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The aggregation of lens proteins induced by glycation is one of the key drivers of diabetic retinopathy and development of diabetic cataracts. Moreover, glycation also causes numerous alterations not only to the tertiary structure of lens proteins but also to serum proteins. There are also evidences of covalent crosslinking among lens crystallins resulting in development of cataract. In this article, the inhibitory potential of butein was tested against the glucose induced glycation and the aggregation α-crystallin (α-cry). The results showed that there was inhibition of advanced glycation products (78.28%) and early glycation products (86.30%) following the treatment of butein. Additionally, the presence of butein caused a significant improvement in the tested biochemical markers of glycation. The treatment with butein reduced the free lysine modification to 23.67%. The secondary and tertiary structural distortions of α-cry were also protected. The mechanism of inhibition further investigated at the molecular level using biophysical and computational techniques. The interaction data showed the butein exhibited strong affinity towards the α-cry. The binding event was entropically driven and energetically favourable. The Gibb's free energy of the interaction was found to be -5.99 to -7.17 kcal mol−1. The binding site of butein in α-cry was deciphered by molecular docking and the dynamics was studied using molecular dynamics (MD) simulations. The simulation data showed that butein formed stable complex with α-cry under physiological conditions. Most of the tested parameters from molecular simulations, such as secondary structure, was found to be stable. The data clearly show the potential of butein in inhibiting the glycation induced aggregation of α-cry and hence can be developed as useful inhibitor in the management of diabetic cataract and retinopathy. [ABSTRACT FROM AUTHOR]

A priori knowledge-enhanced particle filter (PKE-PF) method is proposed to solve the problem of particle impoverishment in bearing fault prognosis with incomplete data. Based on the existing bearing life degradation data and the parameter transfer method in the transfer learning theory, particle initialization optimization, which is very important in the PF method, is carried out to effectively improve particle effectiveness and avoid the problem of premature particle exhaustion. Based on the whole-life degradation experiment of rolling bearings, the validation results show that the traditional PF method and its improved method are prone to particle exhaustion, which seriously affects the fault prediction results. The PKE-PF method proposed in this paper can effectively avoid the problem of premature particle depletion and obtain a more ideal fault prognosis results. [ABSTRACT FROM AUTHOR]

The syndesmosis is an important fibrous joint that plays a crucial role in normal ankle weight-bearing and movements. Syndesmosis injuries include disruption of one or more of the ligaments comprising the distal tibiofibular syndesmosis and are commonly associated with ankle fractures. The treatment of grade 1 syndesmosis injury should be conservative, such as immobilization for one to three weeks followed by gradual return to activity. For the treatment of grade 2 syndesmosis injury, if it was stable enough, the patients still could be managed with conservative therapies. But majority of them strongly favor surgical treatment. For the treatment of grade 3 syndesmosis injury, it should treat with surgical reconstruction. If syndesmosis injury is associated with ankle fractures, surgical reduction, fixation, and reconstruction are usually required. Common surgical treatment methods include syndesmosis screws, composed of either metallic or bioabsorbable material; fibula intramedullary nails; and dynamic button-suture fixation, TightRope or ZipTight. Each method has advantages and disadvantages which must be considered while determining which treatment will provide the best outcomes depending on the patient's needs. Continued exploration of new materials, devices, and methods for surgical fixation is necessary for advancement in this field. [ABSTRACT FROM AUTHOR]

In this article, the existing approaches, including numerical algorithms as well as neural networks to solve dynamic linear matrix equations, have been presented and reviewed. Specifically, the conventional gradient recurrent neural networks (CGRNNs) and the conventional zeroing neural networks (CZNNs) are successively provided to solve the dynamic problems and linear matrix equations, both of which manifest inherent limitations during the solving procedures. To remedy the drawbacks on convergence time, nonzero residual error, and large computational load of the traditional models, an adaptive gradient recurrent neural network (AGRNN) to solve dynamic linear matrix equations is proposed. This proposed inversion-free model possesses rapid convergence rate and accurate calculated solutions. Moreover, theoretical analyses guarantee the advantages of the AGRNN compared with the CGRNN and the CZNN to solve dynamic linear matrix equations. Finally, three numerical experiments, and applications to a PUMA 560 robot motion planning and a mobile subject localization based on angle-of-arrival technique are implemented to testify the advantages of the AGRNN. [ABSTRACT FROM AUTHOR]

In order to solve the problem of poor accuracy of traditional microcontroller attachment stability testing method, a microcontroller attachment stability testing method based on biosensor was designed to solve the existing problems. The reliability test index of the microcontroller is established, then the interference of the microcontroller accessory is detected and responded, and the interference detection signal of the microcontroller accessory is selected. The process design of stability detection of microcontroller accessories based on biosensor is completed. The experimental results show that the stability detection method based on biosensor designed in this paper can ensure the stability detection accuracy of microcontroller accessories above 80%, which is more accurate than traditional methods. It can be used to evaluate the stability, reliability and performance of microcontroller accessories in long-term operation. [ABSTRACT FROM AUTHOR]

Background: Periprosthetic infection is a major cause of failure after segmental endoprosthetic reconstruction. The purpose of this study is to determine whether certain aspects of drain output affect infection risk, particularly the 30 mL/day criterion for removal. Methods: Two hundred and ninety-five patients underwent segmental bone resection and lower limb endoprosthetic reconstruction at one institution. Data on surgical drain management and occurrence of infection were obtained from a retrospective review of patients' charts and radiographs. Univariate and multivariate Cox regression analyses were performed to identify factors associated with infection. Results: Thirty-one of 295 patients (10.5%) developed infection at a median time of 13 months (range 1–108 months). Staphylococcus aureus was the most common organism and was responsible for the majority of cases developing within 1 year of surgery. Mean output at the time of drain removal was 72 mL/day. Ten of 88 patients (11.3%) with ≤ 30 mL/day drainage and 21 of 207 patients (10.1%) with > 30 mL/day drainage developed infection (p = 0.84). In multivariate analysis, independent predictive factors for infection included sarcoma diagnosis (HR 4.13, 95% CI 1.4–12.2, p = 0.01) and preoperative chemotherapy (HR 3.29, 95% CI 1.1–9.6, p = 0.03). Conclusion: Waiting until drain output is < 30 mL/day before drain removal is not associated with decreased risk of infection for segmental endoprostheses of the lower limb after tumor resection. Sarcoma diagnosis and preoperative chemotherapy were independent predictors of infection. [ABSTRACT FROM AUTHOR]

Several organizations use auctions in a procurement bidding system to maintain a low procurement cost. Although several privacy-preserving auction solutions for different application scenarios have been proposed over the past few decades, none of them can perform efficient average procurement bidding while ensuring strong privacy protection for the bids of suppliers. To address this problem, we propose PSPAB, a lightweight, secure average procurement bidding system based on cryptographic tools, to provide full privacy for bids. In addition, this system allows the procurement manager to identify the users in the case of double spending. We formally prove the security of PSPAB under a semi-honest adversary model. Experimental results validate the theoretical analysis and practical application of PSPAB in real-world scenarios. [ABSTRACT FROM AUTHOR]

