Miracle-dz/UniFAR-FTUs huggingface dataset:
An Interactive Low-Cost Smart Assistant System: Information Kiosk as Plug & Play Device

The demand for a self-service device that can relay the information of an organization while maintaining privacy is quite crucial in today’s world. The introduction of kiosks in such states resolves this issue but the prevailing kiosk manufacturing companies don’t provide a plug & play system for kiosks. In order to nullify these issues, the design of an information kiosk as a plug & play system has been described in this paper. This kiosk can provide real-time information to the users removing the necessity of any sort of human assistance. Unlike the existing kiosks, this is a plug & play device, which makes it easier to install any specification or modification required as per the organization’s requirement. It also stands out from the existing ones through the use of image processing and computer vision making it more interactive as well as user friendly. The system also possesses the capability of processing a vast amount of data. These data are collected through sensors and other means as well as conveying with high accuracy and privacy. Furthermore, the system is low-cost in comparison with the available kiosks in the market.
Thermal Modeling of GaN HEMT Devices With Diamond Heat-Spreader

Harvesting the potential performance of GaN-based devices in terms of the areal power density and reliability, relies on the efficiency of their thermal management. Integration of extremely high thermal conductivity Single-crystalline CVD-diamond serves as an efficient solution to their strict thermal requirements. However, the major challenge lies in the Thermal Boundary Resistance (TBR) at the interface of GaN/Diamond or SiC/Diamond. Junction temperature of the device shows a sensitivity of 1.28°C for every unit of TBR for GaN-on-Diamond compared to 0.43°C for every 10 units of TBR for GaN/SiC-on-Diamond. Finite Volume Thermal Analysis has shown a limit of around 22 m2K/GW beyond which the merit of proximity to the heat-source for GaN-on-Diamond can no more outperform GaN/SiC-on-Diamond. Besides, due to the temperature dependency of the thermal conductivity K, an increase in the temperature causes an increase in the thermal resistivity of the device which is more significant in high power operations. Simplified assumption of constant K overestimates the device performance by resulting in 17.4°C lower junction temperature for the areal power density of 10W/mm. Other part of the project regarding the in-house growth of CVD-diamond to be bonded to the GaN device has been simultaneously in progress.
Transient Error Correction Coding Scheme for Reliable Low Power Data Link Layer in NoC

Ensuring reliable data transmission in multicore System on Chip (SoC), which employs Network on Chip (NoC), is a challenging task. This task is well addressed by Error Correcting Codes (ECC) in on-chip as well as off-chip networks. ECC significantly improves reliability of NoC interconnects with area and power overhead. In this paper, we propose a novel Transient Error Correction (TEC) coding scheme for reliable low power data link layer in NoC to attain a high error correction capability with less hardware overhead. Performance of TEC scheme is evaluated with realistic traffic patterns and validated with simulation results. The proposed scheme has less residual errors than the Hamming product code enabling reliable transmission at lower link swing voltage. Further, the scheme reduces the power consumption of NoC interconnects up to 71% as compared to Hamming product code with a marginal increase in codec delay and thus router delay. TEC scheme performs well in high noise environment with no delay penalty associated with retransmission.
Identification and Characterization of New Bacteriophages to Control Multidrug-Resistant Pseudomonas aeruginosa Biofilm on Endotracheal Tubes

Studies involving antimicrobial-coated endotracheal tubes are scarce, and new approaches to control multidrug-resistant Pseudomonas aeruginosa biofilm on these devices should be investigated. In this study, five new P. aeruginosa bacteriophages from domestic sewage were isolated. All of them belong to the order Caudovirales, Myoviridae family. They are pH and heat stable and produce 27 to 46 particles after a latent period of 30 min at 37°C. Their dsDNA genome (ranging from ∼62 to ∼65 kb) encodes 65 to 89 different putative proteins. They exhibit a broad lytic spectrum and infect 69.7% of the P. aeruginosa strains tested. All the bacteriophages were able to reduce the growth of P. aeruginosa strains in planktonic form. The bacteriophages were also able to reduce the biofilm viability rates and the metabolic activity of P. aeruginosa strains in a model of biofilms associated with endotracheal tubes. In addition, scanning electron microscopy micrographs showed disrupted biofilms and cell debris after treatment of bacteriophages, revealing remarkable biofilm reduction. The lytic activity on multidrug-resistant P. aeruginosa biofilm indicates that the isolated bacteriophages might be considered as good candidates for therapeutic studies and for the application of bacteriophage-encoded products.
A Novel Deep Belief Network and Extreme Learning Machine Based Performance Degradation Prediction Method for Proton Exchange Membrane Fuel Cell

