Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Modeling of Fracture Height Propagation in Multilayer Formations Considering the Plastic Zone and Induced Stress

Hydraulic fracturing and acid fracturing are very effective stimulation technologies and are widely used in unconventional reservoir development. Fracture height, as an essential parameter to describe the geometric size of a fracture, is not only the input parameter of two-dimensional fracturing models but also the output parameter of three-dimensional fracturing models. Accurate prediction of fracture height growth can effectively avoid some risks. For example, petroleum reservoirs produce a large amount of formation water because wrong fracture height prediction leads to the connection between the oil or gas reservoir and the water layer. Although some fracture height prediction models were developed, few models considered the effects of the plastic zone, induced stress, and heterogeneous multilayer formation and its interaction. Therefore, considering the influence of many factors, an improved fracture-equilibrium-height model was developed in this study. The successive over-relaxation iteration method and the displacement discontinuity method were used to solve the model. We investigated the effects of the geological and engineering factors on fracture height growth by using the model, and some important conclusions were obtained. The higher the fracture height, the larger the plastic zone size, and the more obvious its influence on fracture height propagation. High overlying or underlying in situ stress and fracture toughness and low fluid density played a positive role in limiting the growth of the fracture height. Induced stress caused by fracture 1 could not only inhibit the height growth of fracture 2 but also promote its growth. The model established in this paper could be coupled to a fracturing simulator to provide a more reliable fracture height prediction.
Effects of a 6-Month Aerobic Exercise Intervention on Mood and Amygdala Functional Plasticity in Young Untrained Subjects

Acute exercise has beneficial effects on mood and is known to induce modulations in functional connectivity (FC) within the emotional network. However, the long-term effects of exercise on affective brain circuits remain largely unknown. Here, we investigated the effects of 6 months of regular exercise on mood, amygdala structure, and functional connectivity. This study comprised N = 18 healthy sedentary subjects assigned to an intervention group (IG; 23.9 ± 3.9 years; 3 trainings/week) and N = 10 subjects assigned to a passive control group (CG; 23.7 ± 4.2 years). At baseline and every two months, performance diagnostics, mood questionnaires, and structural and resting-state-fMRI were conducted. Amygdala-nuclei segmentation and amygdala-to-whole-brain FC analysis were performed. Linear mixed effects models and correlation analyses were conducted between FC, relVO2max, and mood scores. Data showed increases in relVO2max exclusively in the IG. Stronger anticorrelation in amygdala-precuneus FC was found, along with a stronger positive correlation in the amygdala-temporal pole FC in the IG after 4 and 6 months, while mood and amygdala volume did not reveal significant interactions. The relVO2max/amygdala-temporal pole FC correlated positively, and the amygdala-precuneus/amygdala-temporal pole FC correlated negatively. Findings suggest that exercise induced long-term modulations of the amygdala FC with the precuneus and temporal pole, shedding light on potential mechanisms by which exercise has positive influences on mood-related networks, typically altered in affective disorders.
Radial Peripapillary Capillary Plexus Perfusion and Endothelial Dysfunction in Early Post-SARS-CoV-2 Infection

Background: Endothelial cells damage and thromboinflammation are considered key elements in the generation of organ impairment in patients with COVID-19 disease. The endothelial function is evaluated by measuring flow-mediated dilation (FMD). We aimed to analyze the association between FMD impairment and retinal vascular parameters in early post-COVID-19 patients. 00118-00199Tomography (OCT), OCT Angiography (OCTA) and slit lamp examination were performed. FMD ≤ 7% was considered as pathological. Our primary outcome was to assess potential differences in the radial peripapillary capillary plexus flow index (RPCP-FI) and RPCP density (RPCP-D) values between post-COVID-19 patients with and without FMD impairment. The associations of other retinal vascular parameters with FMD impairment were assessed as secondary endpoints. Results: FMD impairment was detected in 31 patients (37.8%). RPCP-FI (p = 0.047), age (p = 0.048) and prevalence of diabetes (p = 0.046) significantly differed in patients with FMD ≤ 7% in regression analysis. RPCP-FI was linearly correlated with FMD values (R = 0.244, p =0.027). SCT was found to be lower in patients with impaired FMD (p = 0.004), although this difference was only a trend in binary logistic regression output (p = 0.07). Conclusions: Early post-COVID-19 patients showed a higher prevalence of FMD impairment compared to the general population. Age, diabetes and RPCP-FI were independently correlated with the presence of endothelial impairment in the early post-infective period.
Utilizing cross-sector collaboration to improve access to behavioral health services in schools

