Miracle-dz/UniFAR-FTUs huggingface dataset:
Pattern of Environmental Performance Relations, Environmental Disclosure, Firm Size, and Financial Performance of Proper-Member Companies Listed on Indonesia Stock Exchange

: This research aims to determine the influence of environmental performance on financial performance with environmental disclosure as the intervening variable and firm size as the moderating variable. The sample consisted of 110 firm-year samples of PROPER-member companies listed on the Indonesia Stock Exchange. The data was analyzed using the structural equation modeling – partial least squared (SEM-PLS) method using WarpPLS 5.0. The results show that environmental performance has a significant positive effect on financial performance. In addition, environmental performance has a significant positive effect on environmental disclosure; however, environmental disclosure is not proven to have any positive effect on financial performance. Environmental disclosure is also not proven to act as a mediating variable on the relationship between environmental performance and financial performance. Meanwhile, this research shows that there is a statistically significant moderating effect of firm size on the relationship between environmental performance and financial performance.
Grapheme to phoneme conversion for Dutch

Grapheme-to-phoneme conversion (G2P) refers to the conversion of a written word to its pronunciation, which plays a crucial role in text-to-speech software and speechto-speech machine translation. We present a G2P model for the Dutch language based on a long short-term memory recurrent neural network (LSTM). Specifically, we use a deep bi-directional LSTM (biLSTM) that takes into consideration the context of the graphemes before predicting the phoneme sequence. By using contextual clues, our model also eliminates the need for explicit alignment of the dataset. We achieve an accuracy of 66.2% completely correct phoneme predictions using a single biLSTM-based model, and 75.5% accuracy when averaging the predictions from an ensemble of such models. Our results demonstrate the power of LSTMs in the G2P task and facilitate further G2P research using unaligned datasets.
Torque-Ripple Reduction and Fast Torque Response Strategy for Predictive Torque Control of Induction Motors

This paper proposes a simple control method of induction motors (IMs) with improved dynamic response and steady-state performance by using a model-based predictive control algorithm. The predictive torque control (PTC) method analyzes the relationship between the electrical torque and stator voltage of IMs by using the stator voltage vector magnitude to obtain the reference voltage vector angle and accurately control the electrical torque. However, the conventional PTC method has a fixed reference voltage vector magnitude and thus has a large torque ripple in the steady state and slow dynamics in the transient state. The proposed PTC method is based on mathematical equations, which allow minimization of torque error and calculation of a relevant reference voltage to establish a better dynamic response in the transient state and accurate control performance in the steady state. Excellent steady-state performance and a quick dynamic response of the proposed method are proved by the simulation and experimental results.
An exploration of growth in computer software micro firms

This paper investigates the drivers of growth in Swedish micro firms providing computer services. Analysis is based on linked data from several sources: registers on business, value added tax (VAT) and education as well as from production statistics. ordinary least squares (OLS) estimations, including approximately 7000 computer service micro firms, show that initial relative labor productivity of micro firms (compared to that of large firms) is significantly positively related to subsequent employment growth in the two following years. Furthermore, exporting micro firms grow faster than those that only sell on the domestic market. The link between exporting and firm growth is higher for export starters. Separate estimations for young micro firms confirm the positive relationships for both exporting and initial productivity. However, share of workers with a tertiary degree is not significantly related to the employment growth of micro firms. Quantile regressions reveal that both exporting and the initial productivity level are particularly important for high-growth micro firms.
Chicken Granulosa Cells Show Differential Expression of Epidermal Growth Factor (EGF) and Luteinizing Hormone (LH) Receptor Messenger RNA and Differential Responsiveness to EGF and LH Dependent upon Location of Granulosa Cells to the Germinal Disc1

