Miracle-dz/UniFAR-FTUs huggingface dataset:
An exosome-based transcriptomic signature for noninvasive, early detection of patients with pancreatic ductal adenocarcinoma: A multicenter cohort study.

BACKGROUND & AIMS Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and majority of patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lack adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly miRNAs, offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC. METHODS Small RNA-sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 non-disease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs was prioritized that discriminated PDAC patients from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n=191) using quantitative real time PCR (qRT-PCR) assays. RESULTS The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (AUC=0.98 training cohort; AUC=0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages 1&II; AUC=0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/ml; AUC=0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC=0.99 vs. AUC=0.86 for CA19-9 alone). CONCLUSIONS In this study, an exosome-based liquid-biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.
Customer Data-driven Business Models: A Case Study in the Retail Industry

: In today’s data era, the retail industry has increased the possibility of acquisition of a large volume of customer data, becoming more achievable its monetization. This paper develops a literature research and an empirical study identifying the different strategies that organizations perform and their instantiation by a concrete retailer. In each of these strategies, there have been identified the reasons for the case study to implement them as well as the specific instantiation performed. The research enriches the literature twofold; (1) by adding the Retail Media strategy as an indirect customer data monetization strategy; (2) by identifying relevant elements of the investment-cost-revenue structure for the different customer data monetization strategies.
On-Line Measurement of Dynamic Tilt Angle by Compensating Gyroscope Drift Error

In real-time movement controlling systems, it is essential to deploy a suitable sensor to measure tilt angle on-line. When the tilt angle is bigger than the preset threshold, the remedial operation should be made timely. This paper proposes an on-line dynamic tilt angle measurement method by compensating gyroscope drift error. First, gyroscope is selected as a measuring unit because it can overcome the interference of external forces to measure dynamic angular speed. Second, an improved least squares support vector machine (LSSVM) is proposed for gyroscope drift-error compensation. The vector base learning method is used to reduce those less important support vectors, and the sparsity of LSSVM can be changed by adjusting the value of <inline-formula> <tex-math notation="LaTeX">$\theta $ </tex-math></inline-formula>. Third, the quantum-behaved particle swarm optimization algorithm is introduced as the optimization method to optimize regularization parameter C and kernel parameter <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula> of LSSVM model because it has good optimization result and fast convergence speed. Fourth, the experiment platform and implementation process are illustrated in detail. Finally, the corresponding experimental results demonstrate that the proposed methodology could measure the dynamic tilt angle accurately.
A highly sensitive and flexible capacitive pressure sensor based on a micro-arrayed polydimethylsiloxane dielectric layer

A flexible pressure sensor with high sensitivity has been proposed which consists of a typical sandwich structure by integrating a polydimethylsiloxane (PDMS) substrate with a micro-arrayed PDMS dielectric layer. A PDMS flexible substrate coated with silver nanowires (AgNWs) is used as a top/bottom electrode material, and a PDMS dielectric layer with micro-array structure is used to ensure high sensitivity of the pressure sensor. As a result, compared with conventional parallel board capacitive sensors, such sensors exhibit good performance, high sensitivity (2.04 kPa−1) in low pressure ranges (0–2000 Pa), low detection limits (<7 Pa) and fast response times (<100 ms). Furthermore, the integration of the sensor electrode and the dielectric layer ensures good bending stability and cycling stability of the sensor. Flexible capacitive pressure sensors can be used to measure the pressure distribution of finger tips when holding an object and grabbed with fingers. The spatial distribution of the applied pressure can also be clearly identified by fabricating a pressure sensor array. Due to its outstanding performance, the flexible pressure sensor shows bright application prospects in wearable sensing devices, electronic skins and humanoid robotics.
EMI Filter Design for a Single-stage Bidirectional and Isolated AC–DC Matrix Converter

This paper describes the design of an electromagnetic interference (EMI) filter for the high-frequency link matrix converter (HFLMC). The proposed method aims to systematize the design process for pre-compliance with CISPR 11 Class B standard in the frequency range 150 kHz to 30 MHz. This approach can be extended to other current source converters which allows time-savings during the project of the filter. Conducted emissions are estimated through extended simulation and take into account the effect of the measurement apparatus. Differential-mode (DM) and common-mode (CM) filtering stages are projected separately and then integrated in a synergistic way in a single PCB to reduce volume and weight. A prototype of the filter was constructed and tested in the laboratory. Experimental results with the characterization of the insertion losses following the CISPR 17 standard are provided. The attenuation capability of the filter was demonstrated in the final part of the paper.
Safe Robotized Polishing of Plastic Optical Fibers for Plasmonic Sensors

