Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Preconception Blood Pressure with the Risk of Anemia in Children under Five Years of Age: A Large Longitudinal Chinese Birth Cohort

Hypertension during pregnancy may increase the risk of anemia in the offspring. However, few studies have investigated the effects of elevated blood pressure during the preconception period on childhood anemia. This large population-based birth cohort study was performed to determine whether abnormal preconception blood pressure has long-term consequences for childhood health. Data were obtained from the China–US Collaborative Project for Neural Tube Defect Prevention. The study consisted of 40,638 women with singleton live births who were registered in a monitoring system before pregnancy in southern China during the period 1993–1996. Children were assessed by hemoglobin measurement at approximately 53 months of age. The incidences of childhood anemia were 19.80% in the hypertension group and 16.07% in the non-hypertension group. Compared with the non-hypertension group, the hypertension group had an increased risk of childhood anemia (adjusted risk ratio (RR): 1.25; 95% confidence interval (CI): 1.11–1.41). After categorization according to blood pressure, combined systolic and diastolic hypertension was associated with a significantly increased risk of childhood anemia, compared with normotension (adjusted RR: 1.37; 95% CI: 1.16–1.63). Compared with women who had normal blood pressure, the adjusted RRs for childhood anemia were 1.20 (95% CI: 1.13–1.28), 1.26 (95% CI: 1.08–1.47), and 1.38 (95% CI: 1.14–1.67) among women with prehypertension, stage-1 hypertension, and stage-2 hypertension, respectively. Our results suggest a linear association between prepregnancy hypertension and the risk of childhood anemia in the Chinese population. Interventions targeting preconception blood pressure may have a positive effect on childhood health.
Adjoint and PDE methods for pricing and risk management of exotic interest rate derivatives

This thesis demonstrates how to compute Greeks accurately and efficiently for the displaced-diffusion LIBOR market model and the separable LIBOR Markovfunctional model. Chapter 1 introduces the problem and discusses the three main classes of interest rate models. The LIBOR market model is introduced in detail in Chapter 2, where we also provide information for an efficient model implementation. In Chapter 3 we extend the pathwise adjoint method to the displaced-diffusion LIBOR market model and present a 20 percent speed improvement. This improvement is achieved without additional approximations to those of Giles and Glasserman, [34]. We also derive the pathwise adjoint method for the predictor-corrector drift approximation. We compare the deltas and vegas computed using log-Euler and predictor-corrector, showing both methods have the same computational order but the latter is more accurate. In Chapter 4 we introduce the separable LIBOR Markov-functional model. We present a new formulation in the spot measure and find that for a Monte Carlo implementation the spot measure performs better than the terminal measure, which is consistent with well-known results for the LIBOR market model. For a PDE implementation, however, we find that the terminal measure performs better than the spot measure. These results are demonstrated by pricing interest rate caps and double-digital options. Chapter 5 presents the separable LIBOR Markov-functional model as a control variate for the LIBOR market model. This method has been previously suggested in the literature, however, it only works for prices and deltas, not vegas. We present a new technique that is effective for all three. Our approach introduces many innovations, but the essential improvement is an accurate, efficient and stable calibration procedure. It achieves a standard error reduction by a factor of 8 and 10 for the prices of a five-factor, 20-year Bermudan swaption and cancellable inverse floater. For the Bermudan swaption a reduction of 5 is achieved for the vega. In Chapter 6 we introduce the adjoint PDE method for Markov-functional models. This is an accurate and efficient way to compute Greeks, where most of the
MTPA control of interior fault-tolerant permanent magnet motor for the marine electric propulsion system

In order to improve the torque output capability of interior fault-tolerant permanent magnet motor (IFTPMM) applied in the electric propulsion ships, the maximum torque per ampere (MTPA) is studied. According to the basic equations of the motor in the d-q coordinate system, the Lagrangian multiplier method is proposed to obtain the multi-order equations of d-q axis current and torque. The optimal operating point of the MTPA control is found by MATLAB and the MTPA control is realized. Compared to the control method of $\text{id}=0$, the simulation waveform shows that the MTPA control is more suitable in IFTPMM and the control algorithm has high efficiency and fast dynamic response, which can meet the requirements of electric propulsion ships for propulsion motors.
Root-Zone Heat Priming Effects on Maximum Quantum Efficiency of PSII, Productivity, Root Morphology and Nutritional Quality of Two Aeroponically Grown Leafy Greens in a Tropical Greenhouse

