Optimizing transcriptomics to study the evolutionary effect of FOXP2

The field of genomics was established with the sequencing of the human genome, a pivotal achievement that has allowed us to address various questions in biology from a unique perspective. One question in particular, that of the evolution of human speech, has gripped philosophers, evolutionary biologists, and now genomicists. However, little is known of the genetic basis that allowed humans to evolve the ability to speak. Of the few genes implicated in human speech, one of the most studied is FOXP2, which encodes for the transcription factor Forkhead box protein P2 (FOXP2). FOXP2 is essential for proper speech development and two mutations in the human lineage are believed to have contributed to the evolution of human speech. To address the effect of FOXP2 and investigate its evolutionary contribution to human speech, one can utilize the power of genomics, more specifically gene expression analysis via ribonucleic acid sequencing (RNA-seq). To this end, I first contributed in developing mcSCRB-seq, a highly sensitive, powerful, and efficient single cell RNA-seq (scRNA-seq) protocol. Previously having emerged as a central method for studying cellular heterogeneity and identifying cellular processes, scRNA-seq was a powerful genomic tool but lacked the sensitivity and cost-efficiency of more established protocols. By systematically evaluating each step of the process, I helped find that the addition of polyethylene glycol increased sensitivity by enhancing the cDNA synthesis reaction. This, along with other optimizations resulted in developing a sensitive and flexible protocol that is cost-efficient and ideal in many research settings. A primary motivation driving the extensive optimizations surrounding single cell transcriptomics has been the generation of cellular atlases, which aim to identify and characterize all of the cells in an organism. As such efforts are carried out in a variety of research groups using a number of different RNA-seq protocols, I contributed in an effort to benchmark and standardize scRNA-seq methods. This not only identified methods which may be ideal for the purpose of cell atlas creation, but also highlighted optimizations that could be integrated into existing protocols. Using mcSCRB-seq as a foundation as well as the findings from the scRNA-seq benchmarking, I helped develop prime-seq, a sensitive, robust, and most importantly, affordable bulk RNA-seq protocol. Bulk RNA-seq was frequently overlooked during the efforts to optimize and establish single-cell techniques, even though the method is still extensively used in analyzing gene expression. Introducing early barcoding and reducing library generation costs kept prime-seq cost-efficient, but basing it off of single-cell methods ensured that it would be a sensitive and powerful technique. I helped verify this by benchmarking it against TruSeq generated data and then helped test the robustness by generating prime-seq libraries from over seventeen species. These optimizations resulted in a final protocol that is well suited for investigating gene expression in comprehensive and high-throughput studies. Finally, I utilized prime-seq in order to develop a comprehensive gene expression atlas to study the function of FOXP2 and its role in speech evolution. I used previously generated mouse models: a knockout model containing one non-functional Foxp2 allele and a humanized model, which has a variant Foxp2 allele with two human-specific mutations. To study the effect globally across the mouse, I helped harvest eighteen tissues which were previously identified to express FOXP2. By then comparing the mouse models to wild-type mice, I helped highlight the importance of FOXP2 within lung development and the importance of the human variant allele in the brain. Both mcSCRB-seq and prime-seq have already been used and published in numerous studies to address a variety of biological and biomedical questions. Additionally, my work on FOXP2 not only provides a thorough expression atlas, but also provides a detailed and cost-efficient plan for undertaking a similar study on other genes of interest. Lastly, the studies on FOXP2 done within this work, lay the foundation for future studies investigating the role of FOXP2 in modulating learning behavior, and thereby affecting human speech