: Plastic optical ﬁbers (POFs) biosensors are getting widespread in a number of application ﬁelds owing to their low cost, high performance, and for their extreme ﬂexibility in terms of detection ability of a large number of speciﬁc substances in different matrices. A speciﬁc category of such sensors are those based on the surface plasmon resonance (SPR) phenomenon, which can be made very speciﬁc by suitable integration with a biological or chemical molecular recognition element (MRE), speciﬁcally designed for binding with the desired substance (the analyte). Despite the ﬂexibility of the SPR-POF sensors, their production is still difﬁcult to automate on a large scale because of the special polishing process of the plastic optical ﬁber. Such a process is currently performed by a human trained operator who rubs the surface of a short ﬁber segment against a sandpaper sheet by following an 8-shaped path while exerting a speciﬁc force in the direction normal to the contact surface. The present paper proposes the adoption of a collaborative robot programmed to perform the same task based on the data acquired from the human operator. To ensure the safe use of the robotic cell by operators who share the same workspace of the robot, the system is endowed with a workspace monitoring system that ensures the polishing task execution while minimizing the possible occurrence of collisions with human operators by suitable exploiting the kinematic redundancy of the robot.
AllSATCC: Boosting AllSAT Solving with Efficient Component Analysis

All Solution SAT (AllSAT) is a variant of Propositional Satisfiability, which aims to find all satisfying assignments for a given formula. AllSAT has significant applications in different domains, such as software testing, data mining, and network verification. In this paper, observing that the lack of component analysis may result in more work for algorithms with non-chronological backtracking, we propose a DPLL-based algorithm for solving AllSAT problem, named AllSATCC, which takes advantage of component analysis to reduce work repetition caused by non-chronological backtracking. The experimental results show that our algorithm outperforms the state-of-the-art algorithms on most instances.
Learning Unforgotten Domain-Invariant Representations for Online Unsupervised Domain Adaptation

Existing unsupervised domain adaptation (UDA) studies focus on transferring knowledge in an offline manner. However, many tasks involve online requirements, especially in real-time systems. In this paper, we discuss Online UDA (OUDA) which assumes that the target samples are arriving sequentially as a small batch. OUDA tasks are challenging for prior UDA methods since online training suffers from catastrophic forgetting which leads to poor generalization. Intuitively, a good memory is a crucial factor in the success of OUDA. We formalize this intuition theoretically with a generalization bound where the OUDA target error can be bounded by the source error, the domain discrepancy distance, and a novel metric on forgetting in continuous online learning. Our theory illustrates the tradeoffs inherent in learning and remembering representations for OUDA. To minimize the proposed forgetting metric, we propose a novel source feature distillation (SFD) method which utilizes the source-only model as a teacher to guide the online training. In the experiment, we modify three UDA algorithms, i.e., DANN, CDAN, and MCC, and evaluate their performance on OUDA tasks with real-world datasets. By applying SFD, the performance of all baselines is significantly improved.
Ultra-Wide Band Diversity Antenna for Omnidirectional Coverage

In this paper, a 41 x 42.2 mm ultra-wide band (UWB) diversity antenna is designed to operate in the frequency band 5.457. 45 GHz with the isolation better than 15dB. To achieve omnidirectional coverage pattern diversity is applied. The proposed design is suitable for UWB applications requiring reliable radio link and coverage.
UMA SOLUÇÃO PARA O SISTEMA BRASILEIRO DE COLETA DE DADOS AMBIENTAIS BASEADA EM NANOSSATÉLITES

