The increasing demand and use of plastics in our daily lives have caused an increase in microplastics (MPs) concentration in water bodies. Increasing MP in water affects aquatic life and is ...associated with several health issues. All sources of water whether fresh, marine, or sewage have reported the presence of various MPs. It is clear from relevant literature that the presence of MP with a particular chemical composition could be indicative of its source and could contribute to its removal. Increasing population density, plastic litters, fishing activities, and industrial wastes are major contributors of MP in water. This review is systematically undertaken where Raman spectroscopy (RS) is used as an indispensable tool to identify the chemical composition of the MP in various water sources (fresh/ground/drinking; ocean/sea; waste/sewage) between 2015 and 2021. Based on the Raman spectra, polystyrene (PS), polyethylene terephthalate (PET), polyethylene (PE), and polypropylene (PP) are some of the common MP identified in the water sources.
Bioeffects of microwave––a brief review Banik, S.; Bandyopadhyay, S.; Ganguly, S.
Bioresource Technology,
04/2003, Letnik:
87, Številka:
2
Book Review, Journal Article
Recenzirano
Since the 18th century scientists have been intrigued by the interaction of electromagnetic fields (EMFs) and various life processes. Attention has been focussed on EMFs in different frequency ...ranges, of which microwave frequency range forms an important part.
Microwaves are part of the electromagnetic spectrum and are considered to be that radiation ranging in frequency from 300 million cycles per second (300 MHz) to 300 billion cycles per second (300 GHz), which correspond to a wavelength range of 1 m down to 1 mm. This nonionising electromagnetic radiation is absorbed at molecular level and manifests as changes in vibrational energy of the molecules or heat (Microwaves irradiating the community,
Hidden hazards, Bantan Books publisher, Australia, 1991).
Identifying and evaluating the biological effects of microwaves have been complex and controversial. Because of the paucity of information on the mechanism of interaction between microwave and biological systems, there has been a persistent view in physical and engineering sciences, that microwave fields are incapable of inducing bioeffects other than by heating (Health Physics 61 (1991) 3). Of late, the nonthermal effects of microwaves on tissue responses are being documented (Physiol. Rev. 61 (1981) 435; Annals of New York Acad. Sci. 247 (1975) 232; J. Microwave Power 14 (1979) 351; Bioelectromagnetics 7 (1986a) 45; Bioelectromagnetics 7 (1986b) 315; Biologic Effects and Health Hazards of Microwave Radiation, Warsaw, Polish Medical Publication (1974) 289; Biologic Effects and Health hazards of the microwave Radiation, Warsaw, Polish Medical Publication (1974) 22; Multidisciplinory perspectives in event-related brain potential research, Washington DC, US Enonmental Protection Agency, (1978) 444).
The present article is an attempt to familiarise the reader with pertinent information regarding the effects, mainly athermal, of microwave irradiation on biologic systems, especially microorganisms.
In the expanding universe, relativistic scalar fields are thought to be attenuated by "Hubble friction," which results from the dilation of the underlying spacetime metric. By contrast, in a ...contracting universe this pseudofriction would lead to amplification. Here, we experimentally measure, with fivefold better accuracy, both Hubble attenuation and amplification in expanding and contracting toroidally shaped Bose-Einstein condensates, in which phonons are analogous to cosmological scalar fields. We find that the observed attenuation or amplification depends on the temporal phase of the phonon field, which is only possible for nonadiabatic dynamics. The measured strength of the Hubble friction disagrees with recent theory Gomez Llorente et al., Phys. Rev. A 100, 043613 (2019)PLRAAN2469-992610.1103/PhysRevA.100.043613 and Eckel et al., SciPost Phys. 10, 64 (2021)SPCHCW2542-465310.21468/SciPostPhys.10.3.064.
