Miracle-dz/UniFAR-FTUs huggingface dataset:
UNSUPERVISED SAR CHANGE DETECTION METHOD BASED ON REFINED SAMPLE SELECTION

Abstract. In deep learning based synthetic aperture radar (SAR) change detection, selecting samples of high quality is a crucial step. In this work, we have proposed a refined sample selection algorithm for unsupervised SAR change detection. The propose and incorporation of volume control factors and multi-hierarchical fuzzy c-means (MH-FCM) algorithm generate samples of large diversity and high confidence, thus satisfying the needs for high quality samples. The method includes two phases: firstly, an enhanced difference image is constructed according to the difference consistency between single pixels and their neighbourhoods, and a triangular threshold segmentation method is then proposed to determine the volume control factors for sample selection. MH-FCM is developed to classify the log mean ratio difference image into 4 classes. Secondly, a dual-channel convolution neural network with an adaptive weighted loss is adopted to learn and predict the input and to obtain the change detection result. Experimental results of the Gaofen-3 dataset in Beijing have validated the effectiveness and usefulness of the proposed method.
Boundary-layer height and surface stability at Hyytiälä, Finland, in ERA5 and observations

Abstract. We investigate the boundary-layer (BL) height at Hyytiälä in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different, pre-existing algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used. The level of agreement, and the sign of systematic bias between the four different methods, depends on the surface-layer stability. For very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson-number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions, highlighting the ongoing challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18:00 UTC, suggesting ERA5 does not resolve the evening transition correctly. BL height estimates from the MWR are also found to be reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturer's algorithm for stable conditions and also the misidentification of the type of BL. A climatology of the annual and diurnal cycle of BL height, based on ERA5 data, and surface-layer stability, based on eddy covariance observations, was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height; unstable BLs are rare, yet so are very stable BLs. The shallowest BLs occur at night in spring and summer, and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data, we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer, reducing the area over which BL height observations from Hyytiälä would be representative.
Visual Rehabilitation After Retinal Prosthesis Implantation: An 18-month Case Report, From Candidate Selection to Follow-Up

Introduction: Various retinal implants are being developed and appear to be a promising option for improving the visual capacities of individuals with retinal dystrophy. A multidisciplinary approach to both assessment of a candidate’s factors and rehabilitation could contribute to improved activity and participation. The purpose of this study was (i) to document the approach taken by a multidisciplinary team in the candidate selection process and in training in the use of the Argus II retinal prosthesis system (RPS), and (ii) to examine the effects of the RPS on sensory and mental functions and on activity and participation. Methods: An A1-B1-A2-B2 experimental case report was used, with repeated measures pre- and post-rehabilitation program design. The A phases represent the periods with the system off, whereas the B phases represent the periods with the system on. A 65-year-old man with retinitis pigmentosa and total blindness was followed by a multidisciplinary team for over 18 months. After receiving the retinal implant, he benefited from a 10-week rehabilitation program (twice per week; B1 phase). Results: Globally, the RPS improved vision in the B phases when the system was on and visual acuity was stable at 2.3 logMAR (functional blindness). The participant’s mental and neuromusculoskeletal function scores were generally stable throughout the data collection periods. Lower performance on some measures at the end of phase B2 coincided with a negative mood. Discussion: Use of the RPS improved activity, but this did not transfer into greater participation in the living environment. Despite efforts made by the rehabilitation team to manage the user’s expectations concerning the RPS, the interventions reactivated his grieving over his vision loss. Implications for Practitioners: New technologies can make users dream of unrealistic possibilities, and managing their expectations requires problem solving supported by a multidisciplinary team.
Global chlorophyll responses to marine heatwaves in satellite ocean color

Marine heatwaves (MHWs), prolonged ocean temperature extremes, have been enhanced by global warming in recent decades. More intense and longer MHWs have increasingly negative impacts on marine organisms that threaten their resilience of marine ecosystems. In this study, we investigated global marine phytoplankton biomass (chlorophyll) estimated by satellite ocean color and its response to MHWs on global and regional scales. We find that MHWs typically decreases chlorophyll concentrations in the tropics and mid-latitudes, with increases at high latitudes. The magnitude of chlorophyll responses to MHWs is increased in response to higher intensity and longer duration of MHWs. We find a change in the response from negative to positive chlorophyll responses to MHWs across the 40°–50° latitude bands in both hemispheres where the strongest meridional gradient in nitrate concentration exists. In these response-changing regions, the latitudinal contrast of the chlorophyll response is more distinctive in the warm season rather than in the cold season because of the shallower climatological mixed layer. The present study highlights the global phytoplankton responses to MHWs and their sensitivity to MHWs properties that imply the importance of upper-ocean interactions between phytoplankton and the mixed-layer.
Expressway Speed Prediction Based on Electronic Toll Collection Data

