Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems

We consider convex-concave saddle point problems with a separable structure and non-strongly convex functions. We propose an efficient stochastic block coordinate descent method using adaptive primal-dual updates, which enables flexible parallel optimization for large-scale problems. Our method shares the efficiency and flexibility of block coordinate descent methods with the simplicity of primal-dual methods and utilizing the structure of the separable convex-concave saddle point problem. It is capable of solving a wide range of machine learning applications, including robust principal component analysis, Lasso, and feature selection by group Lasso, etc. Theoretically and empirically, we demonstrate significantly better performance than state-of-the-art methods in all these applications.
Long‐term persistence of host cells detected by X‐chromosome gene‐based assay in patients undergoing gender‐mismatched hematopoietic stem cell transplantation

Using our recently developed human androgen receptor (HUMARA) gene‐based chimerism assay, long‐term chimerism was investigated in female patients who underwent hematopoietic stem cell transplantation (HCT) with cells from male donors. After restriction digestion of samples, we detected a small number of female‐derived cells within a large population of male‐derived cells, with a sensitivity from 0.1% to 0.05%. Chimerism was examined in four patients with myeloid malignancies: two patients with acute myeloid leukemia (AML) from myelodysplastic syndrome (MDS), and one patient each with AML M3 and AML M4. All patients underwent myeloablative conditioning regimens and exhibited good clinical results during a median follow‐up period of 6.6 years (range, 3.4–7.5 years). Female‐derived cells were detected throughout the entire follow‐up period in all bone marrow samples, but they became undetectable in the peripheral blood samples of 3 patients. Moreover, the HUMARA band pattern suggests that these residual host cells were normal cells. This study confirms the usefulness of the HUMARA gene‐based assay, which showed that patients undergoing HCT frequently show mixed chimerism (MC) for a long period, especially in bone marrow, although the possibility of contamination by host stromal cells cannot be excluded. Am. J. Hematol. 80:101–105, 2005. © 2005 Wiley‐Liss, Inc.
Speech Recognition in Younger and Older Adults: A Dependency on Low-Level Auditory Cortex

A common complaint of older adults is difficulty understanding speech, especially in challenging listening environments. In addition to well known declines in the peripheral auditory system that reduce audibility, age-related changes in central auditory and attention-related systems are hypothesized to have additive negative effects on speech recognition. We examined the extent to which functional and structural differences in speech- and attention-related cortex predicted differences in word recognition between 18 younger adults (19–39 years) and 18 older adults (61–79 years). Subjects performed a word recognition task in an MRI scanner where the intelligibility of words was parametrically varied. Older adults exhibited significantly poorer word recognition in a challenging listening condition compared with younger adults. An anteromedial Heschl's gyrus/superior temporal gyrus (HG/STG) region, engaged by the word recognition task, exhibited age group differences in gray matter volume and predicted word recognition in younger and older adults. Age group differences in anterior cingulate (ACC) activation were also observed. The association between HG gray matter volume, word recognition, and ACC activation was present after controlling for hearing loss. In younger and older adults, causal path modeling analyses demonstrated that individual variation in left HG/STG morphology affected word recognition performance, which was reflected by error monitoring activity in the dorsal ACC. These results have clinical implications for rehabilitation and suggest that some of the perceptual difficulties experienced by older adults are due to structural changes in HG/STG. More broadly, the results suggest the possibility that aging may exaggerate developmental limitations on the ability to recognize speech.
New control variates for Lévy process models

We present a general control variate method for Monte Carlo estimation of the expectations of the functionals of Lévy processes. It is based on fast numerical inversion of the cumulative distribution functions and exploits the strong correlation between the increments of the original process and Brownian motion. In the suggested control variate framework, a similar functional of Brownian motion is used as a main control variate while some other characteristics of the paths are used as auxiliary control variates. The method is applicable for all types of Lévy processes for which the probability density function of the increments is available in closed form. We present the applications of our general approach for simulation of path dependent options. Numerical experiments confirm that our method achieves considerable variance reduction.
The airway vasculature

