Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Attitude Strength in Marketing Intelligence Use Concerning Customer Satisfaction

Considering the strategic importance of satisfying customers and the high costs of conducting customer satisfaction research, deeper understanding of the determinants of customer satisfaction information use seems important. In this paper, we aim at predicting intentions of selectively using satisfaction-related information from decision-maker attitude strength by applying latent variable modelling. The results suggest that two dimensions of attitude strength, commitment and embeddedness, contribute directly and indirectly to selective customer satisfaction intelligence use. Indirect effects occur through cognitive processes and selective judgment of satisfaction-related information.
NEW DEVELOPMENTS AND DIRECTION

In recent years, the research on capital theory has shifted from reverse capital deepening and reswitching in techniques to a new direction, which goes beyond the near-linearities of price-rates of profit trajectories and of wage-rates of profit curves and explicates the reasons behind this kind of near-linearities. The reswitching issue remains in the background of these studies as a remote albeit ever-present possibility. The article contributes some more evidence to the extant literature by utilizing data from the last available benchmark input-output table of the US economy of the year 2012. The derived near-linearities of price trajectories and wage-rate of profit curves are explained by the low effective rank of the economy’s input-output matrices and not from their seemingly random character. These findings shed additional light on a new and more meaningful direction in the research agenda, the possibility of molding the essential features of the economy through dimensionality reduction.
Data Neutrality and Market Competition

We introduce a new hypothetical regulation called data neutrality to examine how nondiscriminatory and open access to a platform’s data when implementing targeted advertising for consumers affects the relevant downstream market competition, the platform’s incentives to produce data, and ultimately, consumer welfare. Under data neutrality, all firms that want to access a platform’s data are treated equally in terms of data usage, regardless of whether the firm is affiliated with the platform. We first show that weak data neutrality that only requires the amount of data provision to be nondiscriminatory may have de facto no impact on the market unless the external data price charged to the unaffiliated seller is also regulated, as in strong data neutrality. From a welfare analysis, we find that data neutrality, whether it is weak or strong, does not necessarily make consumers better off because the platform optimally reduces the amount of data provision under the regulation, which leads to important policy implications.
BOARD OVERSIGHT AND FINANCIAL PERFORMANCE OF ISLAMIC BANKS IN ARAB AND NON-ARAB COUNTRIES

This study analyzes the impact of corporate governance (CG) practices and Shariah Supervisory Board (SSB) on the financial performance of Islamic banks (IB). A sample of 20 Islamic banks from Arab and Non-Arab countries i.e. Bahrain, Kuwait, Jordan, Saudi Arabia, United Arab Emirates, Pakistan and Malaysia were used. A CG-index was adopted from the literature which comprises of three sub-indices including Board of Directors (BOD), Audit Committee (AC) and Shariah Supervisory Board (SSB). The dataset covers the period from 2012 to 2018. The panel data regression technique was used for data analysis. The descriptive statistics suggest that the average score for CG-index is 76% which indicates that Islamic banks reasonably adhere to CG regulations. The panel regression results suggest an insignificant relationship between (1) CG and IB’s financial performance and (2) BOD and IB’s financial performance. These findings are consistent with earlier studies conducted on Arab countries. Moreover, the results also suggest that SSB and AC contribute positively towards asset performance but negatively towards equity performance. Policymakers should revisit the CG regulations in their countries to make them more influential towards the performance of Islamic banks.
Avocado oil extraction processes: method for cold-pressed high-quality edible oil production versus traditional production

