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Introduction: Gestational Diabetes Mellitus (GDM) is a chronic and progressive disease characterised by changes in the metabolism of carbohydrates, lipids, and proteins, leading to glucose intolerance. The foetal heart in GDM is affected throughout the gestational period, which may result in hyperplasia and hypertrophy of myocardial cells. Aim: To determine the cardiac function and structural changes in infants of gestational diabetic mothers using Doppler-echocardiographic data. Materials and Methods: A cross-sectional analytical study was conducted on 30 infants of mothers with GDM and 30 infants of non diabetic mothers at the Department of Physiology, R.G. Kar Medical College and Hospital, in collaboration with the Departments of Paediatric Medicine and Cardiology from January 2023 to August 2023. Neonatal screening echocardiography was performed by a cardiologist using a Philips Echocardiograph machine, Model: EPIQ 7C, Software Version: 4.0.2, with a linear convex probe of S8-3 MHz frequency to assess cardiac structure and function using 2D, M mode, and Conventional Doppler. The parameters studied included aortic root diameter (mm), left atrial diameter (mm), Interventricular Septal (IVS) in diastole (mm), left ventricular posterior wall thickness in diastole (mm), left ventricular internal diameter in diastole (mm), left ventricular internal diameter in end systole (mm), left ventricular fractional shortening (%), and left ventricular ejection fraction (%). Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) version-20.0 with an Independent Student’s t-test. Results: The mean gestational age for the cases was 38.50±2.57 weeks and 39.30±1.97 weeks for controls. The mean maternal age for cases was 25±4.37 years and for controls was 27±5.03 years. The left atrial diameter in cases (12.83±2.14 mm) was significantly smaller than that of the control (14.20±0.55 mm). The left ventricular posterior wall diameter in diastole was significantly increased in cases (4.53±0.50 mm) compared to controls (3.87±0.35 mm). Significant differences were observed in the interventricular septum in diastole {cases: 4.73±0.45 mm, control: 3.97±0.32 mm} and in the left ventricular internal diameter in end systole {cases: 12.30±1.84 mm, control: 13.83±1.02 mm} between cases and controls. Aortic root diameter was increased in 13.3% of cases. The percentage of left ventricular fractional shortening (cases: 35.47±3.74 %, Control: 38.53±2.43 %), Left Ventricular Ejection fraction (cases: 67.63±4.52 %, control: 72.17±4.89 %) were significantly decreased in cases compared to control. Conclusion: The present study demonstrated the development of ventricular hypertrophy and compromised myocardial contractility in infants of diabetic mothers.

The combined application of Cathodoluminescence (CL) with Scanning Electron Microscopy (SEM) on paintings and painted surfaces has the potential to identify both organic and inorganic pigments on a micrometre or even nanometre scale. Additionally, the combination with Energy-Dispersive Spectrometry (EDS) allows for a more holistic, elemental, and mineralogical characterization of pigments. In addressing the need for the creation of a robust, open access database of characteristic CL spectra of pigments, a large project has been undertaken, focusing primarily on common organic and inorganic pigments. The present paper focuses on the CL characterization of 10 significant blue pigments in pure powder form: cerulean blue, Egyptian blue, Han blue, indigo, lapis lazuli, Maya blue, phthalo blue, vivianite, ultramarine blue, and zirconium blue. The CL spectra present characteristic bands for most of the pigments, allowing their secure identification, especially when combining the results with the EDS analyses. The effect of binding media and of the mixture of different pigments was also studied, via the analysis of mixtures of pigments with oil painted over canvas. Overall, both the binding medium and the mixture of pigments do not appear to create significant differences in the occurring spectra, thus allowing the identification of individual pigments. EDS and RAMAN spectra are included in order to facilitate comparison with other databases.

In this current work an open-source 2D Digital Image Correlation (DIC) tool, RealPi2dDIC, is presented to monitor in-situ full field deformation and strain responses of structures during loading. This software is coded in Python3 and uses Raspberry Pi as the computation and Pi camera as the imaging device. This low-cost approach to in-situ DIC analysis enables its application in a broad field of research and industry problems where 2D strain field tensor is one of the principal interests of study. This code is provided with an interactive user interface (UI) making it user friendly and easy-to-use. Furthermore, RealPi2dDIC offers a simple software architecture which can be adopted, modified and extended to suit users’ purpose.

Background Several non-invasive technologies are nowadays available in the market which claim to determine the hemoglobin levels instantly without the requirement of the blood sample. But no study has shown the significance of such non-invasive devices on a routine basis for determining their impact on anemia reduction programs. This study is conducted to determine the impact of regular hemoglobin screening on the women population to determine its potential in reducing anemia, using a digitalized non-invasive device.Method A cross-sectional study was conducted on 203 women of reproductive age group, residing in the Moradabad district. Repetitive readings were taken after a time interval of a minimum of 1 month for determining the impact of regular screening. The entire data collection process was carried out using the EzeCheck mobile app.Results It was observed that the prevalence of anemia was reduced upon the second time screening and was accepted by the women population. Repetitive testing has a significant impact on reducing anemia prevalence. Also, the simplified non-invasive technology for estimating the hemoglobin values, makes the user more comfortable to take the test.Conclusion Non-invasive devices should be used regularly to keep track of hemoglobin levels which will help in the effective treatment of anemia. The mobile app-based testing could help to easily evaluate the reports of the patients from any remote location with instant result interpretation and health assistance.

MicroRNAs (miRNAs) are critical regulators of transcriptional and post-transcriptional gene silencing, which are involved in multiple developmental processes in many organisms. Apart from miRNAs, mouse germ cells express another type of small RNA, piwi-interacting RNAs (piRNAs). Although it has been clear that piRNAs play a role in repression of retrotransposons during spermatogenesis, the function of miRNA in mouse germ cells has been unclear.In this study, we first revealed the expression pattern of miRNAs by using a real-time PCR-based 220-plex miRNA expression profiling method. During development of germ cells, miR-17-92 cluster, which is thought to promote cell cycling, and the ES cell-specific cluster encoding miR-290 to -295 (miR-290-295 cluster) were highly expressed in primordial germ cells (PGCs) and spermatogonia. A set of miRNAs was developmentally regulated. We next analysed function of miRNA biogenesis in germ cell development by using conditional Dicer-knockout mice in which Dicer gene was deleted specifically in the germ cells. Dicer-deleted PGCs and spermatogonia exhibited poor proliferation. Retrotransposon activity was unexpectedly suppressed in Dicer-deleted PGCs, but not affected in the spermatogonia. In Dicer-deleted testis, spermatogenesis was retarded at an early stage when proliferation and/or early differentiation. Additionally, we analysed spermatogenesis in conditional Argonaute2-deficient mice. In contrast to Dicer-deficient testis, spermatogenesis in Argonaute2-deficient testis was indistinguishable from that in wild type.These results illustrate that miRNAs are important for the proliferation of PGCs and spermatogonia, but dispensable for the repression of retrotransposons in developing germ cells. Consistently, miRNAs promoting cell cycling are highly expressed in PGCs and spermatogonia. Furthermore, based on normal spermatogenesis in Argonaute2-deficient testis, the critical function of Dicer in spermatogenesis is independent of Argonaute2.

