Development of a hardware-In-the-Loop (HIL) testbed for cyber-physical security in smart buildings

As smart buildings move towards open communication technologies, providing access to the Building Automation System (BAS) through the intranet, or even remotely through the Internet, has become a common practice. However, BAS was historically developed as a closed environment and designed with limited cyber-security considerations. Thus, smart buildings are vulnerable to cyber-attacks with the increased accessibility. This study introduces the development and capability of a Hardware-in-the-Loop (HIL) testbed for testing and evaluating the cyber-physical security of typical BASs in smart buildings. The testbed consists of three subsystems: (1) a real-time HIL emulator simulating the behavior of a virtual building as well as the Heating, Ventilation, and Air Conditioning (HVAC) equipment via a dynamic simulation in Modelica; (2) a set of real HVAC controllers monitoring the virtual building operation and providing local control signals to control HVAC equipment in the HIL emulator; and (3) a BAS server along with a web-based service for users to fully access the schedule, setpoints, trends, alarms, and other control functions of the HVAC controllers remotely through the BACnet network. The server generates rule-based setpoints to local HVAC controllers. Based on these three subsystems, the HIL testbed supports attack/fault-free and attack/fault-injection experiments at various levels of the building system. The resulting test data can be used to inform the building community and support the cyber-physical security technology transfer to the building industry.Comment: Presented at the 2023 ASHRAE Winter Conferenc

Comparative Study Reveals Insights of Sheepgrass (Leymus chinensis) Coping With Phosphate-Deprived Stress Condition

Sheepgrass [Leymus chinensis (Trin.) Tzvel] is a valuable forage plant highly significant to the grassland productivity of Euro-Asia steppes. Growth of above-ground tissues of L. chinensis is the major component contributing to the grass yield. Although it is generally known that this species is sensitive to ecosystem disturbance and adverse environments, detailed information of how L. chinensis coping with various nutrient deficiency especially phosphate deprivation (-Pi) is still limited. Here, we investigated impact of Pi-deprivation on shoot growth and biomass accumulation as well as photosynthetic properties of L. chinensis. Growth inhibition of Pi-deprived seedlings was most obvious and reduction of biomass accumulation and net photosynthetic rate (Pn) was 55.3 and 63.3%, respectively, compared to the control plants grown under Pi-repleted condition. Also, we compared these characters with seedlings subjected to low-Pi stress condition. Pi-deprivation caused 18.5 and 12.3% more reduction of biomass and Pn relative to low-Pi-stressed seedlings, respectively. Further analysis of in vivo chlorophyll fluorescence and thylakoid membrane protein complexes using 2D-BN/SDS-PAGE combined with immunoblot detection demonstrated that among the measured photosynthetic parameters, decrease of ATP synthase activity was most pronounced in Pi-deprived plants. Together with less extent of lipid peroxidation of the thylakoid membranes and increased ROS scavenger enzyme activities in the leaves of Pi-deprived seedlings, we suggest that the decreased activity of ATP synthase in their thylakoids is the major cause of the greater reduction of photosynthetic efficiency than that of low-Pi stressed plants, leading to the least shoot growth and biomass production in L. chinensis

A critical review of cyber-physical security for building automation systems

Modern Building Automation Systems (BASs), as the brain that enables the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as optimized automation via outsourced cloud analytics and increased building-grid integrations. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber-secure resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. The impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber-secure resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.Comment: 38 pages, 7 figures, 6 tables, submitted to Annual Reviews in Contro

Identification of the C-Reactive Protein Interaction Network Using a Bioinformatics Approach Provides Insights into the Molecular Pathogenesis of Hepatocellular Carcinoma

Background/Aims: C reactive protein (CRP) levels are elevated in many diseases, including malignant tumors and cardiovascular disorders. In this study, the protein interaction network for CRP was evaluated to determine the importance of CRP and its interacting proteins in the molecular pathogenesis of hepatocellular carcinoma (HCC). Methods: Isobaric tags for relative and absolute quantitation (iTRAQ) and mass spectrometry were used to identify CRP interacting proteins in SMMC7721 cells. Moreover, Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to evaluate enriched genes and pathways for differentially expressed genes using DAVID and WebGestalt. Co-immunoprecipitation and western blot analyses were employed to assess interactions between CRP and KRT8, ANXA2, ENO2, and HSP90B1. Results: In total, 52 proteins that interact with CRP were identified. A GO analysis suggested that most of the interacting proteins were involved in CRP complexes and regulated metabolic processes. A KEGG pathway analysis suggested that most CRP-interacting proteins contribute to the TRAIL signaling pathway, Class I PI3K/Akt signaling pathway, plasma membrane estrogen receptor signaling, Nectin adhesion pathway, and S1P1 pathway. Immunoprecipitation and western blot analyses revealed interactions between CRP and KRT8, ANXA2, ENO2, and HSP90B1. Conclusions: iTRAQ based proteomic profiling revealed the network of CRP interacting proteins. This network may activate the PI3K/Akt signaling pathway, thereby contributing to the pathogenesis of HCC