The transport layer security (TLS) protocol is widely adopted by apps as well as malware. With the geometric growth of TLS traffic, accurate and efficient detection of malicious TLS flows is becoming an imperative. However, current studies focus on either detection accuracy or detection efficiency, and few studies take into account both indicators. In this paper, we propose a two-layer detection framework composed of a filtering model (FM) and a malware family classification model (MFCM). In the first layer, a new set of TLS handshake features is presented to train the FM, which is devised to filter out a majority of benign TLS flows. For identifying malware families, both TLS handshake features and statistical features are applied to construct the MFCM in the second layer. Comprehensive experiments are conducted to substantiate the high accuracy and efficiency of the proposed two-layer framework. A total of 96.32% of benign TLS flows can be filtered out by the FM with few malicious TLS flows being discarded provided the threshold of the FM is set to 0.01. Moreover, a multiclassifier is selected to construct the MFCM to provide better performance than a set of binary classifiers under the same feature set. In addition, when the ratio of benign and malicious TLS flows is set to 10:1, the detection efficiency of the two-layer framework is 188% faster than that of the single-layer framework, while the average detection accuracy reaches 99.45%. [ABSTRACT FROM AUTHOR]

In scientific and engineering fields, the solutions to many problems can be transformed into finding the solutions to Sylvester equation, for which various computational methods (e.g., recurrent neural network, RNN) have been presented and investigated. RNN models are frequently used to solve computational problems due to the prevalent exploitation of the gradient-based RNN. However, the overlong convergent time and the too large residual error restrict the widespread applications of the RNN model in solving time-varying problems. Further, a special type of RNN named zeroing neural network (ZNN) is able to solve the time-varying Sylvester equation, which breaks the limitations mentioned above, but fails to handle complex time-varying problems owing to the sharp increment of the calculated amount in matrix inversion involved. To remedy the limitation, a modified gradient-based RNN (MGRNN) model is proposed to generate more accurate computational solutions with less convergent time and adaptive coefficients for solving the time-varying Sylvester equation, which replaces the matrix inversion problem with the matrix transposition problem. Besides, theoretical analyses and mathematical verifications are presented to validate the efficiency and superiority of the proposed MGRNN model compared with the traditional gradient-based recurrent neural network (GRNN) and ZNN models. Furthermore, simulation experiments are conducted to substantiate the properties of the newly proposed MGRNN model for solving the time-varying Sylvester equation. [ABSTRACT FROM AUTHOR]

Background: Ewing sarcoma is a malignancy of primitive cells, possibly of mesenchymal origin. It is probable that genetic perturbations other than EWS-FLI1 cooperate with it to produce the tumor. Sequencing studies identified STAG2 mutations in approximately 15% of cases in humans. In the present study, we hypothesize that loss of Stag2 cooperates with EWS-FLI1 in generating sarcomas derived from murine mesenchymal stem cells (MSCs).Methods: Mice bearing an inducible EWS-FLI1 transgene were crossed to p53-/- mice in pure C57/Bl6 background. MSCs were derived from the bone marrow of the mice. EWS-FLI1 induction and Stag2 knockdown were achieved in vitro by adenovirus-Cre and shRNA-bearing pGIPZ lentiviral infection, respectively. The cells were then treated with ionizing radiation to 10 Gy. Anchorage independent growth in vitro was assessed by soft agar assays. Cellular migration and invasion were evaluated by transwell assays. Cells were injected with Matrigel intramuscularly into C57/Bl6 mice to test for tumor formation.Results: Primary murine MSCs with the genotype EWS-FLI1 p53-/- were resistant to transformation and did not form tumors in syngeneic mice without irradiation. Stag2 inhibition increased the efficiency and speed of sarcoma formation significantly in irradiated EWS-FLI1 p53-/- MSCs. The efficiency of tumor formation was 91% for cells in mice injected with Stag2-repressed cells and 22% for mice receiving cells without Stag2 inhibition (p < .001). Stag2 knockdown reduced survival of mice in Kaplan-Meier analysis (p < .001). It also increased MSC migration and invasion in vitro but did not affect proliferation rate or aneuploidy.Conclusion: Loss of Stag2 has a synergistic effect with EWS-FLI1 in the production of sarcomas from murine MSCs, but the mechanism may not relate to increased proliferation or chromosomal instability. Primary murine MSCs are resistant to transformation, and the combination of p53 null mutation, EWS-FLI1, and Stag2 inhibition does not confer immediate conversion of MSCs to sarcomas. Irradiation is necessary in this model, suggesting that perturbations of other genes beside Stag2 and p53 are likely to be essential in the development of EWS-FLI1-driven sarcomas from MSCs. [ABSTRACT FROM AUTHOR]

The curative effect and adverse reactions of pamidronate disodium in elderly patients with advanced metastatic bone cancer were evaluated. A total of 160 elderly patients with advanced metastatic bone cancer admitted to Affiliated Hospital of Nantong University from February 2012 to January 2015, were divided into the chemotherapy group (n=60) that received routine therapy and the pamidronate disodium group (n=100) that received pamidronate disodium therapy based on the chemotherapy. Pain relief, analgesic time, analgesic duration and side effects were compared between the two groups after treatment. The effect of pain relief in the pamidronate disodium group was significantly higher than that in the chemotherapy group (P<0.001). The total effective rate of the pamidronate disodium group was significantly higher than that of the chemotherapy group (P<0.001). The analgesic onset time in the pamidronate disodium group was earlier than in the chemotherapy group (P<0.001). The analgesic duration in the pamidronate disodium group was longer than that in the chemotherapy group (P<0.001). The incidence of adverse reactions and complications after treatment in the pamidronate disodium group was significantly less than that in the chemotherapy group (P<0.001). The results indicated that pamidronate disodium is effective in the treatment of elderly patients with advanced metastatic bone cancer and patients are less prone to adverse reactions, complications and pain, which is worthy of clinical application. [ABSTRACT FROM AUTHOR]

Domain transfer learning aims to learn common data representations from a source domain and a target domain so that the source domain data can help the classification of the target domain. Conventional transfer representation learning imposes the distributions of source and target domain representations to be similar, which heavily relies on the characterization of the distributions of domains and the distribution matching criteria. In this paper, we proposed a novel framework for domain transfer representation learning. Our motive is to make the learned representations of data points independent from the domains which they belong to. In other words, from an optimal cross-domain representation of a data point, it is difficult to tell which domain it is from. In this way, the learned representations can be generalized to different domains. To measure the dependency between the representations and the corresponding domain which the data points belong to, we propose to use the mutual information between the representations and the domain-belonging indicators. By minimizing such mutual information, we learn the representations which are independent from domains. We build a classwise deep convolutional network model as a representation model and maximize the margin of each data point of the corresponding class, which is defined over the intraclass and interclass neighborhood. To learn the parameters of the model, we construct a unified minimization problem where the margins are maximized while the representation-domain mutual information is minimized. In this way, we learn representations which are not only discriminate but also independent from domains. An iterative algorithm based on the Adam optimization method is proposed to solve the minimization to learn the classwise deep model parameters and the cross-domain representations simultaneously. Extensive experiments over benchmark datasets show its effectiveness and advantage over existing domain transfer learning methods. [ABSTRACT FROM AUTHOR]