This study investigated the effects of root zone (RZ) heat priming on Eruca sativa (cv. Arugula) and Lactuca sativa (cv. Canasta) in a tropical greenhouse by exposing them to three different RZ temperatures (RZTs). For the first group, plants were grown at 25 °C-RZT for 36 days. The second group of plants was grown at 25 °C-RZT for 10 days before transferring to 38 °C-RZT for 10 days and then to 42 °C-RZT for another 16 days (primed). For the third group, plants were grown at 25 °C-RZT for 20 days and for the last 16 days were transferred to 42 °C-RZT (non-primed). RZ heat priming did not affect the leaf expansion of Arugula while the leaf expansion was slower in RZ heat primed Canasta compared to 25 °C-RZT plants. After transferring to 42 °C-RZT in the later stage, RZ heat primed Arugula had similar productivity but a larger root system with higher nutritional quality at harvest and during postharvest storage compared to those of 25 °C-RZT plants. After subjection to 42 °C-RZT, although RZ heat priming enhanced its nutritional quality, the productivity of Canasta was compromised. The results of this study suggest that it is feasible to enhance productivity and nutritional quality of leafy greens at lower production cost through RZT management.
Achieving Ammonium Removal Through Anammox-Derived Feammox With Low Demand of Fe(III)

Feammox-based nitrogen removal technology can reduce energy consumption by aeration and emission of carbon dioxide. However, the huge theoretical demand for Fe(III) becomes a challenge for the further development of Feammox. This study investigated an anammox-derived Feammox process with an intermittent dosage of Fe2O3 and proposed a novel approach to reduce the Fe(III) consumption. The results showed that anammox genera Candidatus Brocadia and Candidatus Kuenenia in the seed anammox sludge significantly decreased after cultivation. The formation of N2 was the dominating pathway in Feammox while that of nitrite and nitrate could be neglected. Batch tests showed that specific Feammox activity of ammonium oxidation was 1.14–9.98 mg N/(g VSS·d). The maximum removal efficiency of ammonium reached 52.3% in the bioreactor with a low dosage of Fe(III) which was only 5.8% of the theoretical demand in Feammox. The removal of ammonium was mainly achieved through Feammox, while partial nitrification/anammox also played a role due to the non-power and unintentional oxygen leakage. The super-low oxygen also responded to the low demand of Fe(III) in the bioreactor because it could trigger the cycle of Fe(III)/Fe(II) by coupling Feammox and chemical oxidation of Fe(II) to Fe(III). Therefore, anammox-derived Feammox can achieve the removal of ammonium with low Fe(III) demand at super-low oxygen.
Afro Love: counter-literacies in Brazilian natural hair communities

ABSTRACT This study explores afro hair as a central component of transnational anti-Black and Black-empowering literacy construction. It argues that Black women in São Paulo City, Brazil, constructed Afro Love Counter-Literacies that were Black-empowering by embracing afro hair. Scholarship on Black feminism, racial literacies, and critical literacies guided the narrative analysis. The findings highlight two interworking mechanisms of Afro-Love Counter-Literacies: (1) alfabetização afro, which refers to languaging, caring for, and styling afro hair; and (2) letramento afro, which describes the development of affirmative beliefs about afro hair. Participants drew upon these literacies to (re)read and (re)write the world through an afro-affirming Black feminist lens.
Scope and Limitations of Current Antibiotic Therapies against Helicobacter pylori: Reviewing Amoxicillin Gastroretentive Formulations

Even though general improvement of quality of life has happened around the globe, statistics show that gastric cancer is still a very serious medical concern in some regions of the world. A big portion of malignant neoplasms that develop inside the stomach are linked to an infection of Helicobacter pylori; in fact, this pathogen has already been categorized as a group 1 carcinogen by the World Health Organization (WHO). Still, the efficacy of current anti-H. pylori therapeutic approaches is insufficient and follows a worrying decreasing trend, mainly due to an exponential increase in resistance to key antibiotics. This work analyzes the clinical and biological characteristics of this pathogen, especially its link to gastric cancer, and provides a comprehensive review of current formulation trends for H. pylori eradication. Research effort has focused both on the discovery of new combinations of chemicals that function as optimized antibiotic regimens, and on the preparation of gastroretentive drug delivery systems (GRDDSs) to improve overall pharmacokinetics. Regarding the last topic, this review aims to summarize the latest trend in amoxicillin-loaded GRDDS, since this is the antibiotic that has shown the least bacterial resistance worldwide. It is expected that the current work could provide some insight into the importance of innovative options to combat this microorganism. Therefore, this review can inspire new research strategies in the development of efficient formulations for the treatment of this infection and the consequent prevention of gastric cancer.
Association between Micronutrient Intake and Breast Cancer Risk According to Body Mass Index in South Korean Adult Women: A Cohort Study

