Introducing and Validating the Cranial-Dorsal-Hip Angle (∠CDH): A Method for Accurate Fetal Position Assessment in the First Trimester and Future AI Applications.

Purpose To introduce the cranial-dorsal-hip angle (∠CDH) as a novel quantitative tool for assessing fetal position in the first trimester and to validate its feasibility for future AI applications. Materials and Methods 2520 first-trimester fetal NT exams with 2582 CRL images (January-August 2022) were analyzed at a tertiary hospital as the pilot group. Additionally, 1418 cases with 1450 fetal CRL images (September-December 2022) were examined for validation. Three expert sonographers defined a standard for fetal positions. ∠CDH measurements, conducted by two ultrasound technicians, were validated for consistency using Bland-Altman plots and the intra-class correlation coefficient (ICC). This method allowed for categorizing fetal positions as hyperflexion, neutral, and hyperextension based on ∠CDH. Comparative accuracy was assessed against Ioannou, Wanyonyi, and Roux methods using the weighted Kappa coefficient (k value). Results The pilot group comprised 2186 fetal CRL images, and the validation group included 1193 images. Measurement consistency was high (ICCs of 0.993; P<0.001). The established 95% reference range for ∠CDH in the neutral fetal position was 118.3° to 137.8°. The ∠CDH method demonstrated superior accuracy over the Ioannou, Wanyonyi, and Roux methods in both groups, with accuracy rates of 94.5% (k values: 0.874, 95%CI: 0.852-0.896) in the pilot group, and 92.6% (k values: 0.838, 95%CI: 0.806-0.871) in the validation group. Conclusion The ∠CDH method has been validated as a highly reproducible and accurate technique for first-trimester fetal position assessment. This sets the stage for its potential future integration into intelligent assessment models.

Integrating crop redistribution and improved management towards meeting China's food demand with lower environmental costs.

China feeds 19.1% of the world's population with 8.6% of the arable land. Here we propose an integrated approach combining crop redistribution and improved management to meet China's food demand in 2030. We simulated the food demand, estimated the national crop production through the productivity of the top 10% of producers in each county, and optimized the spatial distribution of 11 groups of crop types among counties using the data of the top producers. Integrating crop redistribution and improved management increased crop production and can meet the food demand in 2030, while the agricultural inputs (N and P fertilizers and irrigation water) and environmental impacts (reactive N loss and greenhouse gas emissions) were reduced. Although there are significant socio-economic and cultural barriers to implementing such redistribution, these results suggest that integrated measures can achieve food security and decrease negative environmental impacts. County-specific policies and advisory support will be needed to achieve the promises of combining optimization strategies.

Feeding Value Assessment of Substituting Cassava (Manihot esculenta) Residue for Concentrate of Dairy Cows Using an In Vitro Gas Test.

The feeding value of replacing concentrate with cassava (Manihot esculenta) residue in the feed of Holstein cows was confirmed using an in vitro gas test. The treatments consisted of 0% (control, CON), 5%, 10%, 15%, 20%, 25%, and 30% inclusion of cassava residue in fermentation culture medium composed of buffer solution (50 mL) and filtrated rumen fluid (25 mL). The parameters analyzed included the kinetics of gas production and fermentation indexes. Forty-eight hours later, there were no significant differences on in vitro dry matter disappearance (IVDMD), pH, and microbial crude protein (MCP) content among treatments (p > 0.05). However, the "cumulative gas production at 48 h" (GP48), the "asymptotic gas production" (A), and the "maximum gas production rate" (RmaxG) all increased linearly or quadratically (p < 0.01). The GP48 was significantly higher in the 25% treatment compared to the other treatments, except for the 30% (p < 0.01). The A was significantly larger in the 25% treatment compared to the other treatments, except for the 20% and 30% (p < 0.01). The RmaxG was distinctly larger in the 25% treatment compared to other treatments (p < 0.01); moreover, the "time at which RmaxG is reached" (TRmaxG) and the "time at which the maximum rate of substrate degradation is reached" (TRmaxS) were significantly higher in the 25% treatment than the CON, 20%, and 30% treatments (p < 0.01). Additionally, the content of ammonia-N (NH3-N) in all treatments showed linearly and quadratically decreases (p < 0.01), whereas total volatile fatty acid (VFA), iso-butyrate, butyrate, and iso-valerate contents changed quadratically (p = 0.02, p = 0.05, p = 0.01, and p = 0.02, respectively); all of these values peaked in the 25% treatment. In summary, the 25% treatment was associated with more in vitro gas and VFA production, indicating that this cassava residue inclusion level may be used to replace concentrate in the feed of Holstein cows. However, these results need to be verified in vivo.

Molecular characteristics, source contributions, and exposure risks of polycyclic aromatic hydrocarbons in the core city of Central Plains Economic Region, China: Insights from the variation of haze levels.

