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Supplementary Material 1

Additional file 1: Supplementary Table 1. Quality evaluation of RCTs according to Cochrane Collaboration Guidelines. Supplementary Figure 1. Risk of total PARP inhibitor-related hypertension. Supplementary Figure 2. Risk of hypertension with different PARP inhibitors. Supplementary Figure 3. Detailed analysis of olaparib-related hypertension. Supplementary Figure 4. Risk of hypertension in different types of cancer. Supplementary Figure 5. Risk of hypertension in different treatment regime. Supplementary Table 2. Begg's test results of any grade and grade 3-4 hypertension related to total PARP inhibitor. Supplementary Figure 6. Funnel plot of hypertension associated with total PARP inhibitors.

Semi-quantum private comparison (SQPC) enables two classical users with limited quantum capabilities to compare confidential information using a semi-honest third party (TP) with full quantum power. However, entanglement swapping, as an important property of quantum mechanics in previously proposed SQPC protocols is usually neglected. In this paper, we propose a feasible SQPC protocol based on the entanglement swapping of Bell states, where two classical users do not require additional implementation of the semi-quantum key distribution protocol to ensure the security of their private data. Security analysis shows that our protocol is resilient to both external and internal attacks. To verify the feasibility and correctness of the proposed SQPC protocol, we design and simulate the corresponding quantum circuits using IBM Qiskit. Finally, we compare and discuss the proposed protocol with previous similar work. The results reveal that our protocol maintains high qubit efficiency, even when entanglement swapping is employed. Consequently, our proposed approach showcases the potential applications of entanglement swapping in the field of semi-quantum cryptography., Comment: 17 pages, 6 figures. arXiv admin note: text overlap with arXiv:2210.03421

Label propagation is an essential semi-supervised learning method based on graphs, which has a broad spectrum of applications in pattern recognition and data mining. This paper proposes a quantum semi-supervised classifier based on label propagation. Considering the difficulty of graph construction, we develop a variational quantum label propagation (VQLP) method. In this method, a locally parameterized quantum circuit is created to reduce the parameters required in the optimization. Furthermore, we design a quantum semi-supervised binary classifier based on hybrid Bell and $Z$ bases measurement, which has shallower circuit depth and is more suitable for implementation on near-term quantum devices. We demonstrate the performance of the quantum semi-supervised classifier on the Iris data set, and the simulation results show that the quantum semi-supervised classifier has higher classification accuracy than the swap test classifier. This work opens a new path to quantum machine learning based on graphs.

Additional file 1: Table 1. The individual characteristics of the migraine patients. Fig. 1 The correlation between Intra- and Internetwork FC and microstate parameters of HC group. Fig. 2 Comparison of intra-network FC between subgroups divided by the attack frequency. Fig. 3 Comparison of inter-network FC between subgroups divided by the attack frequency. Fig. 4 Comparison of intra-network FC between subgroups divided by pain sides. Fig. 5 Comparison of microstate parameters between subgroups divided by the medications used during attacks. Fig. 6 Comparison of inter-network FC between subgroups divided by the medications used during attacks.

Additional file 1: Table S1. Detailed search strategies of each database. Table S2. Outcomes of the meta-regression analyses. Figure S1. Forest plots of perioperative outcomes including: A. anastomotic leakage; B. Duodenal stump leakage; C. Pancreatic leakage; D. Intra-abdominal abscess; E. Surgical-site infection; F. Pulmonary infection; G. Mortality; H. Need for additional drainage; I. Readmission; J. Reoperation. Figure S2. Subgroup analyses of perioperative outcomes based on sample size (≥100 vs. 0.05.

Blind quantum computing (BQC) ensures that a classical client could delegate complex computing tasks to a remote quantum server safely. In order to detect the dishonest behavior of the participants, we present a verifiable multi-party universal BQC protocol in distributed networks. By using the stabilizer formalism, we propose an honesty check method to test the correctness of the graph states generated by the servers. The honesty of both the clients and the servers can be judged fairly with the help of the arbitrator. Moreover, a load balancer is introduced to control the possible breakdown of servers in the network. No-signaling principle ensures the unconditional security of the protocol. Through the use of universal resource states, our protocol can be applied in more multi-party verifiable universal BQC protocols. The failure management and workload balancing of the protocol also provide a promising prospect for the future BQC network.

Supplementary Materials forpublication.