Expressway section speed can visually reflect the section operation condition, and accurate short time section speed prediction has a wide range of applications in path planning and traffic guidance. However, existing expressway speed prediction data have defects, such as sparse density and incomplete object challenges. Thus, this paper proposes a framework for a combined expressway traffic speed prediction model based on wavelet transform and spatial-temporal graph convolutional network (WSTGCN) of the Electronic Toll Collection (ETC) gantry transaction data. First, the framework pre-processes the ETC gantry transaction data to construct the section speeds. Then wavelet decomposition and single-branch reconstruction are performed on the section speed sequences, and the spatial features are captured by graph convolutional network (GCN) for each reconstructed single-branch sequence, and the temporal features are extracted by connecting the gated recurrent unit (GRU). The experiments use the ETC gantry transaction data of the expressway from Quanzhou to Xiamen. The results indicate that the WSTGCN model makes notable improvements compared to the model of the baseline for different prediction ranges.
Optionality and variability of speech pauses in read speech across languages and rates

Most prosodic boundaries are optional regarding their location. Moreover, markers of prosodic boundaries such as speech pauses show great variability in the duration of pauses as a whole and that of breath noises occurring in these pauses. Optionality and variability of pauses are particularly observable when the speaking rate is varied. In this study we investigated pausing behaviour in six languages of the BonnTempo-Corpus with 46 speakers who read aloud a semantically similar short passage at ﬁve rates, from very fast to very slow. The gen-eral picture across languages shows that pause duration, as ex-pected, correlates with rate, and breath noise duration correlates with total pause duration. The optionality of pauses is reﬂected by the number of pauses (within but also across rates) and by the importance of some locations. The variability is evident in pause and inhalation durations: pause durations and number of inhalations decrease at faster rates, whereas both increase when a pause is less optional at a given location in the text. We consider a closer look at details of pauses to be an important step for prosody modelling and essential for exploring and explain-ing stylistic variation in prosodic phrasing.
Analyzing Human Periodontal Soft Tissue Inflammation and Drug Responses In Vitro Using Epithelium-Capillary Interface On-a-Chip

The gingival epithelium–capillary interface is a unique feature of periodontal soft tissue, preserving periodontal tissue homeostasis and preventing microorganism and toxic substances from entering the subepithelial tissue. However, the function of the interface is disturbed in periodontitis, and mechanisms of the breakdown of the interface are incompletely understood. To address these limitations, we developed a microfluidic epithelium–capillary barrier with a thin culture membrane (10 μm) that closely mimics the in vivo gingival epithelial barrier with an immune micro-environment. To test the validity of the fabricated gingival epithelial barrier model, epithelium–capillary interface-on-a-chip was cultured with human gingival epithelial cells (HGECs) and human vascular endothelial cells (HUVEC). Their key properties were tested using optical microscope, transepithelial/transendothelial electrical resistance (TEER), and permeability assays. The clear expression of VE-cadherin revealed the tight junctions in endothelial cells. Live/dead assays indicated a high cell viability, and the astrocytic morphology of HGE cells was confirmed by F-actin immunostaining. By the third day of cell culture, TEER levels typically exceeded in co-cultures. The resultant permeability coefficients showed a significant difference between 70 kDa and 40 kDa FITC-dextran. The expression of protein intercellular cell adhesion molecule (ICAM-1) and human beta defensin-2 (HBD2) decreased when exposed to TNF-α and LPS, but recovered with the NF-κB inhibitor treatment- Pyrrolidinedithiocarbamic acid (PDTC), indicating the stability of the fabricated chip. These results demonstrate that the developed epithelium-capillary interface system is a valid model for studying periodontal soft tissue function and drug delivery.
Inadequate Interactions and Unbalanced Power Between Scientists and the Public in Chinese Knowledge Sharing Network: Social Network Analysis of the Topic of Genetically Modified Food on Zhihu

