SURVIVAL OF THE FITTEST ‘ENTREPRENEURIAL’ B-SCHOOL

Everyday out of the blue, the MBA factories are conceiving and developing new strategies for survival, growth and dominance. Undoubtedly, it’s an age-old fact that recession or no recession, the Indian job market has always been bullish. In the present fragile economy, it becomes more relevant for the management varsities to have the 'locus of control' on multiplication and not addition, viz. entrepreneurship in lieu of the conventional one-to-one student’s placements. Its high time now that the B-schools should take initiatives towards grooming wealth creators rather than creating job seekers. They need to stop bragging and competing about the average salaries their students are commanding and start to teach and encourage them about the values of wealth creation and entrepreneurship. They should start celebrating their alumni of entrepreneurs and make them involved in the process of grooming new entrepreneurs of their students

Using hidden Markov models for iterative non-intrusive appliance monitoring

Non-intrusive appliance load monitoring is the process of breaking down a household’s total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances are iteratively separated from the aggregate load. Our approach does not require training data to be collected by sub-metering individual appliances. Instead, prior models of general appliance types are tuned to specific appliance instances using only signatures extracted from the aggregate load. The tuned appliance models are used to estimate each appliance’s load, which is subsequently subtracted from the aggregate load. We evaluate our approach using the REDD data set, and show that it can disaggregate 35% of a typical household’s total energy consumption to an accuracy of 83% by only disaggregating three of its highest energy consuming appliances

Intestine‐Specific Expression of Human Chimeric Intestinal Alkaline Phosphatase Attenuates Western Diet‐Induced Barrier Dysfunction and Glucose Intolerance

Intestinal epithelial cell derived alkaline phosphatase (IAP) dephosphorylates/detoxifies bacterial endotoxin lipopolysaccharide (LPS) in the gut lumen. We have earlier demonstrated that consumption of high‐fat high‐cholesterol containing western type‐diet (WD) significantly reduces IAP activity, increases intestinal permeability leading to increased plasma levels of LPS and glucose intolerance. Furthermore, oral supplementation with curcumin that increased IAP activity improved intestinal barrier function as well as glucose tolerance. To directly test the hypothesis that targeted increase in IAP would protect against WD‐induced metabolic consequences, we developed intestine‐specific IAP transgenic mice where expression of human chimeric IAP is under the control of intestine‐specific villin promoter. This chimeric human IAP contains domains from human IAP and human placental alkaline phosphatase, has a higher turnover number, narrower substrate specificity, and selectivity for bacterial LPS. Chimeric IAP was specifically and uniformly overexpressed in these IAP transgenic (IAPTg) mice along the entire length of the intestine. While IAP activity reduced from proximal P1 segment to distal P9 segment in wild‐type (WT) mice, this activity was maintained in the IAPTg mice. Dietary challenge with WD impaired glucose tolerance in WT mice and this intolerance was attenuated in IAPTg mice. Significant decrease in fecal zonulin, a marker for intestinal barrier dysfunction, in WD fed IAPTg mice and a corresponding decrease in translocation of orally administered nonabsorbable 4 kDa FITC dextran to plasma suggests that IAP overexpression improves intestinal barrier function. Thus, targeted increase in IAP activity represents a novel strategy to improve WD‐induced intestinal barrier dysfunction and glucose intolerance

Efficient State-Space Inference of Periodic Latent Force Models

Latent force models (LFM) are principled approaches to incorporating solutions to differential equations within non-parametric inference methods. Unfortunately, the development and application of LFMs can be inhibited by their computational cost, especially when closed-form solutions for the LFM are unavailable, as is the case in many real world problems where these latent forces exhibit periodic behaviour. Given this, we develop a new sparse representation of LFMs which considerably improves their computational efficiency, as well as broadening their applicability, in a principled way, to domains with periodic or near periodic latent forces. Our approach uses a linear basis model to approximate one generative model for each periodic force. We assume that the latent forces are generated from Gaussian process priors and develop a linear basis model which fully expresses these priors. We apply our approach to model the thermal dynamics of domestic buildings and show that it is effective at predicting day-ahead temperatures within the homes. We also apply our approach within queueing theory in which quasi-periodic arrival rates are modelled as latent forces. In both cases, we demonstrate that our approach can be implemented efficiently using state-space methods which encode the linear dynamic systems via LFMs. Further, we show that state estimates obtained using periodic latent force models can reduce the root mean squared error to 17% of that from non-periodic models and 27% of the nearest rival approach which is the resonator model.Comment: 61 pages, 13 figures, accepted for publication in JMLR. Updates from earlier version occur throughout article in response to JMLR review

Antimicrobial prescribing patterns in surgical inpatient of tertiary care hospital in Eastern India

Background: Antimicrobials form the cornerstone of prescriptions for treating infection. Surgical management cannot be possible without the use of antibiotics. Severity of infection, suspected spectrum of organisms and their sensitivity, co-morbidities of the patient, route of antibiotic administration are the important parameter to consider before selecting antibiotic.Methods: Cross-sectional, hospital based, descriptive study was conducted in the ward of Surgery Department of IQ City Medical college, Durgapur over a period of 1 year. The relevant information was entered into the pretested preformats (containing name, age, sex, diagnosis, ongoing treatment as recorded from patients’ prescription slips or CRFs) and analyzed. Necessary permission was granted by the Institutional Ethical Committee and written informed consent was obtained from the patients prior to collecting their prescription slips/CRF.Results: Commonest cause of hospitalization was cholelithiasis (318 (32.7%)). Antimicrobials were the most commonly prescribed drugs (1626 (31.6%)). Single antibiotic prescribing frequency are similar to two antibiotic prescribing (both 44%). Piperacillin+Tazobactum combination most commonly prescribe antibiotic.Conclusions: Beta lactam antibiotic specifically Piperacillin (ATC class: J01D) were the most commonly prescribed antibiotic agents both before and after surgical procedures