BackgroundWilson’s disease (WD) is a rare cause of acute liver failure (ALF) and has a high fatality rate. Rapid and accurate diagnosis is important for ALF because of WD (ALF-WD). Our objective was to establish a simple, rapid, and accurate diagnostic test to distinguish ALF-WD from non-WD ALF (NWDALF) in children.Materials and methodsThe data from all cases with pediatric ALF were retrospectively collected and analyzed. We performed receiver operator characteristics curve (ROC) analysis and confirmed the optimum cut-off points.ResultsFifty-eight patients with pediatric ALF (12 with WD, 46 with other etiologies) were included. Older age was observed in ALF-WD compared to NWDALF (11.16 ± 2.51 years vs. 3.34 ± 3.81 years, p < 0.001). An analysis based on routine biochemical testings revealed that total bilirubin (TBil), direct bilirubin, indirect bilirubin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), AST:ALT ratio, alkaline phosphatase (ALP), ALP:TBil ratio, serum albumin, gamma-glutamyl transferase, cholinesterase, hemoglobin, and platelet were statistically significant between the ALF-WD and NWDALF groups. The optimum cut-off points were obtained through ROC analysis. A scoring system was formed by assigning a score of 1 or 0 to patients who met the 13 cut-off points. Using ROC analysis, we determined a cut-off point of ≥ 6.5 for ALF-WD with 91.7% sensitivity and 97.8% specificity (p < 0.0001). In addition, a best cut-off point of ≥ 1.5 based on only five variables (ALT, AST, AST:ALT ratio, ALP, and ALP:TBil ratio), had 100% sensitivity and 91.3% specificity for ALF-WD (p < 0.0001). Based on this, when age was calculated as the sixth indicator, the best cut-off value of ≥ 2.5 had 100% sensitivity and 97.8% specificity (p < 00.0001).ConclusionOur study developed a new scoring system that consists of simple laboratory tests with good sensitivity and specificity and can be used by clinicians to quickly distinguish ALF-WD from NWDALF in children.

Metric learning plays an essential role in image analysis and classification, and it has attracted more and more attention. In this paper, we propose a quantum adversarial metric learning (QAML) model based on the triplet loss function, where samples are embedded into the high-dimensional Hilbert space and the optimal metric is obtained by minimizing the triplet loss function. The QAML model employs entanglement and interference to build superposition states for triplet samples so that only one parameterized quantum circuit is needed to calculate sample distances, which reduces the demand for quantum resources. Considering the QAML model is fragile to adversarial attacks, an adversarial sample generation strategy is designed based on the quantum gradient ascent method, effectively improving the robustness against the functional adversarial attack. Simulation results show that the QAML model can effectively distinguish samples of MNIST and Iris datasets and has higher robustness accuracy over the general quantum metric learning. The QAML model is a fundamental research problem of machine learning. As a subroutine of classification and clustering tasks, the QAML model opens an avenue for exploring quantum advantages in machine learning., arXiv admin note: substantial text overlap with arXiv:2303.07906

Quantum multicast is a significant transmission mode in a multiparty communication scenario. Multisource collaboration can further enhance the efficient multicast. However, it remains a challenge to realize quantum multicast with a cooperative way in a complex topology network. In this article, we propose a scheme of quantum cooperative multicast in a hybrid topology network. It provides information aggregation and simultaneous multipoint transmission services. First, collaborative information aggregation allows central network data to be integrated into the aggregation node. By exploiting the quantum multicast mode, the aggregation node can simultaneously deliver integrated quantum states to multiple targets. Second, our scheme is feasible for dynamic network expansion. It is capable of extending the network architecture iteratively, while the peer network requests can be handled in parallel. Finally, the new scheme shows great application potential in the distributed quantum network. It is a promising candidate for the implementation of quantum data disaster backup in future.

Objective: This study explored the therapeutic impact of combined cytotoxic T lymphocyte-associated antigen 4 immunoglobulin (CTLA-4-Ig) treatment and microbubble-mediated exposure in a rat model of diabetic nephropathy (DN). Method: We treated rats using CTLA-4-Ig and/or microbubble exposure. At 8 weeks post-intervention, key parameters were evaluated including blood biochemistry, damage to renal tissue, renal parenchymal elasticity, ultrastructural changes in podocytes, and renal parenchymal expression of CD31, CD34, IL-6, Fn, Collagen I, Talin, Paxillin, α3β1, podocin, nephrin, and B7-1. Result: We found that renal function in the rat model of DN can be significantly improved by CTLA-4-Ig and CTLA-4-Ig + ultrasound microbubble treatment. Treatment efficacy was associated with reductions in renal parenchymal hardness, decreases in podocyte reduction, decreased IL-6, Fn and Collagen I expression, increased Talin, Paxillin and α3β1 expression, elevated podocin and nephrin expression, and decreased B7-1 expression. In contrast, these treatments did not impact CD31 or CD34 expression within the renal parenchyma. Conclusion: These findings clearly emphasize that CTLA-4-Ig can effectively prevent podocyte damage, inhibiting inflammation and fibrosis, and thereby treating and preventing DN. In addition, ultrasound microbubble exposure can improve the ability of CTLA-4-Ig to pass through the glomerular basement membrane in order to access podocytes such that combination CTLA-4-Ig + microbubble exposure treatment is superior to treatment with CTLA-4-Ig only.

