Search

Objective This study aimed to investigate the quality of life (QOL) of patients with cleft lip and palate and velopharyngeal insufficiency (VPI) in relation to sex, age, age at initial cleft lip surgery, and age at initial cleft palate surgery. Design This is a cross-sectional study. Setting The study was conducted in a tertiary medical center. Participants The participants were caregivers of 72 patients with cleft lip and palate and VPI aged 4 to 20 years. Main Outcome Measure(s) Participants completed the Chinese version of the caregiver report of the VPI Effects on Life Outcomes (VELO) questionnaire. The Mann–Whitney U test was used to evaluate the patients’ sex, age, age at initial cleft lip repair, and age at initial cleft palate repair in relation to VELO total score and domains. Spearman correlation analysis was completed including all study variables. Associations between the study variables and the VELO total score were tested using a generalized linear mixed model. Results In the univariate analysis, patients’ age and age at initial cleft palate surgery influenced the QOL of patients with VPI. There were no differences in the VELO total score or domains based on sex or age at first cleft lip surgery. In the generalized linear mixed model, patients older than 8 years had higher VELO total scores. Conclusions By caregiver report, the QOL of patients under age 8 years with VPI was lower than older patients. In addition, the caregiver impact domain was higher for parents of children who had their initial cleft palate surgery at age 2 years or younger.

Exploration of hypermetabolism in amyotrophic lateral sclerosis (ALS) with different ethnicities is needed to understand its metabolic implications for clinical management. We aimed to evaluate the features of hypermetabolism and investigate its association with clinical characteristics and prognosis of ALS in a prospective Chinese cohort. This prospective study was conducted at Peking University Third Hospital, China from 2017 to 2020. 343 participants were enrolled initially. After strict screening, 147 matched health controls and 93 patients with ALS were eligible and underwent detailed clinical assessments. Disease severity and progression were evaluated using recognized scales. Metabolic assessments included body composition and metabolic index (MI) [hypermetabolism if MI ≥ 120.0%]. Patients were followed up every 6 months for survival analysis. Compared with controls, hypermetabolism was significantly more prevalent in ALS (p = 0.009). MI was consistently higher in ALS than controls (p = 0.009). Further correlation analysis showed that MI significantly decreased with disease progression, as graded by King’s College staging system (p

The ever-increasing demand for new businesses and the continuous development of the Internet economy have increasingly demanded network communications and service capabilities, and the infrastructure and the deriving technology system of the existing network still face a series of major challenges. New network architectures and key technologies have become the core of a new round of technological revolution and industrial upgrading in the world. Therefore, studying the strategic conception and development paths of new network technology innovation becomes an urgent need for China. In this article, we analyze the challenges faced by the current network technology, discuss the development status of new network fields in China and abroad, and summarize the development trend of new network technologies. Subsequently, we summarize the gaps and development goals of China in the new network field. Finally we propose the key technologies for the new network development in China, including new network architecture, network fulldimension definable technology, polymorphic addressing and routing technology, network intelligence technology, and endogenous security structure. From the aspect of technology roadmap, we suggest that an open, integrated, and secure new architecture should be established to build a new network environment that is intelligent, diversified, personalized, robust, and efficient. From the aspect of national policy, we suggest that support policies should be formulated regarding technology research and development, industrial ecology construction, and market access.

As the field of 3D printing continues to enable the fabrication of biomedical materials and devices, there is increasing demand for the development of biocompatible functional materials with tailor...

Burdened with the specialized bearing requirements brought by the deep fusion of the Internet and the economic society, the current Internet is faced with a series of great challenges including intelligence, diversification, personalization, robustness and efficiency because of some defects such as rigid structure, simple bearing structure based on IP, and disability in suppressing unknown threats. This paper proposes to improve the function, performance, efficiency and security of the Internet from the perspective of network architecture, introduces the “structure definability” to all layers of the network, and provides a network architecture with polymorphic presentation of network functions in all layers called Polymorphic Smart Network (PINet). PINet supports full-dimensional definition and polymorphic presentation of addressing and routing, switching mode, interconnection mode, network element, transmission protocol, service properties and so on. Experimental results have verified that PINet supports the incremental evolution of the Internet and fundamentally meets the business requirement of network intelligence, diversification, personalization, high robustness and high efficiency.

Background The clinical significance of lipid profile in gastric cancer remains unclear. The aim of the present study was to investigate the correlation between serum lipid profiles and patient clinical parameters as well as prognosis in gastric cancer. Methods The preoperative plasma lipid profile levels of 358 gastric cancer patients, who were operated in between 2001 and 2009, were retrospectively evaluated, and the correlation between these factors and patient clinical parameters as well as survival were analyzed. Results There was a significant association between serum high-density lipoprotein cholesterol level (HDL-C

Anaplastic lymphoma kinase (ALK) rearrangements have been reported in 5% to 6% of non‐small cell lung cancer (NSCLC) patients. However, the concurrent existence of two ALK fusions within the same patient have rarely previously been reported. Moreover, considering the diversities of ALK mutations, it is necessary to evaluate the response of both double and new types of ALK fusions to ALK‐tyrosine kinase inhibitors (ALK‐TKIs). Here, we report a case of a 64‐year‐old Chinese woman who was diagnosed with lung adenocarcinoma (ADC) who concurrently harbored two types of ALK‐rearrangements, including an unreported NLRC4‐ALK fusion and EML4‐ALK fusion. After surgery, the patient had a progression‐free survival (PFS) of over 10 months with continuous crizotinib treatment after surgery. Our findings provide a better understanding of ALK‐TKI in patients with two novel ALK concomitant fusions. Key points A lung adenocarcinoma patient harboring concurrent NLRC4‐ALK and EML4‐ALK fusion mutations benefited from crizotinib after surgery. Our findings provide important information for future treatment decision‐making in patients with double ALK fusions.

