cmUML - A UML based framework for formal specification of concurrent, reactive systems

Complex software systems possess concurrent and reactive behaviors requiring precise specifications prior to development. Lamport's transition axiom method is a formal specification method which combines axiomatic and operational approaches. On the other hand Unified Modeling Language (UML), a de facto industry standard visual language, lacks suitable constructs and semantics regarding concurrency aspects. Though UML includes action semantics, its higher level constructs and object semantics are inconsistent. Motivated by Lamport's approach, this paper proposes a UML based specification framework 'cmUML' ('cm' for concurrent modules) for formal specification of concurrent, reactive systems without object level diagrams and OCL. The framework integrates higher level diagrams of UML and addresses various concurrency issues including exception handling. It combines UML-RT and UML// SPT profile as the latter defines a core package for concurrency and causality. Further the framework includes the characteristic safety and liveness aspects of concurrent systems. The proposed framework is in contrast with existing approaches based on low level primitives (semaphore, monitors). The paper includes several specification examples validating the proposed framework

Colorectal Cancer Profile in a Tertiary Care Centre, Bangalore, India

Introduction: Colorectal cancers are a common disease of oncological practice. A raising incidence is seen in Asian population. It is one of the cancers where screening and early diagnosis are possible. Very few articles are there about the cancer scenario in India. A study of the disease profile helps in screening, early diagnosis and management of the disease in developing countries. Aim: To study the cancer presentation in our population which can help in developing strategies for better control of disease. Material and Methods: Medical records of 171 patients registered at Kidwai Hospital from 2010 to 2012 were retrospectively reviewed. Data including age at presentation, sex, location of the cancer and stage at presentation were analyzed. Results: The male to female ratio was 1.26:1 in rectal cancer. In colon cancer the ratio was 1:1.3. The mean age at presentation was 47 years in males and 51 years in females in colorectal cancers together. Thirty eight percent of the patients were less than 45 years old. Eighty percent of the cases were rectal cancers. In 71% of rectal cancers the growth was located within 5cm from anal verge (AV). Stage III was the commonest stage of presentation. Abdominoperineal resection (APR) was the commonest surgical procedure done. Inoperability was highest with lower rectal cancer. Conclusion: Younger age at presentation, low lying rectal cancers and advanced stage at presentation were observed in our study group which includes predominantly rural population. Rectal cancers are the most common cancers referred among colorectal cancers. Screening for colorectal cancers and early evaluation of symptomatic cases need to be encouraged. Patients should be educated regarding this. Screening strategies, etiopathogenesis and genetic abnormalities in colorectal cancer patients need to be defined in developing countries

Enabling Machine Learning Across Heterogeneous Sensor Networks with Graph Autoencoders

Machine Learning (ML) has been applied to enable many life-assisting appli-cations, such as abnormality detection and emdergency request for the soli-tary elderly. However, in most cases machine learning algorithms depend on the layout of the target Internet of Things (IoT) sensor network. Hence, to deploy an application across Heterogeneous Sensor Networks (HSNs), i.e. sensor networks with different sensors type or layouts, it is required to repeat the process of data collection and ML algorithm training. In this paper, we introduce a novel framework leveraging deep learning for graphs to enable using the same activity recognition system across HSNs deployed in differ-ent smart homes. Using our framework, we were able to transfer activity classifiers trained with activity labels on a source HSN to a target HSN, reaching about 75% of the baseline accuracy on the target HSN without us-ing target activity labels. Moreover, our model can quickly adapt to unseen sensor layouts, which makes it highly suitable for the gradual deployment of real-world ML-based applications. In addition, we show that our framework is resilient to suboptimal graph representations of HSNs

Tuberculosis: an overview of current literature on types, diagnosis and drug therapy

Tuberculosis (TB) is an airborne infectious disease caused by organisms of the Mycobacterium tuberculosis complex. It is a global problem and increases in case rates are occurring not only in the developing countries of the world but also in several industrialized nations. There has also been an alarming increase in the number and proportion of cases caused by strains of Mycobacterium tuberculosis that are resistant to multiple first-line drugs. The increase in multiple-drug resistant tuberculosis has re-taught physicians about the importance of pursuing and ensuring treatment until cure. In many low-income and middle-income countries, TB continues to be a major cause of morbidity and mortality, and drug-resistant TB is a major concern in many settings. This article offers an overview of types, diagnosis and management of TB

FITsense: employing multi-modal sensors in smart homes to predict falls.

As people live longer, the increasing average age of the population places additional strains on our health and social services. There are widely recognised benefits to both the individual and society from supporting people to live independently for longer in their own homes. However, falls in particular have been found to be a leading cause of the elderly moving into care, and yet surprisingly preventative approaches are not in place; fall detection and rehabilitation are too late. In this paper we present FITsense, which is building a Smart Home environment to identify increased risk of falls for residents, and so allow timely interventions before falls occurs. An ambient sensor network, installed in the Smart Home, identifies low level events taking place which is analysed to generate a resident’s profile of activities of daily living (ADLs). These ADL profiles are compared to both the resident’s typical profile and to known “risky” profiles to allow evidence-driven intervention recommendations. Human activity recognition to identify ADLs from sensor data is a key challenge. Here we compare a windowing-based and a sequence-based event representation on four existing datasets. We find that windowing works well, giving consistent performance but may lack sufficient granularity for more complex multi-part activities

