Miracle-dz/UniFAR-FTUs huggingface dataset:
RAMAI-RAMAI MENOLAK WISATA HALAL: Kontestasi Politik Identitas dalam Perkembangan Wisata Halal di Indonesia

MasterCard Crescent Rating 2019 data shows Indonesia is the most popular halal tourist destination together with Malaysia. But on the other hand, in 2019 there was a rejection of Halal Tourism in several regions in Indonesia, namely Bali, South Sulawesi, North Sumatra and East Nusa Tenggara. This article tries to analyze why there is a rejection of halal tourism amid the growth of halal tourism in Indonesia. Is it more because of the recent strengthening of the wave of Islamism that has been mounted by practical political interests so that it presents its antithesis namely phobia as a form of cons of hegemony. So that the great potential of halal tourism itself is no longer seen as a great potential that can prosper anyone as a form of the universality of halal tourism. This analytical descriptive research with secondary data uses discourse analysis to answer the problem formulation with the concept of hegemony and identity politics. The conclusion of this article is that the rejection of halal tourism is significantly influenced by identity politics associated with political friction at the national and local level. Data MasterCard Crescent Rating 2019 menunjukkan Indonesia menjadi destinasi wisata halal terpopuler bersama Malaysia. Namun di sisi lain, pada kurun 2019 terjadi penolakan atas Wisata Halal di beberapa wilayah di Indonesia sebut saja Bali, Sulawesi Selatan, Sumatera Utara, dan Nusa Tenggara Timur. Artikel ini mencoba menganalisis mengapa terjadi penolakan wisata halal di tengah pertumbuhan wisata halal di Indonesia. Apakah lebih karena menguatnya gelombang Islamisme akhir-akhir ini yang tertunggangi kepentingan politik praktis sebagai wujud hegemoni sehingga menghadirkan antitesisnya yakni fobia sebagai wujud konter hegemoni, sehingga potensi besar dari wisata halal itu sendiri tidak lagi dilihat sebagai potensi besar yang bisa menyejahterakan siapapun sebagai wujud universalitasitas wisata halal. Penelitian deskriptif analitis dengan data sekunder ini menggunakan analisis wacana untuk menjawab rumusan masalah dengan pisau iris konsep hegemoni dan politik identitas. Hasil penelitian menunjukan bahwa penolakan wisata halal secara signifikan dipengaruhi oleh politik identitas yang terkait dengan friksi politik di level nasional dan lokal.
BlockTrail: A Scalable Multichain Solution for Blockchain-Based Audit Trails

Blockchain-based audit trails provide a consensus-driven and tamper-proof trail of system events that are helpful in creating provenance in enterprise solutions. However, taking into account the transaction bulk generated by these applications and the throughput limitations of existing blockchains, a single ledger for record keeping can be inefficient and costly. To that end, we see an imperative need for a new blockchain design that is capable of addressing current challenges, without compromising security and provenance. Hence, we propose BlockTrail, a scalable and efficient blockchain solution for auditing applications. BlockTrail fragments the legacy blockchain systems into layers of co-dependent hierarchies, thereby reducing the time and space complexity, and increasing the throughput. BlockTrail is prototyped on “Practical Byzantine Fault Tolerance” (PBFT) protocol with a custom-built blockchain. Experiments with BlockTrail show that compared to the conventional schemes, BlockTrail is more efficient, and has less storage footprint.
Changes in oxidative stress levels during two weeks of smoking cessation treatment and their association with nutritional characteristics in Japanese smokers

