Salinity Induced Changes in the Leaf Anatomy of the Mangrove Avicennia Marina Along the Anthropogenically Stressed Tropical Creek

The mangrove Avicennia marina is a dominant mangrove along the anthropogenically stressed tropical Thane creek, west coast of India. Leaf anatomy of the mangrove along the Thane creek, was assessed in relation to stationwise and seasonwise variations in salinity. It was noticed that under the conditions of higher salinity, Avicennia marina showed increased thickness of hypodermal water storage tissue in the leaf (for conservation of water) and produced taller salt extruding glands at the lower epidermis to eliminate more salt; whereas, the thickness of the photosynthetic mesophyllic tissue significantly reduced. At lower salinity or with reduction in salinity in monsoon, contrary to above occurred. These changes probably explain the stunted growth of Avicennia marina in high salinity environment and its vigorous growth at lower salinity

Concentration Effects and Ion Properties Controlling the Fractionation of Halides during Aerosol Formation

During the aerosolization process at the sea surface, halides are incorporated into aerosol droplets, where they may play an important role in tropospheric ozone chemistry. Although this process may significantly contribute to the formation of reactive gas phase molecular halogens, little is known about the environmental factors that control how halides selectively accumulate at the air-water interface. In this study, the production of sea spray aerosol is simulated using electrospray ionization (ESI) of 100 nM equimolar solutions of NaCl, NaBr, NaI, NaNO(2), NaNO(3), NaClO(4), and NaIO(4). The microdroplets generated are analyzed by mass spectrometry to study the comparative enrichment of anions (f(X(-))) and their correlation with ion properties. Although no correlation exists between f(X(-)) and the limiting equivalent ionic conductivity, the correlation coefficient of the linear fit with the size of the anions R(X(-)), dehydration free-energy ΔG(dehyd), and polarizability α, follows the order: R(X(-))(-2) \u3e R(X(-))(-1) \u3e R(X(-)) \u3e ΔG(dehyd) \u3e α. The same pure physical process is observed in H(2)O and D(2)O. The factor f(X(-)) does not change with pH (6.8-8.6), counterion (Li(+), Na(+), K(+), and Cs(+)) substitution effects, or solvent polarity changes in methanol- and ethanol-water mixtures (0 ≤ x(H(2)O) ≤ 1). Sodium polysorbate 20 surfactant is used to modify the structure of the interface. Despite the observed enrichment of I(-) on the air-water interface of equimolar solutions, our results of seawater mimic samples agree with a model in which the interfacial composition is increasingly enriched in I(-) \u3c Br(-) \u3c Cl(-) over the oceanic boundary layer due to concentration effects in sea spray aerosol formation

Numerical classification of actinomadura and nocardiopsis

RESP-916

Replicating Viral Vector-Based Vaccines for COVID-19: Potential Avenue in Vaccination Arena

The “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)” is the third member of human coronavirus (CoV) that is held accountable for the current “coronavirus disease 2019 (COVID-19)” pandemic. In the past two decades, the world has witnessed the emergence of two other similar CoVs, namely SARS-CoV in 2002 and MERS-CoV in 2013. The extent of spread of these earlier versions was relatively low in comparison to SARS-CoV-2. Despite having numerous reports inclined towards the zoonotic origin of the virus, one cannot simply sideline the fact that no animal originated CoV is thus far identified that is considered similar to the initial edition of SARS-CoV-2; however, under-sampling of the diverse variety of coronaviruses remains a concern. Vaccines are proved to be an effective tool for bringing the end to such a devastating pandemic. Many vaccine platforms are explored for the same but in this review paper, we will discuss the potential of replicating viral vectors as vaccine carriers for SARS-CoV-2

Comparison of Training, Anthropometric, Physiological and Psychological Variables of Ultra-Endurance Cyclists and Runners

AbstractWe compared training, anthropometric, physiological and psychological characteristics between 14 cyclists, participants in a 24-hour mountain bike race and 12 runners, participants in a 7-day running ultra-marathon. Methods: Questionnaires and physiological measurements. Results: The differences in ages between cyclists and runners were significant (p << 0.01). The pre-race minus post-race differences (Δ) in body mass (from 76.5 ± 13.1kg to 72.0 ± 12.0kg) and (Δ) in value of hematocrit (6.1 ± 3.5%) were significant only in runners. The post-race minus pre-race difference (Δ) in the rating of perceived exertion was significant in both groups

Privacy Risks of Securing Machine Learning Models against Adversarial Examples

The arms race between attacks and defenses for machine learning models has come to a forefront in recent years, in both the security community and the privacy community. However, one big limitation of previous research is that the security domain and the privacy domain have typically been considered separately. It is thus unclear whether the defense methods in one domain will have any unexpected impact on the other domain. In this paper, we take a step towards resolving this limitation by combining the two domains. In particular, we measure the success of membership inference attacks against six state-of-the-art defense methods that mitigate the risk of adversarial examples (i.e., evasion attacks). Membership inference attacks determine whether or not an individual data record has been part of a model's training set. The accuracy of such attacks reflects the information leakage of training algorithms about individual members of the training set. Adversarial defense methods against adversarial examples influence the model's decision boundaries such that model predictions remain unchanged for a small area around each input. However, this objective is optimized on training data. Thus, individual data records in the training set have a significant influence on robust models. This makes the models more vulnerable to inference attacks. To perform the membership inference attacks, we leverage the existing inference methods that exploit model predictions. We also propose two new inference methods that exploit structural properties of robust models on adversarially perturbed data. Our experimental evaluation demonstrates that compared with the natural training (undefended) approach, adversarial defense methods can indeed increase the target model's risk against membership inference attacks.Comment: ACM CCS 2019, code is available at https://github.com/inspire-group/privacy-vs-robustnes

Quantum Correlations in NMR systems

In conventional NMR experiments, the Zeeman energy gaps of the nuclear spin ensembles are much lower than their thermal energies, and accordingly exhibit tiny polarizations. Generally such low-purity quantum states are devoid of quantum entanglement. However, there exist certain nonclassical correlations which can be observed even in such systems. In this chapter, we discuss three such quantum correlations, namely, quantum contextuality, Leggett-Garg temporal correlations, and quantum discord. In each case, we provide a brief theoretical background and then describe some results from NMR experiments.Comment: 21 pages, 7 figure