Effect of Industrial Effluent on the Growth of Marine Diatom, Chaetoceros simplex (Ostenfeld, 1901)

The marine centric diatom,Chaetoceros simplex (Ostenfeld, 1901) was exposed to five different concentrations of industrial effluent for 96 hrs to investigate the effect on growth. The physico-chemical parameters viz. colour, odour, temperature, salinity, dissolved oxygen, turbidity, pH, alkalinity, hardness, ammonia, nitrite, nitrate, inorganic phosphate, total phosphorous, reactive  silicate, calcium and magnesium were estimated in the effluent. The Ammonia  (326 μg. L-1), Nitrite (19.53 μg. L-1) and Nitrate (471.4 μg. L-1) were observed at higher levels. About 50% of the cell density of C. simplex reached a lesser dilutions of effluent viz. 1:625 and 1:1250 than the control. The highest cell density (14.3 × 104 cell ml-1) was recorded in 1:10000 diluted effluent followed by control and the lowest cell density was observed in 1:625 diluted effluents. From the results, it is evidenced that the lower volume of effluent discharge into higher volume of water could not affect the growth rate of phytoplankton. It is more important that to reduce the effect of pollution and environmental sustainability. @JASEMJ. Appl. Sci. Environ. Manage. December, 2010, Vol. 14 (4) 35 - 3

Security Enhancement in Surveillance Cloud Using Machine Learning Techniques

Most industries are now switching from traditional modes to cloud environments and cloud-based services. It is essential to create a secure environment for the cloud space in order to provide consumers with a safe and protected environment for cloud-based transactions. Here, we discuss the suggested approaches for creating a reliable and safe environment for a surveillance cloud. When assessing the security of vital locations, surveillance data is crucial. We are implementing machine learning methods to improve cloud security to more precisely classify image pixels, we make use of Support Vector Machines (SVM) and Fuzzy C-means Clustering (FCM). We also extend the conventional two-tiered design by adding a third level, the CloudSec module, to lower the risk of potential disclosure of surveillance data.In our work we  evaluates how well our proposed model (FCM-SVM) performed against contemporary models like ANN, KNN, SVD, and Naive Bayes. Comparing our model to other cutting-edge models, we found that it performed better, with an average accuracy of 94.4%

Design, Implementation and Performance Analysis of Highly Efficient Algorithms for AES Key Retrieval in Access-driven Cache-based Side Channel Attacks

Leakage of information between two processes sharing the same processor cache has been exploited in many novel approaches targeting various cryptographic algorithms. The software implementation of AES is an especially attractive target since it makes extensive use of cache-resident table lookups. We consider two attack scenarios where either the plaintext or ciphertext is known. We employ a multi-threaded spy process and ensure that each time slice provided to the victim (running AES) is small enough so that it makes a very limited number of table accesses. We design and implement a suite of algorithms to deduce the 128-bit AES key using as input the set of (unordered) cache line numbers captured by the spy threads in an access-driven cache-based side channel attack. Our algorithms are expressed using simple relational algebraic operations and run in under a minute. Above all, our attack is highly efficient - we demonstrate recovery of the full AES key given only about 6-7 blocks of plaintext or ciphertext (theoretically even a single block would suffice). This is a substantial improvement over previous cache-based side channel attacks that require between 100 and a million encryptions. Moreover, our attack supports varying cache hit/miss observation granularities, does not need frequent interruptions of the victim and will work even if the victim makes up to 60 cache accesses before being interrupted. Finally, we develop analytic models to estimate the number of encryptions/decryptions required as a function of access granularity and compare model results with those obtained from our experiment

S-Box Implementation of AES is NOT side-channel resistant

Several successful cache-based attacks have provided strong impetus for developing side channel resistant software implementations of AES. One of the best-known countermeasures - use of a minimalist 256-byte look-up table - has been employed in the latest (assembly language) versions. Software and hardware prefetching and out-of-order execution in modern processors have served to further shrink the attack surface. Despite these odds, we devise and implement two strategies to retrieve the complete AES key. The first uses adaptively chosen plaintext and random plaintext in a 2-round attack. The second strategy employs only about 50 blocks of random plaintext in a novel single round attack. The attack can be extended to spying on table accesses during decryption in a ciphertext-only attack. We also present an analytical model to explain the effect of false positives and false negatives and capture various practical tradeoffs involving number of blocks of plaintext, offline computation time for key retrieval and success probability

Effect of covid-19 virus on reducing GHG emission and increasing energy generated by renewable energy sources: a brief study in Malaysian context

Coronavirus 2019 (COVID-19) has globally affected the human mortality rate and economic history of the modern world. According to the World Health Organization, COVID-19 has caused a severe threat to the health of the vulnerable groups, notably the elderly. There is still some disagreements regarding the source of the virus and its intermediate host. However, the spread of this disease has caused most countries to enforce strict curfew laws and close most industrial and recreational centres. This study aims to show the potential positive effects of COVID-19 on the environment and the increase of renewable energy generation in Malaysia. To prevent the spread of this disease, Malaysia enacted the Movement Control Order (MCO) law in March 2020. Implementation of this law led to a reduction in environmental pollution, especially air pollution, in this country. The greenhouse gases (GHG) emission , which was 8 Mt CO2 eq. from January 2020 to March 2020, reduced to <1 Mt CO2 eq. for April and May. The reduction of GHG emission and pollutant gases allowed more sunlight to reach photovoltaic panels, hence increasing the renewable energy generation

