Miracle-dz/UniFAR-FTUs huggingface dataset:
Placental Pathology and Maternal Risk Factors for Stillbirth: A Case-Control Study

Background Fetal death is the delivery of a fetus with no sign of life, as indicated by the absence of breathing, heartbeat, pulsation of the umbilical cord, or definite movement of voluntary muscles. Nearly 2.6 million stillbirths are estimated to occur worldwide every year. Almost all of these (98%) stillbirths occur in low- and middle-income countries. About one-sixth of the stillbirths globally were recorded in India in 2019, making it the most burdened country in the world. In light of this, we conducted a study to identify the placental pathologies and maternal factors associated with stillbirth. Methodology A case-control study was conducted at the Department of Obstetrics & Gynecology, Veer Surendra Sai Institute of Medical Sciences and Research (VIMSAR), from June 2022 to May 2023. Cases included pregnant women with a gestational age of 28 weeks or more who delivered a stillbirth infant at VIMSAR, and controls included gestational age-matched deliveries with live birth. Consent to participate in the study was obtained before enrolment. The final sample size was 79 cases and controls. The chi-square test was performed for bivariate analysis, and logistic regression was used for multivariate analysis. Results In our study, we found a significant association between maternal age of more than 30 years (odds ratio (OR) = 3.01, 95% confidence interval (CI) = 1.91-4.22, p = 0.012), maternal education (with up to the primary level or less: OR = 6.19, 95% CI = 2.92-7.87, p = 0.012), history of addiction (tobacco chewing: OR = 5.58, 95% CI = 3.71-7.11, p = 0.03), and the number of antenatal visits (no visit: OR = 6.87, 95% CI = 2.91-7.79, p = 0.019) with an increased risk of stillbirth. Among the obstetrical complications, pre-eclampsia/eclampsia (OR = 3.87, 95% CI = 1.98-5.11, p = 0.001), premature rupture of membranes (PROM)/preterm premature rupture of the membranes (PPROM) (OR = 2.49, 95% CI = 1.31-3.91, p = 0.03) and antepartum hemorrhage (APH) (OR = 2.66, 95% CI = 1.65-3.58, p = 0.02) were found to be significantly related with stillbirth. Among placental pathologies, uteroplacental vascular pathology (OR = 7.39, 95% CI = 3.01-8.97), acute chorioamnionitis (OR = 3.35, 95% CI = 2.11-5.21), chronic inflammation (OR = 2.33, 95% CI = 1.91 4.17), calcific changes (OR = 4.46, 95% CI = 2.56-6.01), and retroplacental clots (OR = 9.95, 95% CI = 4.39-11.71) were associated with stillbirth. Conclusions In our study, advanced maternal age, absence of antenatal visits, low level of education, tobacco addiction, pre-eclampsia/eclampsia, APH, and PROM in pregnancy were the major risk factors associated with stillbirth. Uteroplacental vascular pathology, chorioamnionitis, chronic inflammation, retroplacental hematoma, and calcific changes were the most significant placental lesions associated with stillbirth.
Comment on ‘Wind-influenced projectile motion’

We comment on the article ‘Wind-influenced projectile motion’ by Bernardo et al (2015 Eur. J. Phys. 36 025016) where they examine the trajectory of a particle that is subjected to gravity and a linear air resistance plus the influence from the wind. They find by using the Lambert W function that the particleʼs trajectory for a special angle, the critical angle θ C ? > , between the initial velocity and the horizontal is part of a straight line. In this comment we will show that this result can be proved without using the Lambert W function which is not that well known to beginning students of physics.
Extraction Optimization and Physical Modification of Fish Gelatin from Thunnus tonggol Using Ultraviolet (UV) Irradiation

ABSTRACT In this study, the yield of gelatin extraction from fish waste was optimized using response surface method. The highest yield was obtained with 0.8% citric acid concentration at 72.95°C for 58 minutes. Then, fish gelatin was modified using ultraviolet radiation to overcome fish gelatin defects including unsuitable rheological properties and low thermo-stability. UV irradiation can create crosslinks via alkyl or phenyl groups of the proteins. The modified sample also showed the highest melting point due to the creation of cross-links and improved emulsification and foaming properties of fish gelatin through structural modification and increased surface hydrophobicity of gelatin.
An Analysis of the Mixed IEEE 802.11ax Wireless Networks in the 5 GHz Band

