Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of gut microbiomes and their metabolomes to the performance of Dorper and Tan sheep

Background Livestock is an excellent source of high nutritional value protein for humans; breeding livestock is focused on improving meat productivity and quality. Dorper sheep is a distinguished breed with an excellent growth performance, while Tan sheep is a Chinese local breed famous for its delicious meat. Several studies have demonstrated that the composition of gut microbiome and metabolome modulate host phenotype. Methods In the present study, we performed 16S amplicon sequencing and metabolomic analyses of the rumen and hindgut microbiome of 8-month-old Dorper and Tan sheep, raised under identical feeding and management conditions, to explore the potential effects of gut microbiome and its metabolites on growth performance and meat quality. Results Our study identified Lactobacillus, a marker genus in the rumen, to be significantly associated with the levels of fumaric acid, nicotinic acid, and 2-deoxyadenosine (P-value < 0.05). Statistical analysis showed that nicotinic acid was significantly negatively correlated with body weight (P-value < 0.01), while 2-deoxyadenosine was significantly positively correlated with fatty acids content (P-value < 0.05). There was a biologically significant negative correlation between Phascolarctobacterium and deoxycytidine levels in the hindgut. Deoxycytidine was significantly positively correlated with body weight, protein, and amino acid content. Differences in rumen fermentation patterns that are distinctive among breeds were identified. Tan sheep mainly used Lactobacillus and fumaric acid-mediated pyruvic acid for energy supply, while Dorper sheep utilize glycogenic amino acids. The difference of iron metabolism in the hindgut of Dorper sheep affects lipid production, while Phascolarctobacterium in Tan sheep is related to roughage tolerance. The accumulation of nucleosides promotes the growth performance of Dorper sheep. Conclusion These findings provide insights into how the microbiome-metabolome-dependent mechanisms contribute to growth rate and fat contents in different breeds. This fundamental research is vital to identifying the dominant traits of breeds, improving growth rate and meat quality, and establishing principles for precision feeding.
Conversion of phase noise to intensity noise in electromagnetically induced transparency

We report experimental study of laser phase noise to intensity noise conversion in electromagnetically induced transparency. In particular, we studied how various experimental parameters such as one and two-photon detunings and optical depth affect the intensity noise spectrum. Connection between the intensity noise level and the intensity cross correlation between the two EIT fields was also investigated.
Double prime focus camera for the F/1.14 Large Binocular Telescope

The large Binocular Telescope is currently in the pre- erection phase. The instrument has been already funded and its first-light is expected shortly after that of the LBT. Given the peculiarity of the telescope optics we designed tow prime focus cameras with two five-lens refractive correctors, optimized in the blue-side and red-side of the visible spectrum respectively. This independent coating. Detectors also reflect this choice, being optimized separately. We present the most relevant features of the instrument, the optical design as well as the structural and mechanical layout. Each of the two Prime Focus cameras gather light form a very fast, F/1.14 parabolic primary mirror. The field is corrected over roughly half a degree in size, allowing optical performances in terms of 80 percent of Encircled Energy in better than approximately 0.3 inch. Focal length is slightly increased in order to provide a better sampling using 13.5 micrometers pixel size chips. The CCD array is made up with 4 EEV 42-90 chips, per channel, to obtain an equivalent 6000 by 6000 pixels optimizing the AR coating to the U,B,V and V,R,I,Z bands respectively. The array will be read out in 10 seconds using a 1Meegapixel/second controller with four video channels. The cryostat will use a state of the art dewar to reach an holding time of several days using a limited amount of liquid nitrogen. The whole mechanical design has bene modeled using Finite Elements analysis in order to check for mechanical flexures of the mount tube and of the optical components by themselves. A brief overview of the informative facilities to be provided with the instrument and of a few science case studies that can be attacked by this instrument are also given.
On the operational predictability of blocking