ABSTRACT The benefits and challenges of cross-sector collaboration are well outlined in the literature on community network development. Two sectors, schools and community behavioral health agencies, often work with the same youth inasmuch as students with behavioral difficulties in schools may also receive services from behavioral health providers. The purpose of this article is to present a case study on the implementation of a screening, triage, and referral process developed by a Central Virginia school system and community service board as part of a collaborative network which may provide generalized lessons that other organizations consider when addressing behavioral problems in schools.
Selection Cloud-oriented Learning Technologies for the Formation of Professional Competencies of Bachelors Majoring in Statistics and General Methodology of Their Use

: This article scientiﬁcally substantiates the criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, as well as presents the results of expert evaluation of existing cloud-oriented learning technologies by deﬁned criteria. The criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics were determined: information-didactic, functional, and technological. To implement the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, and effective application in the process of formation of relevant competencies, the method of expert evaluation was applied. The expert evaluation was carried out in two stages: the ﬁrst one selected cloud-oriented learning technologies to determine the most appropriate by author’s criteria and indicators, and the second identiﬁed those cloud-oriented learning technologies that should be used in the educational process as a means to develop professional skills Bachelor of Statistics. According to the research, the most appropriate, convenient, and effective cloud-oriented learning technologies for the formation of professional competencies of future bachelors of statistics by the manifestation of all criteria are cloud-oriented learning technologies CoCalc and Wolfram—Alpha. The general structure of the methodology of using cloud learning technologies for the formation of professional competencies of future bachelors of statistics is described.
Federated Filtering Revisited: New Directions to Distributed Systems Estimation and Filtering – a Case Study

The paper discusses the application of decentralized filtering to state estimation of distributed nonlinear systems. The proposed filter is operated in a novel federated architecture in an attempt to adaptively balance estimation accuracy and sensor fault tolerance in the presence of both state and measurement uncertainty when the observations of the system are subject to a variety of sensor faults. The fault management logic built into the federated structure is accountable for the control of the distributed filter architecture to achieve sensor fault accommodation in a seamless way. The performance of the traditional centralized filtering is contrasted with the proposed federated idea, and its ability to trade-off between fault tolerance and estimation accuracy are examined. Benefits from the application of the method to a chemical distillation process are demonstrated by computer simulations .
Applications of Starch Biopolymers for a Sustainable Modern Agriculture

Protected cultivation in modern agriculture relies extensively on plastic-originated mulch films, nets, packaging, piping, silage, and various applications. Polyolefins synthesized from petrochemical routes are vastly consumed in plasticulture, wherein PP and PE are the dominant commodity plastics. Imposing substantial impacts on our geosphere and humankind, plastics in soil threaten food security, health, and the environment. Mismanaged plastics are not biodegradable under natural conditions and generate problematic emerging pollutants such as nano-micro plastics. Post-consumed petrochemical plastics from agriculture face many challenges in recycling and reusing due to soil contamination in fulfilling the zero waste hierarchy. Hence, biodegradable polymers from renewable sources for agricultural applications are pragmatic as mitigation. Starch is one of the most abundant biodegradable biopolymers from renewable sources; it also contains tunable thermoplastic properties suitable for diverse applications in agriculture. Functional performances of starch such as physicomechanical, barrier, and surface chemistry may be altered for extended agricultural applications. Furthermore, starch can be a multidimensional additive for plasticulture that can function as a filler, a metaphase component in blends/composites, a plasticizer, an efficient carrier for active delivery of biocides, etc. A substantial fraction of food and agricultural wastes and surpluses of starch sources are underutilized, without harnessing useful resources for agriscience. Hence, this review proposes reliable solutions from starch toward timely implementation of sustainable practices, circular economy, waste remediation, and green chemistry for plasticulture in agriscience
CMOS front-end techniques for in-band full-duplex radio

