Miracle-dz/UniFAR-FTUs huggingface dataset:
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?

Bayesian optimisation presents a sample-efficient methodology for global optimisation. Within this framework, a crucial performance-determining subroutine is the maximisation of the acquisition function, a task complicated by the fact that acquisition functions tend to be non-convex and thus nontrivial to optimise. In this paper, we undertake a comprehensive empirical study of approaches to maximise the acquisition function. Additionally, by deriving novel, yet mathematically equivalent, compositional forms for popular acquisition functions, we recast the maximisation task as a compositional optimisation problem, allowing us to benefit from the extensive literature in this field. We highlight the empirical advantages of the compositional approach to acquisition function maximisation across 3958 individual experiments comprising synthetic optimisation tasks as well as tasks from the 2020 NeurIPS competition on Black-Box Optimisation for Machine Learning. Given the generality of the acquisition function maximisation subroutine, we posit that the adoption of compositional optimisers has the potential to yield performance improvements across all domains in which Bayesian optimisation is currently being applied.
Worldvolume approach to the tempered Lefschetz thimble method

As a solution towards the numerical sign problem, we propose a novel hybrid Monte Carlo algorithm, in which molecular dynamics is performed on a continuum set of integration surfaces foliated by the antiholomorphic gradient flow (“the worldvolume of an integration surface”). This is an extension of the tempered Lefschetz thimble method (TLTM) and solves the sign and multimodal problems simultaneously, as the original TLTM does. Furthermore, in this new algorithm, one no longer needs to compute the Jacobian of the gradient flow in generating a configuration, and only needs to evaluate its phase upon measurement. To demonstrate that this algorithm works correctly, we apply the algorithm to a chiral random matrix model, for which the complex Langevin method is known not to work.
Generation of complex database queries and API calls from natural language utterances

Generating queries corresponding to natural language questions is a long standing problem. Traditional methods lack language flexibility, while newer sequence-to-sequence models require large amount of data. Schema-agnostic sequence-to-sequence models can be fine-tuned for a specific schema using a small dataset but these models have relatively low accuracy. We present a method that transforms the query generation problem into an intent classification and slot filling problem. This method can work using small datasets. For questions similar to the ones in the training dataset, it produces complex queries with high accuracy. For other questions, it can use a template-based approach or predict query pieces to construct the queries, still at a higher accuracy than sequence-to-sequence models. On a real-world dataset, a schema fine-tuned state-of-the-art generative model had 60\% exact match accuracy for the query generation task, while our method resulted in 92\% exact match accuracy.
Spectral Methods for Data Science: A Statistical Perspective

Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues (resp. singular values) and eigenvectors (resp. singular vectors) of some properly designed matrices constructed from data. A diverse array of applications have been found in machine learning, data science, and signal processing. Due to their simplicity and effectiveness, spectral methods are not only used as a stand-alone estimator, but also frequently employed to initialize other more sophisticated algorithms to improve performance. While the studies of spectral methods can be traced back to classical matrix perturbation theory and methods of moments, the past decade has witnessed tremendous theoretical advances in demystifying their efficacy through the lens of statistical modeling, with the aid of non-asymptotic random matrix theory. This monograph aims to present a systematic, comprehensive, yet accessible introduction to spectral methods from a modern statistical perspective, highlighting their algorithmic implications in diverse large-scale applications. In particular, our exposition gravitates around several central questions that span various applications: how to characterize the sample efficiency of spectral methods in reaching a target level of statistical accuracy, and how to assess their stability in the face of random noise, missing data, and adversarial corruptions? In addition to conventional $\ell_2$ perturbation analysis, we present a systematic $\ell_{\infty}$ and $\ell_{2,\infty}$ perturbation theory for eigenspace and singular subspaces, which has only recently become available owing to a powerful "leave-one-out" analysis framework.
A Guide to Realistic Uncertainties on the Fundamental Properties of Solar-type Exoplanet Host Stars

Our understanding of the properties and demographics of exoplanets critically relies on our ability to determine the fundamental properties of their host stars. The advent of Gaia and large spectroscopic surveys has now made it possible, in principle, to infer the properties of individual stars, including most exoplanet hosts, to very high precision. However, we show that, in practice, such analyses are limited by uncertainties in both the fundamental scale and our models of stellar evolution, even for stars similar to the Sun. For example, we show that current uncertainties on measured interferometric angular diameters and bolometric fluxes set a systematic uncertainty floor of ≈2.4% in temperature, ≈2.0% in luminosity, and ≈4.2% in radius. Comparisons between widely available model grids suggest uncertainties of order ≈5% in mass and ≈20% in age for main-sequence and subgiant stars. While the radius uncertainties are roughly constant over this range of stars, the model-dependent uncertainties are a complex function of luminosity, temperature, and metallicity. We provide open-source software for approximating these uncertainties for individual targets and discuss strategies for reducing these uncertainties in the future.
Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization

Accurate vertebra localization and identification are required in many clinical applications of spine disorder diagnosis and surgery planning. However, significant challenges are posed in this task by highly varying pathologies (such as vertebral compression fracture, scoliosis, and vertebral fixation) and imaging conditions (such as limited field of view and metal streak artifacts). This paper proposes a robust and accurate method that effectively exploits the anatomical knowledge of the spine to facilitate vertebra localization and identification. A key point localization model is trained to produce activation maps of vertebra centers. They are then re-sampled along the spine centerline to produce spine-rectified activation maps, which are further aggregated into 1-D activation signals. Following this, an anatomically-constrained optimization module is introduced to jointly search for the optimal vertebra centers under a soft constraint that regulates the distance between vertebrae and a hard constraint on the consecutive vertebra indices. When being evaluated on a major public benchmark of 302 highly pathological CT images, the proposed method reports the state of the art identification (id.) rate of 97.4%, and outperforms the best competing method of 94.7% id. rate by reducing the relative id. error rate by half.
Upper limb robotic assessment: Pilot study comparing velocity dependent resistance in individuals with acquired brain injury to healthy controls

Introduction Assessment of velocity dependent resistance (VDR) can provide insights into spasticity in individuals with upper motor neuron syndrome. This study investigates the relationship between Modified Ashworth scores and a biomechanical based representation of VDR using a rehabilitation robot. Comparisons in VDR are made for the upper limb (UL) between individuals with acquired brain injury and healthy controls for the para-sagittal plane. Methods The system manipulates the individual’s limb through five flexion and extension motions at increasing speeds to obtain force profiles at different velocities. An approximation of VDR is calculated and analyzed statistically against clinical scales and tested for interactions. Results All individuals (aged 18–65), including healthy controls exhibited VDR greater than 0 (P < 0.05). MAS scores were found to be related to VDR (P < 0.05) with an interaction found between MAS Bicep and Tricep scores (P < 0.01). Considering this interaction, evidence of differences in VDR were found between several neighboring assessment score combinations. Conclusion The robot can detect and quantify VDR that captures information relevant to UL spasticity. Results suggests a better categorization of VDR is possible and supports further development of rehabilitation robotics for assisting spasticity assessment.
Rumen fermentation, methane production, and microbial composition following in vitro evaluation of red ginseng byproduct as a protein source

Abstract The main objective of this in vitro study was to evaluate red ginseng byproduct (RGP) as a protein resource and its effects on rumen fermentation characteristics, microflora, CO2, and CH4 production in ruminants. Four treatments for in vitro fermentation using buffered rumen fluid over a 48 h incubation period were used: 1, RGP; 2, corn gluten feed (CGF); 3, wheat gluten (WG); and 4, corn germ meal. In vitro dry matter digestibility (IVDMD), in vitro neutral detergent fiber digestibility (IVNDFD), in vitro crude protein digestibility (IVCPD), volatile fatty acids, pH, and ammonia nitrogen (NH3-N) were estimated after 48 h incubation. Gas production was investigated after 3, 6, 12, 24, 36 and 48 h. The CO2 and CH4 were evaluated after 12, 24, 36, and 48 h. A significant difference in total gas production and CO2 emissions was observed (p < 0.01) at all incubation times. CH4 production in RGP were higher (p < 0.05) than that in other treatments but a higher CH4 portion in the total gas production was observed in WG (p < 0.05) at 48 h incubation. The IVDMD, IVNDFD, and IVCPD of RGP was lower than those of other conventional ingredients (p < 0.01). The RGP had the lowest NH3-N value among the treatments (p < 0.01). The RGP also had the lowest total VFA concentration (p < 0.01), but presented the highest acetate proportion and acetate to propionate ratio among the treatments (both, p < 0.01). The abundance of Prevotella ruminicola was higher in RGP than in WG (p < 0.01), whereas RGP has lower methanogenic archaea (p < 0.01). In conclusion, based on the nutritive value, IVDMD, low NH3-N, and decreased methanogenic archaea, RGP inclusion as a protein source in ruminant diets can be an option in replacing conventional feed sources.
Use of Microbial β-Lactamase to Destroy Penicillin Added to Milk

