Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Uncertainty Quantification via Convex Optimization and Relaxation

Many engineering applications face the problem of bounding the expected value of a quantity of interest (performance, risk, cost, etc.) that depends on stochastic uncertainties whose probability distribution is not known exactly. Optimal uncertainty quantification (OUQ) is a framework that aims at obtaining the best bound in these situations by explicitly incorporating available information about the distribution. Unfortunately, this often leads to non-convex optimization problems that are numerically expensive to solve. This thesis emphasizes on efficient numerical algorithms for OUQ problems. It begins by investigating several classes of OUQ problems that can be reformulated as convex optimization problems. Conditions on the objective function and information constraints under which a convex formulation exists are presented. Since the size of the optimization problem can become quite large, solutions for scaling up are also discussed. Finally, the capability of analyzing a practical system through such convex formulations is demonstrated by a numerical example of energy storage placement in power grids. When an equivalent convex formulation is unavailable, it is possible to find a convex problem that provides a meaningful bound for the original problem, also known as a convex relaxation. As an example, the thesis investigates the setting used in Hoeffding's inequality. The naive formulation requires solving a collection of non-convex polynomial optimization problems whose number grows doubly exponentially. After structures such as symmetry are exploited, it is shown that both the number and the size of the polynomial optimization problems can be reduced significantly. Each polynomial optimization problem is then bounded by its convex relaxation using sums-of-squares. These bounds are found to be tight in all the numerical examples tested in the thesis and are significantly better than Hoeffding's bounds.
The relational dynamics of racialised policing: community policing for counterterrorism, suspect communities, and Muslim Americans’ provisional belonging

ABSTRACT For over two decades, policies for countering violent extremism have enacted racial logics to target Muslim communities as suspect communities. While much research in this vein examines either the enactment of counterterrorism policies or Muslim communities’ responses, less is known about how racialised policies are experienced through relational dynamics between these two entities: police who implement counterterrorism policies and their targets – Muslim communities. Bridging critical citizenship, socio-legal, and migration studies, this article conceptualises how racialised policies shape the relationship between agents of the state and suspect communities. With unique analytic leverage from semi-structured interviews with law enforcement and focus groups with Muslim communities, findings show that police consistently deploy racial logics of CVE to distinguish between ‘good’ and ‘bad’ Muslims, rewarding the former with resources and protection and punishing the latter with surveillance and criminalisation. In turn, these definitions inhibit Muslim Americans’ religious and cultural freedom, political expression and collective action, and legitimize their racial profiling and surveillance. Tradeoffs to provisional inclusion mean not only accepting racial logics but also reproducing them within their own communities. This article expands our understanding of how the meanings of belonging are continually negotiated between the state and racialised communities.
Effect of Cement Type and Water-to-Cement Ratio on Fresh Properties of Superabsorbent Polymer-Modified Cement Paste

Superabsorbent polymer (SAP) is a material with the ability to absorb liquid and desorb liquid from and to the environment, and it can ensure the internal curing of cementitious composites. Although the fresh state properties of SAP-modified mixtures (SAPCP) are affected and have been investigated nowadays, the rheological properties of SAPCP are still a virgin field and they are worth studying. Hence, the current study was aimed and conducted to observe what occurred if cements with different chemical compositions, various ratios of water/cement (w/c) and SAP were used together. Accordingly, CEM I 42.5R, CEM II/A-LL 42.5R and CEM IV/B (P) 32.5R were selected as binders in the mixtures, and w/c ratios were 0.40 and 0.50 for SAPCPs. In total, 24 mixtures were designed, produced and tested in the laboratory and spreading table tests, Vicate tests, viscosity tests and shear tests were conducted on the fresh state of the mixtures to observe the fresh behavior of SAPCPs. As a result, it was determined that the SAP, cement and w/c combinations considered in the article were effective on SAPCP fresh properties and rheology. However, it was determined that the use of high amounts of SAP in the mixture, high cement fineness and high oxide ratios in the cement (ratios of silicon dioxide/calcium oxide and aluminum oxide/calcium oxide) negatively affected not only the fresh state properties, but also the rheology. Moreover, the coexistence of the aforementioned negative conditions was the most unfavorable situation: high SAP ratio + high cement fineness + high oxide ratio in SAPCP. For these reasons, it was concluded that cement fineness and chemical composition should be taken into account in the rheology/workability-based design of SAPCPs. Then, the SAP content can be regulated for design purposes.
Shock propagation in the outer heliosphere: 1. Pickup ions and gasdynamics