Nowadays the avocado fruit ( Persea americana Mill.) is widely regarded as an important fruit for its nutritional values, as it is rich in vital human nutrients. The avocado fruit is mainly sold fresh on the market, which however trades also a relevant quantity of second-grade fruits with a relatively high oil content. Traditionally, this oil is extracted from dried fruits by means of organic solvents, but a mechanical method is also used in general in locations where drying systems and/or solvent extraction units cannot be installed. These traditional processes yield a grade of oil that needs subsequent refining and is mainly used in the cosmetic industry. In the late 1990s, in New Zeland, a processing company with the collaboration of Alfa Laval began producing cold-pressed avocado oil (CPAO) to be sold as edible oil for salads and cooking. Over the last fifteen years, CPAO production has increased in many other countries and has led to an expansion of the market which is set to continue, given the growing interest in highquality and healthy food. Avocado oil like olive oil is extracted from the fruit pulp and in particular shares many principles of the extraction process with extra-vergin olive oil. We conducted a review of traditional and modern extraction methods with particular focus on extraction processes and technology for CPAO production.
EXPERIMENTAL MEASUREMENTS AND COMPUTATIONAL PREDICTIONS OF THE INTERNAL FLOW FIELD IN A PRESSURE SWIRL ATOMIZER

The results of LDA measurements within the swirl chamber of a large scale pressure swirl atomizer are presented. Three outlet geometries, conical, curved and square are considered. Axial and tangential velocity components are measured, and the radial component is determined using mass continuity.The measurements confirm CFD predictions of Gortler wall vortices and central recirculation zones.
ACCOUNTING CONSERVATISM AND BOARD CHARACTERISTICS: PORTUGUESE EVIDENCE

For a sample of 26 non-financial listed Portuguese firms-year from 2002 to 2016, this study extends previous research by empirically examining how board structure affects the magnitude of accounting conservatism for companies listed in Portugal. Mainly, we focus on the main characteristics of the board structure that are highlighted by the Portuguese Securities Market Supervisory Authority’s recommendations: board size, board composition, board’s monitoring committees and number of board meeting. This study predicts and finds a non-linear relationship between board size and conservatism. Specifically, we find that as board size increases up to 8 members, the sample firms employ more conservatism, consistent with the idea that smaller boards can be more effective than larger boards in monitoring managerial behaviour. When board size reaches beyond 8 members, a negative relationship between board size and conservatism accounting occurs. We also find that both boards comprised of more non-executive members and high board meetings frequency lead firms to report more conservatively.
The Impact of a New Quality Management Practice on Firm Performance: Evidence from Pakistan

IZA DP No. 14875 NOVEMBER 2021 The Impact of a New Quality Management Practice on Firm Performance: Evidence from Pakistan This paper uses a novel firm level data set to investigate the impact of a unique quality management practice on the production and productivity of a large-scale garments manufacturer in Pakistan. The analysis provides evidence that production complexity is an important element in determining the impact of management practices, as there are sizeable differences in the effects between complex and basic lines of assembly. Most specifications show that the implementation of the new quality management practice has a negative impact on lines at the extreme ends of the complexity spectrum, while conversely it has a positive impact on those basic lines which exhibit the highest levels of complexity. We find evidence consistent with a quantity-quality trade off, in that whilst the implementation of the new management practice generally adversely impacted upon productivity it had the desired effect of reducing the number of daily quality defects observed after the intervention. JEL Classification: L2, M2, O14, O32, O33
Weakly supervised explanation generation for computer aided diagnostic systems