Scholarly accounts of the global rise of statistical credit scoring technologies have tended to portray these automated, digitised systems as supplanting human involvement in lending. This paper ex...

Using the advantages of web crawlers in data collection and distributed storage technologies, we accessed to a wealth of forestry-related data. Combined with the mature big data technology at its present stage, Hadoop’s distributed system was selected to solve the storage problem of massive forestry big data and the memory-based Spark computing framework to realize real-time and fast processing of data. The forestry data contains a wealth of information, and mining this information is of great significance for guiding the development of forestry. We conducts co-word and cluster analyses on the keywords of forestry data, extracts the rules hidden in the data, analyzes the research hotspots more accurately, grasps the evolution trend of subject topics, and plays an important role in promoting the research and development of subject areas. The co-word analysis and clustering algorithm have important practical significance for the topic structure, research hotspot or development trend in the field of forestry research. Distributed storage framework and parallel computing have greatly improved the performance of data mining algorithms. Therefore, the forestry big data mining system by big data technology has important practical significance for promoting the development of intelligent forestry.

Background Lymphovascular invasion (LVI) is a vital risk factor for prognosis across cancers. We aimed to develop a scoring system for stratifying LVI risk in patients with breast cancer. Methods A total of 301 consecutive patients (mean age, 49.8 ± 11.0 years; range, 29–86 years) with breast cancer confirmed by pathological reports were retrospectively evaluated at the authors’ institution between June 2015 and October 2018. All patients underwent contrast-enhanced Magnetic Resonance Imaging (MRI) examinations before surgery. MRI findings and histopathologic characteristics of tumors were collected for analysis. Breast LVI was confirmed by postoperative pathology. We used a stepwise logistic regression to select variables and two cut-points were determined to create a three-tier risk-stratification scoring system. The patients were classified as having low, moderate and high probability of LVI. The area under the receiver operating characteristic curve (AUC) was used to evaluate the discrimination ability of the scoring system. Results Tumor margins, lobulation sign, diffusion-weighted imaging appearance, MRI-reported axillary lymph node metastasis, time to signal intensity curve pattern, and HER-2 were selected as predictors for LVI in the point-based scoring system. Patients were considered at low risk if the score was Conclusion This study shows that a simple and reliable score-based risk-stratification system can be practically used in stratifying the risk of LVI in breast cancer.

Tucker decomposition can provide an intuitive summary to understand brain function by decomposing multi-subject fMRI data into a core tensor and multiple factor matrices, and was mostly used to extract functional connectivity patterns across time/subjects using orthogonality constraints. However, these algorithms are unsuitable for extracting common spatial and temporal patterns across subjects due to distinct characteristics such as high-level noise. Motivated by a successful application of Tucker decomposition to image denoising and the intrinsic sparsity of spatial activations in fMRI, we propose a low-rank Tucker-2 model with spatial sparsity constraint to analyze multi-subject fMRI data. More precisely, we propose to impose a sparsity constraint on spatial maps by using an lp norm (0

Recently, object trackers based on Siamese networks have attracted considerable attentions due to their remarkable tracking performance and widespread application. Especially, the anchor-based methods exploit the region proposal subnetwork to get accurate prediction of a target and make great performance improvement. However, those trackers cannot capture the spatial information very well and the pre-defined anchors will hinder robustness. To solve these problems, we propose a Siamese-based anchor-free object tracking algorithm with multiscale spatial attentions in this paper. Firstly, we take ResNet-50 as the backbone network to generate multiscale features of both template patch and search regions. Secondly, we propose the spatial attention extraction (SAE) block to capture the spatial information among all positions in the template and search region feature maps. Thirdly, we put these features into the SAE block to get the multiscale spatial attentions. Finally, an anchor-free classification and regression subnetwork is used for predicting the location of the target. Unlike anchor-based methods, our tracker directly predicts the target position without predefined parameters. Extensive experiments with state-of-the-art trackers are carried out on four challenging visual object tracking benchmarks: OTB100, UAV123, VOT2016 and GOT-10k. Those experimental results confirm the effectiveness of our proposed tracker.