Pickup ions are expected to play a fundamental role in determining the global structure of the heliosphere since they dominate the internal energy of the outer solar wind beyond the ionization cavity. The dynamical effect of pickup ions on the propagation characteristics of interplanetary shocks is addressed here. It is found that (1) forward and reverse shocks in a heliosphere mediated by pickup ions have higher speeds than expected of shocks in an adiabatic solar wind without pickup ions; (2) identical initial conditions evolve differently in a pickup ion mediated heliosphere compared to an adiabatic heliosphere, producing more complicated velocity, density and temperature structure, and often with multiple forward-reverse shock pairs; (3) pickup ions act to weaken and dissipate shocks in the outer heliosphere although the velocity jumps can remain large; (4) density fluctuations in the outer pickup ion mediated heliosphere do not correlate with velocity fluctuations as well as they do in the inner heliosphere, and (5) the amplitudes of density fluctuations in a pickup ion mediated heliosphere are considerably smaller than those found in an adiabatic heliosphere without pickup ions.
Optimization System of University Public Sports Training Data Management Based on Intelligent Optimization Algorithm

Since many colleges and universities have always used the traditional manual filling and paper saving method to manage various information materials of training data, this brings many problems to daily management, such as data loss and difficulty in data. Find and work inefficient. In order to solve these problems, this paper intends to establish a management system for public sports training data, and hand over the complicated data management work to the system, which can not only reduce the workload of data management personnel, but also improve management efficiency and avoid data data loss, etc. In the design process, this paper uses the PAX page layout to design the system structure, and then introduces the particle swarm optimization algorithm in the intelligent optimization algorithm to optimize the performance of the system and make the data processing function of the system more perfect. This paper mainly aims at students' training performance data management, constructs training performance data table, and analyzes the realization process of training training performance data management. It is hoped that the promotion of this system to the management of public sports training data in colleges and universities can effectively improve the management efficiency.
The Impact of Laser Beam Power on the Microstructure and Some Mechanical Properties of Laser-Alloyed Inconel®600 with WC Particles

Laser surface alloying with WC particles was used in order to improve the wear resistance of Inconel®600-alloy. The applied processing parameters ensured appropriate conditions for the production of composite layers enriched with WC particles that did not melt during the process. As a consequence, the produced layers contained globular shaped WC particles that were well bonded in the matrix. The WC particles were characterized by high hardness HIT = 31.25 GPa and a high Young’s modulus EIT = 609.33 GPa determined by nanoindentation. The most important parameter influencing the thickness of the layer, the percentage of WC particles in the layer and the wear resistance of the produced layers was the power of the laser beam. Three values of laser beam power were used: 1.3 kW, 1.56 kW, and 1.82 kW. An increase in the laser beam power resulted in an increased thickness of the layer from 435 µm to 685 µm. Simultaneously, when the power of the laser beam was higher, the depth of re-melting of the substrate material increased. This was the reason for a decrease in the percentage of WC particles in the composite layer. The layer produced by laser beam power of 1.3 kW contained 20.59% of WC particles, whereas the highest power of the laser beam (1.82 kW) ensured a percentage of WC particles of about 9.46%. As a result, the increase in the laser beam power was the reason for the reduction in the wear resistance of the composite layer. The lowest mass wear intensity factor (Imw = 6.4 mg·cm−2·h−1) characterized the layer produced at laser beam power of 1.3 kW, and the highest Imw (18.5 mg·cm−2·h−1) was obtained for the layer produced with a laser beam power of 1.82 kW. However, all the produced composite layers contained WC particles, which ensured improved wear resistance when compared to the Inconel®600-alloy without the layer (Imw = 60.9 mg·cm−2·h−1).
Representation of Fully Three‐Dimensional Interfacial Curvature in Pore‐Network Models

Quasi two‐dimensional approximations of interfacial curvature, present in current network models of multiphase flow in porous media, are extended to three dimensions. The new expressions for threshold capillary pressure are validated and calibrated using high‐resolution direct numerical simulations on synthetic geometries. The effects of pore‐space expansion and sagittal interface curvature on displacement are quantified, and are shown to be a key step in improving the physical accuracy of network models. Finally, the calibrated network model is used to obtain predictions for relative permeability and capillary pressure in a water‐wet Bentheimer sandstone. The predictions are compared to experimental measurements, revealing that the inclusion of three‐dimensional interfacial curvature leads to more accurate predictions.
Staging Systems and Nomograms for Soft Tissue Sarcoma

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new “dynamic” nomograms and prognostic tools have been developed, allowing doctors to “recalculate” a patient’s prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.
FSFP: Transfer Learning From Long Texts to the Short

