Miracle-dz/UniFAR-FTUs huggingface dataset:
Equilibrium Return in a Multiperiod Asset Market with CRRA Agents : Analytic Support of Simulation Models

In this paper we provide explanations for the results of recent simulation model of financial market. These explanations are based upon mathematical analysis of a dynamic model of a market with arbitrary number of heterogeneous investors dividing their wealth between two assets. The investors’ choices are endogenously modeled in a very general way which is, in particular, consistent with the solutions of the maximization of expected power utility. The local stability analysis of equilibria is performed. The results have implications for the questions of the agents’ survival and return determination in the financial market. We show that these implications are in agreement with the results of simulations performed recently. Apart from support for that simulations, our analytic approach allows us to extend the results, explore their rigorousness and also perform some additional, more complex simulations.
A Distributed Directory Cache Coherence Scheme and Its Eeects on Network Performance List of Figures Figure Page 1 System of 8 Processors Constructed Using 2x2 Switches in The

This paper proposes a new protocol for maintaining cache coherence in a large multiprocessor system. The study focuses on systems with private caching that use a multistage network to interconnect the processors. The protocol, called the Distributed Directory Scheme, distributes part of the directory information into the interconnection network switches. The redistribution of the directory information allows the delivery of coherency commands to be streamlined, thus eliminating a bottleneck inherent in the traditional Full Vector Scheme proposed by Censier and Feautrier. When evaluating the coherence protocol performance, the operations of both the cache coherence protocol and interconnection network are considered simultaneously. It is discovered that both the Distributed Directory Scheme and the Full Vector Scheme cause undesirable traac patterns (hot spots) inside the network. However, the hot spots that arise from the coherence traac in the Distributed Directory Scheme respond quite well to (simpliied) network combining. It is found that the Distributed Directory Scheme access latencies are as much as 34% improved over the Full Vector Scheme access latencies. 5 Diierence in read access latency between the Distributed Directory and Full Vector Scheme without combining for write probability of 0. 6 Non-uniform percentage of the Forward network traac created by the Acknowledgement messages sent by the processors to the memory 7 Average message delay in the Forward network for the Full Vector Scheme for write probabilities 0.2, 0.1, 0.05, and 0. 8 Diierence in message delay in the Forward network for the Full Vector Scheme (switch size = 4). 10 Read access latencies with combining for write probability = 0.1 and 0. 11 Percent decrease in read access latency in Full Vector and Distributed Directory Schemes due to the combing for write probability of 0. 12 Diierence in read access latency between the Distributed Directory and Full Vector Scheme with combining for write probability of 0.
Example-based conceptual styling framework for automotive shapes

Conceptual design in the automotive industry is a time-consuming process. Iterations between concept sketches, created with traditional two dimensional methods, and 3D digital representations of a prototype are currently one of the big bottlenecks. In this paper we present a framework for an integrated 2D-3D design environment. The core of the framework is a model representing the characteristic lines of automotive shapes built from a set of example shapes. From every example shape we extract the same set of characteristic lines and represent them with a feature vector of deformation gradients. Given a set of constraints, our method can generate a new feature vector with an optimization procedure. We provide examples for meaningful manipulations. We demonstrate that these manipulations are intuitive and create plausible shapes.
Thoroughly analyzing the use of ring oscillators for on-chip hardware trojan detection

With the globalization of the IC design flow, structural integrity verification to detect parasitic electrical activities has emerged as an important research domain for testing the genuineness of an Integrated Circuit (IC). Sensors like Ring Oscillators (RO) have been proposed to precisely monitor the internal behaviour of the ICs. In this paper we propose an experimental analysis of the impact of parasitic electrical activities on the frequencies of ROs and on the internal supply voltages measured. Our observations lead us to identify the limits of the usability of ROs for practical and embedded detection of Hardware Trojans.
MRI evidence of mesial temporal sclerosis in subjects without seizures

The identification of mesial temporal sclerosis (MTS) on magnetic resonance imaging (MRI) is critical in the evaluation for temporal lobectomy. The purpose of this study was to estimate the prevalence of MTS by MRI in the general population. We reviewed the charts of patients undergoing MRI scans over an 18-month period. In order to be included, patients had to have no history of seizures, and the MRIs had to read as 'normal'. Patients were excluded if there was a history of seizures, mental illness, or alcohol abuse, and if they had a family history of seizures. Ages had to be from 5 to 50 years. All patients had MRI scans performed in three planes on 1.5 T systems. MRI diagnosis of MTS was based on standard visual diagnostic criteria analyzing: (1) hippocampal atrophy and (2) increased hippocampal T2 signal. Out of 375 charts reviewed, 204 met the inclusion criteria. Of the 204, 29 (14%) had abnormal and asymmetric mesial temporal structures consistent with a diagnosis of unilateral MTS. Nineteen (9.3%) had hippocampal atrophy only, two (1%) had T2 signal abnormalities, and eight (4%) met both criteria. There are some 'false positives' and MRI evidence for MTS is only meaningful in the proper clinical context.
Implementing Psychiatric Interventions on a Medical Ward: Effects on Patients’ Quality of Life and Length of Hospital Stay