This paper presents an analysis of the IEEE 802.11ax networks’ coexistence with legacy stations, namely IEEE 802.11ac, IEEE 802.11n, and IEEE 802.11a. The IEEE 802.11ax standard introduces several new features that can enhance network performance and capacity. The legacy devices that do not support these features will continue to coexist with newer devices, creating a mixed network environment. This usually leads to a deterioration in the overall performance of such networks; therefore, in the paper, we want to show how we can reduce the negative impact of legacy devices. In this study, we investigate the performance of mixed networks by applying various parameters to both the MAC and PHY layers. We focus on evaluating the impact of the BSS coloring mechanism introduced to the IEEE 802.11ax standard on network performance. We also examine the impact of A-MPDU and A-MSDU aggregations on network efficiency. Through simulations, we analyze the typical performance metrics such as throughput, mean packet delay, and packet loss of mixed networks with different topologies and configurations. Our findings indicate that implementing the BSS coloring mechanism in dense networks can increase throughput by up to 43%. We also show that the presence of legacy devices in the network disrupts the functioning of this mechanism. To address this, we recommend using an aggregation technique, which can improve throughput by up to 79%. The presented research revealed that it is possible to optimize the performance of mixed IEEE 802.11ax networks.
ON-ROAD VEHICLE CLASSIFICATION BASED ON RANDOM NEURAL NETWORK AND BAG-OF-VISUAL WORDS

A large increase in the number and types of vehicles occurred due to the growth in population. This fact brings the need for efficient vehicle classification systems that can be used in traffic surveillance and intelligent transportation systems. In this study, a multi-type vehicle classification system based on Random Neural Networks (RNNs) and Bag-Of-Visual Words (BOVWs) is developed. A 10-fold cross-validation technique is used, with a large dataset, to assess the proposed approach. Moreover, the BOVW–RNN's classification performance is compared with LIVCS, a vehicle classification system based on RNNs. The results reveal that BOVW–RNN classification system produces more reliable and accurate classification results than LIVCS. The main contribution of this paper is that the developed system can serve as a framework for many vehicle classification systems.
Observations of Ship Tracks from Ship-Based Platforms

Abstract Ship-based measurements in June 1994 provided information about ship-track clouds and associated atmospheric environment observed from below cloud levels that provide a perspective different from satellite and aircraft measurements. Surface measurements of latent and sensible heat fluxes, sea surface temperatures, and meteorological profiles with free and tethered balloons provided necessary input conditions for models of ship-track formation and maintenance. Remote sensing measurements showed a coupling of ship plume dynamics and entrainment into overlaying clouds. Morphological and dynamic effects were observed on clouds unique to the ship tracks. These morphological changes included lower cloud bases early in the ship-track formation, evidence of raised cloud bases in more mature tracks, sometimes higher cloud tops, thin cloud-free regions paralleling the tracks, and often stronger radar returns. The ship-based lidar aerosol measurements revealed that ship plumes often interacted with the over.
Opportunity Cost to Attending Surgeons of Intraoperative Training for Residents in Cataract Surgery

Purpose To estimate the opportunity cost to attending surgeons of teaching residents cataract surgery in the operating room. Patients and methods Operating room records at an academic teaching hospital from July 2016 to July 2020 were analyzed in this retrospective review of cases. Cases were identified using Current Procedural Terminology (CPT) codes 66982 and 66984 for cataract surgery. Outcomes measured include operative time and work relative value units (wRVUs). Cost analysis was performed using the generic 2021 Medicare Conversion Factor. Results Of 8813 cases, 2906 (33.0%) included resident involvement. For CPT 66982 cases, median (interquartile range (IQR)) operative time was 47 (22) minutes with resident involvement and 28 (18) minutes without (p<0.001). For CPT 66984 cases, median (IQR) operative time was 34 (15) minutes with resident involvement and 20 (11) minutes without (p<0.001). Median wRVUs was 78.5 (20.9) with resident involvement and 61.0 (14.4) without (p<0.001) which converted to an opportunity cost (IQR) per case of $1393.72 ($1055.63). Among cases involving residents, median operative time was significantly higher during the first and second quarters (p<0.001) and for every quarter when compared to cases performed by attendings only (p<0.001). Conclusion Teaching cataract surgery in the operating room is associated with a considerable opportunity cost for attending surgeons.
in resource management: the continuous-time case