Abstract A simple method is described for destruction of penicillin residues in bulk milk to an undetectable amount (less than .003 U/ml) with commercially available crude β -lactamase enzyme. Milk containing . 1 or . 5 U/ml penicillin G was treated with . 01 to 1.0 mU/ml of β -lactamase ( Bacillus cereus ) for up to 96h. The Bacillus stearotbermophilus var. calidolactis assay was used to quantify penicillin in milk between . 003 to 1.0 U/ml. The . 5 U/ml of penicillin G was reduced to an undetectable amount within 18h at 4°C by 1.0 mU/ml of β -lactamase. The development of titratable acidity over 5 to 6h in contaminated milks treated with β -lactamase and inoculated with Streptococcus tbermophilus GH, Streptococcus cremoris , Streptococcus lactis , or a commercial starter culture was the same as for control milk samples containing no additives or only enzyme. Pilot-scale manufacture of Swiss and Cheddar cheeses from contaminated milks treated with β -lactamase yielded cheeses of comparable quality, to control cheeses produced from penicillin-free milk. There were no delays in acid production as judged from pH measurements during production and ripening of the cheeses. About 50% of β -lactamase activity added to milk remained after pasteurization at 63°C for 30min. The safety for human consumption of cheese containing small quantities of penicillin degradation products from milk treated with β -lactamase remains to be established.
Association of Low Leptin with Poor 3-Month Prognosis in Ischemic Stroke Patients with Type 2 Diabetes

Background Leptin, an adipokine, has effects on the cardiovascular system with both protective and harmful role. This study aimed to assess the relationship between leptin and 3-month prognosis in ischemic stroke patients with type 2 diabetes. Patients and Methods As a prospective single-center observational study, we collected consecutive first-ever acute ischemia stroke with type 2 diabetes mellitus from February 2019 to February 2020. Serum samples were obtained at admission, and leptin serum levels were tested by the ELISA method. Logistic regression models were used to assess leptin’s prognostic value to predict the functional outcome and mortality within three months. Results Finally, two hundred and eleven patients were included, and the mean leptin serum level was 16.8 (SD. 6.9) ng/mL. At admission, 53.6% of those included patients (N=113) were defined as severe stroke (NIH Stroke Scale [NIHSS]>5). In multivariable models adjusted for other factors, leptin levels<11.6ng/mL (lowest quartile, Q1) related to severe stroke and the risk increased 175% (odds ratios [OR] =2.75; 95% confidence interval [CI]=2.13–3.38; P=0.002). Serum leptin levels on admission in patients with poor outcomes and nonsurvivors were significantly reduced (P<0.001 and P<0.001). Leptin levels <11.6ng/mL (lowest quartile, Q1) related to a higher risk of poor functional impairment (OR=5.13; 95% CI =3.25–6.86; P<0.001) and mortality (OR=3.19; 95% CI =2.03–4.25; P<0.001). Conclusion The data shows that leptin serum level is a useful prognostic biomarker in ischemic stroke patients with type 2 diabetes, and this relationship is negative.
Modified predictive formula for the electron stopping power

We report an improved predictive formula for the electron stopping power (SP) based on an analysis and fit of SPs and electron inelastic mean free paths (IMFPs) calculated from optical data for 37 elemental solids and energies between 200eV and 30keV. The formula is a function of energy, density, and IMFP, and is recommended for solids with atomic numbers larger than 6. While the mean deviation between predicted and calculated SPs was 7.25%, larger deviations were found for four additional materials, Li (22.2%), Be (17.9%), graphite (15.3%), and diamond (15.7%). The predictive SP formula can be applied to multicomponent materials. Test comparisons for two compounds, guanine and InSb, showed average deviations of 16.0% and 19.1%, respectively. The improved SP formula is expected to be useful in simulations of electron trajectories in solids with the continuous slowing-down approximation (e.g., in Auger-electron spectroscopy and electron microprobe analysis).
Improving behavior characteristics and stress indices of gestating sows housed with group housing facility

Abstract This study was conducted to investigate the effects of group-housing facility (GHF), compared to an individual confinement stall (CON), on the reproductive performance, behavior, and stress hormones of gestating sows. A total of 50 primiparous sows (Landrace × Yorkshire) were randomly allocated into either CON (n = 25) or GHF (n = 25) during the gestation period. One week before parturition, the sows were transferred into conventional farrowing crates, and cross-fostering was conducted within 1 d of delivery. Blood was collected for analyses of stress indices at 75 d of gestation and postpartum. Reproductive performance was estimated during the period of birth to weaning. Behavior patterns were identified at 90 d of gestation. Litter size was not different between the CON and GHF treatments. Weaning to estrus interval, however, tended to be lower in the GHF than in the CON (p < 0.1). Activity, treating, belly nosing, and exploring behaviors were observed only in the GHF group, whereas rubbing was shown only with the CON. Serum cortisol concentration was lower in the GHF than in the CON at 75 d of gestation (p < 0.05). Sows housed in the GHF showed lower epinephrine and norepinephrine concentrations than those housed in the CON at postpartum (p < 0.05). The GHF sows demonstrated more natural behavior characteristics associated with stress relief than the CON sows with no adverse effects on reproductive performance. Therefore, these results suggest that GHF could be applied as an alternative housing facility to improve animal welfare on swine farms.
Luzhong mutton sheep: inbreeding and selection signatures

