singapore embarked on an extensive industrialization programme and has attained the status of a newly industrialized country with one of the highest per capita gross national products in Asia. At the same time, CSR has assumed greater importance in the
Modelling the Impact of Interest Rate Crisis

Financial crisis of 2007-2008 changed the assumptions underlying market models theoretically and in practice. Therefore, this paper focuses on modelling the impact of interest rate crisis. The aim is to describe pricing of financial derivatives mainly interest rate swap pricing method used under both pre-and post-crisis period. To model riskless rate/short rate and credit risk as well as to show various basis spreads that characterize post crisis fixed income markets. Riskless rate was modelled by use of a no arbitrage model CIR++ model and CIR model was used to model default intensity. Exact method of simulation was used by assuming that CIR++ model increments follow a noncentral chi-square distribution and model parameters estimated by use of maximum likelihood method. Model parameters were estimated using both pre-and post-crisis 3 months US LIBOR daily market data and compared to analyze the impact of the crisis. For default intensity simulation Euler scheme method was used for the discretization.
A Literature Review on the Relationship between Tax Sharing and Environmental Pollution

China’s economic development has entered a new normal, it becomes primary task to solve environ-mental problems under the current ecological construction. In the framework of intergovernmental fiscal relations characterized by upward shift of tax rights, this paper sorts out the relevant literature on taxation and local govern-ment behavior, focusing on its impact on environmental regulation and environmental pollution, and answering: Why does the seemingly harsh environmental manage-ment system not have a good effect on suppressing pollution?
ELICITORS AND PHYTOTOXINS FROM THE BLACKLEG FUNGUS: STRUCTURE, BIOACTIVITY AND BIOSYNTHESIS

The phytopathogenic fungus Leptosphaeria maculans can cause blackleg disease on crucifers, which results in significant yield losses. Fungal diseases involve interactions between pathogenic fungi and host plants. One aspect of these interactions is mediated by secondary metabolites produced by both fungi and host plants. Phytotoxins and elicitors as well as phytoanticipins and phytoalexins are metabolites produced by fungi and plants, respectively. This thesis describes and discusses the isolation, structure, biological activity and biosynthesis of the secondary metabolites produced by L. maculans. The elicitor-toxin activity bioassay guided isolation of elicitors and phytotoxins produced by L. maculans in a chemically defined medium lead to the isolation of general elicitors, sirodesmin PL (165) and deacetylsirodesmin PL (166), and specific elicitors, cerebrosides C (14) and D (31) from minimum medium (MM) culture under standard conditions. The known phytotoxins sirodesmin PL (165) and deacetylsirodesmin PL (166) induced the production of phytoalexin spirobrassinin (122) in both resistant plant species (brown mustard, Brassica juncea cv. Cutlass) and susceptible plant species (canola, B. napus cv. Westar). A mixture of cerebrosides C (14) and D (31) induced the production of the phytoalexin rutalexin (127) in resistant plant species (brown mustard, B. juncea cv. Cutlass) but not in susceptible plant species (canola, B. napus cv. Westar). New metabolites leptomaculins A-E (267-269, 272 and 274) and deacetylleptomaculins C-E (270, 273 and 275) were isolated from elicitor-phytotoxin active fractions but did not display detectable elicitor activity or phytotoxicity after purification. New metabolites maculansins A (299) and B (300), which were not detected in cultures of L. maculans incubated in MM, were isolated from cultures of L. maculans incubated in potato dextrose broth (PDB). Maculansins A (299) and B (300) displayed higher phytotoxicity on brown mustard than on canola and white mustard (Sinapis alba cv. Ochre) but did not elicit detectable production of phytoalexins in either brown mustard or canola. Metabolite 2,4-dihydroxy-3,6-dimethylbenzaldehyde (212) was produced in higher amount in cultures of L. maculans incubated in PDB than in MM and displayed strong inhibition effect on the root growth of brown mustard and canola.
Constrained Monopoly Pricing with Endogenous Participation