Transfer learning is a method that studies how to identify the useful knowledge and skills in the previous tasks, and uses them to the new tasks or domains. At present, the research on transfer learning mostly focuses on the field of long texts. However, the source data should be given for the transportation from long texts to the sh ort ones, and the priori probability distribution of the data should be given at the same time. In order to solve the problems, the algorithm which is called FSFP (Free Source selection Free Priori probability distribution) is proposed. It can transfer knowledge from the long texts to the short ones. Latent semantic analysis is used to extract the key words as seed characteristic sets, which are semantically related to the long texts from the target domain. And then the graph structure of online information is built. With the help of the improved Laplacian Eigenmaps, the feature representations of high- dimensional data are mapped to a low-dimensional space. Lastly, the target data are classified in the constraint of minimizing the mutual information between the instance and the feature representation. The experimental results on large data sets show the effectiveness of the new algorithm.
The Iwex spectrum

We describe the analysis of current and temperature cross spectra from the trimoored internal wave experiment Iwex and present a spectral model for the fluctuations in the internal wave range. The model consists of internal waves contaminated by temperature and current fine structure and by current noise. Except for the inertial and tidal frequencies the distribution of wave energy is vertically symmetric and horizontally isotropic. The wave number spectrum is characterized by a bandwidth of about 20–10 equivalent modes (decreasing with frequency), by a power law at high wave numbers, and by a sharp peak at low wave numbers. The general features of this spectrum agree fairly well with the one proposed by Garrett and Munk (1975). The contaminations increase with frequency. Contamination by temperature fine structure is confirmed by independent measurements. The Iwex spectral model provides a consistent description of all observed cross spectra.
Deep optically thin cirrus clouds in the polar regions. I - Infrared extinction characteristics

Abstract The spectral data obtained by the Infrared Interferometer Spectrometer (IRIS) flown on Nimbus 4 satellite in 1970 indicated the existence of optically thin ice clouds in the upper troposphere that probably extended into lower stratosphere, in the polar regions, during winter and early spring. The spectral features of these clouds differ somewhat from that of the optically thin cirrus clouds in the tropics. From theoretical simulation of the infrared spectra in the 8–25 μm region, we infer that these polar clouds have a vertical stratification in particle size, with larger particles (∼12 μm) in the bottom of the cloud and smaller ones (≲1 μm) aloft. Radiative transfer calculations also suggest that the equivalent ice-water content of these polar clouds is of the order of 1 mg cm−2.
Kiss 1 and GPR54 mRNA expression, endocrine profile, follicular development and onset of estrus following kisspeptin administration in pre-pubertal mithun heifers

Present study was undertaken to find out the effect of exogenous kisspeptin administration on Kiss1 and GPR54 mRNA expression, plasma endocrine profile and follicular development in pre-pubertal mithun heifers. Mithun heifers (20), age between 22â€“26 months, were selected and divided randomly into two groups (n=10). Before starting the experiment, all animals were examined by rectal palpation as well as through ultrasonography to ascertain the pre-pubertal status and blood samples were collected. All the animals in group A (treatment) were injected with kisspeptin (Metastin) @ 1.3 Î¼g/kg body wt. at every 3 days interval up to day 20 while in group B (control), normal saline was injected as placebo. Blood samples were collected on the day of injection and on the day of estrus in control as well as treatment group. Trans-rectal ultrasonography was also conducted at every 3 days interval till day 20 and at estrus to study the follicular development. Results revealed significant increase in Kiss1 and GPR54 mRNA expression following kisspeptin administration as compared to control. Level of FSH and Estradiol 17Î² was higher in treatment group while no difference was reported in plasma progesterone in control and treatment group. Increased numbers of medium and large follicle were recorded in treatment group while control group showed only small and medium follicles. Early onset of estrus was reported in treatment group than in control. It may be concluded that exogenous administration of kisspeptin increased expression of Kiss1 and GPR54 mRNA; peripheral FSH and estradiol concentration, increased follicular growth and early onset of estrus in treated heifers than in control.
Gestational Vitamin E Status and Gestational Diabetes Mellitus: A Retrospective Cohort Study

Objectives: To examine the association between vitamin E (VE) status and gestational diabetes mellitus (GDM). Methods: A retrospective cohort study was conducted by using data of 52,791 women at 137 hospitals across 22 provinces of China. A fasting plasma glucose (FPG) level of ≥5.1 mmol/L between the 24th and 40th weeks of gestation was used as the criteria for the diagnosis of GDM. Mean FPG level and GDM rate were calculated within each combination of the first-trimester VE concentration categories and gestational change categories. The associations of the first-trimester VE concentrations and gestational VE change with FPG and GDM were examined by employing generalized additive models (GAMs). Results: 7162 (13.57%) cases were diagnosed with GDM. The GDM rate was 22.44%, 11.50%, 13.41%, 12.87%, 13.17%, 13.44%, 12.64%, and 14.24% among women with the first-trimester VE concentrations of <7.2, 7.2–7.9, 8.0–9.3, 9.4–11.0, 11.1–13.2, 13.3–15.8, 15.9–17.7, and 17.8–35.9 mg/L, respectively. The GDM rate was 15.96%, 13.10%, 13.64%, and 12.87% among women with gestational VE change of <0, 0–0.19, 0.20–0.29, ≥0.30 mg/L per week, respectively. Multivariable adjusted GAM analyses found that the first-trimester VE concentration was associated with the FPG levels and GDM risk in an L-shaped pattern; the FPG levels and GDM risk decreased sharply to a threshold (around 7 mg/L), and then were keep flat. Gestational VE decreases when the first-trimester VE level was less than 11 mg/L were related to increased FPG levels and GDM risk. Conclusions: Both low first-trimester VE levels and subsequent gestational VE decrease were related with increased risk of GDM. The findings suggest the necessity of having VE-rich foods and appropriate VE supplementation to prevent GDM for pregnant women with low baseline VE levels.
Using Word-based Bi-gram as a Discriminator for Crossing Ambiguities in Chinese Word Segmentation