Although several experimental studies have reported that oxidative stress levels decrease during smoking cessation, how they change among general smokers has yet to be completely elucidated. In the present study, a total of 23 smokers who underwent smoking cessation treatment were observed for two-week changes in their levels of 8-OHdG and 8-isoprostane. Physical and nutritional characteristics were measured at the initial patient visit, and casual urine samples were collected at the initial visit and at a follow-up visit two weeks later. Oxidative stress was measured by a high performance liquid chromatography electrochemical detector, and the two-week difference in the levels of oxidative stress was assessed according to demographic and nutrient factors. Neither the urinary level of 8-OHdG nor that of 8-isoprostane decreased, although the cotinine level was decreased at two weeks. A Two-way repeated ANOVA revealed a significant interaction for fat intake by time for the change in the 8-OHdG level (P=0.03) and significant interactions for α-tocopherol intake (P=0.03), iron intake, and carbohydrate intake (P=0.03), all of which were time-dependent for the change in the 8-isoprostane level. The 8-OHdG level decreased among smokers with a high fat intake and was increased with a low fat intake. The 8-isoprostane levels were decreased among smokers with a high carbohydrate intake and increased with a low carbohydrate intake, decreased with a low iron intake and increased with a high iron intake and decreased with a low α-tocopherol intake and increased with a high α-tocopherol intake. Although the present study failed to observe a decrease in oxidative stress levels during the two-week smoking cessation period, we hypothesize that the intake levels of specific nutrients when initiating smoking cessation treatment may predict any subsequent changes in the oxidative stress levels.
A Multi-Subpopulation PSO Fusion based Optimal Tuning of PID Controller

In conduct the design problem optimization algorithms, particle swarm optimization (PSO) could be conceivably stuck at a local minimum in a non-proper region of the search. This led to the need of developing a new class of solution method that can overcome this deficiency. For boots out such problems, this paper presents a fusion algorithm of a multi-subpopulation particle swarm optimization (MS-PSO). The main idea lies in dividing the main search space into multi-subpopulation regions. The fusion is based on performance measurements of the individuals of these multi-subpopulations for finding the optimal solution. The results are obtained by testing the particle swarm optimization and multi-subpopulation particle swarm optimization on the tuning of PID controller to a given system to improve its step response parameters. The result is compared with the performance of PID controller tuned using conventional methods. The proposed PSO based PID controller has significant improved performance.
Lighting Design for Energy Sustainability, Information, and Perception. A Museum Environment as a Case Study

The aim of our research is to investigate the physical connection between light, perception, and information by means of an integrated methodological approach. The proposed method was used for sustainable lighting design aiming at light efficacy and quality, visual perception, communication, and energy saving. Three types of synergic measurement were carried out: photometric, colourimetric, and perception measurements. Starting from the results and the post-processing of photometric and colourimetric measurements on different light sources and fresco surfaces, by applying the eye-tracking technique for eye movement analysis of a people sample, entropy calculations were carried out. The results of observer perception and preferences, patterns of their visual scanning due to different LED (Light Emitting Diode) sources, were quantified by means of Shannon entropy calculation and, consequently, the information content of images that each light source can transmit. A new lighting proposal, based on the use of LED sources characterized by a spectral emission of light in strong compliance with surface colour and relevant transmission image content information was suggested and checked by transient simulations. Our proposal was based on sustainability because this concept is linked to developing perception and visual wellbeing, information, light communication, and lower energy consumption for maintenance, but especially for preventive conservation and the protection of works of art by means quality of light.
Polymeric nanocapsules templated on liquid cores as efficient photoreactors

