Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving k-means clustering with genetic programming for feature construction

k-means is one of the most commonly used clustering algorithms in data mining. Despite this, it has a number of fundamental limitations which prevent it from performing effectively on large or otherwise difficult datasets. A common technique to improve performance of data mining algorithms is feature construction, a technique which combines features together to produce more powerful constructed features that can improve the performance of a given algorithm. Genetic Programming (GP) has been used for feature construction very successfully, due to its program-like structure. This paper proposes two representations for using GP to perform feature construction to improve the performance of k-means, using a wrapper approach. Our results show significant improvements in performance compared to k-means using all original features across six difficult datasets.
Positive modulation of alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptors in prefrontal cortical pyramidal neurons by a novel allosteric potentiator.

Positive modulators of glutamate alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptors can enhance cognitive function in several species. The present experiments compared the actions of a novel biarylpropylsulfonamide compound, LY404187, with the prototypical benzoylpiperidine, 1-(quinoxalin-6-ylcarbonyl)-piperidine (CX516), on AMPA receptors of prefrontal cortex (PFC) pyramidal neurons. LY404187 (0.03-10 microM) selectively enhanced glutamate-evoked currents through AMPA receptor/channels of acutely isolated pyramidal neurons with considerably greater potency (EC50 = 1.3 +/- 0.3 microM) and efficacy (Emax = 45.3 +/- 8.0-fold increase) than did CX516 (EC50 = 2.8 +/- 0.9 mM; Emax = 4.8 +/- 1.4-fold increase). Both LY404187 and CX516 increased the potency of the glutamate concentration-response profile by 6- and 3-fold, respectively. Rapid perfusion experiments demonstrated that LY404187 produced a marked suppression in the magnitude but no change in the kinetics of receptor desensitization; whereas CX516 produced little change in the degree and a modest deceleration of the desensitization process. In PFC slices, both spontaneous and stimulus-evoked AMPA receptor-mediated excitatory postsynaptic potentials were enhanced by nanomolar concentrations of LY404187. Voltage-sensitive N-methyl-D-aspartate (NMDA) receptor-dependent synaptic responses also were indirectly augmented as a consequence of greater postsynaptic depolarization. Consistent with the in vitro data, LY404187 was 1000-fold more potent than CX516 in enhancing the probability of discharge of PFC neurons in response to stimulation of glutamatergic afferents from hippocampus in vivo. This potentiation by LY404187 was reduced by both selective AMPA (LY300168, 1 mg/kg, i.v.) and NMDA (LY235959, 5 mg/kg, i.v.) receptor antagonists. Collectively, these results demonstrate that LY404187 is an extremely potent and centrally active potentiator of native AMPA receptors and has a unique mechanism of action. The therapeutic implications of AMPA receptor potentiators are discussed.
Design of bi-directional series resonant converter as peak power unit in hybrid electric vehicles

This article presents the design of a bi-directional series resonant DC-DC converter for hybrid electric vehicles using supercapacitors as the peak power unit. To achieve high efficiency, the converter is operated at zero current switching. The converter design, operation and working modes will be introduced and a control strategy, to keep the vehicle DC bus voltage stable, will be proposed.
The Global Infectious Disease Threat and Its Implications for the United States

Abstract : This report represents an important initiative on the part of the Intelligence Community to consider the national security dimension of a nontraditional threat. It responds to a growing concern by senior US leaders about the implications--in terms of health, economics, and national security--of the growing global infectious disease threat. The dramatic increase in drug resistant microbes, combined with the lag in development of new antibiotics, the rise of megacities with severe health care deficiencies, environmental degradation, and the growing ease and frequency of cross-border movements of people and produce have greatly facilitated the spread of infectious diseases. In June 1996, President Clinton issued a Presidential Decision Directive calling for a more focused US policy on infectious diseases. The State Department's Strategic Plan for International Affairs lists protecting human health and reducing the spread of infectious diseases as US strategic goals, and Secretary Albright in December 1999 announced the second of two major U.S. initiatives to combat HIV/AIDS. The unprecedented UN Security Council session devoted exclusively to the threat to Africa from HIV/ AIDS in January 2000 is a measure of the international community's concern about the infectious disease threat. As part of this new US Government effort, the National Intelligence Council produced this National Intelligence Estimate.
Expression of hepatitis A virus cDNA in Escherichia coli: antigenic VP1 recombinant protein

