Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Customer Satisfaction lead to Accurate Earnings Forecasts

This paper examines the usefulness of customer satisfaction to analysts when preparing their earnings forecasts. We draw on theory in marketing to predict how customer satisfaction should be associated with earnings forecasts and forecast errors. We assembled a dataset of companies studied in the American Customer Satisfaction Index (University of Michigan), which also appear on the Institutional Brokers Estimate System (I/B/E/S) files. By combining these sources, we were able to analyze the forecast errors of 1,875 analysts following 90 companies yielding 8,034 year-firm-analyst observations. We control for factors known to influence the earnings forecasts, such as firm profitability and risk, as well as potential unobservable factors using a Mixed-effects regression. We find that customer satisfaction has a negative association with the analysts' forecast errors because it allows analysts forecasts to be closer to the business reality. The influence of customer satisfaction varies across sectors. Specifically, we found that in the Information technology sector (i.e. Computer, the Internet Software & Services - e.g. EBay), customer satisfaction has the largest negative impact on earnings forecast errors. In sum, our findings suggest that analysts that neglect customer satisfaction information may deprive themselves of an important proxy of non-financial information, specifically in the information technology sector.
Improved selection criteria for H II regions, based on IRAS sources

We present new criteria for selecting HII regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an HII region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of HII region candidates in theMilkyWay. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known HII regions, which serve as the HII region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H II region sample. Amachine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is log (F-60/F-12) >= (-0.19 x log (F-100/F-25) + 1.52), with detections at 60 and 100 mu m. This selects 3041 HII region candidates from the IRAS PSC. We find that IRAS HII region candidates show evidence of evolution on the two-colour diagram. Merging the WISE HII catalogue with IRAS HII region candidates, we estimate a lower limit of approximately 10 200 for the number of HII regions in the Milky Way.
Market orientation and Company Performance: A study of Selected Japanese and Sri Lankan Companies

There have been a few empirical studies on the relationship between market orientation and business performance of companies in Japan and Sri Lanka. Past studies have found and confirmed market orientation can influence on business performance. The present study investigated and reported that there is a positive relationship between these two variables in both countries. The results from this study suggest that to maintain the higher level of market orientation, both Japanese and Sri Lankan companies should pay more attention on top management emphasis on market orientation and inter departmental connectedness. Notably, Sri Lankan companies should reduce the level of centralization which is likely to enhance market orientation.
Holistic System Design: The Oncology Carinthia Study

Health‐care systems all over the world are facing a formidable challenge. The issue is providing an integral kind of care, with the patient at the centre, rather than technology or doctors. Our research question is: How must health‐care systems be designed to provide holistic, patient‐centred care, at excellent quality and bearable cost? The main topic of this chapter is organization. This is a transdisciplinary, socio‐technical undertaking with far‐reaching implications. Organizational innovation is needed, and it can yield better and more abundant fruits than mere technological creations can. The purpose of this chapter is to explore an exemplar of a long‐term process aimed at achieving a holistic system design. The case is from health care. We trace back the process by which a comprehensive oncological care system was built in the Austrian province of Carinthia, with Klagenfurt as its capital. The study covers a period of roughly 30 years, until 2015. It reports on strong successes, but also some downsides along the way. The chapter delivers several counterintuitive insights and powerful lessons for both practitioners and insights.
Application of Taguchi Method to Study Morphological Evolution of TiO2 Nanotubes Obtained Via Anodization Process

The growth of titanium dioxide nanotubes (TiO2) via anodization process depends on the controlling parameters such as applied potential, anodization time, and electrolyte composition. In the present work, the Taguchi method was applied to evaluate statistically the influence of the anodization parameters on the morphology of anodized TiO2 films. Mixture of ethylene-glycol and glycerol was used as an electrolyte and the settings of the experimental design were parameterized on the basis of four important anodization factors consisting of chemical pretreatment, amount of fluoride, water content and applied potential. Samples were characterized by XRD and FEG-SEM. Based on 4 variables at 3 different settings, full factorial plan requires 34 = 81 tests. In this work the experiment was designed on the basis of an L9 (34) orthogonal array (4 variables, 3 levels, 9 tests). The optimum conditions were found on the basis of smaller-is-better and larger-is-better analyses. The signal-to-noise ratio was employed to find optimal process parameters levels and to analyze the influence of these parameters on the tubular length, internal and external diameters and formation of nanograss on the film surface. Hence, it is clearly shown that the performance of TiO2 nanotubes can be evaluated by the Taguchi method.
Novel approach for a cerium-based highly-efficient catalyst with excellent NH3-SCR performance