Larson, B.A., 1992. Principles of stochastic dynamic optimization in resource management: the continuous-time case. Agric. Econ., 7: 91-107. A wide range of problems in economics, agriculture, and natural resource management have been analyzed using continuous-time optimal control models, where the state variables change over time in a stochastic manner. Using a firm-level investment model and a model of environmental degradation, this paper provides a concise introduction to continuous-time stochastic control techniques. The process used to derive the differential of a stochastic process is stressed and, in turn, is used to explain Ito's lemma, Bellman's equation, the Hamilton-Jacobi equation, the maximum principle, and the expected dynamics of choice variables. A basic extension of the dynamic duality literature is also provided, where the Hamilton-Jacobi equation is used to derive a stochastic and dynamic analogue of Hotelling's lemma.
A compact graphene Q-switched erbium-doped fiber laser using optical circulator and tunable fiber Bragg grating

We demonstrate a passively Q-switched tunable erbium-doped fiber laser (EDFL) based on graphene as a saturable absorber (SA). A three-port optical circulator (OC) and a strain-induced tunable fiber Bragg grating (TFBG) are used as the two end mirrors in an all-fiber linear cavity. The Q-switched EDFL has a low pump threshold of 23.8 mW. The pulse repetition rate of the fiber laser can be widely changed from 9.3 kHz to 69.7 kHz by increasing the pump power from 23.8 mW to 219.9 mW. The minimum pulse duration is 1.7 ? s and the highest pulse energy is 25.4 nJ. The emission wavelength of the laser can be tuned from 1560.43 nm to 1566.27 nm by changing the central wavelength of the strain-induced TFBG.
An Improved Fast Detection Method for Helmets in Complex Construction Environment

To solve the problem that the detection speed of the existing helmet detection algorithm cannot meet the requirements of the practical application problem, we propose a lightweight helmet detection algorithm based on YOLOv4 as the main framework. The algorithm optimizes the backbone network and feature pyramid of YOLOv4. It replaces the original backbone network of YOLOv4 with MobileNetv3 which can improve the computational efficiency by depthwise separable convolution. The algorithm also adds a spatial pyramid module to the feature pyramid part which can improve the detection accuracy of the algorithm. Finally, we obtain the anchor boxes through the K- means++ algorithm to accelerate the convergence speed of the algorithm and improve the accuracy of the model. The experimental results show that the mAP value is 90.4%, and the detection speed can reach 63f/s on a single card RTX 3090.
Quantitative Model and Fast Estimation Algorithm of Sampling Error for Association Rule Mining

Sampling is a simple and effective technique to improve the efficiency and the scalability of algorithms for association rule mining.However,there is lack of necessary research to define the degree of error with respect to the outcome of the algorithm,i.e.,a quantitative model to measure the sampling error,and to estimate the error efficiently.In this paper,based on the systematic analysis, the authors point out the deficiency of the current results in this field and give a novel,flexible quantitative model to measure the sampling error,and propose a high efficient computational method,interval estimation algorithm of cardinal error,for estimating sampling error based on the real observation and the theoretical analysis.Both of theoretical analysis and realistic experiments show the error between sample set and original dataset can be obtained effectively and accurately by the model,the representative capability of sample set to original dataset also can be estimated efficiently and exactly by the interval estimation algorithm of cardinal error.What's more,the interval estimation algorithm of cardinal error can be conveniently nested into sampling algorithms to speed up them and is useful for distributed,parallel association rule mining algorithms.
Low-frequency noise in Au-decorated graphene–Si Schottky barrier diode at selected ambient gases

