Miracle-dz/UniFAR-FTUs huggingface dataset:
Field-Programmable Gate Array-Based Multichannel Measurement System for Interrogating Fiber Bragg Grating Sensors

We develop a field-programmable gate array (FPGA)-based multichannel measurement system for sensing multiplexed fiber Bragg gratings (FBGs), using a high-speed wavelength-swept laser. The wavelength-swept laser, operated with Fourier-domain mode locking (FDML), exhibits a sweep frequency of 50.7 kHz and sweep band of ~60 nm. A breakthrough in multichannel and real-time measurement is achieved by implementing an FPGA with unique parallel-processing circuits. This FPGA enables the implementation of a high-speed centroid-peak–detection circuit for FBG detection, which can be operated with a sampling frequency of 250 MHz. In multichannel measurement systems, the light propagating through each sensor path produces a delay, which reduces the measurement accuracy. This can be solved by implementing a delay-correction technique, which utilizes the time difference between two spectra obtained by a bidirectional scan of the FDML laser. The system is demonstrated to exhibit multichannel sensing and high measurement time resolution of $9.9~\mu \text{s}$ , without being affected by the delay.
The Chinese Hamster Ovary Cell-Based H9 HA Subunit Avian Influenza Vaccine Provides Complete Protection against the H9N2 Virus Challenge in Chickens

(1) Background: Avian influenza has attracted widespread attention because of its severe effect on the poultry industry and potential threat to human health. The H9N2 subtype of avian influenza viruses was the most prevalent in chickens, and there are several commercial vaccines available for the prevention of the H9N2 subtype of avian influenza viruses. However, due to the prompt antigenic drift and antigenic shift of influenza viruses, outbreaks of H9N2 viruses still continuously occur, so surveillance and vaccine updates for H9N2 subtype avian influenza viruses are particularly important. (2) Methods: In this study, we constructed a stable Chinese hamster ovary cell line (CHO) to express the H9 hemagglutinin (HA) protein of the major prevalent H9N2 strain A/chicken/Daye/DY0602/2017 with genetic engineering technology, and then a subunit H9 avian influenza vaccine was prepared using the purified HA protein with a water-in-oil adjuvant. (3) Results: The results showed that the HI antibodies significantly increased after vaccination with the H9 subunit vaccine in specific-pathogen-free (SPF) chickens with a dose–dependent potency of the immunized HA protein, and the 50 μg or more per dose HA protein could provide complete protection against the H9N2 virus challenge. (4) Conclusions: These results indicate that the CHO expression system could be a platform used to develop the subunit vaccine against H9 influenza viruses in chickens.
Target Imaging and Displacement Estimation via SFCW Based MIMO Radar Based on Structured Matrix Completion

In this paper, target imaging and displacement estimation via the stepped-frequency continuous waveform (SFCW) based MIMO (multiple-input multiple-output) radar system with few randomly selected frequencies is studied. Based on the structured matrix completion (MC) algorithm, a novel formulation method is proposed to obtain a high low-rank property of the radar received signal matrix. MC algorithm is then applied to reconstruct the missing data corresponding to the non-selected frequencies. Imaging target via the back projection (BP) algorithm, the missing data reconstruction performance of the proposed method is validated and compared with the existing method. From the view of interferometry, the phase recovery quality of the proposed method is also verified. It is demonstrated that the proposed method can achieve accurate target imaging and displacement estimation with much reduced frequencies.
How to evaluate public displays

After years in the lab, interactive public displays are finding their way into public spaces, shop windows, and public institutions. They are equipped with a multitude of sensors as well as (multi-) touch surfaces allowing not only the audience to be sensed, but also their effectiveness to be measured. The lack of generally accepted design guidelines for public displays and the fact that there are many different objectives (e.g., increasing attention, optimizing interaction times, finding the best interaction technique) make it a challenging task to pick the most suitable evaluation method. Based on a literature survey and our own experiences, this paper provides an overview of study types, paradigms, and methods for evaluation both in the lab and in the real world. Following a discussion of design challenges, we provide a set of guidelines for researchers and practitioners alike to be applied when evaluating public displays.
Evolution of the upper tropospheric outflow in Hurricanes Iselle and Julio (2014) in the Navy Global Environmental Model (NAVGEM) analyses and in satellite and dropsonde observations

