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Research Methodology for Social Sciences provides guidelines for designing and conducting evidence-based research in social sciences and interdisciplinary studies using both qualitative and quantitative data. Blending the particularity of different sub-disciplines and interdisciplinary nature of social sciences, this volume: Provides insights on epistemological issues and deliberates on debates over qualitative research methods; Covers different aspects of qualitative research techniques and evidence-based research techniques, including survey design, choice of sample, construction of indices, statistical inferences and data analysis; Discusses concepts, techniques and tools at different stages of research, beginning with the design of field surveys to collect raw data and then analyse it using statistical and econometric methods. With illustrations, examples and a reader-friendly approach, this volume will serve as a key reference material for compulsory research methodology courses at doctoral levels across different disciplines, such as economics, sociology, women’s studies, education, anthropology, political science, international relations, philosophy, history and business management. This volume will also be indispensable for postgraduate courses dealing with quantitative techniques and data analysis.

This article offers a descriptive qualitative analysis of 3 second-year pre-service teachers' statistical reasoning about the mean. Twenty-six pre-service teachers were tested using an open-ended problem where they were expected to analyze a method in finding the mean of a data. Three of their test results are selected to be analyzed. The results suggest that the pre-service teachers did not use context to develop the interpretation of mean. Therefore, this article also offers strategies to promote statistical reasoning about mean that use various contexts.

The present investigation demonstrated pretreatment of lignocellulosic biomass rice straw using natural deep eutectic solvents (NADESs), and separation of high-quality lignin and holocellulose in a single step. Qualitative analysis of the NADES extract showed that the extracted lignin was of high purity (>90 %), and quantitative analysis showed that nearly 60 ± 5 % ( w / w ) of total lignin was separated from the lignocellulosic biomass. Addition of 5.0 % ( v / v ) water during pretreatment significantly enhanced the total lignin extraction, and nearly 22 ± 3 % more lignin was released from the residual biomass into the NADES extract. X-ray diffraction studies of the untreated and pretreated rice straw biomass showed that the crystallinity index ratio was marginally decreased from 46.4 to 44.3 %, indicating subtle structural alterations in the crystalline and amorphous regions of the cellulosic fractions. Thermogravimetric analysis of the pretreated biomass residue revealed a slightly higher T dcp (295 °C) compared to the T dcp (285 °C) of untreated biomass. Among the tested NADES reagents, lactic acid/choline chloride at molar ratio of 5:1 extracted maximum lignin of 68 ± 4 mg g −1 from the rice straw biomass, and subsequent enzymatic hydrolysis of the residual holocellulose enriched biomass showed maximum reducing sugars of 333 ± 11 mg g −1 with a saccharification efficiency of 36.0 ± 3.2 % in 24 h at 10 % solids loading.

Objectives To compare image noise and sharpness of vessels, liver, and muscle in lower extremity CT angiography between “adaptive statistical iterative reconstruction-V” (ASIR-V) and deep learning reconstruction “TrueFidelity” (TFI). Methods Thirty-seven patients (mean age, 65.2 years; 32 men) with lower extremity CT angiography were enrolled between November and December 2019. Images were reconstructed with two ASIR-V (blending factor of 80% and 100% (AV-100)) and three TFI (low-, medium-, and high-strength-level (TF-H) settings). Two radiologists evaluated these images for vessels (aorta, femoral artery, and popliteal artery), liver, and psoas muscle. For quantitative analyses, conventional indicators (CT number, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)) and blur metric values (indicating the degree of image sharpness) of selected regions of interest were determined. For qualitative analyses, the degrees of quantum mottle and blurring were assessed. Results The higher the blending factor in ASIR-V or the strength in TFI, the lower the noise, the higher the SNR and CNR values, and the higher the blur metric values in all structures. The SNR and CNR values of TF-H images were significantly higher than those of AV-80 images and similar to those of AV-100 images. The blur metric values in TFI images were significantly lower than those in ASIR-V images ( p < 0.001), indicating increased sharpness. Among all the investigated image procedures, the overall qualitative image quality was best in TF-H images. Conclusion TF-H was the most balanced image in terms of image noise and sharpness among the examined image combinations. Key Points • Deep learning image reconstruction “TrueFidelity” is superior to iterative reconstruction “ASIR-V” regarding image noise and sharpness. • The high-strength “TrueFidelity” approach generated the best image quality among the examined image reconstruction procedures. • In iterative and deep learning CT image reconstruction, the higher the blending and strength factors, the lower the image noise and the poorer the image sharpness.

