Miracle-dz/UniFAR-FTUs huggingface dataset:
Alanine aminotransferase, gamma-glutamyltransferase, and incident diabetes: the British Women's Heart and Health Study and meta-analysis.

OBJECTIVE To estimate and compare associations of alanine aminotransferase (ALT) and gamma-glutamyltransferase (GGT) with incident diabetes. RESEARCH DESIGN AND METHODS ALT and GGT were studied as determinants of diabetes in the British Women's Heart and Health Study, a cohort of 4,286 women 60-79 years old (median follow-up 7.3 years). A systematic review and a meta-analysis of 21 prospective, population-based studies of ultrasonography, which diagnosed nonalcoholic fatty liver disease (NAFLD), ALT, and GGT as determinants of diabetes, were conducted, and associations of ALT and GGT with diabetes were compared. RESULTS Ultrasonography-diagnosed NAFLD was associated with more than a doubling in the risk of incident diabetes (three studies). ALT and GGT both predicted diabetes. The fully adjusted hazard ratio (HR) for diabetes per increase in one unit of logged ALT was 1.83 (95% CI 1.57-2.14, I(2) = 8%) and for GGT was 1.92 (1.66-2.21, I(2) = 55%). To directly compare ALT and GGT as determinants of diabetes, the fully adjusted risk of diabetes in the top versus bottom fourth of the ALT and GGT distributions was estimated using data from studies that included results for both markers. For ALT, the HR was 2.02 (1.59-2.58, I(2) = 27%), and for GGT the HR was 2.94 (1.98-3.88, I(2) = 20%), suggesting that GGT may be a better predictor (P = 0.05). CONCLUSIONS Findings are consistent with the role of liver fat in diabetes pathogenesis. GGT may be a better diabetes predictor than ALT, but additional studies with directly determined liver fat content, ALT, and GGT are needed to confirm this finding.
Design & Development of an Automatic Test Packet Generation Prototype for Resolving Functional and Performance Problems

Networks are getting larger and more complex, yet administrators rely on rudimentary tools such as and to debug problems. We propose an automated and systematic approach for testing and debugging networks called “Automatic Test Packet Generation” (ATPG). ATPG reads router configurations and generates a device-independent model. The model is used to generate a minimum set of test packets to (minimally) exercise every link in the network or (maximally) exercise every rule in the network. Test packets are sent periodically, and detected failures trigger a separate mechanism to localize the fault. ATPG can detect both functional (e.g., incorrect firewall rule) and performance problems (e.g., congested queue). ATPG complements but goes beyond earlier work in static checking (which cannot detect liveness or performance faults) or fault localization (which only localize faults given liveness results). We describe our prototype ATPG implementation and results are indicated on two real-world data sets. We find that a small number of test packets suffices to test all rules in these networks: For example, 4000 packets can cover all rules in Stanford backbone network, while 54 are enough to cover all links. Sending 4000 test packets 10 times per second consumes less than 1% of link capacity. ATPG code and the datasets are publicly available. Keywords:Automated Test Packet Generation (ATPG), Media Access Control Address, Ethernet Network, Fault Localization, All-Pairs Reachability Table, Polynomial Runtime
Consumer Trend Prediction System Using Web Mining

The Ministry of Economy, Trade and Industry and the corporate world in Japan have recently embraced the ‘ Cool Japan ’policy. They have assisted Japanese content industries in exporting Japanese media contents, such as manga (comics), to foreign countries, especially in Asia. However, this overseas expansion has not been successful in producing profits to the expected degree. The main reason for this shortfall is that companies are unable to perceive local consumer consumption trends in those countries easily and at low cost. Consequently, they are unable to select media contents that might be popular in such areas in the future. Herein, we design a consumption trend calculating system that incorporates web mining. It is readily applicable to many countries and contents. Specifically, we use web mining of data elicited from search counts on search engines, tweet counts from Twitter, and article data from Wikipedia to calculate consumption trends based on weekly manga sales data in Japan. Results show that this model can predict consumption trends for six months with high accuracy and that it can be adapted to calculate consumption trends of other contents effectively, such as anime (animation) in Japan and manga in France. Moreover, we establish the ASIA TREND MAP web service to inform industries about these calculated consumption trends for Asian countries.
Biometric Security Systems