A loss-of-function homozygous mutation in DDX59 implicates a conserved DEAD-box RNA helicase in nervous system development and function

We report on a homozygous frameshift deletion in DDX59 (c.185del: p.Phe62fs*13) in a family presenting with orofaciodigital syndrome phenotype associated with a broad neurological involvement characterized by microcephaly, intellectual disability, epilepsy, and white matter signal abnormalities associated with cortical and subcortical ischemic events. DDX59 encodes a DEAD-box RNA helicase and its role in brain function and neurological diseases is unclear. We showed a reduction of mutant cDNA and perturbation of SHH signaling from patient-derived cell lines; furthermore, analysis of human brain gene expression provides evidence that DDX59 is enriched in oligodendrocytes and might act within pathways of leukoencephalopathies-associated genes. We also characterized the neuronal phenotype of the Drosophila model using mutant mahe, the homolog of human DDX59, and showed that mahe loss-of-function mutant embryos exhibit impaired development of peripheral and central nervous system. Taken together, our results support a conserved role of this DEAD-box RNA helicase in neurological function

A loss-of-function homozygous mutation in DDX59 implicates a conserved DEAD-box RNA helicase in nervous system development and function.

We report on a homozygous frameshift deletion in DDX59 (c.185del: p.Phe62fs*13) in a family presenting with orofaciodigital syndrome phenotype associated with a broad neurological involvement characterized by microcephaly, intellectual disability, epilepsy, and white matter signal abnormalities associated with cortical and subcortical ischemic events. DDX59 encodes a DEAD-box RNA helicase and its role in brain function and neurological diseases is unclear. We showed a reduction of mutant cDNA and perturbation of SHH signaling from patient-derived cell lines; furthermore, analysis of human brain gene expression provides evidence that DDX59 is enriched in oligodendrocytes and might act within pathways of leukoencephalopathies-associated genes. We also characterized the neuronal phenotype of the Drosophila model using mutant mahe, the homolog of human DDX59, and showed that mahe loss-of-function mutant embryos exhibit impaired development of peripheral and central nervous system. Taken together, our results support a conserved role of this DEAD-box RNA helicase in neurological function

A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)

Background: The Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC, http://www.pcabc.upmc.edu) is one of the first major project-based initiatives stemming from the Pennsylvania Cancer Alliance that was funded for four years by the Department of Health of the Commonwealth of Pennsylvania. The objective of this was to initiate a prototype biorepository and bioinformatics infrastructure with a robust data warehouse by developing a statewide data model (1) for bioinformatics and a repository of serum and tissue samples; (2) a data model for biomarker data storage; and (3) a public access website for disseminating research results and bioinformatics tools. The members of the Consortium cooperate closely, exploring the opportunity for sharing clinical, genomic and other bioinformatics data on patient samples in oncology, for the purpose of developing collaborative research programs across cancer research institutions in Pennsylvania. The Consortium’s intention was to establish a virtual repository of many clinical specimens residing in various centers across the state, in order to make them available for research. One of our primary goals was to facilitate the identification of cancer specific biomarkers and encourage collaborative research efforts among the participating centers.Methods: The PCABC has developed unique partnerships so that every region of the state can effectively contribute and participate. It includes over 80 individuals from 14 organizations, and plans to expand to partners outside the State. This has created a network of researchers, clinicians, bioinformaticians, cancer registrars, program directors, and executives from academic and community health systems, as well as external corporate partners - all working together to accomplish a common mission. The various sub-committees have developed a common IRB protocol template, common data elements for standardizing data collections for three organ sites, intellectual property/tech transfer agreements, and material transfer agreements that have been approved by each of the member institutions. This was the foundational work that has led to the development of a centralized data warehouse that has met each of the institutions’ IRB/HIPAA standards.Results: Currently, this “virtual biorepository” has over 58,000 annotated samples from 11,467 cancer patients available for research purposes. The clinical annotation of tissue samples is either done manually over the internet or semiautomated batch modes through mapping of local data elements with PCABC common data elements. The database currently holds information on 7188 cases (associated with 9278 specimens and 46,666 annotated blocks and blood samples) of prostate cancer, 2736 cases (associated with 3796 specimens and 9336 annotated blocks and blood samples) of breast cancer and 1543 cases (including 1334 specimens and 2671 annotated blocks and blood samples) of melanoma. These numbers continue to grow, and plans to integrate new tumor sites are in progress. Furthermore, the group has also developed a central web-based tool that allows investigators to share their translational (genomics/proteomics) experiment data on research evaluating potential biomarkers via a central location on the Consortium’s web site.Conclusions: The technological achievements and the statewide informatics infrastructure that have been established by the Consortium will enable robust and efficient studies of biomarkers and their relevance to the clinical course of cancer. Studies resulting from the creation of the Consortium may allow for better classification of cancer types, more accurate assessment of disease prognosis, a better ability to identify the most appropriate individuals for clinical trial participation, and better surrogate markers of disease progression and/or response to therapy