TRPV1: A Common Denominator Mediating Antinociceptive and Antiemetic Effects of Cannabinoids

The most common medicinal claims for cannabis are relief from chronic pain, stimulation of appetite, and as an antiemetic. However, the mechanisms by which cannabis reduces pain and prevents nausea and vomiting are not fully understood. Among more than 450 constituents in cannabis, the most abundant cannabinoids are Δ⁹-tetrahydrocannabinol (THC) and cannabidiol (CBD). Cannabinoids either directly or indirectly modulate ion channel function. Transient receptor potential vanilloid 1 (TRPV1) is an ion channel responsible for mediating several modalities of pain, and it is expressed in both the peripheral and the central pain pathways. Activation of TRPV1 in sensory neurons mediates nociception in the ascending pain pathway, while activation of TRPV1 in the central descending pain pathway, which involves the rostral ventral medulla (RVM) and the periaqueductal gray (PAG), mediates antinociception. TRPV1 channels are thought to be implicated in neuropathic/spontaneous pain perception in the setting of impaired descending antinociceptive control. Activation of TRPV1 also can cause the release of calcitonin gene-related peptide (CGRP) and other neuropeptides/neurotransmitters from the peripheral and central nerve terminals, including the vagal nerve terminal innervating the gut that forms central synapses at the nucleus tractus solitarius (NTS). One of the adverse effects of chronic cannabis use is the paradoxical cannabis-induced hyperemesis syndrome (HES), which is becoming more common, perhaps due to the wider availability of cannabis-containing products and the chronic use of products containing higher levels of cannabinoids. Although, the mechanism of HES is unknown, the effective treatment options include hot-water hydrotherapy and the topical application of capsaicin, both activate TRPV1 channels and may involve the vagal-NTS and area postrema (AP) nausea and vomiting pathway. In this review, we will delineate the activation of TRPV1 by cannabinoids and their role in the antinociceptive/nociceptive and antiemetic/emetic effects involving the peripheral, spinal, and supraspinal structures.     

Sensitivity analysis of nonlinear fractional order control systems with state delay

In this paper, we consider a class of nonlinear fractional order control system with delay in state variable. Existence and uniqueness of solution are shown by using method of steps. The sensitivity of the state and control with respect to the parameters of the system is shown. Finally, analytical results are substantiated by numerical examples.     

Investigation on the Effect of ECAP Routes on the Wear Behavior of AA2014

ECAP is an effective process to improve the mechanical strength and wear resistance along with mechanical and microstructural properties. AA2014 solutionized at 495 °C and aged at 195 °C was subjected to Equal Channel Angular Pressed (ECAP) through route A and B_c at room temperature. It was well proved that the mechanical strength increased due to ECAP in AA2014. In order to investigate their wear behavior after ECAP, dry sliding wear tests were conducted using vacuum tribometer at nominal loads of 10N and 30N with constant speed of 2 m/s for sliding distance of 2000 m. The co-efficient of friction and loss in volume were decreased after ECAP both in route A and B_c. The dominant wear mechanisms observed were adhesive, delamination and stick slip process. In addition to these wear mechanisms, abrasive wear also appeared along with transfer of iron particles from the counter surface to the AA2014 pin. Presence of black powder and oxide formation were observed using EDAX analysis on wear debris. Routes A and B_c showed similar wear mechanisms and characteristics which were better than in unECAPed specimens.     

Megalithic and Continuing Peninsular High-Tin Binary Bronzes: Possible Roots in Harappan Binary Bronze Usage?

This paper attempts to trace the development of an unusual and skilled class of alloys, of binary high-tin bronze (i.e. alloys of only copper with a higher percentage of tin), which are found from surprisingly early contexts from Indian antiquity. In particular, the deliberate use was made of binary beta bronze with around 22–24 % tin, specifically exploiting the properties of higher hot-forgability of bronze of this composition due to the formation of the high temperature beta intermetallic compound phase of 22.9 % tin. Quenching resulted in the retention of the beta phase, yielding a musical alloy with golden lustre and improved tensile strength as compared to the as-cast state. Examples of hot forged and quenched high-tin beta bronzes studied by the author from the South Indian Iron Age and megalithic cultures from Tamil Nadu and Maharashtra and Gandharan Grave Culture of Taxila are summarised here ranking amongst the earliest and most finely wrought such finds. There are technological and morphological similarities to surviving high-tin bronze crafts practices documented by the author in Kerala since 1990. Since the 1990’s she has also documented the making of high-tin delta bronze mirrors at Aranmula with a composition closer to the pure delta phase of 32.6 % tin, which instead exploited the specular properties this alloy while managing its brittleness. Although it is difficult to speculate about origins, a long standing practice of using binary tin–bronzes (i.e. only copper–tin alloys) can be detected going back to Harappan bronzes which also seem to be predominantly binary bronzes with not much lead added to them. Though most of these seem to be low-tin bronze, the presence of a couple with higher tin of about 20 % is also notable in terms of the above discussion.     

