Minimalistic consumption:study on Finnish consumers with the context of kitchenware consumption

Abstract. Facing criticisms towards consumerist lifestyle, minimalistic consumption has been proposed and received considerable attention from a significant segment of consumers who want to take another lens of consumption other than indulging in consumerism-oriented attitudes. In recent years, many researchers have started to observe this phenomenon and explain it from different perspectives. Despite the contributions of prior studies, the holistic framework identifying the motivations and goals that consumers aim to achieve through minimalistic consumption practices has been neglected and unstructured in the extant literature. The purpose of this study is to provide insights into the motives and aims of minimalistic consumers and explore the common consumption practices that minimalistic consumers engage in. The qualitative method is used with data collected from seven in-depth interviews. All participants are Finnish consumers who are adopting the minimalistic lifestyle. The chosen context to analyze the customer behavior towards minimalistic consumption is kitchenware consumption. The findings of this study indicate that there are four motivations that encourage Finnish consumers to engage in minimalistic consumption, consisting of self-fulfilling, economic, environmental and social, and personal preference motive. Each motive presents certain goals that consumers want to gain when practicing minimalistic consumption. The results of this study also provide the representative practices of minimalistic consumption and the characteristics of products that minimalistic consumers take into consideration when consuming material goods. The contribution of this study is that it provides a deeper understanding of the minimalistic consumers. Minimalistic consumers should be seen as heterogeneous based on their different motives and aims when engaging in minimalistic consumption. From such an understanding, marketers can design suitable marketing strategies to target this segment

Modulation of the Endothelial Phenotype by Transforming Growth Factor-β2 and Nck Signaling

The development of solid tumors and atherosclerosis requires neovascularization. In contrast to blood vessels of healthy organs, blood vessels associated with atherosclerosis and tumors are poorly organized and leaky. However, it is poorly understood how microenvironmental factors modulate molecular mechanisms underlying the abnormal vascular phenotype. The objective in this project is to determine cellular changes elicited by transforming growth factor-β2 (TGF-β2) and the Nck adaptors in the transition of endothelial sheets from a stable/cohesive to a loosely organized, permeable phenotype. It is hypothesized that the Nck adaptors link heightened matrix stiffness and TGF-β2 signaling thereby inducing cytoskeletal changes underlying the tumor-associated endothelial phenotype. Cell culture experiments coupled with immunofluorescence labeling indicate change in cell morphology and patterns of protein expression/subcellular distribution when TGF-β2-treated cells were compared with control endothelial cells. Preliminary results indicate the Nck modulates TGF-beta-induced changes in cell morphology. These results suggest that the TGF-β2 signaling pathway and/or the silencing of the Nck could be targeted to prevent Endothelial to Mesenchymal Transition (EndMT) and the abnormal vasculature in atherosclerosis.

DIFFICULTIES IN WRITING AN ESSAY OF ENGLISH-MAJORED SOPHOMORES AT TAY DO UNIVERSITY, IN VIETNAM

Writing is an important skill in English that helps people express thoughts, emotion and viewpoint to readers. However, students face some difficulties when writing. Hence, the survey research presents the process of the study about “Difficulties in writing an essay of English-majored sophomores at Tay Do University, in Viet Nam”. It was conducted to find out some difficulties in learning writing (from 200 to 250 - word essay) of 102 the sophomores from Bachelor of English 10 at Tay Do University. Questionnaire, paper interview and essay samples were the instruments of the study. The results showed that sophomores had many problems in writing such as vocabulary, grammar structures, ideas arrangement, background knowledge, and others. Basing on the results, some solutions would be suggested to help students to get a good writing skill. Viết là một kỹ năng quan trọng trong tiếng Anh giúp người viết thể hiện suy nghĩ, cảm xúc và quan điểm với người đọc. Tuy nhiên, sinh viên thường gặp một số khó khăn khi viết. Do đó, nghiên cứu “Khó khăn khi viết bài luận của sinh viên năm thứ hai chuyên ngành Ngôn Ngữ Anh tại Trường Đại học Tây Đô, Việt Nam” được thực hiện nhằm tìm ra một số khó khăn khi học môn viết (bài luận từ 200 đến 250 từ) của 102 sinh viên Cử nhân Tiếng Anh năm thứ hai, khóa 10 của Trường Đại học Tây Đô. Công cụ nghiên cứu gồm bảng câu hỏi, phỏng vấn trên giấy và phân tích bài luận. Kết quả cho thấy sinh viên năm thứ hai gặp nhiều vấn đề về viết như từ vựng, cấu trúc ngữ pháp, sắp xếp ý tưởng, kiến thức nền tảng và những vấn đề khác. Dựa trên kết quả đạt được, một số giải pháp sẽ được đề xuất để giúp sinh viên có được kỹ năng viết tốt hơn. Article visualizations

Ergodic dynamics in sigma–delta quantization: tiling invariant sets and spectral analysis of error