Background: Insufficiency of the rotator cuff is a major problem after resections of proximal humeral tumors and can limit shoulder motion despite preservation of the deltoid muscle and axillary nerve. Allograft-prosthetic composite reconstruction offers one method to reattach the rotator cuff tendons and has been successful in small studies with short followup. However, data are lacking with regard to implant durability, changes in Musculoskeletal Tumor Society (MSTS) scores over time, and delayed complications with extended followup.Questions/purposes: (1) What is the cumulative incidence of allograft-prosthetic composite revision surgery 5 years after the procedure? (2) What are the early- and intermediate-term MSTS scores of allograft-prosthetic composite reconstruction of the shoulder? (3) What are the complications of allograft-prosthetic composite reconstruction?Methods: Twenty-one patients underwent allograft-prosthetic composite reconstruction after tumor resection of the proximal humerus between 2000 and 2015. Six patients who were lost to followup were not included. All patients had malignant or aggressive benign tumors that could be treated with a wide intraarticular approach preserving the deltoid muscle, axillary nerve, and glenoid. Cumulative incidence of implant revision was calculated with death of the patient as a competing risk. Minimum followup was 24 months (with the exception of one patient who died at 22 months), and median followup was 97 months (range, 20-198 months). The upper extremity MSTS score was used to assess function. Various complications were identified from radiographs and charts.Results: The cumulative risk of implant revision was 10.1% at 5 years (95% confidence interval [CI], 1.6%-28.0%). Mean MSTS scores were 86% (± SD 9%) at 1 year and 78% (± SD 13%) at 5 years (mean difference ± SD 9% ± 14%, p = 0.015). Mean active forward elevation was 101° (± SD 33°) at 1 year and 92° (± SD 34°) at 5 years (mean difference ± SD 8° ± 36°, p = 0.41). Notable adverse events included progressive radiographic superior subluxation > 1 cm after 12 months followup (12 of 21 patients), delayed union > 12 months (10 of 21 patients), resorption of the greater tuberosity (nine of 21 patients), and aseptic loosening (three of 21 patients).Conclusions: At intermediate 5-year followup, allograft-prosthetic composite reconstruction of the proximal humerus has an acceptable overall MSTS score and a low incidence of implant revision, but loss of patients to followup and exclusion from the study likely make the results seem better than they actually are. The MSTS score deteriorates between 1 and 5 years. Decreased active forward elevation is not likely to be the sole reason for worsening MSTS scores. A variety of delayed complications including delayed union, resorption of the greater tuberosity, and superior subluxation occurs frequently and may contribute to overall scores. Future studies that compare allograft-prosthetic composites against other forms of reconstruction should attempt to control for possible selection bias and have sufficiently long followup to detect the deterioration of MSTS scores that occur with time.Level Of Evidence: Level IV, therapeutic study. [ABSTRACT FROM AUTHOR]

Background: One of the major challenges in soft tissue sarcomas is to identify factors that predict metastasis. AZGP1 is a potential biomarker of cancer progression, but its value in soft tissue sarcomas remains unknown. The aim of this study is to determine the expression level of AZGP1 in soft tissue sarcomas, and to analyze its influence on tumor progression.Methods: AZGP1 immunohistochemistry (IHC) and RT-PCR were performed in 86 patients with soft tissue sarcomas. The relationships between AZGP1 levels and clinicopathologic features were analyzed. In vitro experiments were performed using fibrosarcoma (HT1080), rhabdomyosarcoma (RD) and synovial sarcoma (SW982) cell lines to corroborate our findings. We used lentiviral over-expression and knockdown assays to examine how changes of AZGP1 expressions might affect cellular migration and invasion.Results: The quantitative RT-PCR results showed that AZGP1 expression was negatively correlated with metastasis and overall survival in soft tissue sarcomas (p < 0.05). Immunohistochemical staining showed lower expression of AZGP1 in patients with metastasis than in those without. Kaplan-Meier survival analysis showed that patients with low expression of AZGP1 had shorter overall (p = 0.056) and metastasis-free survivals (p = 0.038). These findings were corroborated by our in vitro experiments. Over-expression of AZGP1 significantly decreased RD cellular migration and invasion by 64% and 78%, respectively. HT1080 cells migration was inhibited by 2-fold, whereas their invasion was repressed by 7-fold after AZGP1 knockdown.Conclusions: Our study reveals that reduced AZGP1 expression correlates with in vitro cellular migration and invasion. In vivo, it is associated with higher metastatic risk and shorter survival in patients with soft tissue sarcomas. [ABSTRACT FROM AUTHOR]

In this paper, we invest the domain transfer learning problem with multi-instance data. We assume we already have a well-trained multi-instance dictionary and its corresponding classifier from the source domain, which can be used to represent and classify the bags. But it cannot be directly used to the target domain. Thus we propose to adapt them to the target domain by adding an adaptive term to the source domain classifier. The adaptive function is a linear function based on a domain transfer multi-instance dictionary. Given a target domain bag, we first map it to a bag-level feature space using the domain transfer dictionary and then apply a linear adaptive function to its bag-level feature vector. To learn the domain transfer dictionary and the adaptive function parameter, we simultaneously minimize the average classification error of the target domain classifier over the target domain training set, and the complexities of both the adaptive function parameter and the domain transfer dictionary. The minimization problem is solved by an iterative algorithm which updates the dictionary and the function parameter alternately. Experiments over several benchmark data sets show the advantage of the proposed method over existing state-of-the-art domain transfer multi-instance learning methods. [ABSTRACT FROM AUTHOR]

For example, minimally invasive intermetatarsal suture button fixation between the first and second metatarsal has been used to correct medial deviation of the first metatarsal in patients with hallux valgus deformity. If a patient with hallux valgus has a distal metatarsal articular angle greater than 10°, then distal metatarsal redirectional osteotomy and metatarsal translational osteotomy are recommended. Pathologic changes of the first metatarsal play key roles in the pathogenesis of a hallux valgus deformity; two of the more important of these changes are medial deviation [[2], [5], [7]] and hyperpronation of the first metatarsal [[3], [6]]. [Extracted from the article]

In this study, the relationships between high water arsenic exposure and cognitive impairment were investigated. A total of 483 residents aged 40 or older were randomly recruited and were divided into four groups according to the concentrations of arsenic in their water. Consumption levels (̄x¯±sd) of drinking water arsenic for normal, mild, moderate, and high exposure groups were 4±2μg/L, 25±11μg/L, 73±15μg/L, and 183±88μg/L, respectively. The average scores (̄x¯±sd) of the Chinese version Mini-Mental State Examination (MMSE) for females in each group were 21.49±3.14, 19.04±5.87, 16.18±8.14, and 15.82±7.78, and the average scores (̄x¯±sd) for males were 24.50±3.97, 23.16±4.45, 21.00±6.57, and 18.92±7.99, respectively. Significant differences among the average scores of MMSE for males or females in the four groups were found (p<0.05). The prevalence of cognitive impairment for females in each group was 10.86%, 29.63%, 53.48%, and 55.29%, and the prevalence of cognitive impairment for males was 10.71%, 12.00%, 35.71%, and 50.89%, respectively. Significant differences between all groups were observed (p<0.05). In the multivariable regress model, high water was closely associated with the MMSE score (Standardized Coefficient=-0.021) and cognitive impairment (arsenic ˃100 μg/L PR4/1=4.01). The findings of our research suggested a significant positive relationship between arsenic exposure from drinking water and cognitive impairment. [ABSTRACT FROM AUTHOR]