The entire 7-year archive of ECMWF operational analysis and forecast data is used to assess the skill of the Centre's model in short- and medium-range forecasting of atmospheric blocking. The assessment covers 7100-day periods, from 1 December to 10 March of all winters from 1980-81 to 1986-87, inclusive. A slightly modified version of the Legenas and Okland objective zonal index is used to quantify both observed and forecast occurrence of blocking. The study is performed on 500 hPa geopotential height and on Euro-Atlantic and Pacific blocking separately. It is found that blocking frequency is severely underestimated in medium-range forecasts; the model is, on average, reasonably skilful if the initial conditions are blocked, but blocking onset is poorly represented if it occurs more than a few days into the forecast. This inability in entering the blocking regime has a substantial impact on the systematic error of the model. DOI: 10.1034/j.1600-0870.1990. t01-2-00003.x
Optical nanolithography using a scanning near-field probe with an integrated light source

An ultracompact near-field optical probe is described that is based on a single, integrated assembly consisting of a gallium nitride (GaN) light-emitting diode (LED), a microlens, and a cantilever assembly containing a hollow pyramidal probe with a subwavelength aperture at its apex. The LED emits ultraviolet light and may be used as a light source for near-field photolithographic exposure. Using this simple device compatible with many commercial atomic force microscope systems, it is possible to form nanostructures in photoresist with a resolution of 35 nm, corresponding to λ/10.
Observations of downslope winds and rotors in the Falkland Islands

A field campaign aimed at observing the near‐surface flow field across and downwind of a mountain range on the Falkland Islands, South Atlantic, is described. The objective was to understand and eventually predict orographically generated turbulence. The instrumentation was based primarily on an array of automatic weather stations (AWSs), which recorded 30 s mean surface pressure, wind speed and direction (at 2 m), temperature and relative humidity for approximately one year. These measurements were supported by twice‐daily radiosonde releases. The densest part of the AWS array was located to the south of the Wickham mountain range, across Mount Pleasant Airfield (MPA). In northerly flow the array provides a detailed study of the flow downwind of the mountain range. The dataset contains several episodes in which the flow downwind of the mountains is accelerated relative to the upwind flow. During some of these episodes short‐lived (typically ∼1 hour) periods of unsteady flow separation are observed and these are associated with the formation of rotors aloft. Such events present a significant hazard to aviation at MPA. Examination of radiosonde profiles suggests that the presence of a strong temperature inversion at a height similar to the mountain height is a necessary condition for both downwind acceleration and the formation of rotors. The data are used to show that the downwind fractional speed‐up is proportional to the non‐dimensional mountain height (based on upstream near‐surface winds and a depth‐averaged Brunt–Väisälä frequency diagnosed from radiosonde data). Similarly, a relationship is established between a quantity that describes the spatial variability of the flow downwind of the mountains and the upstream wind and depth‐averaged Brunt–Väisälä frequency. The dependence of the flow behaviour on the Froude number (defined in the usual way for two‐layer shallow‐water flow) and ratio of mountain height to inversion height is presented in terms of a flow regime diagram. © Royal Meteorological Society, 2005. S. B. Vosper's and P. F. Sheridan's contributions are Crown copyright
Gain-enhanced double-pass long-wavelength-band erbium-doped fiber amplifier using backward pumping

We propose and demonstrate a novel high-gain-efficiency long-wavelength band (L-band) erbium-doped fiber amplifier with a double-pass backward-pump configuration, in which the strong backward C-band amplified spontaneous emission is effectively utilized. The L-band gain is greatly enhanced in comparison with the copumped configuration. Without using any excessive components, the new configuration can provide the same gain as the conventional configuration, but only using 40% pump power. Meanwhile, the noise figure is also effectively improved under the low pump power.
Bayes factors for discrete observations from diffusion processes

