Miracle-dz/UniFAR-FTUs huggingface dataset:
Main Characteristics of Underwater Supersonic Gas Jet Flows

Underwater supersonic gas jet flows are sophisticated physical phenomena that widely exist in underwater propulsion, such as underwater rocket, high-speed torpedo, and water-piercing missile launcher (WPML). The present study aims to explore the characteristics of underwater supersonic jets. This research carries out two-dimensional and three-dimensional underwater jet experiments and establishes an improved spherical bubble model to study the transient and steady-state characteristics of the underwater supersonic jet. The simulation results show that the entrainment strength and anti-interference ability are the main factors affecting the transient characteristics of underwater supersonic jets. The experimental results show that the jet angle increases with increasing pressure and the increased rate of the jet angle decreases with increasing pressure. The jet pulsation exists in the entire experimental pressure range from 0.4 MPa to 6.5 MPa. The frequency of back-attack increases first and then decreases with increasing pressure in the chamber. The frequency peak appears at 0.8 MPa, which is 5.96 Hz.
GROUND DEFORMATION ANALYSIS USING BASIC PRODUCTS OF THE COPERNICUS GROUND MOTION SERVICE

Abstract. Monitoring ground deformation at national and regional level with millimetre-scale precision, nowadays, is possible by using Advanced Differential Interferometric SAR (A-DInSAR) techniques. This study concerns the results of the European Ground Motion Service (EGMS), part of the Copernicus Land Monitoring Service, which detects and measures land displacement at European scale. This Service provides reliable and consistent information regarding natural ground motion phenomena such as landslides and subsidence. The ground motion is derived from Synthetic Aperture Radar (SAR) time-series analysis of Sentinel-1A/B data. These data, which provide full coverage of Europe from two different observation geometries (ascending and descending) every six days, are processed at full resolution. The paper is focused on the exploitation of the basic product of EGMS for both regional and local purposes. Analysing the slope and aspect of the deformation field is the novelty of this investigation. In particular, the focus is put on the generation of wide-area differential deformation maps. Such maps indicate the gradient of the deformation field. The obtained information is not only beneficial for monitoring anthropogenic phenomena but also vital for urban management and planning. Most of the significant damages to manmade structures and infrastructures are associated with high deformation gradient values. Thus, monitoring the temporal and spatial variations of deformation gradient is essential for dynamic analysis, early-warning, and risk assessment in urban areas. Although EGMS productions are prepared for monitoring at regional level, their resolutions are high enough to investigate at local level. Therefore, this paper considers the local deformations that affect single structures or infrastructures. Local differences in such deformation can indicate damages in the corresponding structures and infrastructures. We illustrate these types of analysis to generate differential deformation maps using datasets available at CTTC.
Isolation of Nine Bacteriophages Shown Effective against Erwinia amylovora in Korea

Erwinia amylovora is a devastating bacterial plant pathogen that infects Rosaceae including apple and pear and causes fire blight. Bacteriophages have been considered as a biological control agent for preventing bacterial infections of plants. In this study, nine bacteriophages (ΦFifi011, ΦFifi044, ΦFifi051, ΦFifi067, ΦFifi106, ΦFifi287, ΦFifi318, ΦFifi450, and ΦFifi451) were isolated from soil and water samples in seven orchards with fire blight in Korea. The genetic diversity of bacteriophage isolates was confirmed through restriction fragment length polymorphism pattern analysis. Host range of the nine phages was tested against 45 E. amylovora strains and 14 E. pyrifoliae strains and nine other bacterial strains. Among the nine phages, ΦFifi044 and ΦFifi451 infected and lysed E. amylovora only. And the remaining seven phages infected both E. amylovora and E. pyrifoliae. The results suggest that the isolated phages were different from each other and effective to control E. amylovora, providing a basis to develop biological agents and utilizing phage cocktails.
Deep-learning architecture to forecast destinations of bus passengers from entry-only smart-card data

