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Rapidly growing social networks and other graph data have created a high demand for graph technologies in the market. A plethora of graph databases, systems, and solutions have emerged, as a result. On the other hand, graph has long been a well studied area in the database research community. Despite the numerous surveys on various graph research topics, there is a lack of survey on graph technologies from an industry perspective. The purpose of this paper is to provide the research community with an industrial perspective on the graph database landscape, so that graph researcher can better understand the industry trend and the challenges that the industry is facing, and work on solutions to help address these problems., Comment: 8 papers, 3 figures, to appear in SIGMOD Record

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes the coronavirus disease (COVID-19). It is confirmed that nucleocapsid (N) protein is closely related to viral pathogenesis, modulation of host immune response, RNA transcription, and replication and virus packaging. Therefore, the N protein is a preponderant antigen target for virus detection. The codon-optimized N gene was designed according to the encoding characteristics of insect cells and inserted into pFastBacTM1 vector with 6 × His-tag-fused N protein for expression in insect sf21 cells. Six anti–N mAbs (4G3, 5B3, 12B6, 18C7-A2, 21H10-A3, 21H10-E9) were prepared by recombinant N protein. The mAbs showed high titers, antibody affinity, and reactivity with the SARS-CoV-2 N protein. Then, fourteen overlapped peptides that covered the intact N protein were synthesized (N1-N14). Peptide N14 was identified as the main linear B-cell epitope region via peptide-ELISA and dot-blot assay, and this region was truncated gradually until mapping the peptide 401-DFSKQLQQ-408. Simultaneously, compared with the sequence of variants of concern (VOCs) and variants of interest (VOIs) strains among the several countries, epitope 401-DFSKQLQQ-408 is very conservative among them. The findings provide new guidance for the design and detection of COVID-19 targets. Key points • The N protein was optimized according to the insect cell codon preference and was highly expressed. • The monoclonal antibodies prepared in this study were shown high antibody titers and high affinity. • Monoclonal antibodies were used to map the epitope 401–408 amino acids of N protein for the first time in this study. Supplementary Information The online version contains supplementary material available at 10.1007/s00253-022-11769-6.

Knowledge graph technology is considered a powerful and semantically enabled solution to link entities, allowing users to derive new knowledge by reasoning data according to various types of reasoning rules. However, in building such a knowledge graph, events modeling, such as that of disasters, is often limited to single, isolated events. The linkages among cascading events are often missing in existing knowledge graphs. This paper introduces our GeoAI (Geospatial Artificial Intelligence) solutions to identify causality among events, in particular, disaster events, based on a set of spatially and temporally-enabled semantic rules. Through a use case of causal disaster events modeling, we demonstrated how these defined rules, including theme-based identification of correlated events, spatiotemporal co-occurrence constraint, and text mining of event metadata, enable the automatic extraction of causal relationships between different events. Our solution enriches the event knowledge base and allows for the exploration of linked cascading events in large knowledge graphs, therefore empowering knowledge query and discovery.

Accurate pore-size-distribution (PSD) is the key to comprehending porous media and shale rock characteristics. There are multiple methods for calculating the PSD of porous media. The Barrett–Joyner...

The effects of build direction on the tensile properties, tension–tension low cycle fatigue behavior, and failure mechanism of polyamide 12 parts fabricated by Multi Jet Fusion have been investigated by addressing the roles of formed voids, sintering interfaces, and geometrical imperfections. Results indicate that the Young's modulus of bulk material with vertical build direction is higher than that of bulk material with horizontal build direction due to the carbon black enhanced sintering interfaces. The tensile strength of the printed bulk material with horizontal and vertical build directions is comparable. It is found that the anisotropic tension–tension low cycle fatigue behavior for the bulk material is significant, while that for the re-entrant lattice structure is weak. The anisotropic fatigue strength of bulk material is derived from the anisotropic distribution of internal voids and sintering interfaces. The fatigue behavior of the re-entrant lattice structure is determined by the geometrical imperfections. The coalescence of the large voids or clusters of voids contributes to the crack initiation and propagation processes that lead to the failure of the bulk material. While the failure of re-entrant lattice structure is mainly determined by the intersection of strut junction rather than the void defect. This result provides the fatigue data that can be used for the structural design with Multi Jet Fusion polyamide 12 as well as reveals the effects of voids, sintering interfaces, and geometrical imperfections on the fatigue behavior of the printed parts. Nanyang Technological University This research was conducted in collaboration with HP Inc. and supported by Nanyang Technological University and the Singapore Government through the Industry Alignment Fund-Industry Collaboration Projects Grant (I1801E0028).

The effect of temperature on the impact characteristics of the ring chain under different working conditions was investigated with ABAQUS simulation, the curves were fitted with MATLAB, and the results were experimentally verified. The temperature has little effect on minimum steady-state stress. The friction energy dissipation has three polynomial temperature relations under heavy-load start-up, and its dissipation does not vary at fluctuating loads. Under two working conditions, the plastic energy dissipation and internal energy increase linearly with temperature; at abrupt load variations, those energies increase with the tendency to stabilization. This method is of great significance for improving the initial characteristics of a scraper conveyor, variable-load operations, and design optimization of the ring chain.

