Miracle-dz/UniFAR-FTUs huggingface dataset:
Capital Allocation in Large Banks - A Renewed Look at Practice

Capital allocation frameworks play an important role in large financial institutions for risk management and performance measurement. These frameworks are predominately developed by practitioners and undergo continuous change. Instead of using economic capital, banks rely for the allocation of equity capital to their business units increasingly on regulatory capital measures like risk-weighted assets. In my paper, I assess the methods used in nowadays practice from a theoretical viewpoint. I demonstrate based on simulated asset and equity returns that some of the commonly used methods provide unreliable results. For example, if RAROC is used in combination with a single firm-wide cost of equity rate, the capital charge is systematically overestimated for businesses that are lowly correlated with the overall market, or for businesses with a left-skewed return distribution. Further, if the cost of equity of listed standalone peers is used as a reference to determine business unit specifc hurdle rates, it is essential to consider differences in leverage, as in the absence of a leverage adjustment the capital charge is underestimated.
Implementing ERP in India–Issues and Problems

ABSTRACT ERP (Enterprise Resource Planning) is a successful technique of integrating business processes to one computer system so that the information is easily available and accessible to everybody in the system. Even though the technique is successful and helps in reducing the lead times, inventory costs, labor costs, etc., the adoption rate is low in India. This paper focuses on the problem areas that companies face while implementing ERP in their business processes. The basic reasons that have accounted for low implementation are that the organization structure in the businesses is still based on traditional management techniques, the communication infrastructure is very poor, the labor laws and low level of support from the government.
Simulation Research on Speed Sensorless Control Technique for PMSM in Electric Drive Mining Truck

In order to achieve sensorless control for permanent magnet synchronous motor (PMSM)，an observer based on model reference adaptive system (MRAS) is designed to estimate the rotor speed according to the mathematic model. A speed sensorless vector control system is established and simulated with Simulink. Simulation results show that the MRAS-based control system, which is able to implement the speed sensorless vector control for PMSM, can preferably track the rotor speed with high precision.
Neurochemical substrates of the rewarding effects of MDMA: implications for the development of pharmacotherapies to MDMA dependence

In recent years, studies with animal models of reward, such as the intracranial self-stimulation, self-administration, and conditioned place preference paradigms, have increased our knowledge on the neurochemical substrates of the rewarding effects of 3,4-methylenedioxymetamphetamine (MDMA) in rodents. However, pharmacological and neuroimaging studies with human participants are scarce. Serotonin [5-hydroxytryptamine (5-HT)], dopamine (DA), endocannabinoids, and endogenous opiates are the main neurotransmitter systems involved in the rewarding effects of MDMA in rodents, but other neurotransmitters such as glutamate, acetylcholine, adenosine, and neurotensin are also involved. The most important finding of recent research is the demonstration of differential involvement of specific neurotransmitter receptor subtypes (5-HT2, 5-HT3, DA D1, DA D2, CB1, &mgr; and &dgr; opioid, etc.) and extracellular proteins (DA and 5-HT transporters) in the acquisition, expression, extinction, and reinstatement of MDMA self-administration and conditioned place preference. It is important to extend the research on the effects of different compounds acting on these receptors/transporters in animal models of reward, especially in priming-induced, cue-induced, and stress-induced reinstatement. Increase in knowledge of the neurochemical substrates of the rewarding effects of MDMA may contribute to the design of new pharmacological treatments for individuals who develop MDMA dependence.
INSIGHT AND EMERGING CHALLENGES ON JAPAN'S INFORMATION AND COMMUNICATION TECHNOLOGY SECTOR

The more science and technology has advanced, the more of research and development have been active in businesses, and businesses have been benefited from their outcome. Not only businesses enjoy the outcome on their own, but they also export the outcome to cross-borders, so called technology trade. Japan generated 1.63 trillion Yen excess of export out of technology trade in 2008. The export has sustained the Japan’s economy. This paper explores the insight of Japan’s technology trade, points out a remarkable excess of technology import in ICT sector, and describes Japan’s challenges for establishing technology competitiveness in ICT sector.
Arrhythmogenic right ventricular cardiomyopathy/dysplasia: clinical impact of molecular genetic studies.

Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is an inherited heart muscle disease that predominantly affects the right ventricle (RV). It is characterized pathologically by RV myocardial atrophy with fibrofatty replacement and clinically by ventricular electric instability with ventricular tachycardia or ventricular fibrillation that may lead to sudden death, primarily in young people and athletes.1 Later in the disease evolution, progression of RV muscle disease and left ventricular involvement may result in heart failure.2 The condition was initially believed to be a developmental defect of the RV myocardium, leading to the original designation of “dysplasia. ” This concept has evolved over the last 25 years into the current perspective of a genetically determined “cardiomyopathy. ”3 Clinical diagnosis of ARVC/D is often difficult because of the nonspecific nature of disease features and the broad spectrum of phenotypic manifestations. The advent of the molecular genetic era has provided new insights in understanding the pathophysiology of ARVC/D, showing that it is a desmosomal disease resulting from defective cell adhesion proteins such as plakoglobin, desmoplakin, plakophilin-2, and desmoglein-2.4–7 The availability of molecular testing for mutation screening of disease genes offers the possibility to identify genetically affected individuals. Potential clinical impact of genotype determination includes diagnosis (family screening and preclinical diagnosis); prediction of clinical phenotype (penetrance, gene-specific clinical manifestations); risk stratification (assessment of malignant versus benign mutations); clinical and genetic counseling (restriction of physical activity, family planning); and therapy (prevention of sudden death by implantable cardioverter/defibrillator [ICD]). Articles p 1641 and p 1650 In this issue of Circulation , studies by Dalal et al8 in the United States and van Tintelen et al9 in the Netherlands address the prevalence and clinical expression of mutations in the plakophilin-2 gene ( PKP2 ) in ARVC/D patient populations of comparable size and fulfilling the task force diagnostic criteria. …
Interactive ray tracing of massive and deformable models

Ray tracing is a fundamental algorithm used for many applications such as computer graphics, geometric simulation, collision detection and line-of-sight computation. Even though the performance of ray tracing algorithms scales with the model complexity, the high memory requirements and the use of static hierarchical structures pose problems with massive models and dynamic data-sets. We present several approaches to address these problems based on new acceleration structures and traversal algorithms. We introduce a compact representation for storing the model and hierarchy while ray tracing triangle meshes that can reduce the memory footprint by up to 80%, while maintaining high performance. As a result, can ray trace massive models with hundreds of millions of triangles on workstations with a few gigabytes of memory. We also show how to use bounding volume hierarchies for ray tracing complex models with interactive performance. In order to handle dynamic scenes, we use refitting algorithms and also present highly-parallel GPU-based algorithms to reconstruct the hierarchies. In practice, our method can construct hierarchies for models with hundreds of thousands of triangles at interactive speeds. Finally, we demonstrate several applications that are enabled by these algorithms. Using deformable BVH and fast data parallel techniques, we introduce a geometric sound propagation algorithm that can run on complex deformable scenes interactively and orders of magnitude faster than comparable previous approaches. In addition, we also use these hierarchical algorithms for fast collision detection between deformable models and GPU rendering of shadows on massive models by employing our compact representations for hybrid ray tracing and rasterization.
Type III Transforming Growth Factor-β (TGF-β) Receptor Mediates Apoptosis in Renal Cell Carcinoma Independent of the Canonical TGF-β Signaling Pathway