Low-intensity pulsed ultrasound (LIPUS), as physical therapy, is widely used in both research and clinical settings. It induces multiple bioeffects, such as alleviating pain, promoting tissue repair, and shortening disease duration. LIPUS can also mediate inflammation. This paper reviews the application of LIPUS in inflammation and discusses the underlying mechanism. In basic experiments, LIPUS can regulate inflammatory responses at the cellular level by affecting some signaling pathways. In a clinical trial, LIPUS has been shown to alleviate inflammatory responses efficiently. As a cheap, safe, and convenient physical method, LIPUS is promising as anti-inflammatory therapy.

A sample including 935 blazars with 415 Flat Spectrum Radio Quasars (FSRQs) and 520 BL Lac objects (BL Lacs) (233 HBLs (High synchrotron peak frequency BL Lacs), 144 IBLs (Intermediate synchrotron peak frequency BL Lacs), and 143 LBLs (Low synchrotron peak frequency BL Lacs)) is selected in Fermi 3FGL catalogue. The correlations between two flux densities of the radio 1.4 GHz and γ -ray at 0.1, 0.3, 1, 3, and 10 GeV are investigated for the samples of all blazars, FSRQs, BL Lacs, and subclasses of HBLs and LBLs, respectively. Results show that there are strong positive correlations between the two flux densities, with the correlation coefficients r = 0.48 ∼ 0.81 , and the chance probabilities p all less than 10 − 4 . The correlation coefficient has different trends with the change of γ -ray emission frequency for different blazar samples, and the average correlation coefficients for all the samples at five respective bands decrease with the increase of γ -ray frequency. Therefore, with the increase of γ -ray frequency, the dominant mechanism of γ -ray radiation of blazar is changing, and at the same frequency the dominant mechanism is different for different samples. The γ -ray emission of HBLs may be mainly dominated by the synchrotron self-Compton, while the other mechanisms are responsible for the γ -ray emissions of LBLs. The origin of γ -ray in FSRQs is more complex than that of BL Lacs.

A new cytotoxic alkaloid, named streptothiazolidine B (1), together with three known compounds (2-4), were isolated from Streptomyces violaceoruber. The structure of the undescribed compound was established using 1D and 2D NMR, and HRESIMS. Streptothiazolidine B was isolated and identified as an amide alkaloid with a unique thiazolidine side chain and its absolute configuration was determined by a combination of NOESY experiment and ECD analysis. Streptothiazolidine B exhibited significant cytotoxic activities against two human tumor cell lines, Li-7 and A2780, with IC50 values of 7.8, and 9.1 μM. Meanwhile, compound 4 showed obvious cytotoxic activities against four human tumor cell lines, THP-1, HT29, Li-7 and A2780, with IC50 values ranging from 3.1 to 10.2 μM.

Cheng CY, Zeng GY, Wang T, et al. Int J Womens Health. 2022;14:687–696. The authors have advised that the funding statement on page 694 is incorrect. The text “Dongguan Social Science and Technology Development (Key) Project in 2019. (Project No. 201950715028172)” should read “Dongguan Social Science and Technology Development (Key) Project in 2019 (Project No. 201950715028173)”. The authors apologize for this error. Read the original article

Semi-quantum private comparison (SQPC) aims to compare the equality of the classical participants’ secrets with the help of a semi-honest TP, in which TP has full quantum capability while the classical participants’ quantum capability is limited. In the existing SQPC protocols, the entanglement resource (e.g., entangled state preparation and entangled state measurement) and pre-shared key are usually required. Besides, the qubit efficiency is relatively low. In this paper, we propose an efficient SQPC protocol based on single-particle states, in which the entanglement resource and pre-shared key are unnecessary. The qubit efficiency of our protocol is far greater than that of all existing SQPC protocols due to the use of single-particle states and circular transmission mode. Moreover, our protocol can be extended to the multi-party case, which can accomplish arbitrary pair’s comparison of equality among $$n(n\ge 2)$$ classical participants. Finally, various kinds of attacks have been analyzed, which show that the proposed protocol is secure against the outside and inside attacks.