This study investigated the association between micronutrient intake and breast cancer risk in South Korean adult women. This association was stratified according to body mass index (BMI) categories. Data from the Korean Genome and Epidemiology Study (KoGES) and the Health Examinee Study were analyzed. Altogether, 63,337 individuals (aged ≥40 years) completed the baseline and first follow-up surveys; 40,432 women without a history of cancer at baseline were included in this study. The association between micronutrient intake and breast cancer was determined by estimating the hazard ratio (HR) and 95% confidence interval (CI) using the Cox proportional hazard regression model. A stratified analysis by BMI (<25 kg/m2 and ≥25 kg/m2) was performed. The an analysis of 15 micronutrients and breast cancer risk revealed that none of the micronutrients were associated with breast cancer risk after adjusting for covariates. In obese women, the risk of breast cancer was significantly reduced in the group that consumed vitamin C more than the recommended level (HR = 0.54, 95% CI: 0.31–0.93) and vitamin B6 levels above the recommended level (HR = 0.48, 95% CI: 0.25–0.89). In obese women, exceeding the recommended daily intake levels of vitamin C and vitamin B6 was associated with a lower risk of breast cancer. However, other micronutrients were not associated with breast cancer risk in these women.
Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA’s Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype ‘intelligent party-line’ system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the “right” data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.
Deep Learning for Image-Based Plant Growth Monitoring: A Review

Deep learning (DL) approaches have received extensive attention in plant growth monitoring due to their ground-breaking performance in image classification; however, the approaches have yet to be fully explored. This review article, therefore, aims to provide a comprehensive overview of the work and the DL developments accomplished over the years. This work includes a brief introduction on plant growth monitoring and the image-based techniques used for phenotyping. The bottleneck in image analysis is discussed and the need of DL methods in plant growth monitoring is highlighted. A number of research works focused on DL based plant growth monitoring-related applications published since 2017 have been identified and included in this work for review. The results show that the advancement in DL approaches has driven plant growth monitoring towards more complicated schemes, from simple growth stages identification towards temporal growth information extraction. The challenges, such as resource-demanding data annotation, data-hungriness for training, and extraction of both spatial and temporal features simultaneously for accurate plant growth prediction, however, remain unsolved.
Improving Global Weather Prediction in GFDL SHiELD Through an Upgraded GFDL Cloud Microphysics Scheme

We describe the third version of the Geophysical Fluid Dynamics Laboratory cloud microphysics scheme (GFDL MP v3) implemented in the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD). Compared to the GFDL MP v2, the GFDL MP v3 is entirely reorganized, optimized, and modularized into functions. The particle size distribution (PSD) of all hydrometeor categories is redefined to better mimic observations, and the cloud droplet number concentration (CDNC) is calculated from the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA2) aerosol data. In addition, the GFDL MP has been redesigned so all processes use the redefined PSD to ensure overall consistency and easily permit the introduction of new PSDs and microphysical processes. A year's worth of global 13‐km, 10‐day weather forecasts were performed with the new GFDL MP. Compared to the GFDL MP v2, the GFDL MP v3 significantly improves SHiELD's predictions of geopotential height, air temperature, and specific humidity in the Troposphere, as well as the high, middle and total cloud fractions and the liquid water path. The predictions are improved even further by the use of reanalysis aerosol data to calculate CDNC, and also by using the more realistic PSD available in GFDL MP v3. However, the upgrade of the GFDL MP shows little impact on the precipitation prediction. Degradations caused by the new scheme are discussed and provide a guide for future GFDL MP development.
Safety system for monitoring of the dangerous gases in electromobility laboratory

