Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactivity in Branded Mobile Apps: A Conceptual Framework

The increasing growth of smartphone apps has prompted marketers and advertisers to take advantage of mobile app technology. As a result, branded mobile apps are created as a brand communication channel to reach out to their current and prospective consumers. In order to derive maximum benefits from branded apps, companies and brands need to ensure that the app interface in which the consumers interact with is user-friendly. According to Harris Interactive survey (2010), branded app users consider usability and user experiences more important than brand name alone. In this sense, app designs that improve the usability of a branded app could contribute to supporting the brand’s promise and building relationships with the users (Weevers 2011). Despite the importance of mobile app usability, empirical research on the effects of branded app features is limited. Previous research has examined the value of website interactivity in improving Web usability (e.g., Ghose and Dou 1998). The potential of interactivity includes sense of entertainment and satisfaction (Rafaeli 1988) and engagement (Schaffer and Hannafin 1986). Therefore, the primary goal of this study is to (a) conceptualize interactivity in the context of mobile app environment and (b) explore how a branded app’s interactivity influences its effectiveness. Building on literature on interactivity (e.g., Lui and Shrum 2002; McMillan and Hwang 2002), the study identifies key dimensions of interactivity within mobile apps. Steuer’s (1992) three dimensions of interactivity are central to the concept of interactivity appeared in the literature. First, speed of response is essential to online media to create a synchronous and interactive user experience (Lui and Shrum 2002; Lui 2003). Second dimension of interactivity, range, has a similar meaning as the dimension of choice (e.g., Ha and James 1998). As a result of choice availability, an individual may feel empowered by being able to choose from several different alternatives (Pavlik 1998) and minimize effort in achieving a task (Ha and James 1998). Finally, mapping refers to a medium’s ability to let the users to control the environment, and the degree of interactivity depends on whether the user can control the flow of information (Shih 1998). Based on such conceptualization, this study suggests six dimensions as critical to interactivity of mobile apps—speed, choice, personalization, navigational control, communication, and entertainment. The first four constructs (i.e., speed, choice, personalization, and navigational control) are drawn from the range and control dimensions of interactivity (Steuer 1992) and applied to the context of mobile apps. The communication construct is conceptualized based on the function of feedback (Ha and James 1998) and transaction facilitation (Song and Zinkhan 2008). The last one is added from the interactivity literature on Web environment and mobile advertisement (i.e., playfulness) (e.g., Gao, Rau, and Salvendy 2010; Lee et al. 2004). A conceptual framework of interactivity within mobile apps is presented in Figure 1.
ADDITION OF NATURAL EXTRACTS WITH ANTIOXIDANT PROPERTIES IN BIODIESEL: ANALYSIS BY NEURAL NETWORKS OF THE MULTILAYER PERCEPTRON TYPE

Biodiesel is capable of replacing diesel because it has similar physicochemical properties, but this biofuel is susceptible to oxidation, which makes the application of antioxidant substances necessary. For this study, alcoholic extracts of senna leaves, hibiscus flowers, and blackberry were used. Biodiesel samples were submitted to physicochemical analysis to evaluate interference in the volume of these alcoholic extracts with antioxidant properties. The data obtained were processed using the neural network of the multilayer perceptron type (MLP). For the network’s training, 200 epochs were used. The samples were randomly divided into three groups, with 70% used for training, 15% for testing, and 15% for validation. The type of extract was considered as a categorical variable, the extract volume as a target variable, and the other ones as input variables. Among the 200 networks trained, with 5 to 20 hidden layers, the 5 with the best performance were highlighted. The Tukey test applied to the means showed no significant difference at the 5% level, between the value of the added volume and the means value predicted by the networks. The sensitive analysis showed that the most important input variable for the construction of the model was the type of extract.
A 14.5-bit ENOB, 10MS/s SAR-ADC with 2nd order hybrid passive-active resonator noise shaping