Polyalthopsis Chaowasku is a recently newly described genus in Annonaceae. Polyalthopsis verrucipes (C.Y.Wu ex P.T.Li) B.Xue & Y.H.Tan is distributed in Southern Yunnan, China. In this article, we report the complete chloroplast (cp) genome of Polyalthiopsis based on Illumina sequencing data. The whole cp genome of this species is 159,965 bp in length, consisting of two inverted repeat regions (IR, 25,974 bp each), one large single-copy region (LSC, 89,030 bp), and one small single-copy region (SSC, 18,987 bp). A total of 130 genes were annotated for the cp genome, including 83 protein-coding genes, 37 tRNAs, and 8 rRNAs. Phylogenetic analysis indicated that P. verrucipes was closely related to Meiogyne hainanensis.

Background At present, plant growth regulators (PGRs) are widely used in agricultural and forestry production. PGRs, like traditional pesticides, have certain toxicities. Naively excessively applying them will cause the acute and chronic poisoning of humans and animals and potentially harm human health. Objective In order to assess, prevent, and control the residues of PGRs in fruits and vegetables, a set of quick, easy, cheap, effective, rugged, and safe (QuEChERS) analytical methods that simultaneously detect multiple PGR residues are urgently needed for quality and safety inspection of agricultural product. Methods In this study, grapes (representative of fruits) and cabbages (representative of vegetables) were used as the detected objects. The 30 commercial product residues of PGRs were detected in both with an ultra-high performance liquid chromatography (UHPLC)-tandem mass spectrometry (MS/MS) method, based on optimized chromatographic, MS, and preparation conditions (extraction solvent and cleanup conditions). Grape and cabbage samples were extracted with acetonitrile containing 5% (v/v) acetic acid, dehydrated using a salt package, purified using the QuEChERS method, ionized using electrospray ionization under positive and negative ion switching mode, detected using multi-reaction monitoring, and quantification using an external standard method of matrix matching standard curve. Results Methanol was selected as the strong elution phase. A methanol-0.1% formic acid-5 mmol/L ammonium acetate solution was selected as the best mobile phase. The optimal extraction solvent was acetonitrile containing 5% acetic acid. Primary secondary amine cleanup could met the determination requirements of PGR residues. The developed method for determination of 30 commercial products of PGR, such as betaine, showed excellent linearity in 1–500, 10–1000, ∼500, ∼2000, and 100–10 000 μg/kg (R ≥ 0.98). At the 0.001 (0.01), 0.05, 0.20, and 1.00 mg/kg additive concentrations, the average addition standard recovery of 30 commercial products of PGR were 61–132% with the relative standard deviations of 1–14% and the LOQs were confirmed to be 1.0–100 μg/kg through the actual addition values of samples. Conclusion The set of optimized QuEChERS UHPLC-MS/MS methods simultaneously detect residues of PGRs in fruits and vegetables with one-time sample preparation for high-throughput, rapid quantitative screening, and confirmation. The methods cover a wide range of PGRs with simple and convenient preparation and small amounts of solvent, and can provide technical support for the supervision of PGR residues in fruits and vegetables. Highlights The optimizations of extraction solvent screening, different ratios of various purification packages in the QuEChERS method, and UPLC-MS conditions were conducted and the precision, sensitivity, and recovery rates of the methods were investigated in order to establish a QuEChERS UPLC-MS/MS method for simultaneously detecting 30 kinds of PGR residues in fruits and vegetables. The methods allow high-throughput determination of multiple PGR residues in fruits and vegetables and can also provide technical references for related compound residue detection of other matrixes.

BACKGROUND: Anterior talofibular ligament (ATFL) injury affects ankle joint stability. To date, very few studies have examined tissue stiffness changes inside injured ligaments. Virtual touch tissue imaging quantification (VTIQ) allows for the non-invasive quantitative measurement of tissue stiffness. The present study aimed to examine the efficacy of VTIQ as a method for detecting ligament injury. METHODS: A total of 206 patients diagnosed with unilateral ATFL type I injury (81 acute cases, 69 subacute cases, and 56 chronic cases) were reviewed retrospectively. Shear wave velocity (SWV) values were collected from both the injured and non-affected sides of the ATFL using a virtual touch tissue imaging quantification technique (ACUSON Oxana 2, Siemens Medical Solutions USA, Inc.). RESULTS: The average SWV of injured ATFL was 4.09±1.15 m/s in the acute group, 5.60±1.39 m/s in the subacute group, and 7.74±1.44 m/s in the chronic group (P0.05). The injured ATFL had a significantly lower SWV value than the non-affected ATFL in the acute and subacute groups (P0.05). Concerning the validity of SWV as a predictor of acute and subacute ATFL injury, the receiver operator characteristics curve analysis showed that the best cut-off point for SWV was 6.165 m/s, with 84.3% sensitivity, 88.5% specificity, and an area under the curve of 0.93 (95% CI, 0.90–0.95). CONCLUSIONS: VTIQ is a reliable sonographic method for detecting acute and subacute ATFL type I injury.