Polymeric nanocapsules templated on liquid cores were obtained without stabilization by low molecular weight surfactants and applied as photochemical reactors. Toluene cores of the capsules were stabilized by novel graft amphiphilic polyelectrolyte poly(allylamine hydrochloride)-graft-poly(vinylnaphthalene) (PAH-graft-PVN) that was synthesized via nitroxide-mediated radical polymerization. Self-aggregation of the photoactive copolymer consisting of a solvophilic backbone and solvophobic side chains in water as a selective solvent leads to formation of intermolecular aggregates in which hydrophobic perylene fluorophore can be solubilized. However, at the water/toluene interface the macromolecules partially uncoil and polymeric chains are able to stabilize emulsion droplets by anchoring the hydrophobic arms in them. Formation of such capsules was followed using dynamic light scattering and electron microscopies. The obtained capsules showed long term stability. Importantly, energy transfer between the polymeric naphthalene moieties and incorporated perylene chromophores was realized much more efficiently in the core–shell capsules than in the copolymer aggregates. This can be explained in terms of the less packed but still confined environment of the nanocapsules. Such an assembly favors migration and transfer of excitation energy, which is otherwise dissipated in naphthalene excimers and aggregates that dominate in the copolymer aggregates formed in an aqueous environment. The obtained nanocapsules were shown to serve as both stable nanocontainers and efficient nanoreactors for photooxidation of perylene as an exemplary reaction. The reaction photosensitized by the polymeric naphthalene chromophores proceeded at least 3 times faster in the capsules than in the aggregates, disregarding the pH of the medium. Such properties make these novel capsules promising for numerous applications concerning photosensitized reactions that may be carried out in an aqueous medium and benefit from the confinement effect.
Scalable frames in Tensor Product Of Hilbert Spaces

‎Tight frames are very similar to orthonormal bases and can be used as a good alternative to them‎. ‎Scaling frames are introduced as a method to transform a general frame to a tight one‎. ‎This paper investigates in under what conditions the tensor product of two frames is a scalable frame‎. ‎We expand some results concerning frame operations of eigenvalues to tensor product of Hilbert spaces‎. ‎Finally‎, ‎we will show that if one of the frames is scalable‎, ‎better conditions are obtained for the approximation of tensor product of frames that is not scalable‎.
Climate Tipping and Economic Growth: Precautionary Capital and the Price of Carbon

The optimal reaction to a productivity shock which becomes more imminent with global warming is to price carbon (proportional to the marginal hazard of a catastrophe) to curb the risk of climate change, but also to accumulate precautionary capital to facilitate smoothing of consumption and curb the adverse effects of the calamity on the economy. We allow for conventional marginal climate damages as well and decompose the optimal carbon price in two catastrophe components and a conventional component. Moreover, the producivity catastrophe is compared with recoverable catastrophes and with a shock to the temperature response.
Modeling Alternative Futures with General Morphological Analysis

General morphological analysis (GMA) is a method for systematically structuring and analyzing the total set of relationships contained in multi-dimensional, non-quantifiable problem complexes. During the past 15 years, GMA has been extended, computerized and applied to long-term strategy management and organizational structuring. It is especially useful for developing scenario models and mapping alternative futures. This article outlines the fundamentals of the morphological approach and describes its use in a number of case studies in scenario development and futures projections done for Swedish government authorities and NGOs.
The Prismatic Layer of Pinna: A Showcase of Methodological Problems and Preconceived Hypotheses

The prismatic layer of Pinna (Mollusca) is one of the most studied models for the understanding of the biomineralization mechanisms, but our knowledge of the organic components of this layer is limited to the proteins of the soluble organic matrices. The interplay of the mineral and organic matrices is studied using scanning electron and atomic force microscopy, infra-red spectrometry, thermogravimetric analyses, aminoacids analyses, thin layer chromatography (TLC), X-ray fluorescence, X-ray Absorption near Edge Structure (XANES) and time-of-flight secondary ion mass spectrometry (TOF-SIMS). Proteins, polysaccharides and lipids are detected within the prisms and their envelopes. The role of the technical choices to study calcareous biominerals is evidenced, showing that a single analysis is not enough to decipher complex biominerals.
Analysis of 3D scale and size effects in numerical concrete