Anaemia is a major public health problem, especially in resource constrained settings. Dependency on assessment of blood hemoglobin (Hgb) concentration impedes anemia detection, risk stratification and intervention. Thus, valid, frugal and scalable technologies are needed. EzeCheck is a noninvasive portable device developed in India for predicting hemoglobin levels in human beings aged 4 years and above using a finger-tip biosensor. In this assessment, we aimed to: (i) evaluate EzeCheck's performance with an automated whole blood hemato-analyzer (Sysmex XN 1000) as the gold standard, and (ii) estimate EzeCheck's agreement with Sahli's method and HemoCue (Hb-301) in real-world primary and higher care facilities. Paired assessments were done at five sites across India i.e., Bhubaneshwar, Shimla, Solan and Mashobra and Ulhasnagar. Participants across all age groups (4 years and above) were assessed. We used a range of statistical tests to evaluate the performance of EzeCheck. It was found that EzeCheck performed well across age and gender categories with convincing validity, concordance, precision and accuracy, and acceptable bias. While comparing EzeCheck with Hemato-analyzer, no statistically significant systematic bias was found. However, EzeCheck showed significant systematic bias when compared to Sahli's method and HemoCue. We concluded that EzeCheck could detect anemia (as per WHO Hgb cut-offs) in 'real-world settings' and 'across age and gender categories', with high sensitivity, specificity and accuracy, and can serve as a replacement to traditional methods of hemoglobin assessment. Further, for countries with higher prevalence of anemia where universal screening may be mandated, the positive predictive value of EzeCheck will be higher. The likelihood ratios also indicated that the device had moderate-to-good utility. EzeCheck is suitable for embedment into program and out-patient health care settings in resource constrained contexts as a spot-check hemoglobinometer.

Summary: RNA has been implicated in the recruitment of chromatin modifiers, and previous studies have provided evidence in favor and against this idea. RNase treatment of chromatin is commonly used to study RNA-mediated regulation of chromatin modifiers, but the limitations of this approach remain unclear. RNase A treatment during chromatin immunoprecipitation (ChIP) reduces chromatin occupancy of the H3K27me3 methyltransferase Polycomb repressive complex 2 (PRC2). This led to suggestions of an “RNA bridge” between PRC2 and chromatin. Here, we show that RNase A treatment during ChIP causes the apparent loss of all facultative heterochromatin, including both PRC2 and H3K27me3 genome-wide. We track this observation to a gain of DNA from non-targeted chromatin, sequenced at the expense of DNA from facultative heterochromatin, which reduces ChIP signals. Our results emphasize substantial limitations in using RNase A treatment for mapping RNA-dependent chromatin occupancy and invalidate conclusions that were previously established for PRC2 based on this assay.

Antimicrobial resistance (AMR) in bacterial pathogens has emerged as a challenge in health care settings resulting in high rates of morbidity and mortality. The aim of the present study was to describe the trends and burden of AMR in a tertiary care hospital. A retrospective observational study was undertaken from October 2018 to March 2021 in a clinical microbiology laboratory where local priority pathogens and their antimicrobial resistance patterns were analyzed. Organism identification and antimicrobial susceptibility testing were performed as per Clinical and Laboratory Standards Institute guidelines. Out of 9948 isolates, Enterobacteriaceae (58%) were mostly isolated followed by Staphylococci (18.6%), Non-fermenting gram negative bacilli (NFGNB) (13.7%), and Enterococci (8.4%) respectively. Highest isolation was from inpatient department (61.3%); 31.5% from outpatient, and 7.2 % from intensive care units. Klebsiella pneumoniae (26.9%) was most isolated organism, mostly from respiratory samples; Escherichia coli was isolated mostly from urine (40.7%). Almost half of the Enterobacteriaceae isolates were extended spectrum beta-lactamase producers while >50% of Enterobacteriaceae and NFGNB isolates were resistant to one or more Carbapenems. Frequency of Methicillin resistant Staphylococcus aureus was 44.7% , Vancomycin resistant Enterococci was 1.2%. A rising trend of resistance to cephalosporins and carbapenems along with fluoroquinolones was observed. Our study has witnessed a high prevalence of Gram negative pathogens with increasing resistance to commonly applied antimicrobials during the surveillance period which can act as a guiding tool in devising local antimicrobial priorities, antibiotic policy, and proper antimicrobial prescribing practices.

Gait phase monitoring wearable sensors play a crucial role in assessing both health and athletic performance, offering valuable insights into an individual’s gait pattern. In this study, we introduced a simple and cost-effective capacitive gait sensor manufacturing approach, utilizing a micropatterned polydimethylsiloxane dielectric layer placed between screen-printed silver electrodes. The sensor demonstrated inherent stretchability and durability, even when the electrode was bent at a 45-degree angle, it maintained an electrode resistance of approximately 3 Ω. This feature is particularly advantageous for gait monitoring applications. Furthermore, the fabricated flexible capacitive pressure sensor exhibited higher sensitivity and linearity at both low and high pressure and displayed very good stability. Notably, the sensors demonstrated rapid response and recovery times for both under low and high pressure. To further explore the capabilities of these new sensors, they were successfully tested as insole-type pressure sensors for real-time gait signal monitoring. The sensors displayed a well-balanced combination of sensitivity and response time, making them well-suited for gait analysis. Beyond gait analysis, the proposed sensor holds the potential for a wide range of applications within biomedical, sports, and commercial systems where soft and conformable sensors are preferred.

Nowadays many research articles are prefaced with research highlights to summarize the main findings of the paper. Highlights not only help researchers precisely and quickly identify the contributions of a paper, they also enhance the discoverability of the article via search engines. We aim to automatically construct research highlights given certain segments of a research paper. We use a pointer-generator network with coverage mechanism and a contextual embedding layer at the input that encodes the input tokens into SciBERT embeddings. We test our model on a benchmark dataset, CSPubSum, and also present MixSub, a new multi-disciplinary corpus of papers for automatic research highlight generation. For both CSPubSum and MixSub, we have observed that the proposed model achieves the best performance compared to related variants and other models proposed in the literature. On the CSPubSum dataset, our model achieves the best performance when the input is only the abstract of a paper as opposed to other segments of the paper. It produces ROUGE-1, ROUGE-2 and ROUGE-L F1-scores of 38.26, 14.26 and 35.51, respectively, METEOR score of 32.62, and BERTScore F1 of 86.65 which outperform all other baselines. On the new MixSub dataset, where only the abstract is the input, our proposed model (when trained on the whole training corpus without distinguishing between the subject categories) achieves ROUGE-1, ROUGE-2 and ROUGE-L F1-scores of 31.78, 9.76 and 29.3, respectively, METEOR score of 24.00, and BERTScore F1 of 85.25.

