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Because of the development of the social economy, people's living standards are also constantly improving recent years. The effect of weather forecast on social economy is more and more important, which has a great influence on agricultural production and personal life. With the advancement of the observation automati-on business, small disturbances may cause systematic errors in observation data. The meteorological observation data's quality is an important factor that directly affects the accuracy of weather forecast and climate forecast. The traditional quality control algorithm uses the climatological limit value of historical data and the allowable value of elements to check, lacks sensitivity to elements fancy changes, and not suitable for demend of quality control. This paper introduces a quality control project of multi-source weather observation based on data mining. Starting from the correlation between the observations of the alike observation element which is not at the same time (time correlation), and the correlation between unlike observation elements at the same time (element correlation), combined with the relevant algorithms in data mining, the paper proposes Two different quality control methods for multi-source meteorological observation data, combined with the complementarity and correlation of the two methods, a synthetic quality control programme is established.

To better understand the effect of growing location on the phytochemical compounds and sensory properties of blueberry (Vaccinium spp.), here we investigated rabbiteye blueberry ‘Brightwell’ (Vaccinium ashei cv. ‘Brightwell’) grown in 10 locations of China. Significant differences in terms of total soluble solids, titratable acidity, flavonoids, phenols, as well as proanthocyanidins and anthocyanins, were found in the fruits (berries) of blueberry plants among the different sampled locations. Furthermore, their sensory properties, which evaluated by the electronic tongue method, also significantly differed among the 10 locations. The content of flavonoids, phenols, proanthocyanidins, and anthocyanins all had significant correlations with sensory properties, except that of aftertaste-astringency. A key finding to emerge was that blueberry plants grown at high altitude locations harbored a high content of total soluble solids, flavonoids, phenols, proanthocyanidins, and anthocyanins along with high scores for the sweetness. These results suggested cultivating blueberry at high altitude can produce fruit that not only possess pronounced beneficial health effects but also good taste.

BACKGROUND This study was conducted to investigate the reliability and efficacy of polyvinyl alcohol combined with coils in the embolization of iatrogenic renal vascular injury with the assistance of 3-dimensional digital subtraction angiography (3D-DSA). MATERIAL AND METHODS Twenty-six patients with minimally invasive renal bleeding who underwent transarterial embolization from January 2012 to January 2019 in our hospital were included in the study. We obtained demographic data from these patients, as well as information on clinical presentation, renal procedures used for treatment, and perioperative details. The changes in renal function tests, serum hemoglobin, serum hematocrit, and technetium Tc 99m dimercaptosuccinic acid (99mTc-DMSA) levels pre- and postembolization were compared. In addition, the embolic area and the technical and clinical success rates were analyzed. Finally, an angiographic manifestation of the renal artery, 3D-DSA, and the effect of embolization were analyzed retrospectively. RESULTS All patients achieved technical and clinical success after embolization (100%, 26/26). There were no significant differences between pre- and postoperative estimated glomerular filtration rate, serum parameters, and 99mTc-DMSA. The embolic area was 12%±10%. Patients did not exhibit severe complications during the follow-up period. CONCLUSIONS Proximal embolization technique assisted by 3D-DSA for renal iatrogenic hemorrhage and vascular lesions is both safe and efficacious, offering high rates for both clinical and technical success. It maximizes the protection of the kidney and reduces the rate of renal resection.

Scabies is a highly contagious disease caused by Sarcoptes scabiei which burrows into stratum corneum of host&rsquo, s skin. In this study, after optimizing vaccination schedule, a vaccination trial is comprised of three test groups of rabbits (n = 10/group) by immunization with (1) rSsCLP5, (2) rSsCLP12, or (3) a mixture of rSsCLP5 and rSsCLP12, three biological replicates groups (n = 10/group) and three control groups (n = 10/group). Levels of specific IgG, total IgE and cytokines in sera were detected and histopathologically analyzed as indicators of vaccine effects. The results showed that 85% (17/20) of rabbits exhibited no detectable skin lesions of S. scabiei infestation in mixed protein groups compared to single protein groups with 75% (15/20) and 70% (14/20), respectively. Moreover, the deworming rates of mixed groups are increased by 10%&ndash, 20% compared with that of single groups. Each of six groups immunized with rSsCLP displayed significant increases of specific IgG, total IgE, IL-10, and TNF-&alpha, The degree of skin damage in test groups also significantly lower than that of control groups. Thus, purified rSsCLP5 and rSsCLP12 subunit cocktail vaccine induced robust immune protection and could significantly decrease mite populations to reduce the direct transmission between rabbits.