Galaxy and mass assembly (GAMA): Self-Organizing Map application on nearby galaxies

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and Sérsic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between two and six clusters. Here we use Self-Organizing Maps (SOM), an unsupervised learning technique that can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these 5D clusters in the feature space on to 2D projections. To further analyse these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped on to three or five clusters. We explore where the ‘green valley’ galaxies are mapped on to the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped on to the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or ‘featured’ can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough

Galaxy And Mass Assembly (GAMA): Self-Organizing Map Application on Nearby Galaxies

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and S\'ersic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between 2 and 6 clusters. Here we use Self Organizing Maps (SOM), an unsupervised learning technique which can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these five-dimensional clusters in the feature space onto two-dimensional projections. To further analyze these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped onto three or five clusters. We explore where the "green valley" galaxies are mapped onto the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped onto the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or "featured" can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough.Comment: 14 pages, 14 figures, accepted by MNRA

Resilient Microgrids through Software-Defined Networking

Multiple major blackouts had occurred in the U.S. power distribution system highlighting the importance of enhancing electricity resiliency. Microgrid is the new paradigm incorporating high flexibility and reliability in power supply. It allows various distributed energy resources and loads to be integrated and coordinated as an intelligent entity through control and communication infrastructure. Microgrid control technologies have been continuously developed over 20 years. However, there is still a lack of communication architecture that is able to provide fast, reliable and elastic services for multi-level data transmission and adaptable network management. This dissertation solves this intractable problem by integrating programmable networks into microgrid to provide flexible and easy-to-manage communication solutions, thus enabling resilient microgrid operations in face of various cyber and physical disturbances. Both theoretical study and experimental tests have shown that the novel software-defined networking (SDN) based communication architecture can significantly improve the microgrid emergency control performance and expedite the development of microgrid applications. While providing resilience benefits to its local customers, a single microgrid can hardly contribute to the resiliency of the main distribution grid. Recent research shows interconnecting individual microgrids to form a networked microgrids community offers a new, more resilient solution for distribution grid. To support this innovation, this dissertation significantly extends the SDN-based communication architecture to achieve fast power support among microgrids, transforming isolated local microgrids into integrated networked microgrids capable of achieving the desired resiliency, elasticity and efficiency. Further, a novel event-triggered communication scheme is devised to enable distributed power sharing among microgrids in both the transient period and the steady state, a capability previously unattainable using existing technologies. This structure is validated through a cyber-physical Hardware-in-the-Loop (HIL) testbed designed in this dissertation for testing and prototyping networked microgrids technologies. One of the multifaceted benefits of the SDN-based architecture is that it provides a platform with open data access for the development of various advanced microgrid applications. As an instance, a generalized microgrid power flow (GMPF) algorithm is developed as an essential tool for control design and microgrid planning. Power flow analysis for islanded microgrid is a challenging problem due to the lack of means to incorporate the hierarchical control effect. This dissertation bridges the gap by introducing three novel GMPF techniques: 1) it introduces the generalized distributed generator (DG) bus and the adaptive swing bus to model the DGs’ behaviors; 2) the droop based power flow is used to initialize the secondary control adjustment; and 3) three types of secondary control modes are developed within a double loop framework. GMPF has proved to have excellent convergence performance and be able to provide information of power sharing and voltage regulation under different control modes, which makes it a powerful tool for microgrid planning, control design, and energy management, etc.

Identification of SSR markers closely linked to the yellow seed coat color gene in heading Chinese cabbage (Brassica rapa L. ssp. pekinensis)

Research on the yellow-seeded variety of heading Chinese cabbage will aid in broadening its germplasm resources and lay a foundation for AA genome research in Brassica crops. Here, an F2 segregating population of 1575 individuals was constructed from two inbred lines (brown-seeded ‘92S105’ and yellow-seeded ‘91-125’). This population was used to identify the linkage molecular markers of the yellow seed coat trait using simple sequence repeat (SSR) techniques combined with a bulk segregant analysis (BSA). Of the 144 SSR primer pairs on the A01-A10 chromosomes from the Brassica database (http://brassicadb.org/brad/), two pairs located on the A06 chromosome showed polymorphic bands between the bulk DNA pools of eight brown-seeded and eight yellow-seeded F2 progeny. Based on the genome sequence, 454 SSR markers were designed to A06 to detect these polymorphic bands and were synthesized. Six SSR markers linked to the seed coat color gene were successfully selected for fine linkage genetic map construction, in which the two closest flanking markers, SSR449a and SSR317, mapped the Brsc-ye gene to a 40.2 kb region with distances of 0.07 and 0.06 cM, respectively. The molecular markers obtained in this report will assist in the marker-assisted selection and breeding of yellow-seeded lines in Brassica rapa L. and other close species