Computer Aided Diagnosis (CAD) systems are developed to aid doctors and clinicians in diagnosis after interpreting and examining a medical image. CAD systems aids in performing the task more consistently. With the arrival of data-driven deep learning paradigm and availability of large amount of data in the medical domain, CAD systems are being developed to diagnose a large variety of diseases ranging from different types of cancers, heart and brain diseases, Alzheimer’s disease, and diabetic retinopathy, etc. These systems are highly competent in performing the task on which they are trained. Although such systems perform at par with the trained clinicians, they suffer from a limitation in that they are completely black box in nature and are trained only on image-level class labels. This poses a problem in deploying CAD systems as stand alone solutions for disease diagnosis. This is because decisions in the medical domain are about health of a patient and are well reasoned and backed by evidence, sometimes from multiple modalities. Hence, there is a critical need for CAD system’s decisions to be explainable. Restricting our focus to only image modality, a solution to design explainable CAD systems could be to train the system using both class labels and local annotations and derive the explanation in a fully supervised manner. However, getting these local annotations is very expensive, time-consuming, and infeasible in most circumstances. In this thesis we address this explainability and data scarcity problem and propose two different approaches towards the development of weakly supervised explainable CAD systems. Firstly, we aim to explain the classification decision by providing heatmaps denoting important regions of interest in the image, which helped the model make the prediction. In order to generate anatomically accurate heatmaps, we provide a mixed set of annotations to our model class labels for the entire training set of images and rough localization of suspect regions for a smaller subset of images in the training set. The proposed approach is illustrated on two different disease classification tasks based on disparate image modalities Diabetic macular edema (DME) classification from OCT slices and Breast Cancer detection from mammographic images. Good classification results are shown on public datasets, supplemented by explanations in the form of suspect regions; these are derived using just a third of images with local annotations, emphasizing the potential for generalisability of the proposed solution.
UNIVERSIDADE DE SÃO PAULO FACULDADE DE ODONTOLOGIA DE BAURU WILLIAN J. G. GUIRRO Relapse of maxillary anterior crowding: short- and long-term study

Objective: The aim of this study was to evaluate the relapse of maxillary anterior crowding in the short and long-term, 5 and 35 years posttreatment. Material and methods: The sample comprised 28 patients, 15 Class I and 13 Class II, treated with 4 premolars extraction, with mean initial age of 12.72 years (s.d.=0.99), final age of 14.74 years (s.d.=1.26) and mean treatment time of 2.02 years (s.d.=0.66). The mean short-term posttreatment age was 20.15 years (s.d.=1.34), and long-term was 49.40 years (s.d.=4.54). The mean time of short-term posttreatment evaluation was 5.40 years (s.d.=0.43) and long-term was 34.65 years (s.d.=4.25). The modified Little irregularity index for maxillary arch was assessed, in the dental casts of initial, final, shortand long-term posttreatment stages. Little index was compared among the 4 stages by repeated measures ANOVA and Tukey tests. Correlation between initial Little index and shortand long-term relapse of this index was verified with Pearson correlation test. Results: The maxillary anterior crowding was significantly corrected with treatment, presented a significant relapse in the short-term of 2.59mm, and presented a slight and not statistically significant increase of 0.41mm from shortto long-term posttreatment evaluation. The severity of initial maxillary anterior crowding was not correlated to shortand long-term relapse. Conclusions: The maxillary anterior crowding presented a significant relapse in the short-term and remained stable from shortto long-term posttreatment evaluation, 35 years after the end of active orthodontic treatment. Key-words: Orthodontics, Relapse, Stability.
WEIGHTED ENSEMBLE BASED EXTRA TREE FOR PERMISSION ANALYSIS FOR ANDROID APPLICATIONS CLASSIFICATION

Selecting optimal features for classification task is one of the essential problems in machine learning field. Feature Selection is one of the most extensively studied methods for dimensionality reduction. The feature selection method preserves a subset of the existing features and discards the rest during the (supervised or unsupervised) learning process. However, representing features plays important role in obtaining the highly discriminant features that contribute in enhancing the classifier performance. Therefore, the aim of this paper is to propose a framework based on ensemble extra tree algorithm to assign weight to features that have high influence in classifying android apps to malware or non-malware with lower computational cost overhead. The presented framework is evaluated by using different machine learning classifiers to examine the permissions features of two datasets in terms of their representation as binary vector or weight vector in enhancing the classification performance. The experimental results show that the presented model based on features weighting approach improved the classification performance.
INTELLECTUAL CAPITAL AND DISCLOSURE PRACTICES OF MISCELLANEOUS INDUSTRIES: EVIDENCE FROM CABLE COMPANIES IN INDONESIA

