Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep metaproteomic analysis of human salivary supernatant

The human salivary proteome is extremely complex, including proteins from salivary glands, serum, and oral microbes. Much has been learned about the host component, but little is known about the microbial component. Here we report a metaproteomic analysis of salivary supernatant pooled from six healthy subjects. For deep interrogation of the salivary proteome, we combined protein dynamic range compression (DRC), multidimensional peptide fractionation, and high‐mass accuracy MS/MS with a novel two‐step peptide identification method using a database of human proteins plus those translated from oral microbe genomes. Peptides were identified from 124 microbial species as well as uncultured phylotypes such as TM7. Streptococcus, Rothia, Actinomyces, Prevotella, Neisseria, Veilonella, Lactobacillus, Selenomonas, Pseudomonas, Staphylococcus, and Campylobacter were abundant among the 65 genera from 12 phyla represented. Taxonomic diversity in our study was broadly consistent with metagenomic studies of saliva. Proteins mapped to 20 KEGG pathways, with carbohydrate metabolism, amino acid metabolism, energy metabolism, translation, membrane transport, and signal transduction most represented. The communities sampled appear to be actively engaged in glycolysis and protein synthesis. This first deep metaproteomic catalog from human salivary supernatant provides a baseline for future studies of shifts in microbial diversity and protein activities potentially associated with oral disease.
A NEURAL RECORDING FRONT END FOR MULTI-CHANNEL WIRELESS IMPLANTABLE APPLICATIONS

A NEURAL RECORDING FRONT END FOR MULTI-CHANNEL WIRELESS IMPLANTABLE APPLICATIONS By Haitao Li By recording neurons’ activities simultaneously, awake animal behaviors can be predicted in real time, brain–machine interfaces controlling the machine by thought can be set up, and treatments for neurological disorders can be explored. Existing commercial neural recording equipment are bench-top systems that are bulky, high cost, consume high power, and require wire bundles tethering the neural recording probes to skull-mounted connector. To overcome these disadvantages, a miniature wireless implanted multi-channel integrated neural recording micro-system with low power and low noise is needed. This thesis work addresses the challenges to developing an analog front end for wireless implanted multi-channel neural recording systems, which include ultra low noise, extremely low power, high power supply rejection radio, low area occupation, sufficient data conversion speed and optimizing design tradeoff between all these requirements. Two versions of a neural amplifier were built. Following optimization guidelines in this thesis, noise efficiency and a new figure of merit for neural amplifiers were effectively improved. A successive approximation (SAR) ADC tailored to wireless implantable neural recording systems was also designed. The new SARADC is able to process 32 neural spikes recording channels in a multiplexing manner with low power consumption and low area occupation. The results of this research lay a solid foundation for future realization of high sensitivity wireless implantable neural recording system
Iterative Soft Decision Feedback Zig-Zag Equalizer for 2D Intersymbol Interference Channels

We present a novel iterative soft decision feedback zig-zag algorithm for detection of binary images corrupted by two dimensional intersymbol interference and additive white Gaussian noise. The algorithm exchanges soft information between maximum-a-posteriori detectors employing different zigzag scan directions. Each detector exploits soft-decision feedback from the other zig-zag detectors. Simulation results for the 2 × 2 averaging mask channel show that, at low signal-to-noise ratios, the new algorithm gains about 1 dB over an iterative row column soft decision feedback algorithm and over a separable mask algorithm, two of the best previously published schemes. When the zig-zag algorithm is concatenated with the row-column algorithm, the concatenated system performs as well as or better than four of the best previously published algorithms, at both low and high signal-to-noise ratios, for a variety of 2 × 2 and 3 × 3 convolution masks; in several cases, the system performs within less than 0.1 dB of the maximum-likelihood performance bound.
Temporary ponds and hygrophilous grasslands plant communities in Monfurado Site of Community Importance

Temporary ponds are seasonal wetlands subjected to extreme and unstable ecological conditions due to the annual alternation between the flooded and dry phases. The ephemeral character of the flora and the changeable annual weather explain why these habitats have been poorly studied and documented. The objective of this study, in the Monfurado Site of Community Importance, was to characterize seasonal wetland plant communities using a phytosociological approach and numerical analysis (classification and ordination). The results lead to the site’s inclusion in two Natura 2000 Network priority habitats: Mediterranean temporary ponds (3170) in depression landform with impermeable layer in the underground with Isoeto-Nanojuncetea vegetation complexes; pseudo-steppe with grasses and annuals of the Thero - Brachypodietea , sub-type ‘Malhadais’ (6220pt2) in shallow areas with Isoeto-Nanojuncetea species.
A framework for stabilization of nonlinear sampled-data systems based on their approximate discrete-time models

