Automated smart hydroponics system using internet of things

This paper presents a design and implementation of an automated smart hydroponics system using internet of things. The challenges to be solved with this system are the increasing food demand in the world, the need of market of new sustainable method of farming using the Internet of Things. The design was implemented using NodeMcu, Node Red, MQTT and sensors that were chosen during component selection based on required parameters and sending it to the cloud to monitor and be processed. Investigation on previous works done and a review of Internet of Things and Hydroponic systems were done. First the prototype was constructed, programmed and tested, as well as sensors data between two different environments were taken and monitored on cloud-based web page with mobile application. Moreover, a bot has been introduced to control the supply chain and for notification purposes. The system improved its performance and allows it to successfully achieve the aim of the entire system implemented. There are some limitations which can be improved as future work such as including data science with the usage of the artificial intelligence to further improve the crops and get better outcome. Lastly to design end user platform to ease user interaction by using attractive design with no technical configuration involved

Identification of scaffold/Matrix Attachment (S/MAR) like DNA element from the gastrointestinal protozoan parasite Giardia lamblia

<p>Abstract</p> <p>Background</p> <p>Chromatin in the nucleus of all eukaryotes is organized into a system of loops and domains. These loops remain fastened at their bases to the fundamental framework of the nucleus, the matrix or the scaffold. The DNA sequences which anchor the bases of the chromatin loops to the matrix are known as Scaffold/Matrix Attachment Regions or S/MARs. Though S/MARs have been studied in yeast and higher eukaryotes and they have been found to be associated with gene organization and regulation of gene expression, they have not been reported in protists like <it>Giardia</it>. Several tools have been discovered and formulated to predict S/MARs from a genome of a higher eukaryote which take into account a number of features. However, the lack of a definitive consensus sequence in S/MARs and the randomness of the protozoan genome in general, make it a challenge to predict and identify such sequences from protists.</p> <p>Results</p> <p>Here, we have analysed the <it>Giardia </it>genome for the probable S/MARs predicted by the available computational tools; and then shown these sequences to be physically associated with the nuclear matrix. Our study also reflects that while no single computational tool is competent to predict such complex elements from protist genomes, a combination of tools followed by experimental verification is the only way to confirm the presence of these elements from these organisms.</p> <p>Conclusion</p> <p>This is the first report of S/MAR elements from the protozoan parasite <it>Giardia lamblia</it>. This initial work is expected to lay a framework for future studies relating to genome organization as well as gene regulatory elements in this parasite.</p

Interactive on smart classroom system using beacon technology

The emergence of many internet industries ushers in IOT era, and about to bring us to the point of universal connectivity. In the field of education, the IOT technology has a broad applicable prospect for a more interactive and intelligent way by improving the quality of teaching and management. The proposed class affair management system is mean to enrich the interaction between lecturers and students which in an efficient and smart way. Based on the existing model, a layered architecture is proposed to build the beacon based campus management system. Backend device and protocols compose the physical layer to collect the raw data from physical objects. Data link layer and control layer are responsible for forming required package and sending to corresponding layer. Beacon technology used for proposed design applies Bluetooth low energy 4.0 standard which allowing devices exchange data through Bluetooth at an extremely low power consumption-using a single coin cell battery can last for several years. Saved up to 97 percentage energy compared with similar system. The entire proposed platform allows participants to bring personally owned devices to access campus management system. Through location information, teaching activities and personalized information notification can be automatically accomplished, which will inspire the innovation and development of classroom teaching mode. Beacon technology has a great potential that can be completely transplanted into other scenario such as the hypermarket and library

Validity of self-reported height and weight and factors associated with errors in self-report

The aim of this investigation is to assess the validity of self-reported height and weight and to examine factors associated with errors in self-report. A cross-sectional study was conducted in Coimbatore, Tamil Nadu, South India, from June 20 to August 20, 2011. The study involved 389 men and 355 women aged 20 years and above. We found that self-reported height and weight were significantly correlated with measured height and weight for men and women [Pearson’s correlation coefficient(r) for men and women: 0.61 and 0.44 in height, 0.91 and 0.85 in weight, 0.76 and 0.64 in body mass index (BMI), respectively]. The prevalence of obesity based on self-reported height and weight were 7.9 and 15.8% for men and women, respectively, which was slightly smaller than that based on measured data 7.7 and 19.7%, respectively. Sensitivity and specificity of obesity based on self-report for both men and women were 97, 62% in men and 89, 64% in women, respectively. Participants with higher measured BMI significantly underestimated their weight compared to those with smaller BMI. It is also observed that among both men and women with measured BMI above 18.5 kg/m2 were likely to underestimate their weight and BMI below 18.5 kg/m2were likely to overestimate their weight. However, the presence of diabetes, hypertension and heart disease was not associated with the difference between measured and self-reported height and weight for both men and women. Our findings indicate that self-reported weight has an acceptable agreement with measured data, but self-reported height has only a moderate agreement with measured data. There were no significant differences by presence of chronic disease and educational level between the self-reported and measured height and weight in both men and women

