Miracle-dz/UniFAR-FTUs huggingface dataset:
Diurnal rhythm and effects of feeding, exercise and recombinant equine growth hormone on serum insulin concentrations in the horse.

REASONS FOR PERFORMING THE STUDY As growth hormone increases lean body mass, it could be a therapy for obese horses. However, growth hormone use induces hyperinsulinaemia in some species, so further investigation is warranted. OBJECTIVES To investigate the effects of feeding, exercise and growth hormone therapy on basal insulin concentrations in healthy horses. STUDY DESIGN In vivo experimental study. METHODS Blood samples were obtained every 30 min from 12 geldings over 24 h, to establish basal serum insulin concentrations, before they underwent a 3-week exercise programme. Horses were allocated into 2 groups and exercised for another 4 weeks. Group A received daily i.m. injections of recombinant equine growth hormone; 5 mg/day for 5 days, then 12.5 mg/day for 16 days. Blood samples were taken daily before feeding. Insulin vs. time area under curve of Groups A and B were compared using a Student's unpaired t test. RESULTS Horses demonstrated insulin peaks within 2 h of feeding of 577 ± 108.3 pmol/l at 09.30 h and 342.4 ± 75.7 pmol/l at 17.30 h, despite receiving the same meal. The nadir was between midnight and 07.30 h. Exercise had no effect on basal insulin concentrations prior to equine growth hormone administrations. The equine growth hormone injections increased serum insulin concentrations (P = 0.01) within Group A, from 44.4 ± 15.3 pmol/l initially to 320.9 ± 238.2 pmol/l by Day 12. Exogenous growth hormone caused variable hyperinsulinaemia, which was alleviated once equine growth hormone administration ceased. CONCLUSIONS Single serum samples taken prior to the morning meal provide basal insulin concentrations. Exercise did not change basal insulin concentrations. However, equine growth hormone injections increased basal insulin concentrations, which were not ameliorated by exercise. POTENTIAL RELEVANCE This therapy is not recommended to address obesity in insulin-resistant equids.
Photoreactivation is the main repair pathway for UV-induced DNA damage in coral planulae

SUMMARY The larvae of most coral species spend some time in the plankton, floating just below the surface and hence exposed to high levels of ultraviolet radiation (UVR). The high levels of UVR are potentially stressful and damaging to DNA and other cellular components, such as proteins, reducing survivorship. Consequently, mechanisms to either shade (prevent) or repair damage potentially play an important role. In this study, the role of photoreactivation in the survival of coral planulae was examined. Photoreactivation is a light-stimulated response to UV-damaged DNA in which photolyase proteins repair damaged DNA. Photoreactivation rates, as well as the localization of photolyase, were explored in planulae under conditions where photoreactivation was or was not inhibited. The results indicate that photoreactivation is the main DNA repair pathway in coral planulae, repairing UV-induced DNA damage swiftly (K=1.75 h–1 and a half-life of repair of 23 min), with no evidence of any light-independent DNA repair mechanisms, such as nucleotide excision repair (NER), at work. Photolyase mRNA was localized to both the ectoderm and endoderm of the larvae. The amount of cell death in the coral planulae increased significantly when photoreactivation was inhibited, by blocking photoreactivating light. We found that photoreactivation, along with additional UV shielding in the form of five mycosporine-like amino acids, are sufficient for survival in surface tropical waters and that planulae do not accumulate DNA damage despite being exposed to high UVR.
Accurate CPU Power Modeling for Multicore Smartphones

CPU is a major source of power consumption in smartphones. Power modeling is a key technology to understand CPU power consumption and also an important tool for power management on smartphones. However, we have found that existing CPU power models on smartphones are ill-suited for modern multicore CPUs: they can give high estimation errors (up to 34%) and high estimation accuracy variation (more than 30%) for different types of workloads on mainstream multicore smartphones. The root cause is that those models estimate the power consumption of a CPU based on only frequency and utilization of the CPU, but do not consider CPU idle power states. However, we have found that CPU idle power states play a critical role in power consumption of modern multicore CPUs. Therefore, we have developed a new approach for CPU power modeling, which takes CPU idle power states into consideration, and thus can significantly improve the power estimation accuracy and stability for multicore smartphones. We present the detailed design of our power modeling approach and a prototype implementation on commercial multicore smartphones. Evaluation results show that our approach consistently achieves a high average accuracy of 98% for various benchmarks, and 96% for real applications, which significantly outperforms the existing approaches.
Fast dynamic binary translation for the kernel