Additional file 1: Table S1: Clinicopathologic variables for patient cohort (n = 224). (DOC 45 KB)

Additional file 4: Table S4: Multivariate Cox regression analysis of Sam68 localization and other potential prognostic factors for CRC patients. (DOC 34 KB)

Additional file 3: Table S3: Multivariate Cox regression analysis of Sam68 levels and other potential prognostic factors for CRC patients. (DOC 33 KB)

Additional file 1: Figure S1. Analysis of conserved amino acid residues involved in substrate binding and catalysis of DddK (a), DddQ (b), DddY (c), Tmm (d), DddP (e), DmdA (f) and DMSOR (g) retrieved from polar metagenomic samples. Figure S2. Maximum likelihood trees of the predicted hits of the top five most abundant genes (DddP, DddK, DddK, DmdA, Tmm) involved in DMSP/DMS cycling which were retrieved from the polar metagenomes, Tara metagenomes/metatranscriptomes datasets. Figure S3. Correlation between dissimilarity of DMS/DMSP related bacterial community and water depth in polar oceans.

Additional file 2: Table S2: Univariate Cox regression analysis of potential prognostic factors for CRC patients. (DOC 58 KB)

The purpose of this study was to study the absorption characteristics of eight main components from dragon's blood phenolic extracts in Caco-2 cells based on the humancolon cancer cell Caco-2 model, and to clarify the oral absorption mechanism of such phenolic extracts. UPLC-MS/MS was used in this study to determine the content of 8 active ingredients including thevetiaflavone, 7,4'-dihydroxyflavone, 7,4'-dihydroxy-5-methoxyhomoisoflavanone, 7,4'-dihydroxyhomoisoflavanone, loureirin C, loureirin A, loureirin B and pterostilbene from dragon's blood phenolic extracts, and Caco-2 cells were used to investigate the effects of incubation time, concentration, temperature, P-gp inhibitor, MRP inhibitor, OCTN1 inhibitor and OCTN2 inhibitor on the absorption of each component. In addition, the transport experiment was conducted to measure the apparent permeability coefficient P_(app) and transport rate of the eight main components to predict the oral absorption mechanism of dragon's blood phenolic extracts. The experimental results showed that the cell uptake of the eight main components in dragon's blood phenolic extracts was time-dependent and concentration dependent, and the uptake of each component did not need to consume energy, which was consistent with the passive diffusion process. P-gp inhibitor, MRP inhibitor and OCTN1 inhibitor had no effect on the cell uptake of each component, only the addition of OCTN2 inhibitor significantly reduced the uptake of pterostilbene(Plt;0.05). In the transport results, the ER values of the outflow rates of the eight components were all less than 1.5. The above results show that the absorption mechanism of the eight components in Draconis resina phenolic extract may be passive diffusion, and pterostilbene may be the substrate of OCTN2.

The paper investigates the influence of different interlayer angles on dynamic behavior of composite sandwich structure subjected to low-velocity impact. The composite sandwich structure is composed of CFRP/epoxy laminates and Nomex honeycomb core. Seven finite element models with seven different interlayer angles, from [0°/0°/0°/Honeycomb/0°/0°/0°] to [0°/90°/0°/Honeycomb/0°/90°/0°], of composite sandwich are implemented by ABAQUS/Explicit. The damage mechanism for composite laminate is applied with 3D Hashin’s damage by VUMAT, while the honeycomb is based on traction separation laws. The modeling results show that as interlayer angle increases, the indent area is decreasing, but the rate of decrease becomes slower. Meanwhile, the energy absorption is increasing with the higher interlayer angle. From mentioned above, it can be concluded that the interlayer angle has an effect on the impact behavior of composite, and the bigger interlayer angle will result in better impact resistance.