In this study, molecular characteristics, source contributions, and health risks of polycyclic aromatic hydrocarbons (PAHs) in PM2.5 for four haze levels in Zhengzhou, a megacity in central China with severe air pollution problems, have been analyzed. The concentrations of PAHs and PM2.5 on heavy haze (HH) days were 63% and 122% higher than non-haze (NH) days. The occurrence of high PAH concentration was often accompanied by the northwest wind along with adverse meteorological conditions that limit regional dispersion. The source apportionment results indicated that almost all sources contributed more PAH concentration on haze days. In particular, coal combustion and vehicle emissions contributions were almost doubled on HH days. The incremental lifetime cancer risk (ILCR) of PAHs has been assessed. BaP and DahA showed relatively high contributions to ILCR, and 31%-48% of ILCR is due to exposure to PAHs on high HH days.

Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm.

The accurate prediction of carbon prices poses a tremendous challenge to relevant industry practitioners and governments. This paper proposes a novel hybrid model incorporating modified ensemble empirical mode decomposition (MEEMD) and long short-term memory (LSTM) optimized by the improved whale optimization algorithm (IWOA). This model is based on the nonlinear and non-stationary characteristics of carbon price. The original carbon price is first decomposed into nine intrinsic mode functions (IMFs) and a residual using the MEEMD model. Then, the random forest method is applied to determine the input variables of each IMF and the residual, in the LSTM neural network. The carbon price is then predicted by the LSTM model optimized by the IWOA. The proposed hybrid model is applied to predict the carbon prices of Beijing, Fujian, and Shanghai to assess its effectiveness. The results reveal that the model achieved higher prediction performance than 11 other benchmark models. Our observations indicate that decomposition of carbon price can effectively improve the accuracy of prediction. Moreover, the improved LSTM model is more suitable for time series prediction. The proposed model provides a novel and effective carbon price forecasting tool for governments and enterprises.

Multi-task learning for quality assessment of fetal head ultrasound images.

It is essential to measure anatomical parameters in prenatal ultrasound images for the growth and development of the fetus, which is highly relied on obtaining a standard plane. However, the acquisition of a standard plane is, in turn, highly subjective and depends on the clinical experience of sonographers. In order to deal with this challenge, we propose a new multi-task learning framework using a faster regional convolutional neural network (MF R-CNN) architecture for standard plane detection and quality assessment. MF R-CNN can identify the critical anatomical structure of the fetal head and analyze whether the magnification of the ultrasound image is appropriate, and then performs quality assessment of ultrasound images based on clinical protocols. Specifically, the first five convolution blocks of the MF R-CNN learn the features shared within the input data, which can be associated with the detection and classification tasks, and then extend to the task-specific output streams. In training, in order to speed up the different convergence of different tasks, we devise a section train method based on transfer learning. In addition, our proposed method also uses prior clinical and statistical knowledge to reduce the false detection rate. By identifying the key anatomical structure and magnification of the ultrasound image, we score the ultrasonic plane of fetal head to judge whether it is a standard image or not. Experimental results on our own-collected dataset show that our method can accurately make a quality assessment of an ultrasound plane within half a second. Our method achieves promising performance compared with state-of-the-art methods, which can improve the examination effectiveness and alleviate the measurement error caused by improper ultrasound scanning.

Global environmental costs of China's thirst for milk.

China has an ever-increasing thirst for milk, with a predicted 3.2-fold increase in demand by 2050 compared to the production level in 2010. What are the environmental implications of meeting this demand, and what is the preferred pathway? We addressed these questions by using a nexus approach, to examine the interdependencies of increasing milk consumption in China by 2050 and its global impacts, under different scenarios of domestic milk production and importation. Meeting China's milk demand in a business as usual scenario will increase global dairy-related (China and the leading milk exporting regions) greenhouse gas (GHG) emissions by 35% (from 565 to 764 Tg CO2eq ) and land use for dairy feed production by 32% (from 84 to 111 million ha) compared to 2010, while reactive nitrogen losses from the dairy sector will increase by 48% (from 3.6 to 5.4 Tg nitrogen). Producing all additional milk in China with current technology will greatly increase animal feed import; from 1.9 to 8.5 Tg for concentrates and from 1.0 to 6.2 Tg for forage (alfalfa). In addition, it will increase domestic dairy related GHG emissions by 2.2 times compared to 2010 levels. Importing the extra milk will transfer the environmental burden from China to milk exporting countries; current dairy exporting countries may be unable to produce all additional milk due to physical limitations or environmental preferences/legislation. For example, the farmland area for cattle-feed production in New Zealand would have to increase by more than 57% (1.3 million ha) and that in Europe by more than 39% (15 million ha), while GHG emissions and nitrogen losses would increase roughly proportionally with the increase of farmland in both regions. We propose that a more sustainable dairy future will rely on high milk demanding regions (such as China) improving their domestic milk and feed production efficiencies up to the level of leading milk producing countries. This will decrease the global dairy related GHG emissions and land use by 12% (90 Tg CO2eq reduction) and 30% (34 million ha land reduction) compared to the business as usual scenario, respectively. However, this still represents an increase in total GHG emissions of 19% whereas land use will decrease by 8% when compared with 2010 levels, respectively.