Purpose: Studies involving mouse models and human uterine smooth muscle cells have shown that phenylephrine inhibits uterine contractions in non-pregnant mice and human in vitro cell via cyclic adenosine monophosphate (cAMP) signaling. However, there has been no limited exploration to date of the effect of phenylephrine on uterine contractions in clinical practice. This study aimed to compare the dose requirement of oxytocin with or without the infusion of prophylactic phenylephrine to prevent post spinal hypotension during cesarean delivery under combined spinal and epidural anesthesia.Methods: This was a double-blinded, single-center, randomized, control study. One hundred and sixty pregnant patients provided informed consent and were randomly allocated to the phenylephrine (phenylephrine infusion) and control (saline infusion) groups. Patients randomized to the phenylephrine group received an intravenous prophylactic phenylephrine infusion at a fixed rate of 0.5 μg/kg/min. The control group received a saline placebo at the same rate and used the same apparatus for delivery. After neonatal delivery and clamping of the umbilical cord, patients received a standard institutional oxytocin protocol. The primary outcome measure was the total dose of oxytocin administered during CD. Secondary outcomes including the proportion (%) of patients requiring a secondary uterotonic agent and estimated blood loss (EBL) in the first 24 h after surgery.Results: The median oxytocin dose administered was significantly higher in the phenylephrine group than in the control group [6.9 ± 2.5 international standardized units (IU) vs. 5.4 ± 2.4 IU, p = 0.0004]. The number of patients that required a secondary uterotonic agent was significantly higher in the phenylephrine group than in the control group (24.2% vs. 9.1%; p = 0.034). The EBL in the first 24-h postoperatively was similar between the two groups (467 ± 47 ml vs. 392 ± 38 ml; p = 0.22).Conclusions: Prophylactic infusion of phenylephrine used to prevent post-spinal hypotension during CD was associated with a higher dose of oxytocin. This has important clinical implications, as the suboptimal use of oxytocin is associated with an increased risk of postpartum hemorrhage and increased maternal morbidity and mortality. Further studies are now needed to confirm these findings.

With the comprehensive completion of the ‘Full Coverage, Full Collection’ construction of the electricity information collection system and the development of various business applications, there are higher requirements for user-side power consumption information data exchange efficiency, access capability and real-time performance. Therefore, there is an urgent need to study information transmission optimization methods on the user side, so as to improve the energy efficiency of the system and save resources. This article first sorts out the characteristics of user-side measurement data in the Energy Internet. According to the object-oriented characteristics, it gives the user-side electricity information communication protocol layered structure. Finally, this paper proposes an optimization method for user-side measurement information transmission based on compressed sensing, compares different compression schemes, and the validity of the algorithms applicated in the transmission of electricity information data is verified.

Background: Alzheimer's disease (AD) currently lacks a cure. Because substantial neuronal damage usually occurs before AD is advanced enough for diagnosis, the best hope for disease-modifying AD therapies likely relies on early intervention or even prevention, and targeting multiple pathways implicated in early AD pathogenesis rather than focusing exclusively on excessive production of β-amyloid (Aβ) species. Methods: Coniferaldehyde (CFA), a food flavoring and agonist of NF-E2-related factor 2 (Nrf2), was selected by multimodal in vitro screening, followed by investigation of several downstream effects potentially involved. Furthermore, in the APP/PS1 AD mouse model, the therapeutic effects of CFA (0.2 mmol kg-1d-1) were tested beginning at 3 months of age. Behavioral phenotypes related to learning and memory capacity, brain pathology and biochemistry, including Aβ transport, were assessed at different time intervals. Results: CFA promoted neuron viability and showed potent neuroprotective effects, especially on mitochondrial structure and functions. In addition, CFA greatly enhanced the brain clearance of Aβ in both free and extracellular vesicle (EV)-contained Aβ forms. In the APP/PS1 mouse model, CFA effectively abolished brain Aβ deposits and reduced the level of toxic soluble Aβ peptides, thus eliminating AD-like pathological changes in the hippocampus and cerebral cortex and preserving learning and memory capacity of the mice. Conclusion: The experimental evidence overall indicated that Nrf2 activation may contribute to the potent anti-AD effects of CFA. With an excellent safety profile, further clinical investigation of coniferaldehyde might bring hope for AD prevention/therapy.

Flexible electronics are being broadly explored for their potentially extensive applications in various sectors, such as the internet-of-things. Among these electronic devices, flexible touch sensors play a leading role in soft touch screens and other human-machine interface technologies. Here, we report that by integrating triboelectric field-effect touch sensors with single-walled carbon nanotubes, touch sensitivity can be enhanced; the response of this device is almost 5 times greater than our previously reported devices. This high performance enables this type of flexible sensors to be made into touch panels.

We demonstrate a simple, nonlithographic method for fabricating piezoresistive pressure sensors with a broad range of working pressures and low detection limit. Our wearable pressure sensor is fabr...

Background: Community acquired pneumonia (CAP) in children is one of the common clinical diseases and infectious diseases threatening the health of the population. CAP has complicated causes, closely related to region, season, age, and primary disease. It is the most common cause of children being hospitalized and the first cause of death for children under 5 years old. At present, the clinical treatment is mainly antibiotics, but abuse and non-standard combination of antibiotics have led to increasing antibiotic resistance. Anerning Granules have the functions of clearing away heat and removing wind, reducing phlegm and relieving cough, and improving cough symptoms and lung signs. Thus, this study aims to evaluate the efficacy and safety of Anerning Granules (AEN) in the treatment of community-acquired pneumonia in children, and to explore whether AEN can reduce the use of antibiotics and have a good effect on the clinical treatment of CAP.Methods and analysis: this study, a randomized, double-blind, single-dummy, parallel control of placebo, multicenter clinical study will be established in 7 hospitals in the same period. A total of 216 patients with community-acquired pneumonia will be randomly allocated at a ratio of 2:1 to two groups: experimental group, control group. The experimental group receives Anerning Granules plus ceftriaxone sodium; the control group receives AEN placebo plus ceftriaxone sodium. Each group will be treated for ten days, and a stage effect evaluation will be conducted on the sixth day. The primary outcome is the end of antibiotics in frequency (DDDs) and effective rate. Secondary outcome measures of effectiveness are the full fever time, sore throat onset time, and safety assessment. Outcomes will be assessed at baseline and after treatment. In addition, adverse events will be monitored throughout the trial process and must be traced to be resolved.Discussion: This study protocol will provide the research data regarding the efficacy and safety of AEN for the treatment of community-acquired pneumonia in children. The first aim is to determine whether Anerning Granules can reduce the use of antibiotics; the second aim is to evaluate the effectiveness of Anerning Granules combined with ceftriaxone sodium in the treatment of children with community-acquired pneumonia. The third aim is to observe the safety of clinical application of Anerning Granules. The results of this study will improve the rational use of drugs, especially the rational application of antibiotics. It will also enable safety evaluation from laboratory indices of adverse events, which will provide reliable evidence for clinical treatment.Trial registration: Clinicaltrials.gov identifier: NCT03675178, registered on 16 September 2018.