Objective The authors investigated the effects of implementing psychiatric interventions on a general medical ward by means of a stepped detection and treatment strategy conducted by a consultation–liaison (CL) nurse in terms of reducing length of hospital stay (LOS) and improving quality of life (QOL) at discharge. Materials and Methods One hundred ninety-three patients participated in a controlled trial, in which patients were screened with COMPRI and INTERMED. A nurse under supervision of a CL psychiatrist conducted interventions, consisting of simple psychiatric interventions by herself, referral to auxiliary services, or initiation of postdischarge care. Intervention patients were compared with historic controls on LOS and QOL (SF36) at discharge. Results In multivariate analysis of variance, a significant effect of the intervention on QOL (p = 0.037) was found, which diminished after controlling for confounders (p = 0.28). No significant effect on LOS was found for the whole sample (p = 0.72), but in patients age 65 years or older, a reduction in LOS (p = 0.05) was found. This effect remained after controlling for confounders (p = 0.06). Conclusions These data suggest that screening for risk of increased health care might improve outcomes in general medical inpatients. Because of the design of the study, however, these findings should be considered preliminary and confirmed in a larger, multicenter, randomized controlled trial.
Fuzzy channel ranking estimation in cognitive wireless networks

In an opportunistic spectrum access (OSA) of cognitive radio wireless networks (CRNs), unlicensed secondary users (cognitive radios, CRs) have only partial knowledge of channel parameters (or other users information) and asymmetric spectral opportunities due to time and space varying channel availabilities. Due to the inherent asymmetry and uncertainty of traffic patterns, CRs can have difficulties to determine properly the real usability of unoccupied channels. In this paper we propose a channel ranking algorithm exploiting fuzzy logic (FL) theory. Using current and prior knowledge of channel availability each CR user builds a channel ranking list that serves as an input entry for an asynchronous neighborhood discovery protocol. Since the rendezvous protocol exploits the channel prioritization, and gives more opportunities to better-quality channels, FL-based channel ranking leads to more efficient communications that traditional crisp value based approaches.
The comparison of “Idiot's Bayes” and multivariate kernel-density in forensic speaker identification using Chinese vowel /a/

The discriminant performance of likelihood ratios based on “Idiot's Bayes” approach and multivariate kernel density were examined on the speech of 21 male Chinese speakers using telephone recordings. The parameters used in this paper are formant central-frequencies, extracted from the Chinese vowel /a/. Experimental results show that the “Idiot's Bayes” approach provides a little stronger support for the same-speaker hypothesis and multivariate kernel density approach provides much stronger support for the different-speaker hypothesis; they both have good performance in Chinese vowel /a/.
An Instruction Folding Method to Prevent Reverse Engineering in Java Platform

To improve tamper resistance of programs against illegal modification, this paper proposes instruction folding applicable to Java platform. In the proposed method, at first, similar methods are selected in a Java program. Next, these methods are merged into one method and diffs among these methods are stored in the program. Then, at runtime, when one of the merged methods is executed, diffs are restored by self-modification, which is realized by the Java instrumentation mechanism. The proposed method is resilient against tampering of folded method. Even if an adversary modifies the folded method, the program goes crash because the method is repeatedly modified at runtime.
Estimating Large Scale Signaling Networks through Nested Effects Models from Intervention Effects in Microarray Data

Targeted interventions in combination with the measurement of secondary effects can be used to computationally reverse engineer features of upstream nontranscriptional signaling cascades based on the nested effect structure. We extend previous work by Markowetz et al., who proposed a statistical framework to score hypothetical networks for this purpose. Our extensions go in several directions: We show how prior assumptions on the network structure can be incorporated into the scoring scheme by defining appropriate prior distributions on the network structure as well as on hyperparameters. A new approach called module networks is introduced to scale up the original approach, which is limited to around 5 genes, to infer large scale networks (up to more than 50 genes). Instead of the data discretization step needed in the original framework, we propose the usage of a beta-uniform mixture distribution on the p-value profile, resulting from differential gene expression calculation, to quantify effects. Extensive simulations on artificial data and application of our module network approach to infer the signaling network between 10 genes in the ER-α pathway in human MCF-7 breast cancer cells show that our approach gives sensible results. Using a bootstrapping approach this reconstruction is found to be statistically stable.
An Institutional Analysis of IFRS Adoption in Poor Jurisdictions