Upper tropospheric outflow was examined during the life cycles of two hurricanes in the eastern and central Pacific Ocean. The outflow from Hurricanes Iselle and Julio was evaluated by using analyses from the Navy Global Environmental Model, which were very highly correlated with satellite atmospheric motion vector and NOAA G‐IV dropsonde observations. A synoptic overview provided the environmental context for the life cycles of both tropical cyclones (TCs). Then, the outflow magnitude and direction within 6 radial degrees of each TC center were analyzed in relation to TC intensity, the synoptic environment, and inertial stability, with the following results. In both Iselle and Julio, the azimuthally averaged outflow magnitude was maximized initially more than 4 radial degrees from the center, and that maximum moved steadily inward during a 4 day intensification period and reached a position radially inward of 2° within 6 h of the time of maximum surface winds. Furthermore, the direction of the outflow in both TCs was related to the evolution of the large‐scale upper tropospheric flow pattern, particularly the phasing of subtropical jet ridges and troughs moving eastward north of both TCs. Finally, outflow channels were consistently bounded by regions of lowest (highest) values of inertial stability counterclockwise (clockwise) from the maximum outflow azimuth, a pattern that persisted throughout the life cycles of both storms regardless of intensity, environmental flow, and the number and direction of outflow channels present.
Fostering the Development of European Regions: A Spatial Dynamic Panel Data Analysis of the Impact of Cohesion Policy

Bouayad-Agha S. , Turpin N. and Védrine L. Fostering the development of European regions: a spatial dynamic panel data analysis of the impact of cohesion policy, Regional Studies. This paper uses a conditional–convergence econometric model to investigate whether cohesion policy affects European economies. Its main contribution is to consider both spatial and temporal dynamics in assessing the impact of European cohesion policy. Econometric estimations rely on a dataset of 143 EU-14-NUTS-1/NUTS-2 regions from 1980 to 2005. The results suggest that Objective 1 programmes have a direct effect on regional gross domestic product per capita growth rates, whereas total Structural Funds do not. Moreover, consideration of the spatial dimension of the panel brings to light a still significant, but less important, impact of Structural Funds.
VO-2 Assisted Unit Cell for Designing THz Reconfigurable Reflectarray Antenna

A hybrid half-wavelength model of gold and Vanadium Oxide (VO-2) is presented in this paper operating at 1.1 THz. With the temperature variation, VO-2 changes its state from insulator to metallic which causes the phase response of the unit cell to change. The phase shift of 198° is obtained based on the switching mechanism of VO-2. This provides a hint at the capacity of VO-2 being used as the switching mechanism at the terahertz band for designing the reconfigurable reflectarray antenna.
DeepCoNet: LSTM Based Detection of Covid19 Using Chest Xray Images

Since the covid19 pandemic, besides real time reverse transcriptase-polymerase chain reaction (RT-PCR), there have been numerous attempts to detect covid19 using deep learning and artificial intelligence that allows medical professionals to analyze clinical findings better. An automated covid19 detection technique based on deep Long Short-Term Memory (LSTM) has been proposed in this work by building on recent methodological advancements. With the proposed approach in this work, we are capable of minimizing the percentage error up to 1.09 on a dataset consisting of chest Xray images. By gathering more data and restructuring our proposed approach in the future, we are hoping to significantly enhance its generalization performance and make it more useful in the clinical setting.
Boolean map saliency combined with motion feature used for dim and small target detection in infrared video sequences

Infrared dim and small target detection plays an important role in infrared search and tracking systems. In this paper, a novel infrared dim and small target detection method based on Boolean map saliency and motion feature is proposed. Infrared targets are the most salient parts in images, with high gray level and continuous moving trajectory. Utilizing this property, we build a feature space containing gray level feature and motion feature. The gray level feature is the intensity of input images, while the motion feature is obtained by motion charge in consecutive frames. In the second step, the Boolean map saliency approach is implemented on the gray level feature and motion feature to obtain the gray saliency map and motion saliency map. In the third step, two saliency maps are combined together to get the final result. Numerical experiments have verified the effectiveness of the proposed method. The final detection result can not only get an accurate detection result, but also with fewer false alarms, which is suitable for practical use.
Essays on atmospheric emissions and environmental policy