This study takes the scientific discussion about genetically modified food on Zhihu as an example, using the method of social network analysis to explore the interactions between Chinese scientists and the public online. The findings indicate that both scientists and non-scientists are inclined to interact with users with a similar identity. Cross-group interactions seem to be hard to achieve on Zhihu. Furthermore, compared with non-scientists, scientist users tend to hold significantly stronger digital social capital than non-scientists on Zhihu. It is suggested that the knowledge sharing network has not fully achieved the goal of effectively promoting equally science dialogue in China.
A Study of Thermal Properties of Commercially Available Innerwear

In this study, three commercially available innerwears were collected from the market. Their air permeability and thermal properties were evaluated by Kawabata Evaluation System for Fabric (KES-F). Exerimental results revealed that the fibre content played an important role in affecting the air permeability and the thermal properties of the innerwears.
Community-Level Social Topic Tracking of Urban Emergency: A Case Study of COVID-19

During the outbreak of COVID-19 in Wuhan, the public used Weibo to acquire information, express emotions, and seek help at a historic and unprecedented scale. This situational information is valuable for authorities to initiate emergency policies and protect people’s health. Although event detection and situation awareness during COVID-19 using social media data have been investigated in recent studies, the spatiotemporal evolution patterns of social topics during COVID-19 at the community level are still limited. To address this limitation, this study developed a methodology to explore the dynamics of social topics under the influence of COVID-19 at a community level in Wuhan using geotagged Weibo posts. The disease-related topics exhibited the spatial variations in different urban communities and reflected the dynamics of public attention. Moreover, we used the reported COVID-19 case data in Wuhan and geotagged Weibo posts in Beijing to validate the effectiveness of the proposed methodology. These findings help to track social topic evolution at the community level and gain a better understanding of the spatial variations of public attention during urban emergencies.
The relation between musical ability and sentence-level intonation perception: A meta-analysis comparing L1 and non-native listening

Studies investigating the relationship between musical abilities and speech prosody report that musicians show an altered— often enhanced—perception of prosody, or report positive correlations between music perception and prosody perception. However, some studies on L1 perception find no such benefits, but show good prosody perception across listeners. In contrast, even advanced L2 users may show difficulties in processing sentence intonation. We hypothesised that musicality might especially be beneficial in challenging circumstances of non-native intonation perception. To test this, we conducted a meta-analysis of previous research investigating the effect of musical abilities on the perception of sentence-level intonation in L1, L2, and unfamiliar languages. Studies were systematically collected, and included various measures of musicality and intonation perception. The meta-analysis combining these outcomes showed a robust positive correlation between musical ability and intonation perception. This effect did not differ between studies on L1 and unfamiliar languages. We suggest intonation perception in unfamiliar languages might be relatively easy due to the absence of semantic interference. Data on L2 users was lacking. Because semantic processing plays a role in L2 perception, we suggest further research is needed to investigate the influence of musical ability on intonation perception in L2 listening.
Kamala Harris, Maya Rudolph and the Prosody of Parody

Despite advances in the studies of both ethnolinguistic and prosodic variation, linguists still know relatively little about how individual speakers may use prosody to construct and perform aspects of their identity in dynamic ways. One novel way to study how individuals employ both personal and ethnolinguistic variation is to examine salient linguistic features that occur both in a natural context and in parodies of that same context. The current study analyzes speech from U.S. Vice President Kamala Harris and actor Maya Rudolph, who frequently parodies Harris on the American television program Saturday Night Live. Using a comparative analysis of data coded in the Autosegmental Metrical Phonology framework using MAE-ToBI conventions, I show that Rudolph closely mirrors several of the unique prosodic patterns employed by Harris, but that Rudolph does not simply mimic her; rather she employs exaggerated versions of Harris’ patterns, especially higher F0 peaks and more phrase-initial falsetto phonation. The results of this study expand our knowledge about how specific idiolectal variants connected to social and ethnic styles are enregistered as part of the public discourse. Additionally, it demonstrates the value of examining parodic performance to better understand and contextualize the speech of public figures.
Embeddedness, values and entrepreneur decision-making: Evidence from the creative industries