Lifetime and reliability seriously affect the applications of proton exchange membrane fuel cell (PEMFC). Performance degradation prediction of PEMFC is the basis for improving the lifetime and reliability of PEMFC. To overcome the lower prediction accuracy caused by uncertainty and nonlinearity characteristics of degradation voltage data, this article proposes a novel deep belief network (DBN) and extreme learning machine (ELM) based performance degradation prediction method for PEMFC. A DBN based fuel cell degradation features extraction model is designed to extract high-quality degradation features in the original degradation data by layer-wise learning. To tackle the issues of overfitting and instability in fuel cell performance degradation prediction, an ELM with good generalization performance is introduced as a nonlinear prediction model, which can get some enhancement of prediction precision and reliability. Based on the designed DBN-ELM model, the particle swarm optimization (PSO) algorithm is used in the model training process to optimize the basic network structure of DBN-ELM further to improve the prediction accuracy of the hybrid neural network. Finally, the proposed prediction method is experimentally validated by using actual data collected from the 5-cells PEMFC stack. The results demonstrate that the proposed approach always has better prediction performance compared with the existing conventional methods, whether in the cases of various training phase or the cases of multi-step-ahead prediction.
Blockchain for Organising Effective Grass-Roots Actions on a Global Commons: Saving The Planet

An overwhelming majority of experts has been flagging for decades that “Saving the Planet” requires immediate, persistent and drastic action to curb a variety of catastrophic risks over the 21st century. However, despite compelling evidence and a range of suggested solutions, transnational coordination of effective measures to protect our biosphere continues to fall short. To remedy, we propose a novel platform for addressing the central issue of affording trust, transparency and truth while minimising administrative overheads. This will empower an even loosely organised, global grass-roots community to coordinate a large-scale project on a shared goal (“Commons”) spanning the digital and real world. The Web3 concept is based on the swiftly emerging “Blockchain” and related cryptographic, distributed and permissionless technologies. “Wisdom of the crowds” mechanisms involving competitive parallelisation and prediction markets are enabled by formalised reputation and staking to incentivise high-quality work, fair validation and best management practice. While these mechanisms have been (mostly separately) applied to science, business, governance, web, sensor, information and communication technologies (ICT), our integrative approach around Blockchain-enabled ‘operating principles and protocols’ sets the basis for designing novel forms of potentially crowdfunded Decentralised Autonomous Organisations (DAOs).
Adaptive Anchor-Based Partial Multiview Clustering

Partial multiview clustering, which aims to effectively merge multiple prespecified incomplete views to improve clustering performance, is a research hotspot and difficulty in the field of machine learning. Guo et al. proposed a partial multiview clustering method (APMC) based on anchor graph, which uses a Gauss kernel function to solve the similarity matrix. The Gaussian kernel function is sensitive to parameter $\sigma $ , and it is difficult to find the optimal value only by stepwise adjustment in practical applications. This undoubtedly affects the practicality of the APMC algorithm. To address this issue, an adaptive partial multiview clustering method based on anchor graph (AAPMC) is developed in this paper, which proposes an adaptive neighbor assignment strategy and utilizes it to improve the anchor-based similarity matrix computation of each view. The method proposed in this paper uses an adaptive method to solve the similarity matrix, eliminating the tediousness of parameter adjustment. In addition, the non-iterative method based on anchors is used to solve the optimal solution with low time complexity and is suitable for large-scale datasets. In short, our method is simple and effective, and it is easier to implement in practice. Extensive experiments show that our model can not only effectively solve the parameter setting problem, but also performs better than the state-of-the-art partial multiview clustering methods.
How does E-commerce Affects A Brick and Mortar Department Store? A Qualitative Case Study Analysis at one of National Department Store in Indonesia

This research aims to explore how e-commerce affects a brick and mortar department store and how a brick and mortar department store cope in digital era. This study is qualitative research with single case study approach at one of national department store in Indonesia. The data was collected using semi-structured interview. Five participants were willing to take part in this study anonymously. The participants' job titles are chief of financial officer (CFO), company's director, chief marketing officer (CMO), head of marketing and customer's loyalty, and regional store manager. To elaborate the interview data, 160 open-ended questionnaires were distributed to the department store customers. The data analysis techniques used in this research are pattern matching and linking the data to propositions. The results of this study indicate that E-commerce has small effect on a bricks and mortar department store and the company would combine offline stores and online technology. The theoretical implication of this research is confirming previous theory and applying the brick and click framework theory into practice. The managerial implication of this study is that a brick and mortar department store could combine offline stores and online technology if the synergy between channels is achieved. The value of this study is providing insight on how e-commerce affects a brick and mortar department store and how a brick and mortar department store turning into brick and click department store in order to cope in digital era.
On the Design of Grid-Side Inverter Voltage Controllers

