Effect of leaf powder of giloy (Tinospora cordifolia) in fish feed on survival and growth of post larvae of Catla catla

The study was designed to evaluate the effect of leaf powder of Giloy (Tinospora cordifolia) in fish feed on survival and growth of post larvae of Catla catla. The experiment consisted of five treatments (T1, T2, T3, T4 and T5) in triplicate. The artificial feed was prepared from de-oiled groundnut cake (49.5%), de-oiled rice bran (49.5%) and vitamin – mineral mixture (1%). The leaf powder of giloy was incorporated into larval feed at various rates. In treatment T1 (control), no leaf powder was incorporated in the feed. In T2, T3, T4 and T5 leaf powder was mixed at the rate of 0.25%, 0.5%, 0.75% and 1%, respectively. One hundred post larvae of C. catla of uniform size (7.3 mm length, 1.5 mg weight) were stocked in each of 5×3=15 tanks. The larvae were fed twice in a day. The water quality parameters were regularly monitored. The survival rate of post larvae in T1, T2, T3, T4 and T5 were recorded as 95.3, 94.3, 97.0, 98.6 and 100%, respectively. Post larvae fed with diet incorporated with 1% leaf powder achieved significantly enhanced (P< 0.05) specific growth rate (6.97%), feed conversion ratio (2.41) and gross conversion efficiency (0.415). The study revealed that giloy leaf powder has very good growth promoting potential in raising post larvae of carp. Thus, it is recommended that the leaf powder of giloy may be incorporated in fish feed upto 1% for enhancing growth and survival of post larvae of carp fishes up to fry stage

7Be ^7 Be Neutrino Signal Variation in KamLAND

Large Mixing Angle (LMA) neutrino oscillation is the main solution for the long-standing Solar Neutrino Problem (SNP). Whether there is any subdominant effect accompanying the dominant LMA solution can not be ruled out at the moment, but will be settled by the forthcoming data from highly skilled real time experiments targeting essentially the low energy domain of solar neutrinos. Assuming a subdominant effect converting one of the active neutrinos into a sterile partner in the varying solar field with changing sunspot activity, we performed field-profile-independent predictions for $^7 Be$ neutrino signal variation, which might be tested in the KamLAND's future solar neutrino detection program. We found that after a substantial reduction of background and running of KamLAND solar mode through the sunspot maximum period (around 2010 - 2012), when the solar field at the resonance may vary from few $kG$ to $300~kG$, the subdominant time variation effect might be clearly visible (more than $5\sigma$) for $^7 Be$ neutrinos.Comment: 12 pages, 4 figures, typos corrected. To appear in JHE

Synthesis, characterization and antimicrobial activities of hydroxytriazenes and their Co(II) complexes

The present paper describes synthesis of flouro chlorosubstituted hydroxytriazenes and their Co(II) complexes.Further these compounds along with their Co(II) complexes have been duly characterized by CHN, IR, 1H NMR and Mass spectral analysis. Complex composition has been determined by Mole ratio and Job’s method. A tetrahedral geometry has been suggested for all the complexes. The compounds have been used for biological activity studies against 4 bacteria and 6 fungal strains. The MIC (Minimum inhibitory concentration) values varied between 25 μg/mL to 50 μg/mL

Antimicrobial photodynamic therapy and its applicability in aquaculture systems and aquatic animal health management: An overview

Global aquaculture production in 2012 touched new high of 90.4 million tonnes including 66.6 million tonnes of food fish and 23.8 million tonnes of aquatic algae providing 19.2 kg per capita food fish suppy. Aquaculture is reported to suffer heavy production and financial losses due to fish infections caused by microbial pathogens. Therefore in order to make aquaculture industry more sustainable, effective strategies to control fish infections are urgently needed. Antimicrobial Photodynamic Therapy (aPDT) is an emerging, low-cost anti-microbial approach to the treatment of locally occurring infections and also for the treatment of aquaculture water and waste waters. Already proven effective in various medical and clinical applications, it utilizes three vital components: a photosensitizing agent (PS), a light source of an appropriate wave length and oxygen. aPDT has got a potential of being a preferred choice over antibiotics in aquaculture systems because of its non-target specificity, few side effects, lack of the pathogenicity reversal and re-growth of the micro-organism after treatment and the lack of development of resistance mechanisms. The technique has been proved effective in vitro against bacteria (including drug-resistant strains), yeasts, fungi, viruses, parasites and even the stubborn biofilms. Although preliminary results indicate that this technology has a high potential to disinfect waters in aquaculture system and also in hatcheries and seed production units, but it clearly needs more deep knowledge and multi-dimenstional approach