POWER TRANSFORMER HEALTH INDEX ESTIMATION USING EVIDENTIAL REASONING

Market-oriented power distribution system requires a well-planned budget with scheduled preventive and corrective maintenance during a replacement of units that are in an unsatisfactory condition. In recent years, the concept of the transformer health index as an integral part of resource management was adopted for the condition assessment and ranking of ETs. However, because of the lack of regular measurement and inspections, the confidence in health index value is greatly reduced.The paper proposes a novel methodology for the ET condition assessment and the lifetime increase through the establishment of priorities for control and maintenance. The solution is based on the upgraded health index, where the confidence to the measurement results is calculated using Evidential reasoning algorithm based on Dempster – Shafer theory. A novel, two – level hierarchical model of ET health index is proposed, with real weighting factors values. This way, the methodology for ET ranking includes the value of available information to describe ET current state. The proposed methodology is tested on real data of an installed ET and compared with the traditional health index calculation

MULTI–CRITERIA HOME ENERGY MANAGEMENT SYSTEM SELECTION FOR THE SMART GRID SUPPORT

Home energy management systems (HEMS) are increasingly used as a tool that creates optimal consumption and production schedules for Smart Grids, by considering objectives such as energy costs, environmental concerns, load profiles, and consumer comfort. Multiple criteria selection of optimal HEMS seems to be superior to the traditional cost benefit assessment in measuring intangibles and soft impacts, introducing qualitative aspects in the analysis. This paper proposes an algorithm for the selection of optimal HEMS, using the fuzzy AHP method. This methodological framework provides a multi-criteria approach for estimating the benefits and costs of different HEMS within the Smart Grid uncertain environment. This method allows the decision makers to incorporate unquantifiable, asymmetrical, incomplete, non-obtainable information and partially ignorant facts into a decision model. Four criteria and eleven performances for the optimal solution selection are defined. The method is successful in the evaluation of alternatives in the presence of heterogeneous criteria and uncertain environment. The methodology is illustrated on the choice of HEMS from the power distribution company perspective. It is concluded that the evaluation of weighting factors has a decisive character in the choice of the final one of several alternative variants. Fuzzification of input values can also contribute to a more flexible view of the given problem and analysis of sensitivity to various input parameters

ENERGY LOSSES ESTIMATION BY POLYNOMIAL FITTING AND K-MEANS CLUSTERING

This paper represents an approach for the estimation and forecast of losses in a distribution power grid from data which are normally collected by the grid operator. The proposed approach utilizes the least squares optimization method in order to calculate the coefficients needed for estimation of losses. Besides optimization, a machine learning technique is introduced for clustering of coefficients into several seasons. The amount of data used in calculations is very large due to the fact that electrical energy injected in distribution grid is measured every fifteen minutes. Therefore, this approach is classified as the big data analysis. The used data sets are available in the Serbian distribution grid operator’s report for the year 2017. Obtained results are fairly accurate and can be used for losses classification as well as future losses estimation

OPTIMAL BATTERY STORAGE LOCATION AND CONTROL IN DISTRIBUTION NETWORK

The paper discusses the problem of the energy losses reduction in electrical networks using a battery energy storage system. One of the main research interests is to define the optimal battery location and control, for the given battery characteristics (battery size, maximum charge / discharge power, discharge depth, etc.), network configuration, network load, and daily load diagram. Battery management involves determining the state of the battery over one period (whether charging or discharging) and with what power it operates. Optimization techniques were used, which were applied to the model described in the paper. The model consists of a fitness function and a constraint. The fitness function is the dependence of the power losses in the network on the current battery power, and it is suggested that the function be fit by a n - order power function. The constraints apply to the very characteristics of the battery for storing electricity. At any time interval, the maximum power that the battery can receive or inject must be met. At any time, the stored energy in the battery must not exceed certain limits. The power of losses in the network is represented as the power of injection into the nodes of the network. The optimization problem was successfully solved by applying a genetic algorithm (GA), when determining optimal battery management. Finally, the optimal battery management algorithm is implemented on the test network. The results of the simulations are presented and discussed

