Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating Monotonicity and Concavity Restrictions into Stochastic Cost Frontiers

into Stochastic Cost Frontiers Dek Terrell and Imad Dashti* September 25, 1997 Abstract This paper embeds Terrell's (1996) method of incorporating monotonicity and concavity conditions into the Bayesian stochastic frontier model proposed by Koop, Osiewalski, and Steel (1994). This method ensures analysis based on a cost function consistent with economic theory, guarantees that all inefficiency is reserved for the error component and should lead to more accurate estimates of inefficiency. An application investigating efficiency in Greene's (1990) utility data with Cobb-Douglas, translog, and Fourier cost frontiers is used to assess the benefits of the procedure.
Energy-Efficient Multi-Channel Cooperative Sensing Scheduling with Heterogeneous Channel Conditions for Cognitive Radio Networks

Spectrum sensing is an important aspect of Cognitive Radio Networks. Secondary users should sense the chann els periodically in order to ensure primary user protection. Sensing with cooperation among several secondary users is more robu st and less error prone. However, cooperation also increases t he energy spent for sensing. Considering the periodic nature o f sensing, even a small amount of savings in each sensing perio d leads to considerable improvement in the long run. In this paper, we consider the problem of energy-efficient spectrum sensing scheduling with satisfactory primary user protect ion. Our model exploits the diversity of secondary users in their received signal-to-noise-ratio value of the primary signa l to determine the sensing duration for each user/channel pair f or higher energy efficiency. We model the mentioned problem as an optimization problem with two different objectives. The first one minimizes the energy consumption whereas the second one minimizes the spectrum sensing duration in order to maximize the remaining time for data transmission. We solve both problems using outer linearization method. In addition, we present t wo sub-optimal but efficient heuristic methods. We provide an extensive performance analysis of our proposed methods und er various number of secondary users, average channel signalto noise-ratio, and channel sampling frequency. Our analysisreveal that all proposals with energy minimization perspective provide significant energy savings compared to a pure transmission t ime maximization technique.
An advanced BPNN face recognition based on curvelet transform and 2DPCA

The paper proposed an advanced face recognition method of BPNN based on Curvelet transform and 2DPCA to increase the face recognition rate. Firstly, we used Curvelet transform to process the face images, after that we got higher dimension feature of face images, then used 2DPCA to reduce the dimension, finally we got some feature vectors, which could represent the face images. We used ORL face database to conduct the experiment, some of the feature vectors to train the BPNN classifier, the others to test. we repeatedly made some of the less important feature vectors value replaced by zeros, and made the recognition result depend on big probability event . We obtained a better result In this way compared with traditional BPNN face recognition, this method can not only improve the face recognition rate, but also reduce the recognition time.
On the fixed points of the max-product algorithm

Graphical models, such as Bayesian networks and Markov random fields represent statistical dependencies of variables by a graph. The max-product b̈elief propagation̈ algorithm is a localmessage passing algorithm on this graph that is known to converge to a unique fixed point when the graph is a tree. Furthermore, when the graph is a tree, the assignment based on the fixed-point is guaranteed to yields the most probable a posteriori (MAP) values of the unobserved variables given the observed ones. Here we prove a result on the fixed points of max-product on a graph with arbitrary toplogy and with arbitrary probability distributions (discrete or continuous valued nodes). We show that the assignment based on the fixed-point is a n̈eighborhood maximum̈ of the posterior probability: the posterior probability of the max-product assignment is guaranteed to be greater than all other assignments in a particular large region around that assignment. The region includes all assignments that differ from the max-product assignment in any subset of nodes that form no more than a single loop in the graph. In some graphs this neighborhood is exponentially large. We illustrate the analysis with examples. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 1999 201 Broadway, Cambridge, Massachusetts 02139
Shielded Cable Transfer Impedance Measurements High frequency range 100 MHz-1 GHz