A new 2nd order noise shaping (NS) based successive approximation register (SAR) ADC is presented in this paper. In comparison to earlier research, this paper considers hybrid passive-active integrators to compensate for the phase error of the passive integrator. To realize the resonator noise shaping in high-speed asynchronous SAR-ADC, the hybrid passive-active sigma-delta modulator (SDM) is introduced as a multi-input feedforward loop filter to overcome the noise barrier of the conventional asynchronous SAR-ADC generated from the CDAC, quantizer, and dynamic comparator. The proposed noise shaping technique significantly reduces the ADC power consumption and area compared with the active SDM noise shaping approach while overcoming the shortcomings of passive SDM, such as large-area penalty, low resolution, and low speed. It consists of a very low power forward gain G and a positive feedback path across a 1st order passive switch capacitor (SC) integrator to desensitize the capacitor ratios under PVT variations. Extensive circuits simulation verifications and system-level results have been used to validate the effectiveness of the proposed NS SAR-ADC. The simulation results show that the proposed SAR ADC consumes 0.88mW at maximum speed, with an SNDR of 89.43 dB and SFDR 98.64 dB within 0.1 fs oversampling frequency.
Using Small Area Prevalence Survey Methods to Conduct Blood Lead Assessments among Children

Introduction: Prevalence surveys conducted in geographically small areas such as towns, zip codes, neighborhoods or census tracts are a valuable tool for estimating the extent to which environmental risks contribute to children’s blood lead levels (BLLs). Population-based, cross-sectional small area prevalence surveys assessing BLLs can be used to establish a baseline lead exposure prevalence for a specific geographic region. Materials and Methods: The required statistical methods, biological and environmental sampling, supportive data, and fieldwork considerations necessary for public health organizations to rapidly conduct child blood lead prevalence surveys at low cost using small area, cluster sampling methodology are described. Results: Comprehensive small area prevalence surveys include partner identification, background data collection, review of the assessment area, resource availability determinations, sample size calculations, obtaining the consent of survey participants, survey administration, blood lead analysis, environmental sampling, educational outreach, follow-up and referral, data entry/analysis, and report production. Discussion: Survey results can be used to estimate the geographic distribution of elevated BLLs and to investigate inequitable lead exposures and risk factors of interest. Conclusions: Public health officials who wish to assess child and household-level blood lead data can quickly apply the data collection methodologies using this standardized protocol here to target resources and obtain assistance with these complex procedures. The standardized methods allow for comparisons across geographic areas and over time.
Contemporary sources and levels of heavy metal contamination in urban soil of Broken Hill, Australia after ad hoc land remediation

Abstract This study used GIS-based and multivariate statistical approach to identify sources of Cr, Mn, Ni, Pb and Zn in urban soil surrounding a large Pb-Zn-Ag orebody. The results show that Mn-Pb-Zn-rich dust originating from the orebody and associated mining works has acted as an important contaminating source of topsoil metals. In contrast, Cr and Ni appear to be sourced naturally from weathering of parent materials. The calculation of contamination indices reflects a high level of Pb and Zn contamination in topsoil near the orebody and a moderate level of Mn contamination, while topsoil contamination with Cr and Ni is negligible.
The Role of Geo-Demographic Big Data for Assessing the Effectiveness of Crowd-Funded Software Projects: A Case Example of “QPress”

The current phenomenon of Big Data – the use of datasets that are too big for traditional business analysis tools used in industry – is driving a shift in how social and economic problems are understood and analysed. This chapter explores the role Big Data can play in analysing the effectiveness of crowd-funding projects, using the data from such a project, which aimed to fund the development of a software plug-in called ‘QPress’. Data analysed included the website metrics of impressions, clicks and average position, which were found to be significantly connected with geographical factors using an ANOVA. These were combined with other country data to perform t-tests in order to form a geo-demographic understanding of those who are displayed advertisements inviting participation in crowd-funding. The chapter concludes that there are a number of interacting variables and that for Big Data studies to be effective, their amalgamation with other data sources, including linked data, is essential to providing an overall picture of the social phenomenon being studied.
Optimal insurance strategy in a risk process under a safety level imposed on the increments of the process