We present a flexible model of monopoly nonlinear pricing with endogenous participation decisions of heterogeneous consumers. We make use of the moments that define the few self-selecting tariff options that are commonly used to implement the optimal nonlinear tariff to estimate how demand and cost variables affect the pricing strategies offered by incumbent monopolists in several early U.S. local cellular telephone markets through the different elements of the theoretical model: marginal costs, average price sensitivity of demand, indexing parameters governing the distribution of the two-dimensional type components, support of the distribution of types, and costs associated to the commercialization of tariff options. Intuitively, the sources of identification are the position and shape of each tariff offered by monopolists, the actual number and features of the tariff options used to implement them, as well as a measure of market penetration in each cellular market during the first and last quarter of monopoly regime. We use our model and the structural estimates to provide a performance comparison (profit+welfare) of nonlinear tariffs relative to linear (uniform), optimal two-part, Coasian marginal cost-plus fixed fee, and flat tariffs. We furthermore address the potential welfare gains of implementing universal service requirements.
Slack and Excessive Loading Avoidance in n-Tendon Continuum Robots

In this work, two tendon tension loading distributions (fixed and moving) are designed to prevent undesired slack and excessive loading in tendons of continuum manipulators. For any given beam configuration, the algorithms utilize the proposed loading distributions to find a new beam configuration as well as base displacement to control the orientation or position of the $n$ -tendon continuum robot. The algorithms account for the bending and axial compliance of the manipulator as well as tendon compliance. Numerical results are provided to demonstrate the orientation and position control algorithms under fixed or moving loading distributions. A 6-tendon continuum robot system is employed to experimentally evaluate the effectiveness and accuracy of the proposed control algorithms. Multiple experiments are carried out and results are reported. The results verify the performance of the proposed control algorithms in avoiding slack and excessive loading in tendons and controlling the orientation and position of continuum structures.
Coping with savanna seasonality: comparative daily activity patterns of African ungulates as revealed by GPS telemetry

Daily activity schedules and time budgets reveal how animals cope with changing environmental conditions in securing food and evading enemies. Theory suggests that animals in populations limited by food availability should be energy maximizers in their foraging time allocation, while those regulated by predation should minimize their mobile activity levels. We compared daily and seasonal variation in activity states among three species of grazing ungulates coexisting in the same region of Kruger National Park, South Africa, and for one of these species between regions differing in rainfall. These grazers differed in body size and digestive physiology, potentially affecting their activity patterns. Hourly movement rates recorded by GPS telemetry were partitioned among activity states by applying independent mixture models. All three species showed activity peaks during the early morning and late afternoon, while resting prevailed pre-dawn as well as through midday. African buffalo showed the strongest diel variation in activity and greatest depression of midday activity, consistent with their large body size. Buffalo maintained similar levels of activity through the day and night, while zebra and sable antelope showed higher levels of diurnal than nocturnal activity. During the late dry season, zebra and coexisting sable, but not buffalo, showed elevated foraging and total mobile activity. Zebra devoted more time to foraging than both ruminants, consistent with greater food intake requirements for hindgut digestion. Sable antelope inhabiting the region with higher rainfall showed similar activity levels to the sable herd in the drier area, but slower rates of movement while foraging and travelling and less elevation in foraging time towards the end of the dry season. Observed patterns indicated subtly changing interplay among different constraints bearing on activity patterns over the diel and seasonal cycles, especially those related to digestive physiology. Simplistic concepts of energy maximization or time minimization were not supported.
Mechanisms of disease‐induced extinction

Parasites are important determinants of ecological dynamics. Despite the widespread perception that parasites (in the broad sense, including microbial pathogens) threaten species with extinction, the simplest deterministic models of parasite dynamics (i.e. of specialist parasites with density-dependent transmission) predict that parasites will always go extinct before their hosts. We review the primary theoretical mechanisms that allow disease-induced extinction and compare them with the empirical literature on parasitic threats to populations to assess the importance of different mechanisms in threatening natural populations. Small pre-epidemic population size and the presence of reservoirs are the most commonly cited factors for disease-induced extinction in empirical studies.
Increasing Enrollment by Optimizing Scholarship Allocations Using Machine Learning and Genetic Algorithms

Eﬀectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management strategies. In this project, we use data at a large, public university to increase their student enrollment. We do this by ﬁrst predicting the enrollment of admitted ﬁrst-year, ﬁrst-time students using a suite of machine learning classiﬁers (AUROC = 0.85). We then use the results from these machine learning experiments in conjunction with genetic algorithms to optimize scholar-ship disbursement. We show the eﬀectiveness of this approach using real-world enrollment metrics. Our optimized model was expected to increase enrollment yield by 15.8% over previous disbursement strategies. After deploying the model and conﬁrming student enrollment decisions, the university actually saw a 23.3% increase in enrollment yield. This resulted in millions of dollars in additional annual tuition revenue and a commitment by the university to employ the method in subsequent enrollment cycles. We see this as a successful case study of how educational institutions can more eﬀectively leverage their data.
Over Diagnosed or Over Looked? The Effect of Age at Time of School Entry on Students Receiving Special Education Services

There is growing evidence that school starting age impacts children's likelihood of receiving special education services, but less is known about variations in this effect. Using a regression discontinuity design, I found that the youngest students in a kindergarten cohort are 40% more likely (p < .001) to be placed in special education than are the oldest students, and that this effect persists through eighth grade. I found little evidence of heterogeneity by gender, race, or socioeconomic status, but some suggestive evidence that the effect is particularly great for White boys in early grades and for Black girls in the later elementary grades. I also found exploratory evidence that this effect is largest in schools with kindergarten cohorts that vary widely in age. These findings add new evidence to support policies to reduce age-induced bias in early special education placements, particularly those that address variation in this effect across students and schools.
Associations of Protective and Acquisitive Self-monitoring with Consumer Attitudes and Behaviors

Acquisitive self-monitors are motivated by gaining social standing (getting ahead, standing out), whereas protective self-monitors are driven by avoiding social disapproval (getting along, blending in; Wolfe et al., 1986). Extending prior research on these orientations and their associations with consumer attitudes and behaviors, participants in Studies 1a (MTurk; N = 156) and 1b (undergraduates; N = 143) completed the Self-Monitoring Scale (Snyder, 1974) and various consumer scales. In these two studies, regression results revealed support for the hypotheses that protective self-monitoring was related to communal consumerism, sociallyconscious consumerism, frugality, and conspicuous consumption, whereas agentic consumerism and self-interested values were related to acquisitive self-monitoring. Study 2 (MTurk; N = 275) used experimental manipulation of advertisements to examine differential ad appeals tailored to protective, acquisitive, and low self-monitoring (bivariate model). Moderation analyses showed protective self-monitoring to be a significant predictor of protective ad preference, whereas no specific ad preferences were found with acquisitive self-monitoring. Overall, results suggest that associations of self-monitoring and consumer behaviors are driven by protective self-monitoring rather than acquisitive self-monitoring. Implications (e.g., market research), limitations (e.g., ad strength, convenience samples), and future directions (e.g., examining multivariate appeals for low self-monitoring) are discussed.
First Steps Towards NLP-based Formative Feedback to Improve Scientific Writing in Hebrew

As scientific writing is an important 21st century skill, its development is a major goal in high school science education. Research shows that developing scientific writing skills requires frequent and tailored feedback, which teachers, who face large classes and limited time for personalized instruction, struggle to give. Natural Language Processing (NLP) technologies offer great promise to assist teachers in thisprocess by automating some of the analysis. However, in Hebrew, the use of NLP in computer-supported writing instruction was until recently hindered by the lack of publicly available resources. In this paper, we present initial results from a study that aims to develop NLP-based techniques to assist teachers in providing personalized feedback in scientific writing in Hebrew, which might be applicable to otherlanguages as well. We focus on writing inquiry reports in Biology, and specifically, on the task of automatically identifying whether the report contains a properly de? ned research question. This serves as a proof-of-concept of whether we can build a pipeline that identifies major components of the report and match them to a predefined grading rubric. To achieve this, we collected several hundreds of reports, annotated them according to a grading rubric to create a supervised data set, and built a machine-learning algorithm that uses NLP-based features. The results show that our model can accurately identify the research question or its absence.To the best of our knowledge, this is the first paper to report on the application of Hebrew NLP for formative assessment in K-12 science education.
Changes in the acoustic behavior of resident bottlenose dolphins near operating vessels