Background Accumulating evidence has demonstrated that long non‐coding RNAs (lncRNAs) MIAT is significantly upregulated in many cancer types including gastric cancer (GC). However, the potential clinical significance of serum exosomal MIAT in GC is unknown. Methods In this study, a total of 109 GC patients, 48 gastric adenoma patients, and 50 healthy individuals were recruited. Serum exosomal MIAT levels were detected in all participants using quantitative real‐time reverse transcription‐polymerase chain reaction (qRT‐PCR). Results The exosomes we extracted from the serum samples were positive for TSG101, CD63, and Flotillin‐1, which were known exosome markers. Serum exosomal MIAT levels were significantly higher in GC patients than in gastric adenoma patients and healthy controls. Interestingly, gastric adenoma patients with higher serum exosomal MIAT expression were more prone to develop GC. In addition, serum exosomal MIAT levels were significantly decreased in post‐treatment blood samples compared to pre‐treatment samples, while markedly increased in the cases suffering recurrence. Moreover, serum exosomal MIAT upregulation was significantly associated with worse clinical variables and shorter survival. Furthermore, serum exosomal MIAT was identified as an independent prognostic factor for GC. Conclusions Collectively, serum exosomal lncRNA MIAT might serve as a promising novel biomarker for monitoring the progression of GC.

With the development of the Industrial Internet of Things and the continuous expansion of application scenarios, many development bottlenecks have followed. Its data security issue has become an obstacle to its widespread application. It has attracted substantial attention from both academia and industry. Blockchain technology has the characteristics of decentralization, openness and transparency and non-tampering. It has natural advantages in solving the security of the Industrial Internet of Things. Accordingly, this paper first analyzes the security risks associated with data storage in the Industrial Internet of Things and proposes the use of blockchain technology to ensure the secure storage of data in the Industrial Internet of Things. In traditional blockchains, the data layer uses Merkle hash trees to store data; however, the Merkle hash tree not able to provide non-member proof, which makes it unable to resist attacks from malicious nodes in the network. To solve this problem, this paper replaces the Merkle hash tree with a password accumulator to provide member proof and non-member proof. Moreover, the existing accumulators have trapdoors and cannot be updated in batches, and unable to meet the blockchain’s expansion requirements. This paper presents an improved RSA accumulator and gives the definition of the accumulator. Finally, this paper uses RSA to construct a batch update accumulator scheme without trapdoor, and shows that the scheme is feasible through correctness and security

The renewable energy plays an increasingly important role in many fields such as lighting, automobile, and electric power. In order to make full use of the renewable energy, various smart Internet of Thing (IoT) devices are deployed. However, in the field of energy management, the two-way mismatch between the demand and the supply of the renewable energy will greatly affect the efficiency of the renewable energy. In addition, the security threat of the energy data and the privacy leakage of the user may hinder the further development of smart IoT devices. Therefore, how to achieve consistency and balance between the demand and the renewable energy supply and how to guarantee the security and privacy of smart IoT devices become the key problems of the energy-efficient smart environment. In this paper, a secure and intelligent energy data management scheme for smart IoT devices is proposed. It is worth noting that, with the help of artificial intelligence (AI) technologies and secure cryptography primitives, the proposed scheme realizes high-efficient and secure energy utilization in a smart environment. Specifically, the proposed scheme aims at improving the efficiency of the energy utilization in the multidimensions of a smart environment. In order to realize the fine-grain energy management of smart IoT devices, strategies of three different dimensions are considered and realized in the proposed scheme. Moreover, technologies in AI are applied and integrated into the energy management scheme. The analysis shows that the proposed scheme can make full use of the renewable energy in smart IoT devices.

