Beyond orchids and dandelions: Susceptibility to environmental influences is not bimodal

This study focused on generality versus specificity of susceptibility of effects of eight family and child-care exposures measured between 3 and 54 months of age (e.g., sensitive parenting, child-care quality) on five child development outcomes assessed at age 4.5 years (e.g. behavior problems, preacademic skill), using data from The National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (n = 1,364, boys = 705; White = 1,097, Black = 176, other = 91), while applying a novel influence-statistics method. Results indicated that susceptibility across the environment-predictor:child-outcome associations is normally rather than bimodally (i.e., orchid–dandelion) distributed. Analysis of susceptibility documents both domain generality and specificity of developmental plasticity, with effect sizes proving small in the former case. As predicted, children who as infants had difficult temperaments or who scored higher on a polygenic-plasticity score (serotonin-transporter-linked promoter region [5-HTTLPR], dopamine receptor D4 [DRD4], brain-derived neurotrophic factor [BDNF]) proved somewhat more susceptible to some of the environmental effects investigated. Results lead to the recommendation that two-types-of-individuals vis-a-vis susceptibility to environmental influences be questioned and general-trait conceptions of susceptibility be further investigated.

Adaption of the OMOP CDM for Rare Diseases

The OMOP Common Data Model (OMOP CDM) is an option to store patient data and to use these in an international context. Up to now, rare diseases can only be partly described in OMOP CDM. Therefore, it is necessary to investigate which special features in the context of rare diseases (e.g. terminologies) have to be considered, how these can be included in OMOP CDM and how physicians can use the data. An interdisciplinary team developed (1) a Transition Database for Rare Diseases by mapping Orpha Code, Alpha ID, SNOMED, ICD-10-GM, ICD-10-WHO and OMOP-conform concepts; and (2) a Rare Diseases Dashboard for physicians of a German Center of Rare Diseases by using methods of user-centered design. This demonstrated how OMOP CDM can be flexibly extended for different medical issues by using independent tools for mappings and visualization. Thereby, the adaption of OMOP CDM allows for international collaboration, enables (distributed) analysis of patient data and thus it can improve the care of people with rare diseases.

Hashing based Data Transaction and Optimized Storage for IoT Applications

Blockchain technology, which would be the underlying technology, has recently become very popular with the increase in cryptocurrencies and is being used in IoT and other fields. There have been shortfalls, however, which impede its implementation, including the volume of space. Transactions will be produced at a significant level due to the huge amount of Connected systems that often work in many networks as data processors. In IoT, the storage issue will become more intense. Current storing data platforms have a wide range of features to respond to an extensive variety spectrum of uses. Nevertheless, new groups of systems have arisen, e.g., blockchain with data version control, fork semantics, tamper-evidence or some variation thereof, and distributed analysis. They're showing new challenges for storage solutions to effectively serve such energy storage Systems by integrating the criteria mentioned in the processing. This paper discusses the potential security and privacy concerns of IoT applications and also it is shown that in first step the storage is enhanced by 50% and further in the next step, it is improved and it takes only 256 bytes irrespective of the input data size.

Dynamic analysis of IoT systems based on full-system emulation in QEMU

The sweeping evolution of the Internet of Things (IoT) requires the development of methods and tools for analyzing such devices. A significant part of similar devices run under operating systems (OS) of the Linux family. Direct application of existing tools for analyzing software (SW) of this class of devices is not always possible. In the process of researching embedded Linux OS, the ELF (embedded linux fuzz) tool was created, which is presented in this work. The article deals with the analysis of systems built exclusively on the basis of Linux kernels. ELF environment is designed for dynamic analysis of devices based on full-system emulation in QEMU. ELF was based on the following aspects: performing software testing and analysis of real devices in an environment as close as possible to their «native» execution environment; integration with existing fuzzing tools; the ability to conduct distributed analysis.