The last two decades witnessed a movement towards harmonization of international financial reporting standards (IFRS) throughout the global economy. This investigation seeks to identify the factors that could explain the adoption of IFRS by poor jurisdictions. While there has been a considerable amount of literature published on the effects and key drivers of IFRS adoption in both developed and developing countries, little attention has been paid to jurisdictions with less developed capital markets and low income levels exclusively. Drawing upon the Institutional Isomorphism theory and analyzing a sample of 45 poor jurisdictions between 2008 and 2013, the study empirically shows that poor jurisdictions are driven by legitimacy concerns rather than by economic reasoning to adopt an international accounting perspective. This in turn has implications for the IASB, as it should seek to influence institutional pressures within a particular jurisdiction in order to promote IFRS adoption. Keywords—IFRS Adoption, isomorphism, poor jurisdictions, accounting harmonization.
Who's who in Gnome: Using LSA to merge software repository identities

Understanding an individual's contribution to an ecosystem often necessitates integrating information from multiple repositories corresponding to different projects within the ecosystem or different kinds of repositories (e.g., mail archives and version control systems). However, recognising that different contributions belong to the same contributor is challenging, since developers may use different aliases. It is known that existing identity merging algorithms are sensitive to large discrepancies between the aliases used by the same individual: the noisier the data, the worse their performance. To assess the scale of the problem for a large software ecosystem, we study all Gnome Git repositories, classify the differences in aliases, and discuss robustness of existing algorithms with respect to these types of differences. We then propose a new identity merging algorithm based on Latent Semantic Analysis (LSA), designed to be robust against more types of differences in aliases, and evaluate it empirically by means of cross-validation on Gnome Git authors. Our results show a clear improvement over existing algorithms in terms of precision and recall on worst-case input data.
1 Boundary Artifact Minimization on Best Matching Blocks in Wavelet-Based Video Compression

The widespread usage of digital videos calls for an intense need of video compression techniques to conserve storage space and minimize bandwidth utilization. Discrete wavelet transform (DWT) has manifested its intrinsic multiresolution and scalability advantages on image compressions without the annoying blocking artifacts. Thus, Motion estimation and motion compensation (MEMC) combined with wavelet transformation has been beneficially applied to improve video compression efficiency and accuracy. However, circular convolution in wavelet transform generates border distortion because of the discontinuous periodic extension on the two ends of the signal, and becomes more apparent as more levels of decomposition are involved. In addition, hierarchical motion vector refinement needs accurate motion estimation from the lower resolution subframes without further distortions after multiple convolutions with the wavelet filter. This paper investigates the use of symmetric-extended wavelet transform (SWT) to reduce the boundary distortions experienced in multiresolutional motion estimation, so as to improve the compression performances in scalable video applications.
Interpretational overhead in system software

Interpreting a program carries a runtime penalty: the interpretational overhead. Traditionally, a compiler removes interpretational overhead by sacrificing inessential details of program execution. However, a broad class of system software is based on non-standard interpretation of machine code or a higher-level language. For example, virtual machine monitors emulate privileged instructions; program instrumentation is used to build dynamic call graphs by intercepting function calls and returns; and dynamic software updating technology allows program code to be altered at runtime. Many of these frameworks are performance-sensitive and several efficiency requirements—both formal and informal—have been put forward over the last four decades. Largely independently, the concept of interpretational overhead received much attention in the partial evaluation (“program specialization”) literature. This dissertation contributes a unifying understanding of efficiency and interpretational overhead in system software. Starting from the observation that a virtual machine monitor is a self-interpreter for machine code, our first contribution is to reconcile the definition of efficient virtualization due to Popek and Goldberg with Jones optimality, a measure of the strength of program specializers. We also present a rational reconstruction of hardware virtualization support (“trap-and-emulate”) from context-threaded interpretation, a technique for implementing fast interpreters due to Berndl et al. As a form of augmented execution, virtualization shares many similarities with program instrumentation. Although several low-overhead instrumentation frameworks are available on today’s hardware, there has been no formal understanding of what it means for instrumentation to be efficient. Our second contribution is a definition of efficiency for program instrumentation in the spirit of Popek and Goldberg’s work. Instrumentation also incurs an implicit overhead because instrumentation code needs access to intermediate execution states and this is antagonistic to optimization. The third contribution is to use partial equivalence relations (PERs) to express the dependence of instrumentation on execution state, enabling an instrumentation/optimization trade-off. Since program instrumentation, applied at runtime, constitutes a kind of dynamic software update, we can similarly restrict allowable future updates to be consistent with existing optimizations. Finally, treating “old” and “new” code in a dynamically-updatable program as being written in different languages permits a semantic explanation of a safety rule that was originally introduced as a syntactic check.
Assessing open source software as a scholarly contribution