Abstract Granulosa cells in the chicken follicle exhibit different phenotypes according to their location relative to the germinal disc (GD). Granulosa cells proximal to the GD (referred to as proximal granulosa cells) are more proliferative, whereas granulosa cells distal to the GD (referred to as distal granulosa cells) are more differentiated. We have shown that epidermal growth factor (EGF) derived from the GD stimulated proliferation of granulosa cells proximal to the GD, whereas extraovarian LH promoted differentiation. We tested the hypothesis that phenotypic differences of granulosa cells are the result of differential responsiveness of granulosa cells to EGF and LH. We found that both granulosa and theca layers of chicken preovulatory follicles expressed mRNA for EGF receptor (EGFr) by polymerase chain reaction (PCR) analysis. However, only the granulosa layer showed differential expression of EGFr and LH receptor (LHr) mRNA. Competitive reverse transcription-PCR revealed that proximal granulosa cells expressed more EGFr mRNA but less LHr mRNA than distal granulosa cells. In addition, proximal granulosa cells proliferated more in response to EGF than their distal counterparts. We further demonstrated that EGF decreased LHr mRNA expression by granulosa cells in a dose-dependent manner, whereas EGF and LH had no effect on EGFr mRNA expression except at one dose of LH (15 ng/ml) that stimulated EGFr mRNA expression. Our findings suggest that EGF derived from the GD influences the phenotypes of granulosa cells. Granulosa cells proximal to the GD exhibit a proliferative phenotype possibly because they are exposed to and are more responsive to GD-derived EGF. Furthermore, GD-derived EGF decreases LHr mRNA expression by proximal granulosa cells and therefore results in less differentiated granulosa cell phenotype. In contrast, granulosa cells distal to the GD are not under the influence of EGF and exhibit a more differentiated phenotype.
Quantum Markov processes and applications in many-body systems

Gegenstand der vorliegenden Arbeit ist die Untersuchung von quantenmechanischen und klassischen Markov-Prozessen und deren Anwendung im Bereich der stark korrelierten Vielteilchensysteme. Unter einem Markov-Prozess versteht man eine spezielle Art eines stochastischen Prozesses, dessen weitere dynamische Entwicklung unabhangig ist von der Vorgeschichte seiner Entwicklung und nur von der derzeitigen Konfiguration abhangt. Die Anwendung von Markov-Prozessen im Bereich der statistischen Mechanik von klassischen Vielteilchensystemen hat eine lange Geschichte. Markov-Prozesse dienen nicht nur der Beschreibung der Dynamik von stochastischen Systemen, sondern liefern vielmehr auch eine sehr praktische Methode, mit dereren Hilfe grundlegende Eigenschaften komplexer Vielteilchenprobleme in Form eines probabilistischen Algorithmus berechnet werden konnen. Ziel dieser Arbeit ist es das Verhalten von quantenmechanischen Markov Prozessen, dies sind Markov-Prozesse, welchen ein quantenmechanischer Konfigurationsraum zu Grunde liegt, zu untersuchen und mit deren Hilfe komplexe Vielteilchensysteme besser zu verstehen. Daruber hinaus formulieren wir einen Quantenalgorithmus, mit dessen Hilfe es moglich ist, die thermischen- und Grundzustandseigenschaften von quantenmechanischen Vielteilchensystemen zu berechnen. Nachdem wir eine kurze Einfuhrung in das Feld der quantenmechanischen Markov-Prozesse gegeben haben, untersuchen wir deren Konvergenzeigenschaften. Wir finden Schranken fur die Konvergenzraten der quantenmechanischen Prozesse, basierend auf einer Verallgemeinerung von geometrischen Schranken, welche fur klassische Prozesse gefunden wurden. Wir verallgemeinern ein Abstandsmas, die Chi-Quadrat Divergenz fur nicht kommutative Wahrscheinlichkeitsraume, welches unseren Untersuchungen zu Grunde liegt. Diese Divergenz ermoglicht auch eine Verallgemeinerung der detaillierten Balance fur quantenmechanische Prozesse. Danach konstruieren wir den Quantenalgorithmus, der als naturliche Verallgemeinerung des Metropolisalgorithmus fur quantenmechanische Hamiltonoperatoren verstanden werden kann. Wir beabsichtigen damit zu zeigen, dass ein Quantencomputer in der Lage ist, als universeller Quantensimulator zu fungieren, welcher nicht nur die Dynamik eines Quantensystems beschreiben kann, sondern auch den Zugang zu statischen Berechnungen ermoglicht. Danach untersuchen wir die Korrelationseigenschaften von klassischen Nichtgleichgewichtszustanden mit Methoden der Quanteninformationstheorie. Wir konstruieren eine Klasse von Matrix-Produkt-Zustanden, deren Korrelationen anhand von klassischen Markov-Prozessen verstanden werden konnen. Schlieslich untersuchen wir die Transporteigenschaften eines stationaren Nichtgleichgewichtszustandes. Die dynamische Gleichung ist so konstruiert, dass der Transport je nach Parameterwahl entweder hauptsachlich stochastisch oder hauptsachlich koharent stattfindet. Wir konnen somit die unterschiedlichen Formen des Transports innerhalb eines Modells miteinander vergleichen.
Reacting to different types of concept drift with adaptive and incremental one-class classifiers