Plotting the individual components is shown in Fig. 11. Adding the pulses gives the solution for V1 0, t2 shown in Fig. 12. All of the results of the above examples were validated using the PSPICE circuit analysis computer program. Use of the exact lossless transmission line model in PSPICE for more complicated lossless transmission-line problems is highly recommended [1]. V (0,t)
Natural Product and Natural Product-Derived Gamma Secretase Modulators from Actaea Racemosa Extracts

Alzheimer’s disease is characterized by pathogenic oligomerization, aggregation, and deposition of amyloid beta peptide (Aβ), resulting in severe neuronal toxicity and associated cognitive dysfunction. In particular, increases in the absolute or relative level of the major long form of Aβ, Aβ42, are associated with increased cellular toxicity and rapidity of disease progression. As a result of this observation, screening to identify potential drugs to reduce the level of Aβ42 have been undertaken by way of modulating the proteolytic activity of the gamma secretase complex without compromising its action on other essential substrates such as Notch. In this review we summarize results from a program that sought to develop such gamma secretase modulators based on novel natural products identified in the extract of Actaea racemosa, the well-known botanical black cohosh. Following isolation of compound 1 (SPI-014), an extensive medicinal chemistry effort was undertaken to define the SAR of 1 and related semisynthetic compounds. Major metabolic and physicochemical liabilities in 1 were overcome including replacement of both the sugar and acetate moieties with more stable alternatives that improved drug-like properties and resulted in development candidate 25 (SPI-1865). Unanticipated off-target adrenal toxicity, however, precluded advancement of this series of compounds into clinical development.
Research on the Method of Features Extraction for Non-Stationary Transient Signal Based on EMD Method

For solving the problem of features extraction on non-stationary transient impact signal, a novel method of features extraction is proposed by signal processing theory. Firstly, the intrinsic mode function (IMF) of the signal is extracted using the empirical mode decomposition (EMD). Combined with Hilbert transformation, the instantaneous frequency of transient single-frequency vibration signal extracted model is established to extract the instantaneous frequency. Secondly, the Hilbert spectrum can be obtained by IMF and the Hilbert boundary spectrum is obtained. The transient characteristic of torsional vibration signal can be extracted effectively using the method. Compared with wavelet decomposition, this algorithm not only avoids the frequency overlapping in the wavelet decomposition, but also overcomes the difficulty in selecting elementary wavelet. The numerical simulation shows the feasibility of the method. The example analysis of transient signal shows the reliability of the method.
Sensing matrix optimization for compressed sensing with consideration of sparse representation error and rank constraint

This paper deals with designing sensing matrix for a compressive sensing (CS) system with sparse representation error and rank constraint taken into account. Unlike the traditional design methods, the newly proposed measure takes the sparse representation error into account and hence is expected to lead to a more robust CS system. An alternative minimization based algorithm is derived for solving the optimal sensing matrix design without rank constraint. The rank constraint is then considered with a penalty term added in the proposed measure. A closed-form solution is derived for finding the optimal sensing matrix. Experiments are carried out and simulations show that the sensing matrix obtained by the proposed approach improves the signal recovery accuracy of the CS system greatly and outperforms those by existing algorithms when the sparse representation error is very high.
Network Scale Modeling of Lymph Transport and Its Effective Pumping Parameters

The lymphatic system is an open-ended network of vessels that run in parallel to the blood circulation system. These vessels are present in almost all of the tissues of the body to remove excess fluid. Similar to blood vessels, lymphatic vessels are found in branched arrangements. Due to the complexity of experiments on lymphatic networks and the difficulty to control the important functional parameters in these setups, computational modeling becomes an effective and essential means of understanding lymphatic network pumping dynamics. Here we aimed to determine the effect of pumping coordination in branched network structures on the regulation of lymph flow. Lymphatic vessel networks were created by building upon our previous lumped-parameter model of lymphangions in series. In our network model, each vessel is itself divided into multiple lymphangions by lymphatic valves that help maintain forward flow. Vessel junctions are modeled by equating the pressures and balancing mass flows. Our results demonstrated that a 1.5 s rest-period between contractions optimizes the flow rate. A time delay between contractions of lymphangions at the junction of branches provided an advantage over synchronous pumping, but additional time delays within individual vessels only increased the flow rate for adverse pressure differences greater than 10.5 cmH2O. Additionally, we quantified the pumping capability of the system under increasing levels of steady transmural pressure and outflow pressure for different network sizes. We observed that peak flow rates normally occurred under transmural pressures between 2 to 4 cmH2O (for multiple pressure differences and network sizes). Networks with 10 lymphangions per vessel had the highest pumping capability under a wide range of adverse pressure differences. For favorable pressure differences, pumping was more efficient with fewer lymphangions. These findings are valuable for translating experimental measurements from the single lymphangion level to tissue and organ scales.
SiGe-On-Insulator (SGOI) Technology and MOSFET Fabrication

In this work, we have developed two different fabrication processes for relaxed Si1xGex-on-insulator (SGOI) substrates: (1) SGOI fabrication by etch-back approach, and (2) by “smart-cut” approach utilizing hydrogen implantation. Etch-back approach produces SGOI substrate with less defects in SiGe film, but the SiGe film uniformity is inferior. “Smart-cut” approach has better control on the SiGe film thickness and uniformity, and is applicable t o wider Ge content range of the SiGe film. We have also fabricated strained-Si n-MOSFET’s on SGOI substrates, in which epitaxial regrowth was used to produce the surface strained Si layer on relaxed SGOI substrate, followed by large-area nMOSFET’s fabrication on this structure. The measured electron mobility shows significant enhancement (1.7 times) over both the universal mobility and that of co-processed bulk-Si MOSFET’s. This SGOI process has a low thermal budget and thus is compatible with a wide range of Ge contents in Si1-xGex layer.
Functional recovery following traumatic spinal cord injury mediated by a unique polymer scaffold seeded with neural stem cells

To better direct repair following spinal cord injury (SCI), we designed an implant modeled after the intact spinal cord consisting of a multicomponent polymer scaffold seeded with neural stem cells. Implantation of the scaffold–neural stem cells unit into an adult rat hemisection model of SCI promoted long-term improvement in function (persistent for 1 year in some animals) relative to a lesion-control group. At 70 days postinjury, animals implanted with scaffold-plus-cells exhibited coordinated, weight-bearing hindlimb stepping. Histology and immunocytochemical analysis suggested that this recovery might be attributable partly to a reduction in tissue loss from secondary injury processes as well as in diminished glial scarring. Tract tracing demonstrated corticospinal tract fibers passing through the injury epicenter to the caudal cord, a phenomenon not present in untreated groups. Together with evidence of enhanced local GAP-43 expression not seen in controls, these findings suggest a possible regeneration component. These results may suggest a new approach to SCI and, more broadly, may serve as a prototype for multidisciplinary strategies against complex neurological problems.
Approximate Inverse Techniques for Block-Partitioned Matrices

This paper proposes some preconditioning options when the system matrix is in block-partitioned form. This form may arise naturally, for example, from the incompressible Navier--Stokes equations, or may be imposed after a domain decomposition reordering. Approximate inverse techniques are used to generate sparse approximate solutions whenever these are needed in forming the preconditioner. The storage requirements for these preconditioners may be much less than for incomplete LU factorization (ILU) preconditioners for tough, large-scale computational fluid dynamics (CFD) problems. The numerical experiments show that these preconditioners can help solve difficult linear systems whose coefficient matrices are highly indefinite.
Expression of Antibodies Directed to Paracoccidioides brasiliensis Glycosphingolipids during the Course of Paracoccidioidomycosis Treatment