The genome of hepatitis A virus (HAV) was reverse transcribed into cDNA and molecularly cloned. cDNA clones coding for the capsid protein VP1 that carries the major HAV antigen were cloned into the expression vector pUR290 and expressed in Escherichia coli. The recombinant fusion protein reacted in an immunoblot with rabbit anti-HAV serum, suggesting that it possesses HAV antigenicity.
Intégration des données de sismique 4D dans les modèles de réservoir : recalage d'images fondé sur l'élasticité non linéraire

Dans une premiere partie, nous proposons une methodologie innovante pour la comparaison d'images en ingenierie de reservoir. L'objectif est de pouvoir comparer des cubes sismiques obtenus par simulation avec ceux observes sur un champ petrolier, dans le but de construire un modele representatif de la realite. Nous developpons une formulation fondee sur du filtrage, de la classification statistique et de la segmentation d'images. Ses performances sont mises en avant sur des cas realistes. Dans une seconde partie, nous nous interessons aux methodes de recalage d'images utilisees en imagerie medicale pour mettre en correspondance des images. Nous introduisons deux nouveaux modeles de recalage fondes sur l'elasticite non lineaire, ou les formes sont apprehendees comme des materiaux de type Saint Venant-Kirchhoff et Ciarlet-Geymonat. Nous justifions theoriquement l'existence de solutions ainsi que la resolution numerique. Le potentiel de ces methodes est illustre sur des images medicales.
The Purloined Poe : Lacan, Derrida & psychoanalytic reading

In 1956 Jacques Lacan proposed an interpretation of Edgar Allan Poe's "Purloined Letter" that at once challenged literary theorists and revealed a radical new concept of psychoanalysis. Lacan's far reaching claims about language and truth provoked a vigorous critique by Jacques Derrida, whose essay in turn spawned further responses from other writers. "The Purloined Poe" brings Poe's story together with these readings to provide a structured exercise in the elaboration of text interpretation.
Leveraging Big Data to Predict Firms Performance

—Though some research studies about big data have been reported in literature recently, few studies about applying big data analytics to analyze firms’ performance are performed and reported in existing business literature. Empowered by a novel framework of big data analytics, this paper illustrates our preliminary work of apply the proposed big data analytics framework to predict firms’ performance in stock market. In particular, the proposed framework leverages big data and probabilistic language modeling to analyze the stock performance of firms in near real-time. Our empirical test demonstrates the merits of the proposed framework. The practical implication of our research work is that firms can apply our big data analytics framework to analyze their internal and external performance, and hence develop more effective business strategies in advance.
Cryptocurrency and its forensic significance

Cryptocurrency is a relatively new form of investment. Its concept was first introduced in 2009, and has grown ever since. To this day, there are thousands of cryptocurrencies. Just as other currencies, cryptocurrency can be related to a crime. Ever since its introduction nearly a decade ago, there have been crimes where cryptocurrency are related. According to ACIC’s crime types, cryptocurrency are related to two crime categories: cybercrime, and illicit drugs. There are also other cases where the type of crimes is not listed as a part of ACIC’s. In response to the crimes that have occurred throughout the years, several governments have moved to establish laws regarding cryptocurrency. Some governments chose to ban cryptocurrency completely, whereas others opted for regulation.
On the dynamic pull-in of electrostatic actuators with multiple degrees of freedom and multiple voltage sources