The problem of designing an optimal insurance strategy in a modification of the risk process with discrete time is investigated. This model introduces stage-by-stage probabilistic constraints (Value-at-Risk (VaR) constraints) on the insurer's capital increments during each stage. Also, the set of admissible insurances is determined by a safety level reflecting a ‘good’ or ‘bad’ capital increment at the previous stage. The mathematical expectation of the insurer's final capital is used as the objective functional. The total loss of the insurer at each stage is modeled by the Gaussian (normal) distribution with parameters depending on a seded loss function (or, in other words, an insurance policy) selected. In contrast to traditional dynamic optimization models for insurance strategies, the proposed approach allows to construct the value functions (and hence the optimal insurance policies) by simply solving a sequence of static insurance optimization problems. It is demonstrated that the optimal seded loss function at each stage depends on the prescribed value of the safety level: it is either a stop-loss insurance or conditional deductible insurance having a discontinuous point. In order to reduce ex post moral hazard, we also investigate the case, where both parties in an insurance contract are obligated to pay more for a larger realization of loss. This leads to that the optimal seeded loss functions are either stop-loss insurances or unconditional deductible insurances.
Using a Brief Mental Imagery Competing Task to Reduce the Number of Intrusive Memories: Exploratory Case Series With Trauma-Exposed Women

Background Novel interventions should be developed for people who have undergone psychological trauma. In a previous case study, we found that the number of intrusive memories of trauma could be reduced with a novel intervention. The intervention included a brief memory reminder, a visuospatial task and mental rotation, and targeted trauma memory hotspots one at a time in separate sessions. Objective This case series (N=3) extended the first case study with 3 new cases to determine whether a similar pattern of beneficial results is observed. We explored whether the brief intervention would result in reduced numbers of intrusive memories and whether it would impact symptoms of posttraumatic stress, depression and anxiety, and general functioning. Acceptability of the intervention was also explored. Methods A total of 3 women completed the study: 2 with posttraumatic stress disorder and other comorbidities and 1 with subthreshold posttraumatic stress disorder. The primary outcome was the change in the number of intrusive memories from the baseline phase to the intervention phase and at the 1-month follow-up, with an assessment of the intrusion frequency at 3 months. Participants monitored the number of intrusive memories in a daily diary for 1 week at baseline, for maximum of 6 weeks during the intervention phase and for 1 week at the 1-month and 3-month follow-ups. The intervention was delivered in person or digitally, with guidance from a clinical psychologist. A repeated AB design was used (A was a preintervention baseline phase and B intervention phase). Intrusions were targeted individually, creating repetitions of an AB design. Results The total number of intrusive memories was reduced from the baseline to the intervention phase for all participants. The total number for participant 3 (P3) reduced from 38.8 per week during the baseline phase to 18.0 per week in the intervention phase. It was 13 at the 3-month follow-up. The total number for P4 reduced from 10.8 per week at baseline to 4.7 per week in the intervention phase. It was 0 at the 3-month follow-up. The total number for P5 was reduced from 33.7 at baseline to 20.7 per week in the intervention phase. It was 8 at the 3-month follow-up. All participants reported reduction in posttraumatic stress symptoms in the postintervention phase. Depression and anxiety symptoms reduced in 2 of the 3 participants in the postintervention phase. Acceptability was favorable. Conclusions We observed good compliance with the intervention and intrusive memory diary in all 3 cases. The number of intrusive memories was reduced for all participants during the intervention phase and at the 1-month follow-up, with some improvement in other symptoms and functioning. Further research should explore the remote delivery of the intervention and whether nonspecialists can deliver the intervention effectively.
Efficacy of statins combined with amiodarone in the treatment of atrial fibrillation: A meta-analysis