CONTENTS PAGE Introduction 433 Vascular structure 434 Vascular anastomoses 434 Counter-current mechanisms 435 Capillary vasculature 437 Postcapillary venules 439 Capacitance vasculature 440 Neural control of vasculatures 442 Sympathetic innervation 442 Parasympathetic innervation 443 Reflex control of vasculatures 444 Neurogenic inflammation 445 Non-neural mediators 446 Cold and drying 447 Conclusions 448 References 448
Using the Timing Information of Heartbeats as an Entity Identifier to Secure Body Sensor Network

Security of the emerging body sensor network (BSN) in telemedicine applications is a crucial problem because personal medical information must be protected against flaws and misdeeds. The solution is, however, nontrivial because lightweight mechanisms have to be deployed to meet the stringent resource constraints of these networks. It has been suggested that the inherent ability of human body to transfer information is a unique and resource-saving method to secure wireless communications within a BSN. For example, physiological characteristics can be captured by individual sensors of a BSN to generate entity identifiers (EIs) for identifying nodes and even securing keying materials, i.e., by a biometric approach. This study demonstrates the performance analysis of such a biometric trait, i.e., the interpulse intervals (IPIs) of heartbeats that were calculated from electrocardiogram and photoplethysmogram of 99 subjects. Based on the characteristics of IPIs, a lightweight generation scheme of EIs is proposed. Individual randomness and group similarity of the generated EIs are then evaluated. False acceptance rate and false rejection rate are also calculated to measure the effectiveness of the proposed identification system. The results suggest that the readily available IPI information can be a good source for generating EIs among BSN nodes.
Data hiding in images with adaptive numbers of least significant bits based on the human visual system

We propose in this paper a novel method for embedding multimedia data (including audio, image, video, or text; compressed or non-compressed) into a host image. The classical LSB concept is adopted, but with the number of LSBs adapting to pixels of different graylevels. A piecewise mapping function according to human visual sensitivity of contrast is used so that adaptivity can be achieved without extra bits for overhead. The leading information for data decoding is few, no more than 3 bytes. Experiments show that a large amount of bit streams (nearly 30%-45% of the host image) can be embedded without sever degradation of the image quality (33-40 dB, depending on the volume of embedded bits).
Extreme learning machine-based functional link network

For their universal approximation, more compact topology and faster learning speed, functional-link neural network has attracted considerable attention, and they have been widely applied in many science and engineering fields. Extreme Learning Machine (ELM) algorithm allowing a fast learning speed with high accuracy by randomly generating the input weights of single layer feedforward neural networks, whereas the output weights are analytically determined using the least-square method. In this paper we shows that ELM can be extended to radial basis functional link network (RBFL), which allows the RBFL kernel's centres and impact widths to be randomly generated after formulating the network in a linear system. Thus, the network weights can be easily solved. The experimental results in artificial and real benchmarking function approximation problems, shows that the RBFL networks with ELM algorithm obtained better results in accuracy, high learning speed and good generalization performance for almost all datasets.
InAs/InP Quantum-Dot Passively Mode-Locked Lasers for 1.55-μ m Applications

This paper reports on recent results on passively mode-locked InAs/InP quantum-dot-based lasers. These low-dimensional structures have proved very attractive in improving most of the properties of these devices. Subpicosecond pulse generation at repetition rates up to beyond 300 GHz has readily been demonstrated. Ultranarrow RF linewidths reach record values of less than 1 kHz. Controlled optical feedback allows a further reduction of this linewidth yielding extremely low timing jitter. A comparison of single-section and standard two-section lasers is given for the first time. These performances open the way to various applications at 1.55 μm, including very high bit rate all-optical signal processing, frequency comb generation, radio over fiber, and low-noise all-optical oscillators.
No selection on immunological markers in response to a highly virulent pathogen in an Arctic breeding bird