Grid-side inverter voltage controllers are commonly designed based on the dynamics of the output filter. While the dynamics of the coupling inductance is sometimes also taken into account, the grid dynamics are almost always neglected. However, as the neglected interplay of the controllers through the grid can be crucial, a stable overall power system can not be guaranteed. To address this problem, we derive a sufficient condition for the stability of the overall system which can be considered during the common decentralized design procedure. We propose a new, simpler control structure for voltage control, which has more degrees of freedom than the conventional control structures. Based on an exemplary microgrid, we demonstrate how the control parameters can be designed decentrally using our stability condition. Simulations finally show that the decentrally designed controllers indeed yield a stable and robust overall system. Our results can also be applied in order to ascertain the stability of energy networks consisting of coupled microgrids.
Integrating Factor Analysis and Multi Dimensional Scaling for Brand Positioning of E-Commerce Platforms

Brand positioning is crucial for any company, as it help to understand the company position against its competitors, and how to fit its marketing mix and strategy to win more consumers. The research aims to analyze brand position of top six e-commerce platform (Tokopedia, Shopee, Bukalapak, Lazada, BliBli and JD.ID) within consumers in Two cities in Indonesia, Jakarta & Tangerang. Products attributes were gathered through literature review and brainstorming. Factor analysis were then used to reduce consumers' attributes into 4 dimensions, i.e. E-commerce Capability, Customer Service, Value for Money, and Product Offering. Six perpetual maps were then created using Multi-dimensional scaling to analyze top six brands on those dimensions. Results shows that Tokopedia and Shopee are superior in E-commerce Capability, whilst sharing similar positioning in term of Value for Money and Product Offering. BliBli is perceived to be superior in Customer Service and can capitalize this dimension as their differentiation strategy.
Selection of Reference Genes for Quantitative Real-Time PCR in Aquatica leii (Coleoptera: Lampyridae) Under Five Different Experimental Conditions

Aquatic fireflies are important indicators of the quality of freshwater environments and key models for research on insect adaptation to freshwater environments. For these investigations, gene expression analyses using quantitative real-time PCR are heavily dependent on reliable reference genes. In this study, based on a transcriptome assembly and annotation for the aquatic firefly Aquatica leii at the adult and larval stages, 10 candidate reference genes (α-tubulin, β-tubulin, β-actin, EF1A, SDHA, UBQ, GST, GAPDH, RPS31, and RPL13A) were identified for analyses of expression stability. Quantitative real-time PCR analyses for each candidate reference genes in A. leii was conducted for four developmental stages, four adult tissue types, two adult sexes, and two ecological stressors [adults exposed to five temperatures and larvae exposed to four concentrations of benzo(a)pyrene]. Results were evaluated by three independent algorithms (geNorm, NormFinder, and BestKeeper) and one comparative algorithm (RefFinder). The expression stability of candidate reference genes in A. leii differed under various conditions. Reference genes with the most stable expressions levels in different tissues, temperatures, sexes, developmental stages, and concentrations of benzo(a)pyrene were α-tubulin, GST, β-actin, β-tubulin, and α-tubulin, respectively. Furthermore, the optimal normalization factors (NFs) for the quantification of the expression levels of target genes by quantitative real-time PCR analyses of A. leii were identified for each experimental group. In particular, NF = 2 for different tissues (α-tubulin + β-tubulin), different sexes (β-actin + EF1A), and larvae exposed to different concentrations of benzo(a)pyrene (α-tubulin + EF1A); NF = 3 for developmental stages (GST + GAPDH + SDHA) and adults exposed to different temperatures (β-tubulin + EFA + GST). In addition, we surveyed the expression profiles of two target genes (CYP3A and CSP8) in larvae exposed to different concentrations of benzo(a)pyrene and in different adult tissues. The results further validated the reliability of the reference genes. The optimal reference genes for various experimental conditions identified in these analyses provide a useful tool for ecological studies of aquatic fireflies.
"I Cannot Do All of This Alone"

Instrumental support is critical for patients and family caregivers facing life-threatening illnesses, injuries, or chronic conditions (e.g., cancer). We partner with CaringBridge.org—a prominent online health community for journaling about health crises—to conduct a study of instrumental support in the following two phases: a content analysis of 641 journal updates; and a survey of 991 users. Quantitative results show that: (1) patients and family caregivers prefer to receive different types of support than their care networks prefer to provide; (2) people generally have more trust in their closest social connections than acquaintances or businesses to provide instrumental support; and (3) users rate “prayer support” as the most important support category to them. Building on these results, we discuss design implications to accommodate divergent preferences and to expand instrumental support networks. We also discuss the need for future work to empower family caregivers and to support spirituality, an understudied topic in HCI.
To Get Lost is to Learn the Way: Automatically Collecting Multi-step Social Engineering Attacks on the Web