-The modern information technology evolution demands the use of computer networks with strict security performance. The password-based authentication system and the token-based systems that are currently deployed are not able to meet this performance Verification using biometrics has become in the last few years a key issue in security and privacy . The problems of traditional personal authentication systems may be solved by biometric systems. Information security has gained more and more attention from researchers because it plays an important role in our daily life. Biometrics-based authentication offers several advantages over other authentication methods; hence there has been a significant rise in the use of biometrics for user authentication in recent years. It is important that such biometrics-based authentication systems be designed to withstand attacks when employed in critical applications, especially in remote applications which are unattended such as ecommerce environment. In this paper we outline the strengths and weakness of biometrics-based authentication, and techniques to enhance the strength of the biometric system with new solutions for eliminating some of the weak links with techniques like steganography , watermarking, cryptosystems. For illustration purpose, finger print authentication, facial recognition has been considered.
Patterns of Scalable Bayesian Inference

Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with few clear overarching principles. In this paper, we seek to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. We review existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, we characterize the general principles that have proven successful for designing scalable inference procedures and comment on the path forward.
Increase Software Dependability via AOP-Based Runtime Adaptation

Increasingly complex application systems operating in dynamic environments are forcing researchers to find ways of developing and evolving dependable software systems dynamically. Runtime Adaptation is a critical feature for dependable application systems to cope with changes in the operating conditions and to meet the required dependability. AOP can improve the modularity of self-adaptive software by encapsulating the crosscutting concerns into aspects cleanly. Therefore, in this paper we take the advantages of AOP and self-adaptive technique, and propose an AOP-based dynamic adaptation approach. We show how to increase system dependability by runtime adaptation from the perspective of system internal state and external environment. Meanwhile, we illustrate our approach by applying it to a simplified on-line train ticket reservation system.
A rat monoclonal antibody reacting specifically with the tyrosylated form of alpha-tubulin. I. Biochemical characterization, effects on microtubule polymerization in vitro, and microtubule polymerization and organization in vivo

The antigenic site recognized by a rat monoclonal antibody (clone YL 1/2) reacting with alpha-tubulin (Kilmartin, J.V., B. Wright, and C. Milstein, 1982, J. Cell Biol., 93:576-582) has been determined and partially characterized. YL 1/2 reacts specifically with the tyrosylated form of brain alpha-tubulin from different mammalian species. YL 1/2 reacts with the synthetic peptide Gly-(Glu)3-Gly-(Glu)2- Tyr, corresponding to the carboxyterminal amino acid sequence of tyrosylated alpha-tubulin, but does not react with Gly-(Glu)3-Gly- (Glu)2, the constituent peptide of detyrosylated alpha-tubulin. Electron microscopy as well as direct and indirect immunofluorescence microscopy shows that YL 1/2 binds to the surface of microtubules polymerized in vitro and in vivo. Further in vitro studies show that the antibody has no effect on the rate and extent of microtubule polymerization, the stability of microtubules, and the incorporation of the microtubule-associated proteins (MAP2) and tau into microtubules. In vivo studies using Swiss 3T3 fibroblasts injected with YL 1/2 show that; when injected at low concentration (2 mg IgG/ml in the injection solution), the antibody binds to microtubules without changing their distribution in the cytoplasm. Injection of larger concentration of YL 1/2 (6 mg IgG/ml) induces the formation of microtubule bundles, and still higher concentrations cause the aggregation of microtubule bundles around the nucleus (greater than 12 mg IgG/ml).
High-resolution three-dimensional views of membrane-associated clathrin and cytoskeleton in critical-point-dried macrophages

We obtained high-resolution topographical information about the distribution of clathrin and cytoskeletal filaments on cytoplasmic membrane surfaces of macrophages spreading onto glass coverslips by both critical-point drying of broken-open cells and preparation of rotary platinum replicas. Irregular patches of the adherent ventral surface of the plasma membrane were exposed in these cells, and large areas of these exposed membranes were covered with clathrin-coated patches, pits, and vesicles. Various amounts of cytoskeleton were attached to the plasma membranes of these spreading cells, either as distinct starlike foci, or as individual filaments and bundles radiating out from the cytoskeletal meshwork. In newly adherent cells a well developed Golgi-GERL complex, characterized by smooth, dish-like cisternae associated with rough endoplasmic reticulum, was observed. There were many coated vesicles budding off from the Golgi cisternae, and these were predominantly of the large type (150 nm) usually associated with the plasma membrane. In critical-point-dried samples, both cytoskeleton and membranes were preserved in detail comparable to that of quick-frozen samples, after appropriate fixation. Rotary replication of critical-point-dried cells provides a rapid, easily controlled, and generally easy to perform method for obtaining samples of exposed membrane large enough to permit quantification of membrane- associated clathrin and cytoskeleton under various experimental conditions.
[Immunohistochemistry (I)].

