Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Identification of Technological Opportunities for Radical Inventions Using International Patent Classification: Application of Patent Data Mining

Identifying technological opportunities early on is critical for the development of radical inventions (RIs). Patents are recognized as one of the most reliable resources for identifying technological opportunities. In line with this, this study aimed to suggest a novel approach for the identification of technological opportunities for RIs, based on the International Patent Classification (IPC), whose design knowledge has not been fully utilized. In this approach, technological opportunities for RIs are identified by measuring the value of technological novelty (VON) of each technology manifested in a patent set, and the value of difficulty (VOD) of each R&D theme contained in the patent set. Specifically, VONs are calculated through a novel map of technological changes over time, based on structured data from the patent set; and VODs are determined using natural language processing, K-means cluster analysis, and complex network analysis of the unstructured data from the patent set. The feasibility and operability of the proposed approach are verified in a case study of unmanned aerial vehicles. The proposed approach can help designers maximize the use of designs and expert knowledge in patent libraries, to formulate technical strategies for RIs.
Assessing Transmission Resilience during Extreme Weather with Outage and Restore Processes

We automatically extract resilience events and novel outage and restore processes from standard transmission utility detailed outage data. This new processing is applied to the outage data collected in NERC’s Transmission Availability Data System to introduce and analyze statistics that quantify resilience of the transmission system against extreme weather events. These metrics (such as outage rate and duration, number of elements outaged, rated capacity outaged, restore duration, maximum simultaneous outages, and element-days lost) are calculated for all large weather-related events on the North American transmission system from 2015 to 2020 and then by extreme weather type that caused them such as hurricanes, tornadoes, and winter storms. Finally, we study how performance of the system changed with respect to the resilience metrics by season and year.
Miniaturized MIMO Antenna Array with High Isolation for 5G Metal-Frame Smartphone Application

In this paper, a highly isolated multiple-input multiple-output (MIMO) antenna array is proposed for fifth-generation (5G) metal frame smartphones. The eight identical small-sized inverted F-shaped folded slots are etched on the metal frame as a MIMO antenna. The bandwidth of the antenna can be adjusted by changing one of the short branches of the antenna. The bandwidth of the antenna can reach the N79 band (4.4~5.0 GHz). By carefully arranging the positions of the eight antenna elements, ideal spatial diversity can be successfully achieved to mitigate the coupling between the antenna elements effectively. What is more, a small combination slot of C-shape (0.0078 × 0.047λ2) and vertical I-shape (0.12 × 0.004λ2) between each antenna element is introduced to improve the element isolation of the MIMO antenna system. The proposed MIMO array has been simulated, fabricated, and measured. The results show good impedance matching (return loss > 6 dB) and high isolation (>22 dB). Due to the decent element isolation, the envelope correlation coefficient (ECC) between each antenna element is below 0.049. It can provide a reliable anti-interference performance for the MIMO antenna system. In addition, the measured radiation efficiencies of the MIMO antenna system are higher than 50%. The interaction of the hand model with the MIMO antenna system is also investigated, including the specific absorption rate (SAR).
Excitation Epoch and Voicing Detection Using Hilbert Envelope with Single-Pass Processing

A technique is presented for excitation epoch and voicing detection in speech signal using its Hilbert envelope and employing single-pass processing. The excitation epoch detection comprises dynamic range compression for reducing amplitude variability, Hilbert envelope calculation and dynamic peak detection for excitation saliency enhancement, and epoch marking by locating the maximum-sum subarray peaks. The voicing detection is based on thresholding the inter-epoch similarity calculated as the normalized covariance of the adjacent inter-epoch intervals of the Hilbert envelope. The total algorithmic delay is less than 60 ms. The epoch detection and the voicing detection for clean and telephone-quality speech showed a good match with those obtained from the EGG, and the detection performances compared favorably with the earlier techniques.
PD-1/PD-L1 Pathway: A Therapeutic Target in CD30+ Large Cell Lymphomas

The programmed death-ligands, PD-L1 and PD-L2, reside on tumor cells and can bind with programmed death-1 protein (PD-1) on T-cells, resulting in tumor immune escape. PD-1 ligands are highly expressed in some CD30+ large cell lymphomas, including classic Hodgkin lymphoma (CHL), primary mediastinal large B-cell lymphoma (PMBL), Epstein–Barr virus (EBV)-positive diffuse large B-cell lymphoma (EBV+ DLBCL), and anaplastic large cell lymphoma (ALCL). The genetic alteration of the chromosome 9p24.1 locus, the location of PD-L1, PD-L2, and JAK2 are the main mechanisms leading to PD-L1 and PD-L2 overexpression and are frequently observed in these CD30+ large cell lymphomas. The JAK/STAT pathway is also commonly constitutively activated in these lymphomas, further contributing to the upregulated expression of PD-L1 and PD-L2. Other mechanisms underlying the overexpression of PD-L1 and PD-L2 in some cases include EBV infection and the activation of the mitogen-activated protein kinase (MAPK) pathway. These cellular and molecular mechanisms provide a scientific rationale for PD-1/PD-L1 blockade in treating patients with relapsed/refractory (R/R) disease and, possibly, in newly diagnosed patients. Given the high efficacy of PD-1 inhibitors in patients with R/R CHL and PMBL, these agents have become a standard treatment in these patient subgroups. Preliminary studies of PD-1 inhibitors in patients with R/R EBV+ DLBCL and R/R ALCL have also shown promising results. Future directions for these patients will likely include PD-1/PD-L1 blockade in combination with other therapeutic agents, such as brentuximab or traditional chemotherapy regimens.
Secure Smart Lock System Utilizing the MQTT Protocol