A highly-efficient NH3-SCR catalyst, CeO2/WO3–TiO2, was prepared by a novel stepwise precipitation approach. This catalyst showed excellent catalytic performance, with superior low-temperature activity, high N2 selectivity and a broad operational temperature window. Furthermore, the CeO2/WO3–TiO2 catalyst could perform well even under an extremely high space velocity condition of 1 000 000 h−1.
“Relevance of corporate environmental reports produced by listed South African companies”

The broad aim of this research is to assess the relevance of environmental reports produced by the Top 100 listed South African (T100LSA) companies. The study is motivated by a lack of research on the relevance of environmental reports in South Africa, given the dramatic increase in the number of companies producing these reports as well as the expansion of the volumes of the reports produced. A content analysis of environmental reports contained in the Integrated Annual Reports (IARs), sustainability reports and companies’ corporate websites is conducted using a control list. The findings of the study reveal that in general, the environmental reports produced by the T100LSA companies are relevant as most companies have disclosed how they select stakeholders for engagement, their methods of engagement, engagement process and outcomes and how content reported on is selected. In addition, the companies have disclosed how they address and respond to key stakeholders’ concerns as well as their initiatives to encourage stakeholders to participate in the companies’ activities. Furthermore the companies disclose their general performance indicators. However, there is a need for improvement in the disclosure of metric to quantify the effectiveness of the stakeholder engagement and reference to GRI sector specific indicators when selecting content to report on. More importantly, there is a need to improve on the use of on-line features to enhance relevance of the reports such as encouraging users to be part of the writing process by enabling them to edit, analyze and share the reported information, and tracking their use of on-line reports.
N ov 2 01 6 Knowing Values and Public Inspection

We present a basic dynamic epistemic logic of “knowing the value”. Analogous to public announcement in standard DEL, we study “public inspection”, a new dynamic operator which updates the agents’ knowledge about the values of constants. We provide a sound and strongly complete axiomatization for the single and multi-agent case, making use of the well-known Armstrong axioms for dependencies in databases.
MINIATURIZED ENDOTHERMIC COOLING MODULE FOR DENATURATION OF ON-CHIP PCR PRODUCT AND ITS ELECTRICAL DETECTION USING NANOWIRE BIOSENSOR

This work presents a miniaturized endothermic cooling module (Fig.1) for denaturation of on-chip polymerase chain reaction (PCR) product and its electrical detection using nanowire biosensor [1] at the downstream of integrated microsystem for application in infectious disease diagnostics, by directly detecting the viral ribonucleic acid (RNA) from blood samples.
Exploring the Use of Twitter by Leading Medical Centers in the United States

Healthcare organizations such as hospitals and clinics increasingly use social media platforms such as Twitter to raise awareness in the community about health and wellness issues. In line with this trend, the current study seeks to understand how Cleveland Clinic, Johns Hopkins Hospital, and Mayo Clinic use their primary Twitter accounts to post information related to each of the following major health topics: brain, cancer, diabetes, diet, exercise, heart, mental health, and obesity. Nearly 6,000 tweets posted by those medical centers were collected and analyzed. The results showed that the three medical centers used diet and cancer topics more frequently than the other six topics in their tweets. Moreover, diabetes was consistently the least frequently used topic in the analyzed tweets. The results associated with the other five topics were mixed.
Behavioural Responses to Corporate Image Building Through Social Media Advertising: A Study Among Nairobi Students

Social media advertising (SMA) is burgeoning and of great importance to both practitioners and academicians to understand how to build a corporate image (CI). The present study examined how organizations in Kenya build their CI through SMA and how consumers respond and behave towards it. This study purely relied on structured questionnaires, which were administered to research subjects. In all, 512 students were part of the survey. The data was first keyed into EpiData 13.0 software and then exported to Stata for quantitative analysis. The researchers used Stata in the data analysis because of their familiarity with the software in analysing data. The findings show that consumers have a favourable response towards SMA of companies in Kenya, which suggest that they can help companies build a good CI. This research has theoretical as well as practical value for the research community and managers. From a developing country perspective, understanding how to build CI, SMA and consumer response (CR) would be critical for both local and foreign firms. This knowledge will enable companies to craft effective marketing strategies on social media in meeting consumers’ needs.
Network Analysis and Modeling , CSCI 5352 Lecture