Modern computer systems generate massive amounts of data in real-time. We have come to the age of big data, where the amount of information exceeds the perceptive abilities of any human being. Frequently the massive data collections arrive over time, in the form of a data stream. Not only the volume and velocity of data poses a challenge for machine learning systems, but also its variability. Such an environment may have non-stationary properties, i.e. change its characteristic over time. This phenomenon is known as concept drift, and is considered as one of the main challenges for moder learning systems. In this paper, we propose to investigate different methods for handling concept drift with adaptive soft one-class classifiers. One-class classification is a promising direction in data stream analytics, as it allows for a novelty detection, data description and learning with limited access to class labels. We describe an adaptive model of Weighted One-Class Support Vector Machine, augmented with mechanisms for incremental learning and forgetting. These allow for our models to swiftly adapt to changes in data, without any need for a dedicated drift detector. We carry out an experimental analysis of the behavior of our method with different forgetting rates for various types of concept drift. Additionally, we compare our classifier with state-of-the-art one-class methods for streaming data. We observe, that our adaptive soft one-class model can efficiently handle different types of concept drifts, while delivering a highly satisfactory accuracy for streaming data.
Labor Laws and Innovation

When contracts are incomplete, dismissal laws prevent employers from arbitrarily discharging employees and thereby limit employers’ ability to hold up innovating employees after an innovation is successful. Therefore, dismissal laws can enhance employees’ innovative efforts and encourage firms to invest in risky but potentially groundbreaking projects. Other forms of labor laws that do not affect dismissal of employees do not have this bright side. We find support for these predictions in empirical tests that exploit country-level changes in dismissal laws in the United States, the United Kingdom, France, and Germany: more stringent dismissal laws foster innovation, particularly in innovation-intensive industries, but other labor laws do not.
Latest Progress and Infrastructure Innovations of Big Data Technology

With the constantly emerging of new ways to release information on the internet, together with the rise of several other technologies such as cloud computing and the internet of things, data is explosively growing at an unprecedented speed, manifesting the coming of the era of big data. Facing the challenge of large-scale, demand diversity and real-time processing for big data, the efficient processing technology has become the core issue of research in the big data field. This paper elaborates in detail the key technologies dealing with big data processing as distributed computing technology, incremental processing technology, stream computing technology, etc., analyses and summaries the mainstream technology platform and system of big data represented by Hadoop, and finally introduces the latest infrastructure innovation progress driven by big data in the last part, including GPU acceleration technology, Software Defined Flash (SDF), etc.
EU Common Agricultural Policy Post-2020: Exploring the Effects of Safety-Net Policy Instruments