Additional file 1: Figure S1. Genus-level composition based on analysis of 16S miTags. Abundant genera (the top 30 genera in terms of maximum relative abundance) are shown with all other genera grouped together as ‘Minor or unclassified’. The four groups: Arctic-Surface (0-100 m), Arctic-Deep (200-4000 m), Antarctic-Surface (0-100 m), and Antarctic-Deep (200-4000 m). Figure S2. Taxonomic distribution of the 214 MAGs recovered from the polar metagenomes. All the MAGs have 80% or higher completeness. Figure S3. Comparison between the Arctic and Antarctic microbiomes. A Venn diagram showing the distribution of OTUs across the Arctic and the Antarctic miTags. Only OTUs with more than 2 miTag numbers are included for analysis. B BLASTp searching Antarctic orthologs using the Arctic orthologs as queries. C BLASTp searching Arctic orthologs using the Antarctic orthologs as queries. Orthologs of lower than 40% similarity or higher than 1e-7 e-value were considered as ‘specific’. Figure S4. Functions enriched in the Arctic microbiomes. The Arctic and Antarctic-specific orthologs were annotated by searching against the COG database. Relative abundance of a given COG is the number of orthologs classified into this COG divided by the total number of orthologs. The 40 most abundant COGs significantly (p-value

Object detection of optical remote sensing image is an important and challenging problem. And it is widely used in the field of aerial and satellite image analysis. With the rapid increase of optical remote sensing image data and popularity of convolutional neural network, the problem has attracted lots of attention recently. However, the detection result of images with complex background is unsatisfactory, so as images with dense and small objects. Aiming at these problems, we propose a method that combined Feature Pyramid Network(FPN) and Deformable Convolution Network(DCN) to improve the Faster RCNN framework, which helps to improve the detection result. The improved network combines the low-level structural information and the high-level semantic information together to enhance the feature representation. The shared convolutional layer makes end-to-end training come true. Additionally, deformable convolution network makes feature extraction better. We adopt the proposed framework to implement experiments on DOTA dataset, attaining mean average precision(mAP)value of 0.834 on the testing dataset, which is an increase of 23% than the classic Faster RCNN.

Purpose: To analyze the clinical effect of new transvaginal pelvic organ prolapse surgery. Method: 100 cases of pelvic organ prolapse accepted by our hospital from July 2017 to July 2018 were selected as subjects and randomly divided into control group and treatment group. Conventional operation and new transvaginal pelvic organ prolapse were performed for treatment respectively, and the results were analyzed after treatment. [Results]: The treatment of the two groups was compared. The operation time and intraoperative blood loss in the treatment group were less than those in the control group. Patients were followed up for 2 months after surgery. The recurrence rate was 4% in the treatment group, 12% in the control group, and low in the treatment group. Conclusion: In the case of pelvic organ prolapse, the new transvaginal pelvic organ prolapse operation is economical and feasible in primary hospitals, which is worth popularizing.

Due to the nonuniform scale variations and severe occlusion, most current state-of-the-art approaches use multicolumn CNN architectures with different receptive fields to tackle these obstacles. We design a single-column network to verify the necessity of multicolumn network, and we find that under similar number of parameters and size of receptive field, single network is able to perform as well as multicolumn network. Following that, we propose a single-column network called FFnet based on residual block. FFnet is a fully convolutional network and easy to train. We perform extensive experiments on Shanghaitech dataset and the UCF_CC_50 dataset, and the results show that our method achieves a better performance than Switch-CNN with nearly half number of parameters, and a closing performance to the state-of-the-art model CP-CNN with almost one-tenth parameters.

Purpose: to explore the clinical effect of integrated traditional Chinese and western medicine in the treatment of pelvic organ prolapse. Method: this study first needs to select the object of study, so the subjects selected are all patients diagnosed as pelvic organ prolapse. The total number of patients in this study is 56. The selected time range for all patients was from June 2017 to June 2018, there were two groups of patients in the 56 patients, the first group was the observation group, the second group was the control group, the two groups had the same number of patients, 28 cases. Only Western medicine treatment was used in the control group, and integrated traditional Chinese and western medicine treatment in the observation group, compared the two groups of patients' effective rate, recurrence rate and whether there is mesh erosion, thickening and tenderness of the broken end. Result: it was proved that the effective rate of treatment in the observation group was higher than that in the control group, and the recurrence rate, the net erosion and the thickening and tenderness of the broken end were also superior to those in the control group, and the difference between the two groups was obvious. Conclusion: the effective rate of clinical treatment of pelvic organ prolapse patients can be effectively improved by combined traditional Chinese and western medicine, which is worthy of further research and development.