<Emphasis Type="Bold">Analysis of Spatio-temporal Characteristics and Regional Frequency of Droughts in the Southern Peninsula of India</Emphasis>

A detailed regional drought study is carried out in the southern peninsula of India to characterize the spatio-temporal nature of droughts and to predict the drought magnitudes for various probabilities in the homogeneous drought regions. The method of several random initializations of the cluster centres of the K-means algorithm is suggested for the identification of the initial regions in the context of drought regionalization, which is shown to perform better than the initialization from the Ward’s algorithm and the Ward’s algorithm itself. The peninsula is classified into seven spatially well-separated homogeneous drought regions. The robust L-moment framework is used for the regional frequency analysis of drought magnitudes computed using the standardized precipitation index. The Pearson type III is found to be appropriate for regional drought frequency analysis in six of the regions, while the robust Wakeby distribution is suggested for one region. Low magnitude droughts are frequent and dominant in the northern part of west coast, the north-eastern coast and its adjoining inland region, while high magnitude droughts are less in number and are experienced in semi-arid central part, southern part of western coast, south-eastern part and north-western inland region. The spatial maps of drought magnitudes indicate that at higher return periods (100 and 200 years) the south-eastern part of the peninsula is likely to encounter high magnitude droughts, while the central region is likely to experience the same at lower return periods (10 and 50 years). Hence these regions need to be given special importance in the drought mitigation planning activities.     

Understanding e‐Government portal use in rural India: role of demographic and personality characteristics

Electronic government (e‐Government) is one of the most important ways to bridge the digital divide in developing countries. We develop a model of e‐Government portal use. We use various individual characteristics, namely demographics and personality, as predictors of e‐Government portal use. Specifically, our predictors were (1) gender, age, income and education; (2) the Big Five personality characteristics, i.e. extraversion, neuroticism, conscientiousness, agreeableness and openness to experience; and (3) personal innovativeness with information technology. We conducted a field study in a village in India. We collected data from over 300 heads of household. We found support for our model, with most variables being significant and explaining 40% of the variance in e‐Government portal use.     

A comprehensive review on bioinspired solar photovoltaic cells

Researchers have derived inspiration from the biophotosynthetic structures in nature and have started to synthesize the modified bioinspired solar cells copying the evolved organic and inorganic material properties. One of the highlighted examples of bioinspired photo voltaic (PV) cells is the astonishing achievement of an increase in the absorption of integrated sunlight waves in unpatterned solar cells simulated from the wings of the butterfly. Further, deployment possibilities of incorporating flexible cells on flat or curved surfaces for optimizing performance are also under progress. This article mainly discusses the recent concepts of bioinspired solar cells at the research and development level with the prospects and challenges that lie ahead in the upcoming field of photovoltaic renewable energy cell technology. Different potential materials found suitable for bioinspired solar cells construction are reviewed with their particular challenges.     

An empirical study of on-line models for relational data streams

To date, Inductive Logic Programming (ILP) systems have largely assumed that all data needed for learning have been provided at the onset of model construction. Increasingly, for application areas like telecommunications, astronomy, text processing, financial markets and biology, machine-generated data are being generated continuously and on a vast scale. We see at least four kinds of problems that this presents for ILP: (1) it may not be possible to store all of the data, even in secondary memory; (2) even if it were possible to store the data, it may be impractical to construct an acceptable model using partitioning techniques that repeatedly perform expensive coverage or subsumption-tests on the data; (3) models constructed at some point may become less effective, or even invalid, as more data become available (exemplified by the “drift” problem when identifying concepts); and (4) the representation of the data instances may need to change as more data become available (a kind of “language drift” problem). In this paper, we investigate the adoption of a stream-based on-line learning approach to relational data. Specifically, we examine the representation of relational data in both an infinite-attribute setting, and in the usual fixed-attribute setting, and develop implementations that use ILP engines in combination with on-line model-constructors. The behaviour of each program is investigated using a set of controlled experiments, and performance in practical settings is demonstrated by constructing complete theories for some of the largest biochemical datasets examined by ILP systems to date, including one with a million examples; to the best of our knowledge, the first time this has been empirically demonstrated with ILP on a real-world data set.