Cyber-physical Systems (CPS) Security: State of the Art and Research Opportunities for Information Systems Academics

Attacks on cyber-physical systems (CPS) continue to grow in frequency. However, cybersecurity academics and practitioners have so far focused primarily on computer systems and networks rather than CPS. Given the alarming frequency with which cybercriminals attack CPS and the unique cyber-physical relationship in CPS, we propose that CPS security needs go beyond what purely computer and network security requires. Thus, we require more focused research on cybersecurity based on the cyber-physical relationship between various CPS components. In this paper, we stock of the current state of CPS security and identify research opportunities for information systems (IS) academics

To find the efficacy of crude extract from plants on germination of seeds

Germination is the growth of an embryonic plant contained within a seed; it results in the formation of the seedling. The seed of a higher plant is a small package produced in a fruit or cone after the union of male and female sex cells. All fully developed seeds contain an embryo and, in most plant species some store of food reserves, wrapped in a seed coat. Some plants produce varying numbers of seeds that lack embryos, these are called empty seeds, and never germinate. Most seeds go through a period of quiescence where there is no active growth; during this time the seed can be safely transported to a new location and/or survive adverse climate conditions until circumstances are favorable for growth. Quiescent seeds are ripe seeds that do not germinate because they are subject to external environmental conditions that prevent the initiation of metabolic processes and cell growth. Under favorable conditions, the seed begins to germinate and the embryonic tissues resume growth. In the present study, research was done to find the effect of crude extract of plants on germination of seeds. The plants which we have chosen may show the positive or negative effect on the germination of seeds. This has some importance in the rain fed areas. Even the specific plant extract soaked and sow in land may helpful to tolerate the drought conditions. Also study is helpful to agriculture or agricultural industry. It helps to find out the anti sprouting property of the plants. However, further work is needed to improve this method

Forecasting of Engine Performance for Gasoline-Ethanol Blends using Machine Learning

The incorporation of alternative fuels in the automotive domain has brought a new paradigm to tackle the environmental and energy crises. Therefore, it is of interest to test and forecast engine performance with blended fuels. This paper presents an experimental study on gasoline-ethanol blends to test and forecast engine behavior due to changes in the fuel. This study employed a machine learning (ML) technique called TOPSIS to forecast the performance of a slightly higher blend fuelled engine based on experimental data obtained from the same engine running on 0% ethanol blend (E0) and E10 fuels under full load conditions. The engine performance predictions of this ML model were validated for 15% ethanol blend (E15) and further used to predict the engine performance of 20% ethanol blend fuel. The prediction R2 score for the ML model was found to be greater than 0.95 and the MAPE range was 1% to 5% for all observed engine performance attributes. Thus, this paper presents the potential of TOPSIS methodology-based ML predictions on blended fuel engine performance to shorten the testing efforts of blended fuel engines. This methodology may help to faster incorporate higher blended fuels in the automotive sector

Forecasting of Engine Performance for Gasoline-Ethanol Blends using Machine Learning

The incorporation of alternative fuels in the automotive domain has brought a new paradigm to tackle the environmental and energy crises. Therefore, it is of interest to test and forecast engine performance with blended fuels. This paper presents an experimental study on gasoline-ethanol blends to test and forecast engine behavior due to changes in the fuel. This study employed a machine learning (ML) technique called TOPSIS to forecast the performance of a slightly higher blend fuelled engine based on experimental data obtained from the same engine running on 0% ethanol blend (E0) and E10 fuels under full load conditions. The engine performance predictions of this ML model were validated for 15% ethanol blend (E15) and further used to predict the engine performance of 20% ethanol blend fuel. The prediction R2 score for the ML model was found to be greater than 0.95 and the MAPE range was 1% to 5% for all observed engine performance attributes. Thus, this paper presents the potential of TOPSIS methodology-based ML predictions on blended fuel engine performance to shorten the testing efforts of blended fuel engines. This methodology may help to faster incorporate higher blended fuels in the automotive sector

Correlation between prostate specific antigen and prostate volume with disease symptom severity assessed by international prostate symptom score

Background: Benign prostatic hyperplasia (BPH) is clinically defined as prostate adenoma, resulting in bladder outlet obstruction (BOO), which may eventually harm the bladder and even kidneys. For differential diagnosis of male LUTS, uroflowmetry can be used together with non-invasive ultrasound to ascertain the flow rate and IPP. PSA is also an important indicator for differential diagnosis. International prostate symptoms score (IPSS) is used to assess the severity of the symptoms for clinical BPH. There is also a recommendation to consider the quality of life (QoL) index, where a QoL score of ≥3 is considered as worrisome. Methods: This was a retro-prospective study based on secondary and primary data collection and analysis, pertaining to BPH patients who visited the study site previously as well as those who are coming for regular follow-up since 2019. Patient enrolment was done at a teaching hospital Shree Krishna Hospital affiliated to the Pramukh Swami Medical College, Bhaikaka University, Karamsad. About 100 patients presenting with lower urinary tract symptoms (LUTS) and histo-pathologically proven cases of BPH were enrolled to pursue research objectives. All patients were followed up to a period of 3-months after initiating the treatment and disease severity through IPSS and quality of life upon completion of treatment were also assessed. Results: PSA is also an important indicator for differential diagnosis, which is generally less than 1 μg/l in patients in absence of clinically confirmed BPH. In our study, mean prostate volume was reported to be 43.46±19.35 cc. A positive correlation was observed between prostate volume and serum PSA with disease severity. Conclusions: Our study evaluated the IPSS to predict the disease severity and correlated it with quality of life, prostate volume and serum PSA. Our findings were in line with currently available evidences, and suggested that QoL, prostate volume and serum PSA are better predictors of disease severity, IPSS

CD1b Tetramers Bind αβ\alpha \beta T Cell Receptors to Identify a Mycobacterial Glycolipid-Reactive T Cell Repertoire in Humans

Microbial lipids activate T cells by binding directly to CD1 and T cell receptors (TCRs) or by indirect effects on antigen-presenting cells involving induction of lipid autoantigens, CD1 transcription, or cytokine release. To distinguish among direct and indirect mechanisms, we developed fluorescent human CD1b tetramers and measured T cell staining. CD1b tetramer staining of T cells requires glucose monomycolate (GMM) antigens, is specific for TCR structure, and is blocked by a recombinant clonotypic TCR comprised of TRAV17 and TRBV4-1, proving that CD1b-glycolipid complexes bind the TCR. GMM-loaded tetramers brightly stain a small subpopulation of blood-derived cells from humans infected with Mycobacterium tuberculosis, providing direct detection of a CD1b-reactive T cell repertoire. Polyclonal T cells from patients sorted with tetramers are activated by GMM antigens presented by CD1b. Whereas prior studies emphasized CD8$^+$ and CD4$^-$CD8$^-$ CD1b-restricted clones, CD1b tetramer-based studies show that nearly all cells express the CD4 co-receptor. These findings prove a cognate mechanism whereby CD1b-glycolipid complexes bind to TCRs. CD1b tetramers detect a natural CD1b-restricted T cell repertoire ex vivo with unexpected features, opening a new investigative path to study the human CD1 system

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London