Owing to continuous cyberattacks, a large amount of threat intelligence is generated online every day. However, threat intelligence is mostly unstructured and multisource heterogeneous text. It is difficult for security analysts to understand the implicit threat in time. Knowledge Graph (KG) is an important research topic in recent years, which can perform automated and real-time analysis of threat intelligence in cybersecurity. As one of the critical technologies of KG, named entity recognition (NER) can identify cyberattack-related entities. It has been proved that long-distance structured information captured by dependency trees provides a rich semantic expression for the neural network. However, existing research works are more focused on the simple linear stack of neural networks when utilizing structured features. The interaction between different types of neural networks is vague. In addition, the existing models are insensitive to the boundaries of complex entity terms in cybersecurity. In this study, we propose a new f eature i ntegration and e ntity b oundary d etection (FIEBD) model. In our model, a new pretrained language model, PERT, is applied to obtain word embedding of cyber texts. Moreover, a novel neural network cell, namely GARU, is developed to incorporate different types of features extracted from graph neural networks and recurrent neural networks. It combines the graph encoder with the gate mechanism, aiming to obtain better hidden representation by explicit interaction. Furthermore, considering a large number of complex entities in cybersecurity, we contribute an entity boundary detection module to perform entity head and tail prediction as an augmentation task. We conduct extensive experiments on cybersecurity datasets. The results demonstrate that the proposed model achieves better performance than existing baseline methods. [ABSTRACT FROM AUTHOR]

The rising prevalence of drug-resistant pathogens is one of the biggest threats to human health. The development of new antibiotics that can overcome drug resistance is in urgent need. Herein, we designed and synthesized a series of amphiphilic tetrahydroquinoline derivatives as small-molecule-based antimicrobial peptidomimetics. Two lead compounds 36 and 52 which contained the tetrahydroquinoline core, hydrophobic alkyl chains (n-nonyl or isoprenyl group), different spacer lengths (n = 4 or 8), and cationic guanidine moiety, showed poor hemolytic activity, low cytotoxicity, and potent broad-spectrum antimicrobial activity against Gram-positive and Gram-negative bacteria, as well as fungi. The further biological evaluation revealed that compounds 36 and 52 can kill bacteria and fungi rapidly via membrane-targeting action and avoid drug resistance development. More importantly, compounds 36 and 52 exhibited similarly potent in vivo antimicrobial activities in a murine corneal infection caused by Staphylococcus aureus ATCC29213 or Pseudomonas aeruginosa ATCC9027, as compared to vancomycin or gatifloxacin. These results suggest that compounds 36 and 52 have great potential as new broad-spectrum antimicrobial agents to combat microbial resistance. [Display omitted] • A series of tetrahydroquinoline amphiphiles as antimicrobials were synthesized by biomimicking AMPs. • The lead compounds 36 and 52 exhibited potent broad-spectrum antimicrobial activity, and low cytotoxicity. • 36 and 52 can rapidly kill bacteria and fungi via membrane-targeting action and avoid drug resistance development. • 36 and 52 exhibited potent in vivo antimicrobial activities in a murine corneal infection model. [ABSTRACT FROM AUTHOR]

Sugarcane is a high biomass crop grown mostly in rain-fed environments. Water is a key determinant of sugarcane productivity, and in most production regions, varying and sometimes severe water stress occurs. Understanding the extent of genetic variation in response to water stress may allow for better targeted breeding programs. In this study a set of field experiments evaluating 31 sugarcane clones under rain-fed and irrigated conditions was conducted in two sugarcane production areas in Yunnan province, South China. While the water treatments had a large impact on mean cane yield there were little or no genotype × water treatment interactions for cane yield or sugar content at harvest, or for dry biomass sampled about five months (early biomass) after the start of crop growth. The high genetic correlation between well-watered and water stress treatments is consistent with the hypothesis that clone performance under water stress is mostly associated with general vigour rather than traits acting specifically under water stress. From a practical breeding program perspective the results suggest that choice or management of water stress level in selection trials is not a critical consideration for sugarcane breeding programs, and that selection under reasonably well watered conditions will be effective for attaining satisfactory selection gains under at least moderate levels of water stress. Early biomass was positively correlated with yield at final harvest for all water treatments. Resolution of the physiological basis of the high genetic correlations between growth under well-watered and water limited conditions may assist in future breeding efforts. [ABSTRACT FROM AUTHOR]

The impacts of pH on roots growth of sugarcane seedlings were explored by a pot test. The nutrient solution with three pH levels, i.e., 5.0, 7.0 and 8.5 were applied to culture five combination seedlings, including A (RB85-5156 × YR05-407), B (YR06-3501 × Tolodo), C (YT94-128 × GZ75-65), D (ROC6 × YR05-733) and E (VMC87-95 × YR05-171). The result indicated that root length, root surface, root volume and root diameter were all in the largest in B combination with solution pH= 7.0, and the root length, root surface, root volume were in the largest in combination A, C, D and E with solution pH=8.5. Root activity in combination C, D and E were in the highest with solution pH=5.0, while it was in the highest for combination B when pH=7.0. In general, the root growth and morphology in all five combinations were better in the solutions with pH of 7.0 and 8.5. [ABSTRACT FROM AUTHOR]

Objective To investigate whether blood haemoglobin A 1c ( HbA1c) levels was predicative of diabetic patients' responsiveness to surgical treatment of ankle fractures. Methods The relationship between blood HbA1c levels and surgical treatment outcomes of 21 diabetic patients undergoing open reduction internal fixation ( ORIF) for ankle fractures was analyzed with Pearson correlation testing and t testing. All patients were treated with ORIF using standard surgical techniques. Treatment outcomes were defined using radiological outcome, the American Orthopaedic Foot and Ankle Score ( AOFAS) ankle-hindfoot scale score, surgical revision rate, and complication rate. Results HbA1c levels were found to have a statistically significant correlation with poor radiological outcomes ( r = 0.547) and AOFAS ankle-hindfoot scores ( r = −0.592). Additionally, though rates of poor radiological outcome, revision, and complication were high in the diabetic population as a whole, these rates were considerably higher among individuals with elevated HbA1c (≥6.5%) and considerably lower among individuals with lower HbA1c (<6.5%) levels. Conclusion Blood HbA1c levels appear to be predictive of risk and complication rates in the surgical treatment outcomes of diabetic patients with ankle fractures. [ABSTRACT FROM AUTHOR]

Smoking has long been associated with osteoporosis, decreased bone mineral density, increased risk of bone fracture, and increased health costs. Nicotine, the main component of cigarette smoke, has major negative effects on bone metabolism and skeletal remodeling in vivo. Although osteoblasts and osteoblast-like cells have been used extensively to study the impact of nicotine, few studies have been performed on human mesenchymal stem cells (hMSCs). In this context, we examined the impact of nicotine on (a) hMSCs proliferation, (b) osteoblastic differentiation, (c) alkaline phosphatase (ALP) activity, and (d) expression of canonical genes during differentiation of hMSCs. MSCs isolated from human bone marrow were treated with different concentrations (0, 0.1, 1 and 10 μM) of nicotine for 7 days. Nicotine caused a dose-dependent decrease in cell proliferation, decreased heme oxygenase-1 (HO-1) expression ( p < 0.05) and attenuated osteogenesis ( p < 0.05) in hMSCs (45 % reduction at day 14). In addition, nicotine caused a dose-dependent decrease in alizarin red staining for calcium and staining for ALP. Induction of HO-1 by peroxisome proliferator-activated receptor delta agonist (GW0742) prevented the effect of nicotine. Nicotine caused a dose-dependent reduction in the expression of BMP-2, a well-known marker for bone formation; however, this was prevented by GW0742 treatment. Therefore, induction of HO-1 prevents the deleterious effects of nicotine on osteogenesis in hMSC. This offers insight into both how nicotine affects bone remodeling and a therapeutic approach to prevent fracture and osteoporosis in smokers. [ABSTRACT FROM AUTHOR]