Sistem centralizovanog upravljanja pumpnim stanicama u sistemima vodosnabdevanja

The pump station centralized management system is described in this paper. Pump stations represent the elements of extreme importance in these systems with the great level of expected reliability. However, the majority of these stations in Serbia, whether they are used for utility systems, or for agriculture, is characterized with low technical level. This condition consequently leads to the great number of negative effects, resulting in decreased energy efficiency, increased operational costs and increased number of failures. In this paper, modern trends in remote process control of these systems are presented. Complete system architecture is proposed, and the implementation of this technical solution on one water supply system in Serbia is described. The introduction of centralized solution for the pump stations control enables high system reliability and security, increased energy efficiency and optimized procedures of operational control and maintenance.U radu je opisan sistem centralizovanog upravljanja pumpnim stanicama. Pumpne stanice imaju veoma značajnu ulogu i predstavljaju elemente sistema od kojih se očekuje velika pouzdanost u radu. Međutim, većinu pumpnih stanica u našoj zemlji, bilo da se nalaze u komunalnim ili poljoprivrednim sistemima, karakteriše veoma nizak nivo tehničke opremljenosti. Ovakvo stanje ima za posledicu brojne negativne efekte kao što su: smanjenje energetske efikasnosti ovih sistema, povećanje troškova proizvodnje i povećanje broja kvarova u sistemu. U ovom radu su prikazane savremene tendencije kada su u pitanju upravljanje i kontrola procesa i uređaja na daljinu. Predložena je kompletna arhitektura sistema za upravljanje i dat je opis realizovanog integrisanog tehničkog rešenja u sistemima vodosnabdevanja. Uvođenje kompletnog centralizovanog rešenja za upravljanje pumpnim stanicama omogućava visoku pouzdanost i sigurnost u sistemu, povećani stepen energetske efikasnosti, kao i optimizovane procedure operativnog upravljanja i održavanja sistema

TRADE-OFF BETWEEN MULTIPLE CRITERIA IN SMART HOME CONTROL SYSTEM DESIGN

The successful automation of a smart home relies on the ability of the smart home control system to organize, process, and analyze different sources of information, according to several criteria. Because of variety of key design criteria that every smart home of the future should meet, the main challenge is the trade-off between them in uncertain environment. In this paper, a problem of smart home design has been solved using the methodology based on multiplicative form of multi-attribute utility theory. Aggregated functions describing different smart home alternatives are compared using stochastic dominance principle. The aggregation of different criteria has been performed through their numerical convolution, unlike usual approach of pairwise comparison, allowing only the additive form of aggregation of individual criteria. The methodology is illustrated on the smart home controller parameter setting

MULTI-CRITERIA ASSESMENT OF THE SMART GRID EFFICIENCY USING THE FUZZY ANALITICAL HYERARCHY PROCESS

In this paper, the key performance indicators related to the smart grid efficiency, as the key factor of any energy management system implementation have been analysed. The authors are proposing multi-criteria fuzzy AHP methodology for the determination of overall smart grid efficiency. Four criteria (technology, costs, user satisfaction, and environmental protection) and seven performances (according to EU and US initiatives for analysis of benefits and effects of smart grid systems) for the selection of optimal smart grid project are defined. The analysis shows that the dominant performances of the optimal smart grid project are efficiency, security and quality of supply. The methodology is illustrated on the choice of smart grid development strategy for the medium size power distribution company

Sensitive and powerful single-cell RNA sequencing using mcSCRB-seq

Single-cell RNA sequencing (scRNA-seq) has emerged as a central genome-wide method to characterize cellular identities and processes. Consequently, improving its sensitivity, flexibility, and cost-efficiency can advance many research questions. Among the flexible platebased methods, single-cell RNA barcoding and sequencing (SCRB-seq) is highly sensitive and efficient. Here, we systematically evaluate experimental conditions of this protocol and find that adding polyethylene glycol considerably increases sensitivity by enhancing cDNA synthesis. Furthermore, using Terra polymerase increases efficiency due to a more even cDNA amplification that requires less sequencing of libraries. We combined these and other improvements to develop a scRNA-seq library protocol we call molecular crowding SCRB-seq (mcSCRB-seq), which we show to be one of the most sensitive, efficient, and flexible scRNA-seq methods to date

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies