Miracle-dz/UniFAR-FTUs huggingface dataset:
LncRNA-NEF inhibits proliferation, migration and invasion of esophageal squamous-cell carcinoma cells by inactivating wnt/β-catenin pathway.

OBJECTIVE Our study aimed to investigate the role of lncRNA-Neighboring Enhancer of FOXA2 (NEF) in esophageal squamous-cell carcinoma. PATIENTS AND METHODS Tumor tissues and adjacent tissues were obtained from esophageal squamous-cell carcinoma patients, and blood samples were extracted from both patients with esophageal squamous-cell carcinoma and healthy volunteers. The expression of NEF was detected by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR). All patients were followed-up for 5 years and ROC curve analysis and survival analysis were performed to evaluate the diagnostic and prognostic values of serum NEF for esophageal squamous-cell carcinoma. NEF expression vector was transfected into cells of esophageal squamous-cell carcinoma cell lines. Cell proliferation, migration and invasion were detected by CCK-8 assay, transwell migration assay, and transwell invasion assay, respectively. The interaction between NEF and wnt/β-catenin pathway were explored by Western blot and qRT-PCR. RESULTS Expression of NEF was significantly downregulated in tumor tissues than in adjacent tissues in most patients. Serum level of NEF was higher in esophageal squamous-cell carcinoma patients than in healthy controls, and was significantly correlated with tumor size and tumor distant tumor metastasis. Serum NEF is a promising diagnostic and prognostic marker for esophageal squamous-cell carcinoma. NEF overexpression inhibited cancer cell proliferation, migration and invasion. NEF overexpression decreased the expression levels of wnt/β-catenin pathway-related proteins, while Wnt activator showed no significant effects on NEF. However, Wnt inhibitor reduced the effects of NEF overexpression on cell proliferation, migration and invasion. CONCLUSIONS LncRNA NEF may inhibit the proliferation, migration and invasion of esophageal squamous-cell carcinoma cells by inactivating with wnt/β-catenin pathway.
Medical Correctness and User Friendliness of Available Apps for Cardiopulmonary Resuscitation: Systematic Search Combined With Guideline Adherence and Usability Evaluation

Background In case of a cardiac arrest, start of cardiopulmonary resuscitation by a bystander before the arrival of the emergency personnel increases the probability of survival. However, the steps of high-quality resuscitation are not known by every bystander or might be forgotten in this complex and time-critical situation. Mobile phone apps offering real-time step-by-step instructions might be a valuable source of information. Objective The aim of this study was to examine mobile phone apps offering real-time instructions in German or English in case of a cardiac arrest, to evaluate their adherence to current resuscitation guidelines, and to test their usability. Methods Our 3-step approach combines a systematic review of currently available apps guiding a medical layperson through a resuscitation situation, an adherence testing to medical guidelines, and a usability evaluation of the determined apps. The systematic review followed an adapted preferred reporting items for systematic reviews and meta-analyses flow diagram, the guideline adherence was tested by applying a conformity checklist, and the usability was evaluated by a group of mobile phone frequent users and emergency physicians with the system usability scale (SUS) tool. Results The structured search in Google Play Store and Apple App Store resulted in 3890 hits. After removing redundant ones, 2640 hits were checked for fulfilling the inclusion criteria. As a result, 34 apps meeting all inclusion criteria were identified. These included apps were analyzed to determine medical accuracy as defined by the European Resuscitation Council’s guidelines. Only 5 out of 34 apps (15%, 5/34) fulfilled all criteria chosen to determine guideline adherence. All other apps provided no or wrong information on at least one relevant topic. The usability of 3 apps was evaluated by 10 mobile phone frequent users and 9 emergency physicians. Of these 3 apps, solely the app “HELP Notfall” (median=87.5) was ranked with an SUS score above the published average of 68. This app was rated significantly superior to “HAMBURG SCHOCKT” (median=55; asymptotic Wilcoxon test: z=−3.63, P<.01, n=19) and “Mein DRK” (median=32.5; asymptotic Wilcoxon test: z=−3.83, P<.01, n=19). Conclusions Implementing a systematic quality control for health-related apps should be enforced to ensure that all products provide medically accurate content and sufficient usability in complex situations. This is of exceptional importance for apps dealing with the treatment of life-threatening events such as cardiac arrest.
AIS Electronic

