Couldn't or Wouldn't? the Influence of Privacy Concerns and Self-Efficacy in Privacy Management on Privacy Protection

Sampling 515 college students, this study investigates how privacy protection, including profile visibility, self-disclosure, and friending, are influenced by privacy concerns and efficacy regarding one's own ability to manage privacy settings, a factor that researchers have yet to give a great deal of attention to in the context of social networking sites (SNSs). The results of this study indicate an inconsistency in adopting strategies to protect privacy, a disconnect from limiting profile visibility and friending to self-disclosure. More specifically, privacy concerns lead SNS users to limit their profile visibility and discourage them from expanding their network. However, they do not constrain self-disclosure. Similarly, while self-efficacy in privacy management encourages SNS users to limit their profile visibility, it facilitates self-disclosure. This suggests that if users are limiting their profile visibility and constraining their friending behaviors, it does not necessarily mean they will reduce self-disclosure on SNSs because these behaviors are predicted by different factors. In addition, the study finds an interaction effect between privacy concerns and self-efficacy in privacy management on friending. It points to the potential problem of increased risk-taking behaviors resulting from high self-efficacy in privacy management and low privacy concerns.Radio-Television-Fil

An in situ study on the coalescence of monolayer-protected Au-Ag nanoparticle deposits upon heating

The structural evolution of thiolate-protected nanoparticles of gold, silver, and their alloys with various Au/Ag ratios (3:1, 1:1, and 1:3) upon heating was investigated by means of in situ synchrotron radiation X-ray diffraction. The relationships between the coalescence and composition of nanoparticles, as well as the surfactant reactions, were clarified. Experimental results show that there existed a critical temperature ranging from 120°C to 164°C, above which the tiny broad X-ray diffraction peaks became sharp and strong due to particle coalescence. The coalescence temperatures for alloy nanoparticle deposits were clearly lower than those for pure metals, which can be ascribed to the rivalry between the thermodynamic effect due to alloying and the interactions between surface-assembled layers and the surface atoms of the nanoparticles. The strong affinity of thiolates to Ag and thus complex interactions give rise to a greater energy barrier for the coalescence of nanoparticles into the bulk and subsequent high coalescence temperature. The influences of particle coalescence on the optical and electrical properties of the nanoparticle deposits were also explored

A Survey and Evaluation of FPGA High-Level Synthesis Tools

High-level synthesis (HLS) is increasingly popular for the design of high-performance and energy-efficient heterogeneous systems, shortening time-to-market and addressing today's system complexity. HLS allows designers to work at a higher-level of abstraction by using a software program to specify the hardware functionality. Additionally, HLS is particularly interesting for designing field-programmable gate array circuits, where hardware implementations can be easily refined and replaced in the target device. Recent years have seen much activity in the HLS research community, with a plethora of HLS tool offerings, from both industry and academia. All these tools may have different input languages, perform different internal optimizations, and produce results of different quality, even for the very same input description. Hence, it is challenging to compare their performance and understand which is the best for the hardware to be implemented. We present a comprehensive analysis of recent HLS tools, as well as overview the areas of active interest in the HLS research community. We also present a first-published methodology to evaluate different HLS tools. We use our methodology to compare one commercial and three academic tools on a common set of C benchmarks, aiming at performing an in-depth evaluation in terms of performance and the use of resources

The landscape, properties, and determinants of transcriptional activation of endogenous transposable elements in grapevine (Vitis vinifera L.) : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