Identifying influential nodes in social networks is a fundamental task. Due to the development of Graph Neural Networks, Graph Convolution Network (GCN) based model has been introduced to solve this problem. Compared to traditional methods, the existing GCN-based models are more accurate in identifying influential nodes because they can better aggregate the multi-dimension features. However, the GCN-based method treats this problem as a binary classification task rather than a regression task, making it less practical. To make the GCN-based model more practical, we treat identifying influential nodes as a regression task. Moreover, when aggregating neighbor features, GCN ignores the difference in neighbor importance, which will affect the prediction performance of the GCN-based models. This paper proposes a graph multi-head attention regression model to address these problems. Vast experiments on twelve real-world social networks demonstrate that the proposed model significantly outperforms baseline methods. To the best of our knowledge, this is the first work to introduce the multi-head attention mechanism to identify influential nodes in social networks. [ABSTRACT FROM AUTHOR]

Abstract: Background: Many investigators have conducted studies to determine the biomechanics, causes, complications and treatment of unilateral facet joint dislocation in the cervical spine. However, there is no quantitative data available on morphological changes in the intervertebral foramen of the cervical spine following unilateral facet joint dislocation. These data are important to understand the cause of neurological compromise following unilateral facet joint dislocation. Methods: Eight embalmed human cadaver cervical spine specimens ranging from level C1-T1 were used. The nerve roots of these specimens at C5-C6 level were marked by wrapping a 0.12mm diameter wire around them. Unilateral facet dislocation at C5-C6 level was simulated by serially sectioning the corresponding ligamentous structures. A CT scan of the specimens was obtained before and after the dislocation was simulated. A sagittal plane through the centre of the pedicle and facet joint was constructed and used for measurement. The height and area of the intervertebral foramen, the facet joint space, nerve root diameter and area, and vertebral alignment both before and after dislocation were evaluated. Results: The intervertebral foramen area changed from 50.72±0.88mm2 to 67.82±4.77mm2 on the non-dislocated side and from 41.39±1.11mm2 to 113.77±5.65mm2 on the dislocated side. The foraminal heights changed from 9.02±0.30mm to 10.52±0.50mm on the non-dislocated side and 10.43±0.50mm to 17.04±0.96mm on the dislocated side. The facet space area in the sagittal plane changed from 6.80±0.80mm2 to 40.02±1.40mm2 on the non-dislocated side. The C-5 anterior displacement showed a great change from 0mm to 5.40±0.24mm on the non-dislocated side and from 0mm to 3.42±0.20mm on the dislocated side. Neither of the nerve roots on either side showed a significant change in size. Conclusions: The lack of change in nerve root area indicates that the associated nerve injury with unilateral facet joint dislocation is probably due to distraction rather than due to direct nerve root compression. [Copyright &y& Elsevier]

Background Context: Cervical traction has a long history as a method of conservative treatment for cervical spine diseases. However, information on quantitative changes in the cervical neural foramen resulting from axial traction in vivo is lacking. Purpose: To quantitatively evaluate the changes in the neural foramen of the cervical spine during axial traction in vivo. Study Design: A prospective radiographic analysis of the cervical neural foramen of adult volunteers. Patient Sample: Fifteen healthy volunteers (10 men, 5 women) without any history of cervical spine disease. Outcome Measures: The changes in cervical cross-sectional foraminal areas and heights were measured. Methods: Cervical magnetic resonance (MR) images of the volunteers were taken at the neutral position and were reconstructed in the oblique plane perpendicular to the long axis of each neural foramen from the C2-3 to the C6-7 level. The changes in the neural foraminal dimensions at incremental axial traction forces (0, 5, 10, and 15 kg) were analyzed. Results: After each 5-kg incremental increase in traction weight, there was a significant (p value less than .05) increase in area and height of the intervertebral foramen compared with the position in which no weight was applied. There was an average increase of 5.81%, 16.56%, and 18.9% in the foraminal area and an average increase of 3.75%, 8.67%, and 10.43% in foraminal height compared with the position with no weight at traction of 5, 10, and 15 kg, respectively. There was no statistically significant difference for the increase in foraminal area and height from 10 to 15 kg of traction (p value greater than .05). Conclusions: There was a significant increase in intervertebral foraminal area and height after each 5-kg increment in traction weight compared with the position in which no weight was applied. From 10 to 15 kg of traction, there was no significant change in the foraminal area and height. [ABSTRACT FROM AUTHOR]

Background Context: The halo skeletal fixator provides the most rigid type of immobilization of all the orthoses that stabilize the cervical spine. Sometimes with older patients (>70 years old), the pin penetrates the cortical and cancellous bone of the skull and enters the intracranial space, which can result in serious complications such as brain injury, infection, hematoma, and loss of cerebrospinal fluid from the subarachnoid space. Currently, there is a lack of relevant literature that examines these concerns. Purpose: To evaluate the thickness of the outer table, diploe, and inner table at the anterolateral and posterolateral pin insertion areas of the skull in elderly cadavers by using computed tomography (CT) scans. In addition, insertion torques at the four standard pin insertion areas was determined by applying halo pins at incremental torque in an effort to suggest safe torque levels for the anterolateral and posterolateral pins. Study Design/setting: A human cadaveric anatomical and biomechanical study relating to thickness and insertion torques at standard pin areas in the elderly. Patient Sample: Twenty-one elderly cadaveric skull specimens. Outcome Measures: Thickness of cortices (tables) and diploe of skull and insertion torque at halo pin insertion areas. Methods: Aquarius Image software at the CT scanner's TeraRecon Aquarius Workstation was used to make the necessary skull thickness measurements at the pin insertion areas. Six, 8, 12, 18, and 36 inch lb of torque were used to determine penetration of the pins through the inner table at each of the four locations (two anterolateral and two posterolateral). Results: The mean anterolateral thickness was 7.36+/-1.57 mm. The average thickness of the outer table, diploe, and inner table were 2.24+/-0.44 mm, 1.52+/-0.41 mm, and 3.59+/-1.70 mm, respectively. The mean posterolateral thickness was 9.47+/-1.12 mm. The average thickness of the outer table, diploe, and inner table were 4.32+/-0.92 mm, 1.88+/-0.35 mm, and 3.27+/-1.21 mm, respectively. No pin penetration was seen at the traditional 8 inch lb of insertion torque in both the anterolateral and posterolateral pin insertion areas. Eighteen inch lb of torque resulted in penetration in 90.48% (19/21) and in 85.71% (18/21) of specimens in the left anterolateral and right anterolateral pin insertion areas, respectively. No penetration was seen even at 36 inch lb of torque in 80.95% (17/21) of the cadavers in both the left and right posterolateral pin insertion areas. Conclusions: The current study supported previous research that 8 inch lb of torque is safe for application of halo pins in the elderly. The posterolateral skull is thicker and stronger than the anterolateral skull. The safe maximum torque is 8 inch lb for anterolateral pin insertion area and 18 inch lb for the posterolateral pin insertion area. [ABSTRACT FROM AUTHOR]