The problem of atmospheric pollution is one of the major concerns about damaging effects of human activities on the environment. Some of the gases released into the atmosphere known as greenhouse gases (GHG) have a global effect, contributing to climate change. An increasing number of scientific studies seek to quantify and predict the possible effects of global warming, and they often conclude that these could be extremely serious. The risks associated to climate change clearly need an international effort to be faced. The aim of this thesis is to provide some empirical evidence to enrich the debate on the evolution of emissions and on the policy instruments that could reduce atmospheric pollution. A first essay analyses the evolution of GHG emissions and acidification emissions for Italy, in the years 1995-2005. The aim is to highlight how different economic factors have driven the evolution of Italian emissions. The main factors considered are economic growth, the development of a technology allowing a more environment-friendly way of production, and the structure of consumption. The knowledge of the role of different determinants is helpful to figure out effective political instruments that would permit to reduce environmental pressures. Essay two and three analyze a specific EU policy, the Energy Taxation Directive (ETD), an environmental taxation approved in 2003 that affects the price of energy products. In 2011, the European Commission proposed a new version of the ETD to increase the effectiveness of the instrument through higher rates and less exemptions. However, in May 2012 the European Parliament did not approve the Commission proposal. These studies simulate the effect that the reform would have had on the level of prices, if implemented. The aim is to shed light on the possible reasons that caused the attempt of improving this instrument to failure. The last essay refers to the current debate regarding carbon-motivated border tax adjustment (CBTA). CBTA are tariffs applied to imports designed to avoid drawbacks of emission reduction policies when only one or few regions (the abating regions) implement them. Through CBTA the abating regions level out different treatment applied to domestic and imported products. Through a multi-region and multi-sector analysis we compute and compare two possible CBTA systems that the EU could implement to complement a hypothetical carbon tax applied to domestic products. Results at country and product level contribute to better understand the effects of this instrument and to add information to the political debate on it.
A semi-automatic cropland mapping approach using GEOBIA and random forests on black-and-white aerial photography

For decades land-use and land-cover (LULC) conversions have had an important impact on land- and ecosystem degradation, accordingly (historical) LULC information is important for the assessment of such impacts. This information can be derived from black-and-white (B&W) aerial photography. Such photography is often visually interpreted, which is a very time-consuming approach. This study shows that machine learning can be applied on only brightness to derive LULC information. Cropland acreage is semi-automatically mapped by means of Geographic Object-Based Image Analysis (GEOBIA) and Random Forest classification in two study sites in Ethiopia and in The Netherlands. The result is a thematic map with two classes: 1) agricultural cropland and 2) other types of land cover. Overall mapping accuracies attained are 90 % and 96 % for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s.
Overview of Bionic Hand

Several approaches for operating bionic limbs are outlined in this paper. While pattern recognition and gesture classification have shown promise, they also foreshadow a number of difficulties due to inaccurate findings from algorithms. However, every once in a while, new methods of gesture classification and pattern recognition emerge. This paper reviews the current state of the art in gesture classification algorithms and their related results.
REGRESI ROBUST UNTUK PEMODELAN DEFORESTASI DI INDONESIA

Deforestasi adalah proses penebangan atau penghilangan hutan secara besar-besaran yang menjadi masalah serius di seluruh dunia. Fenomena ini telah menjadi perhatian global karena dampak negatifnya terhadap lingkungan dan kehidupan manusia. Tinggi rendahnya tingkat deforestasi di Indonesia tentunya sangat penting, hal ini didukung dengan pentingnya memiliki data deforestasi setiap tahunnya untuk kemudian diteliti kembali deforestasi yang tidak stabil. Faktor-faktor yang diasumsikan berpengaruh terhadap deforestasi pada penelitian ini, yaitu produksi kayu bulat dan luas tanaman perkebunan. Metode yang digunakan untuk menganalisis data yang terkontaminasi oleh outlier dan memberikan hasil yang lebih fleksibel adalah regresi robust. Hasil yang diperoleh adalah model regresi robust dan faktor yang berpengaruh secara signifikan terhadap deforestasi di Indonesia sesuai dengan tujuan penelitian. Jenis penelitian yang dilakukan dalam penelitian ini adalah penelitian eksperimen dengan studi literatur. Variabel yang digunakan adalah data deforestasi di Indonesia, produksi kayu bulat dan luas tanaman perkebunan. Setelah itu diperoleh model regresi robust dengan estimasi maximum likelihood type (M). Diperoleh tinggi rendahnya deforestasi tahun 2017-2021 dipengaruhi oleh luas tanaman perkebunan.
Assessing the Environmental Impact of Plant-Based Diets: A Comprehensive Analysis

This study examines a pressing issue related to the loss of natural resources and biodiversity driven by the high reliance of food production on ecosystem management services. The well-being of all living species is impacted by this depletion, which represents a huge obstacle in our collaborative effort to improve environmental quality. Our research aims to explain the environmental effects of food production and raise awareness of pollution levels at various phases of this process. This research combines statistical analysis and visualization to show considerable differences in CO2eq emissions among 43 different food products. In particular, it highlights how animal-based diets have much higher emissions than their plant-based equivalents. Subsequently, the products were divided into three distinct groups: plant-based, animal-based, and refined oils and sugars. This demonstrated how well an unsupervised clustering technique separates food products according to their CO2eq emissions. Where, these findings highlight how excellent plant-based products are for the environment. The main goal of this study goes beyond simple observation since it aims to provide an example of how a comprehensive, health-conscious eating habit may live with a stable ecosystem and clean surroundings. Particularly, reductions in cane sugar production yield substantial reductions in CO2 emissions, whereas even marginal decreases in meat production result in a significant reduction in emissions. These results highlight the potential for sustainable eating habits to aid in environmental conservation and deepen our understanding of the complex interactions between dietary decisions and environmental effects.
Determination of Mycotoxins in Plant-Based Meat Alternatives (PBMAs) and Ingredients after Microwave Cooking

