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Ultrasound imaging plays a pivotal role in assessing fetal health and diagnosing diseases. However, the inherent challenges posed by the high similarity of certain fetal anatomical structures and noise in ultrasound images hinder the accurate identification of ultrasound planes. To address this challenge, we present a graph-enhanced ensembles of multi-scale structure perception architecture for more precise identification of standard ultrasound planes. Specifically, we introduce a local-to-global multi-granularity ensemble module for feature enhancement and noise suppression, coupled with a graph-based multi-view refinement module to perceive relationships within fetal anatomical structures. Additionally, we employ multiple classifiers with branch subnets to capture fine-grained structure representations and integrate a confidence evaluation loss to ensure alignment with the true distribution. Finally, the collaborative decision-making among classifiers is achieved through confidence matching. Extensive experiments demonstrate that our innovative framework achieves state-of-the-art classification performance on multiple datasets, and verify that the improvements benefit from the proposed modules. We also show that our method has outstanding capabilities in evaluating the quality of fetal ultrasound planes, a distinctive attribute absent in current methods.

In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essential foundation for diagnosing congenital heart disease. Previous studies have mostly focused on the detection of adult CCs, which may not be applicable to the fetus. In clinical practice, localization of SCCs needs to recognize end-systole (ES) and end-diastole (ED) frames accurately, ensuring that every frame in the cycle is a standard view. Most existing methods are not based on the detection of key anatomical structures, which may not recognize irrelevant views and background frames, results containing non-standard frames, or even it does not work in clinical practice. We propose an end-to-end hybrid neural network based on an object detector to detect SCCs from fetal ultrasound videos efficiently, which consists of 3 modules, namely Anatomical Structure Detection (ASD), Cardiac Cycle Localization (CCL), and Standard Plane Recognition (SPR). Specifically, ASD uses an object detector to identify 9 key anatomical structures, 3 cardiac motion phases, and the corresponding confidence scores from fetal ultrasound videos. On this basis, we propose a joint probability method in the CCL to learn the cardiac motion cycle based on the 3 cardiac motion phases. In SPR, to reduce the impact of structure detection errors on the accuracy of the standard plane recognition, we use XGBoost algorithm to learn the relation knowledge of the detected anatomical structures. We evaluate our method on the test fetal ultrasound video datasets and clinical examination cases and achieve remarkable results. This study may pave the way for clinical practices. © 2013 IEEE.

Accurate recognition of fetal anatomical structure is a pivotal task in ultrasound (US) image analysis. Sonographers naturally apply anatomical knowledge and clinical expertise to recognizing key anatomical structures in complex US images. However, mainstream object detection approaches usually treat each structure recognition separately, overlooking anatomical correlations between different structures in fetal US planes. In this work, we propose a Fetal Anatomy Reasoning Network (FARN) that incorporates two kinds of relationship forms: a global context semantic block summarized with visual similarity and a local topology relationship block depicting structural pair constraints. Specifically, by designing the Adaptive Relation Graph Reasoning (ARGR) module, anatomical structures are treated as nodes, with two kinds of relationships between nodes modeled as edges. The flexibility of the model is enhanced by constructing the adaptive relationship graph in a data-driven way, enabling adaptation to various data samples without the need for predefined additional constraints. The feature representation is further enhanced by aggregating the outputs of the ARGR module. Comprehensive experimental results demonstrate that FARN achieves promising performance in detecting 37 anatomical structures across key US planes in tertiary obstetric screening. FARN effectively utilizes key relationships to improve detection performance, demonstrates robustness to small-scale, similar, and indistinct structures, and avoids some detection errors that deviate from anatomical norms. Overall, our study serves as a resource for developing efficient and concise approaches to model inter-anatomy relationships. IEEE

Accurate segmentation of the thyroid gland in ultrasound images is an essential initial step in distinguishing between benign and malignant nodules, thus facilitating early diagnosis. Most existing deep learning -based methods to segment thyroid nodules are learned from only a single view or two views, which limits the performance of segmenting nodules at different scales in complex ultrasound scanning environments. To address this limitation, this study proposes a multi -view learning model, abbreviated as MLMSeg. First, a deep convolutional neural network is introduced to encode the features of the local view. Second, a multichannel transformer module is designed to capture long-range dependency correlations of global view between different nodules. Third, there are semantic relationships of structural view between features of different layers. For example, low-level features and high-level features are endowed with hidden relationships in the feature space. To this end, a cross -layer graph convolutional module is proposed to adaptively learn the correlations of high-level and low-level features by constructing graphs across different layers. In addition, in the view fusion, a channel -aware graph attention block is devised to fuse the features from the aforementioned views for accurate segmentation of thyroid nodules. To demonstrate the effectiveness of the proposed method, extensive comparative experiments were conducted with 14 baseline methods. MLMSeg achieved higher Dice coefficients (92.10% and 83.84%) and Intersection over Union scores (86.60% and 73.52%) on two different thyroid datasets. The exceptional segmentation capability of MLMSeg for thyroid nodules can greatly assist in localizing thyroid nodules and facilitating more precise measurements of their transverse and longitudinal diameters, which is of significant clinical relevance for the diagnosis of thyroid nodules.

BackgroundNitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China.ResultsA total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R2) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R2 ranging from 0.58 to 0.63, while the R2 of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction.ConclusionThe results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR

The transition period is the stage of the high incidence of metabolic and infectious diseases in dairy cows. Improving transition dairy cows’ health is crucial for the industry. This study aimed to determine the effects of dietary supplementation medium-chain fatty acids (MCFAs) on immune function, metabolic status, performance of transition dairy cows. Twenty multiparous Holstein cows randomly assigned to two treatments at 35 d before calving. 1) CON (fed the basal 2) MCFA treatment (basal diet was supplemented at an additional 20 g MCFAs mixture every day) until 70 d after calving. The results showed that the serum amyloid A myeloperoxidase concentrations in the blood of cows in MCFA treatment significantly decreased during the early lactation (from 1 d to 28 d after calving) 0.03, 0.04, respectively) compared with the CON, while the tumor necrosis factor concentration was significantly decreased at 56 d after calving (P = 0.02). In addition, the concentration of insulin in the pre-calving (from 21 d before calving to calving) blood of cows in MCFA treatment was significantly decreased (P = 0.04), and concentration of triglyceride also showed a downward trend at 28 d after calving 0.07). Meanwhile, MCFAs supplementation significantly decreased the concentrations of lithocholic acid, hyodeoxycholic acid, and hyocholic acid in the blood at 1 d calving (P = 0.02, < 0.01, < 0.01, respectively), and the level of hyocholic acid taurocholic acid concentrations (P < 0.01, = 0.01, respectively) decreased dramatically at 14 d after calving. However, compared with the CON, the pre-calving dry matter intake and the early lactation milk yield in MCFA treatment were significantly decreased (P = 0.05, 0.02, respectively). In conclusion, MCFAs supplementation transition diet could improve the immune function and metabolic status of dairy cows, and the health of transition cows might be beneficial from the endocrine status.

Haibo Li,1,2,&ast; Yuan Fang,1,2,&ast; Xu Li,2,&ast; Jingting Chen,1 Yao Xiong,1 Yongzhou Shi,3 Shengli Li,1 Lincai Ye,4 Shoubao Wang,1,&ast; Jianda Zhou2,&ast; 1Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Department of Plastic Surgery, The Third Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 3Department of Neurosurgery, Neihuang Chinese Medicine Hospital, Anyang, People’s Republic of China; 4Department of Thoracic and Cardiovascular Surgery, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shoubao Wang; Jianda Zhou, Email wxldragon198418@163.com; zhoujianda@csu.edu.comAim: The development of microsurgery has greatly advanced vascularized composite allotransplantation (VCA). However, like organ transplantation, VCA is also limited by acute rejection, and concerns regarding long-term survival and function of the transplanted graft. Therefore, it is necessary to elucidate the molecular mechanisms underlying acute rejection caused by VCA, in order to improve patient survival.Methods: Firstly, we used Brown Norway rats and Lewis rats to construct animal model of VCA. Regularly record the appearance changes of all subjects. Specimens were collected for histological examination, microRNAs (miRNAs) sequencing and RT-qPCR verification when acute immune rejection occurred. Then, bioinformatics analysis was employed to predict miRNA related molecules and pathway information. Finally, differentially expressed miRNAs were tested and verified.Results: MiRNAs are small non coding RNA transcripts that regulate gene expression at the post-transcriptional level. Studies have shown that miRNAs are involved in immune regulation and several miRNAs have

Conjugated linoleic acid (CLA) has drawn significant attention in the last two decades for its various potent beneficial effects on human health, such as anticarcinogenic and antidiabetic properties. CLA could be generally found in ruminant products, such as milk. The amount of CLA in ruminant products mainly depends on the diet of the animals. In general, the fat content in the ruminant diet is low, and dietary fat supplementation can be provided to improve rumen activity and the fatty acid (FA) profile of meat and milk. Especially, dietary 18-carbon polyunsaturated FA (C18 PUFA), the dominant fat source for ruminants, can modify the milk FA profile and other components by regulating the ruminal microbial ecosystem. In particular, it can improve the CLA in milk, intensify the competition for metabolic hydrogen for propionate producing pathways and decrease methane formation in the rumen. Therefore, lipid supplementation appears to be a promising strategy to naturally increase the additional nutritional value of milk and contribute to lower methane emissions. Meanwhile, it is equally important to reveal the effects of dietary fat supplementation on rumen fermentation, biohydrogenation (BH) process, feed digestion, and microorganisms. Moreover, several bacterial species and strains have been considered to be affected by C18 PUFA or being involved in the process of lipolysis, BH, CLA, or methane emissions. However, no review so far has thoroughly summarized the effects of C18 PUFA supplementation on milk CLA concentration and methane emission from dairy cows and meanwhile taken into consideration the processes such as the microorganisms, digestibility, rumen fermentation, and BH of dairy cattle. Therefore, this review aims to provide an overview of existing knowledge of how dietary fat affects rumen microbiota and several metabolic processes, such as fermentation and BH, and therefore contributes to functional and low-carbon milk production.

In this study, we aimed to determine the effect of mixed-process methods on the ruminal degradability of whole cottonseed (WCS) both in situ and in vitro, and the effect on the production performance of dairy cows. Eight WCS process methods were tested on the ruminal digestibility, including crush-alkali 1 (CA1), crush-alkali 2 (CA2), crush-alkali 3 (CA3), alkali 1-crush (A1C), alkali 2-crush (A2C), alkali 3-crush (A3C), crush-only (CO), and non-processed. Alkali 1, 2, and 3 indicate the supplementation of alkali to WCS at the dose of 4% on dry matter (DM) base as followed: 4% NaOH, 2% NaOH + 2% CaO, and 2% NaOH + 2% CaCl2 alkaline, respectively. Among all treatments, CA2 showed the highest WCS ruminal degradation in situ and the highest intestinal digestibility of WCS in vitro. Furthermore, an animal experiment was conducted for 60 days on 30 Holstein dairy cows, using a diet without WCS (CON group), a diet containing 8% non-processed WCS (NP group), and a diet containing 8% CA2-treated WCS (CA2 group). The results indicated that the dry matter intake, 4% fat-corrected milk production, milk protein, milk fat, and content of short-chain saturated fatty acid of milk in the CA2 group were significantly higher (P < 0.05) than CON group. Furthermore, DMI, the CLA was significantly greater (P < 0.05) in the CA2 group than the other groups. Additionally, the free gossypol concentration in serum or milk was under safety level in the three groups. Overall, crush and alkalization (NaOH: CaO = 1:1) treatment could improve the utilization of WCS in dairy farms.

High‐yield dairy cows with high‐concentrate diets are more prone to experiencing health problems associated with rumen microbial imbalance. This study assessed the effects of Saccharomyces cerevisiae culture (SC), a food supplement, on ruminal pH, volatile fatty acid (VFA), inflammatory cytokines, and performance of high‐yield dairy cows. Forty Holstein cows with similar characteristics (e.g., milk yield, days of milk, and parity) were randomly divided into two groups: an experimental group fed the basal ration supplemented with the SC of 100 g of SC per cow per day (hour, SC group), and a control group fed the same basal ration diet without SC (i.e., CON group). On average, the supplementation of SC started at 73 days of lactation. The experimental period lasted approximately 70 days (from 18 January to 27 March 2020), including 10 days for dietary adaptation. Milk yield was recorded daily. Rumen fluid and milk samples were collected after 2 h of feeding in the morning of day 0, 15, 30, and 60. The data showed that rumen pH increased (p < 0.05) when cows were provided with SC. On average, the cows in the SC group produced 1.36 kg (p < 0.05) more milk per day than those in the CON group. Milk fat content of cows in the SC group was also higher (4.11% vs. 3.96%) (p < 0.05). Compared with the CON group, the concentration of acetic acid in the rumen fluid of dairy cows in the SC group was significantly higher (p < 0.05). There were no differences (p > 0.05) found in milk protein content and propionic acid between groups. The SC group had a tendency increase in butyric acid (p = 0.062) and total VFA (p = 0.058). The result showed that SC supplementation also enhanced the ratio between acetic and propionic. Most of the mean inflammatory cytokine (IL‐2, IL‐6, γ‐IFN, and TNF‐α) concentrations (p < 0.05) of the SC group were lower than CON group. This study demonstrated that high‐yield cows receiving supplemental SC could produce more milk with higher fat content, have h

Background and Objective: Biometric measurements of fetal head are important indicators for maternal and fetal health monitoring during pregnancy. 3D ultrasound (US) has unique advantages over 2D scan in covering the whole fetal head and may promote the diagnoses. However, automatically segmenting the whole fetal head in US volumes still pends as an emerging and unsolved problem. The challenges that automated solutions need to tackle include the poor image quality, boundary ambiguity, long-span occlusion, and the appearance variability across different fetal poses and gestational ages. In this paper, we propose the first fully-automated solution to segment the whole fetal head in US volumes. Methods: The segmentation task is firstly formulated as an end-to-end volumetric mapping under an encoder-decoder deep architecture. We then combine the segmentor with a proposed hybrid attention scheme (HAS) to select discriminative features and suppress the non-informative volumetric features in a composite and hierarchical way. With little computation overhead, HAS proves to be effective in addressing boundary ambiguity and deficiency. To enhance the spatial consistency in segmentation, we further organize multiple segmentors in a cascaded fashion to refine the results by revisiting context in the prediction of predecessors. Results: Validated on a large dataset collected from 100 healthy volunteers, our method presents superior segmentation performance (DSC (Dice Similarity Coefficient), 96.05%), remarkable agreements with experts. With another 156 volumes collected from 52 volunteers, we ahieve high reproducibilities (mean standard deviation 11.524 mL) against scan variations. Conclusion: This is the first investigation about whole fetal head segmentation in 3D US. Our method is promising to be a feasible solution in assisting the volumetric US-based prenatal studies., Comment: Accepted by Computer Methods and Programs in Biomedicine

The 3D ultrasound (US) entrance inspires a multitude of automated prenatal examinations. However, studies about the structuralized description of the whole fetus in 3D US are still rare. In this paper, we propose to estimate the 3D pose of fetus in US volumes to facilitate its quantitative analyses in global and local scales. Given the great challenges in 3D US, including the high volume dimension, poor image quality, symmetric ambiguity in anatomical structures and large variations of fetal pose, our contribution is three-fold. (i) This is the first work about 3D pose estimation of fetus in the literature. We aim to extract the skeleton of whole fetus and assign different segments/joints with correct torso/limb labels. (ii) We propose a self-supervised learning (SSL) framework to finetune the deep network to form visually plausible pose predictions. Specifically, we leverage the landmark-based registration to effectively encode case-adaptive anatomical priors and generate evolving label proxy for supervision. (iii) To enable our 3D network perceive better contextual cues with higher resolution input under limited computing resource, we further adopt the gradient check-pointing (GCP) strategy to save GPU memory and improve the prediction. Extensively validated on a large 3D US dataset, our method tackles varying fetal poses and achieves promising results. 3D pose estimation of fetus has potentials in serving as a map to provide navigation for many advanced studies., Comment: 9 pages, 6 figures, 2 tables. Accepted by MICCAI 2019

Volumetric ultrasound has great potentials in promoting prenatal examinations. Automated solutions are highly desired to efficiently and effectively analyze the massive volumes. Segmentation and landmark localization are two key techniques in making the quantitative evaluation of prenatal ultrasound volumes available in clinic. However, both tasks are non-trivial when considering the poor image quality, boundary ambiguity and anatomical variations in volumetric ultrasound. In this paper, we propose an effective framework for simultaneous segmentation and landmark localization in prenatal ultrasound volumes. The proposed framework has two branches where informative cues of segmentation and landmark localization can be propagated bidirectionally to benefit both tasks. As landmark localization tends to suffer from false positives, we propose a distance based loss to suppress the noise and thus enhance the localization map and in turn the segmentation. Finally, we further leverage an adversarial module to emphasize the correspondence between segmentation and landmark localization. Extensively validated on a volumetric ultrasound dataset of fetal femur, our proposed framework proves to be a promising solution to facilitate the interpretation of prenatal ultrasound volumes., Comment: Accepted by IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2019