Software developers often face challenges in terms of quality and productivity to match competitive costs. The software industry seeks options to minimize this cost during different phases of software development and maintenance with improved productivity. Software developers adopt different tools for different purposes, such as understanding program behavior, debugging memory issues, debugging concurrency issues, and testing. In this article we study different debugging tools mostly used for program design analysis, thread debugging, and resource management. Stand-alone tools do track static or dynamic control flow, thread activities, etc. But these do not specifically identify the thread work-breakdown-structure, global memory location management, thread-data interaction, etc. to allow good comprehension of the concurrency model of the program. Similarly for resource management, we observe that the Valgrind addresses a few required features but does not offer automatic garbage collection. Moreover, to address the outcomes of different tools, developers must compile and configure the application in different environments. This is very time-consuming, requires skills in different software paradigms, and is sometimes not supported by the tool itself. As a result, they cannot be used in an inter-operable manner to analyze by relating the different tool’s outcomes. In this study, we conduct a detailed survey of the available tools and techniques and their limitations in identifying gaps. We address these gaps by implementing the tools for different phases of software development and maintenance. For example, a concurrency model detector based on thread behavior, resource debugger with features of automatic garbage collection, etc. can collectively inter-operate within our designed open-source tool framework Parallelc-Assist to address the common requests of the developers in one toolset. The tool is built upon open-source dynamic instrumentation tool PIN and supports a wide variety of IDEs and OS to detect various multi-threaded memory issues and provide additional features to inject concerns dynamically at run-time to extend it further according to the user’s needs. We verify our tool with a wide variety of industry-standard benchmarks and compare its features with other similar tools.

Resistive random access memories (ReRAM) have drawn attention of researchers due to their unique properties with applications in in-memory computing, which allows storage and computation in the same unit. This mitigates one of the major limitations in current computing architectures, where for each computation we require to move data from memory to processor or vice versa, which incurs immense amount of energy overheads. Among the various technologies for implementing ReRAM, memristor is considered to be one of the most desirable candidates due to its small size, low power consumption, and high data retention. Such ReRAM systems are often fabricated in the form of crossbar for compact layout. However, they suffer from various challenges, one of the major ones being the sneak-path problem during reading of cell values. The read operation is mostly disturbed by sneak-path currents that can result in incorrect reading of the cell. This paper presents a new approach for reading the cell values in memristive crossbars, which is capable of avoiding erroneous read operations caused by sneak-paths. It also supports parallel operations whereby multiple memristor states can be read in a single cycle. A straightforward approach for reading all the cells in an n×ncrossbar, where the read operation is performed sequentially, requires O(n2)cycles, whereas the proposed approach requires O(n)cycles.

Amorphous, glassy or disordered materials play important roles in developing structural materials from metals or ceramics, devices from semiconductors or medicines from organic compounds. Their local structure is frequently similar to crystalline ones. A computer program is presented here that runs under the Windows operating system on a PC to extract pair distribution function (PDF) from electron diffraction in a transmission electron microscope (TEM). A polynomial correction reduces small systematic deviations from the expected average Q-dependence of scattering. Neighbor distance and coordination number measurements are supplemented by either measurement or enforcement of number density. Quantification of similarity is supported by calculation of Pearson’s correlation coefficient and fingerprinting. A rough estimate of fractions in a mixture is computed by multiple least-square fitting using the PDFs from components of the mixture. PDF is also simulated from crystalline structural models (in addition to measured ones) to be used in libraries for fingerprinting or fraction estimation. Crystalline structure models for simulations are obtained from CIF files or str files of ProcessDiffraction. Data from inorganic samples exemplify usage. In contrast to previous free ePDF programs, our stand-alone program does not need a special software environment, which is a novelty. The program is available from the author upon request.

Eco-friendly surface treatment of natural fibers using sodium acetate (CH3COONa) affects the mechanical properties of the developed composites in many ways. In present study, geometrically different kenaf fiber mats (bidirectional (BC), unidirectional (UD) and randomly oriented (RO) were treated at different concentration (10, 15 and 20 percentage w/w) of sodium acetate aqueous solution for varying time (24, 48 and 72 hr.) at room temperature. PLA (Poly-Lactic Acid) was used for the fabrication of treated fiber reinforced bio-degradable composites. The influence of above parameters on mechanical properties were studied. Response surface methodology (RSM) module face centered central composite design was employed for the development of regression models. The relationship between chemical treatment parameters and mechanical responses were predicted by quadratic model. In this study, predicted model was developed for two numerical factors (chemical concentration (CC) and treatment time (TT)) and one categorical factor (type of mat (TOM)). Tensile strength (TS), flexural strength (FS) and impact strength (IS) are considered as response variables. The statistical analysis showed that chemical concentration, treatment time and kenaf mat type have individually and interactively influenced the response of experiments. Chemical concentration was found to be the most influencing factor among all for the changes in mechanical properties. Optimization of input variables was done based on predicted model within bounded reason of responses.

This paper provides a method to understand the underlying semantics of Bharatnatyam dance motion and classifies it. Each dance performance is audio-driven and spans over space and time. The dance is captured and analyzed, which is helpful in cultural heritage preservation, and tutoring systems to assist the naive learner. This paper attempts to solve the fundamental problem; recognizing the motions during a dance performance based on motion-pattern. The used dataset is the video recordings of an Indian Classical Dance form known as Bharatanatyam. The different Adavu s (The basic unit of Bharatanatyam) of Bharatanatyam dance are captured using Kinect. We choose RGB from various forms of captured data (RGB, Depth, and Skeleton). Motion History Image (MHI) and Histogram of Gradient of MHI (HoGMHI) are computed for each motion and used as an input for the Machine Learning (ML) algorithms to recognize motion. The paper explores two ML techniques; Support Vector Machine (SVM) and Convolutional Neural Network (CNN). The overall accuracy of both the classifiers is more than 90%. The novelties of the work are (a) analysing all possible involved motions based on the motion-patterns rather than the joint velocities or pose, (b)exploring the impact of training data and the different features on the classifiers’ accuracy, (c) not restricting the number of frames in a motion during recognition and formulate a method to deal with the variable number of frames in the motions.

Fiber reinforced polymer (FRP) composites are being used in numerous fields owing to their intrinsic strength to weight ratio and various design benefits. However, these materials are prone to environmental aging, particularly moisture absorption. In essence, absorbed moisture infiltrates the polymer matrix and induces changes in the polymer network through chain scission, plasticization, and other bonding interactions. This causes irreversible damages to the material and significantly decreases mechanical strength. In this study, Broadband Dielectric Spectroscopy (BbDS) has been used to identify the absorption mechanisms in glass fiber reinforced polymer (GFRP) composites by detecting the related polarization mechanisms. Here, results show an increase in the real permittivity and dielectric relaxation strength of the material with moisture absorption and attaining a steady-state once absorption approaches saturation. In this work, moisture-induced degradation of tensile and flexural properties of the material have also been studied and a correlation has been found to exist between the dielectric state variables, absorbed moisture, and the mechanical properties of the material. The correlation resolves the integration of the different material physics involved here and can be used to empirically predict the residual strength of a composite structure using the non-destructive broadband dielectric characterization technique.

It is a well-known fact that automotive industries in every country are shifting towards electric vehicles (EVs) and in the days to come it is expected that the industry will become dominated by them, along with hybrid electric vehicles (HEVs). Unfortunately, the acceptance of EVs for mobility is affected by its poor range per charge. Thus, energy optimization and waste energy recuperation are currently in need. A promising method to recover energy that is lost during vehicle deceleration is regenerative braking, which extends the range of a vehicle by recovering the kinetic energy from braking and using it to recharge the battery. However, the intensity of the charging–discharging rate and the operating temperature of lithium–ion (Li–ion) batteries make them vulnerable to failure, making the rate of current delivered to the battery by regenerative braking a serious concern. Therefore, the focus of this review article is on how regenerative braking affects battery life and the precautions being taken to safeguard the battery against increased charge during regenerative braking. In this review paper, various research articles are referred to in order to examine how regenerative braking affects battery life. It is concluded that charging current obtained from long-term regenerative braking is the prominent factor in battery deterioration, regardless of the current intensity. Additionally, the rate of lithium plating is increased if the temperature and state of charge (SOC) are outside of the ideal range. By lowering the depth of discharge (DOD) and using shorter recharging times, higher levels of regenerative braking will extend a battery’s lifecycle even at high SOC and temperature.

We investigated the influence of precession angle, energy filtering and sample thickness on the structural parameters of amorphous SiO2 thin films from the electron reduced density functions obtained by applying precession electron diffraction. The results demonstrate that the peak positions in the electron reduced density functions are generally insensitive to the studied experimental conditions, while both precession angle and energy filtering influence peak heights considerably. It is also shown that introducing precession with small angles of up to 2 degrees and energy filtering results in higher coordination numbers that are closer to the expected theoretical values of 4 and 2 for Si and O, respectively, for data obtained from a thicker sample.

Identifying k ey frames is the first and necessary step before solving the variety of other B haratanatyam problems. The paper aims to partition the momentarily stationary frames (key frame s) from this dance video’s motion frames. The proposed key frame s (KFs) localization is novel, simple, and effective compared to the existing dance video analysis methods. It is distinctive from standard KFs detection algorithms as used in other human motion videos. In the dance’s basic structure, the occurrence of KFs during performances is often not completely stationary and varies with the dance form and the performer. Hence, it is not easy to decide a global threshold (on the quantum of motion) to work across dancers and performances. The earlier approaches try to compute the threshold iteratively. However, the novelty of the paper is: (a) formulating an adaptive threshold, (b) adopting Machine Learning (ML) approach and, (c) generating the effective feature by combining three frame differencing and bit-plane technique for the KF detection. In ML, we use Support Vector Machine (SVM) and Convolutional Neural Network (CNN) as the classifiers. The proposed approaches are also compared and analyzed with the earlier approaches. Finally, the proposed ML techniques emerge as a winner with around 90% accuracy.

Introduction: Diphtheria caused by toxigenic Corynebacterium diphtheriae is an acute respiratory infection characterised by pseudomembrane formation in the throat. Although diphtheria is often reported sporadically across India, molecular characterisation of C.diphtheriae strains could play a crucial role in epidemiological investigations. Aim: To perform molecular characterisation of Corynebacterium diphtheriae isolates of faucial diphtheria cases from Assam, North-East India utilising Multi-Locus Sequence Typing (MLST). Materials and Methods: In this cross-sectional study, three isolates were obtained from three different cluster of cases that occurred across two districts of Assam, India for a period from November 2019 to June 2020. The MLST of these three C.diphtheriae isolates were performed in Multidisciplinary Research Unit of Assam Medical College and Hospital by using the 7-gene MLST alleles of C.diphtheriae to determine the Sequence Types (ST). Results: The MLST of the three isolates of this study revealed two distinct STs, ST-588 and ST-576 with multi-clonal lineages with ST-466, reported in C.diphtheriae strains of North Kerala and ST-301 related strains of Bangladesh, respectively. Conclusion: In spite of frequent reports of diphtheria cases from Assam, molecular typing of the C.diphtheriae strains found in North-Eastern region of India has not yet been performed. This is one of the initial investigations from this region of India to use MLST for typing C.diphtheriae strains. Therefore, studies related to molecular characterisation of C.diphtheriae strains found throughout India could immensely help in determining the clonality and diversity existing among these strains.

The present study was conducted to compare the stemness and morphobiometry of spermatogonial stem cells (SSCs) from the Doom pig on different days of culture (9th, 30th and 65th day) for the development of long-term culture method. The testes from 7-15-day old piglets were collected and two-step enzymatic digestion was used to isolate SSCs. Before in vitro culture of SSC-like cells on the Sertoli cell feeder layer, the cells were enriched by differential plating and Percoll density gradient centrifugation. The isolated SSCs were characterised by alkaline phosphatase and immunofluorescence staining and qPCR analysis of SSC specific marker genes. Stemness was compared based on the expression of different SSC specific marker genes. The putative spermatogonial stem cells (PSSCs) from all the days of culture were found to be positive for alkaline phosphatase and immunofluorescence staining. The results from qPCR analysis showed that PSSCs were positive for SSC marker genes, though their expression decreased gradually from day 9 to day 65 of culture. The shape of the cells was found to change from compact round or oval to amorphous shape on day 65 of culture. Colony diameter ranged from 68.92 ± 1.20 µm (day 9) to 213.53 ± 12.52 µm (day 65) and differed significantly from each other. The number of colonies on day 65 of culture was significantly lower than on days 9 and 30. These results suggest that the enriched SSCs from Doom pigs can be maintained up to two months in vitro in the present culture system.

Pollution due to plastic waste is a major concern for the eco-friendly environment. These manmade waste release various toxins to the environment, which are harmful to mankind. To encounter the effect of the synthetic materials, bio fibre based polymer composites made from bio fibres (jute, hemp, flax, cotton etc.) are emerging as a suitable replacement as bio fibre based polymer composites are low cost, light in weight and eco-friendly. Green Economy is an important aspect of the environment that helps to promote environmentally friendly nature. The present article gives an insight into the various types of bio fibres available along with their mechanical and chemical properties. A detailed discussion on recycling and disposal mechanism and how the use of bio fibre based polymer composites will lead to a sustainable environment in the coming years has been included. At last, the future market trend and potential applications of bio fibre based polymer composites have also been addressed in this article.