This study considers the dynamic response of electrostatic actuators with multiple degrees of freedom that are driven by multiple voltage sources. The critical values of the applied voltages beyond which the dynamic response becomes unstable are investigated. A methodology for extracting a lower bound for this dynamic pull-in voltage is proposed. This lower bound is based on the stable and unstable static response of the system, and can be rapidly extracted because it does not require time integration of momentum equations. As example problems, the dynamic pull-in of two prevalent electrostatic actuators is analyzed.
User Modeling for the Internet of Things

The Internet-of-Things (IoT) consists of a large number of interconnected, low cost devices and the framework for managing them. While this provides the means for rich and ubiquitous personalized interaction, a key gap is the lack of support for user modeling to harness and manage personal data gathered from IoT. Our work fills this gap by creating the IoTum user modeling framework for Internet-of-Things applications. Our design goals were to make it easy for IoT application developers to use, tackling the difficulty of building ubicomp systems. At the same time, we aimed to achieve light-weight, flexible, powerful, reactive user modeling that is accountable, transparent and scrutable. Applications interact with IoTum via three primitives, 'tell' to add evidence to a user model, 'ask' to retrieve interpreted evidenced from the model and 'listen' which establishes a monitoring process which can trigger the application. The first two of these have been part of many previous user modelling frameworks, including Personis, the server by Kobsa and Fink, CUMULATE and info-bead. However, IoTum is the first user modelling framework we are aware of that supports the last of these, the 'listen', which is key to making effective use of the many existing and emerging low cost sensors of IoT. Another important aspect is that IoTum maintains provenance information in the user model, to support accountability, scrutability and explanations. There are also mechanisms to define the user model and do introspection on existing models. To demonstrate that it meets its design goals, we describe its use to build a nutrition chatbot.
A structure-oriented power modeling technique for macrocells

To characterize the power consumption of a macrocell, a general method involves recording the power consumption of all possible input transition events in the look-up tables. However, though this approach is accurate, the size of the table becomes very large. In this paper, we propose a new power modeling technique that takes advantage of the structural information of a macrocell. In this approach, a subset of primary inputs and internal nodes in the macrocell are selected as the state variables to build a state transition graph (STG). These state variables can model the steady-state transitions completely. Moreover, by selecting the characterization patterns properly, the STG can also model the glitch power in the macrocell accurately. To further simplify the complexity of the STG, an incomplete power modeling technique is presented. Without losing much accuracy, the property of compatible patterns is exploited for a macrocell to further reduce the number of edges in the corresponding STG. Experimental results show that our modeling techniques can provide SPICE-like accuracy, while the size of the look-up table is significantly reduced.
Adoption of International Financial Reporting Standards (IFRS) and Assets Quality in the Nigerian Banking Sector: The Fundamental Effect Approach

The main purpose of this work is to examine the effect of the adoption of international financial reporting standards (IFRS) on assets quality in the Nigerian banking sector. Specifically the study sought to determine the effect of the adoption on asset quality, loan volume, , net interest income and profit after tax of deposit money banks listed on the Nigerian Stock Exchange. The adopted research design is causal-comparative. Secondary data on ten out of sixteen listed deposit money banks on the Nigerian Stock Exchange by June 2018 were used. The banks which were selected via judgmental sampling technique were those whose annual financial statements for the immediate year before IFRS adoption year were available and contained figures under Nigerian GAAP/SAS and IFRS-equivalent. The data which were analyzed using paired student t-test approach were sourced from 2011 and 2012 annual reports of the selected banks except Zenith bank for which only 2011 annual financial reports were used. The variables of interest were grouped under Nigerian GAAP (SAS) and IFRS. Findings revealed that overall, the IFRS adoption indicates negative insignificant effect on assets quality of deposit money banks in Nigeria. The study therefore, recommends inter-alia that Financial Reporting Council of Nigeria should partner with the CBN to provide clarity on areas of regulatory hindrance to full and effective implementation of the IFRS with regular.
Rhinitis, rhinosinusitis and quality of life in children