The challenges faced by domain experts, commitments made to domain-specific rule (DSR) languages and process design are described. We investigate the business application developments and existing challenges of evaluation strategies of DSR articulations. Often, multiple domain scenarios pose end-user predicaments complicating the computational ability of DSR. In addition, implementation of DSR and its configuration are belated due to poorly evaluated usability criteria. A new framework is needed, facilitating the DSR language and enhancing the computational intelligence. We intend to evaluate the performance of DSR generation and framework integration with variety of usability conditions including efficiency and effectiveness of configuration through system usability score (SUS). Empirical research involving experimental data, questionnaire surveys, and interview outcomes provide conclusive evaluation attributes and their fact instances from SUS. Both manual and semi-automatic configurations are tested. Semi-automatic configuration appears to be more efficient and satisfactory with regard to artefact performance, quality, learnability, user-friendly and reliability.
Near Real time Multisensor Algorithm for Deforestation Alert Over the Dry Chaco Forest

The objective of this work is to evaluate the performance of a change detection algorithm for deforestation monitoring based on MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) datasets. The algorithm is based on the statistical characterisation of the EVI and LST historical values for each pixel. The goal is to monitor abrupt decreases in those variables dynamics, which could be associated with deforestation events. This model was tested on real satellite time series available over a pilot area in Dry Chaco Forest, Argentina, where deforestation was common in the 2004–2016 period. As validation, a comparison with a benchmark product based on Landsat images is also presented, showing a 51.6% precision, 74.4% recall and an F-score of 0.60 for deforestation in 2013. These results show the advantages of using an automatic algorithm to monitor break points in the time series and the potential of combining LST and EVI to identify deforestation events.
Road Segmentation of UAV RS Image Using Adversarial Network with Multi-Scale Context Aggregation

Semantic segmentation using adversarial networks has been approved to produce the better artificial results in image processing fields. Focused on current Deep Convolutional Neural Networks (DCNNs), since the convolutional kernel size has been fixed in every convolutional operation, the small objects would be ignored with large convolutional kernel size, and the segmentation result of large objects is not continuous with small convolutional kernel size. The paper developed a semantic segmentation model that combined the adversarial networks with multi-scale context aggregation. Further, the model was applied to road segmentation of UAV RS images. The experimental results of this semantic segmentation model with multi-scale context aggregation has a better performance for road segmentation and fit well with the reference standard results. It can improve the road segmentation accuracy obviously in the situation where there are other small regions whose shape or color is similar to road regions in UAV RS images.
The Role of Prior Self-disclosure in Users' Subsequent Self-disclosure in Sharing Economy

New information technologies have greatly enhanced consumers’ ease of use through self-disclosure. However, they have also raised troubling issues about privacy concern. Different with previous literature about self-disclosure with heavy dependency on privacy calculus theory and the overlook of requests for self-disclosure on users’ perceived privacy concern, this study focuses on the investigation into how users respond to the continual streams of requests for self-disclosure as an unavoidable feature of on-demand services adopting the new economic concept ---- sharing economy. By leveraging Prominence-Interpretation Theory, we propose that prior self-disclosure in the registration stage will affect individuals’ understanding about subsequent requests for information in normal use in terms of perceived expertise and trustworthiness, which jointly shape individuals’ perceived privacy concern, thus finally determine their actual behavior of self-disclosure.
A Potential Low Cost Remote Sensing Using GPS Derived PWV