Interconnected communication system facilitating home automation is becoming increasingly popular Internet of Things’ (IoT) domain. One such application is a smart lock. Today, physical locks are being replaced by electro-mechanical ones, with limited network and power capabilities. A physical key is replaced with software that can be operated remotely from a mobile device. Since, these systems widely rely on the wireless network, they are more vulnerable to a security breach. Therefore, development of a network of connected system that ensures reliability and security is fundamental to the field of IoT. Often, securing mechanism requires using complex decision-making algorithms. However, the foundation of a robust system is laid during the design, and development of such a critical embedded system. Thus, it is important to identify, and prioritize the curial system requirements and the steps to engineer them. This paper presents our work that identified and addressed this issue. As part of the research, a proof of concept, of a network of connected devices serving as a secure smart lock, is implemented. It utilizes Message Queuing Telemetry Transportation (MQTT) protocol to enable message transmission between the users and lock. It is light weight, uses less memory on devices and network usage is at par with quality of services that are already available in the market. This paper describes the requirements and design, the technical details of the implementation and the performance aspects of this system.
Super-Resolution Ultrasound Imaging Provides Quantification of the Renal Cortical and Medullary Vasculature in Obese Zucker Rats: A Pilot Study

Obesity is a risk factor of chronic kidney disease (CKD), leading to alterations in the renal vascular structure. This study tested if renal vascular density and tortuosity was quantifiable in vivo in obese rats using microbubble-based super-resolution ultrasound imaging. The kidneys of two 11-week-old and two 20-week-old male obese Zucker rats were compared with age-matched male lean Zucker rats. The super-resolution ultrasound images were manually divided into inner medulla, outer medulla, and cortex, and each area was subdivided into arteries and veins. We quantified vascular density and tortuosity, number of detected microbubbles, and generated tracks. For comparison, we assessed glomerular filtration rate, albumin/creatinine ratio, and renal histology to evaluate CKD. The number of detected microbubbles and generated tracks varied between animals and significantly affected quantification of vessel density. In areas with a comparable number of tracks, density increased in the obese animals, concomitant with a decrease in glomerular filtration rate and an increase in albumin/creatinine ratio, but without any pathology in the histological staining. The results indicate that super-resolution ultrasound imaging can be used to quantify structural alterations in the renal vasculature. Techniques to generate more comparable number of microbubble tracks and confirmation of the findings in larger-scale studies are needed.
EFFECTS OF ASCORBIC ACID AND ACETYLSALICYLIC ACID SUPPLEMENTATION ON THE PERFORMANCE OF BROILER CHICKS EXPOSED TO HEAT STRESS

A total of 100, day-old broiler chicks were randomly divided into 5 equal groups and kept under elevated temperature (93-97°F) to see the effect of ascorbic acid and acetylsalicylic acid on the feed conversion ratio (FCR), immune status and ratio of weight of bursa, thymus and spleen to body weight. Heat stress increased the FCR but decreased the immune response and ratio of bursa, thymus and spleen to body weight of the birds. Ascorbic acid and acetylsalicylic acid supplementation during heat stress had beneficial effects on FCR, immune status and ratio of bursa, thymus and spleen to body weight. Grossly, bursa, thymus and spleen of heat stressed birds were atrophied but in ascorbic acid and acetylsalicylic acid supplemented birds these organs were not atrophied. No specific histopathological changes were observed in all groups
Robust learning with anytime-guaranteed feedback

Under data distributions which may be heavy-tailed, many stochastic gradient-based learning algorithms are driven by feedback queried at points with almost no performance guarantees on their own. Here we explore a modified "anytime online-to-batch" mechanism which for smooth objectives admits high-probability error bounds while requiring only lower-order moment bounds on the stochastic gradients. Using this conversion, we can derive a wide variety of "anytime robust" procedures, for which the task of performance analysis can be effectively reduced to regret control, meaning that existing regret bounds (for the bounded gradient case) can be robustified and leveraged in a straightforward manner. As a direct takeaway, we obtain an easily implemented stochastic gradient-based algorithm for which all queried points formally enjoy sub-Gaussian error bounds, and in practice show noteworthy gains on real-world data applications.
Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance

More than US$ 27 billion is estimated to have been paid-out in farm support in USA alone since 1991 in response to climate change impacts on agriculture, with costs likely continuing to rise. With the wider adoption of precision agriculture - an agriculture management strategy that involves gathering, processing and analyzing temporal, spatial and individual data - in both developed and developing countries, there is an increasing opportunity to harness accumulating, shareable, big data using artificial intelligence (AI) methods, collected from weather stations, field sensor networks, Internet-of-Things devices, unmanned aerial vehicles, and earth observational satellites. This requires smart algorithms tailored to agricultural data types, integrated into digital solutions that are viable, flexible, and scalable for wide deployment for a wide variety of agricultural users and decision-makers. We discuss a novel AI approach that addresses the real-world problem of developing a viable solution for reliably, timely, and cost-effectively forecasting crop status across large agricultural regions using Earth observational information in near-real-time. Our approach is based on extracting time-conditioned topological features which characterize complex spatio-temporal dependencies between crop production regions and integrating such topological signatures into Long Short Term Memory (LSTM). We discuss utility and limitations of the resulting zigzag persistence-based LSTM (ZZTop-LSTM) as a new tool for developing more informed crop insurance rate-making and accurate tracking of changing risk exposures and vulnerabilities within insurance risk areas.
Periodic energy mass on head and edge tones in Maltese wh-constructions

This paper is concerned with the relation between tonal association and prosodic strength in different tone bearing positions in Maltese wh-words. In these words, tones are associated with the stressed syllable (head association) in indirect and quoted questions, but with the initial syllable (edge association) in direct questions. In a language that has pitch accents to cue prominence (a head prominence language according to Jun's typology), the initial syllable, if not stressed, would not typically cue prominence, but rather juncture. Using periodic energy mass as a measure of strength, and thus prominence, we found that mass enhancement is not conditioned by tonal association (either head or edge) but rather by the lexical stress. Whereas the present study shows that the word-initial H tone does not affect the relative prominence between the stressed syllable and the word-initial one, and thus does not cue prominence on the initial syllable, there is a potentially different prominence-cueing function of this early H peak. That is, for example a prominence cueing function at the word level (i.e., one which makes the entire word more prominent) driven by modality or pragmatic force.
AI for Disaster Rapid Damage Assessment from Microblogs

Formal response organizations perform rapid damage assessments after natural and human-induced disasters to measure the extent of damage to infrastructures such as roads, bridges, and buildings. This time-critical task, when performed using traditional approaches such as experts surveying the disaster areas, poses serious challenges and delays response. This paper presents an AI-based system that leverages citizen science to collect damage images reported on social media and perform rapid damage assessment in real-time. Several image processing models in the system tackle non-trivial challenges posed by social media as a data source, such as high-volume of redundant and irrelevant content. The system determines the severity of damage using a state-of-the-art computer vision model. Together with a response organization in the US, we deployed the system to identify damage reports during a major real-world disaster. We observe that almost 42% of the images are unique, 28% relevant, and more importantly, only 10% of them contain either mild or severe damage. Experts from our partner organization provided feedback on the system's mistakes, which we used to perform additional experiments to retrain the models. Consequently, the retrained models based on expert feedback on the target domain data helped us achieve significant performance improvements.
Inharmonious Region Localization by Magnifying Domain Discrepancy

Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another color space to magnify the domain discrepancy between inharmonious region and background, so that the model can identify the inharmonious region more easily. To this end, we present a novel framework consisting of a color mapping module and an inharmonious region localization network, in which the former is equipped with a novel domain discrepancy magnification loss and the latter could be an arbitrary localization network. Extensive experiments on image harmonization dataset show the superiority of our designed framework.
Flexible Gas-Permeable and Resilient Bowtie Antenna for Tensile Strain and Temperature Sensing

As a wireless basic unit, flexible antennas hold a wide range of applications in wearable electronics, soft robotics, and Internet of Things (IoT). However, most of the current flexible antennas are encapsulated by silicone elastomers with poor gas permeability, which severely hinders the evaporation of skin moisture and sweat. In addition, conventional rigid metals as high-frequency conductors are limited by poor elasticity and susceptibility to oxidation for on-skin application. Here, we developed a highly permeable and stretch-resistant flexible bowtie antenna that can capture changes in tensile strain and temperature. A low-impedance flexible carbon nanotube-silver (CNT-Ag) substrate was fabricated as the conductor of the antenna. By optimizing the multibeam bowed geometry and wrapping it in porous thermoplastic polyurethane (TPU) fibers, the final five-beam antenna was obtained and was able to withstand a relatively large tensile stress of 25.2 MPa, yet achieve a high vapor transmission rate of 48.2 mg cm−2 h−1. The antenna obtained an ideal impedance match at 2.28 GHz with doughnut-like radiation and a high radiation efficiency of over 85%. Furthermore, the antenna was successfully used to capture the strain in the wrist epidermis during bending and to detect thermal changes in the beaker of hot water, respectively. Finally, demonstrations of the antenna, such as permeability, radiation to the human body, and integrality in connection with flexible circuits, were carefully developed to reveal its feasibility in the real world. We expect this work to pave the way for the future establishment of epidermally flexible antennas for soft electronics.
Real-Time Estimation of Instantaneous Power System Fundamental Frequency