Siniperca chuatsi feeds on live fry throughout their life. The sustainable development of its farming industry has urgently necessitated the development of artificial diets to substitute live baits. It has been demonstrated that gut microbiota assists in feed adaptation and improves the feed conversion rate in fish. Therefore, this study aimed to understand the potential role of intestinal microorganisms in the domestication of S. chuatsi with a compound diet. Accordingly, we performed 16S rRNA sequencing of the gut microbial communities in S. chuatsi groups that were fed a compound diet (including large and small individuals) and live baits. A total of 2,471 OTUs were identified, and the large individual group possessed the highest number of unique OTUs. The α-diversity index of the gut microbiota in groups that were fed a compound diet was significantly higher (p < 0.05) than that in the live bait group. There were no significant differences in the α-diversity between the large and small individual groups. However, relatively higher numbers of Lactococcus, Klebsiella, and Woeseia were observed in the intestines of the large individual group. Prediction of the metabolic function of the microbiota among these three fish groups by Tax4Fun revealed that most metabolic pathways, such as glycan metabolism and amino acid metabolism, were typically more enriched for the larger individuals. The results indicated that certain taxa mentioned above exist in large individuals and may be closely related to the digestion and absorption of compound diets. The present study provides a basis for understanding the utilization mechanism of artificial feed by S. chuatsi.

The scraper is the core of the conveyor and its vulnerable part. The problem of bending fracture of common welding scrapers in actual production is under consideration. SolidWorks and ANSYS finite element analysis software were used to construct the three-dimensional model for simulation analysis, and the existing structure was improved and optimized. The comparison results showed: well-type stiffener contributes to improvement of the overall strength and rigidity of the scraper. Before optimization, the maximum equivalent stress on the press buckle part of the scraper was 310 MPa, and after optimization it dropped to 230 MPa, i.e., decreased by 26%, and the stress value of one side of stiffener was 170 MPa, with certain bending resistance. After optimization, the stress distribution of the scraper was uniform, with solving the problem of stress concentration. After optimization, the overall safety factor of the scraper increased by nearly 15%, improving its life. Integrity of the optimized scraper was nearly 100%, as compared to that before optimization under the same conditions, which confirmed the validity of scraper optimization.

A method of cutting coal with three drums was advanced, a three-drum shearer was designed, and the free mode and restrained model under prestress of the third drum were analyzed in large mining with ANSYS Workbench 14.0 to solve the damage problem of the cutting blade in a large mining face. The vibration modes caused by its own structural characteristics are obtained, and the dynamic response of all parts of the shearer is studied with MATLAB R2016a software under given conditions and the change of the parameters. The overloads of the front drum give rise to larger vibration displacements that should be avoided in the operation of the shearer. The above approach is of importance to evolve the design concepts and improve cutting characteristics of the largeheight shearer, to provide theoretical backgrounds ensuring safe and reliable mining of superthick coal seams by the large-height shearer.

Supplemental material, sj-docx-1-tah-10.1177_20406207221134409 for Association between haploidentical hematopoietic stem cell transplantation combined with an umbilical cord blood unit and graft-versus-host disease in pediatric patients with acquired severe aplastic anemia by Di Yao, Yuanyuan Tian, Jie Li, Bohan Li, Jun Lu, Jing Ling, Defei Zheng, Yanhua Yao, Peifang Xiao, Lijun Meng and Shaoyan Hu in Therapeutic Advances in Hematology

Today's low-power devices, such as smartphones and wearables, form a very heterogeneous ecosystem. Applications in such a system typically follow a reactive pattern based on stream analytics, i.e., sensing, processing, and actuating. Despite the simplicity of this pattern, deciding where to place the processing tasks of an application to achieve energy efficiency is non-trivial in a heterogeneous system since application components are distributed across multiple devices. In this paper, we present Aves - a decision-making engine based on a holistic energy-prediction model, with which the processing tasks of applications can be placed automatically in an energy-efficient manner without programmer/user intervention. We validate the effectiveness of the model and reveal several counter-intuitive placement decisions. Our decision engine's improvements are typically 10-30%, with up to a factor 14 in the most extreme cases. We also show that Aves gives an accurate decision in comparison with real energy measurements for two sensor-based applications.

A fiber-packed in-tube extraction device was developed with heat-resistant fibers coated with molecularly imprinted polymer as adsorbent for concentration detection of volatile organic compounds (VOCs). The coated fibers were longitudinally packed into a filling chamber. The inner diameter of the filling chamber was 3 mm and its length was 2.5 cm. The filling chamber was connected to gas chromatography port by a stainless needle. The device was heated by an external heater consisting of the heating wire surrounded outside of the filling chamber to gasify the analytes in the adsorbent. The prepared fiber-packed in-tube extraction device was used to analyze benzene, toluene, ethylbenzene and o-xylene (BTEX) in gas sample coupled with gas chromatography. The result showed that the device had better permeability. The extraction time for 150 mL of gas sample was 1.2 min. The linear detection range, recovery, limit of detection (LOD) and limit of quantification (LOQ) were also evaluated for the promising method. The linear detection ranges for BTEX were all 1–300 μg L−1, with the correlation coefficients of greater than 0.9936. The LODs and LOQs of the analytes were in the range of 0.02–0.03 μg L−1 and 0.03–0.05 μg L−1, respectively. The recoveries of BTEX were 90.3%, 94.3%, 98.7% and 103.3%, respectively.

Gas storage in shale (organic-rich mudstone) consists of three different states: free gas in pores and natural fractures; adsorbed gas on organic and inorganic pore walls; and absorbed gas into organic matter (kerogen). Since it is difficult to differentiate absorbed gas from adsorbed gas, most current studies combine the adsorbed gas with absorbed gas and call the combination as gas sorption. In this study, a conceptual model of gas sorption is proposed to account for the contributions from adsorption and absorption to gas storage in shale, respectively. Methane sorption capacity of Barnett and Eagle Ford shale core samples is measured by magnetic suspension sorption system. Regression analysis is performed on the measured data by Simplified Local-Density model coupled with modified Peng-Robinson Equation of State (SLD-PR). Absolute sorption capacity of these two shale core samples is estimated based on the density profile of SLD-PR model. Additionally, the absorbed gas, which is regarded as the gas molecules dissolving/diffusing into the bulk of solid kerogen, is distinguished from the adsorbed gas through interpreting the results of gas expansion measurements using Fick’s law of diffusion. Moreover, methane diffusion coefficients for the two shale core samples are determined, which range from 10−22 m2/s to 10−21 m2/s. The percentage of absorbed gas accounting for total sorbed gas increases with pore pressure. When the pore pressure increases, more gas molecules attempt to adsorb on the surface of kerogen and create a larger gas concentration gradient for gas diffusing into the kerogen. The gas molecules, which adsorb on the pore walls of kerogen and then diffuse into the solid lattice of kerogen, may lead to the swelling of kerogen and thus reduce the pore width for free gas transportation. Therefore, the accurate prediction of the gas absorption capacity of kerogen is significant to understand gas storage mechanism and characterize original gas in place (OGIP) in shale gas reservoirs.

