Pattern recognition and image processing of infrared astronomical satellite images

The Infrared Astronomical Satellite (IRAS) images with wavelengths of 60 [mu] m and 100 [mu] m contain mainly information on both extra-galactic sources and low-temperature interstellar media. The low-temperature interstellar media in the Milky Way impose a cirrus screen of IRAS images, especially in images with 100 [mu] m wavelength. This dissertation deals with the techniques of removing the cirrus clouds from the 100 [mu] m band in order to achieve accurate determinations of point sources and their intensities (fluxes). We employ an image filtering process which utilizes mathematical morphology and wavelet analysis as the key tools in removing the cirrus foreground emission. The filtering process consists of extraction and classification of the size information, and then using the classification results in removal of the cirrus component from each pixel of the image. Extraction of size information is the most important step in this process. It is achieved by either mathematical morphology or wavelet analysis. In the mathematical morphological method, extraction of size information is done using the sieving process. In the wavelet method, multi-resolution techniques are employed instead;The classification of size information distinguishes extra-galactic sources from cirrus using their averaged size information. The cirrus component for each pixel is then removed by using the averaged cirrus size information. The filtered image contains much less cirrus. Intensity alteration for extra-galactic sources in the filtered image are discussed. It is possible to retain the fluxes of the point sources when we weigh the cirrus component differently pixel by pixel. The importance of the uni-directional size information extractions are addressed in this dissertation. Such uni-directional extractions are achieved by constraining the structuring elements, or by constraining the sieving process to be sequential;The generalizations of mathematical morphology operations based on the dynamic hit-or-miss transform are presented in this dissertation. The generalized erosion ([gamma]-erosion) bridges traditional erosion and dilation. It also enriches the morphological operators available in the field of signal and image processing. Traditional closing is generalized into [gamma]-closing, which bridges traditional closing and opening. Properties of [gamma]-erosion and [gamma]-closing are discussed. The sieving process is generalized based on [gamma]-closing, and is bi-directional, with the polarity directly related to the parameter [gamma]. The size information extractors of morphological methods and wavelet methods are justified quantitatively using a prototype peak with fixed slope. The non-linearity of the sieving process is analyzed. It is shown that the sieving process can approach an approximate linearity at positions where the input signal has sharp peaks (i.e., the slopes are large). The spatial discriminating properties of the size information extractors are also very important

LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis

Thematic analysis (TA) has been widely used for analyzing qualitative data in many disciplines and fields. To ensure reliable analysis, the same piece of data is typically assigned to at least two human coders. Moreover, to produce meaningful and useful analysis, human coders develop and deepen their data interpretation and coding over multiple iterations, making TA labor-intensive and time-consuming. Recently the emerging field of large language models (LLMs) research has shown that LLMs have the potential replicate human-like behavior in various tasks: in particular, LLMs outperform crowd workers on text-annotation tasks, suggesting an opportunity to leverage LLMs on TA. We propose a human-LLM collaboration framework (i.e., LLM-in-the-loop) to conduct TA with in-context learning (ICL). This framework provides the prompt to frame discussions with a LLM (e.g., GPT-3.5) to generate the final codebook for TA. We demonstrate the utility of this framework using survey datasets on the aspects of the music listening experience and the usage of a password manager. Results of the two case studies show that the proposed framework yields similar coding quality to that of human coders but reduces TA's labor and time demands.Comment: EMNLP 2023 Finding

Orbital Apex Syndrome Resulting from Mixed Bacterial Sphenoid Sinusitis

Orbital apex syndrome (OAS) is an uncommon disorder characterized by visual loss, ophthalmoplegia, ptosis and hypoaesthesia of the forehead[1]. OAS may result from a variety of inflammatory, infectious, neoplastic and vascular conditions that cause damage to the superior orbital fissure (with resultant oculomotor (III), trochlear (IV), abducens (VI) and ophthalmic branch of the trigeminal nerve (V1) palsies) and to the optic canal leading to optic nerve (II) dysfunction. This case report describes the clinical development of OAS in a patient with bacterial sphenoid sinusitis

Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term

With advancements in natural language processing (NLP) models, automatic explanation generation has been proposed to mitigate misinformation on social media platforms in addition to adding warning labels to identified fake news. While many researchers have focused on generating good explanations, how these explanations can really help humans combat fake news is under-explored. In this study, we compare the effectiveness of a warning label and the state-of-the-art counterfactual explanations generated by GPT-4 in debunking misinformation. In a two-wave, online human-subject study, participants (N = 215) were randomly assigned to a control group in which false contents are shown without any intervention, a warning tag group in which the false claims were labeled, or an explanation group in which the false contents were accompanied by GPT-4 generated explanations. Our results show that both interventions significantly decrease participants' self-reported belief in fake claims in an equivalent manner for the short-term and long-term. We discuss the implications of our findings and directions for future NLP-based misinformation debunking strategies.Comment: EMNLP Findings 202