A unified framework for design of stabilizing controllers for sampled-data differential inclusions via their approximate discrete-time models is presented. Both fixed and fast sampling are considered. In each case, sufficient conditions are presented which guarantee that the controller that stabilizes a family of approximate discrete-time plant models also stabilizes the exact discrete-time plant model for sufficiently small integration and/or sampling periods. Previous results in the literature are extended to cover: 1) continuous-time plants modeled as differential inclusions; 2) general approximate discrete-time plant models; 3) dynamical discontinuous controllers modeled as difference inclusions; and 4) stability with respect to closed arbitrary (not necessarily compact) sets.
Scene Text Extraction Based on HSL

The characteristics of scene text include the uneven lighting and the variability of character color which make scene text extraction more difficult than document image. In this paper, a novel scene text extraction method is proposed based on the independence between hue and lightness. We categorize text region into three types according to the composed color. Different color information is used to segment different text region. The periodicity and instability of hue value in the hue image are considered. A new local adaptive thresholding method is proposed to segment lightness images due to high contrast of scene text. Experiments show that the proposed method can effectively choose hue or lightness information to segment color scene text region, and obtain better results in terms of precision of character recognition.
Continuous Datacenter Consolidation

Efficient mapping of Virtual Machines~(VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly impacts profit. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any initial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods for continuous optimization of the VM-to-server mapping based on combinations of fundamental management actions, namely suspending and resuming physical machines, migrating VMs, and suspending and resuming VMs. By using these methods, cloud infrastructure providers can continuously optimize their server resources regardless of the predictability of the workload. To verify that our approach is applicable in real-world scenarios, we build a proof-of-concept datacenter management system that implements the proposed algorithms. The feasibility of our approach is evaluated through a combination of simulations and real experiments where our system provisions a workload of benchmark applications. Our results indicate that the proposed algorithms are feasible, that the combined management approach achieves the best results, and that the VM suspend and resume mechanism has the largest impact on provider profit.
Wildfire-related floods and debris flows in Montana in 2000 and 2001

Following extensive wildfires in summer 2000, Montana experienced flooding and debris flows in three different burned areas: (1) the Bitterroot area in southwestern Montana, (2) the Canyon Ferry area near Helena, and (3) the Ashland area in southeastern Montana. Flooding and debris flows in the Bitterroot study area began with a large, frontal storm in September-October 2000. No precipitation data were available at sites in the burned area. Daily precipitation at one National Weather Service station near the Bitterroot burn area had a recurrence interval of about 10 years. The storm resulted in debris flows and a peak flood discharge on Little Sleeping Child Creek that had a recurrence interval of about 100 years. July
On fusion of timbre-motivated features for singing voice detection and singer identification

Timbre is the quality of sound which allows the ear to distinguish between musical sounds. In this paper, we study timbre effects in identification of singing voice segments in popular songs. Firstly, we identify between singing voice and instrumental segments in a song. Then, singing voice segments are further categorized according to their singer identity. Timbre-motivated effects are formulated by fusion of systems that use the features from vibrato, harmonic information and other features extracted using Mel and Log frequency scale filter banks. Statistical methods to select singing voice segments with high confidence measure are proposed for better performance in singer identification process. The experiments conducted on a database of 214 popular songs show that the proposed approach is effective.
The Synergizer service for translating gene, protein and other biological identifiers

Summary: The Synergizer is a database and web service that provides translations of biological database identifiers. It is accessible both programmatically and interactively. Availability: The Synergizer is freely available to all users inter-actively via a web application (http://llama.med.harvard.edu/synergizer/translate) and programmatically via a web service. Clients implementing the Synergizer application programming interface (API) are also freely available. Please visit http://llama.med.harvard.edu/synergizer/doc for details. Contact: fritz_roth@hms.harvard.edu
Understanding the causal factors of obesity using the International Classification of Functioning, Disability and Health

Purpose. Behavioural, personal, psychological, sociodemographic, environmental, biological and childbearing factors have been associated with obesity among women. This study quantitatively explored the effects of these factors on predicting body mass index (BMI) in U.S. women using the International Classification of Functioning, Disability and Health (ICF) and determined the effectiveness of using the ICF with population-level data. Methods. We used the ICF Core Sets for Obesity, and data from the 1999–2006 National Health and Nutrition Examination Survey (NHANES) in a sample of 8766 U.S. women to quantify the impact of all associated causal factors. Linear regression was used in the analyses. Results. Body image perceptions (42%) was the most significant contributor, followed by hypertension (12%), general health condition (11%), diabetes/borderline diabetes (10%), arthritis (9%) and performing vigorous activity (9%). Conclusions. To decrease obesity prevalence rates in U.S. women, obesity prevention and treatment programmes should parallel the contributory effects of its most significant causal factors of psychological, biological and behavioural. In addition, more research and data are needed to explore the relationship between BMI in women and the multiple influencing factors by going beyond the more frequently available information of age, gender, race, education, income and parity.
The Cost of Smoking in California.