Objectives: Atrial fibrillation (AF) is a common arrhythmia in clinics with a high mortality rate. Recently, statins combined with amiodarone and amiodarone alone were used in the treatment of AF. This systematic review study aims to investigate the clinical efficacy and usefulness of statins combined with amiodarone and amiodarone alone in treating AF. Methods: Pubmed, Embase, Web of Science, Medline, Cochrane Library, and China National Knowledge Infrastructure were used to search for the relevant studies and full-text articles involved in evaluating statin-amiodarone versus amiodarone alone for AF. All included articles were quality assessed, and the data analysis was conducted with Review Manager 5.4. Results: Eight (8) relevant studies with 758 AF patients were included in this analysis. In the Meta-analysis, Statin-amiodarone treatment reduced AF recurrence (RR, 0.61; 95% CI, 0.50–0.75; p < 0.00001), C-reactive protein (CRP) level (MD, 0.96; 95%CI, 0.64–1.29, p < 0.00001) and Left atrial diameter (LAD) (MD, 0.81; 95%CI, 0.06–1.56; p = 0.03) compared with amiodarone alone for AF. However, no difference was observed for change of total cholesterol (TC) (MD, 1.32; 95%CI, −0.24–2.88; p = 0.10). Conclusion: Statin-amiodarone effectively reduced CRP level, LAD and reduced the recurrence of AF than amiodarone alone.
Abnormal audit fees and audit quality: Australian evidence

We examine the association between abnormal audit fees and audit quality using Australian data. We find that audit quality, measured by auditors’ propensity to issue going concern opinions for financially distressed companies, discretionary accruals, and clients’ propensity to meet or beat earnings benchmarks, declines as positive abnormal audit fees increase in magnitude. Our findings support an economic bonding argument that positive abnormal audit fees reflect the extent of economic bonding between the auditor and the client. We also find that negative abnormal audit fees are negatively associated with the absolute value of discretionary accruals. Our findings suggest that academic researchers, practitioners, regulators, and others interested in assessing the effect of auditor remuneration on auditor independence and audit quality should be concerned with audit fees that are above a normal level rather than audit fees that are below a normal level of audit fees. JEL Classification: M42, M49
BUILDING SECTION INSTANCE SEGMENTATION WITH COMBINED CLASSICAL AND DEEP LEARNING METHODS

Abstract. In big cities, the complexity of urban infrastructure is very high. In city centers, one construction can consist of several building sections of different heights or roof geometries. Most of the existing approaches detect those buildings as a single construction in the form of binary building segmentation maps or as one instance of object-oriented segmentation. However, reconstructing complex buildings consisting of several parts requires a higher level of detail. In this work, we present a methodology for individual building section instance segmentation on satellite imagery. We show that fully convolutional networks (FCNs) can tackle the issue much better than the state-of-the-art Mask-RCNN. A ground truth raster image with pixel value 1 for building sections and 2 for their touching borders was generated to train models on predicting both classes as a semantic output. The semantic outputs were then post-processed with the help of morphology and watershed labeling to generate segmentation on the instance level. The combination of a deep learning-based approach and a classical image processing algorithm allowed us to fulfill the segmentation task on the instance level and reach high-quality results with an mAP of up to 42 %.
Analysis of polysilicon electrothermal flexure microactuators with temperature-dependent properties

The characterization of thermal flexure microactuator behaviors has been performed experimentally and analytically by past efforts. It has been reported, previously, a good agreement of analytical predictions with experimental results only at low input power. One of the reasons is that, in previous models, the thermo-mechanical properties of polysilicon have been considered constant over a wide rang of temperature. In reality, the thermo-mechanical properties of polysilicon such as resistivity, Young' modulus and thermal expansion coefficient are dependents on temperature and change significantly with temperature. In this paper, an electrothermal model of polysilicon thermal flexure microactuator has been developed, incorporating the variation of material properties with temperature. Results indicate that the performance of actuator is affected by the effect of temperature dependencies of these parameters especially at high input power. To verify the validity of model, numerical results are compared with experimental results in literature.
Pengenalan dan Klasifikasi Tulisan pada Nota Pembelian Material (Studi Kasus Proyek Konstruksi)