RNA-Based Therapies: A Cog in the Wheel of Lung Cancer Defense

Lung cancer (LC) is a heterogeneous disease consisting mainly of two subtypes, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), and remains the leading cause of death worldwide. Despite recent advances in therapies, the overall 5-year survival rate of LC remains less than 20%. The efficacy of current therapeutic approaches is compromised by inherent or acquired drug-resistance and severe off-target effects. Therefore, the identification and development of innovative and effective therapeutic approaches are critically desired for LC. The development of RNA-mediated gene inhibition technologies was a turning point in the field of RNA biology. The critical regulatory role of different RNAs in multiple cancer pathways makes them a rich source of targets and innovative tools for developing anticancer therapies. The identification of antisense sequences, short interfering RNAs (siRNAs), microRNAs (miRNAs or miRs), anti-miRs, and mRNA-based platforms holds great promise in preclinical and early clinical evaluation against LC. In the last decade, RNA-based therapies have substantially expanded and tested in clinical trials for multiple malignancies, including LC. This article describes the current understanding of various aspects of RNA-based therapeutics, including modern platforms, modifications, and combinations with chemo-/immunotherapies that have translational potential for LC therapies

Small-signal analysis of a single-stage bridgeless boost half-bridge AC/DC converter with bidirectional switch

A small-signal analysis of a single-stage bridgeless boost half-bridge alternating current/direct current (AC/DC) converter with bidirectional switches is performed using circuit averaging method. The comprehensive approach to develop the small signal model from the steady state analysis is discussed. The small-signal model is then simulated with MATLAB/Simulink. The small-signal model is verified through the comparison of the bode-plot obtained from MATLAB/Simulink and the simulated large signal model in piecewise linear electrical circuit simulation (PLECS). The mathematical model obtain from the small-signal analysis is then used to determine the proportional gain Kp and integral gain Ki . In addition, the switch large-signal model is developed by considering the current and voltage waveforms during load transients and steady-state conditions

Genetically Encoded Spy Peptide Fusion System to Detect Plasma Membrane-Localized Proteins In Vivo

Membrane proteins are the main gatekeepers of cellular state, especially in neurons, serving either to maintain homeostasis or instruct response to synaptic input or other external signals. Visualization of membrane protein localization and trafficking in live cells facilitates understanding the molecular basis of cellular dynamics. We describe here a method for specifically labeling the plasma membrane-localized fraction of heterologous membrane protein expression using channelrhodopsins as a case study. We show that the genetically encoded, covalent binding SpyTag and SpyCatcher pair from the Streptococcus pyogenes fibronectin-binding protein FbaB can selectively label membrane-localized proteins in living cells in culture and in vivo in Caenorhabditis elegans. The SpyTag/SpyCatcher covalent labeling method is highly specific, modular, and stable in living cells. We have used the binding pair to develop a channelrhodopsin membrane localization assay that is amenable to high-throughput screening for opsin discovery and engineering

Development of wireless power transfer system using resonance principle with security features

This research describes a resonance principle based low power Wireless Power Transfer (WPT) system. The reflective impedance model is derived to evaluate the resonance coupling between coils. Additionally, a Cockroft-Walton voltage boosting circuit is incorporated to boost up the received voltage to the appropriate level, instead of using traditional conditioning circuits. The prototype model, operating at 130 kHz, is demonstrated experimentally and analysed graphically to validate the performance of the designed circuit. For an overall span of 100 mm coil separation distance, a maximum efficiency of 60% with no load and 36% with loaded system, is observed at a distance of 55 mm with approximate (e.g., manual) axial orientation of coils. It can be supported widely for portable electronic products and biomedical devices. As an added contribution, the WPT circuit was enabled by a password security feature using an Arduino microcontroller

MicroRNA-1 Attenuates the Growth and Metastasis of Small Cell Lung Cancer through CXCR4/FOXM1/RRM2 Axis

