Miracle-dz/UniFAR-FTUs huggingface dataset:
DAMPAK FLUKTUASI HARGA MINYAK DUNIA TERHADAP PEREKONOMIAN INDONESIA

Studi ini bertujuan untuk mengetahui dampak fluktuasi harga minyak di pasar dunia terhadap perekonomian Indonesia periode tahun 2000–2011. Dengan menggunakan data time series bulanan dan model VAR, studi ini menganalisis dampak fluktuasi harga minyak dunia terhadap pertumbuhan ekonomi, tingkat inflasi, uang beredar, nilai tukar riil, dan suku bunga. Hasil analisis menunjukkan bahwa fluktuasi harga minyak di pasar dunia: (i) berdampak positif terhadap pertumbuhan ekonomi selama 3 bulan (satu kuartal), (ii) mendorong laju inflasi domestik selama satu tahun, (iii) meningkatkan jumlah uang beredar di dalam negeri; penambahan jumlah uang beredar berlangsung selama 5 bulan, (iv) berdampak negatif terhadap nilai tukar riil rupiah selama 10 bulan dan (v) menyebabkan naiknya suku bunga di dalam negeri (efek ini berlangsung selama 10 bulan). Oleh karena itu, pemerintah perlu menempuh langkah-langkah yang bisa mentransformasikan kebiasaan masyarakat yang semula boros BBM menjadi hemat BBM. Selain itu, dibutuhkan kebijakan yang mendorong pengembangan energi alternatif. This study aims to determine the impact of oil price shocks in the world markets on the economy of Indonesia during 2000–2011. Based on monthly time series data and using VAR model, the study tries to analyze effects of oil price shocks to economic growth, inflation rates, money supply, real exchange rates and interest rates. The results show several conclusions: (i) the oil price shocks in the world market have a positive impact on quarterly economic growth; (ii) it also pushes up the domestic inflation rate for a year; (iii) it increases the domestic money supply which lasts for 5 months; (iv) it negatively affects the real exchange rate of Rupiah for 10 months and (v) it leads to rising domestic interest rates (the effect of oil shocks on interest rates lasted for 10 months). Therefore, government needs to take steps that could transform the people habits of fuel uses from wasteful to the efficient one. In addition, the alternative energy development also needs to promoted.
Search Decisions with Limited Memory

This paper concerns a decision problem of an agent, searching to find a low price, whose memory is represented by a partition of the set of possible past prices. The number of elements in the partition is limited. I characterize the optimal partition for the case of a single decision, and then consider memory allocation among several decisions. I consider a case in which a consumer who must allocate a single bit of memory among two decision problems would do better to allocate it exclusively to one of the problems than to use it to convey joint information about both.
On Dynamic Phase Transitions in Satisfiability Problems

The problems to optimize properties of a frustrated system of many variables is a complex matter. Such problems arise in both combinatorial computational problems as well as in complex materials such as spin glasses. Since the theoretical treatment of such system is very hard and complicated one would like to find simpler methods to examine them. In this thesis random K-SAT problems are studied. We have developed a new heuristic method called ASAT which is a stochastic local search method which seem to be faster and simpler than existing ones. It is able to solve problem instances in linear time up to the constraint per variable ratio 4.21. We also examine the state space structure seen by the heuristic by a procedure called ’Simulated heating’. This also reveals the optimal value for the noise parameter in the optimization problem. How this scale with constraint size, K, is also investigated. Finally we use a statistic approach and model random 3-SAT problems with master equations.
Chandra Orion Ultradeep Project: Observations and Source Lists

We present a description of the data reduction methods and the derived catalog of more than 1600 X-ray point sources from the exceptionally deep 2003 January Chandra X-Ray Observatory (Chandra) observation of the Orion Nebula Cluster and embedded populations around OMC-1. The observation was obtained with Chandra's Advanced CCD Imaging Spectrometer (ACIS) and has been nicknamed the Chandra Orion Ultradeep Project (COUP). With an 838 ks exposure made over a continuous period of 13.2 days, the COUP observation provides the most uniform and comprehensive data set on the X-ray emission of normal stars ever obtained in the history of X-ray astronomy.
A reinforcement learning algorithm for adjusting antecedent parameters and weights of fuzzy rules in a fuzzy classifier

This paper proposes a new fuzzy classifier based on reinforcement learning. A fuzzy rule based classification system is a special type of fuzzy modeling where its output is a discrete crisp value. The main challenging issue in designing fuzzy classifiers is constructing fuzzy rule base. Here, each fuzzy rule is considered as an agent who has to select the suitable class between candidate classes. It is considered a weight for each candidate class in each rule. These weights are adjusted using the proposed reinforcement learning algorithm. For each sample of training data, if the final result is true, the winner rule (agent) is rewarded and some other rules are punished based on the criteria which are defined in this paper. If the result is false, the winner rule is punished and the rules with high firing strength that have selected correct class are rewarded. Moreover, the input membership functions of rules are adjusted regarding the defined criteria which depend on punishment frequency of rules. The proposed approach is assessed on some UCI datasets. We compare our ideas in comparison with conventional reward and punishment scheme and multi-layer perceptron network. The experimental results show that our proposed approach outperforms both mentioned approaches in the terms of quality of classification and precision.
Simulation peculiarities of high-frequency zero-current switching quasi-resonant boost converter

The article presents a comparative analysis of three approaches to the modelling of a zero-current switching quasi-resonant boost converter (ZCS-QRBC) performed in Matlab Simulink. The widely used approach based on the use of Power Electronics library components from SimPowerSystems Toolbox is found to be the most effective for an introduction at a glance to the basics of ZCS-QRBC operation as well as for educational purposes. A SPICE-model of ZCS-QRBC based on physical principles of elements operation is preferable to use to obtain the practical results quickly, elaborate ZCS-QRBC topology, select components, and establish a background for experimental investigations. In the later stages of system design the limited use of the simplified model is possible in order to comply with requirements of existing computational resources. It allows estimating the influence of a control method on the system dynamics and control accuracy or stabilization of a certain parameter.
A simplified estimation procedure based on the EM algorithm for the power series cure rate model

ABSTRACT The family of power series cure rate models provides a flexible modeling framework for survival data of populations with a cure fraction. In this work, we present a simplified estimation procedure for the maximum likelihood (ML) approach. ML estimates are obtained via the expectation-maximization (EM) algorithm where the expectation step involves computation of the expected number of concurrent causes for each individual. It has the big advantage that the maximization step can be decomposed into separate maximizations of two lower-dimensional functions of the regression and survival distribution parameters, respectively. Two simulation studies are performed: the first to investigate the accuracy of the estimation procedure for different numbers of covariates and the second to compare our proposal with the direct maximization of the observed log-likelihood function. Finally, we illustrate the technique for parameter estimation on a dataset of survival times for patients with malignant melanoma.
Cloning, expression, and characterization of a novel alkali‐tolerant xylanase from alkaliphilic Bacillus sp. SN5

A xylanase gene (xyn11A) was cloned from the genomic library of alkalophilic Bacillus sp. SN5. It encoded a polypeptide of 366 amino acids, consisting of a family 11 glycoside hydrolase, a short linker region, and a family 36 carbohydrate‐binding module (CBM). The intact xylanase Xyn11A and the CBM‐linker‐truncated Xyn11A‐LC were expressed in Escherichia coli BL21 (DE3). Both purified recombinant proteins exhibited the highest activity at 55 °C. The optimal pH for Xyn11A activity was 7.5, whereas Xyn11A‐LC showed a broad pH profile (>80% activity at pH 5.5–8.5) with optimal activity at pH 5.5 and 7.5–8.0. They had high alkali tolerance, retaining over 80% residual activity after preincubation at pH 8.5–11.0 at 37 °C for 1 H. Xyn11A‐LC showed better thermal stability, lower affinity, and lower catalytic activity to insoluble xylan than Xyn11A, whereas its specific activity for soluble beechwood xylan (4,511.9 U/mg) was greater than that of Xyn11A (3,136.4 U/mg). These results implied that the CBM of Xyn11A could change the enzymatic properties and play a role in degrading insoluble xylan. Xyn11A‐LC is a family 11 alkali‐tolerant cellulase‐free xylanase with high specific activity, which qualifies it as a potential candidate for industrial applications, especially in the paper industry.
Manifold Learning via Multi-Penalty Regularization