Amorphous Boron Nanorod as an Anode Material for Lithium-Ion Batteries at Room Temperature

We report an amorphous boron nanorod anode material for lithium-ion batteries prepared through smelting non-toxic boron oxide in liquid lithium. Boron in theory can provide capacity as high as 3099 mAh g-1 by alloying with Li to form B4Li5. However, experimental studies of boron anode were rarely reported for room temperature lithium-ion batteries. Among the reported studies the electrochemical activity and cycling performance of bulk crystalline boron anode material are poor at room temperature. In this work, we utilized amorphous nanostructured one-dimensional (1D) boron material aiming at improving the electrochemical reactivity between boron and lithium ions at room temperature. The amorphous boron nanorod anode exhibited, at room temperature, a reversible capacity of 170 mAh g-1 at a current rate of 10 mA g-1 between 0.01 and 2 V. The anode also demonstrated good rate capability and cycling stability. Lithium storage mechanism was investigated by both sweep voltammetry measurements and galvanostatic intermittent titration technique (GITT). The sweep voltammetric analysis suggested that the contributions from lithium ions diffusion into boron as well as the capacitive process to the overall lithium charge storage are 57% and 43%, respectively. Results from GITT indicated that the discharge capacity at higher potentials (\u3e ~ 0.2 V vs, Li/Li+) could be ascribed to a capacitive process and at lower potentials (\u3c ~0.2 V vs, Li/Li+) to diffusion-controlled alloying reactions. Solid state nuclear magnetic resonance (NMR) measurement further confirmed that the capacity is from electrochemical reactions between lithium ions and the amorphous boron nanorod. This work provides new insights into designing nanostructured boron material for lithium-ion batteries

All the wiser: Fake news intervention using user reading preferences

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Investigation and analysis of an outbreak of foodborne disease caused by Salmonella enteritidis in a district of Chongqing

ObjectiveTo provide the basis for dealing with similar incidents in the future， an outbreak of foodborne illness caused by the consumption of bread contaminated with Salmonella enteritidis was investigated.MethodsDescriptive epidemiological methods were used to analyze the clinical characteristics， epidemiological distribution and related risk factors of the cases. The etiological food was determined by retrospective cohort study. The biological samples， food remains and environmental samples of the cases and canteen employees were detected by laboratory testing. The causes of the outbreak were comprehensively analyzed based on the results of epidemiological investigation， laboratory tests and sanitary investigation.ResultsRetrospective cohort study showed that a batch of pre-packaged bread produced by a food factory in Chongqing on May 20， 2021 was the suspicious food. A total of 73 people ate the suspicious bread in this incident， and 55 of them got ill with a morbidity rate of 75.34% and a median incubation period of 15 h. At the same time， Salmonella enteritidis was detected in food remains， related environmental samples and anal swabs of patients.ConclusionThe incident was an outbreak of foodborne disease caused by bread contaminated with Salmonella enteritidis

Catalogue of topological electrons and phonons in all allotropes of carbon

Carbon, as one of the most common element in the earth, constructs hundreds of allotropic phases to present rich physical nature. In this work, by combining the ab inito calculations and symmetry analyses method, we systematically study a large number of allotropes of carbon (703), and discovered 315 ideal topological phononic materials and 32 topological electronic materials. The ideal topological phononic nature includes single, charge-two, three, four Weyl honons, the Dirac or Weyl nodal lines phonons, and nodal surfaces phonons. And the topological electron nature ncludes topological insulator, (Type-II) Dirac points, triple nodal points, the Dirac (Weyl) nodal lines, quadratic nodal lines and so on. For convenience, we take the uni in SG 178 and pbg in SG 230 as the examples to describe the topological features in the main. We find that it is the coexistence of single pair Weyl phonons and one-nodal surfaces phonons in the uni in SG 178, which can form the single surface arc in the (100) surface BZ and isolated double-helix surface states (IDHSSs)in the (110) surface BZ. In topological semimetal pbg in SG 230, we find that the perfect triple degenerate nodal point can be found in the near Fermi level, and it can form the clear surface states in the (001) and (110) surface BZ. Our work not only greatly expands the topological features in all allotropes of carbon, but also provide many ideal platforms to study the topological electrons and phonons