BACKGROUND: Small cell lung cancer (SCLC) is an aggressive lung cancer subtype that is associated with high recurrence and poor prognosis. Due to lack of potential drug targets, SCLC patients have few therapeutic options. MicroRNAs (miRNAs) provide an interesting repertoire of therapeutic molecules; however, the identification of miRNAs regulating SCLC growth and metastasis and their precise regulatory mechanisms are not well understood. METHODS: To identify novel miRNAs regulating SCLC, we performed miRNA-sequencing from donor/patient serum samples and analyzed the bulk RNA-sequencing data from the tumors of SCLC patients. Further, we developed a nanotechnology-based, highly sensitive method to detect microRNA-1 (miR-1, identified miRNA) in patient serum samples and SCLC cell lines. To assess the therapeutic potential of miR-1, we developed various in vitro models, including miR-1 sponge (miR-1Zip) and DOX-On-miR-1 (Tet-ON) inducible stable overexpression systems. Mouse models derived from intracardiac injection of SCLC cells (miR-1Zip and DOX-On-miR-1) were established to delineate the role of miR-1 in SCLC metastasis. In situ hybridization and immunohistochemistry were used to analyze the expression of miR-1 and target proteins (mouse and human tumor specimens), respectively. Dual-luciferase assay was used to validate the target of miR-1, and chromatin immunoprecipitation assay was used to investigate the protein-gene interactions. RESULTS: A consistent downregulation of miR-1 was observed in tumor tissues and serum samples of SCLC patients compared to their matched normal controls, and these results were recapitulated in SCLC cell lines. Gain of function studies of miR-1 in SCLC cell lines showed decreased cell growth and oncogenic signaling, whereas loss of function studies of miR-1 rescued this effect. Intracardiac injection of gain of function of miR-1 SCLC cell lines in the mouse models showed a decrease in distant organ metastasis, whereas loss of function of miR-1 potentiated growth and metastasis. Mechanistic studies revealed that CXCR4 is a direct target of miR-1 in SCLC. Using unbiased transcriptomic analysis, we identified CXCR4/FOXM1/RRM2 as a unique axis that regulates SCLC growth and metastasis. Our results further showed that FOXM1 directly binds to the RRM2 promoter and regulates its activity in SCLC. CONCLUSIONS: Our findings revealed that miR-1 is a critical regulator for decreasing SCLC growth and metastasis. It targets the CXCR4/FOXM1/RRM2 axis and has a high potential for the development of novel SCLC therapies. MicroRNA-1 (miR-1) downregulation in the tumor tissues and serum samples of SCLC patients is an important hallmark of tumor growth and metastasis. The introduction of miR-1 in SCLC cell lines decreases cell growth and metastasis. Mechanistically, miR-1 directly targets CXCR4, which further prevents FOXM1 binding to the RRM2 promoter and decreases SCLC growth and metastasis

ST6GalNAc-I Promotes Lung Cancer Metastasis by Altering MUC5AC Sialylation

Lung cancer (LC) is the leading cause of cancer-related mortality. However, the molecular mechanisms associated with the development of metastasis is poorly understood. Understanding the biology of LC metastasis is critical to unveil the molecular mechanisms for designing targeted therapies. We developed two genetically engineered LC mouse models- KrasG12D ;Trp53R172H/+ ;Ad-Cre (KPA) and KrasG12D ; Ad-Cre (KA). Survival analysis showed significantly (P=0.0049) shorter survival in KPA tumor-bearing mice as compared to KA, suggesting the aggressiveness of the model. Our transcriptomic data showed high expression of St6galnac-I in KPA compared to KA tumors. ST6GalNAc-I is an O-glycosyltransferase, which catalyzes the addition of sialic acid (SA) to the initiating GalNAc residues forming sialyl Tn (STn) on glycoproteins, such as mucins. Ectopic expression of species-specific p53 mutants in the syngeneic mouse and human LC cells led to increased cell migration and high expression of ST6GalNAc-I, STn, and MUC5AC. Immunoprecipitation of MUC5AC in the ectopically expressing p53R175H cells exhibited higher affinity towards STn. In addition, ST6GalNAc-I knockout (KO) cells also showed decreased migration, possibly due to reduced glycosylation of MUC5AC as observed by low STn on the glycoprotein. Interestingly, ST6GalNAc-I KO cells injected mice developed less liver metastasis (P=0.01) compared to controls, while co-localization of MUC5AC and STn was observed in the liver metastatic tissues of control mice. Collectively, our findings support the hypothesis that mutant p53R175H mediates ST6GalNAc-I expression, leading to the sialyation of MUC5AC, and thus contribute to LC liver metastasis