It is very important to solve the crossing ambiguities in word segmentation for Chinese information processing. We employ the word-based bi-gram to discriminate the 3-character crossing ambiguous string in two corpora. The precision rates are above 99% and 90% respectively in close test and open test, which are much higher than the best results yielded before.
Recognizing Multitype Misalignments in Wireless EV Chargers With Orientation-Sensitive Coils: A Data-Driven Strategy Using Improved ResNet

In wireless electric vehicle charging systems, misalignments between a ground-assembled transmitter and a vehicle-assembled receiver are undesirable but inevitable, which may cause efficiency deterioration and even thermal risks. The recognition of horizontal misalignment, including that in the longitudinal and lateral direction, has made gradual progress in previous works. However, yaw angle, with rare attention, can also degrade the charging performance, especially for those employing noncentrosymmetric coupling coils, such as rectangular coils. In this article, a data-driven strategy based on an improved residual network (ResNet) is proposed to recognize the above multitype misalignments simultaneously, which is accurate, reliable, and of practical and general value. Large-scale data are sampled using the proposed detection coils by double-group cooperation, which features high sensitivity to misalignments of all kinds, especially yaw angle. Benefitting from the compression technique in the preprocessing phase, the number of training data and labels can be successfully reduced by three-fourths. As the core algorithm of the overall strategy, the adaptive channel parameter recalibration ResNet can effectively perceive slight differences among similar input samples and map them to proper labels. This is achieved by an adaptive operation of nonlinear transformation and recalibrated important channel features during the training process. The effectiveness of the proposed strategy is verified experimentally using a 6.6-kW prototype. Within the 24×24 cm range, 95.2% of the test cases have an error of less than 1.7 cm when recognizing horizontal misalignment, and 91.7% of the test cases have an error of less than 1.5° when recognizing yaw angle.
Fabrication and Performance Analysis of the Aero-Leaf Savonius Wind Turbine Tree

Large wind turbines of the horizontal axis are commonly used to gather wind energy; however, their performance is found to be constrained in conditions of erratic and low-speed wind flow. In contrast, low wind conditions—which are typically present in dense urban areas—are found to favour vertical axis wind turbines (VAWT). These turbines have a simple design, are inexpensive and quiet, and are discovered to be better in low wind situations. In this research, we have chosen wind tree applications to absorb the most available wind energy. The new Aeroleaf Savonius Wind Turbine was developed numerically and a computational fluid dynamics simulation was performed on this new type of Savonius tree to predict its performance. The results indicated that the system could accept wind from any direction and could start rotating as soon as the site had a cut in wind speed of 3.3 m/s. The rotor speed increased by 10.4% from 5.5 to 6.3 m/s wind speed at 0.45 tip speed ratio. The tip speed ratio is 0.52 at the site’s high wind speed, and under these circumstances, the maximum Cp is 12.9%. The turbine was able to produce superior performance coefficients, according to the results.
Highly Sensitive Fiber-Optic SPR Urea Sensor Based on ZIF-8/Urease

A highly sensitive fiber-optic urea sensor was designed and experimentally demonstrated based on surface plasmon resonance (SPR) effect and metal-organic zeolite framework (MOF), [zeolite imidazole skeleton-8 (ZIF-8)]/urease modification. The SPR effect was excited by plating gold film on the thin core fiber (TCF) in multimode-thin core-multimode fiber (MMF) structure, which behaved high refractive index sensitivity. The ZIF-8/urease composite film was grown on the gold film by rapid aqueous phase synthesis method, in which the ZIF-8 could immobilize more urease and made urease and urea fully contact. Since the urease catalyzed urea hydrolysis would change the refractive index, the measurement of urea concentration was realized with high sensitivity and good selectivity. Experimental results showed that the urea measurement sensitivity of the proposed sensor could reach 6 nm/mM within the concentration range of 1–7 mM, which has great application potential in the field of human health monitoring.