During the last two decades, three-dimensional electron diffraction (3D ED) has undergone a renaissance, starting with the introduction of precession (Precession Electron Diffraction Tomography, PEDT) that led to variations on the idea of collecting as much of the diffraction space as possible in order to solve crystal structures from sub-micron sized crystals. The most popular of these acquisition methods is based on the continuous tilting/rotation of the crystal (so-called Microcrystal Electron Diffraction, MicroED) akin to the oscillating crystal method in X-ray crystallography, which was enabled by the increase of sensitivity and acquisition speed in electron detectors. While 3D ED data is more complex than the equivalent X-ray data due to the higher proportion of dynamical scattering, the same basic principles of what is required in terms of data quality and quantity in order to solve a crystal structure apply; high completeness, high data resolution and good signal-to-noise statistics on measured reflection intensities. However, it may not always be possible to collect data in these optimum conditions, the most common limitations being the tilt range of the goniometer stage, often due to a small pole piece gap or the use of a non-tomography holder, or the position of the sample on the TEM grid, which may be too close to a grid bar and then the specimen of interest becomes occluded during tilting. Other factors that can limit the quality of the acquired data include the limited dynamic range of the detector, which can result on truncated intensities, or the sensitivity of the crystal to the electron beam, whereby the crystallinity of the particle is changing under the illumination of the beam. This limits the quality and quantity of the measured intensities and makes structure analysis of such data challenging. Under these circumstances, traditional approaches may fail to elucidate crystal structures, and global optimization methods may be used here as an alternative powerful tool. In this context, this work presents a systematic study on the application of a global optimization method to crystal structure determination from 3D ED data. The results are compared with known structure models and crystal phases obtained from traditional ab initio structure solution methods demonstrating how this strategy can be reliably applied to the analysis of partially complete 3D ED data.

The principal objective of this study is to employ non-destructive broadband dielectric spectroscopy/impedance spectroscopy and machine learning techniques to estimate the moisture content in FRP composites under hygrothermal aging. Here, classification and regression machine learning models that can accurately predict the current moisture saturation state are developed using the frequency domain dielectric response of the composite, in conjunction with the time domain hygrothermal aging effect. First, to categorize the composites based on the present state of the absorbed moisture supervised classification learning models (i.e., quadratic discriminant analysis (QDA), support vector machine (SVM), and artificial neural network-based multilayer perceptron (MLP) classifier) have been developed. Later, to accurately estimate the relative moisture absorption from the dielectric data, supervised regression models (i.e., multiple linear regression (MLR), decision tree regression (DTR), and multi-layer perceptron (MLP) regression) have been developed, which can effectively estimate the relative moisture absorption from the dielectric response of the material with an R¬2 value greater than 0.95. The physics behind the hygrothermal aging of the composites has then been interpreted by comparing the model attributes to see which characteristics most strongly influence the predictions.

BackgroundThe banana (Musa spp.) plant produces elongated and edible fruit. The two main parthenocarpic species of banana are Musa accuminata Colla and Musa balbisiana Colla. There are several health-promoting and disease-preventing effects of Musa accuminata Colla, which are attributed to its important bioactive compounds, including phenolics, carotenoids, biogenic amines, phytosterols, and volatile oils, found in the stem, fruit, pseudostem, leaf, flower, sap, inner trunk, root, and inner core. Banana possesses numerous pharmacological activities, such as antioxidant, immunomodulatory, antimicrobial, antiulcerogenic, hypolipidemic, hypoglycemic, leishmanicidal, anthelmintic, and anticancer properties. Various individual studies have reported anticancer effects of different components of the banana plant. However, according to our understanding, an up-to-date, systematic, and critical analysis of existing scientific results has not yet been carried out.ObjectivesThis review aims to include a thorough assessment of banana and its phytochemicals for cancer prevention and therapy with a focus on cellular and molecular mechanisms of action.MethodsThe available research studies on anticancer activities of banana extracts, fractions and pure compounds were collected using various scholarly databases, such as PubMed, ScienceDirect, and Scopus, based on predetermined selection criteria.ResultsVarious banana extracts, fractions, and phytoconstituents, including ferulic acid, protocatechualdehyde, 2-pentanone, 4-epicyclomusalenone, cycloeucalenol acetate, and chlorogenic acid, have been shown to exhibit cancer preventative and anticancer activities in breast, cervical, colorectal, esophageal, hepatic, oral, prostate, and skin cancers. Bioactive components present in bananas have exhibited antiproliferative, cell cycle arrest-inducing, apoptotic, anti-adhesive, anti-invasive, and antiangiogenic effects through modulation of diverse, dysregulated oncogenic signaling pathways.ConclusionBased on the critical analysis of available literature, banana products and phytoconstituents show enormous potential for future development of drugs for cancer prevention and therapy. However, more mechanistic studies and well-designed clinical trials should be performed to establish its efficacy.

In this current work an open-source 2D Digital Image Correlation (DIC) tool, RealPi2dDIC, is presented to monitor in situ full field deformation and strain responses of structures during loading. This software is coded in Python3 and uses Raspberry Pi as the computation and Pi camera as the imaging device. This low-cost approach to in situ DIC analysis enables its application in a broad field of research and industry problems where 2D strain field tensor is one of the principal interests of study. This code is provided with an interactive user interface (UI) making it user friendly and easy-to-use. Furthermore, RealPi2dDIC offers a simple software architecture which can be adopted, modified and extended to suit users’ purpose.

Thermal conductive gap filler materials are used as thermal interface materials (TIMs) in electronic devices due their numerous advantages, such as higher thermal conductivity, ease of use, and conformity. Silicone is a class of synthetic materials based on a polymeric siloxane backbone which is widely used in thermal gap filler materials. In electronic packages, silicone-based thermal gap filler materials are widely used in industries, whereas silicone-free thermal gap filler materials are emerging as new alternatives for numerous electronics applications. Certainly, characterization of these TIMs is of immense importance since it plays a critical role in heat dissipation and long-term reliability of the electronic packages. Insubstantial studies on the effects of various chemical compounds on the properties of silicone-based and silicone-free TIMs has led to this study, which focuses on the effect of thermal aging on the mechanical, thermal, and dielectric properties of silicone-based and silicone-free TIMs and the chemical compounds that cause the changes in properties of these materials. Characterization techniques such as dynamic mechanical analysis (DMA), thermomechanical analysis (TMA), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), and broadband dielectric spectroscopy (BbDS) are used to study the mechanical, thermal, and dielectric characteristics of these TIMs, which will guide towards a better understanding of the applicability and reliability of these TIMs. The experiments demonstrate that upon thermal aging at 125 °C, the silicone-free TIM becomes hard, while silicone-based TIM remains viscoelastic, which indicates its wide applicability to higher temperature applications for a long time. Though silicone-based TIM displays better mechanical and thermal properties at elevated temperatures, dielectric properties indicate low conductivity for silicone-free TIM, which makes it a better candidate for silicone-sensitive applications where higher electric insulation is desired.

As an alternative photosensitizer in dye-sensitized solar cells, bovine serum albumin (BSA) (a nonhazardous protein) was used in the synthesis of colloidal CdS nanoparticles (NPs). This system has been employed to replace the commonly used N719 dye molecule. Various nanostructured forms of ZnO, namely, nanorod and nanoparticle-based photoanodes, have been sensitized with colloidal CdS NPs to evaluate their effective performance towards quantum dot sensitized solar cells (QDSSCs). A polysulphide (Sx2−)-based electrolyte and CuxS counter electrode were used for cell fabrication and testing. An interesting improvement in the performance of the device by imposing nanorods as a scattering layer on a particle layer has been observed. As a consequence, a maximum conversion efficiency of 1.06% with an open-circuit voltage (VOC) of 0.67 V was achieved for the ZnO nanorod/nanoparticle assembled structure. The introduction of ZnO nanorods over the nanoparticle led to a significant enhancement of the overall efficiency compared to the corresponding bare nanoparticles.