Instantaneous frequency measurement is a critical component of power system control and automation. Recently, electric power distribution networks with a high proportion of renewable energy have been subjected to unprecedented complexity, necessitating more complicated automation solutions. The major reasons for frequency changes include the usage of dispersed generation, the connection of non-linear loads, and the occurrence of some unforeseen system problems. This paper presents two DFT-based power system frequency measuring algorithms. It considers frequency variations from the system’s fundamental frequency, as well as the noise generated by analog to digital converters (ADC). The IEEE Phasor Measurement Unit (PMU) latest Standard specification (IEC/IEEE 60255-118-1:2018) is used to examine these two methodologies. The methodologies are evaluated using test signals that are required to provide PMU quality evaluation and classification while accounting for process noise, ADC conversion noise, and dynamically changing input voltage and current signals. The tradeoff between DFT simplicity in implementation and needed complexity of power systems is put to the test by abrupt variations in frequency and amplitude of the fundamental component.
Silver@quercetin Nanoparticles with Aggregation-Induced Emission for Bioimaging In Vitro and In Vivo

Fluorescent materials based on aggregation-induced emission luminogens (AIEgens) have unique advantages for in situ and real-time monitoring of biomolecules and biological processes because of their high luminescence intensity and resistance to photobleaching. Unfortunately, many AIEgens require time-consuming and expensive syntheses, and the presence of residual toxic reagents reduces their biocompatibility. Herein, silver@quercetin nanoparticles (Ag@QCNPs), which have a clear core–shell structure, were prepared by redox reaction of quercetin (QC), a polyphenolic compound widely obtained from plants, including those used as foods, and silver ions. Ag@QCNPs show both aggregation-induced luminescence and the distinct plasma scattering of silver nanoparticles, as well as good resistance to photobleaching and biocompatibility. The Ag@QCNPs were successfully used for cytoplasmic labeling of living cells and for computerized tomography imaging in tumor-bearing mice, demonstrating their potential for clinical applications.
Directional Migration and Distribution of Magnetic Microparticles in Polypropylene-Matrix Magnetic Composites Molded by an Injection Molding Assisted by External Magnetic Field

Surface-functionalized polymer composites with spherical particles as fillers offer great qualities and have been widely employed in applications of sensors, pharmaceutical industries, anti-icing, and flexible electromagnetic interference shielding. The directional migration and dispersion theory of magnetic microparticles in polypropylene (PP)-matrix magnetic composites must be studied to better acquire the functional surface with remarkable features. In this work, a novel simulation model based on multi-physical field coupling was suggested to analyze the directed migration and distribution of magnetic ferroferric oxide (Fe3O4) particles in injection molding assisted by an external magnetic field using COMSOL Multiphysics® software. To accurately introduce rheological phenomena of polymer melt into the simulation model, the Carreau model was used. Particle size, magnetic field intensity, melt viscosity, and other parameters impacting particle directional motion were discussed in depth. The directional distribution of particles in the simulation model was properly assessed and confirmed by experiment results. This model provides theoretical support for the control, optimization, and investigation of the injection-molding process control of surface-functionalized polymer composites.
A configurational approach to the prosody of topic and focus in Egyptian Arabic. Testing the importance of accent-based and utterance-based acoustic cues

Recent research on Egyptian Arabic suggests that topic and focus are realized by different pitch events and that a focus is followed by post-focus attenuation. It is, however, not known how well these structures are discriminated and which are the relevant acoustic cues. We present results from a Random Forest based discrimination between two topic and two focus types, using 62 acoustic cues over the utterance, of which 37 are related to the target accent. All categories are discriminated very well with some confusion between the subtypes. The two most important cues are the velocity of the fall of the target accent and the scaling of the following peak, followed by the amount of fall in the accent and the intensity of the utterance-final word/syllable. Further important findings are that f0 is especially important to distinguish between target accents and to indicate register lowering, that intensity features are only related to the target word and the last word, and that duration is only relevant in the target accent. This suggests that the target accent is signaled by all acoustic cues, but primarily by a pitch fall, and post-focus attenuation by immediate register lowering and a salient intensity drop at the end of the utterance.