We report results of the current–voltage characteristics and low-frequency noise in Au nanoparticle (AuNP)-decorated graphene–Si Schottky barrier diodes. Measurements were conducted in ambient air with addition of either of two organic vapors, tetrahydrofuran [(CH2)4O; THF] and chloroform (CHCl3), as also during yellow light illumination (592 nm), close to the measured particle plasmon polariton frequency of the Au nanoparticle layer. We observed a shift of the DC characteristics at forward voltages (forward resistance region) when tetrahydrofuran vapor was admitted (in a Au-decorated graphene–Si Schottky diode), and a tiny shift under yellow irradiation when chloroform was added (in not decorated graphene–Si Schottky diode). Significantly larger difference in the low-frequency noise was observed for the two gases during yellow light irradiation, compared with no illumination. The noise intensity was suppressed by AuNPs when compared with noise in graphene–Si Schottky diode without an AuNP layer. We conclude that flicker noise generated in the investigated Au-decorated Schottky diodes can be utilized for gas detection.
Isoflavone Consumption and Risk of Breast Cancer: An Updated Systematic Review with Meta-Analysis of Observational Studies

Rationale: Epidemiological studies that focus on the relationship between dietary isoflavone intake and the risk of breast cancer still lead to inconsistent conclusions. Herein, we conducted a meta-analysis of the latest studies to explore this issue. Method: We performed a systematic search using Web of Science, PubMed, and Embase from inception to August 2021. The robust error meta-regression (REMR) model and generalized least squares trend (GLST) model were used to establish dose–response relationships between isoflavones and breast cancer risk. Results: Seven cohort studies and 17 case-control studies were included in the meta-analysis, and the summary OR for breast cancer was 0.71 (95% CI 0.72–0.81) when comparing the highest to the lowest isoflavone intake. A subgroup analysis further showed that neither menopausal status nor ER status has a significant influence on the association between isoflavone intake and breast cancer risk, while the isoflavone intake doses and study design does. When the isoflavones exposure was less than 10 mg/day, no effects on breast cancer risk were detected. The inverse association was significant in the case-control studies but not in the cohort studies. In the dose–response meta-analysis of the cohort studies, we observed an inverse association between isoflavone intake and breast cancer: a 10 mg/day increase in isoflavone intake was related to reductions of 6.8% (OR = 0.932, 95% CI 0.90–0.96) and 3.2% (OR = 0.968, 95% CI 0.94–0.99) in breast cancer risk when using REMR and GLST, respectively. In the dose–response meta-analysis of the case-control studies, the inverse association for every 10 mg/day isoflavone intake was associated with breast cancer risk reductions by 11.7%. Conclusion: present evidence demonstrated that taking in dietary isoflavone is helpful in reducing the breast cancer risk.
Cross-View Recurrence-Based Self-Supervised Super-Resolution of Light Field

Compared with external-supervised learning-based (ESLB) methods, self-supervised learning-based (SSLB) methods can overcome the domain gap problem caused by different light field (LF) acquisition conditions, which results in the performance degradation of light field super-resolution on unseen test datasets. Current SSLB methods exploit the cross-scale recurrence feature in the single view image for super-resolution, ignoring the correlation information among views. Different from previous works, we propose a cross-view recurrence-based self-supervised mapping framework to correlate complementary information among views in the down-scaled input LF. Specifically, the cross-view recurrence information consists of geometry structure features and similar structure features. The former is to provide sub-pixel information according to disparity correlations among adjacent views, and the latter is to acquire similar color and contour information among arbitrary views, which can compensate for error disparity guidance of geometry structure features in sharp variance areas. Moreover, instead of the widely used “All-to-All” strategy, we propose a “Part-to-Part” mapping strategy, which is better competent for SSLB approaches with limited training examples solely extracted from input LF. Finally, considering that self-supervised methods need to retrain from the beginning toward each test image, based on the proposed “part-to-part” strategy, an efficient end-to-end network is designed to extract these cross-view features for superior SASR performance with less training time. Experiment results demonstrate that our method outperforms other state-of-the-art ESLB methods on both large and small domain gap cases. Compared with the only SSLB method (LFZSSR), our approach achieves better performance with 524 times less training time.
Evaluation of PERSIANN system satellite-based estimates of tropical rainfall