Tucker decomposition (TKD) has been utilized to identify functional connectivity patterns using processed fMRI data, but seldom focuses on originally acquired fMRI data. This study proposes to decompose multi-subject fMRI data in a natural three-way of voxel × time × subject via TKD. Different from existing tensor decomposition algorithms such as canonical polyadic decomposition (CPD) for extracting shared spatial maps (SMs), we propose to extract both shared and individual SMs by exploring spatial-temporal-subject relationship contained in the core tensor. We test the proposed method using multi-subject resting-state fMRI data with comparison to CPD for evaluating shared SMs and independent vector analysis (IVA) for assessing individual SMs under different model orders. The results show that the proposed method yields better and more robust shared SMs than CPD and more consistent individual SMs than IVA, indicating the potential of TKD in providing group and individual brain networks in a high-dimensional coupling way.

Heng Zhao,1,* Li-Dan Zhang,2,* Li-Fang Liu,1 Chun-Qing Li,3 Wei-Li Song,3 Yong-Yang Pang,1 Yun-Liang Zhang,1 Dan Li4 1Endocrinology Laboratory, The First Central Hospital of Baoding, Baoding, Hebei Province, 071000, People’s Republic of China; 2Department of Nuclear Medicine, The First Central Hospital of Baoding, Baoding, Hebei Province, 071000, People’s Republic of China; 3Outpatient Department, The First Central Hospital of Baoding, Baoding, Hebei Province, 071000, People’s Republic of China; 4Department of Ophthalmology, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Dan LiDepartment of Ophthalmology, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of ChinaTel +86 189 31251885Fax +86 031 25981539Email drli_ld@163.comYun-Liang ZhangEndocrinology Laboratory, The First Central Hospital of Baoding, Baoding, Hebei Province, 071000, People’s Republic of ChinaTel +86 137 31251133Fax +86 0312-5976520Email zyl_zhang98@163.comPurpose: This study aimed to describe the levels of glycated hemoglobin (HbA1c), D-dimer (D-D), and fibrinogen (FIB) in different types of diabetic retinopathy (DR).Methods: A total of 61 patients with diabetes, who were treated in our department between November 2017 and May 2019, were selected. According to their non-mydriatic fundus photography and fundus angiography results, patients were divided into three groups, ie, the non-DR (NDR) group (n=23), the non-proliferative DR (NPDR) group (n=17), and the proliferative DR (PDR) group (n=21). A control group of 20 people who had tested negative for diabetes was also included. The levels of HbA1c, D-D, and FIB were measured and compared, respectively.Results: The mean values of HbA1c were 6.8% (5.2%, 7.7%), 7.4% (5.8%, 9.0%), and 8.5% (6.3%, 9.7%) in the NDR, NPDR, and PDR groups, respectively. The control group values were 4.9% (4.1%, 5.8%). These results indicated a significant statistical difference between groups. The mean values of D-D were 0.39 ± 0.21 mg/L, 1.06 ± 0.54 mg/L, and 1.39 ± 0.59 mg/L in the NDR, NPDR, and PDR groups, respectively. The control group result was 0.36 ± 0.17 mg/L. The values of the NPDR and PDR groups were significantly higher than those of the NDR and control groups, and the value of the PDR group was significantly higher than that of the NPDR group, indicating a significant difference between the groups (P < 0.001). The mean values of FIB were 3.07 ± 0.42 g/L, 4.38 ± 0.54 g/L, and 4.46 ± 1.09 g/L in the NDR, NPDR, and PDR groups, respectively. The control group result was 2.97 ± 0.67 g/L. The difference between the groups was statistically significant (P < 0.05).Conclusion: Blood levels of HbA1c, D-D, and FIB in the PDR group were significantly higher than in the NPDR group.Keywords: glycated hemoglobin, HbA1c, D-dimer, D-D, fibrinogen, FIB, diabetic retinopathy, DR, microangiopathy