Neste artigo, será apresentado o projeto CONASAT (Constelação de Nanossatélites Ambientais) desenvolvido pelo INPE (Instituto Nacional de Pesquisas Espaciais), em parceria com a AEB (Agência Espacial Brasileira) e a UFRN (Universidade Federal do Rio Grande do Norte). O objetivo principal desse projeto é apresentar uma solução de baixo custo para o Sistema Brasileiro de Coleta de Dados Ambientais (SBCDA), baseada em uma constelação de nanossatélites, com massa entre 1 kg a 10 kg, usando tecnologias emergentes nos ramos da eletrônica e da telecomunicação. Adicionalmente, será apresentada uma visão geral dos principais produtos tecnológicos do projeto CONASAT: o Receptor/Decodificador para SBCDA e ARGOS, chamado de Data Collecting System (DCS), e o software do Subsistema de Determinação e Controle de Atitude (SDCA) do satélite. O primeiro é responsável por receber e decodificar os dados oriundos das Plataformas de Coleta de Dados Ambientais (PCDs), enquanto que o segundo é responsável pela orientação do satélite em órbita de acordo com as necessidade de operação. Por fim, algumas conclusões e considerações finais sobre o projeto CONASAT serão apresentadas.
Underwater wireless power transfer system with a curly coil structure for AUVs

An underwater wireless power transfer system with a curly coil structure is proposed to adapt to the cylindrical symmetric hull of the autonomous underwater vehicles (AUVs). The unipolar and bipolar curly coils are optimised to minimise the weight of the receiver with the same output power. It is revealed that the bipolar curly coil structure has a heavier receiver than the unipolar curly coil structure. However, the electromagnetic field radiation in the AUV of the bipolar curly coil structure is much smaller than that of the unipolar curly coil structure, which means that the bipolar curly coil structure has a smaller influence on the electronics components in the AUV. Therefore, the bipolar curly coil is adopted for the prototype. The series−series (SS) and double-sided inductor−capacitor−capacitor (LCC−LCC) compensation topologies for the bipolar curly coil structure are also investigated. A prototype was built and the experimental results showed that distorted coil currents are generated in the SS compensation topology, while the LCC−LCC compensation has a nearly sinusoidal coil current. The efficiencies of the SS and LCC−LCC compensation topologies are approximately the same, at ∼95%, which indicates that the proposed curly coil structure is applicable.
A wideband isolation technique using bezel coupled T‐type isolator for smartwatch MIMO applications

This letter presents a wideband bezel coupled T‐type isolator, decoupling two antenna elements for smartwatch multiple‐input multiple‐out applications. The antenna elements consist of PIFA antennas operating at 2.45 GHz, covering Bluetooth and Wi‐Fi bands. The proposed T‐type isolator has been installed between the antenna elements made by inserting two slits in the bezel separated by 21 mm. The separated segment of the bezel is connected with the circular ground plane by a conducting strip and an inductor. In this way, the slits offer stray capacitance, and the capacitive coupling between the T‐type isolator has been utilized to achieve a wide isolation bandwidth. Meanwhile, the isolation can also be tuned using the gaps of the slits and the inductor. The design performance has been validated in simulations and measurement. The measured impedance bandwidth is higher than 120 MHz whereas the isolation bandwidth is 790 MHz with a maximum isolation higher than 22 dB. The measured envelop correlation coefficient is below 0.01. The proposed design is a good candidate for smartwatch applications.
Utilizing Blockchain Technology for Settlement in a Microgrid

Blockchains have been embraced by many industries where transactions, either financial or non-financial, are involved. Furthermore, blockchains have been proven to support transactions, without the need for a third-party or other middlemen. Given the distributed properties of blockchains, they are very suitable as the underlying foundation of peer-to-peer applications. Among the peer-to-peer applications that could be improved with the support of blockchains, is the microgrid. Microgrids are finite energy systems where peers may purchase energy among themselves. This thesis investigates the blockchains ability to work as the underlying technology to support settlement in a microgrid. The blockchain is essentially a distributed, immutable ledger. However, there exists many versions of this ledger based on implementation features such as governance and consensus etc. A thorough background study of blockchains, and the differences in the blockchain features are presented. Furthermore, existing systems using blockchains for settlement in peer-to-peer energy systems are presented. Based on the findings in the background study and related work, a new blockchain as the technology for supporting these transactions is proposed and implemented. Results from the tests show that the proof-of-concept blockchain developed in this thesis works well as the underlying technology for settling energy flow in a microgrid. However, further development and testing is required for a real system.
How Estonian village structures have evolved: a study into the morphological form of the villages of Paduvere and Vaimastvere from the 1700s to the present day

ABSTRACT The following article focuses on the morphological development of Estonian village structures during the last several hundred years using a comparative qualitative map analysis based on historical maps and plans. The results show that the different stages in the genesis of Estonian village structures can be described by distinct characteristics that are still distinguishable in modern landscapes. Understanding how these forms have changed throughout history has the potential to guide future spatial planning decisions in the Estonian countryside.
Dietary product based on sea urchin caviar and Sardinops melanostictus fat