In this paper, the Precipitable Water Vapor (PWV) content of the atmosphere is derived using the Global Positioning System (GPS) signal delays. The PWV values from GPS are calculated at different elevation cut-off angles. It was found that the significant range of elevation cut-off angles is from 5° to 50°. The PWV values calculated from GPS using varying cutoff angles from this range were then compared to the PWV values calculated using the radiosonde data. The correlation coefficient and the Root Mean Square (RMS) error between the GPS and radiosonde derived PWV decreases with the increasing cut-off angle and the distance between the two. The seasonal parameters also effect the relation between the two.
Genotype to phenotype: Diet-by-mitochondrial DNA haplotype interactions drive metabolic flexibility and organismal fitness

Diet may be modified seasonally or by biogeographic, demographic or cultural shifts. It can differentially influence mitochondrial bioenergetics, retrograde signalling to the nuclear genome, and anterograde signalling to mitochondria. All these interactions have the potential to alter the frequencies of mtDNA haplotypes (mitotypes) in nature and may impact human health. In a model laboratory system, we fed four diets varying in Protein: Carbohydrate (P:C) ratio (1:2, 1:4, 1:8 and 1:16 P:C) to four homoplasmic Drosophila melanogaster mitotypes (nuclear genome standardised) and assayed their frequency in population cages. When fed a high protein 1:2 P:C diet, the frequency of flies harbouring Alstonville mtDNA increased. In contrast, when fed the high carbohydrate 1:16 P:C food the incidence of flies harbouring Dahomey mtDNA increased. This result, driven by differences in larval development, was generalisable to the replacement of the laboratory diet with fruits having high and low P:C ratios, perturbation of the nuclear genome and changes to the microbiome. Structural modelling and cellular assays suggested a V161L mutation in the ND4 subunit of complex I of Dahomey mtDNA was mildly deleterious, reduced mitochondrial functions, increased oxidative stress and resulted in an increase in larval development time on the 1:2 P:C diet. The 1:16 P:C diet triggered a cascade of changes in both mitotypes. In Dahomey larvae, increased feeding fuelled increased β-oxidation and the partial bypass of the complex I mutation. Conversely, Alstonville larvae upregulated genes involved with oxidative phosphorylation, increased glycogen metabolism and they were more physically active. We hypothesise that the increased physical activity diverted energy from growth and cell division and thereby slowed development. These data further question the use of mtDNA as an assumed neutral marker in evolutionary and population genetic studies. Moreover, if humans respond similarly, we posit that individuals with specific mtDNA variations may differentially metabolise carbohydrates, which has implications for a variety of diseases including cardiovascular disease, obesity, and perhaps Parkinson’s Disease.
Semi-Automatic Deforestation Detection Algorithm with PALSAR-2/ScanSAR HH/HV Polarizations

A preliminary version of the semi-automatic deforestation detection algorithm was developed for the JJ-FAST system, which monitors deforestation and forest changes in tropical regions for approximately every 1.5 months and covers 77 countries. PALSAR-2/ScanSAR HH, HV, HH and HV ratio were used to detect various deforestation stages. Multitemporal data were used to suppress the effect of seasonality and rainfall. Moreover, the deforestation accuracies for the active deforestation spots in Brazil and Peru were estimated. The user's accuracies achieved as 80.5% in the dry season, but these decreased to 11.1% in the rainy season.
Basin Scale pCO2 Distribution in Case 1 Waters: An Investigation from Bay of Bengal, India

Partial pressure of Carbon Dioxide (pCO2) is an important parameter to determine the air-sea CO2 fluxes. The sea surface pCO2 is highly variable, primarily regulated by seasonal Sea Surface Temperature (SST). Bay of Bengal (BoB) remains an underexplored region in terms of air-sea interaction studies. While a few studies have been conducted at the western and northern coast of BoB, pCO2 estimation in case 1 waters at basin scale has not been carried out so far. The present study aims at developing an empirical relation for the estimation of the pCO2 using SST and Sea Surface Salinity (SSS) and developing seasonal climatological pCO2 maps for case 1 waters of BoB using remotely sensed SST and SSS. The results show that pCO2 is significantly correlated $(\mathrm{R}^{2}=0.8)$ with SST and SSS and more pCO2 maps can be prepared for seasons to understand the effects of seasonality and physical phenomena.
LCR: Load-Aware Cache Replacement Algorithm for Flash-Based SSDs