Metformin is the first-line anti-diabetic drug for type 2 diabetes. It has been found to significantly reduce liver aminotransferase in nonalcoholic fatty liver disease (NAFLD). However, whether metformin improves NAFLD progression remains controversial. Sirtuin 1 (SIRT1), an NAD+-dependent deacetylase, plays a vital role in hepatic steatosis and inflammation. Here, we investigated the effect of metformin on steatohepatitis and the role of SIRT1 in diet-induced obese (DIO) mice. The results showed that metformin significantly reduced body weight and fat mass of DIO mice. In addition, metformin also alleviated adiposity and hepatic steatosis, and greatly upregulated uncoupling protein 1 (UCP1) expression in adipose tissues of DIO mice. Unexpectedly, the effects of metformin on reducing body weight and alleviating hepatic steatosis were not impaired in Sirt1 heterozygous knockout (Sirt1+/−) mice. However, SIRT1-deficiency remarkably impaired the effects of metformin on lowering serum transaminases levels, downregulating the mRNA expression of proinflammatory factors, and increasing the protein level of hepatic Cholesterol 25-Hydroxylase (CH25H), a cholesterol hydroxylase in cholesterol catabolism. In summary, we demonstrated that metformin alleviates steatohepatitis in a SIRT1-dependent manner, and modulation of M1 polarization and cholesterol metabolism may be the underlying mechanism.

A dual-layer dual-anisotropic conductive Janus-structural film (DDCJF) with magnetism and green luminescence is fabricated by electrospinning. Two layers are tightly bonded together into DDCJF. The top layer is Janus-structural film with left and right structure using Janus nanobelt as building unit, and bottom layer is non-array film using nanofiber as building unit. In top layer, the nanobelts in the left and right regions are arranged vertically, which leads to mutually perpendicular of conducting directions, thus forming the dual-anisotropic conduction. DDCJF has adjustable magnetism, luminescence and dual-anisotropic conductivity. On the micro level, using Janus nanobelts as building units renders DDCJF excellent fluorescence properties and high degree of anisotropy. Macroscopically, the design of dual-layer structure can avoid the performance influence between top and bottom layers. The property of each layer of DDCJF is relatively independent due to the peculiar duallayer Janus structure, successfully realizing integration as well as isolation in the DDCJF.

In order to accurately evaluate the cumulative blasting effect of roadway, an entropy-weighted matter-element extension model was introduced to evaluate the blasting effect. Through the analysis of blasting quality, blasting economic and technical benefits, and blasting safety, 12 indexes such as bulk rate, blasting shape, and explosive consumption were selected to build a comprehensive evaluation model. Then, in order to avoid the uncertainty of subjective weighting method in the evaluation process, the entropy weighting method was introduced to determine the weight coefficient of matter-element index. Finally, the model is applied to the blasting example of Kong Zhuang coal mine, and the grading of blasting effect is evaluated qualitatively and quantitatively. Results show that the evaluation of the model is consistent with the actual grade. In addition, compared with ordinary smooth blasting, cumulative blasting can reduce the explosive consumption by 27%, increase the blasthole utilization rate to 97.1%, and improve the forming quality of roadway.

Background: Transrectal natural orifice specimen extraction (NOSE) is less invasive compare to traditional laparoscopic-assisted anterior resection (LAR). However, psychological evaluation of patients after transrectal LAR-NOSE is needed to evaluate its clinical feasibility. This study aimed to compare patient outcomes between LAR and LAR-NOSE.Methods: We studied 215 patients with colorectal cancer who underwent surgery between June 2015 and April 2018; they were randomized into two groups: LAR-NOSE (n=109) and LAR (n=106). Data on pain, anxiety, and depression were collected and compared. Pain was assessed by a visual analogue scale (VAS) and anxiety and depression by the self-rating anxiety scale (SAS), self-rating depression scale (SDS), and state-trait anxiety inventory. The overall survival and 5-year disease-free survival (DFS) rates were noted.Results: The extraction success rate in the LAR-NOSE group was 87.1% (95/109 cases). The LAR-NOSE SAS (44.21 ± 8.46) and SDS (37.29 ± 8.98) scores were significantly lower than the LAR scores (51.04 ± 9.12 and 44.65 ± 9.27, respectively; PPPConclusion: patients in the LAR-NOSE group showed better outcomes related to postoperative anxiety and depression, postoperative complications, and short-term postoperative recovery. Our results suggest transrectal NOSE as a feasible and potentially preferable method for treatment in selected patients.Registration No: SHDFYY2015-098 Date:2015.02.01

In order to deal with the curse of dimension caused by diversification, complication and elaboration of wind power data, this paper proposes a nonlinear dimension-reduction and reconstruction method based on the principal of optimal RBF kernel component analysis (ORBF-KPCA), so as to impose accurate burrow the intrinsic features of massive wind power data. Concerning the problem of difficulty in selection of kernel parameters in the traditional KPCA method, this paper searches the optimum kernel parameter to minimize the difference between the dimension-reduced results of raw data and homogenous data by means of a cross-validation method. Then a multi-dimensional scale (MDS) technique based on k-nearest neighbors is used for preimage the reconstruction method. An actual example shows the proposed method is better than the common linear dimension-reduction methods in reliability and continuity of results, and can not only improve forecasting efficiency to avoid the curse of dimension, but also achieve higher prediction accuracy.