This paper deals with the design and tests of the safety and monitoring system of hazardous gases in the laboratory. The most dangerous gases which can be produced by lead-acid batteries or lithium-ion batteries during excessive charging or discharging are precisely monitored and shown on the LCD display. Gases emitted by batteries can be potentially dangerous for human and our system should offer real-time values on the LCD display and offers sound and light alarm for people in the laboratory. The system also supports email notifications for remote management and monitoring of the laboratory during long-term cyclic battery tests since the laboratory is without humans. If a dangerous situation occurs, the light and sound alarm start to warn the human operator and remote operators about this situation. On the LCD and email notifications is clearly highlighted which type of gas or another value caused the alarm situation.
Prescribed-time stabilisation for uncertain reaction-diffusion equations with Neumann boundary control

We study the Neumann boundary feedback stabilisation for reaction-diffusion equations with matched boundary uncertainties (including internal uncertainty and external disturbance) within a prescribed time, where the convergence time is independent of initial conditions and can be prescribed a priori. We first estimate the uncertainties within the prescribed time by constructing an estimator and then propose the prescribed-time boundary control law by utilising backstepping transformation with a time-varying kernel. Neumann boundary control is verified to be uniformly bounded.
In Vitro and In Vivo Genotoxicity Assessments and Phytochemical Analysis of the Traditional Herbal Prescription Siryung-Tang

Siryung-tang (SRT) is a traditional herbal prescription containing Oryeong-san and Soshiho-tang that is used to treat digestive system diseases. We performed safety evaluations of SRT based on genotoxicity and developed an assay for quality control using high-performance liquid chromatography with a photodiode array detector. Genotoxicity was evaluated based on bacterial reverse mutation (Salmonella typhimurium TA1535, TA98, TA100, and TA1537, and Escherichia coli WP2 uvrA), chromosomal aberration (Chinese hamster lung cells), and micronucleus (mouse) tests. Quality control analysis was conducted using a SunFire C18 column and gradient elution with a distilled water–acetonitrile mobile phase system containing 0.1% (v/v) formic acid for 12 markers (5-(hydroxy-methyl)furfural, 3,4-dihydroxybenzaldehyde, liquiritin apioside, liquiritin, coumarin, baicalin, wogonoside, cinnamaldehyde, baicalein, glycyrrhizin, wogonin, and atractylenolide III). SRT showed no genotoxicity in three tests. Ames tests showed that SRT at 313–5000 μg/plate did not significantly increase the number of revertant colonies with or without metabolic activation among five bacterial strains. Moreover, in vivo micronucleus testing showed that SRT did not increase the frequency of bone marrow micronuclei. The number of chromosomal aberrations associated with SRT was similar to that observed in the negative controls. The 12 markers were detected at 0.04–16.86 mg/g in a freeze-dried SRT sample and completely eluted within 45 min. The extraction recovery was 95.39–104.319% and the relative standard deviation value of the precision was ≤2.09%. Our study will be used as basic data for the safety and standardization of SRT.
Error analysis for a difference scheme approximating mean curvature flow

We analyse a finite difference scheme for the approximation of level set solutions to mean curvature flow. The scheme which was proposed by Crandall & Lions (Numer. Math. 75, (1996) 17-41) is a monotone and consistent discretization of a regularized version of the underlying problem. We derive an L[infin]-error bound between the numerical solution and the viscosity solution to the level set equation provided that the space and time step sizes are appropriately related to the regularization parameter.
Deoxyshikonin Mediates Heme Oxygenase-1 Induction and Apoptotic Response via p38 Signaling in Tongue Cancer Cell Lines

Deoxyshikonin (DSK), a phytochemical constituent, has been documented to elicit various oncostatic properties alone or in combination with established therapeutics. However, its role in restraining oral squamous cell carcinoma (OSCC) is mostly unclear. Here, we examined the tumor-suppressive effect of DSK and explored the molecular mechanisms underlying DSK’s activities on controlling oral cancer. Our results showed that DSK dose-dependently lessened the cell viability of tongue cancer cell lines, involving induction of cell cycle arrest at the sub-G1 phase and apoptotic cell death. Moreover, a unique signature of apoptosis-related proteins, including augmented nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) expression and caspase activation, was observed in DSK-treated tongue cancer cell lines. Furthermore, DSK-mediated upregulation of HO-1 and cleavage of caspase-9 and -3 were significantly inhibited by pharmacological blockage of p38 kinase. Collectively, these data revealed that DSK halted cell cycle progression and elicited cell apoptosis in tongue cancer cell lines, reshaping a p38-dependent profile of apoptotic proteome. Our findings provided novel insights into the therapeutic implications of a natural compound on the management of OSCC.