The value of a "free" customer

We study the problem of a firm that faces asymmetric information about the productivity of its potential workers. In our framework, a worker’s productivity is either assigned by nature at birth, or determined by an unobservable initial action of the worker that has persistent effects over time. We provide a characterization of the optimal dynamic compensation scheme that attracts only high productivity workers: consumption –regardless of time period– is ranked according to likelihood ratios of output histories, and the inverse of the marginal utility of consumption satisfies the martingale property derived in Rogerson (1985). However, in the case of i.i.d. output and square root utility we show that, contrary to the features of the optimal contract for a repeated moral hazard problem, the level and the variance of consumption are negatively correlated, due to the influence of early luck into future compensation. Moreover, in this example long-term inequality is lower under persistent private informationCustomer lifetime value, CRM, Dynamic programming, GMM Estimation

A Cyber -Physical System for Industrial Air Pollution Monitoring using Raspberry Pi

In this paper the proposed system will focus on the monitoring of air pollutants concentration with the help of combination of Internet of things with wireless sensor networks. The analysis of air quality can be done by calculating air quality index. This information will be displayed on the webpage via internet in real time. By the combination of internet of things and wireless sensor networks for purpose of air pollution monitoring it becomes easy to keep the air quality data updated in real time. Also the system is cost effective which make its installation possible in various areas. The system existing before was based on microcontroller based toxic gas detecting and alerting system and the developing system will have a complete monitoring system which is IOT based. Also the information will be directly sent to the internet from system; no need of computer for transmission purpose which reduces the cost further. The main objective of this system is to monitor air pollution by using internet of things application. Also to obtain cost effective system that will help to keep track of concentration of pollutants in air and find effect of concentration of pollutants on air in terms of air quality index to achieve real time monitoring by continuously updating the data on webpage via internet

Ethnobotanical Studies of Nubra Valley - A Cold Arid Zone of Himalaya

An attempt has been made to explore traditional medicinal knowledge of Nubra valley, the cold arid zone of Himalaya. Ethnobotanical information were gathered through several visits, group discussions and cross checked with local medicine men. The study identified 65 plant species belonging to 30 families have been used to cure various diseases and ailments. Maximum number of species was recorded to be used in kidney complaints (14 spp.), cold & cough (13 spp.) and fever (11 spp.). Leaves of 27 species; whole plant extract of 20 species and root/bulb of 19 species were mostly used. Juice, raw items, paste and decoction of plant species were the common method of usage. A large number of ethnic groups with varied culture inhabiting the remote and isolated valleys of Ladakh offer a great scope for ethnobotanical studies. Over exploitation of medicinal herbs can lead to the local extinction of the valuable herbs indicating an urgent need to draw up the necessary plans for medicinal plant utilization and conservation

Formulation and standardization of homoeopathic mother tincture of Cinnamomum zeylanicum

Alcoholic preparation of drugs in Homoeopathy, are called as tincture. The mother tincture of Cinnamomum zeylanicum was prepared by 100 g of coarse powder (40 mess) of Cinnamomum zeylanicum was macerated with 95 v/v % of alcohol to make 1000 ml of mother tincture for eight days (drug strength 1/10). It was shaken occasionally, and filtered. The mother tincture was standardized by using various physical, chemical and chromatographic parameters.Keywords: Cinnamomum zeylanicum, mother tinctur

Divergence of chikungunya virus in India: Tale of two cities

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DEVELOPMENT AND CHARACTERIZATION OF SRM MICROSPHERES OF REPAGLINIDE

The aim of current work to develop and evaluate sustained release mucoadhesive (SRM) microspheres of Repaglinide using emulsification solvent evaporation technique. Effects of formulation variables i.e. polymer concentration and phase volume ratio on particle size, % mucoadhesion and drug release were investigated in this study. Scanning electron microscopy of microspheres with maximum drug content (Formulation CH1:8) demonstrated smooth surface spherical particles with mean diameter of 64.78 ± 3.26 μm. The mean Particle size, % drug loading and mucoadhesion were found to vary by changing the formulation variables. Microspheres size was significantly increased as increasing the polymer concentration in the aqueous phase while size of microspheres decrease as increase in volume of continuous phase. Decrease in size of microspheres leads to decrease in mucoadhesion time, % drug loading and faster the drug release. It can be concluded that the present mucoadhesive microspheres can be an ideal system to deliver the Repaglinide in sustained release manner for management of Type II Diabetes Mellitus

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Objectives: Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. Setting: A regional cancer centre in Australia. Participants: Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data. Primary and secondary outcome measures: Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC). Results: The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours. Conclusions: Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems

Empowering sustainable manufacturing: unleashing digital innovation in spool fabrication industries

In industrial landscapes, spool fabrication industries play a crucial role in the successful completion of numerous industrial projects by providing prefabricated modules. However, the implementation of digitalized sustainable practices in spool fabrication industries is progressing slowly and is still in its embryonic stage due to several challenges. To implement digitalized sustainable manufacturing (SM), digital technologies such as Internet of Things, Cloud computing, Big data analytics, Cyber-physical systems, Augmented reality, Virtual reality, and Machine learning are required in the context of sustainability. The scope of the present study entails prioritization of the enablers that promote the implementation of digitalized sustainable practices in spool fabrication industries using the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF-SWARA) method integrated with Triangular Fuzzy Bonferroni Mean (TFBM). The enablers are identified through a systematic literature review and are validated by a team of seven experts through a questionnaire survey. Then the finally identified enablers are analyzed by the IMF-SWARA and TFBM integrated approach. The results indicate that the most significant enablers are management support, leadership, governmental policies and regulations to implement digitalized SM. The study provides a comprehensive analysis of digital SM enablers in the spool fabrication industry and offers guidelines for the transformation of conventional systems into digitalized SM practices

Importance of EMT Factor ZEB1 in cDC1 “MutuDC Line” Mediated Induction of Th1 Immune Response

The role of Epithelial to Mesenchymal Transition (EMT) factor Zeb1 is well defined in metastasis and cancer progression but it's importance in dendritic cells (DCs) is unexplored until now. For the first time we report here that Zeb1 controls immunogenic responses of CD8α+ conventional Type-I (cDC1) DCs. We found that ZEB1 expression increases significantly after TLR9 stimulation and its depletion impairs activation, co-stimulation and secretion of important cytokines like IL-6, IL-10 and IL-12 in cDC1 MutuDC line. We further confirmed our findings in primary cDC1 DCs derived from bone marrow. Co-culture of these Zeb1 knock down (KD) DCs with OT-II CD4+ T helper cells skewed their differentiation toward Th2 subtype. Moreover, adoptive transfer of activated Zeb1 KD DCs cleared intestinal worms in helminth infected mice by increasing Th2 responses in vivo. Integrative genomic analysis showed Zeb1 as an activator of immune response genes in cDC1 MutuDCs as compared to other pathway genes. In addition, differentially regulated genes in Zeb1 KD RNA-seq showed significant enrichment of Th2 activation pathways supporting our in vitro findings. Mechanistically, we showed that decreased IL-12 secreted by Zeb1 KD DCs is the plausible mechanism for increased Th2 differentiation. Collectively our data demonstrate that Zeb1 could be targeted in DCs to modulate T-cell mediated adaptive immune responses