Abstract: Background context: Long-term results of patients treated with conventional laminoplasty have shown a significant number of patients complicated with kyphotic deformity. The authors hypothesize that by maintaining the spinous process–ligament–muscle complex (SPLMC) during laminoplasty, followed by postoperative muscle strengthening exercises, the formation of kyphosis can be decreased. Purpose: To evaluate the incidence of kyphosis in a select patient group undergoing laminoplasty with preservation of the SPLMC followed by neck strengthening exercises. Study design/setting: A midterm retrospective study of 30 patients following laminoplasty with preservation of the SPLMC. Patient sample: Thirty consecutive patients with cervical myelopathy attributable to multilevel cervical spinal stenosis underwent laminoplasty with preservation of the SPLMC from April 1998 to July 2002. Outcome measures: Preoperative and postoperative Japanese Orthopedic Association (JOA) scores, Guigui angles, and axial symptoms were measured. Methods: Thirty patients with multiple-level cervical myelopathy were studied. Fourteen had a normal lordotic curve, whereas 16 had a straight curve. All these patients underwent laminoplasty with preservation of the SPLMC. For the first 6 months, isometric neck muscle exercises were performed. After this time, the intensity of the exercises was gradually increased. Results: The average preoperative JOA score was 5.8±1.4. Mean JOA score at 3.8 years follow-up was 13.6±2.1. The recovery ratio was 69%. All 14 presurgical lordotic curves remained lordotic. Fourteen of the 16 straight spines improved to a lordotic configuration. Using the Guigui method, the preoperative lordotic angle was corrected by approximately 9 degrees (mean preoperative of 9.89±1.13 degrees, mean postoperative of 18.66±1.85 degrees), and the preoperative straight angle was corrected by approximately 15 degrees (mean preoperative of 0.91±2.14 degrees, mean postoperative of 15.88±1.71 degrees). Conclusions: Laminoplasty with preservation of the SPLMC followed by appropriate postoperative muscle exercises may be an encouraging way to maintain or restore the physiological curve and prevent kyphotic deformity at a medium term follow-up. [Copyright &y& Elsevier]

Background Context: Transarticular C1-2 screws are widely used in posterior cervical spine instrumentation. Injury to the vertebral artery during insertion of transarticular Cl-2 screw remains a serious complication. Use of a computer-assisted surgery system decreases this complication considerably. However, this system encounters problems in ensuring complete accuracy because of positional variations during preoperative and intraoperative imaging generation. Therefore, intraoperative fluoroscopy still is one of the commonly used methods to guide insertion of transarticular Cl-2 screw. Evaluation of a true lateral radiographic view of the C2 pedicle for screw trajectory during C1-2 transarticular screw insertion may help to minimize this potential complication. Purpose: To evaluate the value of intraoperative true lateral radiograph of the C2 pedicle for screw trajectory during C1-2 transarticular screw insertion. Study Design: To compare the height of the C2 pedicle area allowing instrumentation on true lateral view radiograph of the C2 pedicle and computed tomographic (CT) scan with multiplanar reconstruction. Methods: Twenty embalmed human cadaveric cervical spine specimens were used to insert a total of 40 C1-2 transarticular screws using Magerl and Seemann technique. One side of the C2 transverse foramen was filled with radiopaque material (lead oxide) to simulate the artery and to demarcate the danger zone for better visualization on radiography. Measurements and calculation of the mean and standard deviation of the height of the area allowing instrumentation of the C2 pedicle were done on true lateral view radiograph of the C2 pedicle, the sagittal and 30 degrees sagittal views relative to the frontal plane passing exactly through the center of the C2 pedicle of CT scans. Student t test was applied to calculate the statistical significance of measured values. Statistical significance was defined as pResults: On true lateral radiographic views of the C2 pedicle, the height of the area allowing instrumentation of the pedicle was 7.75+/-0.92 mm (right) and 7.64+/-0.63 (left), p>or=.36. Using sagittal CT scan views, the height of pedicles was 7.71+/-0.7 mm (right) and 7.58+/-1.01 mm (left), p>or=.23. On 30 degrees sagittal CT scan views, the height of pedicles was 7.84+/-1.00 mm (right) and 7.76+/-1.02 mm (left), p>or=.27. The p value was >or=.78, >or=.56, and >or=.49 for true lateral radiographic view and sagittal CT scan view, true lateral radiographic view and 30 degrees sagittal CT scan view, and sagittal CT scan view and 30 degrees sagittal CT scan views, respectively. On lateral view of cervical spine, the decline angle of the transarticular screw was 51.3+/-0.50 degrees (right) and 50.68+/-0.41 degrees (left), p>or=.17. Mean decline angle was 51+/-0.43 degrees . On the anteroposterior (AP) view, radiograph median angle was 6.87+/-0.53 degrees (right) and 6.0+/-0.59 degrees (left), p>or=.25. Mean median angle was 6.44+/-0.62 degrees. Conclusions: True lateral radiographic views of the pedicles provide useful information for defining screw trajectory intraoperatively. Using this view along with AP and lateral view of cervical spine and preoperative three-dimensional CT scan may narrow the margin of error in this delicate area. [ABSTRACT FROM AUTHOR]

Directed cell migration towards a softer environment is called negative durotaxis. The mechanism and pathological relevance of negative durotaxis in tumor progression still requires in-depth investigation. Here, we report that YAP promotes the negative durotaxis of melanoma. We uncovered that the RhoA-myosin II pathway may underlie the YAP enhanced negative durotaxis of melanoma cells. Acral melanoma is the most common subtype of melanoma in non-Caucasians and tends to develop in a stress-bearing area. We report that acral melanoma patients exhibit YAP amplification and increased YAP activity. We detected a decreasing stiffness gradient from the tumor to the surrounding area in the acral melanoma microenvironment. We further identified that this stiffness gradient could facilitate the negative durotaxis of melanoma cells. Our study advanced the understanding of mechanical force and YAP in acral melanoma and we proposed negative durotaxis as a new mechanism for melanoma dissemination. [ABSTRACT FROM AUTHOR]

The first-order optimizers in deep neural networks (DNN) are of pivotal essence for a concrete loss function to reach the local minimum or global one on the loss surface within convergence time. However, each optimizer possesses its own superiority and virtue when encountering a specific application scene and environment. In addition, the existing modified optimizers mostly emphasize a given optimizer without any transfer property. In this paper, a zeroing neural dynamics (ZND) based optimization approach for the first-order optimizers is proposed, which can assist ZND via the activation function to expedite the process of solving gradient information, with lower loss and higher accuracy. To the best of our knowledge, it is the first work to integrate the ZND in control domain with the first-order optimizers in DNN. This generic work is an optimization method for the most commonly-used first-order optimizers to handle different application scenes, rather than developing a brand-new algorithm besides the existing optimizers or their modifications. Furthermore, mathematic derivations concerning the gradient information transformation of the ZND are systematically provided. Finally, comparison experiments are implemented, which demonstrates the effectiveness of the proposed approach with different loss functions and network frameworks on the Reuters, CIFAR, and MNIST data sets. [ABSTRACT FROM AUTHOR]

With the popularity of cloud computing and IoT, consistently increasing data brings us a great burden to store locally. Due to the local limited storage capacity and expensive maintenance cost, individuals and enterprises are preferred to outsource their data to the public commercial cloud (e.g., Google Drive and Dropbox). However, the commercial cloud can not be fully trusted because data on the cloud may be modified by various reasons (e.g., outside hackers' attacks, hardware or software failures). To ensure data integrity, one of the most popular techniques is secure cloud storage (SCS). Nevertheless, traditional solutions of SCS with heavy cryptographic operations make data outsourcing computationally complicated. Moreover, most proposed approaches only focus on verifying data integrity while neglecting the functionality of data dynamics. To address these issues, we propose a Sec ure A uditable C loud S torage (SecACS) scheme supporting data dynamics. SecACS requires less computation time by employing lightweight cryptographic operations. Compared to the previous solutions, the extensive experimental results demonstrate that SecACS achieves one order of magnitude faster in outsourcing data and twice faster in checking data integrity. [ABSTRACT FROM AUTHOR]