ABSTRACT Paracoccidioidomycosis (PCM) is a granulomatous disease caused by the dimorphic fungus Paracoccidioides brasiliensis. The immunoglobulin classes and isotypes of antibodies directed to acidic glycosphingolipids (GSLs) and glucosylceramide of P. brasiliensis were determined by enzyme-linked immunosorbent assay of sera from 31 PCM patients. The reactivities of 38 serum samples were analyzed by considering the stage of treatment: before antifungal treatment (n = 10), during 1 to 4 months of treatment (T1-4; n = 9), during 5 to 12 months of treatment (T5-12; n = 9), and posttreatment (PT; n = 10). Sera from healthy subjects (n = 12) were used as controls. Only the GSL Pb-1 antigen, which presents the carbohydrate structure Galfβ1-6(Manα1-3)Manβ1, was reactive with the PCM patient sera. The PCM patient sera did not react with Pb-2, which lacks the Galf residue and which is considered the biosynthetic precursor of Pb-1, indicating that the Galf residue is essential for antibody reactivity. The Pb-1 glycolipid from nontreated patients elicited a primary immune response with immunoglobulin M (IgM) production and subsequent switching to IgG1 production. The IgG1 titer increased after the start of antifungal treatment (T1-4 group), and general decreases in the anti-Pb-1 antibody titers were observed after 5 months of treatment (T5-12 and PT groups). The Pb-1 antigen, an acidic GSL with terminal Galf residue, has potential application as an elicitor of the host immune response in patients with PCM.
Predictors of Comorbid Depressive Disorders in Youth With Posttraumatic Stress Disorder

Emotional Abuse . 394 . 698 Predictors of comorbid depressive disorders in youth with Posttraumatic Stress Disorder Elizabeth Solomon, M.S.2,3, Victor Carrion, M.D. 2, John Rettger, Ph.D. 2, and Amy Garrett, Ph.D1,2. 1Center for Interdisciplinary Brain Sciences Research ,2Early Life Stress Research Program, 3PGSPStanford Psy.D. Consortium Stanford University School of Medicine, Palo Alto, CA 94305
New supersymmetric AdS4 type II vacua

We review the supersymmetric AdS4 ×wℳ︁6 backgrounds of type IIA/IIB supergravity constructed in [1]. In type IIA the supersymmetry is 𝒩 = 2, and the six‐dimensional internal space is locally an S2 bundle over a four‐dimensional Kähler‐Einstein base; in IIB the internal space is the direct product of a circle and a five‐dimensional squashed Sasaki‐Einstein manifold. These backgrounds do not contain any sources, all fluxes (including the Romans mass in IIA) are generally non‐zero, and the dilaton and warp factor are non‐constant. The IIA solutions include the massive deformations of the IIA reduction of the eleven‐dimensional AdS4 × Yp,q solutions, and had been predicted to exist on the basis of the AdS4/CFT3 correspondence.
Combining Graph Structure Exploitation and Propositional Reasoning for the Maximum Clique Problem

State-of-the-art branch-and-bound algorithms for the maximum clique problem (Maxclique) generally exploit the structural information of a graph $G$ to partition $G$ into independent sets, in order to derive an upper bound for the cardinality of a maximum clique of $G$, which cannot be very tight for imperfect graphs. On the other hand, while Maxclique can be easily encoded into MaxSAT to be solved using a MaxSAT solver, general-purpose MaxSAT solvers are not competitive for solving Maxclique, because they do not exploit the structural information of the graph. Recently, we have shown that propositional reasoning developed for the MaxSAT solvers can be used to improve the upper bound based on the partition. In this paper, we propose and study several improvements to this approach by better combining graph structure exploitation and propositional reasoning to solve Maxclique. Experimental results show that the improvements are very effective on hard random graphs and on DIMACS Maxclique benchmarks which are widely used to evaluate branch-and-bound algorithms for Maxclique.
State-space models for the dynamics of wild animal populations