Through the simulation analysis of the settlement and deformation law of the surface buildings caused by the construction of the biased tunnel, the following points are obtained: (1) The Peak formula is revised, and the influence range of the biased tunnel is predicted based on the formula. (2) It is concluded that when the tunnel is biased, the position of maximum deformation caused by ground settlement is generally in a parallel area 0.5 times the buried depth from the center line of the tunnel. (3) Through the double-layer verification of simulation analysis and monitoring measurement data, prior to the construction of buildings with similar weak foundations, their foundations should be reinforced in advance. (4) In the process of this simulation, the complicated influence of water pressure on tunnel excavation was not considered, which can be further optimized in the later stage.

Sensor-based applications using Big Data are of increasing importance in various fields. A typical example of such use cases is building health-care applications [1], [2]. A typical scenario is where a patient's heart rate is monitored by a smartwatch. A smartphone can then analyze the gathered data and identify patterns in the patient's heart rate. However, if the data analysis is too complex to be performed on a smartphone, the computation could be offloaded to a nearby cloudlet or a remote cloud. A decision usually follows the analysis, and actuation is performed accordingly (e.g., a message is sent to either the patient or the doctor). Developing such an application is intrinsically complex, as the programmer needs to reconcile different APIs specific to different platforms.

Testicular dysfunction due to hyperglycemia is the main cause of infertility in diabetic men. Over the years, in order to solve this growing problem, a lot of research has been done and a variety of treatments have been created, but so far, there is no safe, effective, and practical method to prevent male infertility caused by diabetes. In this review, we emphasize the male infertility mechanism caused by diabetes from the effects of oxidative stress and autophagy on the function of testes via the PI3K/Akt/mTOR signaling pathway, and we highlight that oxidative stress-induced autophagy breaks the feedforward loop linking Nrf2 and p62 and promotes oxidative damage in diabetic testes.

This report unravels the dependence of the microstructure and electrochemical performances of Li-rich layered transition metal oxide (LLMO) on the molecular structure of polymer templates for the formation of oxalate precursor. A representative LLMO, Li1.2Mn0.54Ni0.13Co0.13, is synthesized by co-precipitation method, and three samples, LLMO-PVP, LLMO-PEG and LLMO-PVA, are obtained with polymer templates, polyvinyl pyrrolidone (PVP), polyethyleneglycol (PEG) and polyvinyl alcohol (PVA), respectively. The physical and chemical properties of the resulting products are analyzed with SEM, TEM, XRD, BET, ICP, and XPS, and their electrochemical performances as cathode of Li-ion battery are evaluated with EIS, GITT and charge/discharge tests. It is found that LLMO-PVP exhibits the best performances, followed by LLMO-PEG, while LLMO-PVA behaves poorest. This difference is ascribed to the various microstructures of the resulting products, which are determined by the molecular structure of polymer templates.

Monitoring the changes of the retaining pile wall during the excavation of the deep foundation pit, and accurately grasping the side displacement changes of the retaining pile wall can effectively grasp the safety status of the foundation pit construction. In this paper, taking Guangfo Ring Road as an example, theoretical analysis, numerical simulation and other methods are used to study the influence of foundation pit excavation on the horizontal displacement and deformation of the ground connecting wall during the reinforcement of mixed piles in the area adjacent to high-rise buildings. Get the following conclusion : (1) With reinforced ground connecting walls and non-reinforced ground connecting walls, the horizontal displacement curve of ground connecting walls is roughly the same, showing a trend of change between the larger and the smaller ends. As the excavation depth continues to increase, the changing trend of the “bow” becomes more obvious, which is in line with the changing law of the enclosure structure. (2) After the mixing pile is used for reinforcement, the maximum horizontal displacement of the ground connecting wall is greatly reduced. Compared with the case without reinforcement measures, the horizontal displacement value of the ground connecting wall is 5.66mm, which is reduced by 6.23mm. The reduction ratio is 52%, indicating that the mixing pile has a great inhibitory effect on the horizontal displacement of the ground connecting wall. (3) By comparing on-site monitoring and numerical calculation data, the change trend of the wall horizontal displacement of the measured value and the simulated value is approximately the same. The measured maximum value of the monitoring section is 8.46mm, the simulated maximum value is 5.66mm, and the difference between the two is 2.8 mm, verified the rationality of the model, and provided some experience for the excavation of foundation pits to protect adjacent buildings.