Thin strip with varying thickness, a novel structural and functional material, is fabricated by micro flexible rolling, and has three thickness features including the thicker zone, the thinner zone and the transition zone. Rolling and roll lifting speeds determine the thickness distributions, and have a great influence on the surface roughness, then the final product quality which is of significant importance for thin materials in subsequent processing. In this study, surface roughness alteration of aluminium alloy strips during micro flexible rolling was investigated with considering the influences of rolling speeds, roll lifting speeds, thickness ratios (the ratio of the thicker zone to the thinner zone) and lubrication conditions, and the mechanisms were discussed. The results show that rolling parameters have a significant effect on the alteration of surface roughness from the thicker zone to the thinner zone along the rolling direction. The experimental observations indicate that the surface roughness of thin strips with varying thicknesses presents a decreasing tendency with the increase of contact area results from downward rolling phase along the transition zone, however, it is constantly higher than that in the upward rolling phase.

In this study, SAC305 and SAC305-0.3Ni solder balls were soldered onto Cu, high temperature treated Cu (H-Cu) and graphene coated Cu (G-Cu) substrates, respectively. The microstructure, the interfacial reaction, and the hardness of the solder joints were investigated. The interfacial intermetallic compound (IMC) is Cu6Sn5 in the solder joints of SAC305/Cu, SAC305/H-Cu, and SAC305/G-Cu. With the addition of 0.3 wt% Ni in the SAC305 solder, the interfacial IMC on Cu, H-Cu, and G-Cu transforms from Cu6Sn5 into (Cu, Ni)6Sn5. The thickness of Cu6Sn5 and (Cu, Ni)6Sn5 is the lowest on G-Cu substrate. Meanwhile, smooth (Cu, Ni)6Sn5 interfacial IMC layers are obtained in SAC305-0.3Ni/H-Cu and SAC305-0.3Ni/G-Cu solder joints. Both the SAC305 and the SAC305-0.3Ni solder bulks have the highest β-Sn content and the lowest concentration of eutectic phases on G-Cu substrate. Consequently, the hardness of the solder bulks on G-Cu is lower than that on the other two kinds of substrates., Electronic Components, Technology and Materials

ObjectiveThe impact of forage feeding strategy on growth performance, ruminal fermentation and nutrient digestibility in post-weaning calves was investigated.MethodsForty-five female Holstein calves (body weight [BW] = 79.79±0.38 kg) were enrolled in the 35-d study at one week after weaning and randomly assigned to one of three dietary treatments. All diets were fed as total mixed ration containing 60% (dry matter [DM] basis) of basal starter feed and 40% (DM basis) of forage, but varied in composition of forage source including i) alfalfa (40% DM, AH); ii) alfalfa hay (26.7% DM)+oat hay (13.3% DM; OH); iii) alfalfa hay (26.7% DM)+corn silage (13.3% DM; WS).ResultsDry matter intake was not different among treatment groups (p>0.05). However, BW (p<0.05) and average daily gain (p<0.05) of calves fed AH and OH were greater than WS-fed calves, whereas heart girth was greater in OH-fed calves than those fed AH and WS (p<0.05). Ruminal fermentation parameters including proportion of butyric acid, acetated-to-propionate ratio, concentration of total volatile fatty acid, protozoal protein, bacterial protein, and microbial protein in rumen were the highest in OH (p<0.05) and the lowest in WS. Compared with the AH and WS, feeding oat hay to postweaning calves increased crude protein digestibility (p<0.05), and decreased duration of diarrhea (p<0.05) and fecal index (p<0.05).ConclusionOur results suggested that partially replacing alfalfa hay with oat hay improved ruminal fermentation, nitrogen utilization, and reduced incidence of diarrhea in post-weaning dairy calves.