In natural populations, epidemics provide opportunities to look for intense natural selection on genes coding for life history and immune or other physiological traits. If the populations being considered are of management or conservation concern, then identifying the traits under selection (or ‘markers’) might provide insights into possible intervention strategies during epidemics. We assessed potential for selection on multiple immune and life history traits of Arctic breeding common eiders (Somateria mollissima) during annual avian cholera outbreaks (summers of 2006, 2007 & 2008). We measured prelaying body condition, immune traits, and subsequent reproductive investment (i.e., clutch size) and survival of female common eiders and whether they were infected with Pasteurella multocida, the causative agent of avian cholera. We found no clear and consistent evidence of directional selection on immune traits; however, infected birds had higher levels of haptoglobin than uninfected birds. Also, females that laid larger clutches had slightly lower immune responses during the prelaying period reflecting possible downregulation of the immune system to support higher costs of reproduction. This supports a recent study indicating that birds investing in larger clutches were more likely to die from avian cholera and points to a possible management option to maximize female survival during outbreaks.
Computational Intelligence Approaches for Energy Optimization in Wireless Sensor Networks

Wireless sensor networking is a promising technology that can lead to automatic, intelligent, easier and more secure systems. A wireless sensor network (WSN) consists of small battery powered devices with limited energy resources. One of the major challenges in WSN lies in the energy constraint and computation resources available at the sensor nodes. One way to achieve energy efficiency would be through the use of a clustering technique. In this paper, we propose computational intelligence (CI) approaches to deal with the problem of sensor nodes clustering in a WSN with the ultimate goal to reduce energy expenditures and thus to extend the lifetime of the network. The main motivation is that CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures, and scenario changes. The main features of the proposed work span over two aspects. First, four metaheuristics have been adapted to deal with the tackled problem namely genetic algorithms, evolution strat.
Computational chemistry

Identifying molecules that might fulfil the stringent criteria necessary to become a drug from the vast number of possibilities has often been likened to searching for a needle in a haystack. Two computational chemists with a focus on drug discovery, Yvonne Martin and Brian Shoichet, discuss what attracts them to working on strategies to cut the haystack down to size.
Understanding sensorimotor adaptation and learning for rehabilitation

Purpose of reviewUnderstanding the behavioral mechanisms of sensorimotor adaptation and learning is essential for designing rational rehabilitation interventions. Recent findingsAdaptation is the trial-and-error process of adjusting movement to new demands and is now thought to be more than a simple error cancellation process. Instead, it may calibrate the brain's prediction of how the body will move and takes into account costs associated with the new task demand. Damage of the cerebellum systematically disrupts adaptation, but damage to other brain regions often does not. Adapting to perturbations driven by a device like a robot or a treadmill leads to only partial generalization to unconstrained ‘real-world’ movements. Repeated adaptation can lead to learning a new motor calibration, but process of consolidation of this type of learning is less understood in patients. SummaryAdaptation is inherently important for rehabilitation by making movement flexible, but can also be used to ascertain whether some patients can generate a more normal motor pattern. Repeated adaptation can lead to learning of a new, more permanent motor calibration. Though less understood, this type of learning is likely to be an important method for making long-term improvements in patients' movement patterns.
Hyperspectral reflected light microscopy of plasmonic Au/Ag alloy nanoparticles incubated as multiplex chromatic biomarkers with cancer cells.

