The Exploration of Static Typography for Expressing The Emotive Qualities of Music

This thesis explores how the pure form of static typography can express the emotive qualities of music. More specifically, how typefaces/letterforms and typographic compositions can produce emotive associations; and whether combining both aspects can enhance the emotive value. Emotion, typography and music are the three core subject areas of this research. Using music as the medium to elicit emotions, the findings from this thesis indicate that typeface/letterform is the most effective aspect of static typography to express emotive qualities, followed by the combination of both typographic aspects, and typographic composition which has the least impact for emotive connections. Five influential factors affecting the process of emotive association between music and static typography has been found: 1) Association of typographic attributes and design principles to emotive qualities, 2) Direct association using emotive terms and adjectives, 3) Connotation through personal memory and imagination, 4) Association to human voice and human touch, and 5) Association to phonetic properties of music. Chapter 2 of this thesis presents a review of the literature from the three main subject areas. It begins from the psychology of emotions and the importance of emotional attachment in design. Next, the chapter discusses the visual logic and creation of emotions through the pure anatomy of letterforms and typographic experimentation. The third section continues with how music can evoke emotions and the analogy between the properties of music and typographic characteristics. Chapter 3 4 presents original research of this thesis, initiating with a formative pilot study where three music sequences were selected and three corresponding typographic compositions designed by the researcher. The method of matching one sequence to one design piece was employed. Chapter 4 continues with original research, where modification was made to the methodology to obtain more specific results. Each aspect of static typography was investigated individually. The combination of both aspects was also tested to examine whether it can enhance the emotive impact. Findings from this research intend to present fresh realization to graphic designers, typographers and type designers, highlighting the tangible and enduring essence of static typography, with its power to engage the audience on an emotive level

Side-channel attack analysis on in-memory computing architectures

In-memory computing (IMC) systems have great potential for accelerating data-intensive tasks such as deep neural networks (DNNs). As DNN models are generally highly proprietary, the neural network architectures become valuable targets for attacks. In IMC systems, since the whole model is mapped on chip and weight memory read can be restricted, the system acts as a "black box" for customers. However, the localized and stationary weight and data patterns may subject IMC systems to other attacks. In this paper, we propose a side-channel attack methodology on IMC architectures. We show that it is possible to extract model architectural information from power trace measurements without any prior knowledge of the neural network. We first developed a simulation framework that can emulate the dynamic power traces of the IMC macros. We then performed side-channel attacks to extract information such as the stored layer type, layer sequence, output channel/feature size and convolution kernel size from power traces of the IMC macros. Based on the extracted information, full networks can potentially be reconstructed without any knowledge of the neural network. Finally, we discuss potential countermeasures for building IMC systems that offer resistance to these model extraction attack

Epidemiology and outcomes of anal abscess in patients on chronic dialysis: a 14-year retrospective study

OBJECTIVES: We conducted this retrospective study to elucidate the clinical presentation and outcomes of anal abscess in chronic dialysis patients. METHODS: We performed a chart review of patients who were hospitalized for anal abscess from Jan. 2002 to Dec. 2015. A total of 3,074 episodes of anal abscess were identified. Of these, 43 chronic dialysis patients with first-time anal abscess were enrolled. Patients were divided into a surgical group and a nonsurgical group according to the treatment received during hospitalization. The baseline characteristics, clinical findings, treatments and outcomes were obtained and analyzed. The endpoints of this study were in-hospital mortality, one-year mortality and one-year recurrence. RESULTS: Of the 43 patients, 27 (62.7%) received surgical treatment, and 16 (37.2%) received antibiotic treatment alone. There was no significant difference in age, sex, body mass index, smoking habits, comorbidities, or dialysis characteristics between the two groups. Perianal abscess was the most common type of anal abscess, and 39.5% of patients experienced fistula formation. Most patients had mixed aerobic and anaerobic flora. Our data demonstrate that there was no significant difference in hospital stay, one-year survival or recurrence rate between the surgical group and nonsurgical group. However, there was a trend toward better in-hospital survival in patients who received surgical treatment (p=0.082). CONCLUSION: In chronic dialysis patients with anal abscess, there was no statistically significant difference in clinical presentation and outcomes between the surgical and nonsurgical groups, although the surgical group had a trend of better in-hospital survival

Subtyping intractable functional constipation in children using clinical and laboratory data in a classification model