ObjectiveThe impact of forage feeding strategy on growth performance, ruminal fermentation and nutrient digestibility in post-weaning calves was investigated.MethodsForty-five female Holstein calves (body weight [BW] = 79.79±0.38 kg) were enrolled in the 35-d study at one week after weaning and randomly assigned to one of three dietary treatments. All diets were fed as total mixed ration containing 60% (dry matter [DM] basis) of basal starter feed and 40% (DM basis) of forage, but varied in composition of forage source including i) alfalfa (40% DM, AH); ii) alfalfa hay (26.7% DM)+oat hay (13.3% DM; OH); iii) alfalfa hay (26.7% DM)+corn silage (13.3% DM; WS).ResultsDry matter intake was not different among treatment groups (p>0.05). However, BW (p<0.05) and average daily gain (p<0.05) of calves fed AH and OH were greater than WS-fed calves, whereas heart girth was greater in OH-fed calves than those fed AH and WS (p<0.05). Ruminal fermentation parameters including proportion of butyric acid, acetated-to-propionate ratio, concentration of total volatile fatty acid, protozoal protein, bacterial protein, and microbial protein in rumen were the highest in OH (p<0.05) and the lowest in WS. Compared with the AH and WS, feeding oat hay to postweaning calves increased crude protein digestibility (p<0.05), and decreased duration of diarrhea (p<0.05) and fecal index (p<0.05).ConclusionOur results suggested that partially replacing alfalfa hay with oat hay improved ruminal fermentation, nitrogen utilization, and reduced incidence of diarrhea in post-weaning dairy calves.

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.

With global climate and environment deterioration, the desertification is getting worse and the phenomenon of wind-sand flow frequently occurs in many areas. Hangers of suspension bridges may suffer the impact from wind-sand flow and be damaged. In this study, the riding-type hangers with four strands which are the commonly used hanger of long-span suspension bridges are taken as an example to investigate the influence of wind-sand flow on the hangers. The aerodynamic interference effect can occur among the four strands under the action of wind-sand flow. In order to explore the influence of wind-sand flow on the hangers, the wind-sand flow field around the riding-type hangers of a long-span suspension bridge is simulated within the FLUENT software on the basis of the numerical simulation of computational fluid dynamics. The pressure and velocity contour, aerostatic coefficients and forces produced by the wind-sand flow under different wind attack angle and volume fractions of sand phase are analyzed from the simulation. Results indicate that the forces exerted by the wind-sand flow on riding-type hangers are greater than the forces exerted only by wind. In the wind and wind-sand flow field, the drag and lift coefficients of the front two strands of hangers exhibit minor changes with increasing wind attack angle, whereas those of the back two strands increase first and then decrease to a small value. The volume fraction of the sand phase has an insignificant effect on the drag and lift coefficients, but has a significant effect on the force exerted on the hanger, and the force exerted on the hangers multiplies when the volume fraction of the sand phase multiplies. The results lay a theoretical foundation for the corrosion fatigue analysis of riding-type hangers for large-span suspension bridges under the action of wind-sand flow.

A main cable of a long-span suspension bridge is semi-surrounded by a catwalk during construction. Thus, design parameters of a catwalk may have influences on the galloping stability of a main cable during construction. To study the influence of catwalk design parameters on the galloping of steepled main cables, two main foci have been conducted. Firstly, the aerodynamic coefficients of the catwalk with actual design parameters are obtained by numerical simulation based on computational fluid dynamics (CFD), and the numerical results are compared with those of the previous wind tunnel test. Several typical main cables with different cross sections of a long-span suspension bridge during construction are selected, and their Den Hartog coefficients are obtained based on the numerical simulation considering the aerodynamic influences of the catwalks. Then four typical working conditions of a main cable which have great potential to occur galloping are selected based on the galloping analyze, and their aerodynamic coefficients considering the influence of the catwalk with different design parameters are obtained. The influence of the catwalk design parameters on galloping of the main cables is analyzed based on the Den Hartog criterion. Results indicate that catwalk design parameters have evident influences on aerodynamic coefficients and galloping of the main cables. The parameters of the catwalk which are favorable for suppressing the galloping of the main cables are determined, which establish a good guideline for the galloping-resistant design of the catwalk-main cable system on suspension bridges.