Recently, deep learning-based image watermarking methods have been proposed for copyright protection, which are robust to common post-processing operations. However, they suffer from distinct performance drops to open-set distortions, where distortions applied on testing samples are unseen in the training stage. To address this issue, we propose a random distortion assignment-based meta-learning framework for robust image watermarking, where meta-train and meta-test tasks are constructed to simulate open-set distortion scenarios. The embedding and extraction network of watermark information is constructed based on the invertible neural network and equipped with a multi-stage distortion layer, which can conduct random combinations of basic post-processing operators. Besides, to obtain a better balance between robustness and visual imperceptibility, a hybrid loss function is designed by considering global and local similarities based on wavelet decomposition to capture multi-scale texture information. Extensive experiments are conducted by considering various open-set distortions to verify the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Vital nodes identification in social networks keeps attracting lots of attention in recent years because of its great theoretical and practical significance for many applications. Degree centrality is one of the most efficient neighborhood-based metrics and has been widely used because of its simplicity and low computation complexity. Many other centralities derived from degree have been proposed to try to further improve the accuracy on ranking performance by extending the coverage area of neighbors. But a common problem of degree and its extensional centralities is that the directivity of edges between nodes is not considered. In directed network, nodes' importance are not only related with their neighbor numbers but also related with the relationships between the nodes and their neighbors. In this paper, we propose a modification method with an adjustable parameter α on degree to improve its ranking accuracy in directed networks. This method redefines the degree of a node by separately taking into account its out-degree and in-degree and uses parameter α to flexibly set the relative weights between out-degree and in-degree when evaluating nodes' importance in different scenes, which can effectively avoid the situation that too many neighbors from one direction could lead to extreme high value of centrality. We also apply this method on another two centralities: semi-local and k-hop, and for the two centralities that considering multi-step neighbors, the corresponding improvement centralities could eliminate the irrelevant multi-step neighbors when evaluating nodes' importance. Experimental results in 3 real social networks and 1 artificial network indicate that, setting α to be appropriate value the improvement centralities can better estimate nodes' connection abilities, propagation abilities and immunization abilities while keeping the same compute complexity with the corresponding original centralities, especially in the network with low percentage of bidirectional edges. Moreover, the improvement method proposed in this paper also can be applied to other centralities, such as eigenvector centrality, neighborhood centrality, Exdegree centrality and percolation based centrality, to improve their performances in directed networks. • Improved method redefines a node degree by separately considering in and out degree. • Improvement centrality performs better on identifying bridge nodes with α = 0. 5. • Improvement centrality performs better on identifying influential nodes with α > 0. 5. • Improvement centrality performs better on identifying immunization node with proper α. • Improvement method performs better in networks with fewer bidirectional edges. [ABSTRACT FROM AUTHOR]

Background: Adult head and neck rhabdomyosarcoma (HNRMS) is an exceptionally rare malignancy, and there is a paucity of data and research dedicated to understanding its characteristics and management in adult populations. This study aimed to assess the outcomes and identify survival predictors in adult HNRMS. Methods: We retrospectively evaluated 42 adult patients (> 16 years) with HNRMS who received radiotherapy (RT)-based treatment at our institute between 2008 and 2022. We analysed the clinical characteristics and prognosis of these patients, including the locoregional recurrence-free survival (LRFS), progression-free survival (PFS), and overall survival (OS), using the Kaplan–Meier method. The chi-square and Fisher's exact tests were used to analyse differences between groups for dichotomous and categorical variables, respectively. Survival rates were calculated using the Kaplan–Meier method. Prognostic variables were assessed through univariate Cox analyses. Results: The median patient age was 28 years (range, 16–82 years). Alveolar RMS was the most common histological type, observed in 21 patients (50.0%), followed by embryonal in 16 patients (38.1%). The anatomic sites of origin were orbital in one (2.4%), parameningeal in 26 (61.9%), and non-orbital/non-parameningeal in 15 (35.7%) patients. Nineteen patients (45.2%) had regional lymph node metastasis, and five patients (11.9%) presented with distant metastatic disease. Distant metastasis (n = 17) was the primary cause of treatment failure. At a median follow-up of 47.0 months, the 5-year LRFS, PFS, and OS rates were 69.0%, 39.7%, and 41.0%, respectively. Univariate analysis revealed that tumour size, lymph node involvement, and the local treatment pattern (surgery and RT vs. RT alone) were significant predictors of survival. Conclusions: The main failure pattern in patients with HNRMS receiving RT-based treatment was distant metastasis. Tumour size > 5 cm and lymph node involvement were predictors of worse LRFS. Multimodality local treatment, combining surgery and RT, is effective and provides survival benefits. [ABSTRACT FROM AUTHOR]

Cross-modality matching refers to the problem of comparing similarity/dissimilarity of a pair of data points of different modalities, such as an image and a text. Deep neural networks have been popular to represent data points of different modalities due to their ability to extract effective features. However, existing works use simple distance metrics to compare the deep features of multiple modalities, which do not fit the nature of cross-modality matching, because it imposes the features of different modalities to be of the same dimension and do not allow cross-feature matching. To solve this problem, we propose to use convolutional neural network (CNN) models with soft-max activation layer to represent a pair of different-modality data points to two histograms (not necessarily of the same dimensions) and compare their dissimilarity by using earth mover's distance (EMD). The EMD can match the features extracted by the two CNN models of different modalities freely. Moreover, we develop a joint learning framework to learn the CNN parameters specifically for the EMD-driven comparison, supervised by the relevance/irrelevance labels of the data pairs of different modalities. The experiments over applications such as image–text retrieval, and malware detection show its advantage over existing cross-modality matching methods. [ABSTRACT FROM AUTHOR]

In adaptive steganography, existing universal stego post-processing methods can enhance security, but suffer from incorrect extraction of messages and undesired visual defects, especially in flat regions. To address this issue, a reversible adversarial steganography method is proposed by modifying the LSB or 2ndLSB of stego-images, which has promising visual quality and security. To that end, the content-adaptive adversarial perturbations are first generated, which consider image texture with noise residual features to counter deep learning-based steganalyzers. Then, a data compression strategy of adversarial perturbations is designed by applying lossless run-length encoding based on the sparse nature of non-zero elements in the perturbations to reduce the perturbation's quantity. Finally, reversible data hiding based on ternary coding is applied to embed and extract stego images with compressed adversarial perturbations. Extensive experimental results demonstrate that the proposed method can effectively enhance security and visual quality compared with state-of-the-art methods. • A reversible adversarial steganography framework is proposed for better security. • A content-adaptive adversarial perturbation is designed to improve the image quality. • A data compression strategy is applied to boost the reversible embedding process. • Experiments verify better security against targeted and non-targeted steganalysis. [ABSTRACT FROM AUTHOR]