Low Energy Solar Neutrinos and Spin Flavour Precession

The possibility that the Gallium data effectively indicates a time modulation of the solar active neutrino flux in possible connection to solar activity is examined on the light of spin flavour precession to sterile neutrinos as a subdominant process in addition to oscillations. We distinguish two sets of Gallium data, relating them to high and low solar activity. Such modulation affects principally the low energy neutrinos ($pp$ and $^7 Be$) so that the effect, if it exists, will become most clear in the forthcoming Borexino and LENS experiments and will provide evidence for a neutrino magnetic moment. Using a model previously developed, we perform two separate fits in relation to low and high activity periods to all solar neutrino data. These fits include the very recent charged current spectrum from the SNO experiment. We also derive the model predictions for Borexino and LENS experiments.Comment: 20 pages, 5 ps figures, 1 eps figure, final version to be published in JHE

KamLAND, solar antineutrinos and the solar magnetic field

In this work the possibility of detecting solar electron antineutrinos produced by a solar core magnetic field from the KamLAND recent observations is investigated. We find a scaling of the antineutrino probability with respect to the magnetic field profile in the sense that the same probability function can be reproduced by any profile with a suitable peak field value. In this way the solar electron antineutrino spectrum can be unambiguosly predicted. We use this scaling and the negative results indicated by the KamLAND experiment to obtain upper bounds on the solar electron antineutrino flux. We get $\phi_{\bar\nu}<3.8\times 10^{-3}\phi(^8B)$ at 95% CL. For 90% CL this becomes $\phi_{\bar\nu}<3.4\times 10^{-3}\phi(^8B)$, an improvement by a factor of 3-5 with respect to existing bounds. These limits are independent of the detailed structure of the magnetic field in the solar interior. We also derive upper bounds on the peak field value which are uniquely determined for a fixed solar field profile. In the most efficient antineutrino producing case, we get (95% CL) an upper limit on the product of the neutrino magnetic moment by the solar field $\mu B< 2.8\times 10^{-19}$ MeV or $B_0 \leq 4.9 \times 10^7 G$ for $\mu_\nu=10^{-12}\mu_B$.Comment: 15 pages. References corrected. Minor changes in the tex

Determining causality in travel mode choice

This article presents one of the pioneering studies on causal modeling in travel mode choice decision-making using causal discovery algorithms. These models are a major advancement from conventional correlation-based techniques. We propose a novel methodology that combines causal discovery with structural equation modeling (SEM). This modeling approach overcomes some of the limitations of SEM by combining the strengths of both causal discovery and SEM. Causal discovery algorithms determine causal graphs from observational data and domain knowledge, and SEMs estimate direct causal effects and test the performance of causal discovery algorithms. In this study, we test four causal discovery algorithms: Peter-Clark (PC), Fast Causal Inference (FCI), Fast Greedy Equivalence Search (FGES), and Direct Linear Non-Gaussian Acyclic Models (DirectLiNGAM). The results show that DirectLiNGAM based SEM model best captures causality in mode choice behavior. It passes several goodness-of-fit tests, including Root Mean Square Error of Approximation (RMSEA) and Goodness-of-Fit Index (GFI), and it achieves the lowest Bayesian Information Criterion (BIC) value. The analyses are conducted on data collected from the 2017 National Household Travel Survey in the New York Metropolitan area

The COVID-19 pandemic and the future of telecommuting in the United States

This study focuses on an important transport-related long-term effect of the COVID-19 pandemic in the United States: an increase in telecommuting. Analyzing a nationally representative panel survey of adults, we find that 40–50% of workers expect to telecommute at least a few times per month post-pandemic, up from 24% pre-COVID. If given the option, 90–95% of those who first telecommuted during the pandemic plan to continue the practice regularly. We also find that new telecommuters are demographically similar to pre-COVID telecommuters. Both pre- and post-COVID, higher educational attainment and income, together with certain job categories, largely determine whether workers have the option to telecommute. Despite growth in telecommuting, approximately half of workers expect to remain unable to telecommute and between 2/3 and 3/4 of workers expect their post-pandemic telecommuting patterns to be unchanged from their pre-COVID patterns. This limits the contribution telecommuting can make to reducing peak hour transport demand