SUMMARY We present an approach to model selection for a time series of data on a fine time scale. The underlying process generating the data is modelled as a continuous time stochastic process. The underlying continuous processes are assumed to be diffusions with time varying drift and diffusion coefficient. Several approaches to modelling the diffusion coefficient are described. To perform model selection, we propose an approximation to the Bayes factor that uses only the discrete data. We illustrate our approach for several well-known processes including: Brownian motion with drift, the Ornstein-Uhlenbeck process, a mean reversion process with drift, exponential Brownian motion, and a logistic growth model. Finally, we apply our technique to data from the Standard & Poor's 500 stock index by comparing a random walk to a mean reversion model.
Seasonal predictions of precipitation over Africa using coupled ocean-atmosphere general circulation models: skill of the ENSEMBLES project multimodel ensemble forecasts

ENSEMBLES stream 2 single-model and multimodel ensemble seasonal precipitation forecasts are evaluated over the African continent with respect to Global Precipitation Climatology Centre (GPCC) precipitation data for the 1960–2005 time period using deterministic and probabilistic skill scores. Focus is set on three regions of Africa during main precipitation seasons: West Africa during boreal summer, southern Africa during austral summer and the Greater Horn of Africa during the ‘long rains’ and ‘short rains’ transition seasons. The 45-member multimodel improves the ensemble spread-skill ratio over all regions, which translates into enhanced skill in terms of anomaly correlation and ranked probability skill scores for climatological precipitation deciles overWest Africa and southern Africa. Results are contrasted depending on the region and probabilistic formulations of the ensemble predictions after a quantile—quantile calibration give valuable information essentially over areas where deterministic skill is found. Probabilistic skill scores illustrate the range of possibilities formore user-related applications of ensemble seasonal forecasts.Asimple illustration using a cost-loss model shows that model potential economic values can reach over 10% depending on the regions and occurrences studied.
Subsystem Global Modal Parameterization for efficient simulation of flexible multibody systems

This paper presents a new model order reduction strategy for flexible multibody simulation, namely the Subsystem Global Modal Parameterization. The proposed method is based on a system‐level reduction technique, named Global Modal Parameterization, but offers significant improvements for systems with many independent DOFs. The approach splits up the motion of a mechanism or part of a mechanism into a relative motion, in which the members move relatively with respect to each other, and a global motion of the system, in which the relative position of the members does not change. The relative motion is described by a local Global Modal Parameterization model expressed in a mechanism‐attached frame, and the global motion is described by the motion of the mechanism‐attached frame. In order to improve simulation efficiency, mass invariants are used, which are also introduced in this paper. Two numerical examples are presented, which show the good accuracy and the major simulation efficiency improvements this new approach offers. Copyright © 2011 John Wiley & Sons, Ltd.
An Inverse to the Askey-Wilson Operator

We study properties of the kernel of a right inverse of the Askey-Wilson divided difference operator on L 2 weighted with the weight function of the continuous q-Jacobi polynomials. This operator is embedded in a one-parameter family of integral operators, denoted by D -t q whose kernel is related to the Poisson kernel. It is shown that as t → 1 - , the t-commutator (D q D -t q - tD -t q D q )f tends to the constant term in the orthogonal expansion of f in continuous q-Jacobi polynomials.
Frequency and temperature dependence of elastic moduli of polymers

The frequency and temperature dependence of the elastic moduli of a number of commercially available polymers has been studied in the temperature range of 0–35 °C and for frequencies 102–106 Hz. Away from transitions a significant new relationship has been obtained, i.e., the Young’s modulus of these polymers is proportional to log of frequency. Using this relationship, together with the low and high frequency data, transitions in some of the polymers were identified.
Characterization of diamond surface-channel metal-semiconductor field-effect transistor with device simulation