Shale gas is an effective gas resource all over the world. The evaluation of pore structure plays a critical role in exploring shale gas efficiently. Nitrogen adsorption experiment is one of the significant approaches to analyze pore size structure of shale. Shale is extremely heterogeneous due to component diversity and structure complexity. Therefore, adsorption isotherms for homogeneous adsorbents and empirical isotherms may not apply to shale. The shape of adsorption-desorption curve indicates that nitrogen adsorption on shale includes monolayer adsorption, multilayer adsorption, and capillary condensation. Usually, Langmuir isotherm is a monolayer adsorption model for ideal interfaces; BET (Brunauer, Emmett, Teller) adsorption isotherm is a multilayer adsorption model based on specific assumptions; Freundlich isotherm is an empirical equation widely applied in liquid phase adsorption. In this study, a new nitrogen adsorption isotherm is applied to simultaneously depict monolayer adsorption, multilayer adsorption, and capillary condensation, which provides more real and accurate representation of nitrogen adsorption on shale. In addition, parameters are discussed in relation to heat of adsorption which is relevant to the shape of the adsorption isotherm curve. The curve fitting results indicate that our new nitrogen adsorption isotherm can appropriately describe the whole process of nitrogen adsorption on shale.

GDPR (General Data Protection Regulation) is a new regulation of the European Union that superimposes strict privacy constraints on storing, accessing and processing user data, as a way to ensure that personal user data are not violated neither disclosed without an explicit consent. As a consequence, business processes that interact with large amounts of such data may easily cause GDPR violations, due to the typical complexity of such processes. Inspired by these considerations, this paper highlights the challenges and critical aspects associated with the GDPR compliance journey when opting for naïve straight-forward solutions. We propose a business-aware GDPR compliance journey using online process mining. Using several large log files generated based on a real scenario, we show that the proposed tool is both effective and efficient. As such, it proves to be a powerful concept for usage in incremental GDPR compliance environments.

Based on the operation principle of modular multi-level converter (MMC), the mechanism of submodule capacitors' continuous overvoltage under the single-phase grounding fault at the valve side of converter transformer or bridge arm reactor in the neutral-line grounded MMC-HVDC system is discussed. Continuous overvoltage and bypass overvoltage have contradictory demands for the setting value of overvoltage bypass protection of converter valves. In order to provide reference for the setting value, several influencing factors are analyzed to filtrate the severest circumstance of continuous overvoltage, including converter states, converter transformer ratio, voltage of PCC point, reactive power of the fault converter, power flow in DC grid and DCBs' state. Furthermore, the valve controlled unbalance protection with the minimum number of current measuring devices to identify faults quickly is proposed to suppress the continuous overvoltage, which is helpful to reduce the equipment area and avoid the effect of measuring devices' inconsistency on the accuracy of protection. Finally, a four-terminal MMC-HVDC grid is set up in PSCAD/ EMTDC. Simulation results show that the valve controlled unbalance protection can effectively suppress the continuous overvoltage and has good fault ride-through ability under AC/DC side faults and reliable protection selectivity under internal faults of converter stations.

Yuanyuan Tian,1 Wenjing Song,1 Dan Li,1 Lu Cai,2 Yuguang Zhao1 1Cancer Center, the First Hospital of Jilin University, Changchun, Jilin 130021, People’s Republic of China; 2Departments of Pediatrics, Radiation Oncology, Pharmacology and Toxicology, University of Louisville, Louisville, KY 40292, USACorrespondence: Yuguang ZhaoCancer Center, the First Hospital of Jilin University, Changchun, Jilin 130021, People’s Republic of ChinaTel +8643115804303822Email zhaoyuguang@jlu.edu.cnAbstract: Resveratrol, as a natural product compound, has been recently attracted much attention for its potent effects on cancer. Cancer is a serious disease threatening human survival and social development. Autophagy is a cellular pathway to realize the metabolic needs of the cell itself and the renewal of some organelles and plays opposing, context-dependent role in tumorigenesis. So the regulation of autophagy is of great significance in the treatment of cancer. p62, as an autophagy adaptor protein, is a preferred target for autophagy and is constantly controlled by constitutive autophagy. As a tumor-suppression mechanism, autophagy deficiency is common in tumors, which results in aberrant accumulation of p62 and activates p62-regulated pathways, such as activation of mTOR in nutrient sensing, and the activation of the Keap1-Nrf2 pathway for antioxidant stress, which are associated with cancer development. In this review, we emphasize that resveratrol can induce autophagy in the treatment of cancer and accelerates the degradation of p62, and then, the mTOR activation is blocked and Nrf2 activation is suppressed. As a result, the multidrug resistance of cancer cells can be reversed by resveratrol.Keywords: resveratrol, cancer, autophagy, p62, mTOR, Nrf2

The basic helix&ndash, loop&ndash, helix (bHLH) family is the second largest superfamily of transcription factors that belongs to all three eukaryotic kingdoms. The key function of this superfamily is the regulation of growth and developmental mechanisms in plants. However, the bHLH gene family in Carthamus tinctorius has not yet been studied. Here, we identified 41 bHLH genes in Carthamus tinctorius that were classified into 23 subgroups. Further, we conducted a phylogenetic analysis and identified 10 conserved protein motifs found in the safflower bHLH family. We comprehensively analyzed a group of bHLH genes that could be associated with flavonoid biosynthesis in safflower by gene expression analysis, gene ontology annotation, protein interaction network prediction, subcellular localization of the candidate CtbHLH40 gene, and real-time quantitative expression analysis. This study provides genome-wide identification of the genes related to biochemical and physiological processes in safflower.

The basic helix–loop–helix (bHLH) family is the second largest superfamily of transcription factors that belongs to all three eukaryotic kingdoms. The key function of this superfamily is the regulation of growth and developmental mechanisms in plants. However, the bHLH gene family in Carthamus tinctorius has not yet been studied. Here, we identified 41 bHLH genes in Carthamus tinctorius that were classified into 23 subgroups. Further, we conducted a phylogenetic analysis and identified 10 conserved protein motifs found in the safflower bHLH family. We comprehensively analyzed a group of bHLH genes that could be associated with flavonoid biosynthesis in safflower by gene expression analysis, gene ontology annotation, protein interaction network prediction, subcellular localization of the candidate CtbHLH40 gene, and real-time quantitative expression analysis. This study provides genome-wide identification of the genes related to biochemical and physiological processes in safflower.

