Production Potential of Different Pasture Grasses under Off-Season Rainfall in Arid Conditions of Bikaner, India

Livestock rearing is the important source of livelihood in arid region of Rajasthan where the crop production is unstable due to low and erratic rainfall. The rangelands and pastures are important land use system and provide main support to the livestock in the arid region of Rajasthan. Grazing of livestock is a common practice in arid zone as about 50 % of total area of western Rajasthan is available for grazing mainly for cows, sheep and goat, however, the availability of green fodder is restricted to monsoon and post monsoon months only and during rest of the period livestock graze on dry grasses and crop residues available in cultivated, fallow and wastelands and other grazing lands. The perennial grasses like Lasiurus sindicus, Cenchrus ciliaris, C. setigerus, Panicum turgidum, P. antidotale etc. with some annuals are dominated in the rangelands and pastures in the arid zone of Rajasthan. Generally these grasses are grown during rainy season but also regenerated during off-season condition when sufficient moisture is available through rainfall or irrigation and provide fodder during the lean period. Productivity of these pasture grasses were assessed during rainy season but information of the production potential during off-season is not available in literature. Therefore, present study was conducted during March to May 2015 at Arid Region Campus of CSWRI, Bikaner to assess the production potential and regeneration of different grasses during off-season under arid condition

Functional Nicotinic Acetylcholine Receptors Containing α6 Subunits Are On Gabaergic Neuronal Boutons Adherent To Ventral Tegmental Area Dopamine Neurons

Diverse nicotinic acetylcholine receptor (nAChR) subtypes containing different subunit combinations can be placed on nerve terminals or soma/dendrites in the ventral tegmental area (VTA). nAChR α6 subunit message is abundant in the VTA, but α6*-nAChR cellular localization, function, pharmacology, and roles in cholinergic modulation of dopaminergic (DA) neurons within the VTA are not well understood. Here, we report evidence for α6β2*-nAChR expression on GABA neuronal boutons terminating on VTA DA neurons. α-Conotoxin (α-Ctx) MII labeling coupled with immunocytochemical staining localizes putative α6*-nAChRs to presynaptic GABAergic boutons on acutely dissociated, rat VTA DA neurons. Functionally, acetylcholine (ACh) induces increases in the frequency of bicuculline-, picrotoxin-, and 4-aminopyridine-sensitive miniature IPSCs (mIPSCs) mediated by GABAA receptors. These increases are abolished by α6*-nAChR-selective α-Ctx MII or α-Ctx PIA (1 nM) but not by α7 (10 nM methyllycaconitine) or α4* (1 μM dihydro-β-erythroidine)-nAChR-selective antagonists. ACh also fails to increase mIPSC frequency in VTA DA neurons prepared from nAChR β2 knock-out mice. Moreover, ACh induces an α-Ctx PIA-sensitive elevation in intraterminal Ca2+ in synaptosomes prepared from the rat VTA. Subchronic exposure to 500 nM nicotine reduces ACh-induced GABA release onto the VTA DA neurons, as does 10 d of systemic nicotine exposure. Collectively, these results indicate that α6β2*-nAChRs are located on presynaptic GABAergic boutons within the VTA and modulate GABA release onto DA neurons. These presynaptic α6β2*-nAChRs likely play important roles in nicotinic modulation of DA neuronal activity. Copyright © 2011 the authors

Functional presynaptic [alpha]6-containing nicotinic acetylcholine receptors participate in nicotine reward in the VTA: where and how

In the ventral tegmental area (VTA), [alpha]6-nAChRs express abundantly, but their location, function, pharmacology, and roles in cholinergic modulation of dopaminergic (DA) neurons remain elusive. Using a VTA neuron-adherent bouton preparation, we report that functional [alpha]6-nAChRs are located on GABAergic presynaptic boutons, where they mediate cholinergic modulation of GABA release onto DA neurons. Smoking-relevant concentrations of nicotine desensitize [alpha]6-nAChRs, cause a disinhibition in DA neurons and consequently mediate nicotine reward