Medication use pattern and quality assessment of psychiatry outpatient department prescriptions of a tertiary care hospital

Background: Psychiatric illness is a major but often underreported health burden. The field of psychopharmacotherapy is continuously evolving therefore needs monitoring to prevent irrationality. In this setting, authors analyzed the prescribing pattern of psychotropic drugs while simultaneously monitoring prescription quality in a tertiary care teaching private hospital.Methods: A 6 month-prospective observational study was conducted in psychiatry out-patient department. Prescription pattern was analyzed using World Health Organization (WHO) drug use indicators. The quality of the prescriptions was assessed as per prescription writing guidelines issued by The Department of Health and Family Welfare, Government of West Bengal.Results: Of the 745 prescriptions analyzed, depression and psychosis constituted the bulk of diagnosed cases irrespective of any gender predominance. The average number of psychotropic drugs per prescription was 2.85±1.48. Antidepressants, sedative-hypnotic and anxiolytics are most commonly prescribed drugs. 37.58% of psychotropic drugs were given as fixed dose combination, most common being risperidone with trihexyphenidyl. Only 2.91% of the drugs were prescribed in generic name whereas 53.99% were enlisted in national essential medicine list 2015. Polypharmacy and therapeutic duplication were noted in 41% and 26.84 % of prescriptions and dose, duration and frequency were not mentioned in 2.68%, 53.02% and 19.00% of the prescription respectively.Conclusions: Use of psychotropic drugs follows closely with different treatment guideline, though routine uses of central anticholinergics with atypical antipsychotics are not recommended. Despite high utilization of NLEM, more generic prescribing, correct prescription dosing schedule, avoidance of polypharmacy and non-Judicious use of multivitamin FDCs may significantly improve treatment outcome

An apyrase from Mimosa pudica contains N5,N10-methenyl tetrahydrofolate and is stimulated by light

An apyrase (NTP/NDPase) implicated in the response of Mimosa pudica to stimuli, such as touch, has been cloned, sequenced and expressed in Escherichia coli. While purifying and characterizing this enzyme, it was observed that a chromophore is associated with it, having absorption in the ultraviolet-A/blue region of the spectrum. The absorbance maximum of the chromophore, purified from the enzyme complex by gel filtration and HPLC, is around 350 nm. The chromophore has been identified as N5,N10-methenyl tetrahydrofolate (MTHF) by comparing the excitation and emission spectra of synthetic MTHF and the isolated cofactor, and by reconstitution of the enzyme complex with synthetic MTHF. Upon excitation with light (350 nm), an increase of apyrase activity was observed in the purified or reconstituted holoenzyme but not in the apoenzyme. The wavelength dependence of the light stimulation matched well with the fluorescence excitation spectra of the cofactor, MTHF. Possible implications of the results for signal transduction in M. pudica have been discussed

Translation Of Telugu-Marathi and Vice-Versa using Rule Based Machine Translation

In todays digital world automated Machine Translation of one language to another has covered a long way to achieve different kinds of success stories. Whereas Babel Fish supports a good number of foreign languages and only Hindi from Indian languages, the Google Translator takes care of about 10 Indian languages. Though most of the Automated Machine Translation Systems are doing well but handling Indian languages needs a major care while handling the local proverbs/ idioms. Most of the Machine Translation system follows the direct translation approach while translating one Indian language to other. Our research at KMIT R&D Lab found that handling the local proverbs/idioms is not given enough attention by the earlier research work. This paper focuses on two of the majorly spoken Indian languages Marathi and Telugu, and translation between them. Handling proverbs and idioms of both the languages have been given a special care, and the research outcome shows a significant achievement in this direction.Comment: 13 pages, Fourth International Conference on Advances in Computing and Information Technology (ACITY 2014) Delhi, India - May 201

Anti-microbial sensitivity and resistance of organisms in blood-culture samples from prolonged fever cases: evidence from a tertiary care hospital in West Bengal, India

Background: Currently there is a rise in resistance to anti-microbials which is a matter of concern in treatment of systemic infections. Blood culture is considered “gold standard” in diagnosis of suspected systemic infection. The susceptibility to antibiotics thereafter determine the future course of treatment. The current study aims to find out the sensitivity and resistance pattern of the blood culture isolates.Methods: A cross-sectional study was performed on the blood culture samples sent within 24hours of admission of the adult patients reporting fever for 7 days or more with no history of consumption of any antibiotics within last month. Total 134 blood samples were analysed. The proportion of sensitivity and resistance to anti-bacterial agents was calculated among those samples which showed growth in the culture. Background information of the patients in terms of age, sex and religion were also noted.Results: Mean age of the patients was 39.33 (±12.19) years. Overall 47.76% were female patients and remaining were male. Among the Hindu patients majority were male while among Muslims majority were female. Of the total number of blood cultures examined 46.27% showed growth of bacteria. Staphylococcus aureus was the most frequently found bacteria isolated in cultures, followed by coagulase negative Staphylococcus and Pseudomonas. Of the frequently used antibiotics, higher sensitivity was seen with vancomycin, amikacin, netilmycin, imipenem, gentamicin. High resistance was observed in use of antibiotics like cefixime, amoxicillin-clavulanic acid and azithromycin.Conclusions: High level of resistance to several commonly used advanced antibiotics warrant judicial and evidence-based use of these drugs.