Database administrators construct secondary indexes on data tables to accelerate query processing in relational database management systems (RDBMSs). These indexes are built on top of the most frequently queried columns according to the data statistics. Unfortunately, maintaining multiple secondary indexes in the same database can be extremely space consuming, causing significant performance degradation due to the potential exhaustion of memory space. In this paper, we demonstrate that there exist many opportunities to exploit column correlations for accelerating data access. We propose HERMIT, a succinct secondary indexing mechanism for modern RDBMSs. HERMIT judiciously leverages the rich soft functional dependencies hidden among columns to prune out redundant structures for indexed key access. Instead of building a complete index that stores every single entry in the key columns, HERMIT navigates any incoming key access queries to an existing index built on the correlated columns. This is achieved through the Tiered Regression Search Tree (TRS-Tree), a succinct, ML-enhanced data structure that performs fast curve fitting to adaptively and dynamically capture both column correlations and outliers. Our extensive experimental study in two different RDBMSs have confirmed that HERMIT can significantly reduce space consumption with limited performance overhead in terms of query response time and index maintenance time, especially when supporting complex range queries., To appear in SIGMOD 2019

The rising demands of real-time analytics have emphasized the need for Hybrid Transactional and Analytical Processing (HTAP) systems, which can handle both fast transactions and analytics concurrently. Wildfire is such a large-scale HTAP system prototyped at IBM Research - Almaden, with many techniques developed in this project incorporated into the IBM’s HTAP product offering. To support both workloads efficiently, Wildfire organizes data differently across multiple zones, with more recent data in a more transaction-friendly zone and older data in a more analytics-friendly zone. Data evolve from one zone to another, as they age. In fact, many other HTAP systems have also employed the multi-zone design, including SAP HANA, MemSQL, and SnappyData. Providing a unified index on the large volumes of data across multiple zones is crucial to enable fastpoint queries and range queries, for both transaction processing and real-time analytics. However, due to the scale and evolving nature of the data, this is a highly challenging task. In this paper, we present Umzi, the multi-version and multi-zone LSM-like indexing method in the Wildfire HTAP system. To the best of our knowledge, Umzi is the first indexing method to support evolving data across multiple zones in an HTAP system, providing a consistent and unified indexing view on the data, despite the constantly on-going changes underneath. Umzi employs a flexible index structure that combines hash and sort techniques together to support both equality and range queries. Moreover, it fully exploits the storage hierarchy in a distributed cluster environment (memory, SSD, and distributed shared storage) for index efficiency. Finally, all index maintenance operations in Umzi are designed to be non-blocking and lock-free for queries to achieve maximum concurrency, while only minimum locking overhead is incurred for concurrent index modifications.

Aiming at the feasibility of applying glass fiber concrete as a new material to tunnel engineering, with the help of a combination of theoretical analysis, laboratory tests and engineering applications, the effect of glass fiber on the mechanical properties of concrete under different dosages and different lengths is studied. By monitoring the cracks in the middle partition wall, and applying the glass fiber to the middle partition wall in Laoshan Tunnel, to achieve the verification of the optimal length and the optimal mixing amount. The main conclusions are: (1) When the length of glass fiber is 12 mm, the tensile and compressive strength reach the maximum value; (2) Determine the optimal volume rate is 1% in order to prevent the concrete cracking effectively; (3) The crack resistance of the mid-board with glass fiber concrete is better than the ordinary concrete, which proves the feasibility of practical application of glass fiber concrete.

With their distinctive sensory characterizations and unique processing technologies, Chinese ethnic meat products possess great potential for development and continuity in modern China's meat industry. Due to the greater demand for meat products and higher quality and safety concerns in economically fast growing China, the development and continuity of ethnic meat products face its own unique challenges. In this review, the classification of typical ethnic products and their characteristics, and the research progress on their quality and processing technologies are discussed. The application of innovative and green technologies to improve the safety and quality of ethnic meat products for greater industrialization and sustainable development is highlighted. Furthermore, the strategy for promoting the production of Chinese ethnic meat products during the next five years is presented.

The partial cDNA sequences of eight reference genes (actb, tuba1, gapdh58, gapdh59, eef1a1, RNA 18 s, pabpc1, ube2I) were cloned from largemouth bass Micropterus salmoides. The expression levels of these eight genes were compared in the various tissues (eye, spleen, kidney, gill, muscle, brain, liver, heart, gut and gonad) of M. salmoides fed on forage fish. The results showed that the candidate genes exhibited tissue-specific expression to various degrees and the stability ranking order was eef1a1 > tuba1 > RNA 18 s > pabpc1 > ube2I > actb > gapdh58 > gapdh59 among tissue types. Four candidate genes eef1a1, tuba1, RNA 18 s and actb were used to analyse the stability in liver tissues of largemouth bass between the forage-fish group and the formulated-feed group. The candidate genes also showed some changes in expression levels in the livers, while eef1a1 and tuba1 had the most stable expression in livers of fish fed on alternative diets within 10 candidates. So eef1a1 and tuba1 were recommended as optimal reference gene in quantitative real-time PCR analysis to normalise the expression levels of target genes in tissues and lives of the M. salmoides fed on alternative diets. In livers, the expression levels of gck normalised by eef1a1 and tuba1 showed the significant up-regulation in formulated feed group (P < 0.05) than those in forage-fish group. While sex difference has no significant effects on the expression levels of gck in both groups.