Quality of life (QoL) or, rather, health‐related QoL, is currently regarded as a crucial aspect of the general well‐being of patients and, in consequence, of the effects of a disease and its treatment. This is particularly true for respiratory allergy (asthma and rhinitis), which are chronic diseases and also for sinusitis (rhinosinusitis). A number of questionnaires (instruments), either generic or specific, have been developed and validated to assess the QoL in adults and children, for asthma and rhinitis, whereas there are few specific instruments for chronic rhinosinusitis. The literature provides strong evidence of the effects of allergic rhinitis, asthma and their treatments on QoL in paediatric patients, as well as in adults, whereas the number of experimental data on rhinosinusitis is limited, especially in children. Clinical trials evidenced some controversial points, mainly the weak correlation existing between QoL and traditional objective parameters. It has become clear that the QoL questionnaires measure the aspects of the disease that partially differ from the routinely evaluated parameters and that QoL should integrate, not replace, the objective measurements.
Differentiation of follicular from mucosa‐associated lymphoid tissue lymphoma by detection of t(14;18) on single‐cell preparations and paraffin‐embedded sections

A 57‐year‐old woman was referred to the Kyoto Prefectural University of Medicine because of multiple polypoid lesions in the duodenum. On the basis of the histopathologic findings, mucosa‐associated lymphoid tissue lymphoma had been diagnosed. The polypoid lesions did not show any improvement in spite of antimicrobial therapy for elimination of Helicobacter pylori. Because the disease remained stable during the clinical course, no other specific treatment was administered. We performed fluorescence in situ hybridization (FISH) analysis on a single‐cell preparation obtained from the duodenal lesions, to assess the specific chromosome translocation. We identified BCL2/IGH fusion at a frequency of 83%. Two‐color FISH was also performed on paraffin‐embedded tissue sections, which demonstrated BCL2/IGH fusion–positive cells in neoplastic follicles. These findings, together with the CD10+ immunophenotyping of tumor cells, led to a diagnosis of primary follicular lymphoma of the duodenum. Interphase FISH with the IGH gene and oncogene probes is a rapid and powerful tool for assessing genomic changes in gastrointestinal lymphoma on single‐cell preparations and tissue sections. This technique is particularly useful in view of the increasingly small core biopsy samples and needle aspirations obtained for diagnostic purposes. © 2002 Wiley‐Liss, Inc.
H-Morph: an indirect approach to advancing front hex meshing

H-Morph is a new automatic algorithm for the generation of a hexahedral-dominant finite element mesh for arbitrary volumes. The H-Morph method starts with an initial tetrahedral mesh and systematically transforms and combines tetrahedra into hexahedra. It uses an advancing front technique where the initial front consists of a set of prescribed quadrilateral surface facets. Fronts are individually processed by recovering each of the six quadrilateral faces of a hexahedron from the tetrahedral mesh. Recovery techniques similar to those used in boundary constrained Delaunay mesh generation are used. Tetrahedra internal to the six hexahedral faces are then removed and a hexahedron is formed. At any time during the H-Morph procedure a valid mixed hexahedral–tetrahedral mesh is in existence within the volume. The procedure continues until no tetrahedra remain within the volume, or tetrahedra remain which cannot be transformed or combined into valid hexahedral elements. Any remaining tetrahedra are typically towards the interior of the volume, generally a less critical region for analysis. Transition from tetrahedra to hexahedra in the final mesh is accomplished through pyramid-shaped elements. Advantages of the proposed method include its ability to conform to an existing quadrilateral surface mesh, its ability to mesh without the need to decompose or recognize special classes of geometry, and its characteristic well-aligned layers of elements parallel to the boundary. Example test cases are presented on a variety of models. Copyright © 2000 John Wiley & Sons, Ltd.
Solving virtual machine packing with a Reordering Grouping Genetic Algorithm

We formally define multi-capacity bin packing, a generalization of conventional bin packing, and develop an algorithm called Reordering Grouping Genetic Algorithm (RGGA) to assign VMs to servers. We first test RGGA on conventional bin packing problems and show that it yields excellent results but much more efficiently. We then generate a multi-constraint test set, and demonstrate the effectiveness of RGGA in this context. Lastly, we show the applicability of RGGA in its desired context by using it to develop an assignment of real virtual machines to servers.
High level expression and purification of the Epstein-Barr virus encoded cytokine viral interleukin 10: efficient removal of endotoxin.