The DC operation of surface-channel metal-semiconductor field-effect transistors (MESFETs) using p-type conductive layers on hydrogen-terminated diamond surfaces is investigated by two-dimensional device simulation. As a result, a model to describe the surface semiconducting layer, in which acceptors are distributed two-dimensionally on the surface, is found to reproduce actual device characteristics well. Based on the model, the carrier (hole) concentration at a depth of 10 nm is determined to be three orders less than that at the surface. This thin channel realizes complete channel pinch-off and drain-current saturation with high transconductance, observed in the actual diamond surface-channel MESFETs. In the simulation, the transconductance of diamond surface-channel MESFETs with a self-aligned 1 µm gate exceeds 100 mS/mm. This result agrees well with a recent experimental result. The transconductance over 100 mS/mm can compete with that of Si metal-oxide-semiconductor field-effect transistors (MOSFETs) of the same gate length. The hydrogen-terminated diaomond surface is naturally equipped with the silicon-on-insulator-like (SOI-like) thin channel and shallow junction depth required for a nanoscale FET, such as one with a gate length of less than 50 nm.
A Class of Ratio Cum Product‐Type Estimator in Double Sampling

A class of ratio cum product-type estimator is proposed in case of double sampling in the present paper. Its bias and variance to the first order of approximation are obtained. For an appropriate weight ‘a’ and a good range of α-values, it is found that the proposed estimator is more efficient than the set of estimator viz., simple mean estimator, usual ratio and product estimators, SRIVASTAVA's estimator (1967), CHAKARBARTY's estimator and product-type estimator, which are in fact the particular cases of it. The proposed estimator is as efficient as linear regression estimator in double sampling at optimum value of α.
Edinburgh Explorer Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease

microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease', Cerebral Flow Abstract Cerebral small vessel disease (SVD) is a cause of stroke and dementia. Retinal capillary microvessels revealed by optical coherence tomography angiography (OCTA) are developmentally related to brain microvessels. We quantified retinal vessel density (VD) and branching complexity, investigating relationships with SVD lesions, white matter integrity on diffusion tensor imaging (DTI) and cerebrovascular reactivity (CVR) to CO 2 in patients with minor stroke. We enrolled 123 patients (mean age 68.1 (cid:1) SD 9.9 years), 115 contributed retinal data. Right (R) and left (L) eyes are reported. After adjusting for age, eye disease, diabetes, blood pressure and image quality, lower VD remained associated with higher mean diffusivity (MD) (standardized b ; R (cid:3) 0.16 [95%CI (cid:3) 0.32 to (cid:3) 0.01]) and lower CVR (L 0.17 [0.03 to 0.31] and R 0.19 [0.02 to 0.36]) in normal appearing white matter (NAWM). Sparser branching remained associated with sub-visible white matter damage shown by higher MD (R (cid:3) 0.24 [ (cid:3) 0.08 to (cid:3) 0.40]), lower fractional anisotropy (FA) (L 0.17 [0.01 to 0.33]), and lower CVR (R 0.20 [0.02 to 0.38]) in NAWM. OCTA-derived metrics provide evidence of microvessel abnormalities that may underpin SVD lesions in the brain.
On the zeros of Epstein's zeta function

Let Q ( x, y ) = ax 2 + bxy + cy 2 be a positive definite quadratic form with discriminant d = b 2 – 4 ac . The Epstein zeta function associated with Q is given by where Σ′ means the sum is over all pairs ( x, y ) of integers not both zero, and as usual, s = σ + it .
Beyond Strategy and Design: Gaining a Competitive Advantage in an Uncertain World

Leadership is facing a time of significant challenge and complexity. Numerous sociological and technological advances are driving the complexity, making it necessary for leaders to discover solutions to meet new challenges. There is no serious question on the need for organizational strategy and design alignment. Numerous studies have demonstrated that successful organizations align their strategy and design with their unique operational environment. Although, while alignment is essential, especially during turbulent times, it is not sufficient. This article considers what leaders might do to gain a competitive advantage in an uncertain world. This author's premise based on research: Focus on individual and organizational virtues and character. When organizations solely focus on behaviors, they fail to account for habits that can both contribute to or against organizational success. Today's world is too chaotic not to deepen understanding of how people think, act, and feel. The addition of character and virtues holds the key to unlocking productivity, creativity, and competitive advantage. Moving beyond behaviors and focusing on the development of leadership virtues and character improves performance and provides a competitive advantage.
Well-posedness and blow-up for a modified two-component Camassa–Holm equation