Although smart-card data secures collective travel information on public transportation users, the reality is that only a few cities are equipped with an automatic fare collection (AFC) system that can provide user information for both boarding and alighting locations. Many researchers have delved into forecasting the destinations of smart-card users. Such effort, however, have never been validated with actual data on a large scale. In the present study, a deep-learning model was developed to estimate the destinations of bus passengers based on both entry-only smart-card data and land-use characteristics. A supervised machine-learning model was trained using exact information on both boarding and alighting. That information was provided by the AFC system in Seoul, Korea. The model performance was superior to that of the most prevalent schemes developed thus far.
The reference genome and full-length transcriptome of pakchoi provide insights into cuticle formation and heat adaption

Abstract Brassica rapa includes various vegetables with high economic value. Among them, green petiole type pakchoi (B. rapa ssp. chinensis) is one of the major vegetables grown in southern China. Compared with other B. rapa varieties, green petiole type pakchoi shows a higher level of heat resistance, which is partially derived from the rich epicuticular wax. Here we sequence a high-quality genome of green petiole type pakchoi, which has been widely used as the parent in breeding. Our results reveal that long terminal repeat retrotransposon insertion plays critical roles in promoting the genome expansion and transcriptional diversity of pakchoi genes through preferential insertions, particularly in cuticle biosynthetic genes. After whole-genome triplication, over-retained pakchoi genes escape stringent selection pressure, and among them a set of cuticle-related genes are retained. Using bulked-segregant analysis of a heat-resistant pakchoi cultivar, we identify a frame-shift deletion across the third exon and the subsequent intron of BrcCER1 in candidate regions. Using Nanopore long-read sequencing, we analyze the full-length transcriptome of two pakchoi cultivars with opposite sensitivity to high temperature. We find that the heat-resistant pakchoi cultivar can mitigate heat-caused leaf damage by activating an unfolded protein response, as well as by inhibiting chloroplast development and energy metabolism, which are presumably mediated by both transcriptional regulation and splicing factors. Our study provides valuable resources for Brassica functional genomics and breeding research, and deepens our understanding of plant stress resistance.
EVALUATION OF THE AXILLARY NODAL STATUS POST NEO-ADJUVANT CHEMOTHERAPY IN LOCALLY ADVANCED FEMALE BREAST CANCER PATIENTS

Background: Breast cancer is the most common neoplasm among women in the majority of the developed countries, accounting for one-third of newly diagnosed malignancies. Given the efficiency of neo-adjuvant chemotherapy (NACT) in reducing tumor size, it is logical to assume the same response in axilla. Objective: Our propose was to assess axillary lymph nodes (ALNs) response to NACT using clinical, ultrasound (US) or pathological examinations of sentinel lymph node biopsy (SLNB) or ALN dissection (ALND). Patients and methods: This prospective study included 100 female patients with locally advanced breast cancer (LABC) with clinically palpable or US detectable ALNs. True cut biopsy of primary tumor and fine needle aspiration cytology (FNAC) of ALNs were performed before NACT. Clinical and US response of ALNs was assessed. Surgical local control started with SLNB then ALND in all patients followed by appropriate mastectomy procedure. Primary tumor, SLNB and ALND specimens were submitted for pathological examination. Negative SLN by hematoxylin and eosin (H&E) were subjected to immunohistochemical (IHC) section. Results: Clinical, US and pathological complete response (pCR) to NACT were encountered in 47.1%, 33.3% and 31.4% of patients, respectively. The sensitivity of clinical, radiological, SLNB in predicting pCR were 60%, 82.9%, and 94.1% respectively. US was better than clinical examination in response assessment with accuracy of 78.5% versus (vs.) 60.8%, respectively (p<0.001). SLNB was more sensitive than clinical examination in predicting pCR with accuracy of 94.9%. The detection rate of SLN was 76.5%. Conclusions: pCR post NACT is high enough to make axillary conservation worthwhile. US and SLNB can assess and predict nodal response with accepted accuracy rate and SLNB is feasible after NACT.
COMPARISON AND EVALUATION OF DIFFERENT APPROACHES FOR EFFICIENT PROCESSING OF LONG GROUND-BASED SAR TIMES SERIES