Many detrimental effects on the environment, economy, and society are associated with the structure and practices of food systems around the world. While there is increasing agreement on the need for substantive change in food systems towards sustainability, divergent perspectives exist on what the appropriate points of intervention and strategies to achieve such change are. Change in diets and nutrition, the importance of social food movements, and sustainable farming practices are all disparately featured in the literature; yet, there is little effort to compare and integrate these perspectives. This review offers a comprehensive overview of perspectives on food systems change towards sustainability. We discern where there is convergence and assess how the literature reflects emergent theory on sustainability transformation. We analyzed more than 200 peer-reviewed articles employing an approach that combines quantitative and qualitative analysis. First, we performed a semantic hierarchical cluster analysis of the full texts to identify thematic clusters representing different perspectives on sustainability transformations and transitions of food systems. Second, we conducted a qualitative text analysis for representative articles of each cluster to examine how deep changes in the food system are conceptualized. We identified five distinct approaches to food systems change that are currently discussed, i.e. Alternative food movements, Sustainable diets, Sustainable agriculture, Healthy and diverse societies, and Food as commons. Each approach provides a nuanced perspective on identified sustainability problems, envisioned sustainable food systems, and proposed actions to change food systems towards sustainability. The findings offer guidance for researchers and practitioners working on food systems change towards sustainability.

PurposeAs an alternative to technetium-99m-macroaggregated albumin (99mTc-MAA), a scout dose of holmium-166 (166Ho) microspheres can be used prior to 166Ho-radioembolization. The use of identical particles for pre-treatment and treatment procedures may improve the predictive value of pre-treatment analysis of distribution. The aim of this study was to analyze the agreement between 166Ho-scout and 166Ho-therapeutic dose in comparison with the agreement between 99mTc-MAA and 166Ho-therapeutic dose.MethodsTwo separate scout dose procedures were performed (99mTc-MAA and 166Ho-scout) before treatment in 53 patients. First, qualitative assessment was performed by two blinded nuclear medicine physicians who visually rated the agreement between the 99mTc-MAA, 166Ho-scout, and 166Ho-therapeutic dose SPECT-scans (i.e., all performed in the same patient) on a 5-point scale. Second, agreement was measured quantitatively by delineating lesions and normal liver on FDG-PET/CT. These volumes of interest (VOIs) were co-registered to the SPECT/CT images. The predicted absorbed doses (based on 99mTc-MAA and 166Ho-scout) were compared with the actual absorbed dose on post-treatment SPECT.ResultsA total of 23 procedures (71 lesions, 22 patients) were included for analysis. In the qualitative analysis, 166Ho-scout was superior with a median score of 4 vs. 2.5 for 99mTc-MAA (p < 0.001). The quantitative analysis showed significantly narrower 95%-limits of agreement for 166Ho-scout in comparison with 99mTc-MAA when evaluating lesion absorbed dose (− 90.3 and 105.3 Gy vs. − 164.1 and 197.0 Gy, respectively). Evaluation of normal liver absorbed dose did not show difference in agreement between both scout doses and 166Ho-therapeutic dose (− 2.9 and 5.5 Gy vs − 3.6 and 4.1 Gy for 99mTc-MAA and 166Ho-scout, respectively).ConclusionsIn this study, 166Ho-scout was shown to have a superior predictive value for intrahepatic distribution in comparison with 99mTc-MAA.

Compared with common deep learning methods (e.g., convolutional neural networks), transfer learning is characterized by simplicity, efficiency and its low training cost, breaking the curse of small datasets. Medical image analysis plays an indispensable role in both scientific research and clinical diagnosis. Common medical image acquisition methods include Computer Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound (US), X-Ray, etc. Although these medical imaging methods can be applied for non-invasive qualitative and quantitative analysis of patients—compared with image datasets in other computer vision fields such like faces—medical images, especially its labeling, is still scarce and insufficient. Therefore, more and more researchers adopted transfer learning for medical image processing. In this study, after reviewing one hundred representative papers from IEEE, Elsevier, Google Scholar, Web of Science and various sources published from 2000 to 2020, a comprehensive review is presented, including (i) structure of CNN, (ii) background knowledge of transfer learning, (iii) different types of strategies performing transfer learning, (iv) application of transfer learning in various sub-fields of medical image analysis, and (v) discussion on the future prospect of transfer learning in the field of medical image analysis. Through this review paper, beginners could receive an overall and systematic knowledge of transfer learning application in medical image analysis. And policymaker of related realm will benefit from the summary of the trend of transfer learning in medical imaging field and may be encouraged to make policy positive to the future development of transfer learning in the field of medical image analysis.