INTRODUCTION The economic impact of smoking, including healthcare costs and the value of lost productivity due to illness and mortality, was estimated for California for 2009. METHODS Smoking-attributable healthcare costs were estimated using a series of econometric models that estimate expenditures for hospital care, ambulatory care, prescriptions, home health care, and nursing home care. Lost productivity due to illness was estimated using an econometric model predicting how smoking status affects the number of days lost from work or other activities. The value of lives lost from premature mortality due to smoking was estimated using an epidemiological approach. RESULTS Almost 4 million Californians still smoke, including 146 000 adolescents. The cost of smoking in 2009 totaled $18.1 billion, including $9.8 billion in healthcare costs, $1.4 billion in lost productivity from illness, and $6.8 billion in lost productivity from premature mortality. This amounts to $487 per California resident and $4603 per smoker. Costs were greater for men than for women. Hospital costs comprised 44% of healthcare costs. CONCLUSIONS Despite extensive efforts at tobacco control in California, healthcare and lost productivity costs attributable to smoking remain high. Compared to costs for 1999, the total cost was 15% greater in 2009. However, after adjusting for inflation, real costs have fallen by 13% over the past decade, indicating that efforts have been successful in reducing the economic burden of smoking in the state.
Visual Analytics for Large Document Sets

We examine what we refer to as topic similarity networks: graphs in which nodes represent latent topics in text collections and links represent similarity among topics. Efficient and effective approaches to both building and labeling such networks are described. Visualizations of topic models based on these networks are shown to be a powerful means of exploring, characterizing, and summarizing large collections of unstructured text documents
Effects of Acupuncture on Menopause-Related Symptoms in Breast Cancer Survivors: A Meta-analysis of Randomized Controlled Trials

Background: Evidence regarding the effects of acupuncture on hot flashes in breast cancer survivors is conflicting. Little is known about the intermediate-term effects of acupuncture on hot flashes and other menopause-related symptoms in breast cancer survivors. Objective: The objective of this study was to evaluate the short-term and intermediate-term effects of acupuncture on menopause-related symptoms and particularly on hot flashes in breast cancer survivors. Methods: Electronic databases including EMBASE, PubMed, PsycINFO, Web of Science, CINAHL, Wanfang Data Chinese Database, and China Knowledge Resource Integrated Database from inception until June 15, 2014, were searched. Randomized controlled trials in which acupuncture was compared with sham controls or other interventions according to the reduction of hot flashes or menopause-related symptoms in breast cancer survivors were included. Results: We analyzed 7 studies involving 342 participants. Acupuncture significantly reduced the frequency of hot flashes and severity of menopause-related symptoms (g = −0.23 and −0.36, respectively) immediately after the completion of treatment. In comparison with sham acupuncture, effects of true acupuncture on the frequency and severity of hot flashes were not significantly different. At 1 to 3 months’ follow-up, the severity of menopause-related symptoms remained significantly reduced (g = −0.56). Conclusion: Acupuncture yielded small-size effects on reducing hot-flash frequency and the severity of menopause-related symptoms. Implications for Practice: Acupuncture may be used as a complementary therapy for breast cancer survivors experiencing hot flashes and other menopause-related symptoms; however, whether acupuncture exerts specific treatment effects other than needling or placebo effects needs to be further evaluated.
EFFECT OF THYME ( ZATARIA MULTIFLORA ) EXTRACT AND PROBIOTIC ( BROILACT ) FEEDING ON BLOOD THYROID HORMONES CONCENTRATION AND GROWTH HORMONE GENE EXPRESSION OF LIVER IN BROILER CHICKENS

This study was conducted to examine the effects of thyme extract and probiotic on biological growth promoters. Therefore blood thyroid hormones (T3 and T4) concentration and growth hormone (GH) gene expression were measured. 108 one-day-old Ross male broiler were randomly allocated in 3 experimental treatments including: controlunsupplemented (CTRL), birds supplemented with Zataria multiflora extract (Thy) and probiotic in feed (Pro). Each treatment had 3 replicates of 12 broilers. The birds were fed on a cornsoybean based diet. T3 & T4 concentrations and GH gene expression in liver were determined. At 42 day of age T3 concentration not significantly changed in treatments (P>0.05). T4 concentration was significantly higher in Pro compared to Thy (P<0.05). GH gene expression in Pro birds significantly increased compared with CTRL and Thy birds (P<0.05) and thyme extract had no effect on GH gene expression and T3 and T4 (P>0.05). It may be concluded that dietary supplementation of probiotic may influence the biological growth promoters so T3 & T4 concentrations and GH gene expression in broiler and thyme extract had no effect on this biological parameters. Researchers indicated that some phytogenic extracts or probiotics improve growth performance.
Cold Fronts in CDM clusters