Abstract. Ground-based Synthetic Aperture Radar (GB-SAR) is a monitoring tool which, once installed, acquires a large amount of data autonomously. For the IBIS-FM system, approximately 760 SAR images per day are acquired, which corresponds to more than 23 000 scenes per month. Therefore, this paper analysis different strategies for the interferometric processing of such large data stacks to find a compromise between accuracy, computational effort and the ability to (re-)process specific time intervals independently. This study compares the single master approach with the sequential approach and in addition two block-wise approaches. Moreover, a new baseline configuration called Daily Baseline Subset (DBAS) is compared which uses interferograms having a multiple of one day as temporal baseline. We evaluate them on a data stack of 30 000 images, acquired at Enguri Dam in Georgia. We check the unwrapping errors and the quality of the displacement estimation to compare the different configurations. We found that block-wise approaches show the best results considering unwrapping errors and Root Mean Square Error, while in our study the DBAS approach shows to the most plausible displacement map which is also dependent on the individual reduction of atmospheric noise.
A method for measuring supply chain interoperability

ABSTRACT The ability of systems or organisations to provide services to, and accept services from, other systems or organisations is the fundamental tenet of interoperability. This paper introduces supply chain interoperability and proposes it as a metric to facilitate supply chain management performance analysis. Interoperability can be considered a similarity metric with regard to a set of characteristics. Our methodology adapts and expands an interoperability measurement tool initially developed in and for a military context. Through an illustrative example, we demonstrate the assessment of interoperability across a supply chain, where participants are described using deterministic and stochastic characters. Our measurement methodology can assist in efficiently directing resources to best improve interoperability between and among the various elements of a supply chain.
Photodynamic Therapy in Combination with the Hepatitis B Core Virus-like Particles (HBc VLPs) to Prime Anticancer Immunity for Colorectal Cancer Treatment

Simple Summary Photodynamic therapy (PDT) by means of a photosensitizer is a clinically used therapeutic treatment in a variety of cancers. To further improve the anti-cancer efficiency of PDT, combination therapy with immune agents is a promising option. In this study, we used a viral vaccine as the immune therapeutic partner for PDT. We studied the biological properties of single and combined modalities. Our research suggests that combination therapy enhances innate and humoral immunity, improved survival, and generated a long-term memory capacity in the MC-38 murine colorectal tumor model to prevent a recurrence. Abstract Photodynamic therapy (PDT), which combines light and oxygen with a photosensitizer to induce reactive oxygen species (ROS)-mediated killing of primary tumor cells, benefits from non-invasive properties and its negligible toxicity to surrounding healthy tissues. In this study, we have shown that the second-generation photosensitizer FOSCAN can be internalized by tumor cells and effectively induce tumor cell death when exposed to laser irradiation in vitro. In addition, these dying tumor cells can be phagocytosed by dendritic cells and lead to their activation and maturation as assessed by in vitro co-culture models. While PDT induces immunogenic tumor cell apoptosis, its application for the treatment of tumors located in deep tissues and advanced malignancies has been limited. In this study, we demonstrate that hepatitis B core virus-like particles (HBc VLPs) can serve as a vaccine to enhance PDT-induced anti-cancer immunity by priming humoral immune responses and inducing CD8+ T cell responses. The combination of PDT and HBc VLPs increased the survival rate of MC-38 tumor-bearing mice to 55%, compared to 33% in PDT alone and no tumor-free mice in vaccine alone. Moreover, the combination effectively prevented tumor recurrence in vivo through enhanced immune memory T cells after therapy. Therefore, as both are clinically approved techniques, this combination provides a promising strategy for cancer therapy.
A compact multiband antenna using λ/4 rectangular stub loaded with metamaterial for IEEE 802.11N and IEEE 802.16E