In recent years, there is a growing interest towards the green synthesis of metal nanoparticles, particularly from plants; however, yet no published study on the synthesis of ZnO.NPs using the Deverra tortuosa extract. Through this study, zinc oxide nanoparticles (ZnO.NPs) have been synthesized based on using the environmentally benign extract of the aerial parts of D. tortuosa as a reducing and capping agent. ZnO.NPs synthesis was confirmed using UV-Visible (UV-Vis) spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD) and High Resolution-Transmission Electron Microscope (HR-TEM). The qualitative and quantitative analyses of plant extract were done. The potential anticancer activity was in vitro investigated against two cancer cell lines (human colon adenocarcinoma “Caco-2” and human lung adenocarcinoma “A549”) compared to their activities on the human lung fibroblast cell line (WI38) using the MTT assay. Both the aqueous extract and ZnO.NPs showed a remarkable selective cytotoxicity against the two examined cancer cell lines.

In this study, polypropylene (PP), a versatile commodity thermoplastic, and cyclic olefin copolymer (COC), an amorphous engineering thermoplastic, were blended over full composition range by melt-mixing technique using a co-rotating twin-screw extruder. PP is likely to be compatible with COC due to its olefinic behaviour, and PP/COC blends provide significant promising properties. FTIR spectra, Raman spectra and wide-angle X-ray scattering (WAXS) patterns of polypropylene, cyclic olefin copolymer and its blends were recorded in solid phases and carried out qualitative and quantitative analysis in detail. The characteristic absorption peaks of PP, COC and PP/COC blends were determined and compared. PP/COC blends did not generate new chemical reactions, while the intensity of fundamental vibration peaks in the spectra tends to vary with respect to the component contents in the blends. The ratio of the integral intensities of polypropylene and cyclic olefin copolymer fundamental vibrations in the Raman spectra were used for the quantitative analysis of PP/COC blends, and the obtained results showed very good agreement with the experimental values. IR spectra, Raman spectra and WAXS patterns of PP/COC blends are useful to track the uniformity of blending and determine the blend composition.

This paper is concerned with the dynamics of large bubbles subject to various strengths of buoyancy effects, which are associated with applications for underwater explosion. The bubble is produced by electric discharge in a low-pressure tank to enhance the buoyancy effects. Experiments are carried out for a bubble in an infinite field, below a free surface and above a rigid boundary. The effects of buoyancy are reflected by the dimensionless parameter ${\\it\\delta}=\\sqrt{{\\it\\rho}gR_{m}/(p_{amb}-p_{v})}$ , where $R_{m}$ , $p_{amb}$ , $p_{v}$ , ${\\it\\rho}$ and $g$ are the maximum bubble radius, ambient pressure, saturated vapour pressure, density of water and the acceleration of gravity respectively. A systematic study of buoyancy effects is carried out for a wide range of ${\\it\\delta}$ from 0.034 to 0.95. A series of new phenomena and new features is observed. The bubbles recorded are transparent, and thus we are able to display and study the jet formation, development and impact on the opposite bubble surface as well as the subsequent collapsing and rebounding of the ring bubble. Qualitative analyses are carried out for the bubble migration, jet velocity and jet initiation time, etc. for different values of ${\\it\\delta}$ . When a bubble oscillates below a free surface or above a rigid boundary, the Bjerknes force due to the free surface (or rigid boundary) and the buoyancy are in opposite directions. Three situations are studied for each of the two configurations: (i) the Bjerknes force being dominant, (ii) the buoyancy force being dominant and (iii) the two forces being approximately balanced. For case (iii), we further consider two subcases, where both the balanced Bjerknes and buoyancy forces are weak or strong. When the Bjerknes and buoyancy forces are approximately balanced over the pulsation, some representative bubble behaviours are observed: the bubble near free surface is found to split into two parts jetting away from each other for small ${\\it\\delta}$ , or involutes from both top and bottom for large ${\\it\\delta}$ . A bubble above a rigid wall is found to be subject to contraction from the lateral part leading to bubble splitting. New criteria are established based on experimental results for neutral collapses where there is no dominant jetting along one direction, which correlate well with the criteria of Blake et al. (J. Fluid Mech., vol. 170, 1986, pp. 479–497; J. Fluid Mech., vol. 181, 1987, pp. 197–212) but agree better with the experimental and computational results.