To improve the oil recovery in the middle and late stages of oilfield development, it is very necessary to study the subsurface reservoir architecture. However, how to effectively improve the efficiency of architecture identification is also a big problem for the logging big data in dense well pattern area. In this study, we apply support vector machine (SVM), a supervised machine learning algorithm, and principal component analysis (PCA) data dimension reduction to three types of logging data (spontaneous potential (SP), gamma ray (GR), and acoustic (AC)) in order to automate the identification of braided river architectural elements on the PI2 braided river sand group of the Lamadian Oilfield in the north of Daqing Placanticline in the Songliao Basin, China. Manual qualitative identification shows that the architectural elements of the second sand group of the first member of Putaohua braided river reservoir (PI2) in the Lamadian area consist of mid-channel bars, braided channels, and floodplains. The presence of three types of sediments (medium-to fine-grain sand, fine-grain silty sand, and mudstone) indicates that changes occur in the water body energy within the PI2 braided river. The SVM algorithm development process includes determining the input and output variables, selecting the kernel functions, optimizing the parameters, training the algorithm with known samples, and testing the algorithm. With the twelve feature parameters (median, relative barycenter, variance, and the root of variational variance of SP, GR and AC data, respectively) as input variables and the braided river architecture categories as output variables, we use Gaussian radial basis function (RBF) and grid search to determine the optimal parameters values for penalty factor C and parameter gamma (γ). Without dimension reduction, the identification accuracy of the algorithm is 85.15%. To eliminate data redundancy, we used PCA to reduce the input data dimensionality. With dimension reduction, the identification accuracy of the algorithm increased by 6.93 percentage points to 92.08%. Because the logging response features are not distinctly different in the transition zone of mid-channel bar and braided channel, it is common for these two architectures to be misclassified. Even with this persistent misclassification, the error of our SVM algorithm identification process is only 7.92%, this method is robust enough to provide accurate results when applied to specific repetitive and complex geological big data problems.

Aims In wetlands, water levels can fluctuate, which often disturbs local organisms, such as aquatic plants. The responses of Alternanthera philoxeroides, Myriophyllum aquaticum, and Ludwigia adscendens to water level fluctuations of different frequencies were examined here. Methods Water level fluctuations were simulated at four frequencies: static (0 frequency), one cycle (1 fre- quency), two cycles (2 frequency), and four cycles (4 frequency), and with fluctuation amplitudes (± 25 cm) dur- ing a 60 day experiment. Morphological and physiological traits of plants, including branching number, shoot length, total biomass, shoot root ratio, chlorophyll content, and maximum PSII quantum efficiency (Fv/Fm) were assessed. Important findings Water level fluctuation was found to have no significant impact on branching number, root shoot ratio, or Fv/Fm of A. philoxeroides, but all scenarios except 1 frequency were significantly associated with longer shoots and lower total biomass and chlorophyll content. The traits of M. aquaticum showed different re- sponses to water level fluctuation: branching number and Fv/Fm showed no changes, but shoot length (2 fre- quency) and root shoot ratio (1 and 4 frequency) increased significantly, and total biomass and chlorophyll content (expect 4 frequency) decreased. In L. adscendens, water level fluctuation was associated with lower branching number in all scenarios except 2 frequency, shoot length in all scenarios except 1 and 2 frequency, total biomass in all scenarios except 2 frequency, and chlorophyll content but had no significant effects on root shoot ratio or

Shale pore characterization is crucial for understanding the mechanism of shale hydrocarbon accumulation and its effective exploitation. X-ray diffraction (XRD), optical microscopy, scanning electron microscopy (SEM), pore extraction, nitrogen (N2) adsorption, and fluid-rock interaction experiments were used to study the shale pore structure of the fourth member of the Paleogene Shahejie Formation in the Damintun Depression, East China. The Damintun shale included three types of pores: organic matter pores, mineral matrix pores, and microfractures. The dissolution pores were mainly developed between and inside the matrix minerals, such as calcite, dolomite, and feldspar. The average shale visible dissolution porosity determined using SEM was 1.12%. N2 adsorption analysis revealed that the less than 20 nm pores were the main reservoir space in the Damintun shale. Fluid-rock interaction experiments indicated that the degrees of dissolution of the calcite and dolomite were similar and stronger than those of the K-feldspar and plagioclase. The shale with a high content of carbonate minerals (calcite and dolomite) exhibited more intense dissolution. The degree of dissolution pores development was positively correlated with total organic carbon (TOC) and carbonate mineral (calcite and dolomite) contents. The average contribution of the dissolution porosity to the total porosity of the shale was 18.20%. However, the contribution of the dissolution pores increased with increasing pore size only when the average pore diameter was larger than 12 nm. This may be due to the fact that small pores (diameter

With the rapid development of information economy, how to make full use of the existing store information for decision—making and analysis of goods has significant importance in the store’s sales forecast. As a potential way to realize the interaction and integration between physical world and information space, the concept of digital twins had been proposed recently which attracted high attentions of academics practitioners in related fields. Based on the previous research on the concept of digital twins, the reference system architecture of digital twins convenience stores is designed. A digital twins model based on BP neural network is proposed as the example of convenience store prediction, compared with the traditional grey prediction, the results show that the model has smaller prediction error and higher accuracy.