Dynamic binary translation (DBT) is a powerful technique with several important applications. System-level binary translators have been used for implementing a Virtual Machine Monitor [2] and for instrumentation in the OS kernel [10]. In current designs, the performance overhead of binary translation on kernel-intensive workloads is high. e.g., over 10x slowdowns were reported on the syscall nanobenchmark in [2], 2-5x slowdowns were reported on lmbench microbenchmarks in [10]. These overheads are primarily due to the extra work required to correctly handle kernel mechanisms like interrupts, exceptions, and physical CPU concurrency. We present a kernel-level binary translation mechanism which exhibits near-native performance even on applications with large kernel activity. Our translator relaxes transparency requirements and aggressively takes advantage of kernel invariants to eliminate sources of slowdown. We have implemented our translator as a loadable module in unmodified Linux, and present performance and scalability experiments on multiprocessor hardware. Although our implementation is Linux specific, our mechanisms are quite general; we only take advantage of typical kernel design patterns, not Linux-specific features. For example, our translator performs 3x faster than previous kernel-level DBT implementations while running the Apache web server.
Vocabulary Manipulation for Neural Machine Translation

In order to capture rich language phenomena, neural machine translation models have to use a large vocabulary size, which requires high computing time and large memory usage. In this paper, we alleviate this issue by introducing a sentence-level or batch-level vocabulary, which is only a very small sub-set of the full output vocabulary. For each sentence or batch, we only predict the target words in its sentence-level or batch-level vocabulary. Thus, we reduce both the computing time and the memory usage. Our method simply takes into account the translation options of each word or phrase in the source sentence, and picks a very small target vocabulary for each sentence based on a word-to-word translation model or a bilingual phrase library learned from a traditional machine translation model. Experimental results on the large-scale English-to-French task show that our method achieves better translation performance by 1 BLEU point over the large vocabulary neural machine translation system of Jean et al. (2015).
Minor Nucleotide Substitutions in the omp31 Gene ofBrucella ovis Result in Antigenic Differences in the Major Outer Membrane Protein That It Encodes Compared to Those of the OtherBrucella Species

ABSTRACT The gene coding for the major outer membrane protein Omp31 was sequenced in five Brucella species and their biovars. Although the omp31 genes appeared to be highly conserved in the genus Brucella, nine nucleotide substitutions were detected in the gene of Brucella ovis compared to that ofBrucella melitensis. As shown by differential binding properties of monoclonal antibodies (MAbs) to the twoBrucella species, these nucleotide substitutions result in different antigenic properties of Omp31. The antigenic differences were also evidenced when sera from B. ovis-infected rams were tested by Western blotting with the recombinant B. melitensis or B. ovis Omp31 proteins. Twelve available sera reacted with recombinant B. ovis Omp31, but only four of them reacted with recombinant B. melitensisOmp31. These results validate previous evidence for the potential of Omp31 as a diagnostic antigen for B. ovis infection in rams and demonstrate that B. ovis Omp31, instead of B. melitensis Omp31, should be used to evaluate this point. The antigenic differences between the B. melitensis andB. ovis Omp31 proteins should also be taken into account when Omp31 is evaluated as a candidate for the development of subcellular vaccines against B. ovis infection. No reactivity against recombinant B. melitensis Omp31 was detected, by Western blotting, with sera from B. melitensis-infected sheep. Accordingly, Omp31 does not seem to be a good diagnostic antigen for B. melitensis infections in sheep. Two immunodominant regions were identified on the B. ovis Omp31 protein by using recombinant DNA techniques and specific MAbs. Sera from B. ovis-infected rams that reacted with the recombinant protein were tested by Western blotting against one of these immunodominant regions shown to be exposed at the bacterial surface. Only 4 of the 12 sera reacted, but with strong intensity.
Loss of Histone Deacetylase 2 Improves Working Memory and Accelerates Extinction Learning