To maintain the accuracy of supervised learning models in the presence of evolving data streams, we provide temporally-biased sampling schemes that weight recent data most heavily, with inclusion probabilities for a given data item decaying exponentially over time. We then periodically retrain the models on the current sample. This approach speeds up the training process relative to training on all of the data. Moreover, time-biasing lets the models adapt to recent changes in the data while -- unlike in a sliding-window approach -- still keeping some old data to ensure robustness in the face of temporary fluctuations and periodicities in the data values. In addition, the sampling-based approach allows existing analytic algorithms for static data to be applied to dynamic streaming data essentially without change. We provide and analyze both a simple sampling scheme (T-TBS) that probabilistically maintains a target sample size and a novel reservoir-based scheme (R-TBS) that is the first to provide both complete control over the decay rate and a guaranteed upper bound on the sample size, while maximizing both expected sample size and sample-size stability. The latter scheme rests on the notion of a "fractional sample" and, unlike T-TBS, allows for data arrival rates that are unknown and time varying. R-TBS and T-TBS are of independent interest, extending the known set of unequal-probability sampling schemes. We discuss distributed implementation strategies; experiments in Spark illuminate the performance and scalability of the algorithms, and show that our approach can increase machine learning robustness in the face of evolving data., Comment: 17 pages, 14 figures, extended version of an EDBT'18 paper

First fabrication of microorganism-graphene oxide composites for Uranium(VI) adsorption from aqueous solutions was performed via immobilized Lysinibacillus sp. on graphene oxide (GO). Lysinibacillus-GO was characterized using scanning electron microscopy and Fourier transform infrared spectroscopy. The influence of contact time, pH values, U(VI) initial concentration, as well as the adsorption kinetics and isotherm of U(VI) in aqueous solution were estimated through batch adsorption experiments. Results revealed that Lysinibacillus-GO exhibited superior U(VI) removal ability, and its maximum adsorption capacity for U(VI) from aqueous solution was 149.3 mg/g. Furthermore, the pseudo-second order kinetic and Langmuir isotherm model matched well with this adsorption process according to the adsorption kinetic and isotherm study, suggesting that monolayer coverage of U(VI) adsorption occurred on the Lysinibacillus-GO surface and that chemisorption was the main limiting step for controlling adsorption rate. The adsorption mechanism of U(VI) by Lysinibacillus-GO adsorbent was mainly ascribed to an inner-sphere complexation between U(VI) and oxygen-containing groups. Regeneration study demonstrated that Lysinibacillus-GO can be used as a regenerated adsorbent for capturing U(VI) from aqueous solutions. This study provides new insights in taking full advantage of adsorption feature of GO and ubiquitous microbial resources and their use in remediating uranium-polluted aqueous environments.

Streptococus agalactiae and S. iniae are two common pathogens of fish Streptococcus diseases. Symptoms of disease caused by both Streptococcus pathogens were quite similar, and it was difficult to distinguish the two pathogens from each other directly from the symptoms. Therefore it is necessary to develop a rapid identification method in order to control the disease effectively and rapidly. According to the cfb gene sequence of S. agalactiae and 16S rRNA gene sequence of S. iniae, two pairs of primers were designed and synthesized, and a rapid duplex PCR assay for identification of S. agalactiae and S. iniae was established by optimization of amplification conditions. A 474 bp fragment specific for S. agalactiae and a 296 bp fragment for S. iniae were produced, but no product was amplified from the other common pathogenic bacteria of fish such as Aeromonas hydrophila and Pseudomonas aeruginosa. The method is quite sensitive, and can detect a template concentration as low as 3.2×10-3 ng/μL for S. agalactiae and 3.0×10-2 ng/μL for S. iniae, respectively. A total of eleven pathogen samples collected from pond-cultured tilapia in Guangdong and Hainan provinces were analyzed by duplex PCR. Sequencing and BLAST analysis revealed that all the sequences were cfb gene of S. agalactiae. Results of molecular identification were consistent with the previous results of biochemical assays. The double PCR method would provide a sensitive and accurate method for rapid identification of S. agalactiae and S. iniae.

There was an error in the legend of Figure 1B, "Percentage of bees showing proboscis extension response (mean+SE) of pollen (P, solid) and nectar (N, empty) foragers of Apis mellifera (triangles) and A. cerana (circles) in their own colonies, across different sucrose concentrations (plotted as log scale but with actual concentrations)." The correct Figure 1B legend is: B: foragers tested 90 min after being fed 30μl 30% sucrose solution. Data based on 3 colonies per species (N = 90 bees per species).