AbstractThis paper has two themes that are intertwined. The first is the dynamics of certain piecewise affine maps on Rm that arise from a class of analog-to-digital conversion methods called ΣΔ (sigma–delta) quantization. The second is the analysis of reconstruction error associated with each such method.ΣΔ quantization generates approximate representations of functions by sequences that lie in a restricted set of discrete values. These are special sequences in that their local averages track the function values closely, thus enabling simple convolutional reconstruction. In this paper, we are concerned with the approximation of constant functions only, a basic case that presents surprisingly complex behavior. An mth order ΣΔ scheme with input x can be translated into a dynamical system that produces a discrete-valued sequence (in particular, a 0–1 sequence) q as its output. When the schemes are stable, we show that the underlying piecewise affine maps possess invariant sets that tile Rm up to a finite multiplicity. When this multiplicity is one (the single-tile case), the dynamics within the tile is isomorphic to that of a generalized skew translation on Tm.The value of x can be approximated using any consecutive M elements in q with increasing accuracy in M. We show that the asymptotical behavior of reconstruction error depends on the regularity of the invariant sets, the order m, and some arithmetic properties of x. We determine the behavior in a number of cases of practical interest and provide good upper bounds in some other cases when exact analysis is not yet available

POCS-based framework of signal reconstruction from generalized non-uniform samples

We formalize the use of projections onto convex sets (POCS) for the reconstruction of signals from non-uniform samples in their highest generality. This covers signals in any Hilbert space $\mathscr H$, including multi-dimensional and multi-channel signals, and samples that are most generally inner products of the signals with given kernel functions in $\mathscr H$. An attractive feature of the POCS method is the unconditional convergence of its iterates to an estimate that is consistent with the samples of the input, even when these samples are of very heterogeneous nature on top of their non-uniformity, and/or under insufficient sampling. Moreover, the error of the iterates is systematically monotonically decreasing, and their limit retrieves the input signal whenever the samples are uniquely characteristic of this signal. In the second part of the paper, we focus on the case where the sampling kernel functions are orthogonal in $\mathscr H$, while the input may be confined in a smaller closed space $\mathscr A$ (of bandlimitation for example). This covers the increasingly popular application of time encoding by integration, including multi-channel encoding. We push the analysis of the POCS method in this case by giving a special parallelized version of it, showing its connection with the pseudo-inversion of the linear operator defined by the samples, and giving a multiplierless discrete-time implementation of it that paradoxically accelerates the convergence of the iteration.Comment: 12 pages, 4 figures, 1 tabl

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices

The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have to a rapid increase in the use of supervised machine learning in the 3D medical image analysis and diagnosis. In particular, deep convolutional neural networks (D-CNNs) have been key players and were adopted by the medical imaging community to assist clinicians and medical experts in disease diagnosis and treatment. However, training and inferencing deep neural networks such as D-CNN on high-resolution 3D volumes of Computed Tomography (CT) scans for diagnostic tasks pose formidable computational challenges. This challenge raises the need of developing deep learning-based approaches that are robust in learning representations in 2D images, instead 3D scans. In this work, we propose for the first time a new strategy to train \emph{slice-level} classifiers on CT scans based on the descriptors of the adjacent slices along the axis. In particular, each of which is extracted through a convolutional neural network (CNN). This method is applicable to CT datasets with per-slice labels such as the RSNA Intracranial Hemorrhage (ICH) dataset, which aims to predict the presence of ICH and classify it into 5 different sub-types. We obtain a single model in the top 4% best-performing solutions of the RSNA ICH challenge, where model ensembles are allowed. Experiments also show that the proposed method significantly outperforms the baseline model on CQ500. The proposed method is general and can be applied to other 3D medical diagnosis tasks such as MRI imaging. To encourage new advances in the field, we will make our codes and pre-trained model available upon acceptance of the paper.Comment: Accepted for presentation at the 22nd IEEE Statistical Signal Processing (SSP) worksho

Modulation of the Endothelial Phenotype by Transforming Growth Factor-β2 and Nck Signaling

The development of solid tumors and atherosclerosis requires neovascularization. In contrast to blood vessels of healthy organs, blood vessels associated with atherosclerosis and tumors are poorly organized and leaky. However, it is poorly understood how microenvironmental factors modulate molecular mechanisms underlying the abnormal vascular phenotype. The objective in this project is to determine cellular changes elicited by transforming growth factor-β2 (TGF-β2) and the Nck adaptors in the transition of endothelial sheets from a stable/cohesive to a loosely organized, permeable phenotype. It is hypothesized that the Nck adaptors link heightened matrix stiffness and TGF-β2 signaling thereby inducing cytoskeletal changes underlying the tumor-associated endothelial phenotype. Cell culture experiments coupled with immunofluorescence labeling indicate change in cell morphology and patterns of protein expression/subcellular distribution when TGF-β2-treated cells were compared with control endothelial cells. Preliminary results indicate the Nck modulates TGF-beta-induced changes in cell morphology. These results suggest that the TGF-β2 signaling pathway and/or the silencing of the Nck could be targeted to prevent Endothelial to Mesenchymal Transition (EndMT) and the abnormal vasculature in atherosclerosis.

Set theoretic compression with an application to image coding

We show that the complete information that is available after an image has been encoded is not just an approximate quantized image version, but a whole set of consistent images that contains the original image by necessity. From this starting point, we develop a set of tools to design a new class of encoders for image compression, based on a set decomposition and recombination of image features. As an initial validation, we show the results of an experiment where these tools are used to modify the encoding process of block discrete cosine transform (DCT) coding in order to yield less blocking artifacts