Purpose: Alterations in transforming growth factor-β (TGF-β) signaling occur early during malignant transformation of renal epithelial cells and are associated with loss of type III TGF-β receptor (TβRIII) expression. We evaluated the role of TβRIII in mediation of apoptosis using in vitro cell culture and in vivo animal models of clear cell renal cell carcinoma. Experimental Design: TβR3 expression was manipulated with adenoviral gene vector delivery system in vitro and in vivo. Induction of apoptosis and signaling through the Smad and mitogen-activated protein kinase (MAPK) pathways were examined at various time points after infection. To study viral oncolysis in vivo, human renal cell carcinoma cells were implanted s.c. in the flanks of nude mice and treated with intratumoral injections of adenovirus. Results: Restoring TβRIII expression in clear cell renal cell carcinoma resulted in a marked induction of apoptosis using in vitro cell culture and in vivo animal models. The expression of the cytoplasmic domain, but not the extracellular domain, of TβRIII mimicked the induction of apoptosis by full-length TβRIII in cell culture and the growth inhibition of tumors in athymic nude mice. TβRIII-associated apoptosis was not dependent on signaling through the canonical TGF-β/Smad pathway but was mediated through p38 MAPK. Conclusion: These findings indicate a novel mechanistic antitumor function for TβRIII and further support its role as an important tumor suppressor in clear cell renal cell carcinoma.
Enhancing Financial Inclusion: The Catalytic Role of Self Help Groups

A large section of rural population does not have any access to formal credit. The exclusion of such a vast segment of the population warranted a new form of intermediary and in response to this self help groups emerged in India. Whether SHGs could be an effective intermediary in bringing more financial inclusion is studied in this article. It is observed that financial inclusion through SHG efforts has a tremendous potential, but there is the need of increasing effort by NGOs, state governments and MFIs and banks. To enhance the ambit of inclusion through the SHG format other products like micro insurance and money transfer services also need to be introduced along with lone credit facility.
Antibiotic and Bacteriocin Sensitivity of Listeria monocytogenes Strains Isolated from Different Foods

This study aimed to determine the antibiotic and bacteriocin sensitivity of Listeria monocytogenes strains isolated from animal derived foods. With disc diffusion assay, all fourteen L. monocytogenes strains were suscepti-ble to the antibiotics, including penicillin G, vancomycin, tetracycline, chloramphenicol, rifampicin, erythromycin, gentamicin and trime- thoprim. However, the percentages of fosfomycin and streptomycin resistances were 92.9% and 7.1%, respectively. Multiple resistances were not observed among the tested strains. The results of well diffusion assays showed that all strains were inhibited by the cell-free supernatant of a bacteriocin-producing strain, Pediococcus acidilactici 13, with the inhibition zones ranging from 16.00 to 24.50 mm. These results provide useful information on antibiotic resistance of L. monocytogenes strains isolated from foods, and can potentially be used to develop bacteriocin-based interventions to guard against the hazards associated with L. monocytogenes in ready-to-eat meat and poultry products.
Group II metabotropic glutamate receptor type 2 allosteric potentiators prevent sodium lactate-induced panic-like response in panic-vulnerable rats

Rats with chronic inhibition of GABA synthesis by infusion of l-allyglycine, a glutamic acid decarboxylase inhibitor, into their dorsomedial/perifornical hypothalamus are anxious and exhibit panic-like cardio-respiratory responses to treatment with intravenous (i.v.) sodium lactate (NaLac) infusions, in a manner similar to what occurs in patients with panic disorder. We previously showed that either NMDA receptor antagonists or metabotropic glutamate receptor type 2/3 receptor agonists can block such a NaLac response, suggesting that a glutamate mechanism is contributing to this panic-like state. Using this animal model of panic, we tested the efficacy of CBiPES and THIIC, which are selective group II metabotropic glutamate type 2 receptor allosteric potentiators (at 10–30mg/kg i.p.), in preventing NaLac-induced panic-like behavioral and cardiovascular responses. The positive control was alprazolam (3mg/kg i.p.), a clinically effective anti-panic benzodiazepine. As predicted, panic-prone rats given a NaLac challenge displayed NaLac-induced panic-like cardiovascular (i.e. tachycardia and hypertensive) responses and “anxiety” (i.e. decreased social interaction time) and “flight” (i.e. increased locomotion) -associated behaviors; however, systemic injection of the panic-prone rats with CBiPES, THIIC or alprazolam prior to the NaLac dose blocked all NaLac-induced panic-like behaviors and cardiovascular responses. These data suggested that in a rat animal model, selective group II metabotropic glutamate type 2 receptor allosteric potentiators show an anti-panic efficacy similar to alprazolam.
Synaptic transmission is impaired at neuronal autonomic synapses in agrin‐null mice