To characterize the structural and functional properties of viral interleukin 10 (vIL-10), its cDNA was cloned into the bacterial expression vector pMAL-c2, which directs the synthesis of the inserted gene as a fusion protein with maltose binding protein (MBP). The MBP-vIL-10 fusion protein was expressed in Escherichia coli and purified from cell lysates using amylose resin chromatography. Viral interleukin 10 (IL-10) was released from the fusion protein by cleavage with the proteolytic enzyme factor Xa. We show that vIL-10 will bind to heparin and use this property to purify vIL-10 from factor Xa cleaved products and trace contaminants using heparin agarose chromatography. A simple one-step procedure is described for the removal of endotoxins from heavily contaminated vIL-10 preparations. The protocol exploits the high binding affinity of MBP for amylose resin or vIL-10 for heparin and the ability of Triton-X114 to dissociate endotoxins from proteins. The biological activity of purified vIL-10 was demonstrated through its ability to inhibit interferon gamma (IFN-gamma) production by mitogen activated peripheral blood mononuclear cells and to down-regulate HLA-class II expression on activated monocytes/macrophages. The availability of an efficient expression and purification strategy for vIL-10 together with appropriate assays will contribute to a greater understanding of how vIL-10 has evolved to retain and modify those activities of cellular IL-10 best suited for Epstein-Barr virus (EBV)'s specialized niche within the host.
Cognitive Economy and Behavior of the Agents in the Decision-Making Process

As is known, by a few years the theory of unlimited rationality was subjected to many criticisms arising from empirical research in cognitive field. These can be summarised by characterizing the theory of the action in the three main components of causal reasoning, rating and choice: Shafir [1], Kanheman [2].
Complex dynamics and chaos in a scalar linear continuous system with impulsive feedback

This paper deals with a hybrid system comprised of scalar continuous dynamics and a pulse-modulated feedback that represents a simplified version of a model earlier proposed for describing the mechanism of pulsatile hormone regulation in endocrinology. It is shown that even in this drastically reduced form, the system demonstrates a wide range of complex behaviors, including chaotic dynamics.
Single sample face recognition with Gabor feature based linear regression

By constructing a linear model representing using the auxiliary intra-personal variations, the adaptive linear regression classifier(ALRC) successfully popularized the linear regression classifier(LRC) to the single sample per person(SSPP) scenario. However, ALRC simply uses original face images to constitute the feature space, which is not robust enough against the variations of probe images, and leads to the algorithm computationally very expensive. To address the two problems, in this paper, the image Gabor features is used for ALRC scheme. By using Gabor kernels based feature space, the abilities of ALRC against variations can be improved. Meanwhile, principal component analysis(PCA) is implemented in the feature extracted stage. Experiments on representative face databases show that Gabor-feature based ALRC can achieve better recognition performance than original ALRC, and reduce much computational burden compared with later.
Stalking Victimization and Substance Use in College Dating Relationships: An Exploratory Analysis

Traditionally, most dating violence research has focused on physical aggression and has left stalking behaviors largely unexamined, despite evidence that stalking of an intimate partner occurs with high frequency. Moreover, the extent to which stalking victimization has the same negative mental health consequences as other forms of dating violence is unclear. Thus, using a sample of male and female undergraduate students in current dating relationships (N = 357), the association between stalking victimization and alcohol and drug use was explored. Results indicated that for both men and women, stalking victimization from a dating partner was related to alcohol and drug use, even after controlling for age, gender, length of dating relationship, and physical aggression victimization. These preliminary findings suggest that stalking victimization is associated with deleterious consequences; thus, additional research is needed to better understand the longitudinal, long-term consequences of stalking victimization. Additional implications and directions for future research are discussed.