By exploiting people's psychological vulnerabilities, modern web-based social engineering (SE) attacks manipulate victims to download malware and expose personal information. To effectively lure users, some SE attacks constitute a sequence of web pages starting from a landing page and require browser interactions at each web page, which we call multi-step SE attacks. Also, different browser interactions executed on a web page often branch to multiple sequences to redirect users to different SE attacks. Although common systems analyze only landing pages or conduct browser interactions limited to a specific attack, little effort has been made to follow such sequences of web pages to collect multi-step SE attacks. We propose StraySheep, a system to automatically crawl a sequence of web pages and detect diverse multi-step SE attacks. We evaluate the effectiveness of StraySheep's three modules (landing-page-collection, web-crawling, and SE-detection) in terms of the rate of collected landing pages leading to SE attacks, efficiency of web crawling to reach more SE attacks, and accuracy in detecting the attacks. Our experimental results indicate that StraySheep can lead to 20% more SE attacks than Alexa top sites and search results of trend words, crawl five times more efficiently than a simple crawling module, and detect SE attacks with 95.5% accuracy. We demonstrate that StraySheep can collect various SE attacks; not limited to a specific attack. We also clarify attackers' techniques for tricking users and browser interactions redirecting users to attacks.
Polyunsaturated Fatty Acids Influence LPS-Induced Inflammation of Fish Macrophages Through Differential Modulation of Pathogen Recognition and p38 MAPK/NF-κB Signaling

Polyunsaturated fatty acids (PUFAs) not only serve as essential nutrients but also function as modulators of the immune response in marine fish. However, their immunomodulatory mechanism is poorly understood given that the underlying regulation of the innate immune response in fish has not been fully elucidated. Hence, study of the innate immunity of fish could help elucidate the mechanism by which PUFAs affect the fish immune response. Here, we used combined transcriptome analysis and in vitro experimentation to study the mechanism of LPS-induced inflammation. Transcriptome profiling indicated that LPS elicited strong pro-inflammatory responses featuring high expression levels of pathogen recognition receptors (PRRs) and cytokines along with the activation of NF-κB and MAPK signaling pathways. The transcription factor p65 alone could increase the transcription of IL1β by binding to the promoter of IL1β, and this promoting effect disappeared after mutation or deletion of its binding sites. We then examined the effects of PUFAs on the levels of gene expression and the abundance of proteins of critical kinases associated with LPS-induced inflammation. We found that LA exerts pro-inflammatory response while ALA, EPA, and DHA induced anti-inflammatory effects by modulating the expression of PRRs, phosphorylation of IKK and p38, and the nuclear translocation of p65. Overall, this study advances our understanding of the regulatory mechanisms by which PUFAs regulate LPS-induced inflammation in a non-model fish species.
Chromosome-Level Genome Assembly of Cerasus humilis Using PacBio and Hi-C Technologies

The Chinese dwarf cherry (Cerasus humilis) is a perennial woody fruit (Figure 1A) native to northern China (Du et al., 1993; Wang et al., 2011; Mu et al., 2016). The fruits of C. humilis are red, yellow, green, and purple and have nutritional value (Li et al., 2014; Mo et al., 2015; Wang et al., 2018). The seed kernels of C. humilis have been used as a traditional medicine for more than 2000 years in China (Mu et al., 2015). Besides applications in medicine, the Chinese dwarf cherry could potentially have other benefits, including the control of soil erosion, due to its adaptable nature and ability to grow in soils with high salinity and low moisture levels. Unlike most fruit trees in the genus of Prunus, C. humilis typically reaches a height of 0.5–1.2m and has no obvious juvenile period. Flowering and the production of fruit typically start in the second year after seed sowing. In 2016, an efficientAgrobacterium-mediated genetic transformation system was successfully established by Mu et al. (2016) and transgenic C. humilis plants showed a significant improvement in rooting abilities. This indicates that C. humilis has great potential as a model plant in genetic studies of the genus Prunus, particularly since C. humilis provides an ideal material for the investigation of genetic regulation of fruit quality due to it has various fruit variations. Genetic improvement is becoming more and more important as there is an increasing demand for elite cultivars ofC. humilis. However, due to a lack of genomic information, the current breeding process cannot keep up with the rapid expansion of cultivation. Previously, the chromosome number of this genus has been proved to be 2 × = 16 (Ochatt and Patatochatt, 1994; Verde et al., 2013). The chromosome number of C. humilis has been clarified by Wang et al. (2020) in a study that provided a chromosome-level reference genome of C. humilis using a combination of the PacBio single molecule real-time (SMRT) sequencing and high-throughput chromosome conformation capture (Hi-C) technologies (Figure 1B).