Abstract Intense artificial selection has been imposed to Luzhong mutton sheep population in the past years. Improvements on growth and reproductive performance are two breeding goals in the present herd. Although some progresses were phenotypically observed possibly due to inbreeding induced by strong selection in terms of these traits, the genomic evaluation was poorly understood. Therefore, a high-density SNP array was used to characterize the pattern of runs of homozygosity (ROH), estimate inbreeding and inbreeding depressions on early growth performance and litter size based upon ROH, and scan positive selection signatures of recent population. Consequently, a low inbreeding level was observed which had negative effects on litter size, but not on early growth performance. And 160 genes were under selection, of which some were reported to be linked to several traits of sheep including body weight, litter size, carcass and meat quality, milk yield and composition, fiber quality and health, and the top genes were associated with growth (growth hormone [GH]- growth hormone receptor [GHR]- Insulin-like growth factor 1 [IGF1] axis) and litter size (bone morphogenic proteins [BMPs]-associated). The effectiveness of previous breeding measures was highlighted, but purging selection was proposed to alleviate the inbreeding depression on litter size, providing some genomic insights to breeding management of Luzhong mutton sheep.
Circulating miRNA Signatures Associated with Insulin Resistance in Adolescents with Obesity

Purpose MicroRNAs (miRNAs) are implicated in metabolic changes accompanying progression of obesity, insulin resistance (IR), and metabolic disorders in children. Identifying circulating miRNAs that uniquely associate with these disorders may be useful in early identification and prevention of obesity-related complications. We aimed to identify circulating miRNA signatures that distinguish adolescents with obesity and IR from those with obesity unaccompanied by IR. Methods Adolescents (aged 10–17 years) with obesity were recruited from a weight management clinic. Fasting serum samples were obtained from 33 participants. A total of 179 miRNAs were queried by a quantitative RT-PCR-based miRNA focus panel. Differentially expressed miRNAs were compared between groups using Student’s t-test or one-way ANOVA analysis, and the association between IR evaluated by homeostatic model assessment model (HOMA-IR > 4) and body mass index (BMI) status was assessed using Pearson’s correlation analysis. Results We found an expression pattern consisting of 12 elevated miRNAs linked to IR in obese adolescents. miR-30d, -221, and -122 were significantly correlated with clinical and biochemical markers of obesity and IR, suggestive of IR in adolescents at risk. Conclusion Specific signatures of circulating miRNAs reflected metabolic phenotypes and predicted the presence of IR in adolescents with obesity, suggesting that miRNA indicators may identify obesity-associated complications in childhood. Further studies will be needed to understand cause versus effect and the mechanisms by which IR status links to changes in blood miRNA profiles.
Towards Measuring Place Function Similarity at Fine Spatial Granularity with Trajectory Embedding.

Modeling place functions from a computational perspective is a prevalent research topic. Trajectory embedding, as a neural-network-backed dimension reduction technology, allows the possibility to put places with similar social functions at close locations in the embedding space if the places share similar chronological context as part of a trajectory. The embedding similarity was previously proposed as a new metric for measuring the similarity of place functions. This study explores if this approach is meaningful for geographical units at a much smaller geographical granularity compared to previous studies. In addition, this study investigates if the geographical distance can influence the embedding similarity. The empirical evaluations based on a big vehicle trajectory data set confirm that the embedding similarity can be a metric proxy for place functions. However, the results also show that the embedding similarity is still bounded by the distance at the local scale.
Fibrous gels modelled as fluid-filled continua with double-well energy landscape

Several biological materials are fibre networks infused with fluid, often referred to as fibrous gels. An important feature of these gels is that the fibres buckle under compression, causing a densification of the network that is accompanied by a reduction in volume and release of fluid. Displacement-controlled compression of fibrous gels has shown that the network can exist in a rarefied and a densified state over a range of stresses. Continuum chemo-elastic theories can be used to model the mechanical behaviour of these gels, but they suffer from the drawback that the stored energy function of the underlying network is based on neo-Hookean elasticity, which cannot account for the existence of multiple phases. Here we use a double-well stored energy function in a chemo-elastic model of gels to capture the existence of two phases of the network. We model cyclic compression/decompression experiments on fibrous gels and show that they exhibit propagating interfaces and hysteretic stress–strain curves that have been observed in experiments. We can capture features in the rate-dependent response of these fibrous gels without recourse to finite-element calculations. We also perform experiments to show that certain features in the stress–strain curves of fibrous gels predicted by our model can be found in the compression response of blood clots. Our methods may be extended to other tissues and synthetic gels that have a fibrous structure.