Size effect on strength of quasi-brittle materials like concrete, ice and rock, in the literature often referred as geomaterials, has been an issue of discussion over the last three decades. Size effect investigations have been carried out either by experiments or through numerical simulations. Usually mechanical properties of specimens of different sizes (volumes) are investigated. Most commonly, specimens are scaled two-dimensionally. In a numerical study, fracture experiments were investigated subjected to 3point bending. Here, concrete prisms are scaled in all three dimensions. As numerical model a 3D beam lattice model was used, which has proven to be quite suitable for simulating fracture experiments of concrete. Samples are modeled with regular lattices with inclusion of the concrete heterogeneity. The aggregate content Pk and the aggregate geometry can vary. The aggregates shapes can be either ideal spherical, crushed or oval shaped. For building an ideal spherical aggregate distribution, a computer program is used. In case of non-spherical aggregates, a different approach, which is described in Chapter 4, is adopted: Small real concrete prisms containing aggregates with high density (like marble) are scanned directly by means of X-ray tomography and the resulting 3D images are implemented into the 3D lattice. Without the availability of huge computing facilities and parallel solvers, fracture simulation with 3D models and size effect investigation can not be done. Even with state-of-the-art computing facilities at the time the simulations were conducted, the size range from the smallest to the largest specimen was limited to 1:8. There were also other constraints: specimen sizes are rather small and the ratio of the specimen size and largest aggregate diameter D/dmax is for some sizes small (with D/dmax < 3). Numerical results of the size effect analyses are presented in Chapters 5 to 7. Dependent which aggregate shapes are used in the mixture, the fracture behaviour differs. Regardless of aggregate content and shape, size effect on bending strength can be found in all cases. However, the calculated slopes in
Modelling and Analysis on Noisy Financial Time Series

Building the prediction model(s) from the historical time series has attracted many researchers in last few decades. For example, the traders of hedge funds and experts in agriculture are demanding the precise models to make the prediction of the possible trends and cycles. Even though many statistical or machine learning (ML) models have been proposed, however, there are no universal solutions available to resolve such particular problem. In this paper, the powerful forward-backward non-linear filter and wavelet-based denoising method are introduced to remove the high level of noise embedded in financial time series. With the filtered time series, the statistical model known as autoregression is utilized to model the historical times aeries and make the prediction. The proposed models and approaches have been evaluated using the sample time series, and the experimental results have proved that the proposed approaches are able to make the precise prediction very efficiently and effectively.
Market Competition, Perceived Environmental Uncertainty, Supply Chain Management Systems, and Organizational Performance: Hotel Starred in Bali Province, Indonesia

Abstract- The purpose of this study is to examine the effect of market competition (MC) and perceived environmental uncertainty (PEU) on the use of supply chain management (SCM) information and the utilization of SCM information on organizational performance, based on contingency theory. Data were collected using a questionnaire sent directly to the main managers of three, four and five-star hotels in the Province of Bali, Indonesia. This study uses organizational level analysis units. The data obtained were 122 and analyzed using WarpPls 6.0. The results showed that MC and PEU had a positive and significant effect on the utilization of SCM information (broad scope, timeliness, aggregation, and integration). In addition, the use of SCM information, affects the performance of three, four and five-star hotels in Bali Province, Indonesia.
Cognitive vs Chronological Age as Barriers to Using Wearable Activity Monitors in Older Adults

Despite widespread availability, the use of smart devices is still very limited among seniors who could benefit from adopting these systems. This research-in-progress study draws on the theory of aging and subjective assessments of health, as well as information systems adoption literature to propose a theoretical model to explore the effects of older adults’ cognitive age on their disability perceptions which can influence their adoption of smart devices. The results will be achieved using a combination of qualitative and quantitative methods. Potential contributions from this research to theory and practice are also outlined.
Identifying Market Segments for Technology Adoption 1