In-band full-duplex wireless communication (FD), i.e. transmission and reception at the same time at the same frequency, is an emerging research topic, driven by the increasing demand for mobile data traffic in the crowded radio spectrum. Besides promising up to twice the spectral efficiency, additional advantages are being explored. The main issue in FD is strong self-interference (SI) from the transmitter (TX) into the local receiver (RX). In typical links, over 90dB total SI-rejection is required to fully compete with half-duplex links. This rejection is achieved by combining SI-isolation and cancellation in different domains. This work shows that impairments in the radio components limit the achievable SI-cancellation in the digital domain, typically requiring at least 40dB SI-rejection in the analog and RF domain. Implementing such analog cancellation paths to achieve competitive link budgets with CMOS integration potential, small form factor, limited complexity and low power consumption remains challenging. This work studies the feasibility of FD using a custom designed CMOS front-end. Full implementation details and analysis are presented of a 65-nanometer mixer-first front-end with a vector modulator (VM) downmixer for SI-cancellation. Using this front-end, the impact of several transceiver impairments on its full-duplex operation were experimentally investigated, such as distortion, phase noise, image rejection and transmitter impairments. The receiver was found to have over 90dB linear link budget potential in a 16.25 MHz bandwidth, when combined with only 20dB worst-case antenna isolation, thanks to its highly linear rejection of SI present at the receiver input. An improved second front-end was developed in 65nm CMOS, targeting over 100dB linear link budget, supporting a significantly higher transmit power, increased receiver linearity and reduced noise floor. Transistor-level simulations of the full system showed the reduced NF, increased linearity and expected cancellation behavior. Preliminary measurements on the stand-alone power amplifier are also presented. Complete measurements are outside the time span of this thesis work. Overall, this thesis demonstrates that vector-modulator downmixers are a promising building block for SI-cancelling full-duplex front-ends, enabling highly integrated full-duplex radios that can compete with relaxed half-duplex links.
Acute and Chronic Toxicity of Binary Mixtures of Bisphenol A and Heavy Metals

Bisphenol A (BPA) and heavy metals are widespread contaminants in the environment. However, the combined toxicities of these contaminants are still unknown. In this study, the bioluminescent bacteria Vibrio qinghaiensis Q67 was used to detect the single and combined toxicities of BPA and heavy metals, then the joint effects of these contaminants were evaluated. The results show that chronic toxicities of chromium (Cr), cadmium (Cd), lead (Pb), arsenic (As), mercury (Hg), nickel (Ni), and BPA were time–dependent; in fact, the acute toxicities of these contaminants were stronger than the chronic toxicities. Furthermore, the combined toxicities of BPA and heavy metals displayed BPA + Hg > BPA + Cr > BPA + As > BPA + Ni > BPA + Pb > BPA + Cd in the acute test and BPA + Hg > BPA + Cd > BPA + As > BPA + Cd in the chronic test, which suggested that the combined toxicity of BPA and Hg was stronger than that of other mixtures in acute as well as chronic tests. Additionally, both CA and IA models underestimated the toxicities of mixtures at low concentrations but overestimated them at high concentrations, which indicates that CA and IA models were not suitable to predict the toxicities of mixtures of BPA and heavy metals. Moreover, the joint effects of BPA and heavy metals mainly showed antagonism and additive in the context of acute exposure but synergism and additive in the context of chronic exposure. Indeed, the difference in the joint effects on acute and chronic exposure can be explained by the possibility that mixtures inhibited cell growth and luminescence in chronic cultivation. The chronic toxicity of the mixture should be considered if the mixture results in the inhibition of the growth of cells.
Fall Detection System Using Millimeter-Wave Radar Based on Neural Network and Information Fusion

Falls are fatal for the elderly, and timely detection after falls is crucial. As a contactless device, the radar sensor can monitor users’ falls with the advantage of not revealing their privacy. Today, the use of radar for fall detection has made a significant progress. However, most current methods cannot be used in real complex scenes. They usually collect fewer types of actions, and the ratio of the number of nonfall samples to the number of fall samples is small, which is not consistent with the real-life scene. In addition, the classifiers are usually trained and tested on the same environments and the same people, which cannot be easily extended to new environments and new people. We designed a robust fall detection system based on the frequency-modulated continuous-wave (FMCW) radar to solve these issues. The system detects the moment of human movement and calculates the range–velocity map, range–horizontal angle map, and range–vertical angle map of the radar signals, and creates three neural networks for these three signal maps. The stacking method of ensemble learning is used to fuse the time–space–velocity features extracted by the three neural networks to identify falls. The method was trained and tested on a data set consisting of ten scenes, 21 subjects, 52 nonfall action types, and 12 fall action types. The results show that on the test set containing only new environments and new subjects, the recall is 0.983 and the precision is 0.975.
Estimation of Equivalent Current Distribution Using Fourier Transform and Eigenmode Currents