This research article describes a compact multiband antenna using λ/4 rectangular stub, loaded with metamaterial for the frequency bands 2.4, 3.5, and 5.8 GHz allocated to IEEE 802.11n (WLAN) and IEEE 802.16e (WiMAX) standards in wireless communication. Compactness, multiband, and impedance matching operations in the proposed design are accomplished by utilizing a rectangular microstrip patch, a novel metamaterial based split ring resonator (SRR), a λ/4 rectangular stub and a ground plane. The proposed SRR negative permeability retrieval mechanism is explained in detail. The electrical dimensions of the designed antenna are 0.206 λ0 × 0.174 λ0 (25 × 22 mm2) at lower resonating band (2.4 GHz) and fabricated on a widely available FR4 substrate having 4.4 as dielectric constant and 1.6 mm as thickness. The average gain of 2.58 dBi, good impedance matching, stable radiation characteristics with high co‐polarization value and return loss bandwidth of 13.7% (2.26–2.57 GHz), 10.09% (3.27–3.60 GHz) and 5.09% (5.69–5.98 GHz) are observed at the bands of operation when the antenna is fabricated and tested. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1000–1006, 2017
Smart Graphene Nanoplatelet Strain Sensor for Natural Frequency Sensing of Stainless Steel (SS304) and Human Health Monitoring

The main purpose of this article is to monitor the natural frequency of stainless steel (SS304) with and without defect by spray-coated smart graphene nanoplatelet (GNPs)-doped poly (methyl methacrylate) (PMMA) nanocomposite strain sensor and human health by smart Lycra denim textile sensor. Methods such as impact hammer test and NI-daq, finite element method (FEM) simulation by Abaqus 6.12, and fast Fourier transform (FFT) study were applied for frequency monitoring of SS304. For human health monitoring, edema disease inspection, cough, and biceps locomotion were studied by graphene sol–gel textile sensor. We report eight sensors fabricated by scotch tape exfoliation method and their sensitivity was checked in terms of gauge factor (GF). The highest and lowest GF-based sensors were checked for sensitivity in the defect (hole) specimen. These sensors were used to sense the natural frequency of SS304 at three different positions in the cantilever beam. The same quantity of GNPs was used for making Lycra denim textile sensors for human health monitoring. The Lycra denim textile sensor showed a 216% change in resistance in the left calf muscle, which is less than right leg flexibility, indicating good sensitivity. In addition, the textile sensor helped in sensing coughing and biceps monitoring. The ease in fabrication and high sensitivity demonstrate the potential ability of GNPs for futuristic smart material for structural and human health monitoring.
SINEs as Credible Signs to Prove Common Ancestry in the Tree of Life: A Brief Review of Pioneering Case Studies in Retroposon Systematics

Currently, the insertions of SINEs (and other retrotransposed elements) are regarded as one of the most reliable synapomorphies in molecular systematics. The methodological mainstream of molecular systematics is the calculation of nucleotide (or amino acid) sequence divergences under a suitable substitution model. In contrast, SINE insertion analysis does not require any complex model because SINE insertions are unidirectional and irreversible. This straightforward methodology was named the “SINE method,” which resolved various taxonomic issues that could not be settled by sequence comparison alone. The SINE method has challenged several traditional hypotheses proposed based on the fossil record and anatomy, prompting constructive discussions in the Evo/Devo era. Here, we review our pioneering SINE studies on salmon, cichlids, cetaceans, Afrotherian mammals, and birds. We emphasize the power of the SINE method in detecting incomplete lineage sorting by tracing the genealogy of specific genomic loci with minimal noise. Finally, in the context of the whole-genome era, we discuss how the SINE method can be applied to further our understanding of the tree of life.
Integrating Motivational Strategies Into Massive Open Online Courses (MOOCs): The Application and Administration of the Motivation Design Model