We develop a unified framework for jointly defining population dynamics models and measurements taken on a population. The framework is a state-space model where the population processes are modelled by the state process and measurements are modelled by the observation process. In many cases, the expected value for the state process can be represented as a generalisation of the standard population projection matrix: each sub-process within the state process may be modelled by a separate matrix and the product of these matrices is a generalised Leslie matrix. By selecting appropriate matrices and their ordering, a wide range of models may be specified. The method is fully flexible for allowing stochastic variation in the processes. Process parameters may themselves be modelled as functions of covariates. The structure accommodates effects such as density dependence, competition and predator–prey relationships, and metapopulations are readily modelled. Observations on the population enter through an observation process model, and we show how likelihood functions can be built that reflect both demographic stochasticity (which appears in the state process) and stochastic errors in the observations. Parameter estimation and estimation of state process variables can be conducted using sequential Monte Carlo procedures. © 2003 Elsevier B.V. All rights reserved.
A simple tool for assessing the completeness in apparent magnitude of magnitude–redshift samples

A new tool is proposed for finding out the completeness limit in apparent magnitude of a magnitude-redshift sample. The technique, closely related to the statistical test proposed by Efron & Petrosian, presents a real improvement compared to standard completeness tests. Namely, no a priori assumptions are required concerning the redshift-space distribution of the sources. It means in particular that neither the clustering nor the evolution of the mean number density of the galaxies affects the result of the search.
Validation of disease states in schizophrenia: comparison of cluster analysis between US and European populations

Background There is controversy as to whether use of statistical clustering methods to identify common disease patterns in schizophrenia identifies patterns generalizable across countries. Objective The goal of this study was to compare disease states identified in a published study (Mohr/Lenert, 2004) considering US patients to disease states in a European cohort (EuroSC) considering English, French, and German patients. Methods Using methods paralleling those in Mohr/Lenert, we conducted a principal component analysis (PCA) on Positive and Negative Syndrome Scale items in the EuroSC data set (n=1,208), followed by k-means cluster analyses and a search for an optimal k. The optimal model structure was compared to Mohr/Lenert by assigning discrete severity levels to each cluster in each factor based on the cluster center. A harmonized model was created and patients were assigned to health states using both approaches; agreement rates in state assignment were then calculated. Results Five factors accounting for 56% of total variance were obtained from PCA. These factors corresponded to positive symptoms (Factor 1), negative symptoms (Factor 2), cognitive impairment (Factor 3), hostility/aggression (Factor 4), and mood disorder (Factor 5) (as in Mohr/Lenert). The optimal number of cluster states was six. The kappa statistic (95% confidence interval) for agreement in state assignment was 0.686 (0.670–0.703). Conclusion The patterns of schizophrenia effects identified using clustering in two different data sets were reasonably similar. Results suggest the Mohr/Lenert health state model is potentially generalizable to other populations.
QUERY-BY-EXAMPLE MUSIC RETRIEVAL APPROACH BASED ON MUSICAL GENRE SHIFT BY CHANGING INSTRUMENT VOLUME

We describe a novel Query-by-Example (QBE) approach in Music Information Retrieval, which allows a user to customize query examples by directly modifying the volume of different instrument parts. The underlying hypothesis is that the musical genre shifts (changes) in relation to the volume balance of different instruments. On the basis of this hypothesis, we aim to clarify the relationship between the change of the volume balance of a query and the shift in the musical genre of retrieved similar pieces, and thus help instruct a user in generating alternative queries without choosing other pieces. Our QBE system first separates all instrument parts from the audio signal of a piece with the help of its musical score, and then lets a user remix those parts to change acoustic features that represent musical mood of the piece. The distribution of those features is modeled by the Gaussian Mixture Model for each musical piece, and the Earth Movers Distance between mixtures of different pieces is used as the degree of their mood similarity. Experimental results showed that the shift was actually caused by the volume change of vocal, guitar, and drums.