Neuronal synapse formation is a multistep process regulated by several pre‐ and postsynaptic adhesion and signaling proteins. Recently, we found that agrin acts as one such synaptogenic factor at neuronal synapses in the PNS by demonstrating that structural synapse formation is impaired in the superior cervical ganglia (SCG) of z+ agrin‐deficient mice and in SCG cultures derived from those animals. Here, we tested whether synaptic function is defective in agrin‐null (AGD−/−) ganglia and began to define agrin's mechanism of action. Our electrophysiological recordings of compound action potentials showed that presynaptic stimulation evoked action potentials in ≈40% of AGD−/− ganglionic neurons compared to 90% of wild‐type neurons; moreover, transmission could not be potentiated as in wild‐type or z+ agrin‐deficient ganglia. Intracellular recordings also showed that nerve‐evoked excitatory postsynaptic potentials in AGD−/− neurons were only 1/3 the size of those in wild‐type neurons and mostly subthreshold. Consistent with these defects in transmission, we found an ≈40–50% decrease in synapse number in AGD−/− ganglia and cultures, and decreased levels of differentiation at the residual synapses in culture. Furthermore, surface levels of acetylcholine receptors (AChRs) were equivalent in cultured AGD−/− and wild‐type neurons, and depolarization reduced the synaptic localization of AChRs in AGD−/− but not wild‐type neurons. These findings provide the first direct demonstration that agrin is required for proper structural and functional development of an interneuronal synapse in vivo. Moreover, they suggest a novel role for agrin, in stabilizing the postsynaptic density of nAChR at nascent neuronal synapses. © 2007 Wiley Periodicals, Inc. Develop Neurobiol, 2007
Synapses in the Network

In the face of apparent failures to govern complex environmental problems by the central state, new modes of governance have been proposed in recent years. Network governance is an emerging concept that has not yet been consolidated. In network governance, processes of (collective) learning become an essential feature. The key issue approached here is the mutual relations between network structure and learning, with the aim of improving environmental management. Up to now, there have been few attempts to apply social network analysis (SNA) to learning and governance issues. Moreover, little research exists that draws on structural characteristics of networks as a whole, as opposed to actor-related network measures. Given the ambiguities of the concepts at stake, we begin by explicating our understanding of both networks and learning. In doing so, we identify the pertinent challenge of individual as opposed to collective actors that make up a governance network. We introduce three learning-related functions that networks can perform to different degrees: information transmission, deliberation, and resilience. We address two main research questions: (1) What are the characteristics of networks that foster collective learning in each of the three dimensions? To this end, we consider SNA-based network measures such as network size, density, cohesion, centralization, or the occurrence of weak as opposed to strong ties. (2) How does collective learning alter network structures? We conclude by outlining a number of open issues for further research.
Exploiting Big Data for Evaluation Studies

The collection and analysis of relevant data for evaluating public policies is not a straightforward task. An important type of such studies is the so-called ex-post evaluation. The main objective of ex-post evaluations is to determine to what extent a realized intervention is successful in tackling a societal challenge, e.g., youth unemployment. At a first glance an obvious method is to collect some baseline measurements for a set of relevant variables, apply the intervention for a while and collect the new measurement values for the same set of variables. Then, comparing the measurement values of the variables before and after the intervention provides an insight into the extent of successfulness of the intervention. This, however, is only true if the "ceteris paribus" condition holds. In practice it is infeasible to enforce this condition for societal challenges. Often, after having the baseline measurements, several phenomena emerge that may impact the new measurements without being taken into account. This makes it difficult to determine how much of the measured differences between the values of the variables before and after the intervention should be attributed to the emerging phenomena (or the so-called counterfactuals) and how much of the differences can be attributed to the applied intervention. This paper discusses how exploiting big data may contribute to the task of elucidating the influences of counterfactuals (and interventions) in ex-post evaluation studies. The paper proposes a framework to utilize big data for accounting for the impact of emerging phenomena in ex-post evaluation studies.
An Examination of the Market Structure of the U.S. Produce Industry