This paper explores embeddedness in small firms from a foundational perspective and how these foundations effect resource dependency and business decision-making. Building on debates in firms embeddedness and its role in addressing questions of resource-limitation, the paper positions embeddedness as outcome of a value-set occurring within an organisation directly affecting resource decisions. Using case studies of six creative industries small and micro firms, it argues foundational embeddedness influences firm-based practices and relationships over conventional business logics. Certain flexibilities in this foundational embeddedness can be seen, responding to external challenges through formation of esoteric relations and iterative systems. The extent of this flexibility is however limited by the entrepreneurs’ willingness to compromise individual values. Foundational embeddedness is thus a necessary consideration in understanding entrepreneurial decision-making.
The Current State of Information Technology Governance Literature

This chapter introduces current and prior IT governance literature across five key focus areas being strategic alignment of business and IT systems, delivery of value from IT systems, risk management of IT systems, management of IT resources and measurement of the performance of IT systems. The chapter focuses on synthesising the current literature on ITG to achieve three primary objectives. First, the review presents a detailed overview of research across the key focus areas of ITG. Second, the synthesis of the literature identifies important gaps in ITG research. Third, the review aims to guide future thinking and research on ITG in each of the focus areas. This chapter will provide a comprehensive understanding of the current state of IT governance literature.
Use of deep convolutional neural networks and change detection technology for railway track inspections

Railroad track inspections conducted in accordance with federal regulations and internal railway operating practices result in significant labor costs and occupy valuable network capacity. These factors, combined with advancements in the field of machine vision, have encouraged a transition from human visual inspections to machine-based alternatives. Commercial machine vision technologies for railway inspection currently exist, and automated analysis approaches—which deliver objective results—are available in some systems. However, they are limited to a “pass/fail” approach through the detection of components which fail to meet maintenance or geometry thresholds, as opposed to being able to detect subtle changes in track conditions to identify evolving problems. To overcome these limitations, this paper presents results from the field deployment and validation of a system that pairs three-dimensional (3D) machine vision with automated change detection technology. The change detection approach uses a deep convolution neural network (DCNN) to accurately characterize track conditions between repeat runs. Current automated track inspection technologies were studied, and the applicability of change detection is discussed. The paper presents the process for 3D image capture, DCNN training, and evaluation by comparing DCNN results to an expert human evaluator. Finally, it presents change detection results for fastener presence and spike height. Results indicate that this technology can successfully identify fasteners and spikes with percent accuracies greater than 98% and that it can successfully generate change detection results for comparison of track condition among runs.
Evaluation of Green Hotel Guests’ Behavioral Intention

Abstract Green or ecological consumers can gradually become a prominent market segment. The purpose of this study is to investigate tourists’ behavior intentions for staying overnight at green hotels by integrating environmental education (EE) from the Theory of Planned Behavior (TPB) perspective. Data of 350 usable questionnaires for this research were collected from a quasi-random selection of people at the checkout counter of three of the 19 winners of the 2008 green hotel competition in Taiwan. This result indicates that a green hotel that provides green service can be supported by supporting EE. The findings and applications of this study are useful for both academia and practitioners.
Design of low-dropout regulator for ultra low power on-chip applications

Low Drop Out (LDO) voltage regulators are commonly used to supply low-voltage digital circuits such as microprocessor cores. These digital circuits normally are continuously changing from one mode of operation to another. Therefore, the load demand can change rapidly resulting in large voltage transients at the output of the regulator which can adversely affect the digital circuitry. In this Master's Thesis, design topologies and challenges of very low-power fully integrated On-Chip Low-Dropout (LDO) regulators have been analyzed. Instead of conventional LDO which makes use of a large external capacitor to have better dynamic response and stability, a CapacitorLess LDO (CL-LDO) is chosen on considerations of smaller area. The most challenging part of designing this kind of regulator is achieving high current efficiency by reducing the quiescent current while ensuring good stability response as well as good regulation performance. Thus, different circuit techniques must be carefully added in order to balance the lack of the large external capacitor having the minimum impact on system efficiency. This work focuses on designing a fully integrated low-dropout regulator with good dynamic performance, high regulation performance and ultra-low power consumption. The stability is achieved by the use of two pole-splitting techniques, namely Cascode and Nested-Miller compensation. The good dynamic response with low quiescent current are achieved by the use of an adaptive biasing circuit, a gm-boost circuit and adaptive power transistor architecture.