Ting Wang,1 Wei Tao,2 Lei Zhang,3 Shengli Li4,5 1Department of Hematology, 2Department of Neurology, 3Department of Medical Oncology, The Second People’s Hospital of Liaocheng City, 4Department of Hematology, Jining No. 1 People’s Hospital, 5Department of Hematology, Institute of Biotherapy for Hematological Malignancies, The Second Affiliated Hospital of Shandong University, Jining, Shandong, China Abstract: microRNAs are important in cancer biogenesis and development. However, their underlying mechanisms in multiple myeloma (MM) are barely characterized. microRNA-20a (miR-20a) is a member of the microRNA-17-92 cluster. It has been implicated in various cancers, regulating the proliferation and invasion of cancer cells in vitro. Compared with healthy donors, it also has been reported to be elevated in plasma of MM patients. Here, we investigated the function of miR-20a. Our results showed that it promotes proliferation and inhibits apoptosis of MM cells in vitro by inhibiting early growth response protein 2. The effects of miR-20a were also evaluated in MM xenograft models of SCID/NOD mice. Apparent antitumor activity was achieved in xenograft mice injected with miR-20a inhibitor, while mimics of miR-20a significantly promoted tumor growth. These data indicate that miR-20a plays a crucial role in the biology of MM and represents a potential target for novel therapies for MM patients. Keywords: miR-20a, EGR2, multiple myeloma

This study investigated the effects of ensiled mulberry leaves (EML) and sun-dried mulberry fruit pomace (SMFP) on the ruminal bacterial and archaeal community composition of finishing steers. Corn grain- and cotton meal-based concentrate was partially replaced with EML or SMFP. The diets had similar crude protein (CP), neutral detergent fiber (NDF), and metabolizable energy. Following the feeding trial, the steers were slaughtered and ruminal liquid samples were collected to study the ruminal microbiome. Extraction of DNA, amplification of the V4 region of the 16S rRNA gene, and Illumina MiSeq pyrosequencing were performed for each sample. Following sequence de-noising, chimera checking, and quality trimming, an average of 209,610 sequences were generated per sample. Quantitative real-time PCR was performed to examine the selected bacterial species in the rumen. Our results showed that the predominant phyla were Bacteroidetes (43.90%), Firmicutes (39.06%), Proteobacteria (4.31%), and Tenericutes (2.04%), and the predominant genera included Prevotella (13.82%), Ruminococcus (2.51%), Butyrivibrio (2.38%), and Succiniclasticum (2.26%). Compared to the control group, EML and SMFP groups had a higher abundance of total bacteria (p < 0.001); however, the bacterial community composition was similar among the three groups. At the phylum level, there were no significant differences in Firmicutes (p = 0.7932), Bacteroidetes (p = 0.2330), Tenericutes (p = 0.2811), or Proteobacteria (p = 0.0680) levels among the three groups; however, Fibrobacteres decreased in EML (p = 0.0431). At the genus level, there were no differences in Prevotella (p = 0.4280), Ruminococcus (p = 0.2639), Butyrivibrio (p = 0.4433), or Succiniclasticum (p = 0.0431) levels among the groups. Additionally, the dietary treatments had no significant effects on the archaeal community composition in the rumen. Therefore, EML and SMFP supplementation had no significant effects on the ruminal bacterial or ar

Deep neural networks are state-of-the-art models for understanding the content of images, video and raw input data. However, implementing a deep neural network in embedded systems is a challenging task, because a typical deep neural network, such as a Deep Belief Network using 128x128 images as input, could exhaust Giga bytes of memory and result in bandwidth and computing bottleneck. To address this challenge, this paper presents a hardware-oriented deep learning algorithm, named as the Deep Adaptive Network, which attempts to exploit the sparsity in the neural connections. The proposed method adaptively reduces the weights associated with negligible features to zero, leading to sparse feedforward network architecture. Furthermore, since the small proportion of important weights are significantly larger than zero, they can be robustly thresholded and represented using single-bit integers (-1 and +1), leading to implementations of deep neural networks with sparse and binary connections. Our experiments showed that, for the application of recognizing MNIST handwritten digits, the features extracted by a two-layer Deep Adaptive Network with about 25% reserved important connections achieved 97.2% classification accuracy, which was almost the same with the standard Deep Belief Network (97.3%). Furthermore, for efficient hardware implementations, the sparse-and-binary-weighted deep neural network could save about 99.3% memory and 99.9% computation units without significant loss of classification accuracy for pattern recognition applications., Comment: 10 pages, extended and submitted to IEEE Transactions of Systems, Man, and Cybernetics