Flash-based SSDs are usually equipped with an onboard cache to further improve system performance by smoothing the gap between the upper-level applications and lower-level flash chips. Since modern SSDs are usually composed of multiple flash chips, and the load of flash chips are significantly different, it is very meaningful to be aware of the chip load condition when designing a cache replacement algorithm. Nevertheless, existing cache replacement algorithms only consider to reduce the cache miss ratio so as to reduce the I/O requests to the underlying flash memory as much as possible, none of them considers the load condition of flash chips. In this paper, we propose a Load- aware Cache Replacement algorithm, called LCR, to improve the performance of flash-based SSDs. The basic idea is to give a higher priority to cache the blocks on overloaded flash chips. We evaluate the performance of our scheme by using a trace- driven simulator with multiple real-world workloads, and results show that compared with the most common algorithm LRU and the state-of-the-art algorithm GCaR, LCR reduces the average response time by as much as 39.2% and 12.3%, respectively.
Salient Object Detection Via Double Sparse Representations Under Visual Attention Guidance

This paper introduces a novel method for salient object detection from the perspective of sparse representation under visual attention guidance. After pretreatment and regional analysis with eye fixation detection and multi scale segmentation, regions that are used to make up the foreground and background dictionaries are respectively selected by sorting the visual attraction level of all image regions. For saliency measurement, the reconstruction errors instead of common local and global contrasts are used as the saliency indicator, which is expected to improve the object integrity. In addition, the multi scale workflow is conductive to enhance the robustness for objects of different sizes. The proposed method was compared to six state-of-the-art saliency detection methods using three benchmark datasets, and it was confirmed to have more favorable performance in the detection of multiple objects as well as maintaining the integrity of the object area.
Gaze Patterns and the Temporal Organization of Multiple Activities in Mobile Smartphone Uses

We have analyzed the temporal organization of gaze switches (to and away from the mobile screen) of mobile smartphone users in urban environments, and we discuss how such patterns of gaze switches can help us understand how users jointly manage mobile communication as well as other activities in everyday urban settings. More specifically, we report on the findings of an empirical study of smartphone use in transport situations, in which we have combined video recordings made with user-worn camera glasses with mobile screen capture data. First we show how being oriented toward multiactivity appears as a particular form of attunement to the potential sequential implicativeness of events occurring on screen or in the mobility environment. This provides the opportunity to treat them as possible occasions to switch the orientation of one’s gaze from one activity-relevant field of activity to another. Second we discuss how interfaces with a “rugged” sequential texture. We argue that such rugged interfaces offer frequent sequential opportunities that might be especially useful in multiactivity situations in public places, where balancing the demands of two or more activities may constitute a serious moral and/or safety concern.
City Research Online

Models can help scientists study and understand phenomena. Such models need to be informed by theory. We report on the early stages of our ongoing study in which we use interactive visualisation to help improve the construction of theory-driven models, by facilitating the exploration of statistical summaries of input variables, compare the quality of alternative models and keep track of the model-building process. Later work will investigate whether machine-learning techniques can be incorporated without compromising the models’ theoretical bases.
Assessing Rigour Criteria in Information Systems Research - The Example of Case Study Research Methodology

Research in information systems (IS) calls for increased validity of research findings through a rigorous research process. This research investigates the approach of researchers to suggested rigour criteria. Drawing upon existing literature on case study research methodology, we identify a set of criteria for establishing the rigour of a case study research. A coding scheme is developed based on these criteria. Our overarching proposition is that a rigorous research process should specify most of the identified criteria. Applying the content analysis approach, we conducted a systematic literature review of case studies published in the basket-of-eight journals in IS to ascertain researchers’ approach towards stipulated rigor criteria. Our result and observation indicate that although researchers prioritise rigour in the conduct of their research, there is an increasing rate of idiosyncratic research practices in addition to dearth of guidelines for analysing qualitative data in information systems research.
A 0.13- $\mu\text{m}$  CMOS SoC for Simultaneous Multichannel Optogenetics and Neural Recording