In the 1940s it was first noted that the adoption of agricultural innovations tended to follow a normal type distribution. Rogers (1964) articulated this process and classified farmers into five groups according to their speed of adoption: innovators, early adopters, early majority, late majority and laggards. Further, Rogers noted that speed of adoption tended to be a function of wealth, age, education, risk preference, sensitivity to social pressure and organizational memberships. This adoption-diffusion model has important marketing implications. If the model holds, the optimal strategy for encouraging adoption is to develop a marketing strategy that will encourage the innovators and early adopters to being using the product, who will then influence others to imitate them, as they tend to be opinion leaders in the community. However, the adoption-diffusion model was originally developed to explain the adoption of technologies such as hybrid corn, where adoption is relatively costless. Modern technologies can be quite different, involving sizeable expenditures in equipment, infrastructure or human capital, and/or involving large additional commitments of time. In this study, the relevance of Rogers (1964) adoption diffusion model is investigated for a new modern technology “Irrigator Pro”, which is a computer based irrigation-scheduling software developed by the US Department of Agriculture. For this technology, the market segments with the greatest propensity to adopt Irrigator Pro were found to be different to those that would be predicted using the traditional adoption-diffusion model.
Slither: A Static Analysis Framework for Smart Contracts

This paper describes Slither, a static analysis framework designed to provide rich information about Ethereum smart contracts. It works by converting Solidity smart contracts into an intermediate representation called SlithIR. SlithIR uses Static Single Assignment (SSA) form and a reduced instruction set to ease implementation of analyses while preserving semantic information that would be lost in transforming Solidity to bytecode. Slither allows for the application of commonly used program analysis techniques like dataflow and taint tracking. Our framework has four main use cases: (1) automated detection of vulnerabilities, (2) automated detection of code optimization opportunities, (3) improvement of the user's understanding of the contracts, and (4) assistance with code review. In this paper, we present an overview of Slither, detail the design of its intermediate representation, and evaluate its capabilities on real-world contracts. We show that Slither's bug detection is fast, accurate, and outperforms other static analysis tools at finding issues in Ethereum smart contracts in terms of speed, robustness, and balance of detection and false positives. We compared tools using a large dataset of smart contracts and manually reviewed results for 1000 of the most used contracts.
The Effect of Residential Location and Housing Unit Characteristics on Labor Force Participation of Childbearing Women in Indonesia: Using Twin Births As A Quasi-Natural Experiment

I empirically investigated the influence of residential location and housing unit characteristics on the labor force participation of childbearing women by applying quasi-experimental methods and taking a developing countryâ€™s perspective â€“ where the family size tends to grow faster. While the choices of residential location and housing unit characteristics are rarely exogenous, it is important to deal with the endogeneity problem. I use instrumental variable models, with twin births and gender composition as the exogenous sources of variation in the family size, and exploit an enormous micro dataset from the Indonesian Census Population 2010. Previous works of literature have examined the effect of twin birth on the female labor supply, but less attention given to the housing decision. This study provides new evidence of a forward-looking behavior about the residential location and housing consumption due to household size effects and shows that such behavior will most likely influence the female labor supply
Model Averaging OLS and 2SLS: An Application of the WALS Procedure

More commonly, applied and theoretical researchers are examining model averaging as a tool when considering estimation of regression models. Weighted-average least squares (WALS), originally proposed by Magnus and Durbin (1999, Econometrica) within the framework of estimating some of the parameters of a linear regression model when other coefficients are of no interest, is one such model averaging method with their proposed approach being a Bayesian combination of frequentist ordinary least squares and restricted least squares estimators. We generalize their work, along with that of other researchers, to consider averaging ordinary least squares (OLS) and two stage least squares (2SLS) estimators when possibly one or more regressors are endogenous. We derive asymptotic properties of our weighted OLS and 2SLS estimator under a local misspecification framework, showing that results from the existing WALS literature apply equally well to our case. In particular, determining the optimal weight function reduces to the problem of estimating the mean of a normally distributed random variate, which is unrelated to the details specific to the regression model of interest, including the extent of correlation between the explanatory variable(s) and the error term. We illustrate our findings with two examples. The first example, from a commonly adopted econometrics textbook, considers returns to schooling, and the second case is a growth regression application, which examines whether religion assists in explaining disparities in cross-country economic growth.