SUMMARY: The characterization of cis‐regulatory DNA elements (CREs) is essential for deciphering the regulation of gene expression in eukaryotes. Although there have been endeavors to identify CREs in plants, the properties of CREs in polyploid genomes are still largely unknown. Here, we conducted the genome‐wide identification of DNase I‐hypersensitive sites (DHSs) in leaf and stem tissues of the auto‐octoploid species Saccharum officinarum. We revealed that DHSs showed highly similar distributions in the genomes of these two S. officinarum tissues. Notably, we observed that approximately 74% of DHSs were located in distal intergenic regions, suggesting considerable differences in the abundance of distal CREs between S. officinarum and other plants. Leaf‐ and stem‐dependent transcriptional regulatory networks were also developed by mining the binding motifs of transcription factors (TFs) from tissue‐specific DHSs. Four TEOSINTE BRANCHED 1, CYCLOIDEA, and PCF1 (TCP) TFs (TCP2, TCP4, TCP7, and TCP14) and two ethylene‐responsive factors (ERFs) (ERF109 and ERF03) showed strong causal connections with short binding distances from each other, pointing to their possible roles in the regulatory networks of leaf and stem development. Through functional validation in transiently transgenic protoplasts, we isolate a set of tissue‐specific promoters. Overall, the DHS maps presented here offer a global view of the potential transcriptional regulatory elements in polyploid sugarcane and can be expected to serve as a valuable resource for both transcriptional network elucidation and genome editing in sugarcane breeding. Significance Statement: Whole genome‐wide open chromatin maps were constructed in the auto‐octoploid species Saccharum officinarum. We revealed that distal open chromatin was prevalent in sugarcane. Leaf‐ and stem‐specific promoters were isolated, which can be expected to serve as a valuable resource for both transcriptional network elucidation and genome editing in sugarcane breeding. [ABSTRACT FROM AUTHOR]

Now, the classifier network anomaly traffic detection method is generally considered to be a general method of good detection effect and high detection precision. In order to detect abnormal network traffic more efficiently, so as to ensure the security of Internet users, a network traffic anomaly detection algorithm based on Mahout Classifier is studied. Aiming at the problem of time correlation and the influence of abnormal samples on accuracy of detection statistics, and the first detection point is eliminated and the applicable detection point is added. The BP neural network algorithm and Bayesian network model are used to predict the abnormal probability of the anomaly node, the detection precision is optimized, and the exception points of the training set are reorganized. In view of the anomalies detected by anomaly detection models, an emergency response method is proposed, which not only detects anomalies, but also handles anomalies. [ABSTRACT FROM AUTHOR]

Abstract Background Anterior cervical trans-pedicle screw fixation was introduced to overcome some of the disadvantages associated with anterior cervical corpectomy and fusion. In vitro biomechanical studies on the trans-pedicle screw fixation have shown excellent pull-out strength and favorable stability. Comprehensive biomechanical performance studies on the trans-pedicle screw fixation, however, are lacking. Methods The control computed tomography images (C2-T2) were obtained from a 22-year-old male volunteer. A three dimensional computational model of lower cervical spine (C3-T1) was developed using computed tomography scans from a 22 year old human subject. The models of intact C3-T1 (intact group), anterior cervical trans-pedicle screw fixation (trans-pedicle group), and anterior cervical corpectomy and fusion (traditional group) were analyzed with using a finite element software. A moment of 1 N·m and a compressive load of 73.6 N were loaded on the upper surface and upper facet joint surfaces of C3. Under six conditions, four parameters such as the range of motion, titanium mesh plant stress, end-plate stress, and bone-screw stress were measured and compared on two treatment groups. Findings Compared with the intact model, the range of motions for treatment groups were decreased. Compared with cervical corpectomy and fusion, the titanium plant, C4 upper end-plate and C7 lower end-plate stresses in trans-pedicle group were reduced. No significant difference was discovered on bone-screw stress between the two groups for lateral flexion and rotation, but bone-screw stress is smaller in trans-pedicle group when compared with traditional group. With exception of individual difference, trans-pedicle group had better biomechanical results than traditional group in range of motions, titanium mesh plant stress, end-plate stress and bone-screw stress. Interpretation The trans-pedicle method has better biomechanical properties than the anterior cervical corpectomy and fusion making it a viable alternative for cervical fixations. Highlights • Anterior trans-pedicle screw fixation reconstruction FE model was built. • Biomechanical properties on this model were comprehensively analyzed. • By comparing the two reconstruction models, better biomechanical properties in this model were discovered. • Bone-screw interface stresses were greater in the caudal level than in cranial level. [ABSTRACT FROM AUTHOR]

With the rapid development of social networks, hackers begin to try to spread malware more widely by utilizing various kinds of social networks. Thus, studying malware epidemic dynamics in these networks is becoming a popular subject in the literature. Most of the previous works focus on the effects of factors, such as network topology and user behavior, on malware propagation. Some researchers try to analyze the heterogeneity of infection rates, but the common problem of their works is the factors they mentioned that could affect the heterogeneity are not comprehensive enough. In this paper, focusing on the effects of heterogeneous infection rates, we propose a novel model called HSID (heterogeneous-susceptible–infectious–dormant model) to characterize virus propagation in social networks, in which a connection factor is presented to evaluate the heterogeneous relationships between nodes, and a resistance factor is introduced to represent node’s mutable resistant ability. We analyzed how key parameters in the two factors affect the heterogeneity and then performed simulations to explore the effects in three real-world social networks. The results indicate: heterogeneous relationship could lead to wider diffusion in directed network, and heterogeneous security awareness could lead to wider diffusion in both directed and undirected networks; heterogeneous relationship could restrain the outbreak of malware but heterogeneous initial security awareness would increase the probability; furthermore, the increasing resistibility along with infected times would lead to malware’s disappearance in social networks. [ABSTRACT FROM AUTHOR]

Sugarcane is a complex polyploid aneuploid cash crop, and transgenic varieties are important for molecular genetic and traditional breeding approaches. Herein, the sugarcane variety ROC22 served as the receptor, the Bar gene served as a screening marker, and positive and negative fragments of the ScD27.2 gene, upstream of strigolactones (SLs) biosynthesis genes driven by the 35S promoter, were introduced by Agrobacterium tumefaciens-mediated transformation. Regenerated plants were obtained by co-culture, screening culture, and differentiation induction, and 27 sense and antisense ScD27.2 transgenic seedlings were obtained by herbicide screening. PCR detection and 1% Basta (Glufosinate) application on leaves revealed Bar in all lines, with all testing positive for herbicide application and 23 containing the target gene (positive resistance screening rate = 87.5%). q-PCR and phenotypic analyses showed that ScD27.2 expression, plant height, tiller number, root length, stem diameter, and fresh weight were decreased in transgenic (ScD27.2R-9) compared with non-transgenic (NT and ScD27.2F-2) lines. ScD27.2 expression was downregulated, and growth potential was inhibited. Under 20% PEG treatment, malondialdehyde (MDA) content in ScD27.2R-9 was higher than in NT, while proline content was lower. Under drought stress, ScD27.2 expression, MDA levels, and proline content in ScD27.2F-2 and NT were higher than in non-treated controls, ScD27.2 expression increased with time, and MDA and proline levels also increased. ScD27.2 expression in ScD27.2R-9 decreased under 20% PEG treatment, MDA and proline increased (but not to NT levels), and growth was lower than NT. The 20% PEG treatment also increased the levels of (±)-2′-epi-5-deoxystrigol and (+)-abscisic acid in the rooting culture media of ScD27.2F-2, ScD27.2R-9, and NT lines, but the levels of (+)-abscisic acid content in ScD27.2R-9 was lower than in NT. Thus, interfering with ScD27.2 expression decreased resistance to 20% PEG treatment. ScD27.2 encodes a β-carotene isomerase involved in SLs biosynthesis that might function in sugarcane resistance to drought stress. It explains the role of SLs in sugarcane growth and development and responses to drought stress. [ABSTRACT FROM AUTHOR]