Finite-region stabilization via dynamic output feedback for 2-D Roesser models

Finite-region stability (FRS), a generalization of finite-time stability, has been used to analyze the transient behavior of discrete two-dimensional (2-D) systems. In this paper, we consider the problem of FRS for discrete 2-D Roesser models via dynamic output feedback. First, a sufficient condition is given to design the dynamic output feedback controller with a state feedback-observer structure, which ensures the closed-loop system FRS. Then, this condition is reducible to a condition that is solvable by linear matrix inequalities. Finally, viable experimental results are demonstrated by an illustrative example

Performance Analysis and Beamforming Design of a Secure Cooperative MISO-NOMA Network.

This paper studies the cell-edge user's performance of a secure multiple-input single-output non-orthogonal multiple-access (MISO-NOMA) system under the Rayleigh fading channel in the presence of an eavesdropper. We suppose a worst-case scenario that an eavesdropper has ideal user detection ability. In particular, we suggest an optimization-based beamforming scheme with MISO-NOMA to improve the security and outage probability of a cell-edge user while maintaining the quality of service of the near-user and degrading the performance of the eavesdropper. To this end, power allocation coefficients are adjusted with the help of target data rates of both the users by utilizing a simultaneous wireless information and power transfer with time switching/power splitting protocol, where the near-user is used to forward the information to cell-edge user. The analytical results demonstrate that our beamformer analysis can achieve reduced outage probability of cell-edge user in the presence of the eavesdropper. Moreover, the provided simulation results validate our theoretical analysis and show that our approach improves the overall performance of a two-user cooperative MISO-NOMA system

Integrating TOPSIS and ELECTRE-Ⅰ methods with cubic m-polar fuzzy sets and its application to the diagnosis of psychiatric disorders

Many real-world decision-making issues frequently involve competing sets of criteria, uncertainty, and inaccurate information. Some of these require the involvement of a group of decision-makers, where it is necessary to reduce the various available individual preferences to a single collective preference. To enhance the effectiveness of multi-criteria decisions, multi-criteria decision-making is a popular decision-making technique that makes the procedure more precise, reasonable, and efficient. The "Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)" and "Elimination and Choice Transforming Reality (ELECTRE)" are prominent ranking methods and widely used in the multi-criteria decision-making to solve complicated decision-making problems. In this study, two $m$-polar fuzzy set-based ranking methods are proposed by extending the ELECTRE-Ⅰ and TOPSIS approaches equipped with cubic $m$-polar fuzzy (C$m$PF) sets, where the experts provide assessment results on feasible alternatives through a C$m$PF decision matrix. The first proposed method, C$m$PF-TOPSIS, focuses on the alternative that is closest to a C$m$PF positive ideal solution and farthest away from the C$m$PF negative ideal solution. The Euclidean and normalized Euclidean distances are used to determine the proximity of an alternative to ideal solutions. In contrast, the second developed method is C$m$PF-ELECTRE-Ⅰ which uses an outranking directed decision graph to determine the optimal alternative, which entirely depends on the C$m$PF concordance and discordance sets. Furthermore, a practical case study is carried out in the diagnosis of impulse control disorders to illustrate the feasibility and applicability of the proposed methods. Finally, a comparative analysis is performed to demonstrate the veracity, superiority, and effectiveness of the proposed methods

Selected pomegranate germplasm from Afghanistan: morphological variability and relationship among collected accessions