Background Scabies is caused by Sarcoptes scabiei burrowing into the stratum corneum of the host’s skin and is detrimental to the health of humans and animals. Vaccines are an attractive alternative to replace the acaricides currently used in their control. Methods In the present study, the S. scabiei chitinase-like protein 5 (SsCLP5) was characterized and recombinant SsCLP5 (rSsCLP5) was evaluated as a candidate vaccine protein for anti-mite protection in rabbits. The expression, characterization and immunolocalization of SsCLP5 were examined. Vaccination experiments were performed on three test groups (n = 12 per group) immunized with purified rSsCLP5. Control groups (n = 12 per group) were immunized with PBS, QuilA saponin or empty vector protein. After challenge, the inflammatory reaction and skin lesions were graded and rSsCLP5 indirect ELISA was used to detect antibody IgG levels in serum samples at the time of vaccination and post-challenge. Results The results showed that rSsCLP5 had high immunoreactivity and immunogenicity. In S. scabiei, SsCLP5 had a wide distribution in the chewing mouthpart, legs and exoskeleton, especially the outer layer of the exoskeleton. Vaccination with rSsCLP5 resulted in 74.3% (26/35) of rabbits showing no detectable lesions after challenge with S. scabiei. Conclusions Our data demonstrate that rSsCLP5 is a promising candidate for a recombinant protein-based vaccine against S. scabiei. This study also provides a method for studying scabies vaccine using rabbit as an animal model and a basis for screening more effective candidate proteins. Electronic supplementary material The online version of this article (10.1186/s13071-018-3184-y) contains supplementary material, which is available to authorized users.

Nephogram could provide important information for meteorological business, and nephogram recognition is a kind of challenge in the meteorological industry. In this paper, a selective neural network ensemble method based on K-means and Hadoop processing technology is proposed. This method combines the neural network, K-means clustering and AdaBoost in cloud environment. The experimental results show that the recognition precision of the method proposed by this paper is higher than that of traditional method in a stand-alone environment.

In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data management and value mining. The promising combination of blockchain and the Internet of things as BCoT (blockchain of things) can solve these problems. This paper introduces an innovative method DCOMB (dual combination Bloom filter) to firstly convert the computational power of bitcoin mining into the computational power of query. Furthermore, this article uses the DCOMB method to build blockchain-based IoT data query model. DCOMB can implement queries only through mining hash calculation. This model combines the data stream of the IoT with the timestamp of the blockchain, improving the interoperability of data and the versatility of the IoT database system. The experiment results show that the random reading performance of DCOMB query is higher than that of COMB (combination Bloom filter), and the error rate of DCOMB is lower. Meanwhile, both DCOMB and COMB query performance are better than MySQL (My Structured Query Language).

In this paper, the blockchain technology is utilized to build the first incentive mechanism of nodes as per data storage for wireless sensor networks (WSNs). In our system, the nodes storing the data are rewarded with digital money. The more the data stored by the node, the more the reward it achieves. Moreover, two blockchains are constructed. One is utilized to store data of each node and another is to control the access of data. In addition, our proposal adopts the provable data possession to replace the proof of work (PoW) in original bitcoins to carry out the mining and storage of new data blocks, which greatly reduces the computing power comparing to the PoW mechanism. Furthermore, the preserving hash functions are used to compare the stored data and the new data block. The new data can be stored in the node which is closest to the existing data, and only the different subblocks are stored. Thus, it can greatly save the storage space of network nodes.

Scabies is an allergic skin disease that affects millions of mammals worldwide, including humans. It is a neglected tropical disease that represents a significant public health threat, particularly in economically disadvantaged populations. An effective vaccine is not currently available, and the exact mode of pathogenesis remains unclear. Herein, we identified, cloned and recombinantly expressed triosephosphate isomerase from Sarcoptes scabiei (S. scabiei). Immunohistochemical analyses showed that S. scabiei triosephosphate isomerase (Ss-TIM) is localized in the legs and chewing mouthparts of mites, and in infected rabbit skin (keratinized skin and embedded mites). Intradermal skin tests of rabbits injected with recombinant S. scabiei triosephosphate isomerase (rSs-TIM) revealed a flare, erythema and wheal reaction. These findings suggest that Ss-TIM may contribute to host invasion and induce an allergic response in the host.

Because of their unique electronic, magnetic and optical features, the rare earth has become an important strategic resource. Moreover, improving the exploitation of rare earth resources is very significant. To our knowledge, for the first time the hierarchical clustering technology under Map Reduce environment is utilized to process the experiment data of the tailings of rare earth ion in this paper. According to analyze of the experiment data, the leaching trend of rare earth ions in tailings under optimum conditions is researched. Finally, the data analysis shows that when the volume of sampling location is 400 ml, it can not only increase the concentration of rare earth ions in the leaching solution to ensure the economy and maneuverability of subsequent rare earth enrichment, but also insure the leaching rate of rare earth in the tailings and improve the utilization ratio of rare earth resources.