Increasing competition due to market globalization, product diversity and technological breakthroughs stimulates independent automotive companies to collaborate in a supply chain that allows them to gain mutual benefits. Especially the events of the past years have shell-shocked even the most ardent industry participants – a crisis and the following hard recovery. Not only the critical challenges in implementing process lean with low cost and high quality, also critical to success is the ability to efficiently meet stricter emissions and fuel economy standards escalating in most jurisdictions. With all the factors working beneath the waves, supply chain management becomes the core source of a company’s competitive advantages and even the trump of the entire automotive industry’s success. A proper supply chain strategy provides financial returns and other key factors superior to the old concepts which brought profits before but no longer up to date now. Correctly design and effectively evaluate the supply chains, and improve the supply chain structure dynamically over time, are the key methods for an automotive company to survive and succeed in the volatile and critical automobile industrial environment. In this research work, based on the real case study in the automotive door system supply, different supply chain scenarios are designed and corresponding performance evaluations are made by applying different methods, namely the conventional model and the integrated model with their corresponding algorithms. With conventional model, the evaluation is done from different aspects, where the chosen perspectives such as costs, flexibility, stability, and reliability are assessed respectively for the multi-stage international supply chains. The data applied in this model comes from real-case door module supply, and the evaluation results helps in the decision making in localization process of that certain project. To be able to evaluate more complicated supply chain scenarios in a more accurate and efficient way, an integrated model is designed for the comprehensive performance evaluation. Based on the fuzzy theory, a MDFIE (Multilevel Dynamic Fuzzy Integrated Evaluation) algorithm is developed to assess the automotive supply chain performance. With the real case of vehicle door system supply, a detailed index system is designed based on a profound understanding of the automotive door supply chain. And with this new method, supply chain scenarios with different outsource degree and integration degree are evaluated and analyzed, a positive solution of deeper integration and downstream task shifting in the automotive supply structure is concluded in the end. In addition to the use in this research work, the integrated model, especially the index system can be flexibly adjusted for other automotive supply chains under their special interest and requirements. And with the MDFIE algorithm or other possible methods, the model can also be further developed into user-friendly software or system for the normal application. This software development is suggested for the further research. Based on the researches done in this work, a new tier structure is proposed as well. A mega system supplier which is defined as the new Tier 0,5 and other outsourced service companies which are playing as the half tiers (tier 1,5/ 2,5…) are discussed in this work. With all the theoretical researches and practical investigations, this new structure which occupies the niche positions of supply chain is supposed to be benefiting the entire automotive supply chain in many critical aspects, like the long lasting over capacity problem and the coming E-mobility trend. Some other suggestions like the application of RFID technology are also proposed for increasing the productivity and strengthen the information flow along supply chain. In general, improving the entire automotive supply chain performance, is the ultimate goal of supply chain management, which means balancing all participators’ maximum profits and offering the highest market service level. The realization of the proposals and concepts, is also supposed to be studied in the further research. ZUSAMENFASSUNG: Die strengeren Emissions- und Kraftstoffverbrauchstandards effizient zu erfüllen, spielt neben der kritischen Herausforderungen bei der Umsetzung „Lean Prozess“ mit niedrigen Kosten und hoher Qualität für den Erfolg auch eine entscheidende Rolle. Der zunehmende Wettbewerb infolge der Globalisierung der Märkte, der Produktvielfalt und technologischer Durchbrüche stimuliert die Zusammenarbeit von unabhängiger Automobileunternehmen. Insbesondre in den letzten Jahren wurden die Teilnehmer aus dem Industriebranche von der Krise und dessen nachstehender Erholung schockiert. Mit allen Faktoren unter den Wellen bleibt das Supply-Chain-Management die Hauptquelle für die Wettbewerbsvorteile eines Unternehmens und überhaupt der Trumpf des Erfolgs in der gesamten Automobilindustrie. Eine richtige Supply Chain-Strategie bietet finanzielle Erträge und andere wichtige Faktoren, die besser als die alten Konzepte sind. Richtiges Design und gewissenhaftes Abschätzen des Supply Chains, und im Laufe der Zeit die Supply-Chain-Struktur dynamisch zu Verbessern sind die Schlüssel-Methoden für ein Automobilunternehmen, um in dem unberechenbaren und kritischen Automobilindustrieumfeld zu überleben und erfolgreich zu bleiben. Diese Arbeit basiert auf der realen Fallstudien der Türsystemlieferung in der Automobilindustrie. Verschiedene Supply Chain Szenarien werden entworfen und die entsprechenden Leistungen werden durch Anwendung unterschiedlicher Methoden bewertet, und zwar das herkömmlichen Modell und das integrierte Modell mit den entsprechenden Algorithmen. Beim herkömmlichen Modell wird unter verschiedenen Aspekten bewertet, wobei die gewählten Perspektiven wie Kosten, Flexibilität, Stabilität und Zuverlässigkeit jeweils für die mehrstufigen internationalen Lieferketten bewertet werden. Die genommenen Daten in diesem Modell stammen aus den Fällen von Türmodul - Auslieferung. Die Bewertungsergebnisse sind beim Entscheidungstreffen im Lokalisierungsprozess des gewissen Projektes hilfreich. Um die komplizierter Supply Chain Szenarien in einer genaueren und effizienteren Methode bewerten zu können, wird ein integriertes Modell für die umfassenden Leistungsbewertung gebaut. Auf der Basis von Fuzzy-Theorie, wird ein MDFIE (Multilevel Dynamische Fuzzy Integrierte Evaluation) Algorithmus entwickelt. Anhand der realen Auslieferungsfälle im Fahrzeugtürensystem wird ein detailliertes Index-System ausgelegt, welches auf einem tiefen Verständnis der Automotive Supply Chain basiert. Mit dieser neuen Methode werden Supply-Chain-Szenarien durch unterschiedliche Outsourcengrade und Integrationsgrade ausgewertet und analysiert. Eine positive Lösung von der vertiefen Integration und von der nachgeordneten Aufgabenumlagerung in der Automobilzuliefer-Struktur wird am Ende kristallisiert. Zusätzlich zu dem Einsatz in dieser Arbeit kann das integrierte Modell, vor allem das Index-System flexibel für andere Wertschöpfungsketten ihrer besonderen Interessen und Bedürfnissen entsprechend angepasst werden. Und mit dem MDFIE Algorithmus oder andere mögliche Methoden kann das Modell auch in einer benutzerfreundlichen Software oder System für die normale Anwendung integriert und entwickelt werden. Diese Software-Entwicklung wird für die weitere Forschung vorgeschlagen. Basierend auf den Untersuchungen in dieser Arbeit wird eine neue Stufenstruktur auch vorgeschlagen. Ein Mega-Systemzulieferer, die sogenannt neues Tier 0,5 ist, und ausgelagerter Service-Unternehmen, die als Hälfte Tiers (Tier 1,5 / 2,5 ...) definiert werden, sind in dieser Arbeit diskutiert. Mit theoretischen und praktischen Forschungen soll diese neue Struktur, deren Nische Positionen der Supply Chain beschäftigt sind, zu Gunsten der gesamten automobilen Wertschöpfungskette in vielen kritischen Aspekten bringen, z.B. das Überkapazitätsproblem und der kommende E-Mobilität Trend. Einige andere Vorschläge wie die Anwendung der RFID-Technologie zur Steigerung der Produktivität und zur Stärkung der Informationsfluss entlang der Lieferkette wird auch gemacht. Das ultimative Ziel des Supply-Chain- Managemenes ist die allgemeine Verbesserung der gesamten automobilen Wertschöpfungskettenleistung, die die maximale Gewinne von allen Teilnehmern zur Balancierung und den höchsten Market-Service-Level bedeutet. Die Realisierung der Vorschläge und Konzepte soll auch in der weiteren Forschung untersucht werden.