CLINICAL OFFICES • Surgical Pathology 300 Pasteur Dr Rm H2110 MC 5243 Stanford, CA 94305 Tel (650) 723-7211 Fax (650) 725-7409 • Pathology 300 Pasteur Dr Rm L235 MC 5324 Stanford, CA 94305 Tel (650) 723-9016 Fax (650) 725-6902 • Valley Care Dept Of Pathology 5555 W Las Positas Blvd Pleasanton, CA 94588 Tel (925) 416-3404 Fax (925) 416-6593 ACADEMIC CONTACT INFORMATION • Alternate Contact Darlene Washington Administrative Assistant Email darlenew@stanford.edu Tel 650-725-0405
LEARNING APPROACH TO STUDY EFFECT OF FLEXIBLE SPINE ON RUNNING BEHAVIOR OF A QUADRUPED ROBOT

Effect of flexibility in the spine of a quadruped robot on its energy efficiency and stability is studied. The approach is based on learning parameters of cyclic position command to the actuators. The learning system employs a reinforcement learning method to find the parameters that result in stable running while the velocity-energy ratio is minimized. The learning is done on a simulated system and the final results are tested on a situated robot. The results show that a wider range of parameters results in stable running for softer spine. In addition, robot with harder spine consumes more energy.
Space environment information system: Applicability for mission design and operations

ESA's Space Environment Information System (SPENVIS) is a system of models of the space environment and its effects on materials (e.g. spacecraft). It covers the natural radiation belts, solar energetic particles, cosmic rays, plasmas, and micro-particles. SPENVIS currently integrates 35 distinct models, with new ones being added regularly. The underlying models arise from many years of research, supported by national and international space agencies, resulting in a variety of tools to investigate the Sun-Earth connection and near-earth environment. SPENVIS was originally developed as a browserbased research tool that collects these tools together, being capable of recreating the full range of conditions in most of the solar system. In recent years SPENVIS has been further developed into an Operational System. In addition to enhancing the modeling capabilities, this required an enhancement to the customer perspective, i.e. ease-of-use, consistency, stability, runtime, support, etc. SPENVIS is now available as a web-based or standalone application. As a Spacecraft Operational Support System, SPENVIS is further tailored to preferentially reproduce the current radiation environment for a range of common LEO, MEO and GEO orbits, and predict likely future variability and effects via a purpose designed user interface. It will also accept autonomous input data regarding the real-time space environment via a variety of ISES-standard alerts and reports. This paper presents the latest developments, with particular significance for the satellite operations community.
Cell killing by lysosomotropic detergents

We have studied the mechanism by which lysosomotropic detergents kill baby hamster kidney cells. Lysosomotropic detergents are lysosomotropic amines (compounds with pK between 5 and 9, such as imidazole or morpholine) containing straight-chain hydrocarbon "tails" of 9-14 carbon atoms (Firestone, R. A., J. M. Pisano, and R. J. Bonney. 1979, J. Med. Chem., 22:1130-1133). Using lucifer yellow CH as a specific fluorescent label for lysosomes, it was shown by light microscopy that N-dodecyl (C12)-imidazole acted rapidly to damage lysosomes, causing leakage of dye into the cytoplasm. This was followed at later times by vacuolization, blebbing of the plasma membrane, cell rounding, and cell death. 3H-labeled C12-imidazole rapidly diffused into cells where much of it was trapped in lysosomes as shown by its co-migration with lysosomes in Percoll gradients. Cells preincubated with C12-imidazole released it slowly into C12-imidazole-free media, permitting the cells to be killed by the preincubation dose. Cell killing by the lysosomotropic detergents exhibited strongly sigmoidal dose-response curves. The sensitivity of baby hamster kidney cells to killing by C12- imidazole was density dependent, the cells being most sensitive at lowest cell densities, and relatively resistant at confluence. The amount of 3H-C12-imidazole taken up by the cells was also density dependent, with highest specific uptake occurring at the lowest cell density. A rise in lysosomal pH, measured in fluoresceinated dextran- labeled cells, commenced immediately upon addition of C12-imidazole to cells, and continued for over an hour. This was followed after a lag of 1-2 h by inhibition of protein and RNA synthesis and by lactate dehydrogenase release. Ionophores or lysosomotropic amines, such as methylamine, that raise intralysosomal pH provided substantial protection of the cells from killing by lysosomotropic detergents. These findings provide strong support for the idea that lysosomotropic detergents kill cells by disrupting lysosomes from within.
Power Quality Improvement of Grid-inter Connected DG system With Closed-Loop Power Control technique