Many real-world networks are representations of dynamical systems, that is, systems that change over time. The way we record or sample those changes over time can have a large impact on what structure we then observe. For instance, a static network may be simply a " snapshot " of the sys-tem's structure at a particular moment in time t, showing us the set of vertices and edges extant in some window of time t 1 ≤ t < t 2. Or, we might have a sequence of such snapshots for some set of sampling times {t 0 , t 1 ,. , t k }, or we might have a cumulative network, which includes all the edges and vertices that ever occurred up to our observation time t. In rare cases, we may have a complete trace of the system's evolution, with timestamps for each change in the set of vertices or edges. At their most basic level, temporal (or evolving or dynamical) networks can change over time by either changing the number of vertices, or changing the number of edges they contain.
Bayesian perspectives for epidemiological research

One misconception (of many) about Bayesian analyses is that prior distributions introduce assumptions that are more questionable than assumptions made by frequentist methods; yet the assumptions in priors can be more reasonable than the assumptions implicit in standard frequentist models. Another misconception is that Bayesian methods are computationally difficult and require special software. But perfectly adequate Bayesian analyses can be carried out with common software for frequentist analysis. Under a wide range of priors, the accuracy of these approximations is just as good as the frequentist accuracy of the software—and more than adequate for the inaccurate observational studies found in health and social sciences. An easy way to do Bayesian analyses is via inversevariance (information) weighted averaging of the prior with the frequentist estimate. A more general method expresses the prior distributions in the form of prior data or ‘data equivalents’, which are then entered in the analysis as a new data stratum. That form reveals the strength of the prior judgements being introduced and may lead to tempering of those judgements. It is argued that a criterion for scientific acceptability of a prior distribution is that it be expressible as prior data, so that the strength of prior assumptions can be gauged by how much data they represent.
MMP 13 inhibition rescues cognitive decline in Alzheimer transgenic mice via BACE 1 regulation

MMP13 (matrix metallopeptidase 13) plays a key role in bone metabolism and cancer development, but has no known functions in Alzheimer’s disease. In this study, we used high-throughput small molecule screening in SH-SY5Y cells that stably expressed a luciferase reporter gene driven by the BACE1 (b-site amyloid precursor protein cleaving enzyme 1) promoter, which included a portion of the 50 untranslated region (50UTR). We identified that CL82198, a selective inhibitor of MMP13, decreased BACE1 protein levels in cultured neuronal cells. This effect was dependent on PI3K (phosphatidylinositide 3-kinase) signalling, and was unrelated to BACE1 gene transcription and protein degradation. Further, we found that eukaryotic translation initiation factor 4B (eIF4B) played a key role, as the mutation of eIF4B at serine 422 (S422R) or deletion of the BACE1 50UTR attenuated MMP13mediated BACE1 regulation. In APPswe/PS1E9 mice, an animal model of Alzheimer’s disease, hippocampal Mmp13 knockdown or intraperitoneal CL82198 administration reduced BACE1 protein levels and the related amyloid-b precursor protein processing, amyloid-b load and eIF4B phosphorylation, whereas spatial and associative learning and memory performances were improved. Collectively, MMP13 inhibition/CL82198 treatment exhibited therapeutic potential for Alzheimer’s disease, via the translational regulation of BACE1.
A modified H.263 algorithm using bit allocation buffer control algorithm

Buffer control is an important problem in very low bit-rate video coding. Previously the authors had proposed a new buffer control algorithm for motion-compensated hybrid DPCM/DCT coding. The algorithm is based on the use of a bit allocation algorithm to determine the quantization scale factors in such a coder to meet a given target bit rate. Simulation results showed that, using the proposed algorithm, the H.261 coder can achieve a higher PSNR and better visual quality than the coder using a traditional buffer control algorithm. In this paper, we apply this buffer control algorithm to a modified version of the H.263 algorithm for very low bit-rate video coding. Comparing the performance of the modified H.263 codec with the TMN5 model also shows that better visual quality can be obtained at comparable PSNR values.
The controversy over homocysteine and cardiovascular risk 1,2 Perspective