A hyperspectral microscopy system based on a reflected light method for plasmonic nanoparticle (NP) imaging was designed and compared with a conventional darkfield method for spatial localization and spectroscopic identification of single Au, Ag and Au/Ag alloy NPs incubated with fixed human cancer cell preparations. A new synthesis protocol based on co-reduction of Au and Ag salts combined with the seeded growth technique was used for the fabrication of monodispersed alloy NPs with sizes ranging from 30 to 100 nm in diameter. We validated theoretically and experimentally the performance of 60 nm Au, Ag and Au/Ag (50 : 50) NPs as multiplexed biological chromatic markers for biomedical diagnostics and optical biosensing. The advantages of the proposed reflected light microscopy method are presented for NP imaging in a complex and highly diffusing medium such as a cellular environment. The obtained information is essential for the development of a high throughput, selective and efficient strategy for cancer detection and treatment.
Digital game design for elderly users

The current paper reviews and discusses digital game design for elderly users. The aim of the paper is to look beyond the traditional perspective of usability requirements imposed by age-related functional limitations, towards the design opportunities that exist to create digital games that will offer engaging content combined with an interface that seniors can easily and pleasurably use.
BAG‐1 modulates the chaperone activity of Hsp70/Hsc70

The 70 kDa heat shock family of molecular chaperones is essential to a variety of cellular processes, yet it is unclear how these proteins are regulated in vivo. We present evidence that the protein BAG‐1 is a potential modulator of the molecular chaperones, Hsp70 and Hsc70. BAG‐1 binds to the ATPase domain of Hsp70 and Hsc70, without requirement for their carboxy‐terminal peptide‐binding domain, and can be co‐immunoprecipitated with Hsp/Hsc70 from cell lysates. Purified BAG‐1 and Hsp/Hsc70 efficiently form heteromeric complexes in vitro. BAG‐1 inhibits Hsp/Hsc70‐mediated in vitro refolding of an unfolded protein substrate, whereas BAG‐1 mutants that fail to bind Hsp/Hsc70 do not affect chaperone activity. The binding of BAG‐1 to one of its known cellular targets, Bcl‐2, in cell lysates was found to be dependent on ATP, consistent with the possible involvement of Hsp/Hsc70 in complex formation. Overexpression of BAG‐1 also protected certain cell lines from heat shock‐induced cell death. The identification of Hsp/Hsc70 as a partner protein for BAG‐1 may explain the diverse interactions observed between BAG‐1 and several other proteins, including Raf‐1, steroid hormone receptors and certain tyrosine kinase growth factor receptors. The inhibitory effects of BAG‐1 on Hsp/Hsc70 chaperone activity suggest that BAG‐1 represents a novel type of chaperone regulatory proteins and thus suggest a link between cell signaling, cell death and the stress response.
Kempopeptins A and B, serine protease inhibitors with different selectivity profiles from a marine cyanobacterium, Lyngbya sp.

Two cyclodepsipeptides named kempopeptins A (1) and B (2) were isolated from a collection of a Floridian marine cyanobacterium, Lyngbya sp. , that had previously afforded the structurally related potent elastase inhibitors lyngbyastatin 7 and somamide B. The structures of 1 and 2 were elucidated mainly by 1D and 2D NMR spectroscopy, and the absolute configuration was established by chiral HPLC and Marfey's analysis of the degradation products. Kempopeptin A (1) exhibited an IC50 against elastase of 0.32 microM and against chymotrypsin of 2.6 microM, while kempopeptin B (2) inhibited trypsin with an IC50 of 8.4 microM.
TWEAK Appears as a Modulator of Endometrial IL-18 Related Cytotoxic Activity of Uterine Natural Killers