Various biologically active substances are present in the caviar (roe) of sea urchins, which cause a positive effect on the human body and are used as part of dietary supplements for the prevention and treatment of many diseases. Caviar food products are represented by a small assortment. This paper presents the findings of research on the development of caviar products with pronounced dietary properties based on sea urchin caviar and Sardinops melanostictus fat. Sardine oil is a rich source of omega-3 fatty acids. The developed caviar products contain phospholipids in the amount of 7.5–9.2 g/100 g and polyunsaturated fatty acids of the omega-3 family in the amount of 6.53–10.05 g/100 g. During 6 months of storage at a temperature from –2°C to –6°C, the quality and safety indicators of products did not change. Caviar products have been recommended for therapeutic and preventive dietary nutrition for cardiovascular diseases.
Action competencies for sustainability and its implications to environmental education for prospective science teachers: A systematic literature review

Students ’ action competence must be taught and developed, particularly for prospective science teachers, to have a pedagogical perspective as environmental educators. As indicated by publications in respected journals, researchers ’ focus and alignment on the issue of action competence are highly expected. This systematic literature review aims to compare the findings of research articles published by Web of Science-indexed journals. The keyword used to find the articles on the Web of Science ’ s database was “ action competence, ” which discovered 193 publications. Furthermore, 25 articles met the criteria to be analyzed. Preferred reporting items for systematic reviews and meta-analysis was the inclusion and exclusion model used. In the last three years, research focused on action competence has increased. The research employed several methods, i.e., qualitative, quantitative, mixed-methods, and development research. Jelle Boeve-de Pauw and Wanda Sass were the authors who frequently published research that focused on action competence. The keyword action competence was directly associated with environmental education, sustainable development, education-based learning for sustainable development, and evaluation. The authors who published their research with this focus were from 16 countries, mainly from Europe, i.e., Sweden, Belgium, and Denmark. The continent diversity of authors who contributed articles indicated that the action competence issue had become a global concern. Furthermore, it was found that the number of non-collaborating publications (universities or countries) was higher than those collaborating, even though single authors rarely wrote the articles. The recent trend shows that publications are authored by scientists with various backgrounds such as fields, universities, and even countries. The authors of this paper developed and proposed eight ideas to be reflected by prospective science teachers or science teacher education providers in educating future science teachers concerned about action competence about sustainable development.
Rx-refill Graph Neural Network to Reduce Drug Overprescribing Risks (Extended Abstract)

Prescription (aka Rx) drugs can be easily overprescribed and lead to drug abuse or opioid overdose. Accordingly, a state-run prescription drug monitoring program (PDMP) in the United States has been developed to reduce overprescribing. However, PDMP has limited capability in detecting patients' potential overprescribing behaviors, impairing its effectiveness in preventing drug abuse and overdose in patients. In this paper, we propose a novel model RxNet, which builds 1) a dynamic heterogeneous graph to model Rx refills that are essentially prescribing and dispensing (P&D) relationships among various patients, 2) an RxLSTM network to explore the dynamic Rx-refill behavior and medical condition variation of patients, and 3) a dosing-adaptive network to extract and recalibrate dosing patterns and obtain the refined patient representations which are finally utilized for overprescribing detection. The extensive experimental results on a one-year state-wide PDMP data demonstrate that RxNet consistently outperforms state-of-the-art methods in predicting patients at high risk of opioid overdose and drug abuse.
Electric Power System Operation: A Technique to Modelling, Monitoring and Control via Petri Nets

: P etri nets have been widely used as a tool to model, monitor and control several kind of systems. In this paper, P etri nets are used to model, monitor and control Electrical Power Systems (EPS). The electric power model will be expanded through a linear transformation. The restrictions imposed for that expansion specialize the new places with attributes that allow to monitor or control the dynamics of the original P etri net.
A TRANSMITTING BOUNDARY FOR TRANSIENT WAVE ANALYSES

An artificial boundary condition at the edge of finite computational grids is devised. Itcan simulate the transmitting process of clastic surface waves and body waves incident atarbitrary angles under any accuracy required. It may be used for two- or three-dimensionaltransient wave analyses in laterally heterogeneous media and easily incorporated into exist-ing finite element or finite difference computational codes.