In recent years, the rapid development of computer science and technology brings health care into the information era. As a typical representation, wireless body area networks (WBANs) has also promoted the development of medical technology into a higher field. However, collecting data from users seriously affects personal privacy and security, that WBANs needs to overcome. In order to resolve the flaws of the existing secure authentication protocols in WBANs, we propose a lightweight implicit authentication protocol based on the Elliptic Curve Qu-Vantone (ECQV) algorithm. Moreover, we take advantage of the bidirectional key chain to design a group key management protocol between the personal digital assistance (PDA) and each of cluster head sensor nodes. The security and performance analysis show that our protocol can be performed with perfect forward security and backward security in data communication. In addition, the experimental simulation and theoretic analysis show that our protocol is more suitable for WBANs.

Internet of Things (IoT) is a research field that has been continuously developed and innovated in recent years and is also an important driving force for the improvement of people’s life in the future. There are lots of scenarios in IoT where we need to collaborate through devices to complete tasks; that is, a device sends data to other devices, and other devices operate on the aid of the data. These transmitted data are often users’ privacy data, such as medical data and grid data. We propose an instant encrypted transmission based security scheme for such scenarios in IoT. The analysis in this paper indicates that our scheme can guarantee the security of users’ data while ensuring rapid transmission and acquisition of instant IoT data.

Scabies is a parasitic disease caused by the ectoparasiteSarcoptes scabiei, affecting different mammalian species, including rabbits, worldwide. In the present study, we cloned and expressed a novel inorganic pyrophosphatase, Ssc-PYP-1, fromS. scabieivar.cuniculi. Immunofluorescence staining showed that native Ssc-PYP-1 was localized in the tegument around the mouthparts and the entire legs, as well as in the cuticle of the mites. Interestingly, obvious staining was also observed on the fecal pellets of mites and in the integument of the mites. Based on its good immunoreactivity, an indirect enzyme-linked immunosorbent assay (ELISA) using recombinant Ssc-PYP-1 (rSsc-PYP-1) as the capture antigen was developed to diagnose sarcoptic mange in naturally infected rabbits; the assay had a sensitivity of 92·0% and specificity of 93·6%. Finally, using the rSsc-PYP-1-ELISA, the Ssc-PYP-1 antibody from 10 experimentally infected rabbits could be detected from 1 week post-infection. This is the first report ofS. scabieiinorganic pyrophosphatase and the protein could serve as a potential serodiagnostic candidate for sarcoptic mange in rabbits.

// Ran He 1, * , Nengxing Shen 1, * , Haojie Zhang 1, * , Yongjun Ren 2 , Manli He 1 , Jing Xu 1 , Cheng Guo 1 , Yue Xie 1 , Xiaobin Gu 1 , Weimin Lai 1 , Xuerong Peng 3 and Guangyou Yang 1 1 Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Wenjiang, China 2 Sichuan Animal Sciences Academy, Sichuan Chengdu, China 3 Department of Chemistry, College of Life and Basic Science, Sichuan Agricultural University, Wenjiang, China * These authors contributed equally to this work Correspondence to: Guangyou Yang, email: guangyou1963@aliyun.com Keywords: chitinase-like protein, Sarcoptes scabiei, enzyme-linked immunosorbent assay, immunolocalization, intradermal skin test Received: May 23, 2017 Accepted: September 03, 2017 Published: September 19, 2017 ABSTRACT Scabies, caused by the mite Sarcoptes scabiei , is an allergic skin disease that affects millions of people and other mammals worldwide. This highly contagious parasitic disease is among the top 50 epidemic disease and is regarded as a neglected tropical disease. Diagnosis of scabies is difficult in the early stage, and the pathogenesis of scabies is not currently clear. Here, we expressed, identified and located the chitinase-like protein of S. scabiei (SsCLP), and evaluated its potential as an early-stage diagnostic antigen for rabbit scabies. Indirect ELISA using recombinant SsCLP (rSsCLP) exhibited diagnostic sensitivity of 94.4% (17/18) and specificity of 86.7% (26/30). Early diagnostic test after artificial infection of rabbits with S. scabiei for 1 week showed a positive detection rate of 96.7% (29/30). Immunolocalization assays showed that fluorescence signals were localized on the surface of mites and, in infected rabbits, were observed in keratinized skin and embedded mites. Intradermal skin tests of rabbits by injecting rSsCLP showed a wheal, flare and erythema reaction. These results suggest that S. scabiei chitinase-like protein is conducive to host invasion, participates in inducing the allergic response of the host, and is an effective antigen for the diagnosis of S. scabiei .

Scabies is a disease that harms humans and other animals that is caused by the itch mite Sarcoptes scabiei burrowing into the stratum corneum of the skin. In the early stages of scabies, symptoms are often subclinical and there are no effective diagnostic methods. Herein, we cloned, expressed and characterised an S. scabiei protein tyrosine kinase (SsPTK) and evaluated its diagnostic value as a recombinant antigen in rabbit during the early stages of Sarcoptes infestation. The SsPTK protein is ~30 kDa, lacks a signal peptide, and shares high homology with a PTK from the rabbit ear mite Psoroptes ovis cuniculi. The protein was widely distributed at the front end of mites, particularly in the chewing mouthparts and legs. Indirect ELISA using recombinant SsPTK showed good diagnostic value, with 95.2% (40/42) sensitivity and 94.1% (48/51) specificity for detecting anti-PTK antibody in serum samples from naturally-infested rabbits. More importantly, PTK ELISA could diagnose infection in the early stages (infestation for 1 week) with an accuracy of 100% (24/24). SsPTK therefore shows potential as a sensitive antigen for the early diagnosis of parasitic mite infestation.

The present study aimed to investigate the clinical effectiveness and safety of endovascular embolization for the treatment of pseudoaneurysm secondary to previous abdominal and pelvic surgery or radiological percutaneous abdominal procedure. A retrospective review was performed on all patients with abdominal and pelvic pseudoaneurysm confirmed by CT angiography or digital subtraction angiography and treated with endovascular embolization. Different techniques of embolization with coils were applied and the outcomes, including clinical effectiveness and safety, were assessed. A total of 31 patients with a total of 32 pseudoaneurysms were included in the present study. Of these pseudoaneurysms, 23 were from the main trunks and branches of the gastroduodenal artery, 5 were from the splenic artery, 2 were from the common hepatic artery, 1 was from the right hepatic artery and 1 was from the right internal iliac artery. There were no serious complications observed and there was no occurrence of re-bleeding following embolization. The embolization of the pseudoaneurysms was successful in all patients. In conclusion, endovascular embolization is a safe and effective method for the treatment of secondary iatrogenic pseudoaneurysm in the abdomen and pelvis.

The present study aimed to evaluate the clinical efficacy and safety of angiography and coil embolization for pseudoaneurysm post-pancreatoduodenectomy (PD). A total of 17 patients with gastrointestinal or abdominal hemorrhage after PD were included in the present study. Angiography was performed on the celiac artery, common hepatic artery, splenic artery, gastroduodenal artery and superior mesenteric artery to determine the size of the pseudoaneurysm, the parent artery and its collateral branches. A variety of embolization techniques have been applied to embolize pseudoaneurysm, including the sac packing technique, proximal embolization, exclusion technique and sandwich technique. Different techniques with coils were used for embolization and the clinical effects of embolization were analyzed. A total of 18 pseudoaneurysms were identified in 17 patients. In 2 patients, severe technical complications occurred, including migration of the coil and rupture of pseudoaneurysm, and one of them died, which may have been associated with this complication. No serious clinical complications were observed in the other patients. A total of 7 patients had mild clinical complications, including mild abdominal and dorsal pain, which were alleviated after symptomatic management. A total of 15 patients with definite pseudoaneurysm were successfully embolized without re-bleeding and complications. The clinical success rate was 94.1% (16/17). In conclusion, a variety of embolization techniques may be applied for the treatment of pseudoaneurysm after PD, which have high technical and clinical success rates and small trauma. It is recommended in emergency situations, but care should be taken to avoid serious technical complications.

Using image processing technology, a k-means algorithm based selective neural network ensemble method and Hadoop processing technology, combine cloud platform with BP neural network algorithm, K-means algorithm and AdaBoost algorithm, to study cloud shape recognition technology based on cloud computing platform. The research results show that the recognition precision of image recognition technology of cloud computing platform is higher than that of cloud shape recognition technology based on traditional BP AdaBoost ensemble algorithm and single operation image recognition technology based on a k-means algorithm based selective neural network ensemble method.

Colorectal cancer (CRC) is one of the leading causes of cancer-associated mortality worldwide. Long non-coding RNAs (lncRNAs) have been revealed to modulate various biological cell processes, and are involved in the initiation and progression of different diseases, including CRC. However, the role of lncRNA bladder cancer-associated transcript 2 (BLACAT2) in CRC has not been defined. The present study aimed to investigate the role of BLACAT2 in CRC. The present study measured the expression levels of BLACAT2 in CRC cells and tissues by reverse-transcription-quantitative polymerase chain reaction, and associations among BLACAT2 expression levels, important clinicopathological parameters and patient survival were statistically evaluated. The functional role of BLACAT2 in metastasis, proliferation and drug resistance was also detected. BLACAT2 was overexpressed in CRC cells and tissues, and high BLACAT2 expression was associated with larger tumor size, and more advanced lymph node (N), metastasis (M) and tumor-NM stages. Additionally, survival analysis demonstrated that patients with high BLACAT2 expression exhibited poor overall survival. Notably, high BLACAT2 expression was identified as an independent risk factor for overall survival. Migration and invasion assays revealed that BLACAT2 promoted migration and invasion, respectively. In addition, overexpression of BLACAT2 increased colony numbers and optical density values of CRC cells in a colony formation assay and an MTT assay, respectively. Furthermore, BLACAT2 levels were significantly increased in 5-fluorouracil-resistant cells, and overexpression of BLACAT2 was markedly associated with a low cell inhibition rate. In conclusion, BLACAT2 overexpression may contribute to the metastasis, proliferation and chemoresistance of CRC cells, and high BLACAT2 expression may be a promising prognostic marker for patients with CRC.

Location accuracy is an important index for the evaluation of location networks and the localisation algorithm related to the accuracy of the results. Classical location algorithms scarcely correct errors accurately. Moreover, they have poor resistance to error interference and low location accuracy. To achieve error-resistant lightning localisation, weighted rough-fuzzy C-means (WRFCM) was introduced in location calculation. The performance of this localisation algorithm was analysed using a lightning accident case through regional simulation. Results show that the lightning localisation algorithm based on WFCM overcomes the disadvantage in which traditional location algorithms easily diverge; the algorithm also has an improved ability to resist error interference and can solve the lightning points steadily and accurately.

BACKGROUND This study aimed to assess the relative safety and short-term efficacy of drug-eluting bead transarterial chemoembolization (DEB-TACE) and conventional transarterial chemoembolization (c-TACE) for treating peculiar anatomical sites of gastric cancer liver metastasis. MATERIAL AND METHODS Of the 68 patients with gastric cancer liver metastases confirmed by imaging and pathology, 35 were treated with DEB-TACE and 33 with c-TACE. The DEB-TACE group comprised 26 males and 9 females aged 28-75 years (56.8±6.3), and the c-TACE group included 19 males and 14 females aged 33-77 (60.2±9.4) years. Liver functions of the 2 groups were compared between pre-TACE and 1-week and 1-month after TACE. Computed tomography and magnetic resonance imaging were reexamined at 1, 3, and 6 months after TACE, and short-term efficacy was assessed based on modified response evaluation criteria in solid tumors. RESULTS One month following DEB-TACE and c-TACE, the number of cases with objective response (OR) was 29 cases (29 out of 35 cases, 82.9%) and 20 cases (20 out of 33 cases, 60.6%) and disease control (DC) in the 2 groups was 33 cases (33 out of 35 cases, 94.3%) and 26 cases (26 out of 33 cases, 78.8%) respectively (P=0.041, P=0.031). Alanine transaminase (ALT) and Aspartate transaminase (AST) significantly increased in the DEB-TACE and c-TACE groups 1 week later (P