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

BACKGROUND: The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A) tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A) tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. RESULTS: By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (approximately 17%) showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. CONCLUSION: An extensive protein network was revealed for plant polyadenylation machinery, in which all predicted proteins were found to be connecting to the complex. The gene expression profiles are indicative that specialized sub-complexes may be formed to carry out targeted processing of mRNA in different developmental stages and tissue types. These results offer a roadmap for further functional characterizations of the protein factors, and for building models when testing the genetic contributions of these genes in plant growth and development

IAPAR 8 - Rio Negro, nova cultivar de feijoeiro

After five cycles of selection under  field conditions, a new bean (Phaseolus vulgaris L.) cultivar was obtained, ‘IAPAR 8 - Rio Negro', which has black seed coat, upright growth habit, 92 days from emergence to maturity, and field resistance to all physiological races of the fungus Colletotrichum lindemuthianum known to the moment. Its 1000 seeds weight is around 210 g, it shows wide adaptation, and yields 3000 kg/ha under good edaphic and climatic conditions. Yield data of the new cultivar, obtained from three different localities in the state of Paraná, Brazil, and its main characteristics are presented.Após cinco ciclos de seleção em condições de campo, foi criada a nova cultivar de feijoeiro (Phaseolus vulgaris L.) 'IAPAR 8 - Rio Negro', de tegumento de cor preta, de porte ereto, de ciclo médio de 92 dias, e que apresenta resistência de campo a todas raças fisiológicas do fungo Colletotrichum lindemuthianum conhecidas até o momento. Seu peso de mil sementes é em torno de 210 gramas, tem ampla adaptação e atinge produtividade de até 3.000 kg/ha em boas condições edafoclimáticas. Resultados de produção da nova variedade, obtidas em três diferentes locais do Estado do Paraná e suas principais características, são apresentados

A Polyadenylation Factor Subunit Implicated in Regulating Oxidative Signaling in Arabidopsis thaliana

BACKGROUND: Plants respond to many unfavorable environmental conditions via signaling mediated by altered levels of various reactive oxygen species (ROS). To gain additional insight into oxidative signaling responses, Arabidopsis mutants that exhibited tolerance to oxidative stress were isolated. We describe herein the isolation and characterization of one such mutant, oxt6. METHODOLOGY/PRINCIPAL FINDINGS: The oxt6 mutation is due to the disruption of a complex gene (At1g30460) that encodes the Arabidopsis ortholog of the 30-kD subunit of the cleavage and polyadenylation specificity factor (CPSF30) as well as a larger, related 65-kD protein. Expression of mRNAs encoding Arabidopsis CPSF30 alone was able to restore wild-type growth and stress susceptibility to the oxt6 mutant. Transcriptional profiling and single gene expression studies show elevated constitutive expression of a subset of genes that encode proteins containing thioredoxin- and glutaredoxin-related domains in the oxt6 mutant, suggesting that stress can be ameliorated by these gene classes. Bulk poly(A) tail length was not seemingly affected in the oxt6 mutant, but poly(A) site selection was different, indicating a subtle effect on polyadenylation in the mutant. CONCLUSIONS/SIGNIFICANCE: These results implicate the Arabidopsis CPSF30 protein in the posttranscriptional control of the responses of plants to stress, and in particular to the expression of a set of genes that suffices to confer tolerance to oxidative stress

In Vitro Downregulation of Matrix Metalloproteinase-9 in Rat Glial Cells by CCR5 Antagonist Maraviroc: Therapeutic Implication for HIV Brain Infection

BACKGROUND: Matrix metalloproteinases (MMPs) released by glial cells are important mediators of neuroinflammation and neurologic damage in HIV infection. The use of antiretroviral drugs able to combat the detrimental effect of chronic inflammation and target the exaggerated MMP activity might represent an attractive therapeutic challenge. Recent studies suggest that CCR5 antagonist maraviroc (MVC) exerts immunomodulant and anti-inflammatory activity beyond its anti-HIV properties. We investigated the in vitro effect of MVC on the activity of MMPs in astrocyte and microglia cultures. METHODOLOGY/PRINCIPAL FINDINGS: Primary cultures of rat astrocytes and microglia were activated by exposure to phorbol myristate acetate (PMA) or lypopolysaccharide (LPS) and treated in vitro with MVC. Culture supernatants were subjected to gelatin zymography and quantitative determination of MMP-9 and MMP-2 was done by computerized scanning densitometry. MMP-9 levels were significantly elevated in culture supernatants from both LPS- and PMA-activated astrocytes and microglia in comparison to controls. The treatment with MVC significantly inhibited in a dose-dependent manner the levels and expression of MMP-9 in PMA-activated astrocytes (p<0,05) and, to a lesser extent, in PMA-activated microglia. By contrast, levels of MMP-2 did not significantly change, although a tendency to decrease was seen in PMA-activated astrocytes after treatment with MVC. The inhibition of levels and expression of MMP-9 in PMA-activated glial cells did not depend on cytotoxic effects of MVC. No inhibition of MMP-9 and MMP-2 were found in both LPS-activated astrocytes and microglia. CONCLUSIONS: The present in vitro study suggests that CCR5 antagonist compounds, through their ability to inhibit MMP-9 expression and levels, might have a great potential for the treatment of HIV-associated neurologic damage