Background TWEAK (Tumor necrosis factor like WEAK inducer of apoptosis) is highly expressed by different immune cells and triggers multiple cellular responses, including control of angiogenesis. Our objective was to investigate its role in the human endometrium during the implantation window, using an ex-vivo endometrial microhistoculture model. Indeed, previous results suggested that basic TWEAK expression influences the IL-18 related uNK recruitment and local cytotoxicity. Methodology/Principal Findings Endometrial biopsies were performed 7 to 9 days after the ovulation surge of women in monitored natural cycles. Biopsies were cut in micro-pieces and cultured on collagen sponge with appropriate medium. Morphology, functionality and cell death were analysed at different time of the culture. We used this ex vivo model to study mRNA expressions of NKp46 (a uNK cytotoxic receptor) and TGF-beta1 (protein which regulates uNK cytokine production) after adjunction of excess of recombinant IL-18 and either recombinant TWEAK or its antibody. NKp46 protein expression was also detailed by immunohistochemistry in selected patients with high basic mRNA level of IL-18 and either low or high mRNA level of TWEAK. The NKp46 immunostaining was stronger in patients with an IL-18 over-expression and a low TWEAK expression, when compared with patients with both IL-18 and TWEAK high expressions. We did not observe any difference for TWEAK expression when recombinant protein IL-18 or its antibody was added, or conversely, for IL-18 expression when TWEAK or its antibody was added in the culture medium. In a pro-inflammatory environment (obtained by an excess of IL-18), inhibition of TWEAK was able to increase significantly NKp46 and TGF-beta1 mRNA expressions. Conclusions/Significance TWEAK doesn't act on IL-18 expression but seems to control IL-18 related cytotoxicity on uNK cells when IL-18 is over-expressed. Thus, TWEAK appears as a crucial physiological modulator to prevent endometrial uNK cytotoxicity in human.
Deducing Chemical Reaction Rate Constants and Their Regions of Confidence from Noisy Measurements of Time Series of Concentration

We present a new method for estimating rate coefficients from noisy observations of concentration levels at discrete time points. Our inference method is based on a new maximum likelihood approach to the estimation of probability density function of the variations in reactant concentration. The inference procedure returns the rate coefficients with their intervals of confidence, and the variance of noise in the input data.
High-Resolution Quantification of Hepatitis C Virus Genome-Wide Mutation Load and Its Correlation with the Outcome of Peginterferon-Alpha2a and Ribavirin Combination Therapy

Hepatitis C virus (HCV) is a highly mutable RNA virus and circulates as a heterogeneous population in individual patients. The magnitude of such population heterogeneity has long been proposed to be linked with diverse clinical phenotypes, including antiviral therapy. Yet data accumulated thus far are fairly inconclusive. By the integration of long RT-PCR with 454 sequencing, we have built a pipeline optimized for the quantification of HCV genome-wide mutation load at 1% resolution of mutation frequency, followed by a retrospective study to examine the role of HCV mutation load in peginterferon-alpha2a and ribavirin combination antiviral therapy. Genome-wide HCV mutation load varied widely with a range from 92 to 1639 mutations and presented a Poisson distribution among 56 patients (Kolmogorov-Smirnov statistic = 0.078, p = 0.25). Patients achieving sustained virological response (n = 26) had significantly lower mutation loads than that in null responders (n = 30) (mean and standard derivation: 524±279 vs. 805±271, p = 0.00035). All 36,818 mutations detected in 56 patients displayed a power-law distribution in terms of mutation frequency in viral population. The low-frequency mutation load, but not the high-frequency load, was proportional firmly to the total mutation load. In-depth analyses revealed that intra-patient HCV population structure was shaped by multiple factors, including immune pressure, strain difference and genetic drift. These findings explain previous conflicting reports using low-resolution methods and highlight a dominant role of natural selection in response to therapeutic intervention. By attaining its signatures from complex interaction between host and virus, the high-resolution quantification of HCV mutation load predicts outcomes from interferon-based antiviral therapy and could also be a potential biomarker in other clinical settings.
The Research and Application of Embedded Mobile Database

The article discusses the characteristics of mobile and embedded database as well as its synchronization realization on mobile terminal along with practical application. The article further provides several methods to improve the data accessing rate, efficiency, stability, maintainability and uniformity of the database, including multithread technology, three-layer duplication/buffer architecture, data’s optimization, and conflict detection mechanism. The result based on the analysis demonstrates a great improvement on those aspects. The result may have significance meaning and impact to the future research on embedded mobile database.