Recent literature, largely from the U.S. Department of Agriculture Economic Research Service, indicates that substantial changes have occurred in the produce industry in recent years. With the rise of retail mass merchandisers and increased concentration in the retail food industry, the procurement power of these large firms reportedly has also increased. With direct buying and contracting, market intermediaries such as brokers and wholesalers allegedly are being bypassed. As a result, these market intermediaries ostensibly are also consolidating, becoming fewer and larger with increased emphasis on servicing the food-service industry. However, the findings of this study indicate that there is no convinc­ ing evidence that the market structure of the U.S. produce industry has markedly changed since the early 1980s. While supermarket concentration has increased noticeably, the same cannot be said for produce market intermediaries such as brokers and wholesalers.
Customer‐led and market‐oriented: a matter of balance

This article is prompted by Slater and Narver’s (1998) SMJ article entitled ‘Customer-led and market-oriented: Let’s not confuse the two’. It is suggested here that Slater and Narver’s contention that strategic success is a function of market-led orientation rather than customer-led orientation is too reductionist a proposition which gives inadequate weight to the resource endowment and scale differences between companies. The argument is offered that success through time for the bulk of businesses will be directly related to close relationships with existing customers, particularly for smaller companies, which are the vast majority. Copyright © 1999 John Wiley & Sons, Ltd.
SUPERVISED FEATURE SELECTION BASED EXTREME LEARNING MACHINE ( SFS-ELM ) CLASSIFIER FOR CYBER BULLYING DETECTION IN TWITTER

Cyber bullying detection that are prevailing commonly in social networks like Twitter is one of the focussed research area. Text mining and detecting cyber bullying has several research challenges and lot of research scope to work with. This research work makes use of supervised feature selection by ranking method in order to choose the features from the tweets. After that extreme learning machine (ELM) classifier is employed in order to perform the detection of cyber bullying tweets. Performance metrics such as accuracy and time taken for classification are chosen in order to evaluate the efficiency of the classifiers namely ELM and the proposed SFS-ELM. Implementations are done in MATLAB tool. From the obtained results it is evident that the proposed SFS-ELM produces better results than that of ELM Keywords— Cyber bullying, Twitter, feature selection, classification, detection, extreme learning machine, machine learning.
Probabilistic model-based sentiment analysis of twitter messages

We present a machine learning approach to sentiment classification on twitter messages (tweets). We classify each tweet into two categories: polar and non-polar. Tweets with positive or negative sentiment are considered polar. They are considered non-polar otherwise. Sentiment analysis of tweets can potentially benefit different parties, such as consumers and marketing researchers, for obtaining opinions on different products and services. We present methods for text normalization of the noisy tweets and their classification with respect to the polarity. We experiment with a mixture model approach for generation of sentimental words, which are later used as indicator features of the classification model. Based on a gold standard manually annotated ensemble of tweets, with the new approach, we obtain F-scores that are relatively 10% better than a classification baseline that uses raw word n-gram features.
Business Communication Technologies: A New Course

This article describes a new course that focuses on the impact of evolving communication technologies on business. Two core questions are addressed in the class: First, how does a manager or employee choose the appropriate channel for a given communication situation? Second, how does an organization choose which technologies are appropriate for its business needs? In the course, we answer those questions by examining strategic models, assessing specific technologies, and presenting case studies. The article discusses these ideas and evaluates the effectiveness of the course.