Manifold regularization is an approach which exploits the geometry of the marginal distribution. The main goal of this paper is to analyze the convergence issues of such regularization algorithms in learning theory. We propose a more general multi-penalty framework and establish the optimal convergence rates under the general smoothness assumption. We study a theoretical analysis of the performance of the multi-penalty regularization over the reproducing kernel Hilbert space. We discuss the error estimates of the regularization schemes under some prior assumptions for the joint probability measure on the sample space. We analyze the convergence rates of learning algorithms measured in the norm in reproducing kernel Hilbert space and in the norm in Hilbert space of square-integrable functions. The convergence issues for the learning algorithms are discussed in probabilistic sense by exponential tail inequalities. In order to optimize the regularization functional, one of the crucial issue is to select regularization parameters to ensure good performance of the solution. We propose a new parameter choice rule “the penalty balancing principle” based on augmented Tikhonov regularization for the choice of regularization parameters. The superiority of multi-penalty regularization over single-penalty regularization is shown using the academic example and moon data set.
Lean or agile: A solution for supply chain management in the textiles and clothing industry?

The textiles and apparel industry has been neglected in terms of supply chain management research. Recently, the industry has undergone a great deal of change, particularly with global sourcing and high levels of price competition. In addition, textiles and clothing has market characteristics, such as short product lifecycle, high volatility, low predictability, and a high level of impulse purchase, making such issues as quick response of paramount importance. This article discusses characteristics of the textiles and apparel industry and identifies the perspectives of lean, agile and leagility (a combination of these) within existing supply chain literature, which have been proffered as solutions to achieving quick response and reduced lead times. Through case studies of textile and apparel companies, different approaches to supply chain management are illustrated.
Stick–slip friction of gecko-mimetic flaps on smooth and rough surfaces

The discovery and understanding of gecko ‘frictional-adhesion’ adhering and climbing mechanism has allowed researchers to mimic and create gecko-inspired adhesives. A few experimental and theoretical approaches have been taken to understand the effect of surface roughness on synthetic adhesive performance, and the implications of stick–slip friction during shearing. This work extends previous studies by using a modified surface forces apparatus to quantitatively measure and model frictional forces between arrays of polydimethylsiloxane gecko footpad-mimetic tilted microflaps against smooth and rough glass surfaces. Constant attachments and detachments occur between the surfaces during shearing, as described by an avalanche model. These detachments ultimately result in failure of the adhesion interface and have been characterized in this study. Stick–slip friction disappears with increasing velocity when the flaps are sheared against a smooth silica surface; however, stick–slip was always present at all velocities and loads tested when shearing the flaps against rough glass surfaces. These results demonstrate the significance of pre-load, shearing velocity, shearing distances, commensurability and shearing direction of gecko-mimetic adhesives and provide us a simple model for analysing and/or designing such systems.
Hotel Employees' Perception of the Statutory Minimum Wage Policy in Hong Kong

Employee compensation is one of the largest expenses for businesses. Given the labor-intensive nature of the hotel industry, hotel employees' perceptions of the statutory minimum wage (SMW) policy have become a major concern for hotel operators since the introduction of the policy in Hong Kong. This exploratory study examines these perceptions, together with hotel employees' job and compensation satisfaction and intention to leave, since the introduction of the SMW policy. A survey of 161 hotel employees in Hong Kong was carried out. Respondents demonstrated high awareness of the SMW policy but viewed its effect on the hotel industry as limited. The largest gap between the perceived importance of, and satisfaction with, a factor related to job satisfaction was found for the benefits package. As well as making a contribution to the academic literature, this study provides practical implications of the SMW policy for the hotel industry in Hong Kong and other countries considering adopting a similar measure.
Détection et suivi d'objets mobiles perçus depuis un capteur visuel embarqué