FUIQA: Fetal Ultrasound Image Quality Assessment With Deep Convolutional Networks.

The quality of ultrasound (US) images for the obstetric examination is crucial for accurate biometric measurement. However, manual quality control is a labor intensive process and often impractical in a clinical setting. To improve the efficiency of examination and alleviate the measurement error caused by improper US scanning operation and slice selection, a computerized fetal US image quality assessment (FUIQA) scheme is proposed to assist the implementation of US image quality control in the clinical obstetric examination. The proposed FUIQA is realized with two deep convolutional neural network models, which are denoted as L-CNN and C-CNN, respectively. The L-CNN aims to find the region of interest (ROI) of the fetal abdominal region in the US image. Based on the ROI found by the L-CNN, the C-CNN evaluates the image quality by assessing the goodness of depiction for the key structures of stomach bubble and umbilical vein. To further boost the performance of the L-CNN, we augment the input sources of the neural network with the local phase features along with the original US data. It will be shown that the heterogeneous input sources will help to improve the performance of the L-CNN. The performance of the proposed FUIQA is compared with the subjective image quality evaluation results from three medical doctors. With comprehensive experiments, it will be illustrated that the computerized assessment with our FUIQA scheme can be comparable to the subjective ratings from medical doctors.

Assessment of Ruminal Bacterial and Archaeal Community Structure in Yak (Bos grunniens).

The aim of this study was to determine the microbial community composition in the rumen of yaks under different feeding regimes. Microbial communities were assessed by sequencing bacterial and archaeal 16S ribosomal RNA gene fragments obtained from yaks (Bos grunniens) from Qinghai-Tibetan Plateau, China. Samples were obtained from 14 animals allocated to either pasture grazing (Graze), a grazing and supplementary feeding regime (GSF), or an indoor feeding regime (Feed). The predominant bacterial phyla across feeding regimes were Bacteroidetes (51.06%) and Firmicutes (32.73%). At genus level, 25 genera were shared across all samples. The relative abundance of Prevotella in the graze and GSF regime group were significantly higher than that in the feed regime group. Meanwhile, the relative abundance of Ruminococcus was lower in the graze group than the feed and GSF regime groups. The most abundant archaeal phylum was Euryarchaeota, which accounted for 99.67% of the sequences. Ten genera were detected across feeding regimes, seven genera were shared by all samples, and the most abundant was genus Methanobrevibacter (91.60%). The relative abundance of the most detected genera were similar across feeding regime groups. Our results suggest that the ruminal bacterial community structure differs across yak feeding regimes while the archaeal community structures are largely similar.

[Research Progress of Medical Ultrasound Assessment of Placental Function].

Our country has been using maturity grading method, which was proposed by Grammum in 1979, to evaluate the placental function. However, this method is subjective to consequence because it totally depends on the observation and experiences of clinicians. With the development of ultrasound technology, therefore, we reviewed more novel applications in other aspects of placenta (such as blood flow, vascularization, etc). Over the past years, scholars in the world have done a lot of research around these topics. In this review we introduce placental maturity grading with B-mode ultrasound, placental vascularization qualitative and quantitative analysis with three-dimensional Doppler ultrasound and placental volume measurement, respectively.

Assessment criteria for rotated stereociliary bundles in the guinea pig cochlea.

OBJECTIVE: Our study examined the relationship between variant stereociliary bundles of cochlear outer hair cells (OHCs) and auditory function to analyze assessment criteria for rotated stereociliary bundles in the guinea pig cochlea. METHODS: Auditory brainstem response and distortion product otoacoustic emission (DPOAE) were recorded on 100 guinea pigs. Variant hair cells were identified and counted by scanning electron and light microscopy. RESULTS: The most common variation observed was rotation of stereociliary bundles in the first-row OHCs (OHC1), with most 13.3% variant OHC1 rotated 90 degrees and a few 2.5% rotated 180 degrees. Occasionally, the length and angle of the 2 arms of an OHC deviated from the norm. The auditory brainstem response threshold of affected animals increased only slightly, 20- to 30-dB sound pressure level. More importantly, amplitude of DPOAE increased significantly (40.5 dB sound pressure level). CONCLUSION: Our study suggests that rotation of stereociliary bundles in the cochlear OHC was found to be prevalent in 28% of the animals. We established the assessment criteria for rotated stereociliary bundles that were more than 10% OHC1 rotated. This hair bundle seemed to be rotated by 90 degrees from the normal orientation and was accompanied with changes of auditory function. Increased amplitude of DPOAE is associated with the variation of rotated OHC that might result in hearing loss.