Transposable elements (TEs) are an intrinsic mutagen of eukaryotic genomes and have been proposed to be important in increasing genetic diversity in plants. It has been known that biotic and abiotic stress treatments induce TE transcription, the first stage in TE mobilisation. This research began with an investigation of TE transcription activity in grapevine embryogenic callus subjected to biotic stressors (Botrytis cinerea extracts and live Hanseniaspora uvarum cultures) to determine the location and regulation of autonomous TEs. Short-read RNA sequencing (RNAseq) has been commonly used to determine TE transcription patterns at a family level. This research sought to further these approaches by establishing an analysis pipeline to identify the expression of individual TE loci from Illumina RNAseq data. We efficiently identified that only 1.7%-2.5% of total annotated TE loci were transcribed in our system. This work identified a strong tendency for TE expression candidates to be found within introns of expressed genes. It was also discovered that these pairs of TEs and genes shared the same differential expression patterns in response to applied stressors. Our analysis pipeline was successfully validated using publically available RNAseq datasets from Arabidopsis, wild-type and epigenetic mutant (ibm2 and ddm1) lines, and Drosophila datasets of amyotrophic lateral sclerosis (ALS) models exhibiting a TE transcriptional storm. We successfully identified an Arabidopsis COPIA-93 locus previously proven to mobilise in ddm1 mutant and a subset of Drosophila TE loci that potentially contributed to full-length autonomous TE transcripts in the ALS models that have not been previously reported. Oxford Nanopore Technology (ONT) cDNA sequencing was deployed to determine whether autonomous TEs were being expressed as a precursor of mobilisation. Only low levels of full-length transcription of one Gypsy-V1 locus and three hAT-7 loci was detected in this data, suggesting rare intact transcription from autonomous TE loci despite stress treatments. This finding suggested that TE mobilisation might require inhibition of the epigenetic silencing system. We, therefore, treated embryogenic callus with the histone deacetylase inhibitors (HDACi), trichostatin A (TSA) or 4-phenylbutyric acid (4PBA), to alter the heterochromatic architecture of callus cells. Only the 4PBA treatment showed a noticeable shift in the transcriptional landscape of TE transcription, significantly increasing the proportion of intergenic TE loci in the expression candidate pool and resulting in significant up-regulation of 2,059 TE loci. ONT cDNA sequencing of these samples detected very low levels of intact sequencing reads from different yet a single Gypsy-V1 locus and six hAT-7 loci. Five genes participating in the RNA-dependent DNA methylation (RdDM) pathway (AGO2, AGO4, RDR1, RDR6, and NERD) were upregulated, suggesting that callus exposed to 4PBA responded by an enhancement of RdDM, maintaining effective control of TE transcription and therefore TE mobility. Overall, this thesis contributes to the understanding of the landscape, properties, and determinants of transcriptional activation of endogenous transposable elements, revealing the closely connected transcriptional relationship between TEs and co-localised genes. These findings shed light on the genetic and epigenetic impact of endogenous TE activation on genes in nature

Use electrochemistry to charge the next dynamic thermal metamaterials

Electrochemistry has enabled a wide range of important energy technologies such as fuel cells and batteries, emerging as a powerful tool to achieve active materials and devices with novel applications. In this Perspective, we highlight the great potential of electrochemistry in propelling the next generation of dynamic thermal metamaterials with a focus on thermal radiation applications. After a brief introduction of the mechanisms of electrochemistry to change material properties, we discuss the possibilities of achieving highly tunable thermal radiation features by electrochemically manipulating the carrier densities of plasmonic materials. Recent studies in the intersections between electrochemistry, metamaterials, and thermal radiation applications are reviewed, indicating an emerging research direction incorporating these three fields — electrochemically dynamic thermal metamaterials. Towards this direction, we anticipate a promising pathway of employing conducting polymers and point out its remarkable opportunities and potential challenges. We hope this perspective could encourage more researchers to contribute to the development of this interdisciplinary field targeting the next energy technologies and applications

Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic Scenes

In this paper, we study multi-label atomic activity recognition. Despite the notable progress in action recognition, it is still challenging to recognize atomic activities due to a deficiency in a holistic understanding of both multiple road users' motions and their contextual information. In this paper, we introduce Action-slot, a slot attention-based approach that learns visual action-centric representations, capturing both motion and contextual information. Our key idea is to design action slots that are capable of paying attention to regions where atomic activities occur, without the need for explicit perception guidance. To further enhance slot attention, we introduce a background slot that competes with action slots, aiding the training process in avoiding unnecessary focus on background regions devoid of activities. Yet, the imbalanced class distribution in the existing dataset hampers the assessment of rare activities. To address the limitation, we collect a synthetic dataset called TACO, which is four times larger than OATS and features a balanced distribution of atomic activities. To validate the effectiveness of our method, we conduct comprehensive experiments and ablation studies against various action recognition baselines. We also show that the performance of multi-label atomic activity recognition on real-world datasets can be improved by pretraining representations on TACO. We will release our source code and dataset. See the videos of visualization on the project page: https://hcis-lab.github.io/Action-slot

3D-PL: Domain Adaptive Depth Estimation with 3D-aware Pseudo-Labeling

For monocular depth estimation, acquiring ground truths for real data is not easy, and thus domain adaptation methods are commonly adopted using the supervised synthetic data. However, this may still incur a large domain gap due to the lack of supervision from the real data. In this paper, we develop a domain adaptation framework via generating reliable pseudo ground truths of depth from real data to provide direct supervisions. Specifically, we propose two mechanisms for pseudo-labeling: 1) 2D-based pseudo-labels via measuring the consistency of depth predictions when images are with the same content but different styles; 2) 3D-aware pseudo-labels via a point cloud completion network that learns to complete the depth values in the 3D space, thus providing more structural information in a scene to refine and generate more reliable pseudo-labels. In experiments, we show that our pseudo-labeling methods improve depth estimation in various settings, including the usage of stereo pairs during training. Furthermore, the proposed method performs favorably against several state-of-the-art unsupervised domain adaptation approaches in real-world datasets.Comment: Accepted in ECCV 2022. Project page: https://ccc870206.github.io/3D-PL