Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.     

Current Understandings on Magnesium Deficiency and Future Outlooks for Sustainable Agriculture

The productivity of agricultural produce is fairly dependent on the availability of nutrients and efficient use. Magnesium (Mg²⁺) is an essential macronutrient of living cells and is the second most prevalent free divalent cation in plants. Mg²⁺ plays a role in several physiological processes that support plant growth and development. However, it has been largely forgotten in fertilization management strategies to increase crop production, which leads to severe reductions in plant growth and yield. In this review, we discuss how the Mg²⁺ shortage induces several responses in plants at different levels: morphological, physiological, biochemical and molecular. Additionally, the Mg²⁺ uptake and transport mechanisms in different cellular organelles and the role of Mg²⁺ transporters in regulating Mg²⁺ homeostasis are also discussed. Overall, in this review, we critically summarize the available information about the responses of Mg deficiency on plant growth and development, which would facilitate plant scientists to create Mg²⁺-deficiency-resilient crops through agronomic and genetic biofortification.     

Synthesis and characterization of caprolactone based polyurethane with degradable and antifouling performance

In this work,a degradable polyurethane composed of caprolactone(CL)and L-Lactide(LLA)as soft seg-ments,and 4,4'-methylenebis(cyclohexyl isocyanate)(H12MDI)and polytetramethylene ether glycol(PTMEG)as hard segments,was prepared.Hydrolytic degradation experiment revealed that the degrad-able polyurethane(PU)could be degraded in artificial seawater.It also showed that caprolactone-co-polyurethane(CL-PU)copolymer with higher crystallinity degraded much slower in artificial seawater.However,the introduction of LLA resulted in an increase in the hydrophilicity and reduction in the crys-tallinity of degradable PU,as demonstrated by the contact angle analysis.The result of the scanning elec-tron microscope showed that the surface of degradable PU renewed under static condition.Moreover,degradable PU was able to be used as a carrier,and it controlled the release rate of 4,5-dichloro-2-octyl-isothiazolone(DCOIT).The anti-diatom(Navicula incerta)test demonstrated that the(caprolactone-co-L-lactide)-co-polyurethane 4(CL/LAx-PU4)with DCOIT contents prevented the adhe-sion of diatom Navicula incerta(88.37％reduction)due to their self-polishing and the release of antifou-lants.Therefore,the degradable PU consisted of CL,LLA,and DCOIT could be a durable resin with good antifouling activity for the application in the marine anti-biofouling field.     

Catalase (CAT) Gene Family in Rapeseed (Brassica napus L.): Genome-Wide Analysis,Identification, and Expression Pattern in Response to Multiple Hormones and Abiotic Stress Conditions

Catalase (CAT) is an antioxidant enzyme expressed by the CAT gene family and exists in almost all aerobic organisms. Environmental stresses induce the generation of reactive oxygen species (ROS) that eventually hinder plant growth and development. The CAT enzyme translates the hydrogen peroxide (H₂O₂) to water (H₂O) and reduce the ROS levels to shelter the cells’ death. So far, the CAT gene family has not been reported in rapeseed (Brassica napus L.). Therefore, a genome-wide comprehensive analysis was conducted to classify the CAT genes in the rapeseed genome. The current study identified 14 BnCAT genes in the rapeseed genome. Based on phylogenetic and synteny analysis, the BnCATs belong to four groups (Groups I–IV). A gene structure and conserved motif analysis showed that Group I, Group II, and Group IV possess almost the same intron/exon pattern, and an equal number of motifs, while Group III contains diverse structures and contain 15 motifs. By analyzing the cis-elements in the promoters, we identified five hormone-correlated responsive elements and four stress-related responsive elements. Further, six putative bna-miRNAs were also identified, targeting three genes (BnCAT4, BnCAT6, and BnCAT8). Gene ontology (GO) enrichment analysis showed that the BnCAT genes were largely related to cellular organelles, ROS response, stimulus response, stress response, and antioxidant enzymes. Almost 10 BnCAT genes showed higher expression levels in different tissues, i.e., root, leaf, stem, and silique. The expression analysis showed that BnCAT1–BnCAT3 and BnCAT11–BnCAT13 were significantly upregulated by cold, salinity, abscisic acid (ABA), and gibberellic acid (GA) treatment, but not by drought and methyl jasmonate (MeJA). Notably, most of the genes were upregulated by waterlogging stress, except BnCAT6, BnCAT9, and BnCAT10. Our results opened new windows for future investigations and provided insights into the CAT family genes in rapeseed.     