This research work focuses on the development of a piezoelectric magnetostrictive smart composite with advanced sensing capability. The composite piezoelectric property is achieved from the dispersion of single-walled carbon nanotubes (SWCNTs) and the magnetostrictive property from Terfenol-D nanoparticles. Finite element analysis (FEA) is used to examine the feasibility of modelling the piezoelectric (change in electric field) and magnetostrictive (change in magnetic field) self-sensing responses in the presence of applied stress. The numerical work was coupled with a series of mechanical tests to characterize the piezoelectric response, magnetostriction response and mechanical strength. Tensile tests of the composite samples manufactured as is (virgin), samples with SWCNTs, samples with Terfenol-D nanoparticles and samples with both SWCNTs and Terfenol-D nanoparticles were conducted. It was observed that an increase in volume fraction of Terfenol-d nanoparticles increases the change in magnetization, therefore increasing voltage response up to the point of saturation. The optimum change in amplitude was observed with 0.35% volume fraction of Terfenol-D nanoparticles. A constant ratio of SWCNTs was maintained, and maximum change in electrical resistance was at 7.4%. Fracture toughness for the samples with all nanoparticles was explored, and the results showed improved resistance to crack propagation.

Paragonimiasis or lung fluke infection is one of the neglected tropical parasitic disease which is found worldwide. Several endemic foci have been discovered in the Northeast India. Pulmonary paragonimiasis presenting with haemoptysis is generally mistaken for pulmonary tuberculosis. Herein, we present a case of pulmonary paragonimiasis, which initially presented with haemoptysis and remained undiagnosed for two years. The patient was treated with Praziquantel 25mg/kg thrice daily for two days along with the supportive care. Subsequently, on follow up after three months the patient had improved with no fever and cough.

Estimation of the flow generated in the Brahmaputra river basin is important for establishing an effective flood prediction and warning services as well as for water resources assessment and management. But this is a data scarce region with few and unevenly distributed hydrometeorological stations. Five high-resolution satellite rainfall products (CPC RFE2.0, RFE2.0-Modified, CMORPH, GSMaP, and TRMM 3B42) were evaluated at different spatial and temporal resolutions (daily, dekadal, monthly, and seasonal) with observed rain gauge data from 2004 to 2006 to determine their ability to fill the data gap and suitability for use in hydrological and water resources management applications. Grid-to-grid (G-G) and catchment-to-catchment (C-C) comparisons were performed using the verification methods developed by the International Precipitation Working Group (IPWG). Comparing different products, RFE2.0-Modified, TRMM 3B42, and CMORPH performed best; they all detected heavy, moderate, and low rainfall but still significantly underestimated magnitude of rainfall, particularly in orographically influenced areas. Overall, RFE2.0-Modified performed best showing a high correlation coefficient with observed data and low mean absolute error, root mean square error, and multiple bias and is reasonably good at detecting the occurrence of rainfall. TRMM 3B42 showed the second best performance. The study demonstrates that there is a potential use of satellite rainfall in a data scarce region.

Association between proteins and DNA is crucial for many vital cellular functions such as gene transcription, DNA replication and recombination, repair, segregation, chromosomal stability, cell cycle progression, and epigenetic silencing. It is important to know the genomic targets of DNA-binding proteins and the mechanisms by which they control and guide gene regulation pathways and cellular proliferation. Chromatin immunoprecipitation (ChIP) is an important technique in the study of protein-gene interactions. Using ChIP, DNA-protein interactions are studied within the context of the cell. The basic steps in this technique are fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA. Although ChIP is a very versatile tool, the procedure requires the optimization of reaction conditions. Several modifications to the original ChIP technique have been published to improve the success and to enhance the utility of this procedure. This review addresses the critical parameters and the variants of ChIP as well as the different analytical tools that can be combined with ChIP to enable better understanding of DNA-protein interactions in vivo.

Wetlands provide a diverse range of ecosystem services supporting livelihoods of many people. Despite their value, wetlands are continuously being degraded. There is scant information on individual wetlands, people’s dependency and their exploitation at a local scale. We therefore assessed wetland ecosystem services, the drivers of change and impacts of those drivers on ecosystem services and people’s dependency through a case study of the Maguri-Motapung Beel wetlands of Assam, India. Both qualitative and quantitative data were collected through household surveys, focus group discussions, key informant interviews and community workshops. The analyses showed a total of 29 ecosystem services, and high dependency on these with five out of seven livelihood strategies sourced from ecosystem services. Over-exploitation of wetland resources and siltation were reported as the major direct drivers of change with impacts on both ecosystem services and people’s livelihoods. Drastic decreases in availability of thatch, fish stocks, fodder and tourism were observed. This suggests that there is an urgent need for a comprehensive participatory management plan. Actions are needed to maintain the Maguri-Motapung Beel wetlands and the flow of services in order to sustain people’s livelihoods in the area. With an estimated 50% global loss of wetlands in the last century and the loss of 5,000 square kilometers a year in Asia alone, the loss of ecosystem services and livelihood impacts shown in our study may be typical of what is occurring in the region and perhaps globally.

Miller Fisher syndrome (MFS) is an uncommon variant of Guillain-Barré syndrome (GBS). It is characterized by external ophthalmoplegia, ataxia, and areflexia. The incidence of MFS as a proportion of GBS was reported to be 1 to 5 % in western countries and considerably higher in Eastern Asia i.e. 19% in Taiwan and 25% in Japan. Here we report the clinical features of a patient who initially presented with ataxia then subsequently developed limb weakness, areflexia and ophthalmoplegia. CSF study and NCV study supported our clinical diagnosis. Patient was managed conservatively. No intravenous immunoglobulin was given but the patient gradually improved in symptoms including power, ataxia, ophthalmoparesis. After one month the patient was discharged from hospital with complete recovery. DOI: http://dx.doi.org/10.3329/bsmmuj.v5i1.11028 BSMMU J 2012; 5(1):69-71

Background: The 12-lead ECG is the primary clinical tool for non-invasive assessment of cardiac electrical function. Before any surgery, ECG is commonly used in pre-operative check-up. Therefore pre-operative check-up of large number of people can be a valuable tool for accurate estimates of the prevalence of ECG abnormalities of general population. Objectives: To observe the extent of ECG changes in a group of population undergoing ENT surgery and to describe the prevalence of changes in relation to age and sex. Methods: 704 consecutive adult stable patients were included between age of 20 – 60 years without previously diagnosed case of any other systemic diseases who came to this hospital for elective surgical procedures and were investigated with new ECG for pre-operative check-up in private Hospital between January 201 to December 2010. Results: Total number of ECG recordings were 704; out of them 479 were male & 225 were female. Among 704 ECG recording 486(69.03%) were normal. The number of old myocardial infarction (MI) was in 36 cases (5.11%). Cardiac Ischaemia observed by ST depressions/T inversion was present in 15 cases (2.13%). Conclusion: The observation of the study is concludes that nearly 70% of all asymptomatic people (between 20 – 60 years) possessing normal ECG but Ischaemic changes (like Q wave/ST depression & T inversion/ LBBB) was present in about 8% cases. ECG changes of IHD (Ischaemic Heart Disease) increases with age and male groups at higher risk of developing IHD. Key Words: ECG; Pre-operative Check-up; Myocardial Infarction (MI). DOI: http://dx.doi.org/10.3329/bsmmuj.v4i2.8630 BSMMU J 2011; 4(2):56-59