BACKGROUND In this study, we evaluated the advantages and disadvantages of angioembolization in patients with Grade III-V blunt renal trauma compared with other treatments. MATERIAL AND METHODS We prospectively collected data on patients hospitalized for Grade III-V blunt renal trauma. Organ damage was graded according to the American Association for the Surgery of Trauma (AAST) criteria. Initial grouping was then performed according to the hemodynamics and "initial treatment". The eligible patients were divided into 3 groups: conservative treatment group (Group A), arterial embolization group (Group B), and surgical group (Group C). The success rate, significance, and follow-up renal function were evaluated. RESULTS In Group B of Grade IV, estimated glomerular filtration rate (eGFR) and serum creatinine (Scr) levels were slightly decreased and increased, respectively, after embolization compared with before embolization (P=0.002, P=0.039). In Grade V, the eGFR of Group B after embolization was lower than before embolization (P=0.041); The levels of serum urea (Urea) and Scr in Group B after treatment were higher than those before treatment (P=0.042, P=0.024). Conservative treatment and angioembolization were better than exploration in protecting renal function of Grade IV (P=0.035 and P=0.047, respectively). CONCLUSIONS The success rate of angioembolization was high and protected renal function to the greatest extent, and there were no differences in renal function at long-term follow-up. However, it is difficult to manage renal vessel laceration or avulsion by embolization alone, and various endovascular therapies are required to protect the function of residual kidneys.

Ground-based microwave radiometer is a new type of automatic atmospheric detection device with high precision and multi-channel. In order to investigate the reliability of detection data, this article compares and analyses the meteorological elements retrieved from microwave radiometer (MWR) and observational data from radiosonde. The results show that temperature profile and water vapour density profile from MWR have better positive correlation with those from radiosonde. The temperature retrieved from MWR is lower than that from radiosonde in non-precipitation condition, but higher in precipitation condition. The bias may be related to sampling methods, MWR retrieval methods, precipitation and so on.

In order to ensure the stability of the data collected by the meteorological observation equipment, it is necessary to conduct consistency detection on the observation equipment. This paper proposes an algorithm based on interest degree association rules. The interest association rule mining algorithm is applied to the consistency detection of meteorological observation equipment, and the consistency model of meteorological observation equipment of association rules can be formed. The verification of real data shows that the algorithm can not only mine all the rules with strong correlation, but also be superior in temporal performance compared with similar non-Apriori algorithms. Through association rule mining algorithm, all association items are extracted to form a case base. The rule matching method is used to detect the consistency between devices, and the algorithm is optimized experimentally, and the optimal parameter solution is obtained, which determines the device consistency.

Location accuracy is an important measurement for evaluation of lightning locating networks, and the location algorithm directly affect the accuracy of the lightning detection results. According to the existed weakness of arrival time difference in traditional location method such as poor ability of resisting error interference and low location accuracy, and iterative algorithms are easy to diverge, an improved DBSCAN algorithm is introduced in location calculation. The performance of the proposed location algorithm was confirmed by regional simulation. The results showed that ADBSCAN does not require manual intervention, and has better clustering effect for lightning location results. The lightning location algorithm based on ADBSCAN overcomes the shortcomings that iterative algorithms are easy to diverge and fall into local optimum, and can solve the lightning points steadily and accurately.

Accurate and reliable surface meteorological data are necessary for the related meteorological research and improving climate prediction level. In this paper, a comprehensive quality control system is designed for the data of surface meteorological observation from cities. The system includes the data structure of backstage database, as well as the foreground quality-check system based on multithreading mechanism. Comprehensive quality control is necessary before storing the surface meteorological observation data. Besides the traditional control methods such as extreme values check, internal consistency check, the equipment states are also added into this system using the logistic regression. The system not only improves the efficiency of data processing, but also makes the meteorological observation data more representative, accurate and comparative.

As an important task of data mining, sequential pattern mining is also an important and challenging task in many practical applications. Traditional sequential pattern mining algorithms usually use frequent patterns as interesting sequence patterns, but frequency is not always a good proxy for interestingness This paper proposes a sequential patterns mining algorithm based on interestingness, using the branch and bound method of OPUS to traversal all possible candidate sequences. Algorithm uses bitmap as data structure to reduce storage space and experimental results on synthetic data with known patterns and experimental results confirms the validity of proposed algorithm.

Concerning the problem of uncertainty problem of different environment meteorological models and in order to improve the accuracy of PM2.5 concentration forecast, based on the forecast products of the three environment meteorological models including CUACE, BREMPS and WRF-Chem in Shanghai, the wavelet neural network combined wavelet theory with neural network was used to build the multi-model ensemble forecasting model of PM2.5 concentration. The experiment was carried out by data of Beijing station, and this model was compared with other four models (BP neural network, RBF neural network, Elman neural network and T-S fuzzy neural network). The results showed that PM2.5 forecasted by wavelet neural network was better than other models, the prediction deviation was reduced effectively. The PM2.5 daily average concentration forecasted by wavelet neural network was closest to the observation, the proposed model has comparatively high forecasting accuracies.