Recently, high-resolution Chandra observations revealed the existence of very sharp features in the X-ray surface brightness and temperature maps of several clusters (Vikhlinin et al., 2001). These features, called “cold fronts” , are characterized by an increase in surface brightness by a factor ∼ > 2 over 10-50 kpc, accompanied by a drop in temperature of a similar magnitude. The existence of such sharp gradients can be used to put interesting constraints on the physics of the intracluster medium (ICM), if their mechanism and longevity are well understood. Here, we present results of a search for cold fronts in high-resolution simulations of galaxy clusters in cold dark matter (CDM) models. We show that sharp gradients with properties similar to those of observed cold fronts naturally arise in cluster mergers when the shocks heat gas surrounding the merging sub-cluster, while its dense core remains relatively cold. The compression induced by supersonic motions and shock heating during the merger enhance the amplitude of gas density and temperature gradients across the front. Our results indicate that cold fronts are non-equilibrium transient phenomena and can be observed for a period of less than a billion years. We show that the velocity and density ﬁelds of gas surrounding the cold front can be very irregular which would complicate analyses aiming to put constraints on the physical conditions of the intracluster medium in the vicinity of the front.
Functional Partnership of the Copper Export Machinery and Glutathione Balance in Human Cells*

Background: Redox machinery was implicated in regulating copper export from cells. Results: The redox state of Atox1 depends on glutathione balance. In low glutathione, Atox1 becomes essential for cell viability independently of copper levels. Conclusion: Atox1 and glutathione work together to maintain normal cell growth. Significance: Interactions of two pathways explain differences between various cells in their metal and redox sensitivity. Cells use the redox properties of copper in numerous physiologic processes, including antioxidant defense, neurotransmitter biosynthesis, and angiogenesis. Copper delivery to the secretory pathway is an essential step in copper utilization and homeostatic maintenance. We demonstrate that the glutathione/glutathione disulfide (GSH/GSSG) pair controls the copper transport pathway by regulating the redox state of a copper chaperone Atox1. GSSG oxidizes copper-coordinating cysteines of Atox1 with the formation of an intramolecular disulfide. GSH alone is sufficient to reduce the disulfide, restoring the ability of Atox1 to bind copper; glutaredoxin 1 facilitates this reaction when GSH is low. In cells, high GSH both reduces Atox1 and is required for cell viability in the absence of Atox1. In turn, Atox1, which has a redox potential similar to that of glutaredoxin, becomes essential for cell survival when GSH levels decrease. Atox1+/+ cells resist short term glutathione depletion, whereas Atox1−/− cells under the same conditions are not viable. We conclude that GSH balance and copper homeostasis are functionally linked and jointly maintain conditions for copper secretion and cell proliferation.
Analysis of S Band Substrate Integrated Waveguide Power Divider, Circulator and Coupler

The Substrate Integrated Waveguide (SIW) technology is a very promising technique with which we can take the advantages of both waveguides and planar transmission lines. Therefore, in [2.1-3] GHz band various microwave components and devices have been designed successfully using Ansoft HFSS software. We then proceeded to the realization of the coupler and then made measurements of the frequency response in the range [2.1-3] GHz using a network analyzer. Thus, results of this modeling are presented, discussed and allow to integrate these devices in planar circuits.
Probabilistic dialogue act extraction for concept based multilingual translation systems

This paper describes a probabilistic methodfor dialogue act (DA) extraction for concept-based multilingual translation systems. A DA is a unit of a semantic interlingua and it consists of speaker information, speech act, concept and argu-ment. Probabilistic models for the extraction of speech acts or concepts are trained as speech act or concept dependent word n-gram models. The proposed method is evaluated on DA-annotated English and Japanese databases. The experimental results show that the proposed method gives a better performance compared to the conventioanl grammar-based approach. In addition, the proposed method is much more robust for erroneous inputs obtained as speech recognition outputs.
Kluth Type IV3 Membranous Esophageal Atresia at Middle One-third of Esophagus: An Extremely Rare Entity

We herein present an extremely rare case of an isolated membranous atresia causing near-complete obstruction of the esophagus. The neonate presented with drooling of saliva and frothing from the mouth. A red rubber catheter met with an obstruction at 12 cm from the gum margins. Radiograph showed paucity of gas in the abdomen. Thoracotomy revealed external continuity of esophagus; dilated and elongated proximal segment constituting upper half of esophagus, and a membrane with tiny opening in the center, at its junction with narrow distal segment. Excision was performed. A high index of suspicion for membrane should be kept in dealing with esophageal obstruction beyond 10 cm from the gum margins, particularly those with paucity of abdominal gas pattern or gasless abdomen.