Aim: To evaluate the clinical value of plasma D-dimer/fibrinogen ratio (DFR) in patients hospitalized for heart failure (HF). Methods: Clinical data of 235 patients were retrospectively analyzed. Kaplan–Meier method and Cox regression analysis were used to identify significant prognosticators. Results: The Kaplan–Meier analysis showed that a higher DFR level was significantly associated with an increase in the end point outcomes, including HF readmission, thrombotic events and death (log-rank test: p

Accurate and effective short-term power load forecasting (STLF) is very important for power systems Considering the temporal and non-linear characteristics of power load, this paper studies the application of standard long-short term memory (LSTM) network and its two typical variants, the Gated Recurrent Unit (GRU) and the Just Another NETwork (JANET) in STLF. So as to evaluate performance of the LSTMs, this paper compares three networks from prediction accuracy and training time. Furthermore, the hyperparameters of all LSTMs and the selection of training samples and inputs in the standard LSTM are discussed. The results of two actual examples show the LSTMs are all able to achieve accuracy of over 92% for the day-ahead hourly load prediction, but the standard LSTM and GRU have higher accuracy (over 94%), and the JANET has higher efficiency. Also, the optimal input window size is closely related to the power load period, and the prediction accuracy of LSTMs for STLF can be significantly improved through filtering training samples based on day-type or adding the loads of previous day to the inputs.

Background: Metabolic-associated fatty liver disease (MAFLD) refers to abnormal accumulation of fat in the liver for metabolic dysfunction. With modern socioeconomic conditions and changes in dietary patterns, the prevalence of MAFLD is increasing, to the detrimental of children’s learning and quality of life. We investigated the prevalence and influencing factors of metabolic-associated fatty liver disease (MAFLD) in school-aged children and adolescents in Shenyang, China. Methods: In 2019, we collected demographic, anthropometric and liver health assessments from a random sample of Shenyang’ s school-aged children (7-12 years old) and adolescents (13-18 years old). Experienced hepatologists used transient elastography to diagnose the presence of fatty liver in the students. A random subsample was selected to complete a questionnaire to explore the impact of lifestyle habits on fatty liver disease.Results: The overall prevalence of MAFLD in these students was 23.83%, with a non-significant difference between children (22.73%) and adolescents (24.43%). The prevalence of MAFLD was significantly higher among boys than among girls. Compared with non-overweight students, a significantly higher proportion of the overweight group had fatty liver. Moreover, questionnaire responses on exercise habits, normal diet, and parental factors were associated with fatty liver.Conclusions: MAFLD is very prevalent in children and adolescents in Shenyang city. Due to the close relationship between MAFLD and obesity, lifestyle plays a major role in the occurrence of MAFLD.Trial registration: the First Affiliated Hospital of China Medical University, [2020]2020-258-2. Registered 6 June 2020 - Retrospectively registered.

IntroductionThis study aims to explore the effects of combination of laparoscopy and hysteroscopy in pregnancy outcome in women diagnosed with congenital uterine malformation (CUM). The observation criteria include pregnancy rate, misdiagnosis rate, rate of spontaneous abortion and preterm birth rate.Material and methodsA total of 180 patients with congenital uterine malformation, who were treated in our hospital from January 2015 to June 2018, were enrolled in the study. Prior to hospitalization, all the patients had neither a history of genital tract surgery nor endocrine abnormalities, chromosomal abnormalities, immune abnormalities or other factors affecting pregnancy. Furthermore, the ovarian functions were normal, and there were no factors leading to infertility in the male partners. The diagnosis was mainly based on medical history, clinical manifestations, gynecological examinations, and ultrasonography including two-dimensional and three-dimensional ultrasonography, as well as hysterosalpingogram (HSG), magnetic resonance imaging (MRI), hysteroscopy, and/or laparoscopy or surgery. Patients were diagnosed and classified according to the Buttram classification.ResultsAmong these 180 patients, 37 patients were diagnosed with complete septate uterus, 96 patients had sub-septate uterus, 25 patients had unicornuate uterus, 11 patients were diagnosed with bicornuate uterus, and 11 patients had didelphic uterus. The total number of preoperative pregnancies was 112, including 106 spontaneous abortions, with an abortion rate of 94.64%, and 86 total postoperative pregnancies, among which spontaneous abortions occurred 11 times, with an abortion rate of 12.79%. The difference was statistically significant (p < 0.05).ConclusionsUterine malformation surgery can significantly improve the reproductive prognosis in patients with CUM.

Background Spatial sparsity has been found to be in line with the intrinsic characteristic of brain activation. However, identifying a sparse representation of complex-valued fMRI data is challenging due to high noise within the phase data. New methods We propose to reduce the noise by combining real and imaginary parts of complex-valued fMRI data along spatial and temporal dimensions to form a real-valued spatiotemporal concatenation model. This model not only enables flexible usage of existing real-valued sparse representation algorithms but also allows for the reconstruction of complex-valued spatial and temporal components from their real and imaginary estimates. We propose to select components from both real and imaginary estimates to reconstruct the complex-valued component, using phase denoising to recover weak brain activity from high-amplitude noise. Results The K-SVD algorithm was used to obtain a sparse representation within the spatiotemporal concatenation model. The results from simulated and experimental complex-valued fMRI datasets validated the efficacy of our method. Comparison with existing methods Compared to a magnitude-only approach, the proposed method detected additional voxels manifest within several specific regions expected to be involved but likely missing from the magnitude-only data, e.g., in the anterior cingulate cortex region. Simulation results showed that the additional voxels were accurate and unique information from the phase data. Compared to a complex-valued dictionary learning algorithm, our method exhibited lower noise for both magnitude and phase maps. Conclusions The proposed method is robust to noise and effective for identifying a sparse representation of the natively complex-valued fMRI data.