The estimation of the equivalent current distribution is a challenge when the precise geometry of the real source is unknown. In this study, a novel estimation method for the equivalent current distribution is proposed. The proposed method is a hybrid of the Fourier transform and eigenmode currents of equivalent sources. The equivalent current distribution is estimated using the proposed method as follows. First, the Fourier transform is applied to an electric field integral equation, and the initial equivalent current distribution on a specific estimation plane is estimated from the near-field data of the real source. Utilizing the initial equivalent current distribution, the equivalent sources that are uniformly arranged over the estimation plane are thinned. Subsequently, the equivalent current distribution is estimated using a matrix equation and the eigenmode currents of the remaining equivalent sources. The advantages of the proposed method are as follows. First, the precise geometry of the real source is not needed during estimation. Second, the number of equivalent sources is reduced, and the estimation of the equivalent current distribution is well conditioned. The performance of the proposed method is validated both numerically and experimentally. Empirical guidelines for threshold values for thinning equivalent sources are provided.
How to Predict the Economic Growth Rates of a Country？ A DSGE Model with the Accumulation of Human Capital

ABSTRACT We propose an endogenous economic growth DSGE model based on human capital accumulation theory. Then we estimate the DSGE model by the Bayesian method, using the economic data of China, the USA, and Japan from 1996: Q1 to 2018: Q4. It is shown that the estimated models can accurately predict the economic growth rates of the three countries and can tightly fit the economic data of the three countries. Therefore, the model proposed can be employed to predict the economic growth of a typical country and to analyse the determinants of its economic growth in the short and long term. We find that levelling up technology in all fields is helpful for economic growth in the short term, and stimulating labour supply, mitigating monopoly in the goods market and labour market, and increasing the contribution of physical capital in goods production are helpful for economic growth in the long term.
Long-Term Exposure of MoS2 to Oxygen and Water Promoted Armchair-to-Zigzag-Directional Line Unzippings

Understanding the long-term stability of MoS2 is important for various optoelectronic applications. Herein, we show that the long-term exposure to an oxygen atmosphere for up to a few months results in zigzag (zz)-directional line unzipping of the MoS2 basal plane. In contrast to exposure to dry or humid N2 atmospheres, dry O2 treatment promotes the initial formation of line defects, mainly along the armchair (ac) direction, and humid O2 treatment further promotes ac line unzipping near edges. Further incubation of MoS2 for a few months in an O2 atmosphere results in massive zz-directional line unzipping. The photoluminescence and the strain-doping plot based on two prominent bands in the Raman spectrum show that, in contrast to dry-N2-treated MoS2, the O2-treated MoS2 primarily exhibits hole doping, whereas humid-O2-treated MoS2 mainly exists in a neutral charge state with tension. This study provides a guideline for MoS2 preservation and a further method for generating controlled defects.
Implicit and Explicit Attitudes Towards Male Looking Females and Female Looking Males: Evidence from China

In many reports, it is not difficult to see that some beautiful and feminine boys have received a lot of criticism from society. We investigated whether people’s attitude is biased against males wearing female-type and females wearing male-type. Thirty-five adults were included and measured their implicit and explicit attitudes. In the implicit test, we find that people tend to use less time and make fewer mistakes to associate the female wearing male-type with positive words and the male wearing female-type with negative words. Meanwhile, in the explicit survey, the data displays that Chinese people prefer females wearing male-type rather than males wearing female-type. This study explores people's attitudes towards others' dress and provides a new connection between positive and negative views and between female cross-gender wearers and male cross-gender wearers.
TOWARDS ROBUST INDOOR VISUAL SLAM AND DENSE RECONSTRUCTION FOR MOBILE ROBOTS

Abstract. Mobile robots are being increasingly employed in various indoor scenarios. The fundamental prerequisite is that the robot can reconstruct an accurate and complete map of the observed environment and estimate the track of its movements in this map. Current visual SLAM methods can perform this task reasonably well, but mostly in small spaces, such as a single room, and often tested in well-textured environments. In real-world applications of large indoor scenes, they lack robustness and fail to build a globally consistent map. To this end, we propose a novel system that can robustly solve the problem encountered by existing visual SLAM methods, such as weak texture and long-term drift. By combining information from a wheel odometer, the robot poses can be predicted smoothly in the absence of texture. The geometric cues are leveraged by aligning Truncated Signed Distance Function (TSDF) based submaps to minimize the long-term drift. To reconstruct a more complete and accurate dense map, we refine the sensor depth maps by taking advantage of color information and the optimization result of global bundle adjustment. As a result, the system can provide precise trajectory estimation and a globally consistent map for the downstream tasks. We validate the accuracy and robustness of the proposed method on both public and self-collected datasets and show the complementary nature of each module. Evaluation results based on high precision ground-truth show an improvement in the mean Absolute Trajectory Error (ATE) from 21 cm to 2 cm for the trajectory estimation, and the reconstructed map has a mean accuracy of 8 cm.