The proposed system presents power-control strategies of a grid-connected hybrid generation system with versatile power transfer. This hybrid system allows maximum utilization of freely available renewable energy sources like wind and photovoltaic energies. For this, an adaptive MPPT algorithm along with standard perturbs and observes method will be used for the system. Also, this configuration allows the two sources to supply the load separately or simultaneously depending on the availability of the energy sources. The turbine rotor speed is the main determinant of mechanical output from DG energy and Solar cell operating voltage in the case of output power from solar energy.The inverter converts the DC output from non-conventional energy into useful AC power for the connected load. In order to utilization distributed generation (DG) unit interfacing converters to actively compensate harmonics, this paper proposes an enhanced current control approach, which seamlessly integrates system harmonic mitigation capabilities with the primary DG power generation function. As the proposed current controller has two well- decoupled control branches to independently control fundamental and harmonic DG currents, local nonlinear load harmonic current detection and distribution system harmonic voltage detection are not necessary for the proposed harmonic compensation method. Moreover, a closed-loop power control scheme is employed to directly derive the fundamental current reference without using any phase-locked loops (PLL). The proposed power control scheme effectively eliminates the impacts of steady-state fundamental current tracking errors in the DG units. Thus, an accurate power control is realized even when the harmonic compensation functions are activated hybrid system operates under normal conditions which include normal room temperature in the case of solar. The simulation results are presented to illustrate the operating principle, feasibility and reliability of this proposed system. Index Terms- Active power filter, distributed generation, harmonic compensation, harmonic extraction, phase-locked loop (PLL), resonant controller, virtual impedance.
Angiodysplasia Natural History and Efficacy of Therapeutic Interventions

Angiodysplasia, a disease for which the optimal treatment is uncertain, is a frequent cause of lower intestinal bleeding among older patients. To study the natural history o f angiodysplasia and compare the efficacy of medical therapy, endoscopic electrocoagulation, and surgery, the course o f 101 patients evaluated from 1974 through 1983 at the Massachusetts General Hospital was reviewed. Angiodysplasia caused bleeding that ranged from occult blood in stools to massive hemorrhage and was also observed incidentally in nonbleeding patients. Patients were followed for up to 10 years (mean of 22 months). Rebleeding was defined as evidence of hemorrhage requiring hospital admission, transfusion, or surgery. Thirty-one patients were treated surgically, 19 patients were treated endoscopically, and 36 patients were treated medically. Using life table analysis we observed similar rebleeding rates among medically and endoscopically treated groups. The surgically treated group had a frequency of rebleeding less than half that o f the other groups (P = O. 15). A multivariate regression analysis failed to identify any factors other than coagulopathy to explain the different incidence of rebleeding in the patients treated by endoscopic electrocoagulation and surgery.
CAM Practices and Treatment Adherence Among Key Subpopulations of HIV+ Latinos Receiving Care in the San Diego-Tijuana Border Region: A Latent Class Analysis

Latinos living in the United States-Mexico border region bear a disproportionate HIV/AIDS burden compared to individuals living in the interior of both nations and face a constellation of barriers that determine their ability to access and adhere to HIV care. Use of complementary and alternative medicine (CAM) may be associated with suboptimal treatment adherence. Sociodemographic factors, health practices, and social determinants of health unique to the border region may further contribute to health disparities that undermine care engagement and continuity. Improved understanding of HIV-positive Latino subgroups and their risk profiles can lead to more effective, targeted clinical and public health interventions. We undertook this study to identify and characterize distinct classes of HIV-positive Latinos in the San Diego-Tijuana border region, differentiated by HIV and border-related factors, utilizing latent class analysis. We investigated relationships between class membership and CAM utilization and self-reported antiretroviral therapy (ART) adherence. Five distinct classes were identified with unique demographic, HIV risk, and border mobility profiles. CAM was recently used by nearly half of each class, though there were significant differences in the proportion of CAM use by class ranging from 44.4 to 90.9%. As well, all classes were currently receiving ART at similarly high rates and ART adherence outcomes were not significantly different based on class. Findings highlight the significant use of CAM by all HIV-positive Latinos in the border region and imply the need for a research framework which appropriately acknowledges the heterogeneous nature of this population, such as intersectionality. Further research is recommended into understanding how patients integrate CAM into HIV treatment and the risks and benefits of incorporating CAM into HIV treatment.
STEFTR: A Hybrid Versatile Method for State Estimation and Feature Extraction From the Trajectory of Animal Behavior

Animal behavior is the final and integrated output of brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient prior knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach for behavioral state estimation and feature extraction (STEFTR) only from low-content animal trajectory data. To demonstrate the effectiveness of the proposed method, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales—from mm to 1,000 km in space and from sub-seconds to days in time. We successfully estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.