Cette these traite de la detection et du suivi d'objets mobiles dans un environnement dynamique, en utilisant une camera embarquee sur un robot mobile. Ce sujet represente encore un defi important car on exploite uniquement la vision mono-camera pour le resoudre. Nous devons detecter les objets mobiles dans la scene par une analyse de leurs deplacements apparents dans les images, en excluant le mouvement propre de la camera. Dans une premiere etape, nous proposons une analyse spatio-temporelle de la sequence d'images, sur la base du flot optique epars. La methode de clustering a contrario permet le groupement des points dynamiques, sans information a priori sur le nombre de groupes a former et sans reglage de parametres. La reussite de cette methode reside dans une accumulation suffisante des donnees pour bien caracteriser la position et la vitesse des points. Nous appelons temps de pistage, le temps necessaire pour acquerir les images analysees pour bien caracteriser les points. Nous avons developpe une carte probabiliste afin de trouver les zones dans l'image qui ont les probabilites la plus grandes de contenir un objet mobile. Cette carte permet la selection active de nouveaux points pres des regions detectees precedemment en permettant d'elargir la taille de ces regions. Dans la deuxieme etape nous mettons en oeuvre une approche iterative pour executer detection, clustering et suivi sur des sequences d'images acquises depuis une camera fixe en interieur et en exterieur. Un objet est represente par un contour actif qui est mis a jour de sorte que le modele initial reste a l'interieur du contour. Finalement nous presentons des resultats experimentaux sur des images acquises depuis une camera embarquee sur un robot mobile se deplacant dans un environnement exterieur avec des objets mobiles rigides et nonrigides. Nous montrons que la methode est utilisable pour detecter des obstacles pendant la navigation dans un environnement inconnu a priori, d'abord pour des faibles vitesses, puis pour des vitesses plus realistes apres compensation du mouvement propre du robot dans les images.
Stock Price Reactions to On-Target Earnings Announcements Implications for Earnings Management

We investigate the consequences of earnings management by analyzing stock price reactions to on-target quarterly earnings announcements (earnings that coincide with analysts' consensus expectations) during 1993-1999. We use techniques advanced in Jones (1991), Kang and Sivaramakrishnan (1995), and Collins and Hribar (2000) to distinguish observations where firms apparently manage earnings in order to meet expectations. We find that mean security returns during the earnings announcement period are 0.18% to 0.91% less for observations where firms apparently increase earnings than for those where firms apparently decrease earnings to meet expectations. These differences are statistically significant at conventional levels. We also find that returns during the earnings disclosure period vary inversely with the extent that firms appear to manage earnings upward. Overall, the evidence suggests that market participants are aware of incentives to manage earnings to meet expectations, and that they discount managed earnings components when interpreting quarterly earnings disclosures. Finally, we point out that the issue of stock splits should be investigated with care when using published consensus analyst forecasts.
A Survey on Time-Varying Copulas: Specification, Simulations, and Application

The aim of this article is to bring together different specifications for copula models with time-varying dependence structure. Copula models are widely used in financial econometrics and risk management. They are considered to be a competitive alternative to the Gaussian dependence structure. The dynamic structure of the dependence between the data can be modeled by allowing either the copula function or the dependence parameter to be time-varying. First, we give a brief description of eight different models, among which there are fully parametric, semiparametric, and adaptive methods. The purpose of this study is to compare the applicability of each particular model in different cases. We conduct a simulation study to show the performance for model selection, to compare the model fit for different setups and to study the ability of the models to estimate the (latent) time-varying dependence parameter. Finally, we provide an illustration by applying the competing models on the same financial dataset and compare their performance by means of Value-at-Risk.
Long slot Van Atta array for far-field wireless power transfer