As rice is an important staple food globally, research for development and enhancement of its nutritional value it is an imperative task. Identification of nutrient enriched rice germplasm and ...exploiting them for breeding programme is the easiest way to develop better quality rice. In this study, we analyzed 113 aromatic rice germplasm in order to identify quantitative trait loci (QTL) underpinning nutrition components and determined by measuring the normal frequency distribution for Fe, Zn, amylose, and protein content in those rice germplasm. Comparatively, the germplasm Radhuni pagal, Kalobakri, Thakurbhog (26.6 ppm) and Hatisail exhibited the highest mean values for Fe (16.9 ppm), Zn (34.1 ppm), amylose (26.6 ppm) and protein content (11.0 ppm), respectively. Moreover, a significant linear relationship (R.sup.2 = 0.693) was observed between Fe and Zn contents. Cluster analysis based on Mahalanobis D.sup.2 distances revealed four major clusters of 113 rice germplasm, with cluster III containing a maximum 37 germplasm and a maximum inter-cluster distance between clusters III and IV. The 45 polymorphic SSRs and four trait associations exhibited eight significant quantitative trait loci (QTL) located on eight different chromosomes using composite interval mapping (CIM). The highly significant QTL (variance 7.89%, LOD 2.02) for protein content (QTL.pro.1) was observed on chromosome 1 at 94.9cM position. Also, four QTLs for amylose content were observed with the highly significant QTL.amy.8 located on chromosome 8 exhibiting 7.2% variance with LOD 1.83. Only one QTL (QTL.Fe.9) for Fe content was located on chromosome 9 (LOD 1.24), and two (QTL.Zn.4 and QTL.Zn.5) for Zn on chromosome 4 (LOD 1.71) and 5 (LOD 1.18), respectively. Overall, germplasm from clusters III and IV might offer higher heterotic response with the identified QTLs playing a significant role in any rice biofortification breeding program and released with development of new varieties.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A nonlinear Schrödinger equation (NLSE) has been derived by employing reductive perturbation method for investigating the modulational instability of dust-ion-acoustic waves (DIAWs) in a ...four-component plasma having stationary negatively charged dust grains, inertial warm ions, and inertialess non-thermal electrons, and positrons. It is observed that under consideration, the plasma system supports both modulationally stable and unstable domains, which are determined by the sign of the dispersive and nonlinear coefficients of NLSE, of the DIAWs. It is also found that the nonlinearity as well as the height and width of the first and second-order rogue waves increases with the non-thermality of electron and positron. The relevancy of our present investigation to the observations in space plasmas is pinpointed.
Graphic abstract
Chiral interfaces and molecular recognition phenomena are of special interest not only for the understanding of biological recognition processes but also for the potential application in material ...science. Langmuir monolayers at the air-water interface have successfully been used as simple models to mimic biological phenomena. Recent experimental studies revealed that both chirality and molecular recognition processes of amphiphiles are controlling the features of the nano-aggregates at the air/water interface. The objective of experimental studies has been to gain information about the properties of mesoscopic length scale aggregates obtained on the basis of chiral discrimation effects and the formation of supramolecular entities by molecular recognition of non-surface active species dissolved in the aqueous subphase. Differences in the two-dimensional morphology and lattice structures of the nano-aggregates cannot be explained by macroscopic theories and needed information about the detailed orientation and distance dependence of the intermolecular interaction within the aggregates. First new bottom-up studies have been directed toward understanding the driving forces for the aggregation processes of monolayers. Different types of interactions have been successfully considered using semi-empirical quantum chemical methods. The possibilities of Langmuir-Blodgett (LB) patterning to be an alternative paradigm for large-area patterning with mesostructured features are discussed.
The thermoelastic interaction for the three-phase-lag （TPL） heat equation in an isotropic infinite elastic body with a spherical cavity is studied by two-temperature generalized thermoelasticity ...theory （2TT）. The heat conduction equation in the theory of TPL is a hyperbolic partial differential equation with a fourth-order derivative with respect to time. The medium is assumed to be initially quiescent. By the Laplace trans- formation, the fundamental equations are expressed in the form of a vector-matrix differ- ential equation, which is solved by a state-space approach. The general solution obtained is applied to a specific problem, when the boundary of the cavity is subjected to the ther- mal loading （the thermal shock and the ramp-type heating） and the mechanical loading. The inversion of the Laplace transform is carried out by the Fourier series expansion tech- niques. The numerical values of the physical quantity are computed for the copper like ma- terial. Significant dissimilarities between two models （the two-temperature Green-Naghdi theory with energy dissipation （2TGN-III） and two-temperature TPL model （2T3phase）） are shown graphically. The effects of two-temperature and ramping parameters are also studied.
Abstract
Lung diseases are the most common ailments seen among people with the history of smoking. Prompt and timely recognition and diagnosis may help in saving many lives. In order to detect cancer ...at early stages machine learning algorithms can be employed. Use of simple machine learning algorithms will help identify the carcinoma faster with high accuracy and lesser expense. This work shows the use three of simple machine learning (ML) algorithms like Logistic Regression, Support Vector Machine (SVM), and K-Nearest Neighbours (KNN). ML models were built using lung cancer patients’ dataset. The dataset was used to train the model as well as test the model. The three classifiers will detect the presence of lung cancer. For each classifier the Accuracy, Mean Square Error(MSE), precision, and Recall (R2) was calculated. A comparative study of the classifiers was done to identify which among the three was the best one. The main objective of the paper is to identify the best efficient machine-learning algorithm in terms of confusion matrices, accuracy, and precision for the prediction and diagnosis of lung cancer
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