This paper presents a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS system-on-chip (SoC) for simultaneous multichannel optogenetics and multichannel neural recording in freely moving laboratory animals. This fully integrated system provides 10 multimodal recording channels with analog-to-digital conversion and a four- channel LED driver circuit for optogenetic stimulation. The bio-amplifier design includes a programmable bandwidth (BW) (0.5 Hz–7 kHz) to collect either the action potentials (APs) and/or the local field potentials (LFPs) and has a noise efficiency factor (NEF) of 2.30 for an input-referred noise of 3.2 <inline-formula> <tex-math notation="LaTeX">$\mu V_{\text {rms}}$ </tex-math></inline-formula> within a BW of 10–7 kHz. The low-power delta–sigma (<inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula>) MASH 1-1-1 analog-to-digital converter (ADC) is designed to work at low oversampling ratios (OSRs) (≤50) and has an effective number of bits (ENOB) of 9.75 bits at an OSR of 25 (BW of 10 kHz). The utilization of a <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> ADC is the key to address the flexibility needed to address different noise versus power consumption tradeoff of various experimental settings. It leverages a new technique that reduces its size by subtracting the output of each <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> branch in the digital domain, instead of in the analog domain as done conventionally. The ADC is followed by an on-chip fourth-order cascaded integrator-comb (CIC4) decimation filter (DF). A whole recording channel, including the bio-amplifier, the <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> MASH 1-1-1, and the DF consumes 11.2 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula>. Optical stimulation is performed with an LED driver using a regulated cascode current source with feedback that can accommodate a wide range of LED parameters and battery voltages. The SoC is validated <italic>in vivo</italic> within a wireless experimental platform in both the ventral posteromedial nucleus (VPM) and cerebral motor cortex brain regions of a virally mediated Channelrhodopsin-2 (ChR2) rat.
Hisui Status Toward FY2019 Launch

Hyperspectral Imager Suite (HISUI) is a future spaceborne hyperspectral Earth imaging system being developed by Japanese Ministry of Economy, Trade, and Industry (METI). HISUI will be launched and deployed on International Space Station (ISS) for two - three year operation from 2020. Manufacturing and testing of HISUI Flight Model were almost completed, and design of HISUI Exposed Payload System is being conducted. HISUI data policy and research announcement as well as synergy with other earth observing instruments onboard ISS are also being discussed.
Early-time diffusion in imaging through obscuring random media: two-way propagation and deblurring

The radiative transport theory predicts that a short pulse propagating through a random medium consisting of discrete scatterers of sizes large compared to the wavelength develops to develop an "early-time diffusion" (ETD) component: a sharply rising structure in the time-resolved intensity, immediately following the coherent (ballistic) signal, but attenuated at a rate substantially lower than the coherent attenuation. This phenomenon offers a possibility of application in imaging through obscuring (e.g., atmospheric) media. We describe here an imaging scenario utilizing the ETD signal, evaluate the resulting point-spread function characterizing the image resolution, and show how that resolution can be significantly improved by means of regularized deconvolution techniques.
Autonomous vehicle services or ride-sharing services? A game theoretic investigation

Transportation service is rapidly changing in past few decades. On one hand, ride-sharing services in the sharing economy impacts the transportation industry. On the other hand, autonomous vehicles may also revolutionize transportation services. We consider a transportation service provider choosing between offering ride-sharing services or autonomous vehicle services. For each service mode, we derive its optimal prices, subsidies, revenue sharing proportions, and quantity of vehicle deployment. A comparison between these two modes is then conducted. We find that the autonomous vehicle service is more profitable than the ride-sharing one under economy of scale. Interestingly, the optimal service price decreases in the cost of deploying autonomous vehicles. Our study thus sheds lights in the choice of quality incentive and price incentive.