The design of a Van Atta array of long slots is presented for far-field wireless power transfer (WPT). The proposed array overcomes the scanning and bandwidth limitations of Van Atta arrays based on resonant elements for WPT applications. The proposed array consists of four slots with eight input ports, resulting in 32 access points. The Van Atta scheme is implemented by connecting pairs of input ports with coaxial cables. Measurements validate the design at a center frequency of 5.8 GHz. Monostatic RCS measurements show that the array has a −10 dB beamwidth of about 118° in the E-plane. The scanning performance of the array is preserved in the considered band: 4.8–6.2 GHz.
Coupled Metabolic and Photolytic Pathway for Degradation of Pyridinedicarboxylic Acids, Especially Dipicolinic Acid

Three isomers of pyridinedicarboxylic acid (PDCA) (2,3-, 2,5-, and 2,6-PDCA) were partially oxidized by marine bacteria when grown aerobically on the corresponding phthalate analogs. The metabolites, unlike the parent PDCAs, absorbed light in the solar actinic range (wavelengths greater than 300 nm) and were readily degraded in sunlight. The principal product from 2,6-PDCA (dipicolinic acid) metabolism was extracted from a culture fluid, purified by column chromatography, and analyzed by UV-visible, infrared, and 13C nuclear magnetic resonance spectroscopy. The compound was identified as 2,3-dihydroxypicolinic acid (2,3-DHPA). 2,3-DHPA was photolyzed in aqueous solution (pH 8.0) with a half-life of 100 min. Eight photoproducts, three of which were photolabile, were detected by high-performance liquid chromatography. Ammonia was also photoproduced from 2,3-DHPA. Analysis of the photoproducts by UV-visible spectroscopy and by high-performance liquid chromatography of 2,4-dinitrophenylhydrazones indicated that the products were conjugated carbonyls and carboxylic acids. Six of the photoproducts were readily consumed by bacterial strain CC9M. In illuminated aquatic environments, coupled bio- and photodegradative mechanisms probably contribute to the degradation of PDCAs.
Delft University of Technology Analysis of the genes involved in thiocyanate oxidation during growth in continuous culture of the haloalkaliphilic sulfur-oxidizing bacterium Thioalkalivibrio thiocyanoxidans ARh 2T using transcriptomics

Thiocyanate (N C S ) is a moderately toxic, inorganic sulfur compound. It occurs naturally as a by-product of the degradation of glucosinolatecontaining plants and is produced industrially in a number of mining processes. Currently, two pathways for the primary degradation of thiocyanate in bacteria are recognized, the carbonyl sulfide pathway and the cyanate pathway, of which only the former has been fully characterized. Use of the cyanate pathway has been shown in only 10 strains of Thioalkalivibrio, a genus of obligately haloalkaliphilic sulfuroxidizing Gammaproteobacteria found in soda lakes. So far, only the key enzyme in this reaction, thiocyanate dehydrogenase (TcDH), has been purified and studied. To gain a better understanding of the other genes involved in the cyanate pathway, we conducted a transcriptomics experiment comparing gene expression during the growth of Thioalkalivibrio thiocyanoxidans ARh 2T with thiosulfate with that during its growth with thiocyanate. Triplicate cultures were grown in continuous substratelimited mode, followed by transcriptome sequencing (RNA-Seq) of the total mRNA. Differential expression analysis showed that a cluster of genes surrounding the gene for TcDH were strongly upregulated during growth with thiocyanate. This cluster includes genes for putative copper uptake systems (copCD, ABC-type transporters), a putative electron acceptor (fccAB), and a two-component regulatory system (histidine kinase and a 54-responsive Fis family transcriptional regulator). Additionally, we observed the increased expression of RuBisCO and some carboxysome shell genes involved in inorganic carbon fixation, as well as of aprAB, genes involved in sulfite oxidation through the reverse sulfidogenesis pathway. IMPORTANCE Thiocyanate is a moderately toxic and chemically stable sulfur compound that is produced by both natural and industrial processes. Despite its significance as a pollutant, knowledge of the microbial degradation of thiocyanate is very limited. Therefore, investigation of thiocyanate oxidation in haloalkaliphiles such as the genus Thioalkalivibrio may lead to improved biotechnological applications in wastewater remediation.