Abstract Attaining green environment for various machining processes has now caught the attention of many manufacturing industries. The input parameters involved in those machining processes are mainly responsible for achieving the desired performance as they are directly related to the process outputs. Hence, proper selection of the input process parameters becomes vital for having sustainable machining environment. In this paper, an integrated application of step-wise weight assessment ratio analysis (SWARA) and combined compromise solution (CoCoSo) methods is presented to identify the optimal parametric combinations of two green dry milling processes. In the first example, cutting speed, depth of cut, feed rate and nose radius are treated as the input parameters, while power factor, electric consumption and surface roughness are the responses. On the other hand, in the second example, cutting speed, feed rate, depth of cut and width of cut, and surface roughness, active cutting energy and material removal rate are respectively considered as the input parameters and responses. Instead of considering equal weights, SWARA method assigns relative subjective importance to the responses based on the preference set by the decision-makers, while CoCoSo ranks the experimental trials from the best to the worst. The derived optimal parametric settings are finally analyzed using the developed regression equations. It is observed that SWARA-CoCoSo method outperforms the other popular optimization techniques in identifying the best parametric intermixes for the green dry milling processes for having improved machining performance with minimal environmental effect.

Abstract As the COVID-19 infection continues to ravage the world, the advent of an efficient as well as the economization of the existing RT-PCR based detection assay essentially can become a blessing in these testing times and significantly help in the management of the pandemic. This study demonstrated an innovative and rapid corroboration of COVID-19 test based on innovative multiplex PCR. An assessment of optimal PCR conditions to simultaneously amplify the SARS-CoV-2 genes E, S and RdRp has been made by fast-conventional and HRM coupled multiplex real-time PCR using the same sets of primers. All variables of practical value were studied by amplifying known target-sequences from ten-fold dilutions of archived positive samples of COVID-19 disease. The multiplexing with newly designed E, S and RdRp primers have shown an efficient amplification of the target region of SARS-CoV-2. A distinct amplification was observed in 37 min using thermal cycler while it took 96 min in HRM coupled real time detection using SYBR green over a wide range of template concentrations. Our findings revealed decent concordance with other commercially available detection kits. This fast HRM coupled multiplex real-time PCR with SYBR green approach offers rapid and sensitive detection of SARS-CoV-2 in a cost-effective manner apart from the added advantage of primer compatibility for use in conventional multiplex PCR. The highly reproducible novel approach can propel extended applicability for developing sustainable commercial product besides providing relief to a resource limited setting.

In the context of supply chain management, supplier selection can be defined as the process by which organizations score and evaluate a range of alternative suppliers to choose the best possible one who can provide superior quality of raw materials at cheaper rate and lesser lead time. It is a decision making process with multiple trade-offs between various conflicting criteria which in turn helps the organizations identify the suitable suppliers that would establish a robust supply chain assisting in maintaining a competitive edge. The main objective of supplier selection is thus focused on reducing purchase risk, maximizing overall value to the organization, and developing closeness and long-term relationships between the suppliers and the organization. In this paper, while selecting the most suitable supplier for gearboxes in an Indian iron and steel industry, assessments of three decision makers on the performance of five candidate suppliers with respect to five evaluation criteria are first aggregated using rough numbers. The definitive distances of those rough numbers are then treated as the inputs to a 25 full-factorial design plan with the corresponding multi-attributive border approximation area comparison (MABAC) scores as the output variables. Finally, a design of experiments (DoE)-based metamodel is formulated to interlink the computed MABAC scores with the considered criteria. The competing suppliers are ranked based on this rough-MABAC-DoE-based metamodel, which also easies out the computational steps when new suppliers are included in the decision making process.

Nanosafety has been a subject of scrupulous indagation attributed to the ambiguity in terms of harmonizing and perceiving the nano risk evaluation. Nanotoxicity is an emanate pigeonhole of nanotechnology. The burgeoning of commercial products grafted with engineered nanomaterials has been escalated exponentially. Inevitably, the profile of nanomaterials and their repercussions on the ecosystem and mankind must be meticulously assessed. The research fraternity has to evolve innovations to prognosticate the unsought nuisance that does not prevail yet in the frame of reference with nanotoxicity due to the proliferation in the utilization of nanomaterials for consumers' product. Besides, it is imperative to contemplate whether the size is the only characteristic that matters for the detrimental impacts of nanoscale materials. The design and development of safe nanomaterials substantially in drug discovery could be a benchmark. As safety assessment is of utmost importance, therefore it is pre-eminent to lessen animal analysis by the inception of auxiliary or prognostic in silico and in vitro methods which has become a precedence. To perceive the paradigms in nanotoxicity, this robust indagation will provide comprehensive exploration in clearance, kinetics, metabolism, mapping of fate, and physical properties of toxicity of nanomaterials. First, the different characteristics of engineered nanomaterials linked to different toxicological effects is presented. Accordingly, the mechanism by which nanoparticles exhibit toxicity is delineated to aid in nanoparticle redesign to reduce their impact. Second, an overview of the physiochemical techniques and biochemical methodologies adopted for characterization of nanoparticles for testing and screening their toxicological effects is presented. Third, adverse impact of nanoparticle toxicity on human and environment is highlighted. Finally, the challenging pathways and significant strategies to eradicate the risk of nanotoxocity is addressed to proffer a solid rationale in translating the promises of nanotechnology.

Introduction: Pneumonia is the single largest infectious cause of death in children worldwide. Aetiology of pneumonia can be identified using multiple diagnostic tools including culture, serology and Polymerase Chain Reaction (PCR); common pathogens include Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, some atypical bacteria like Mycoplasma pneumoniae and Chlamydophila pneumoniae. Aim: To find out the bacteriological agents causing Community Acquired Pneumonia (CAP) in under five year children and to compare the conventional culture and PCR in identifying the pathogen. Materials and Methods: This cross-sectional study was undertaken in the Department of Microbiology and Department of Paediatrics in a tertiary care centre of Assam, India, between March 2016 to September 2018. The study was undertaken with 200 under five year old children who were clinically diagnosed as CAP. Oropharyngeal (OP) swabs and blood culture were processed for bacteriological culture. PCR assay of OP swabs for Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus etc., including atypical bacteria like Mycoplasma pneumoniae and Chlamydophila pneumoniae were performed. Data entry, database management and statistical analysis were performed using Epi-Info software version 7.0. Results: A total of 200 subjects were included in the present study with a male:female ratio of 1.63:1. Most of the study subjects were

During March 13–June 23, 2018, anthrax-like cutaneous lesions attributed to the Bacillus cereus group of organisms developed in 12 newborns in India. We traced the source of infection to the healthcare kits used for newborn care. We used multilocus sequence typing to characterize the 19 selected strains from various sources in hospital settings, including the healthcare kits. This analysis revealed the existence of a genetically diverse population comprising mostly new sequence types. Phylogenetic analysis clustered most strains into the previously defined clade I, composed primarily of pathogenic bacilli. We suggest that the synergistic interaction of nonhemolytic enterotoxin and sphingomyelinase might have a role in the development of cutaneous lesions. The infection was controlled by removing the healthcare kits and by implementing an ideal housekeeping program. All the newborns recovered after treatment with ciprofloxacin and amikacin.