High price volatility in EU and world markets, caused by climate change and extreme weather events, the growing market orientation of the Common Agricultural Policy (CAP) of the EU and other factors, led to income uncertainty. This pushed the discussion about the future design of the EU CAP aiming at more target-oriented policies to stabilize farm income. At the same time the financial crises and their consequences increased the focus on the efficiency of CAP instruments. Compared to the US farm bill, risk management instruments have played only a minor role in the EU CAP in the past. Against this background, this study aims at analysing different policy options of so-called safety nets in the future CAP to cover downside risks of farm income. Specifically, this study aims at answering the following questions. How, and to what extent can safety net instruments protect from downside risks and stabilize agricultural incomes? How much will these flexible payments increase the CAP budget costs? Are the current US safety net policies a suitable model for designing such policies for the CAP post 2020? To answer these questions, this study applies an extended version of the Global Trade Analysis Project (GTAP) that depicts a much more detailed representation of the EU CAP policy instruments. In addition, this extended model includes new policy instruments to protect the agricultural sector in case of price, revenue and income losses. A stochastic component affects production and prices and thus income based on exogenous global yield shocks and enables the assessment of the income stabilising effect of the different policy instruments. We simulated a baseline scenario and three policy scenarios many times using the extended GTAP and considering the full range of yield shocks. This set-up allows us to assess the effects of safety net instruments on income stabilization and budget cost.
Breast edema following staging axillary node dissection in patients with breast carcinoma treated by radical radiotherapy

Seventy‐four patients with carcinoma of the breast were treated by irradiation without a mastectomy at Stanford between May 1973 and March 1980. Seventy‐six breasts were treated because two patients had bilateral simultaneous cancers. Breast edema was noted in 41% of these cases. Analysis of potential predisposing factors revealed that this complication occurred primarily in patients who received a staging axillary lymph node dissection. Lymphedema occurred in 26 of 33 breasts (79%) in patients who had staging axillary dissections; this complication developed in only three of 12 (25%) with axillary samplings and two of 31 (6%) with no axillary surgery. Two groups of patients were identified: (1) 28 patients whose breast edema occurrred early (prior to or during radiation therapy), and (2) three patients with late onset edema that developed several months postirradiation. The early edema, which is clearly related to axillary lymph node dissection, gradually improved during the follow‐up period with complete or near complete resolution expected by three years. Late onset edema was rare, appears to be related to an axillary radiation dose greater than 5500 rad, and may be irreversible. There was no correlation of breast edema with tumor stage, radiation time/dose factors, the use of bolus, patient weight, or breast size.
Spinal cord regeneration in a tail autotomizing urodele

Adult urodele amphibians possess extensive regenerative abilities, including lens, jaws, limbs, and tails. In this study, we examined the cellular events and time course of spinal cord regeneration in a species, Plethodon cinereus, that has the ability to autotomize its tail as an antipredator strategy. We propose that this species may have enhanced regenerative abilities as further coadaptations with this antipredator strategy. We examined the expression of nestin, vimentin, and glial fibrillary acidic protein (GFAP) after autotomy as markers of neural precursor cells and astroglia; we also traced the appearance of new neurons using 5‐bromo‐2′‐deoxyuridine/neuronal nuclei (BrdU/NeuN) double labeling. As expected, the regenerating ependymal tube was a major source of new neurons; however, the spinal cord cranial to the plane of autotomy showed significant mitotic activity, more extensive than what is reported for other urodeles that cannot autotomize their tails. In addition, this species shows upregulation of nestin, vimentin, and GFAP within days after tail autotomy; further, this expression is upregulated within the spinal cord cranial to the plane of autotomy, not just within the extending ependymal tube, as reported in other urodeles. We suggest that enhanced survival of the spinal cord cranial to autotomy allows this portion to participate in the enhanced recovery and regeneration of the spinal cord. J. Morphol. 2011. © 2011 Wiley Periodicals, Inc.
Detection et elimination d'irregularites sur les surfaces manipulees en c. A. O