The important role of intellectual capital for value creation has led many companies to disclose their intellectual capital information in annual reports. This study aims to provide, via content analysis, an overview of the disclosure and presentation of intellectual capital information in the annual reports of cable companies listed on the Indonesia Stock Exchange in 2015. This study found that structural capital is the most common category of intellectual capital disclosed in the annual reports. In addition, most intellectual capital disclosures are discursive, with positive and past-oriented information. However, there is no systematic framework for disclosing intellectual capital information in annual reports. Disclosures made do not have a special pattern and are still random. This finding may contribute to an understanding of how companies communicate intellectual capital information for their own benefit, as well as the benefit of stakeholders, customers and employees.
Finite-difference time-domain simulations of the effects of air gaps in double-shell extended hemispherical lenses

The effects of parasitic air gaps on the input impedance and radiation characteristics of dense double-shell integrated lens antennas are studied numerically at millimetre waves using the finite-difference time-domain method. The lens core is made up of Macor or silicon, and is coated with a quarter wavelength matching layer. Two kinds of gaps are compared: they are located either (i) between both shells of the lens, or (ii) between the lens base and the feed substrate. We show that their impact is much more critical in the second case, and that it becomes dramatic for silicon lenses, even with very thin gaps (smaller than λ0/100); the three major observed effects are the following: (i) strong shift of the resonant frequency, (ii) beam broadening and directivity loss, (iii) increase of the side lobe level.
An investigation of statistical reasoning skills of middle school students about distribution

This study aims to examine the informal statistical reasoning processes students perform to sense and comprehend the distribution. In two activities that we applied to eight students in the 11-13 age range, we examined students’ statistical reasoning skills throughout their modeling processes to help them develop a foundation. We observed that students were able to create distribution displays in the activities that we applied, to express some statistical concepts, and to elaborate and analyze distribution representations. We explained the modeling process that students experienced during the activities, according to the RISM framework. One of the significant results that we have obtained is that when students can see the distribution as a whole, they realize the spread of the distribution, the center of the distribution, the variability of the distribution, and their probabilistic thinking increases when they express it through various samples.
Punish One, Teach A Hundred: The Sobering Effect of Peer Punishment on the Unpunished

Direct experience of a peer’s punishment might have a sobering effect above and beyond deterrence (information about punishments). We test this mechanism in China studying the reactions to listed state-owned enterprises’ (SOEs) punishments for fraudulent loan guarantees by firms in the same location or industry (peers) and non-peer firms, across SOEs and non-SOEs. After experiencing SOEs’ punishments, peer SOEs cut their loan guarantees by more than non-peer SOEs and peer non-SOEs, even if information is common to all firms. The reaction is stronger for peer SOEs whose CEOs have higher career concerns or face lower costs of cutting guarantees. JEL classification: D91, D72, G32, G41, K42. Keywords: Corporate Governance, Cultural Finance, Information Transmission, Peer Effects, Reputational Sanctions, Related Party Transactions, Emerging Markets, Corporate Fraud, Government Ownership. *We thank Franklin Allen, Will Cong, Tony Cookson, Mara Faccio, Ray Fisman, Henry Friedman, Mark DeFond, Vyacheslav (Slava) Fos, Nickolay Gantchev, Mariassunta Giannetti, Xavier Giroud, Zhiguo He, Yue Heng, Yi Huang, Sudarshan Jayaraman, Wei Jiang, Andrew Karolyi, Jonathan Karpoff, Da Ke, Kai Li, Chen Lin, Clark Liu, Bill Megginson, Roni Michaely, Randall Morck, Dhananjay Nanda, Jacopo Ponticelli, Shiva Rajgopal, Tao Shu, Zheng (Michael) Song, Dragon Tang, Cong Wang, Yongxiang Wang, Shang-Jin Wei, K.C. John Wei, Wei Xiong, Zhishu Yang, Bernard Yeung, Stefan Zeume, Shan Zhao, Hao Zhou, Bohui Zhang, Hong Zhang, and seminar and conference participants at the 2019 AFA, the 2019 EFA, the 5th CEIBS Finance/Accounting Symposium, the 2018 China Financial Research Conference, 2018 CICF, the CUHK-RCFS Conference on Corporate Finance and Financial Intermediation, the LBS Accounting Symposium, the Mitsui Symposium on Comparative Corporate Governance and Globalization, the 2020 NBER Chinese Economy Working Group Meeting, the Sun Yat-Sen University Finance International Conference, University of Colorado, University of Kentucky, University of Hong Kong, University of Oklahoma, City University of Hong Kong, and Hong Kong Polytechnic University for valuable comments. All errors are our own. Weber gratefully acknowledges financial support from the Fama Research Fund and the Fama-Miller Center at the University of Chicago Booth School of Business. Carroll School of Management, Boston College, Chestnut Hill, MA, USA. e-Mail: dacuntof@bc.edu University of Chicago Booth School of Business and NBER. e-Mail: michael.weber@chicagobooth.edu §Peking University HSBC Business School. e-Mail: jinxie@phbs.pku. edu.cn.
Nonvolatile hydrogenated-amorphous-silicon thin-film-transistor memory devices