At present some developed countries have put forward their digital continuity action plans. And the digital continuity has also become a hot spot in the research of electronic records. However, the technology and measures for the protection of the digital continuity are still lack.

Since the British National Archives put forward the concept of the digital continuity in 2007, Some developed countries have developed a digital continuity plan of action. At the same time, digital continuity has become a hot topic in electronic document research. However, there is still a lack of technologies and measures to protect digital continuity.

With the rapid growth of cloud storage center, the cumulative volume of data reaches EB and even ZB from PB. As a result, both network size and the number of storage nodes continue to grow explosively, while the data failure rate is still increasing. Cloud storage centers encode the raw data into erasure codes, to save the system overhead as much as possible meanwhile guarantee the reliability of data. However, the state-of-art erasure codes techniques still rely on a conventional centralized model which results in unaffordable encoding/decoding cost, and thus cannot adapt to the data-intensive processing requirements for distributed cloud storage environments. In the paper, the preservation mechanism of combining erasure code and copy backup is proposed, to improve the reliability of electronic records in cloud storage. This paper focuses on the erasure code archiving of electronic documents and puts forward the ability aware erasure code filing of electronic documents. Moreover, the corresponding implementation algorithm and steps are described.

Table S1. Number of scabies mite at week 4 post-challenge. (PDF 48 kb)

Infestation of the epidermis with the highly contagious ectoparasite, Sarcoptes scabiei, causes scabies, which is characterized by intense itching, pruritus, and secondary infection. This condition affects humans, livestock, and wildlife worldwide, incurring large economic losses and reducing the quality of human life. In the present study, we cloned the alpha-enolase, a key enzyme in the glycolytic and gluconeogenesis pathways, from S. scabiei var. cuniculi, characterized it and produced soluble recombinant enolase protein (rSsc-eno). We determined the localization of Ssc-eno in isolated mites and mites in lesioned skin. The results showed that native enolase was intensely localized in the tegument of the mouthparts, the entire legs, and the whole mites' body, as well as in the gut and reproduction system. Interestingly, we found that native enolase was widely distributed in mites in lesioned skin, with obvious high protein intensity compared with isolated mites. Building on good immunoreactivity, an indirect enzyme-linked immunosorbent assay (ELISA) based on rSsc-eno showed 92% sensitivity and 95.8% specificity, compared with other indirect ELISA in this study, rSsc-eno based ELISA is better in detecting scabies in rabbits. Besides, this method can detect S. scabiei infection as early as 1 week post infection. Compared with other detection methods, such as traditional microscopic examination and recently published universal conventional PCR, rSsc-eno ELISA was more effective to detect early infection in rabbits. Additionally, in vitro incubation experiments demonstrated the concentration-dependent acaricidal activity of rabbit anti-rSsc-eno sera against larval mites, suggested its potential as a vaccine candidate.

Cloud storage services can enable data owners to eliminate the need for the initial investment of expensive infrastructure setup and also minimize development and maintenance costs. Outsourcing the health data to e-health cloud storage server is very beneficial. Nonetheless, storing the health data on cloud servers also brings serious security challenges. In this paper, we propose a highly efficient data integrity auditing scheme for cloud storage for mobile health applications. The authentication tag for each data block generated by biosensor nodes is minimal in our scheme due to the use of hash operation. Moreover, in data integrity checking phase, message-locked encryption scheme is utilized to encrypt and transport the auditing information of the checked data blocks, which significantly reduces the required amount of calculation and communication resources. Compared with the conventional third party auditing schemes, the presented scheme speeds up the tag generation and tag checking process by more than one thousand times.

Cloud storage is now an important development trend in information technology. To ensure the integrity of data storage in cloud storing, researchers have present some proof of storage schemes. In some cases, the ability to check data possession is delegated by data owners. Hence, the delegable provable data possession and proxy provable data possession are proposed. However the schemes are not secure since the proxy or designated verifier stores some delegation information in cloud storage servers. In this paper, we propose PC-DV POS scheme, which can preserve clients’ privacy and designate a verifier by the client signed the data blocks. In particular, we utilize group signatures and key exchange to construct homomorphic authenticators, so that only the designated verifier is able to check the integrity of shared data for users without retrieving the entire data, and cannot reveal the identities of signers on all blocks in shared data.