Cette these traite du probleme de la detection et de correction des defauts sur les surfaces utilisees en cao. Elle propose deux nouvelles methodes de correction reposant sur l'amelioration du reseau de points de controle, les autres donnees demeurant inchangees. La premiere partie fixe le cadre de l'etude, rappelle quelques notions sur la modelisation des courbes et des surfaces en cao et la geometrie differentielle, et presente le probleme de la qualite des courbes et des surfaces. Une synthese de l'existant concernant les techniques d'inspection et de correction des surfaces est ensuite exposee. La deuxieme partie presente la premiere methode proposee pour la correction des surfaces convexes. Il s'agit d'une heuristique geometrique qui corrige automatiquement les surfaces localement presque convexes et opere en reconstruisant l'enveloppe convexe des points de controle. L'etude du probleme du lien entre la convexite de la surface et la convexite du polyedre de controle conduit a completer cette heuristique par un algorithme de regularisation du reseau de points de controle. La troisieme partie presente l'application de methodes globales d'optimisation (principalement l'algorithme du recuit simule qui est le mieux adapte) a la correction des surfaces. L'algorithme obtenu est alors general et s'applique a toutes les surfaces. Le principe consiste, en utilisant une approche stochastique, a minimiser l'energie de deformation de la surface calculee en fonction des positions d'un sous-ensemble de poles libres qui peuvent etre deplaces dans un intervalle dl autour de leur position initiale. Pour obtenir des performances compatibles avec l'environnement interactif des systemes de cao, l'energie de deformation est calculee sur le polyedre de controle a l'aide des courbures discretes (moyenne et gaussienne).
STRATEGIC DECISION-MAKING SUPPORTED BY TRADITIONAL FINANCIAL INDICATORS

Traditional financial indicators calculated from financial statements cannot provide adequate information for the management, do not support strategic decisions. The reason for this is the methodology used in producing financial statements and the operational logic of financial accounting. Financial accounting thinks in terms of business year that is 12 months. It deals with events of the past, more accurately, with so called economic activities. Financial accounting evaluates such economic activities in terms of monetary processes, which means that the traditional financial indicators have their limits in application. Could it mean that traditional financial indicators cannot be used in the long-term strategic decision making? In our study we point out two connections between financial indicators and strategic decision making. Firstly, we focus on financial indicators used in supported strategic decision making, in strategic indicator systems. Secondly, we focus on cases in which financial indicators complement the methods of strategic decision making, add something to the tools available in strategic management.
SCALE‐SPECIFIC SEX‐BIASED DISPERSAL IN THE VALAIS SHREW UNVEILED BY GENETIC VARIATION ON THE Y CHROMOSOME, AUTOSOMES, AND MITOCHONDRIAL DNA

We investigated sex specificities in the evolutionary processes shaping Y chromosome, autosomes, and mitochondrial DNA patterns of genetic structure in the Valais shrew (Sorex antinorii), a mountain dwelling species with a hierarchical distribution. Both hierarchical analyses of variance and isolation‐by‐distance analyses revealed patterns of population structure that were not consistent across maternal, paternal, and biparentally inherited markers. Differentiation on a Y microsatellite was lower than expected from the comparison with autosomal microsatellites and mtDNA, and it was mostly due to genetic variance among populations within valleys, whereas the opposite was observed on other markers. In addition, there was no pattern of isolation by distance for the Y, whereas there was strong isolation by distance on mtDNA and autosomes. We use a hierarchical island model of coancestry dynamics to discuss the relative roles of the microevolutionary forces that may induce such patterns. We conclude that sex‐biased dispersal is the most important driver of the observed genetic structure, but with an intriguing twist: it seems that dispersal is strongly male biased at large spatial scale, whereas it is mildly biased in favor of females at local scale. These results add to recent reports of scale‐specific sex‐biased dispersal patterns, and emphasize the usefulness of the Y chromosome in conjunction with mtDNA and autosomes to infer sex specificities.
Examining Predictors and Mediators of Vulnerability to Telecommunications Fraud among Senior Citizens in Taiwan

Advances in telecommunications technologies such as the online voice and video calling, smart phones, and micro messaging service have not only made life easier for millions of users, they also strengthened their social ties and improved their psychological well-being. On the other hand, potential risks of being defrauded go hand in hand with the social and psychological benefits of advanced telecommunications technologies in the mobile era. To respond to the pressing need for a better understanding of how fraudulent telecommunications occur, this study seeks to examine predictors and mediators of the vulnerability of seniors to telecommunications fraud with a focus on the role of calling behaviors, social presence, trust, perceived dependence, and perceived importance in telecommunications technology. Results show that 4 factors play essential roles in telecommunication among seniors. Implications of the findings for telecommunications policymaking are discussed.