In the European honey bee, Apis mellifera, pollen foragers have a higher sucrose responsiveness than nectar foragers when tested using a proboscis extension response (PER) assay. In addition, Africanized honey bees have a higher sucrose responsiveness than European honey bees. Based on the biology of the Eastern honey bee, A. cerana, we hypothesized that A. cerana should also have a higher responsiveness to sucrose than A. mellifera. To test this hypothesis, we compared the sucrose thresholds of pollen foragers and nectar foragers in both A. cerana and A. mellifera in Fujian Province, China. Pollen foragers were more responsive to sucrose than nectar foragers in both species, consistent with previous studies. However, contrary to our hypothesis, A. mellifera was more responsive than A. cerana. We also demonstrated that this higher sucrose responsiveness in A. mellifera was not due to differences in the colony environment by co-fostering two species of bees in the same mixed-species colonies. Because A. mellifera foragers were more responsive to sucrose, we predicted that their nectar foragers should bring in less concentrated nectar compared to that of A. cerana. However, we found no differences between the two species. We conclude that A. cerana shows a different pattern in sucrose responsiveness from that of Africanized bees. There may be other mechanisms that enable A. cerana to perform well in areas with sparse nectar resources.

Cyclic nucleotide phosphodiesterases (PDEs) decompose second messengers cAMP and cGMP that play critical roles in many physiological processes. PDE1 of Saccharomyces cerevisiae has been subcloned and expressed in Escherichia coli. Recombinant yPDE1 has a KM of 110 μM and a kcat of 16.9 s–1 for cAMP and a KM of 105 μM and a kcat of 11.8 s–1 for cGMP. Thus, the specificity constant (kcat/KMcAMP)/(kcat/KMcGMP) of 1.4 indicates a dual specificity of yPDE1 for hydrolysis of both cAMP and cGMP. The crystal structures of unliganded yPDE1 and its complex with GMP at 1.31 Å resolution reveal a new structural folding that is different from those of human PDEs but is partially similar to that of some other metalloenzymes such as metallo-β-lactamase. In spite of their different structures and divalent metals, yPDE1 and human PDEs may share a common mechanism for hydrolysis of cAMP and cGMP.

Today, scientific experiments and simulations produce massive amounts of heterogeneous data that need to be stored and analyzed. Given that these large datasets are stored in many files, formats and locations, how can scientists find relevant data, duplicates or similarities? In this context, we concentrate on developing algorithms to compare similarity of time series for the purpose of search, classification and clustering. For example, generating accurate patterns from climate related time series is important not only for building models for weather forecasting and climate prediction, but also for modeling and predicting the cycle of carbon, water, and energy. We developed the methodology and ran an exploratory analysis of climatic and ecosystem variables from the FLUXNET2015 dataset. The proposed combination of similarity metrics, nonlinear dimension reduction, clustering methods and validity measures for time series data has never been applied to unlabeled datasets before, and provides a process that can be easily extended to other scientific time series data. The dimensionality reduction step provides a good way to identify the optimum number of clusters, detect outliers and assign initial labels to the time series data. We evaluated multiple similarity metrics, in terms of the internal cluster validity for driver as well as response variables. While the best metric often depends on a number of factor, the Euclidean distance seems to perform well for most variables and also in terms of computational expense.

A ubiquitous problem in aggregating data across different experimental and observational data sources is a lack of software infrastructure that enables flexible and extensible standardization of data and metadata. To address this challenge, we developed HDMF, a hierarchical data modeling framework for modern science data standards. With HDMF, we separate the process of data standardization into three main components: (1) data modeling and specification, (2) data I/O and storage, and (3) data interaction and data APIs. To enable standards to support the complex requirements and varying use cases throughout the data life cycle, HDMF provides object mapping infrastructure to insulate and integrate these various components. This approach supports the flexible development of data standards and extensions, optimized storage backends, and data APIs, while allowing the other components of the data standards ecosystem to remain stable. To meet the demands of modern, large-scale science data, HDMF provides advanced data I/O functionality for iterative data write, lazy data load, and parallel I/O. It also supports optimization of data storage via support for chunking, compression, linking, and modular data storage. We demonstrate the application of HDMF in practice to design NWB 2.0 [13], a modern data standard for collaborative science across the neurophysiology community.

The use of quantum computing in graph community detection and regularity checking related to Szemerédi's Regularity Lemma (SRL) are demonstrated with D-Wave Systems' quantum annealer and simulations. We demonstrate the capability of quantum computing in solving hard problems relevant to big data. A new community detection algorithm based on SRL is also introduced and tested.

Efficient protection of huge amount of IoT produced data is key for wide scale data analytic services. The most efficient way is to use pure symmetric encryption as that allows both fast decryption at the analytic engine side as well as energy efficient encryption at the IoT side. However, symmetric encryption can only be performed if there is a way to directly map an encrypted object to the correct key. Typically, such mapping require a unique IoT identity, which constitute a privacy problem. In this paper, we present an IoT identity protection scheme for symmetric IoT data encryption. We give basic security definitions for this problem setting, present a new construction and give security proofs of security level achieved with the construction. Performance figures for a proof of concept implementation are also given. The new scheme gives a fair trade-off between identity privacy and complexity.