During the period 2008-09 and in the frame of PHDP 58 Afghan and 18 foreign pomegranate accessions have been collected and grown under homogeneous environmental and cultivation practice conditions in ex situ collections. Standardized procedures were adopted to describe mature trees, leaves, flowers and fruits for a total of 30 phenotypic traits. Within the National Collection of Pomegranate of Afghanistan, coefficients of variability ranged from 8.8 to 31.7% for fruit diameter and weight of non edible part, respectively. Principal component analysis revealed the absence of correlated variables among different organs. The whole set of accessions resulted discriminated on the basis of the studied morphological parameters and all the accessions were grouped into 3 sub-sets by hierarchical cluster analysis. Local accessions resulted distributed in the 3 clusters, nevertheless the largest one held all the foreign varieties while the second one included all the accessions collected under the putative name of ‘Bedana’. The adopted morphological studies allowed to identify one true-to-type ‘Bedana’ accession, considered the best Afghan variety for fresh consume due to its very soft seed, and to solve the cases of homonymy. Analogously, various accessions originally collected from different regions of Afghanistan under the name of ‘Kandahari’ were identified and renamed

Ranking of Downstream Fish Passage Designs for a Hydroelectric Project under Spherical Fuzzy Bipolar Soft Framework

Nowadays, several real-world decision-making problems concerning falling economies, power crises, depleting resources, etc., require efficient decision-making. To solve such problems, researchers proposed several hybrid models by combining the spherical fuzzy sets with other theories, such as spherical fuzzy soft sets, which is an efficient tool to deal with the uncertainties concerning positive, neutral, and negative memberships in the soft environment. However, all the existing hybridizations of spherical fuzzy sets fail to deal with information symmetrically in a bipolar soft environment. Accordingly, this paper presents a novel hybrid model called spherical fuzzy bipolar soft sets (SFBSSs) by fusing spherical fuzzy sets and bipolar soft sets, considering the opposite sets of parameters in symmetry. An example considering the selection of a chief management officer (CMO) for a multi-national company illustrates the proposed model in detail. In addition, some symmetric properties and algebraic operations of the initiated model, including subset, complement, relative null SFBSSs, relative absolute SFBSSs, extended union, extended intersection, restricted union, restricted intersection, AND, and OR operations, are discussed and illustrated via numerical examples. Further, some fundamental results, namely, commutativity, associativity, distribution, and De Morgan’s laws are presented for SFBSSs. Moreover, by considering the massive impact of hydropower in combating the energy crisis and possible dangers to fish migration, a multi-attribute decision-making problem concerning the ranking of downstream fish passage designs for a hydroelectric project is modeled and solved under the developed algorithm based on SFBSSs. Finally, a comparative analysis discusses the supremacy of the initiated model over its building blocks

Ranking of Downstream Fish Passage Designs for a Hydroelectric Project under Spherical Fuzzy Bipolar Soft Framework

Nowadays, several real-world decision-making problems concerning falling economies, power crises, depleting resources, etc., require efficient decision-making. To solve such problems, researchers proposed several hybrid models by combining the spherical fuzzy sets with other theories, such as spherical fuzzy soft sets, which is an efficient tool to deal with the uncertainties concerning positive, neutral, and negative memberships in the soft environment. However, all the existing hybridizations of spherical fuzzy sets fail to deal with information symmetrically in a bipolar soft environment. Accordingly, this paper presents a novel hybrid model called spherical fuzzy bipolar soft sets (SFBSSs) by fusing spherical fuzzy sets and bipolar soft sets, considering the opposite sets of parameters in symmetry. An example considering the selection of a chief management officer (CMO) for a multi-national company illustrates the proposed model in detail. In addition, some symmetric properties and algebraic operations of the initiated model, including subset, complement, relative null SFBSSs, relative absolute SFBSSs, extended union, extended intersection, restricted union, restricted intersection, AND, and OR operations, are discussed and illustrated via numerical examples. Further, some fundamental results, namely, commutativity, associativity, distribution, and De Morgan’s laws are presented for SFBSSs. Moreover, by considering the massive impact of hydropower in combating the energy crisis and possible dangers to fish migration, a multi-attribute decision-making problem concerning the ranking of downstream fish passage designs for a hydroelectric project is modeled and solved under the developed algorithm based on SFBSSs. Finally, a comparative analysis discusses the supremacy of the initiated model over its building blocks