Histone acetylation and deacetylation can be dynamically regulated in response to environmental stimuli and play important roles in learning and memory. Pharmacological inhibition of histone deacetylases (HDACs) improves performance in learning tasks; however, many of these classical agents are “pan-HDAC” inhibitors, and their use makes it difficult to determine the roles of specific HDACs in cognitive function. We took a genetic approach using mice lacking the class I HDACs, HDAC1 or HDAC2, in postmitotic forebrain neurons to investigate the specificity or functional redundancy of these HDACs in learning and synaptic plasticity. We show that selective knock-out of Hdac2 led to a robust acceleration of the extinction rate of conditioned fear responses and a conditioned taste aversion as well as enhanced performance in an attentional set-shifting task. Hdac2 knock-out had no impact on episodic memory or motor learning, suggesting that the effects are task-dependent, with the predominant impact of HDAC2 inhibition being an enhancement in an animal's ability to rapidly adapt its behavioral strategy as a result of changes in associative contingencies. Our results demonstrate that the loss of HDAC2 improves associative learning, with no effect in nonassociative learning tasks, suggesting a specific role for HDAC2 in particular types of learning. HDAC2 may be an intriguing target for cognitive and psychiatric disorders that are characterized by an inability to inhibit behavioral responsiveness to maladaptive or no longer relevant associations.
Echocardiographic and Hemodynamic Predictors of Survival in Precapillary Pulmonary Hypertension: Seven-Year Follow-Up

Background—In this study, we looked at the prognostic value of echocardiographic and hemodynamic measures in a large cohort of patients with precapillary pulmonary hypertension before and after initiation of treatment. Methods and Results—Data were collected prospectively in a cohort of consecutive patients with precapillary pulmonary hypertension referred between 2002 and 2011. A range of clinical and echocardiographic variables were collected and stored on a database to assess predictors of survival. Invasive hemodynamic data including pulmonary artery pressure, pulmonary vascular resistance, capillary wedge pressure, and cardiac index were also obtained at baseline in all patients. Outcome was defined as mortality because of cardiovascular-related death. The study cohort comprised 777 patients (514 women) with precapillary pulmonary hypertension. A total of 195 (25%) died. In multivariable analysis, moderate or severe tricuspid regurgitation (hazard ratio [HR], 26.537; 95% confidence interval, 11.536–61.044; P<0.001), right ventricular myocardial performance index (HR, 3.421; 95% confidence interval, 1.777–6.584; P<0.001), and the presence of pericardial effusion (HR, 1.38; 95% confidence interval, 1.023–1.862; P=0.035) were independent predictors of mortality. High pulmonary vascular resistance and right atrial pressure by invasive hemodynamic measurements were independent predictors of mortality (HR, 1.084; 95% confidence interval, 1.041–1.130, and 1.079, respectively; 95% confidence interval, 1.049–1.111; P<0.001 for both), whereas patients with a higher cardiac index had better survival overall (HR, 0.384; 95% confidence interval, 0.307–0.481; P<0.001). Conclusions—Right ventricular dysfunction, moderate–severe tricuspid regurgitation, low cardiac index, and raised right atrial pressure were associated with poor survival for both pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertensive disease patients. The severity of tricuspid regurgitation, myocardial performance index, presence of pericardial effusion, pulmonary vascular resistance, cardiac index, and right atrial pressure may be used to stratify risk of death.
Demand Response Management in Smart Grids With Heterogeneous Consumer Preferences