Introduction Academic computer science has an odd relationship with software: Publishing papers about software is considered a distinctly stronger contribution than publishing the software. The historical reasons for this paradox no longer apply, but their legacy remains. This limits researchers who see the open-source software movement as an opportunity to make a scholarly contribution. Expanded definitions of scholarship acknowledge both application and discovery as important components.1 One obstacle remains: evaluation. To raise software to the status of a first-class contribution, we propose "best practices" for the evaluation of the scholarly contribution of open-source software. Typically, scholars who develop software do not include it as a primary contribution for performance reviews. Instead, they write articles about the software and present the articles as contributions. This conflation of articles and software serves neither medium well. An article describes an original intellectual contribution consisting of an idea, the argument for its importance and correctness, and supporting data. In contrast, software is more often an implementation of prior ideas in a usable form. It bridges the often considerable gap between an idea and the practical application of that idea. The original idea and its implementation represent distinct kinds of contribution. The critical gap is the perceived incomparability of these two contributions. Lacking a concise description adapted to the traditional practices of performance review committees, software is difficult to evaluate as a scholarly contribution and is often relegated to second-class status. We propose a framework for common assessment based on widely accepted definitions of scholarship. Within this general framework, we consider the material and procedures that a performance review committee uses to evaluate a publication. We then describe how software can be summarized in a compatible form of bibliographic citation and supplementary material.
DOPAMINE AS A NEUROACTIVE SUBSTANCE IN THE JELLYFISH POLYORCHIS PENICILLATUS

Summary Recent studies have shown that nerve-rich tissues in the margin of Polyorchis penicillatus (Eschscholtz), one of the hydromedusae, contain dopamine. The present experiments were conducted to determine the physiological action of dopamine at the cellular level. In the current-clamp mode, dopamine, ranging from 10~ 8 to 10~ 3 moll~ 1 , applied to cultured swimming motor neurons of this jellyfish produced hyperpolarizations accompanied by a decrease of firing rate or complete inhibition of spiking produced by anodal break excitation. Dopamine in the voltage-clamp mode elicited outward currents at more positive levels than -5 5 mV, which is the reversal potential of the response. The results of a series of ionic experiments suggest that the inhibitory effect of dopamine is caused by an increased permeability to potassium ions.
Development of a Direct Headspace Collection Method from Arabidopsis Seedlings Using HS-SPME-GC-TOF-MS Analysis

Plants produce various volatile organic compounds (VOCs), which are thought to be a crucial factor in their interactions with harmful insects, plants and animals. Composition of VOCs may differ when plants are grown under different nutrient conditions, i.e., macronutrient-deficient conditions. However, in plants, relationships between macronutrient assimilation and VOC composition remain unclear. In order to identify the kinds of VOCs that can be emitted when plants are grown under various environmental conditions, we established a conventional method for VOC profiling in Arabidopsis thaliana (Arabidopsis) involving headspace-solid-phase microextraction-gas chromatography-time-of-flight-mass spectrometry (HS-SPME-GC-TOF-MS). We grew Arabidopsis seedlings in an HS vial to directly perform HS analysis. To maximize the analytical performance of VOCs, we optimized the extraction method and the analytical conditions of HP-SPME-GC-TOF-MS. Using the optimized method, we conducted VOC profiling of Arabidopsis seedlings, which were grown under two different nutrition conditions, nutrition-rich and nutrition-deficient conditions. The VOC profiles clearly showed a distinct pattern with respect to each condition. This study suggests that HS-SPME-GC-TOF-MS analysis has immense potential to detect changes in the levels of VOCs in not only Arabidopsis, but other plants grown under various environmental conditions.
Three New Algorithms to Solve N-POMDPs

In many fields in computational sustainability, applications of POMDPs are inhibited by the complexity of the optimal solution. One way of delivering simple solutions is to represent the policy with a small number of alpha-vectors. We would like to find the best possible policy that can be expressed using a fixed number N of alpha-vectors. We call this the N-POMDP problem. The existing solver alpha-min approximately solves finite-horizon POMDPs with a controllable number of alpha-vectors. However alpha-min is a greedy algorithm without performance guarantees, and it is rather slow. This paper proposes three new algorithms, based on a general approach that we call alpha-min-2. These three algorithms are able to approximately solve N-POMDPs. Alpha-min-2-fast (heuristic) and alpha-min-2-p (with performance guarantees) are designed to complement an existing POMDP solver, while alpha-min-2-solve (heuristic) is a solver itself. Complexity results are provided for each of the algorithms, and they are tested on well-known benchmarks. These new algorithms will help users to interpret solutions to POMDP problems in computational sustainability.