Maritime traffic is an issue of major ecological concern, and vessel noise may be an important source of disturbance for coastal cetaceans. In the Sado estuary, Portugal, core habitat areas of a small resident population of bottlenose dolphins (Tursiops truncatus) overlap with routes of intense maritime traffic, which presents an opportunity to assess vocal responses of these dolphins to specific vessel noise sources. Field recordings of dolphin vocalizations were made from April to November 2011, using a calibrated system. Dolphin behavior and group size were recorded, as well as the operating boat condition (no boats or specific boat type) in a 1,000 m radius. Spectral analyses of vocalizations allowed the categorization and quantitative analysis of echolocation click trains and social calls, including whistles. Mean overall call rates decreased significantly in the presence of operating vessels. Creaks (fast click trains) were significantly reduced in the presence of ferry boats. Significant differences were also observed in the whistles' minimum, maximum, and start frequencies. These changes in call emission rates and temporary shifts in whistles characteristics may be a vocal response to the proximity of operating vessels, facilitating communication in this busy, noisy estuary.
Design of a Novel One Transistor-Dram Based on Bulk Silicon Substrate

In this work, we propose a novel device based on bulk silicon substrate and use it as a dynamic random access memory (DRAM) with TCAD simulation. The operation principle of this device is similar to that of Z2-FET which was demonstrated previously in SOI substrate. In our device, LDD doping and gate control are combined to build up the carrier injection barriers which enable feedback mechanism. The designed device shows similar sharp switch and gate-controlled hysteresis in its output characteristics. It is further demonstrated for DRAM application without need of extra capacitor. The DRAM operation shows high speed and reasonably long retention time.
Middleware for Work Support in Industrial Contexts (MiWSICx)

It is generally acknowledged that technological innovation is leading to an increase in the complexity of industrial work. Hence, work assistance has emerged as an important theme in the context of cyber-physical production systems and Industry 4.0 to assist workers in assembly, logistics, maintenance and supervision. Recent research in this domain has focused on demonstrating assistance applications using mobile computing devices such as tablets, smartphones, AR/VR glasses and wearables, but the aspects of technology induced complexity in industrial work - distribution , concurrency, information complexity , and variability of information interaction , and their subsequent effect on human workers is yet to be tackled. This paper has two core contributions: first, it reframes the problem of complex industrial work through activity theory , which leads to a conceptual model that couples human information needs to interactive artefacts within an activity context . Second, the problem of assistance is viewed as managing information flow between multiple devices grouped into fluid and adaptive activity contexts, managed by MiWSICx, (Middleware for Work Support in Industrial Contexts) a novel, distributed middleware designed using the actor model of concurrent computation.
Managing Human Resources In A Higher Education Institution: Managing The Lecturers

This study aims at discussing the management of human resources (HR) at Muhammadiyah University, Jakarta, comprises HR planning, recruitment, selection, training and development, compensation, and performance evaluation activities. This study uses a qualitative method with a case study approach. Data collected from document studies, interviews and observation. The results of the study show that : (1) HR Planning is unstructured and has not been centralized yet, (2) recruitment activities sti ll mostly emphasized from within the internal resources (3) interview-based selections is applied and unsupported by written tests, (4) training and development is carried out by each department without set guidelines, (5) centralized compensation system is conducted by the university, and (6) performance appraisal of lecturers is conducted through evaluation by students in the absence of any official policy. This study recommends the necessities for external and internal analysis (SWOT analysis), routine coordination and evaluation during plan developments, and establishment of policy and guidelines for managing the lecturers of the university. The study raises an interesting case of HR management in an old Islamic-based university in Indonesia. Moreover, this study proposes information system flow model of HRM for Muhammadiyah University of Jakarta.
A Uniform Logic of Information Update ∗

Unlike standard modal logics, many dynamic epistemic logics are not closed under uniform substitution. A distinction therefore arises between the logic and its substitution core , the set of formulas all of whose substi-tution instances are valid. The classic example of a non-uniform dynamic epistemic logic is Public Announcement Logic ( PAL ), and a well-known open problem is to axiomatize the substitution core of PAL . In this paper we solve this problem for PAL over the class of all relational models with inﬁnitely many agents, PAL - K ω , as well as standard extensions thereof, e.g., PAL - T ω , PAL - S4 ω , and PAL - S5 ω . We introduce a new Uniform Public Announcement Logic ( UPAL ), prove completeness of a deductive system with respect to UPAL semantics, and show that this system axiomatizes the substitution core of PAL .