In this article, we consider a newly modified two-component Camassa–Holm equation. First, we establish the local well-posedness result, then we present a precise blow-up scenario. Afterwards, we derive a new conservation law, by which and the precise blow-up scenario we prove three blow-up results and a blow-up rate estimate result.
A GWAS Finds Variants at 2p21 Associated with Self-Reported Sensitive Skin in the Han Chinese Population

ACKNOWLEDGMENTS The study was supported by the Independent Research Fund Denmark (DFF Sapere Aude grant number 4004-00422) and the European Research Council, European Union (StG 677268 NextDART). The study is partly funded through the National Institutes of Health, United States/National Cancer Institute Cancer Center Support Grants P30 CA015704 and P01 CA225517. We would like to thank all patients with cancer who contributed samples; all collaborators taking part in the study; Bente Rotbøl, Tripti Tamhane, Anna Gyllenberg Burkal, Anni Flarup Løye, and Julien Candrian for excellent technical assistance; and all current and former members of the SRH research group for scientific discussions.
Olley–Pakes productivity decomposition: computation and inference

We show how a moment‐based estimation procedure can be used to compute point estimates and standard errors for the two components of the widely used Olley–Pakes decomposition of aggregate (weighted average) productivity. When applied to business level microdata, the procedure allows for autocovariance and heteroscedasticity robust inference and hypothesis testing about, for example, the coevolution of the productivity components in different groups of firms. We provide an application to Finnish firm level data and find that formal statistical inference casts doubt on the conclusions that one might draw on the basis of a visual inspection of the components of the decomposition.
An Efficient One-Class SVM for Novelty Detection in IoT

One-Class Support Vector Machines (OCSVMs) are a set of common approaches for novelty detection due to their flexibility in fitting complex nonlinear boundaries between normal and novel data. Novelty detection is important in the Internet of Things (“IoT”) due to the potential threats that IoT devices can present, and OCSVMs often perform well in these environments due to the variety of devices, traffic patterns, and anomalies that IoT devices present. Unfortunately, conventional OCSVMs can introduce prohibitive memory and computational overhead in detection. This work designs, implements, and evaluates an efficient OCSVM for such practical settings. We extend Nyström and (Gaussian) Sketching approaches to OCSVM, combining these methods with clustering and Gaussian mixture models to achieve 15-30x speedup in prediction time and 30-40x reduction in memory requirements without sacrificing detection accuracy. Here, the very nature of IoT devices is crucial: they tend to admit few modes of normal operation, allowing for efficient pattern compression.
Bioacoustic Classification Framework: Spectral and Cepstral Based Approaches.

The field of bioacoustics plays an important role on preventing and reducing human impact on environment, by enabling the development of tools capable of performing automated analysis of environmental data. Deep learning methods were successful on automating the process of species identification in environmental recordings, requiring nonetheless a large number of training samples per species. Hence, efforts were made to develop high-accuracy methods capable of automating species detection in noisy environments with limited training data. In this document, we address the problem of automating species detection in noisy environments with limited training data, proposing an end-to-end spectral based approach for training a convolutional neural network (CNN) on Mel spectrograms to predict a set of species present in the Rainforest Connection’s acoustic recordings. Additionally, we propose a cepstral based framework for training a Long Short-Term Memory (LSTM) network on the Mel-frequency cepstral coefficients (MFCCs), complementing this approach with the motifs extracted by the matrix profile algorithm. Finally, we evaluate the performance of the approaches so that the bioacoustic classification framework can be established.