COVID-19 has been declared a pandemic by WHO on March 11, 2020. No specific treatment and vaccine with documented safety and efficacy for the disease have been established. Hence it is of utmost importance to identify more therapeutics such as Chinese medicine formulae to meet the urgent need. Qing Fei Pai Du Tang (QFPDT), a Chinese medicine formula consisting of 21 herbs from five classical formulae has been reported to be efficacious on COVID-19 in 10 provinces in mainland China. QFPDT could prevent the progression from mild cases and shorten the average duration of symptoms and hospital stay. It has been recommended in the 6th and 7th versions of Clinical Practice Guideline on COVID-19 in China. The basic scientific studies, supported by network pharmacology, on the possible therapeutic targets of QFPDT and its constituent herbs including Ephedra sinica, Bupleurum chinense, Pogostemon cablin, Cinnamomum cassia, Scutellaria baicalensis were reviewed. The anti-oxidation, immuno-modulation and antiviral mechanisms through different pathways were collated. Two clusters of actions identified were cytokine storm prevention and angiotensin converting enzyme 2 (ACE2) receptor binding regulation. The multi-target mechanisms of QFPDT for treating viral infection in general and COVID-19 in particular were validated. While large scale clinical studies on QFPDT are being conducted in China, one should use real world data for exploration of integrative treatment with inclusion of pharmacokinetic, pharmacodynamic and herb-drug interaction studies.

The aim of this study was to evaluate the prognostic value of a novel scoring system, based on D‑dimer, total cholesterol, high-sensitivity cardiac troponin T (hs-cTnT), and serum albumin levels, in patients with heart failure.A total of 221 patients diagnosed with heart failure between May 2016 to January 2020 were enrolled in this retrospective study. The prognostic significance of the biomarkers D‑dimer, total cholesterol, hs-cTnT, and serum albumin was determined with univariate and multivariate Cox proportional hazard models. A novel prognostic score based on these predictors was established. The Kaplan-Meier method and log-rank test were used to compare the adverse outcomes of patients in different risk groups.Results from univariate and multivariate analyses showed that high D‑dimer, low serum albumin, high hs-cTnT, and low total cholesterol levels were independent prognostic factors for adverse outcomes (D-dimer0.63 mg/l, HR = 1.84, 95% CI = 1.16-2.94, p = 0.010; serum albumin34 g/l, HR = 0.67, 95% CI = 0.45-0.99, p = 0.046; hs-cTnT24.06 pg/ml, HR = 1.65, 95% CI = 1.08-2.53, p = 0.020; total cholesterol3.68 mmol/l, HR = 0.63, 95% CI = 0.43-0.92, p = 0.017). Moreover, all the patients were stratified into low-risk or high-risk group according to a scoring system based on these four markers. Kaplan-Meier analyses demonstrated that patients in the high-risk group were more prone to having adverse outcomes compared with patients in the low-risk group.D‑dimer, total cholesterol, hs-cTnT, and serum albumin levels were independent prognostic factors in the setting of heart failure. A novel and comprehensive scoring system based on these biomarkers is an easily available and effective tool for predicting the adverse outcomes of patients with heart failure.ZIEL DER ARBEIT: Ziel der vorliegenden Studie war es, den prognostischen Wert eines neuen Score-Systems zu untersuchen, der auf den Werten für D‑Dimere, Gesamtcholesterin, hochsensitives kardiales Troponin (hs-cTnT) und Serumalbumin bei Patienten mit Herzinsuffizienz beruht.In diese retrospektive Studie wurden 221 Patienten mit Diagnosestellung einer Herzinsuffizienz zwischen Mai 2016 und Januar 2020 einbezogen. Die prognostische Bedeutung der Biomarker D‑Dimere, Gesamtcholesterin, hs-cTnT und Serumalbumin wurde anhand univariater und multivariater Cox-Proportional-Hazard-Modelle ermittelt. Es wurde ein neuer prognostischer Score auf der Grundlage dieser Prädiktoren etabliert. Um unerwünschte Ereignisse zwischen den Patienten in verschiedenen Risikogruppen zu vergleichen, wurden die Kaplan-Meier-Methode und der Log-Rank-Test eingesetzt.Die Ergebnisse der univariaten und multivariaten Analysen zeigten, dass hohe Werte für D‑Dimere und hs-cTnT sowie niedrige Werte für Gesamtcholesterin und Serumalbumin unabhängige prognostische Faktoren für ungünstige Outcomes waren (D-Dimere0,63 mg/l; Hazard Ratio, HR = 1,84; 95%-Konfidenzintervall, 95%-KI = 1,16–2,94; p = 0,010; Serumalbumin34 g/l; HR = 0,67; 95%-KI = 0,45–0,99; p = 0,046; hs-cTnT24,06 pg/ml; HR = 1,65; 95%-KI = 1,08–2,53; p = 0,020; Gesamtcholesterin3,68 mmol/l; HR = 0,63; 95%-KI = 0,43–0,92; p = 0,017). Darüber hinaus wurden alle Patienten gemäß einem Scoring-System auf Grundlage dieser 4 Parameter in eine Niedrigrisikogruppe oder Hochrisikogruppe eingeteilt. Die Kaplan-Meier-Analysen ergaben, dass bei den Patienten in der Hochrisikogruppe eine höhere Tendenz zu ungünstigen Outcomes als bei den Patienten in der Niedrigrisikogruppe bestand.Die Werte für D‑Dimere, Gesamtcholesterin, hs-cTnT sowie Serumalbumin stellten sich als unabhängige prognostische Faktoren bei Vorliegen einer Herzinsuffizienz heraus. Ein neues und umfassendes Scoring-System auf der Basis dieser Biomarker erwies sich als leicht verfügbares und effektives Instrument zur Vorhersage ungünstiger Outcomes bei Patienten mit Herzinsuffizienz.