Massive Open Online Courses, aka MOOCs, have become an indispensable part of the online education routine. Many universities and organizations put a lot of effort into designing, developing, and running such courses. However, it still remains to be an under-researched area. One of the most important issues associated with success in MOOCs is the learner motivation. High dropout and low retention rates have been attributed to learners’ low motivation. A recipe for these motivational challenges in MOOCs is provided by the ARCS-V motivational theory. This motivation design model provides a frame for analyzing the MOOCs learners, learning environment, and the resources. Based on this analysis, the model provides suggestions for assigning motivational tactics and strategies. Therefore, the purpose of this chapter is to introduce Keller’s ARCS-V motivational design model and discuss it as a potential remedy to motivational issues in MOOCs by administering and delivering motivational strategies based on the model in MOOCs environments. Integrating Motivational Strategies Into Massive Open Online Courses (MOOCs): The Application and Administration of the Motivation Design Model
Radial displacement-sensorless control for bearingless induction motor

Aimed at rotor position identification of bearingless induction motor( BIM),a displacementsensorless control scheme based on modified back electromotive force was proposed for the BIM. Firstly,to eliminate the flux observation error,on the basis of the back electromotive force( BEMF) method,the low pass filter was added to the flux observation model of radial suspension force winding. At the same time,the amplitude and phase deviation caused by the addition of low pass filter were compensated. Secondly,the modified flux observation model of radial suspension force winding was obtained and the rotor radial deviation was obtained according to the relationship equation between flux and displacement. Thus,the radial displacement self-detecting was achieved. Finally,a displacement-sensorless vector control system of the BIM was established using the presented position detection method. The simulation results show that the control system not only can accurately detect the rotor radial position,but also has good speed and torque characteristics. The further experimental results also show that the method had a good ability of radial displacement self-detecting.The BIM can realize stable suspension operation with displacement-sensorless.
A deep-learning, vision-based framework for testing swarm algorithms using inexpensive mini drones

The ability to explore dangerous buildings or hostile landscapes using a swarm of inexpensive mini drones is relevant to many search and rescue or surveillance scenarios encountered by civilian first responders and military personnel. Swarms of mini drones, implementing various path planning algorithms, provide a unique solution in situations where there is the risk to human life or use of expensive Unmanned Aerial Vehicle technology would be cost-prohibitive or both. Although inexpensive, off-the-shelf drones contain stabilization circuitry and onboard cameras, they suffer restricted flying time and lack GPS systems. The limited capability of such drones has curtailed their use by researchers investigating practical search and genetic algorithms, and many researchers rely on simulation, rather than testing with actual drones. In this paper, we describe an ad hoc framework for testing swarm algorithms while taking the first step toward implementing swarm intelligence using low-cost, offthe-shelf drones and an inexpensive network router. We initially created a public dataset, MINIUAV, including images of Tello and TelloEdu mini-drones taken from our live drone video recordings and photos scraped from various internet resources. Using the images, we then trained a deep-learning-based YOLOv4-Tiny (You Only Look Once) object detector allowing us to implement a swarm intelligence rule where drones act collectively based on a swarm alignment rule. Our results show the object detector allows a drone to identify a neighboring drone with greater than 90% accuracy. Finally, the dataset used to train the object detector will be made available on request.
Social Museography and Sustainable Historical Heritage

The Sustainable Development Goals set by the United Nations in the 2030 agenda point out the need to safeguard cultural heritage and the importance of convergence towards quality education. Through different museum projects (between 2010 and 2021), the DIDPATRI research group of the University of Barcelona has developed heritage museum models following sustainability parameters. The lines of work have been based on the use of previous museum cultures (integrating existing models) to respond to the needs of the present. The working hypotheses have raised the need to build a new social museography around the historical heritage, which can respond to the social demands of citizen education and sustainability. Museography should be oriented to formal and non-formal teaching-learning environments. Social museography must be based on the understanding of historical heritage in broad sectors of the public as well as on the participation of social agents, civil society, and the scientific community. Social museography must be based on the enhancement of heritage resources (tangible or intangible) in a way that is compatible with sustainable development options; it must be built with the support of protocols that consider production costs that are consistent with the economic and social resources available and with the reasonable use of complex technologies. This desire for research (on the paths of a new social museography) has been channeled through the development of research and transfer projects. The results obtained have generated empirical models that have contributed (methodologically) to the development of museographic options that respond to emerging demands in the environment of historical-archaeological heritage.