A Novel DUF569 Gene Is a Positive Regulator of the Drought Stress Response in Arabidopsis

In the last two decades, global environmental change has increased abiotic stress on plants and severely affected crops. For example, drought stress is a serious abiotic stress that rapidly and substantially alters the morphological, physiological, and molecular responses of plants. In Arabidopsis, several drought-responsive genes have been identified; however, the underlying molecular mechanism of drought tolerance in plants remains largely unclear. Here, we report that the “domain of unknown function” novel gene DUF569 (AT1G69890) positively regulates drought stress in Arabidopsis. The Arabidopsis loss-of-function mutant atduf569 showed significant sensitivity to drought stress, i.e., severe wilting at the rosette-leaf stage after water was withheld for 3 days. Importantly, the mutant plant did not recover after rewatering, unlike wild-type (WT) plants. In addition, atduf569 plants showed significantly lower abscisic acid accumulation under optimal and drought-stress conditions, as well as significantly higher electrolyte leakage when compared with WT Col-0 plants. Spectrophotometric analyses also indicated a significantly lower accumulation of polyphenols, flavonoids, carotenoids, and chlorophylls in atduf569 mutant plants. Overall, our results suggest that novel DUF569 is a positive regulator of the response to drought in Arabidopsis.     

Analysis and tuning of adaptive generalized predictive control

The adaptive Generalized Predictive Controller (Clarke et al., 1987a, b) is capable of controlling plants with variable dead-time, unknown model orders and unstable poles and zeros. This paper shows how the GPC control law can be written in an equivalent general linear transfer function form which simplifies closed-loop (eg. root locus) analysis. Three recommended strategies for selecting the design parameters during the commissioning stage allow the user to adjust the closed-loop speed of response on-line using only a single active tuning parameter. Experimental runs confirm the ability of adaptive GPC to provide a consistent closed-loop response in spite of large process changes.     

PMSS: A programmable memory system and scheduler for complex memory patterns

HPC industry demands more computing units on FPGAs, to enhance the performance by using task/data parallelism. FPGAs can provide its ultimate performance on certain kernels by customizing the hardware for the applications. However, applications are getting more complex, with multiple kernels and complex data arrangements, generating overhead while scheduling/managing system resources. Due to this reason all classes of multi threaded machines–minicomputer to supercomputer–require to have efficient hardware scheduler and memory manager that improves the effective bandwidth and latency of the DRAM main memory. This architecture could be a very competitive choice for supercomputing systems that meets the demand of parallelism for HPC benchmarks. In this article, we proposed a Programmable Memory System and Scheduler (PMSS), which provides high speed complex data access pattern to the multi threaded architecture. This proposed PMSS system is implemented and tested on a Xilinx ML505 evaluation FPGA board. The performance of the system is compared with a microprocessor based system that has been integrated with the Xilkernel operating system. Results show that the modified PMSS based multi-accelerator system consumes 50% less hardware resources, 32% less on-chip power and achieves approximately a 19x speedup compared to the MicroBlaze based system.     

PHOTOCATALYTIC OXIDATION OF ALDEHYDES/PCE USING POROUS ANATASE TITANIA AND VISIBLE-LIGHT-RESPONSIVE BROOKITE TITANIA

We have synthesized an annealed porous aerogel titania (LUAG2), which demonstrates a very high photocatalytic activity for aldehydes and perchloroethylene (PCE) photocatalytic oxidation (PCO) in gas phase under blacklight and fluorescent light irradiation. LUAG2 has a BET surface area of 237 m²/g and a porosity of 0.31 (volume fraction). X-ray diffraction (XRD) analysis shows LUAG2 is nearly pure anatase. It has improved the destruction of PCE and aldehydes as a group by 10-34% with black light compared to Degussa P-25. The optimum water vapor to butyraldehyde molar ratio is around 1/3. LUAG2 also shows better mineralization to CO₂ than Degussa P-25 TiO₂ does. Under irradiation of a 4 W fluorescent lamp LUAG2 gives a consistently higher conversion than that of Degussa P-25. The highly active photocatalyst indicates potential applications in indoor and outdoor environmental pollution control. A visible-light-responsive TiO₂, NTB 200, is also investigated for comparison purposes.     

Video background modeling: recent approaches,issues and our proposed techniques

Effective and efficient background subtraction is important to a number of computer vision tasks. We introduce several new techniques to address key challenges for background modeling using a Gaussian mixture model (GMM) for moving objects detection in a video acquired by a static camera. The novel features of our proposed model are that it automatically learns dynamics of a scene and adapts its parameters accordingly, suppresses ghosts in the foreground mask using a SURF features matching algorithm, and introduces a new spatio-temporal filter to further refine the foreground detection results. Detection of abrupt illumination changes in the scene is dealt with by a model shifting-based scheme to reuse already learned models and spatio-temporal history of foreground blobs is used to detect and handle paused objects. The proposed model is rigorously tested and compared with several previous models and has shown significant performance improvements.