Consumer demand profiles and fluctuating renewable power generation are two main sources of uncertainty in matching demand and supply. This paper proposes a model of the electricity market that captures the uncertainties on both the operator and user sides. The system operator (SO) implements a temporal linear pricing strategy that depends on real-time demand and renewable generation in the considered period combining real-time pricing with time-of-use pricing. The announced pricing strategy sets up a noncooperative game of incomplete information among the users with heterogeneous, but correlated consumption preferences. An explicit characterization of the optimal user behavior using the Bayesian Nash equilibrium solution concept is derived. This explicit characterization allows the SO to derive pricing policies that influence demand to serve practical objectives, such as minimizing peak-to-average ratio or attaining a desired rate of return. Numerical experiments show that the pricing policies yield close to optimal welfare values while improving these practical objectives.
NK cells developing in vitro from fetal mouse progenitors express at least one member of the Ly49 family that is acquired in a time‐dependent and stochastic manner independently of CD94 and NKG2

NK cells developing in vitro from fetal progenitors in the presence of IL‐2 are phenotypically and functionally indistinguishable from mature adult NK cells, with the exception that they generally lack surface expression of any of the Ly49 molecules that have previously been examined. Using two recently developed anti‐Ly49 mAb, we show here that most of these NK cells in fact express high levels of at least one previously uncharacterized member of the Ly49 family, most likely Ly49E. Detailed kinetic and clonal analysis revealed that these Ly49 molecules were acquired in a progressive and stochastic manner independently of CD94 and NKG2. CD94 and NKG2 were both expressed early in NK cell development, sometimes in the absence of NK1.1, with CD94 invariably being expressed at two different levels. IL‐4 differentially inhibited the expression of CD94 and Ly49 receptors, but had little or no effect on the expression of NKRP1 molecules.
RINGOSTAR: an evolutionary AWG-based WDM upgrade of optical ring networks

The paper describes the study of the multichannel upgrade of IEEE Standard 802.17 Resilient Packet Ring (RPR) in particular and optical single-channel ring networks in general by making use of wavelength-division multiplexing (WDM). The paper describes and discusses a novel evolutionary multichannel upgrade approach that uses WDM on a central passive arrayed-waveguide grating (AWG)-based single-hop star network rather than on the ring. The AWG-based star subnetwork allows for a dramatically larger spatial reuse of WDM wavelength channels than conventional upgrades of optical single-channel ring networks that use WDM on the ring where all nodes need to be WDM upgraded. In the resultant hybrid optical ring-star network, termed RINGOSTAR, only a subset of the nodes are required to be WDM upgraded with a single additional tunable transceiver in order to improve the performance dramatically. The novel concept of proxy stripping is also introduced, which is used to route ring traffic on single-hop short cuts across the star subnetwork rather than the peripheral ring, resulting in a dramatically increased spatial reuse factor on the ring. By means of analysis, the performance of RINGOSTAR is investigated in terms of mean hop distance, spatial reuse, and capacity. The findings show that RINGOSTAR significantly outperforms unidirectional, bidirectional, and meshed WDM rings. Finally, the tradeoffs of RINGOSTAR are addressed.
A control scheme for automatic path tracking of vehicles subject to wheel slip constraint

We present a control scheme for automatic path tracking of a four-wheeled steering and four-wheeled drive (4WS4WD) vehicle subject to wheel slip constraint. The wheel slip, containing wheel slip ratio in longitudinal direction and slip angle in lateral direction, is a vector that serves as an index to avoid the tire-road friction saturation. Using linearization and singular perturbation theory, a linear and order-reduced design model is obtained, and the wheel slip is replaced by its quasi-steady state for the controller design. We propose a control structure of wheel torque and steering to transform the original tracking problem to a problem of state regulation subject to input constraint. A low-and-high gain technique is applied to construct the constrained controller and to enhance the utilization of the constrained wheel slip. Simulation shows that the new proposed control, scheme subject to wheel slip constraint coordinates well between wheel steering and wheel torque during tracking.
The Association between Sleep Duration and Non-Alcoholic Fatty Liver Disease among Japanese Men and Women