BackgroundChildren with intractable functional constipation (IFC) who are refractory to traditional pharmacological intervention develop severe symptoms that can persist even in adulthood, resulting in a substantial deterioration in their quality of life. In order to better manage IFC patients, efficient subtyping of IFC into its three subtypes, normal transit constipation (NTC), outlet obstruction constipation (OOC), and slow transit constipation (STC), at early stages is crucial. With advancements in technology, machine learning can classify IFC early through the use of validated questionnaires and the different serum concentrations of gastrointestinal motility-related hormones.MethodA hundred and one children with IFC and 50 controls were enrolled in this study. Three supervised machine-learning methods, support vector machine, random forest, and light gradient boosting machine (LGBM), were used to classify children with IFC into the three subtypes based on their symptom severity, self-efficacy, and quality of life which were quantified using certified questionnaires and their serum concentrations of the gastrointestinal hormones evaluated with enzyme-linked immunosorbent assay. The accuracy of machine learning subtyping was evaluated with respect to radiopaque markers.ResultsOf 101 IFC patients, 37 had NTC, 49 had OOC, and 15 had STC. The variables significant for IFC subtype classification, according to SelectKBest, were stool frequency, the satisfaction domain of the Patient Assessment of Constipation Quality of Life questionnaire (PAC-QOL), the emotional self-efficacy for Functional Constipation questionnaire (SEFCQ), motilin serum concentration, and vasoactive intestinal peptide serum concentration. Among the three models, the LGBM model demonstrated an accuracy of 83.8%, a precision of 84.5%, a recall of 83.6%, a f1-score of 83.4%, and an area under the receiver operating characteristic curve (AUROC) of 0.89 in discriminating IFC subtypes.ConclusionUsing clinical characteristics measured by certified questionnaires and serum concentrations of the gastrointestinal hormones, machine learning can efficiently classify pediatric IFC into its three subtypes. Of the three models tested, the LGBM model is the most accurate model for the classification of IFC, with an accuracy of 83.8%, demonstrating that machine learning is an efficient tool for the management of IFC in children

Altered Striatocerebellar Metabolism and Systemic Inflammation in Parkinson’s Disease

Parkinson’s disease (PD) is the most second common neurodegenerative movement disorder. Neuroinflammation due to systemic inflammation and elevated oxidative stress is considered a major factor promoting the pathogenesis of PD, but the relationship of structural brain imaging parameters to clinical inflammatory markers has not been well studied. Our aim was to evaluate the association of magnetic resonance spectroscopy (MRS) measures with inflammatory markers. Blood samples were collected from 33 patients with newly diagnosed PD and 30 healthy volunteers. MRS data including levels of N-acetylaspartate (NAA), creatine (Cre), and choline (Cho) were measured in the bilateral basal ganglia and cerebellum. Inflammatory markers included plasma nuclear DNA, plasma mitochondrial DNA, and apoptotic leukocyte levels. The Cho/Cre ratio in the dominant basal ganglion, the dominant basal ganglia to cerebellum ratios of two MRS parameters NAA/Cre and Cho/Cre, and levels of nuclear DNA, mitochondrial DNA, and apoptotic leukocytes were significantly different between PD patients and normal healthy volunteers. Significant positive correlations were noted between MRS measures and inflammatory marker levels. In conclusion, patients with PD seem to have abnormal levels of inflammatory markers in the peripheral circulation and deficits in MRS measures in the dominant basal ganglion and cerebellum

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Copula-Based Factor Model for Credit Risk Analysis

A standard quantitative method to access credit risk employs a factor model based on joint multi- variate normal distribution properties. By extending a one-factor Gaussian copula model to make a more accurate default forecast, this paper proposes to incorporate a state-dependent recovery rate into the con- ditional factor loading, and model them by sharing a unique common factor. The common factor governs the default rate and recovery rate simultaneously and creates their association implicitly. In accordance with Basel III, this paper shows that the tendency of default is more governed by systematic risk rather than idiosyncratic risk during a hectic period. Among the models considered, the one with random factor loading and a state-dependent recovery rate turns out to be the most superior on the default prediction

Management outputs efficiency comparison: the credit departments within farmer associations in Taiwan and Japan

Farmer associations (FAs) in Taiwan and Japan Agricultural (JA) Cooperatives in Japan play an important role in agricultural development. Both have experienced dramatic changes in the macroeconomic environment, and have faced similar management issues. This study focuses on the comparison of operational management efficiency and productivity between the two agricultural institutions in two different countries, focusing on their respective credit departments. Using financial data covered from 2010 to 2014, a Stochastic Metafrontier Regression Model is adopted to explore how operating performances have influenced the productivity of such institutions. Environmental variables such as number of regional financial institutions, regional location, scale of fixed assets, and population density affect inefficiency. With an overall higher number of input and output variables, results show that the average efficiency of credit department within JA Cooperatives when producing output is at 97%, while that of FAs is lower at 90%. Therefore, FAs have more room for efficiency improvement and technological progress