The identification and tracking for model pigs, as a vital research content for studying the habits of model pigs, drawed more and more considerable attention. To fulfill people requirements for the effectiveness of the non-significant model pig tracking in breeding environment, a Camshift tracking approach based on correlation probability graph, i.e., CamTracor−PG, is proposed in this paper, in which the correlation probability graph is introduced to achieve target positioning and tracking. Technically, acquiring images through a vision sensor, according to the circular arrangement of pixels in the inverse probability projection graph, and multiplying the inverse projection probability value of a pixel by its surrounding pixels could obtain the weighted sum. Then, the target projection grayscale graph is established by utilizing the correlation probability value for positioning, identification, and tracking of model pigs. Finally, extensive experiments are conducted to validate reliability and efficiency of our approach.

Microelectromechanical systems (MEMS) using flexible and/or stretchable polymers can bring new functions of conformal integration of sensors on flat and curved surfaces. Here, we report flexible strain/pressure sensors using polydimethylsiloxane (PDMS) and polyimide-based MEMS. The MEMS device architecture enables the integration of three electrical sensors, outputting digital signals, onto an area of 50 mm2 for strain and pressure detection. We show that engineered sensors with various sensitivities in bending mode can be applied to control robotic arms. Another demonstration of pressure sensing using these sensors enables the potential of pressure control in handling physical objects. Our integrated wearable flexible sensors, compared to widely used rigid sensors, derive flexibility and stretchability from polymer materials and have huge potential applications in robotics, prosthetics, and other wearable technologies requiring flexible sensors.

Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data-driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex-valued resting-state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post-ICA phase de-ambiguity and denoising are then performed. The ability of spatial source phase to characterize spatial differences is examined by the homogeneity of variance test (voxel-wise F-test) with false discovery rate correction. Resampling techniques are performed to ensure that the observations are significant and reliable. We focus on two components of interest widely used in analyzing SZs, including the default mode network (DMN) and auditory cortex. Results show that the spatial source phase exhibits more significant variance changes and higher sensitivity to the spatial differences between SZs and HCs in the anterior areas of DMN and the left auditory cortex, compared to the magnitude of spatial activations. Our findings show that the spatial source phase can potentially serve as a new brain imaging biomarker and provide a novel perspective on differences in SZs compared to HCs, consistent with but extending previous work showing increased variability in patient data.

To deal with the serious visual artifacts caused by the consistent restoration algorithm on local motion blurred images, a novel two stage blur region detection method including coarse location and region refinement for local blurred images is proposed in this paper. First, blur feature discriminant criteria in frequency domain and spatial domain is defined to generate blur feature image; then, binarization is used on the blur feature image to obtain the coarse blur region detection map; subsequently, morphological methods are used to process the clear and blur areas and the trimap is obtained. Finally, the refinement detection of blur region is achieved by combination of the trimap and automatic KNN matting algorithm. Experimental results show that the proposed algorithm can detect the local blurred region quickly and effectively, and it has outperformed other traditional methods in the application of blur region detection and image restoration as well.

In view of the complex and changeable environment in underground coal mines, an improved algorithm based on the principal component analysis-scale invariant feature transform (PCA-SIFT) and mean shift is proposed to address the issues for which existing tracking algorithms are not adequate; for example, when differentiating between moving targets and the background, the tracking in the case of moving objects (e.g., confusion between foreground and background) is not optimal. This results in poor resolution and the inability to deal with very dusty conditions, scale change, and rotation. The proposed feature target tracking model was developed using the scale invariance property of the PCA-SIFT feature-extraction algorithm. Finally, the mean-shift method was used to track moving objects. The experimental results showed that the optimized algorithm for tracking moving objects was significantly better and more robust than the existing algorithm.

Business Intelligence involves the strategies and technologies employed by businesses for the data analysis of business information. This study investigates the impact of Business Intelligence on the Marketing with emphasis on cooperative Learning. Descriptive-survey research method and field study were employed. 186 samples of employees from insurance companies are statistical population. The face validity and the experts' opinions were employed to determine the validity of the questionnaire for data investigating. Cronbach's alpha and Composite reliability were employed to appraised the accuracy of questions. The methods employed in descriptive statistics as Absolute Frequency Distribution tables, are mean for confirmatory factor. The results revealed that Business Intelligence has a certain and critical impact on marketing through cooperative Learning (Value of Statistics was greater than 1.96), Financial Performance (VoS was greater than 2.57), and Customer Behavior (VoS was greater than 2.57). Also, Business Intelligence teams have a certain and critical impact on Financial Performance (VoS was greater than 2.57), and Customer Behavior (VoS was greater than 2.57). Despite, Business Intelligence does not have a notable impact on Marketing (VoS was less than 1.64).