The floating gate n-channel amorphous-silicon thin-film transistor nonvolatile memory device, which includes an a-Si:H layer embedded in the SiNx gate dielectric layer, has been prepared and studied. The transistor’s hysteresis of transfer characteristic curves has been used to demonstrate its memory function. A steady threshold voltage change between the “0” and “1” states has been achieved. A large charge retention time of >3600s with the “write” and “erase” gap of 0.5V has been detected. This kind of device brings additional functions to the a-Si:H thin-film transistors, which can expand its application into various areas.
The Aerodynamic Excitation of Trapped Diametral Acoustic Modes in Rectangular Ducted Cavities

iii ACKNOWLEDGEMENTS.iv NOMENCLATURE. v CHAPTER 1: Introduction. 1 1.1 Problem and Motivation. 1 1.2 Thesis Outline. 3 CHAPTER 2: Literature Review. 5 2.
No Need to Know Everything! Efﬁciently Augmenting Language Models With External Knowledge

Large transformer-based pre-trained language models have achieved impressive performance on a variety of knowledge-intensive tasks and can capture semantic, syntactic, and factual knowledge in their parameters. However, storing large amounts of factual knowledge in the parameters of the model is sub-optimal given the resource requirements and ever-growing amounts of knowledge. Instead of packing all the knowledge in the model parameters, we argue that a more efﬁcient alternative is to provide contextually relevant structured knowledge to the model and train it to use that knowledge. This allows the training of the language model to be de-coupled from the external knowledge source and the latter can be updated without affecting the parameters of the language model. Empirical evaluation using different subsets of LAMA probe reveals that such an approach allows smaller language models with access to external knowledge to achieve signiﬁcant and robust outperformance over much larger language models.
Customer‐focused approaches to innovation in housebuilding

Customer focus has become a catch phrase not only in the service industry but also in the housebuilding industry. Furthermore, UK speculative housebuilders have increasingly been searching for ways to be more customer focused. This study, through an analysis of the concept of customer satisfaction in the service industry, identifies three key aspects in customer focus that may be applied to the housebuilding industry: good service, customized house design on top of quality products, and good information flows between customers and the housebuilder and within the company. This paper explores how these key issues are dealt with in UK speculative housebuilding in two empirical studies to search for ways forward.
TWO-STEP METHOD FOR ASSESSING SIMILARITY OF RANDOM SETS

The paper concerns a new statistical method for assessing dissimilarity of two random sets based on one realisation of each of them. The method focuses on shapes of the components of the random sets, namely on the curvature of their boundaries together with the ratios of their perimeters and areas. Theoretical background is introduced and then, the method is described, justified by a simulation study and applied to real data of two different types of tissue mammary cancer and mastopathy.