Elevated plasma total homocysteine (tHcy) is a risk factor for occlusive cardiovascular disease (CVD). This concept is based on the observations of premature vascular disease in patients with homocystinuria, the relation between tHcy and both clinical CVD as well as preclinical atherosclerotic disease, the relation between tHcy in children and CVD in their parents or relatives, and reduction in CVD or surrogate endpoints after tHcy-lowering intervention with B vitamins. Plausible mechanisms include the in vivo interference with nitric oxide–dependent reactive vasodilatation. Some observations have raised questions about tHcy as a risk factor. 1 ) Some prospective studies showed a weak relation or no relation between tHcy and CVD. 2 ) Several traditional risk factors are associated with tHcy and may confound the relation between tHcy and CVD. 3 ) tHcy is related to renal function, and hyperhomocysteinemia may reflect early nephrosclerosis. 4 ) The C677T transition of the methylenetetrahydrofolate reductase gene causes a moderate increase in tHcy but no or only minor increased CVD risk. However, the strength of some of these arguments can be questioned because there is increasing evidence that tHcy is a proximate risk factor provoking the acute event, it strongly interacts with traditional risk factors, and it may predict CVD or death in patients with chronic renal failure. Furthermore, the studies of the C677T polymorphism lack sta-tistical power, and the TT genotype may even modulate CVD risk independently of homocysteine. Thus, only placebo-controlled intervention studies with tHcy-lowering B vitamins and clinical endpoints can provide additional valid arguments for the debate over whether tHcy is a causal CVD risk factor.
Do Central Banks Respond Timely to Developments in the Global Economy?

Our analysis suggests; they do not! To arrive at this conclusion we construct a real-time data set of interest rate projections from central banks in three small open economies; New Zealand, Norway, and Sweden, and analyze if revisions to these projections (i.e., forward guidance) can be predicted by timely information. Doing so, we find a systematic role for forward looking international indicators in predicting the revisions to the interest rate projections in all countries. In contrast, using similar indexes for the domestic economy yields largely insignificant results. Furthermore, we find that revisions to forward guidance matter. Using a VAR identified with external instruments based on forecast errors from the predictive regressions, we show that the responses to output, inflation, the exchange rate and asset returns resemble those one typically associates with a conventional monetary policy shock.
Electrical Oscillations in Wind Power Plants: Modeling, Control, and Mitigation

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“We Need Supervisors”: Problematic Implementationof Curriculum 2013 among Mathematics Teachers

Article Info Abstract Article History Received: 20-04-2020 The development of curriculum is a dynamic process which aims to comply with the evolvement of knowledge and technology.However, the implementations of reformed curriculum have been acknowledged to raise various issues. Likewise, among the issues related to the implementation of the Curriculum 2013, known as K13, in Indonesia were teachers’ difficulties, including mathematics teachers. This study aimed at investigating and describing the difficulties faced by junior high school mathematics teachers in implementing K13. The study applied a mixedmethod approach involving 66 from the total of 78 junior high school mathematics teachers in Lhokseumawe, Aceh Province, as the study sample. The findings showed that 50%-60% participants are encountering difficulties in components of trainings and socialization of K13, lesson planning, learning action, and assessment and reporting the learning outcome. Although 93.94% teachers have taken the K13 training, but only 56.45% of them sometimes implemented the curriculum in the classrooms. Additionally, the main resource of the difficulties was the ineffectiveness of trainings and socializations of K13 the teachers had attended. The teachers expected that there would be a learning community or forum as the follow-up action of the trainings, which can supervise the implementation of K13 in their classes. The directions for further research to improve the curriculum implementation were discussed. Revised: 18-06-2020 Accepted: 23-06-2020
The Role of M otivational P ersisten ce and Resilience Over th e W ell-being Changes R egistered in T im e 1

The present study investigates the interaction between personal characteristics that are considered nowadays strengths used to face difficult events or transition period. A number of 200 married or living together participants completed self-reports for common goals, motivational persistence, resilience and well-being. Results show that persistence and resilience do interact with each other at an individual level but also from a family concept perspective. Moreover, maintaining a positive outlook and family spirituality do have an impact over the intensity and direction of the relationship between long term purposes pursuing (LTPP) and recurrence of unattained purposes (RUP) and changes in well-being registered in time. Resiliency as a personal characteristic and family resilience show good psychometric qualities for this study. Although some of the results are descriptive, in-depth analyses of direction and intensity of the relationships lead the final conclusions to suggestions for further research and implications for psychological practice.
Text mining in insurance: from unstructured data to meaning

Every day insurance companies collect an enormous quantity of text data from multiple sources. By exploiting Natural Language Processing, we present a strategy to make beneficial use of the large information available in documents. After a brief review of the basics of text mining, we describe a case study where, by analyzing the accident narratives written by the researchers of the National Highway Traffic Safety Administration (NHTSA) of the U. S. Department of Transportation, we aim at grasping latent information useful to fine-tune policy premiums. The process is based on two steps. First, we classify the reports according to the relevance of their content to find the risk profile of the people involved. Next we use these profiles to add new latent risk covariates for the ratemaking process of the customers of a company.