Objective: To examine the relationship between sleep duration and non-alcoholic fatty liver disease (NAFLD). Methods: We evaluated 3,968 subjects who underwent health check-ups from June 2012 to May 2013 at the Watari Hospital Health Center in Fukushima Prefecture in Japan. Fatty liver was detected by ultrasonography. Sleep duration and lifestyle factors were estimated using a questionnaire. Sleep duration was categorized into the following groups: ≤6, 6 to ≤7, >7 to ≤8, and >8 h. The four sleep duration groups were compared using the χ2 test and Kruskal-Wallis test. Results: In total, 2,172 subjects were enrolled. The overall prevalence of NAFLD was 29.6% (men, 38.0%; women, 25.3%). The proportion of NAFLD tended to decrease as sleep duration increased in men. The proportion with NAFLD was lowest in the group with a sleep duration of 6 to ≤7 h and highest in the groups with sleep durations of ≤6 and >8 h in women. The distribution showed a U-shaped curve. The age-adjusted odds ratio (OR) (95% confidence interval (CI)) for subjects with NAFLD with a sleep duration ≤6 h compared to the reference (6 to ≤7 h) was 1.44 (1.06-1.96) in women. Conclusion: Sleep shortage tends to be associated with NAFLD in women and may be mediated by body adiposity.
Robust Indoor Wireless Localization Using Sparse Recovery

With the multi-antenna design of WiFi interfaces, phased array has become a promising mechanism for accurateWiFi localization. State-of-the-art WiFi-based solutions using AoA (Angle-of-Arrival), however, face a number of critical challenges. First, their localization accuracy degrades dramatically when the Signal-to-Noise Ratio (SNR) becomes low. Second, they do not fully utilize coherent processing across all available domains. In this paper, we present ROArray, a Robust Array based system that accurately localizes a target even with low SNRs. In the spatial domain, ROArray can produce sharp AoA spectrums by parameterizing the steering vector based on a sparse grid. Then, to expand into the frequency domain, it jointly estimates the ToAs (Time-of-Arrival) and AoAs of all the paths using multi-subcarrier OFDM measurements. Furthermore, through multi-packet fusion, ROArray is enabled to perform coherent estimation across the spatial, frequency, and time domains. Such coherent processing not only increases the virtual aperture size, which enlarges the number of maximum resolvable paths, but also improves the system robustness to noise. Our implementation using off-the-shelf WiFi cards demonstrates that, with low SNRs, ROArray significantly outperforms state-of-the-art solutions in terms of localization accuracy; when medium or high SNRs are present, it achieves comparable accuracy.
The Damage Evolution Process of Orthotropic Notched Laminate of Fiber-Reinforced Composite

The damage evolution process of the single- or double-edge notched specimens sub jected to uniaxial tensile load is studied systematically by moire technique in this paper. A method for directly measuring the damaged region on the moire fringe pattern is proposed. Some relations between the mechanical parameters of the damage process are evaluated and analyzed. The strain distribution in the whole damage process in cluding onset, stable and unstable propagation of damage is discussed.
Molecular Mechanism for the Dual Alcohol Modulation of Cys-loop Receptors

Cys-loop receptors constitute a superfamily of pentameric ligand-gated ion channels (pLGICs), including receptors for acetylcholine, serotonin, glycine and γ-aminobutyric acid. Several bacterial homologues have been identified that are excellent models for understanding allosteric binding of alcohols and anesthetics in human Cys-loop receptors. Recently, we showed that a single point mutation on a prokaryotic homologue (GLIC) could transform it from a channel weakly potentiated by ethanol into a highly ethanol-sensitive channel. Here, we have employed molecular simulations to study ethanol binding to GLIC, and to elucidate the role of the ethanol-enhancing mutation in GLIC modulation. By performing 1-µs simulations with and without ethanol on wild-type and mutated GLIC, we observed spontaneous binding in both intra-subunit and inter-subunit transmembrane cavities. In contrast to the glycine receptor GlyR, in which we previously observed ethanol binding primarily in an inter-subunit cavity, ethanol primarily occupied an intra-subunit cavity in wild-type GLIC. However, the highly ethanol-sensitive GLIC mutation significantly enhanced ethanol binding in the inter-subunit cavity. These results demonstrate dramatic effects of the F(14′)A mutation on the distribution of ligands, and are consistent with a two-site model of pLGIC inhibition and potentiation.