Abstract Background Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. With the rise in number of annotation strategies, next-generation sequencing methods have provided further understanding the functions of HPs. Results In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. In this study, we introduced three more classifiers to our annotation system, viz. pseudogenes linked to HPs, homology modelling and non-coding RNAs associated to HPs. We discuss the challenges and performance of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81.08 to 97.67), Naive Bayes (54.05 to 96.67), Decision tree J48 (67.57 to 97.00), and SMO_npolyk (59.46 to 96.67). Conclusion With the introduction of three new classification features, the performance of the nine-point classification scoring schema has an improved accuracy to functionally annotate the HPs.

Molecular interaction of aromatic dyes with biological macromolecules are important for the development of minimally invasive disease diagnostic biotechnologies. In the present work, we have used Toluidine Blue (TB) as a model dye, which is a well-known staining agent for the diagnosis of oral cancer and have studied the interaction of various biological macromolecules (protein and DNA) with the dye at different pH. Our spectroscopic studies confirm that TB interacts with Human Serum Albumin (HSA), a model protein at very high pH conditions which is very hard to achieve physiologically. On the other hand, TB significantly interacts with the DNA at physiological pH value (7.4). Our molecular studies strengthen the understanding of the Toluidine Blue staining of cancer cells, where the relative ratio of the nucleic acids is higher than the normal intracellular content. We have also developed a non-invasive, non-contact spectroscopic technique to explore the possibility of quantitatively detecting oral cancer by exploiting the interaction of TB with DNA. We have also reported development of a prototype named “Oral-O-Scope” for the detection of Oral cancer and have carried out human studies using the prototype.

Abstract We present new transmission electron microscopy (TEM) based electron diffraction characterization techniques (orientation imaging combined with 3D precession electron diffraction tomography-ADT) applied on cultural heritage materials. We have determined precisely unit cell parameters, crystal symmetry, atomic structure, and orientation/phase mapping of various pigment/opacifier crystallites at nm scale which are present in green and white Roman glass tesserae. Such TEM techniques can be an alternative to Synchrotron based techniques, and allow to distinguish accurately at nm scale between different crystal structures even in cases of same/very close chemical composition, where is also possible to visualize between different crystal orientations and amorphous/crystalline phases. This study additionally demonstrates that although opacifiers in green and white tesserae are found to have average Pb2Sb2O7 cubic and CaSb2O6 trigonal structures, their pyrochlore related framework can host many other elements like Cu, Ca, Fe through ionic exchanges at high firing temperatures which in turn may also contribute to the tesserae colour appearance.

Due to various added advantages over the conventional material removal processes, non-traditional machining (NTM) processes have now been widely applied in different manufacturing industries. To achieve the desired response values, it is always recommended to operate these NTM processes at their optimal parametric settings. Various single response optimization techniques are already available to determine the optimal combinations of NTM process parameters for achieving maximum or minimum value of a single response. In this paper, a multivariate quality loss function approach is adopted for simultaneous optimization of responses for three NTM processes. It is observed that this approach outperforms the other multi-response optimization techniques, like desirability function, distance function and mean squared error methods with respect to the achieved re-sponse values. With modification of the corresponding objective function and constraints of the de-veloped non-linear programming problem, it can be effectively applied to any non-traditional as well as conventional machining process as a multi-objective optimization tool.

Recent studies have identified a number of oncogenic histone point mutations in different cancers. Here the authors provide evidence that H3.3 G34R substitution mutation, which is found in paediatric gliomas, causes changes in H3K9me3 and H3K36me3 by interfering with the KDM4 family of K9/K36 demethylases.

The crystal structure of naturally occurring zaccariniite (RhNiAs) has been studied in Transmission Electron Microscopy (TEM) with variable angle Precession Electron Diffraction (PED) techniques. The analysis of the data has yielded tetragonal cell parameters of 3.86, 3.86, 6.77 Å and space group of P4/nmm for the basic structure, and its constituent atom positions for Ni, As and Rh were determined as well by ab-initio structure resolution method. The data is related to “Structural characterization and ab-initio resolution of natural occurring zaccariniite (RhNiAs) by means of Precession Electron Diffraction” (Roqué Rosell et al., 2019). Keywords: PED, RhNiAs, Zaccariniite, Crystallographic infromation file

Silica has many industrial (i.e., glass formers) and scientific applications. The understanding and prediction of the interesting properties of such materials are dependent on the knowledge of detailed atomic structures. In this work, amorphous silica subjected to an accelerated alkali silica reaction (ASR) was recorded at different time intervals so as to follow the evolution of the structure by means of high-resolution transmission electron microscopy (HRTEM), electron energy loss spectroscopy (EELS), and electron pair distribution function (e-PDF), combined with X-ray powder diffraction (XRPD). An increase in the size of the amorphous silica nanostructures and nanopores was observed by HRTEM, which was accompanied by the possible formation of Si–OH surface species. All of the studied samples were found to be amorphous, as observed by HRTEM, a fact that was also confirmed by XRPD and e-PDF analysis. A broad diffuse peak observed in the XRPD pattern showed a shift toward higher angles following the higher reaction times of the ASR-treated material. A comparison of the EELS spectra revealed varying spectral features in the peak edges with different reaction times due to the interaction evolution between oxygen and the silicon and OH ions. Solid-state nuclear magnetic resonance (NMR) was also used to elucidate the silica nanostructures.

Organic and biological compounds (especially those related to the pharmaceutical industry) have always been of great interest for researchers due to their importance for the development of new drugs to diagnose, cure, treat or prevent disease. As many new API (active pharmaceutical ingredients) and their polymorphs are in nanocrystalline or in amorphous form blended with amorphous polymeric matrix (known as amorphous solid dispersion—ASD), their structural identification and characterization at nm scale with conventional X-Ray/Raman/IR techniques becomes difficult. During any API synthesis/production or in the formulated drug product, impurities must be identified and characterized. Electron energy loss spectroscopy (EELS) at high energy resolution by transmission electron microscope (TEM) is expected to be a promising technique to screen and identify the different (organic) compounds used in a typical pharmaceutical or biological system and to detect any impurities present, if any, during the synthesis or formulation process. In this work, we propose the use of monochromated TEM-EELS, to analyze selected peptides and organic compounds and their polymorphs. In order to validate EELS for fingerprinting (in low loss/optical region) and by further correlation with advanced DFT, simulations were utilized.