Abstrak—CV Bangun Karya Sejahtera merupakan perusahaan yang aktif bergerak di bidang properti dan memiliki banyak arus kas masuk maupun keluar. Perusahaan telah memiliki sistem informasi untuk membantu memantau aliran dana. Namun, karyawan harus memasukkan data tersebut secara manual ke dalam sistem. Proses input ini seringkali memakan banyak waktu mereka. Oleh karena itu, tugas akhir ini bermaksud untuk menambahkan fitur pada sistem informasi yang ada untuk membantu karyawan dalam menginput data secara otomatis ke dalam sistem informasi perusahaan yang ada. Fitur ini memanfaatkan teknologi Optical Character Recognition (OCR). Ini dikembangkan menggunakan kerangka Flask berdasarkan bahasa pemrograman Python. Klasifikasi dilakukan dengan menggunakan Support Vector Machine. Hasil penelitian menunjukkan bahwa fitur tambahan dapat melakukan pengenalan dan klasifikasi teks dengan SGDClassifier rata-rata 8,89 detik. Adanya fitur OCR pada sistem informasi ini diharapkan dapat membantu karyawan perusahaan dalam menginput data ke dalam sistem informasi CV Bangun Karya Sejahtera.
Onsite Wastewater Treatment Upgrade for Water Reuse in Cooling Towers and Toilets

The increasing population size and housing density are responsible for greater consumption of water resources, causing drinking water shortages in many regions. To reduce water consumption, it is essential to perform wastewater treatment, particularly in onsite non-potable water systems (ONWS). This article discusses the performance of a wastewater treatment system in a shopping mall in Brazil (City of Guarulhos, São Paulo State, Brazil), using data collected over 3 years (2015–2018) that resulted in water reuse ranging from 12 to 42 m³ per day. The strategy used for this wastewater treatment and further reuse in cooling towers and toilets initially included nine steps; after adjustments, an additional step (tertiary decanter) was added. All steps were named as follows: (1) railing; (2) fats boxes; (3) aerobic reactors with selector tank; (4) denitrification; (5) flocculation; (6) secondary decanter; (7) ultrafiltration; (8) disinfection; (9) filtration by zeolites; and (10) tertiary decanter. Based on using FeCl3 as a flocculant followed by filtration by zeolites (SFM) for ion adsorption and removing above 99% of the biological oxygen demand (BOD5), generating a final BOD5 of <2.0 mg/L, total dissolved solids of 130 to 594 mg/L, pH ranging from 6.75 to 7.79, and remaining pathogen-free. This treatment demonstrated the feasibility of reusing water in air conditioning cooling towers and toilets, generating up to 797 m³/month of treated water for reuse with savings of up to 27% in drinking water consumption at the mall.
The existence and role of independent board members and their impact on the board’s effectiveness and firm’s value: The case of the emerging market

The implementation of good corporate governance (GCG) within a firm dictates its organizational behavior driven down by the board functionality effectiveness, among which the existence and role of an independent board member are taken into account. This study examines the effect of the existence and role of independent board members in Indonesia listed firm on the board’s functionality effectiveness, and subsequently, its impact on the value of the firm. Since Indonesia adopts a two-board system instead of a one-board system, the independent board member is known as an independent commissioner (IC) who sits on the company board of commissioners (BOC) which is equivalent to the company board of directors (BOD) in the one-board system. It is found through regression analysis that when an IC holds a powerful leadership position, it enhances the BOC’s functionality effectiveness. Likewise, if the IC has the position as the chair of BOC’s sub-committee in the company. The regression analysis was conducted in two periods, before the establishment of the Financial Services Authority (FSA) and after.