Abstract PERSIANN, an automated system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, has been developed for the estimation of rainfall from geosynchronous satellite longwave infared imagery (GOES–IR) at a resolution of 0.25° × 0.25° every half–hour. The accuracy of the rainfall product is improved by adaptively adjusting the network parameters using the instantaneous rain–rate estimates from the Tropical Rainfall Measurement Mission (TRMM) microwave imager (TMI product 2A12), and the random errors are further reduced by accumulation to a resolution of 1° × 1° daily. The authors' current GOES–IR–TRMM TMI based product, named PERSIANN–GT, was evaluated over the region 30°S–30°N, 90°E–30°W, which includes the tropical Pacific Ocean and parts of Asia, Australia, and the Americas. The resulting rain–rate estimates agree well with the National Climatic Data Center radar–gauge composite data over Florida and Texas (correlation coefficient r > 0.7). The product al.
Association of PM2.5 from agriculture sources and acute myocardial infarction onset: results from 2015 to 2018 in China

Background and purpose: Acute myocardial infarction (AMI) is a manifestation of coronary artery disease. Fine particulate matter (PM2.5) has been regarded as a risk factor for AMI-related mortality and hospitalizations. Agricultural activities contribute greatly to PM2.5 formation, indicating potential health risks of PM2.5 in agricultural areas. Health effect studies on agricultural source remain scarce, and currently available evidence is controversial. This study investigated the health effects of short-term exposure to PM2.5 from agricultural sources on AMI onset using a nationwide analysis in China. Methods: We reviewed case records from the China Cardiovascular Association Database and extracted the data of 355,815 patients with AMI onset from 1,653 hospitals for the period 2015 to 2018. We obtained daily concentrations of PM2.5 from agricultural sources using the source-oriented Community Multiscale Air Quality model. Moreover, we proposed a time-stratified case-crossover study to examine associations between exposure to PM2.5 from agricultural sources and AMI onset and determined lag effects with a maximum of 3 days. Additionally, we conducted multiple subgroup and sensitivity analyses. Results: Exposure to PM2.5 from agricultural sources caused a significantly increased risk of the onset of AMI and its subtypes. Short-term exposure to PM2.5 from agricultural sources on the current day (lag 0) was positively associated with a 4.4% (95% confidence interval [95% CI]: 3.3%–5.5%), 4.9% (95% CI: 3.5%–6.3%), and 3.4% (95% CI: 1.5%–5.4%) increase in the odds of AMI, ST-elevation myocardial infarction (STEMI), and non-STEMI (NSTEMI), for each 10 μg/m3 increase. Meanwhile, higher risk estimations were pronounced in individuals who were aged above 65 years, who lived in southern China, and who resided in the rural area setting, and significant differences were mostly found in NSTEMI onsets. Conclusions: Short-term exposure to PM2.5 from agricultural sources may trigger the onset of AMI and its two subtypes. Improving agriculture management through ammonia emission abatement can help in achieving PM2.5 reduction and protecting public health.
Optically pumped membrane BH-DFB lasers for low-threshold and single-mode operation

High optical confinement and high index coupling in 1.55 /spl mu/m-wavelength GaInAsP-InP membrane buried heterostructure distributed feedback (BH-DFB) lasers consisting of deeply etched single-quantum-well wire-like active regions were demonstrated under room-temperature (RT) continuous-wave (CW) optical pumping. A threshold pump power of 1.5 mW and a submode suppression ratio (SMSR) of 42 dB were obtained for a 142-nm-thick membrane with a cavity length of 120 /spl mu/m and a stripe width of 2 /spl mu/m. We have also realized membrane BH-DFB laser arrays by arranging the laser cavities (10 /spl mu/m spaced 15 elements with five different grating periods). A total wavelength span of 72 nm was achieved with a small lasing wavelength fluctuation up to 1.2 nm at RT-CW condition under optical pumping. From this value, membrane thickness fluctuation was estimated to be 0.4 nm. Threshold pump power of 3.4 mW and SMSR of 45 dB were achieved in a typical device.