To understand the malaria prevalence and epidemic characteristics in Taixing City from 2005 to 2015, so as to provide the evidences for formulating the prevention and control strategy.The malaria data of Internet reported cases as well as the reports on epidemiological survey of malaria cases in Taixing City from 2005 to 2015 were collected and analyzed with the methods of descriptive statistics and correlation analysis.A total of 61 malaria cases were reported in Taixing City from 2005 to 2015, including 4 local cases and 57 imported cases. There were 9 cases of vivax malaria, 47 cases of falciparum malaria, 2 cases of malariae malaria, and 3 cases of ovale malaria. There was no seasonality in the occurrence of imported malaria. Though there was no correlation between the times of malaria attack and the duration for going out (The malaria cases are mainly imported ones in Taixing City, and the

C18H12N2, monoclinic, P21/c (no. 14), a = 27.514(5) Å, b = 6.3231(11) Å, c = 7.4175(13) Å, β = 95.805(2)°, V = 1283.8(4) Å3, Z = 4, R gt(F) = 0.0439, wR ref(F 2) = 0.1233, T = 296(2) K.

In the process of supernova explosion the leakage of neutrinos is very important. Adopting an one-dimensional spherically symmetrical model, and under the different neutrino leakage modes, the explosion processes of type II supernovae with masses of 12 M⊙, 14 M⊙, and 15 M⊙ are simulated numerically. The results indicate that all these different neutrino leakage modes have influences on the supernova collapse, shock propagation, and supernova explosion. The best values of the related parameters which are propitious for the type II supernova explosion are given. In addition, the impacts of the equation of state and the compression modulus on the simulated results are discussed.

Recently, deterministic joint remote state preparation (JRSP) schemes have been proposed to achieve 100% success probability. In this paper, we propose a new version of deterministic JRSP scheme of an arbitrary two-qubit state by using the six-qubit cluster state as shared quantum resource. Compared with previous schemes, our scheme has high efficiency since less quantum resource is required, some additional unitary operations and measurements are unnecessary. We point out that the existing two types of deterministic JRSP schemes based on GHZ states and EPR pairs are equivalent.

A Mo middling has been obtained through Cu-Mo bulk flotation. In order to further enrich molybdenite and separate pyrite form this middling. A series flotation tests were conducted to concentrate Mo. Important parameters including regrinding fineness, CaO dosage and cleaning flotation stages were optimized to enhance Mo enrichment. In addition, a close-circuit flotation test was conducted under optimum parameters and a Mo concentrate with 22.92% of Mo grade and 93.75% of Mo recovery was obtained, which satisfied the plant requirement.

Phosphate being one of the three major nutrients required for agricultural plant growth usually presents as collophane in China. Since fine phosphate and other gauge minerals associate with each other and form intergrowth, the beneficiation of collophane is extremely difficult. In this paper, the flotation strategy for a low grade collophane ore from Guizhou province in China was studied in detail. Direct, reverse and direct-reverse combined flotation sheets were employed to collophane flotation. The results reveal that direct-reverse flotation is a suitable flotation flow sheet for this collophane ore. With direct-reverse flotation sheet, the grade of P2O5 in concentrate is 33%, which is improved by 3% comparing direct flotation and P2O5 recovery could achieve 80%. In addition, content of MgO decreased to 0.9%, which satisfied the requirement of wet-process phosphoric acid.

Phosphate is a typical oxide ore characterizing that generating abundant froth during flotation. In this research a new flotation machine was employed in the flotation of phosphate. Comparing to regular flotation machine, in the reverse flotation of dolomite the recovery and grade of MgO has no significance improvement. While, in the case of reverse flotation of silicon dioxide, the new flotation machine has significance advantage. In 5 minutes of flotation time, the yield of froth is 20.66% with new machine, which equals to yield using regular machine under 8 minutes. The flotation time has been shorten by new machine. In addition, the recovery of silicon dioxide improved by 6% and the grade of silicon dioxide in phosphate concentrate decreased by 1.3% comparing the regular flotation machine. The results demonstrate that new flotation machine is more suitable and efficient for phosphate flotation

In this paper, we study the geometrothermodynamics of(2 + 1)-dimensional spinning dilaton black hole. We show that the Ruppeiner curvature vanishes, which implies that there exist no phase transitions and thermodynamic interactions. However when the thermodynamics fluctuation is included, the geometry structure is reconsidered. The non-vanishing Ruppeiner curvature is obtained, which means the phase space is non-flat. We also study the phase transitions and show that it can indeed take place at some points.