It is still a challenge to obtain two-photon excited fluorescent bioimaging probes with intense emission, high photo-stability and low cytotoxicity. In the present work, four Zn(II)-coordinated complexes (1-4) constructed from two novel D-A and D-p-A ligands (L-1 and L-2) are investigated both experimentally and theoretically, aiming to explore efficient two-photon probes for bioimaging. Molecular geometry optimization used for theoretical calculations is achieved using the crystallographic data. Notably, the results indicate that complexes 1 and 2 display enhanced two-photon absorption (2PA) cross sections compared to their corresponding D-A ligand (L1). Furthermore, it was found that complex 1 has the advantages of moderate 2PA cross section in the near-infrared region, longer fluorescence lifetime, higher quantum yield, good biocompatibility and enhanced two-photon excited fluorescence. Therefore, complex 1 is evaluated as a bioimaging probe for in vitro imaging of HepG2 cells, in which it is observed under a two-photon scanning microscope that complex 1 exhibits effective co-staining with endoplasmic reticulum (ER) and nuclear membrane; as well as for in vivo imaging of zebrafish larva, in which it is observed that complex 1 exhibits specificity in the intestinal system., Funding Agencies|National Natural Science Foundation of China [51372003, 21271004, 51272001, 51472003, 51432001, 21271003]; Ministry of Education Funded Projects Focus on returned overseas scholar; Program for New Century Excellent Talents in University (China); Doctoral Program Foundation of Ministry of Education of China [20113401110004]; China Postdoctoral Science Foundation [2015M571912]; Swedish Research Council (VR) [621-2013-5357]; Swedish Government strategic faculty grant in materials science (SFO, MATLIU) in Advanced Functional Materials (AFM)

With the deterioration of global climate and environment, the phenomenon of wind-sand flow frequently occurs in many regions. Suspension bridge suspender cables suffer corrosion and impact from wind-sand flow. The riding-type suspender cable with four strands which is commonly used in suspender cables of long-span suspension bridges is taken as an example to investigate the influence of wind-sand flow on the suspender cables. The wind-sand flow field around the suspender cables of a long-span suspension bridge is simulated within the FLUENT software on the basis of the numerical simulation of computational fluid dynamics. The forces produced by the wind-sand flow on the suspender cables are analyzed from the simulation, and then the numerical results and the calculated results based on a theoretical equation which was used to obtain the pressure on a building in a wind-sand area are compared together. Results show there are big differences between them. The reasons will be investigated in future research, and finally a new suitable theoretical equation for the pressure of wind-sand flow on suspender cables will be proposed.

So far, Google Trend data have been used for influenza surveillance in many European and American countries; however, there are few attempts to apply the low-cost surveillance method in Asian developing countries. To investigate the correlation between the search trends and the influenza activity in Asia, we examined the Google query data of four Asian developing countries.

The search engine based on influenza monitoring system has been widely applied in many European and American countries. However, there are not any correlative researches reported for African developing countries. Especially, the countries Egypt has not designed an influenza monitoring system on the basis of the Internet search data. This study aims at analyzing the correlation between the Google search data and the H1N1 morbidity data of Egypt, and examining the feasibility of Google Flu Model in predicting the H1N1 influenza trend.

N-carbazolylacetic acid was synthesized using a new method in a high yield and two carbazolylacetato complexes [Zn(Cabo)-(phen)2ClO4]·0.5C2H5OH and [Cd(Cabo)(phen)2-ClO4] (Cabo=N-carbazolylacetate, phen=1,10-phenanthroline) were synthesized and characterized by elemental analysis, IR, UV–Vis spectra, thermal analyses, photoluminescence measurement and X-ray diffraction studies. Both of the complexes exhibit strong blue emission in solid state as well as high thermal stability and solvent-resistant properties.

The title complex, {[N(CH3)4]2[Cd(SCN)2S]}n, was prepared by self-assembling from the reaction of a methanol/water (volume ratio, 1/1) solution containing cadmium(II) thiocyanate with equivalent amount of tetramethylammonium thiocyanate. The result of single X-ray determination for the complex reveals that a novel polymeric cadmium(II) complex bridged by sulfur and thiocyanato ions was obtained, which formed a two-dimensional (2D) structure.