In this study, we investigate the role of microwave cooking in reducing mycotoxin contamination in plant-based food matrices, with a focus on veggie burgers (purchased and home-made) and their ingredients (soybean, potatoes, zucchini, carrots). Two different conditions were studied (Max–Min) that were 800 W for 60 s and 800 W for 90 s, respectively. The degradation patterns of aflatoxins (AFB1, AFB2, AFG1, AFG2), fumonisins (FB1, FB2, FB3), trichothecenes (T2, HT2, ZEA), and ochratoxin A (OTA) were studied. The extraction procedures were conducted with the QuEChERS extraction, and the analyses were conducted with liquid chromatography–tandem mass spectrometry (LC-MS/MS). Principal component analysis (PCA) showed that degradation under microwave cooking varies considerably across different food matrices and cooking conditions. This study provides valuable insights into the degradation of mycotoxins during microwave cooking and underscores the need for more research in this area to ensure food safety.
A knowledge graph embedding model based attention mechanism for enhanced node information integration

The purpose of knowledge embedding is to extract entities and relations from the knowledge graph into low-dimensional dense vectors, in order to be applied to downstream tasks, such as connection prediction and intelligent classification. Existing knowledge embedding methods still have many limitations, such as the contradiction between the vast amount of data and limited computing power, and the challenge of effectively representing rare entities. This article proposed a knowledge embedding learning model, which incorporates a graph attention mechanism to integrate key node information. It can effectively aggregate key information from the global graph structure, shield redundant information, and represent rare nodes in the knowledge base independently of its own structure. We introduce a relation update layer to further update the relation based on the results of entity training. The experiment shows that our method matches or surpasses the performance of other baseline models in link prediction on the FB15K-237 dataset. The metric Hits@1 has increased by 10.9% compared to the second-ranked baseline model. In addition, we conducted further analysis on rare nodes with fewer neighborhoods, confirming that our model can embed rare nodes more accurately than the baseline models.
Effects of Cavity Depth of Glass Facades on Energy Performance of the Office Building Facade Scenarios of Dhaka City, Bangladesh

The concern of warming brought on by extreme solar radiation entering the glazed façade may become serious in Bangladesh, where high-rise buildings now commonly use these systems. This scenario will lead to higher energy usage since there will be a greater requirement for electricity to cool the indoor environment. Determining the effects of the Cavity Depth of Glass facades on the energy consumption of office buildings in Dhaka, Bangladesh, is the primary goal of this study. To establish techniques for optimization, different cavity depths, and other glazed façade system parameters have been proposed. Results were obtained by modelling the variables of the investigation using the computer simulation software EnergyPlus. As per the findings of the study, glazed façade systems in Dhaka may benefit greatly from a cavity depth of 1000 mm combined with bronze laminated glass. The glass façade's thermal performance is enhanced under the ideal cavity system since there is a discernible drop in the building's annual end-use energy of about 12.28 % and a drop in indoor temperature of roughly 2°C.
The role of apoptosis in spinal cord injury: a bibliometric analysis from 1994 to 2023

Background Apoptosis after spinal cord injury (SCI) plays a pivotal role in the secondary injury mechanisms, which cause the ultimate neurologic insults. A better understanding of the molecular and cellular basis of apoptosis in SCI allows for improved glial and neuronal survival via the administrations of anti-apoptotic biomarkers. The knowledge structure, development trends, and research hotspots of apoptosis and SCI have not yet been systematically investigated. Methods Articles and reviews on apoptosis and SCI, published from 1st January 1994 to 1st Oct 2023, were retrieved from the Web of Science™. Bibliometrix in R was used to evaluate annual publications, countries, affiliations, authors, sources, documents, key words, and hot topics. Results A total of 3,359 publications in accordance with the criterions were obtained, which exhibited an ascending trend in annual publications. The most productive countries were the USA and China. Journal of Neurotrauma was the most impactive journal; Wenzhou Medical University was the most prolific affiliation; Cuzzocrea S was the most productive and influential author. “Apoptosis,” “spinal-cord-injury,” “expression,” “activation,” and “functional recovery” were the most frequent key words. Additionally, “transplantation,” “mesenchymal stemness-cells,” “therapies,” “activation,” “regeneration,” “repair,” “autophagy,” “exosomes,” “nlrp3 inflammasome,” “neuroinflammation,” and “knockdown” were the latest emerging key words, which may inform the hottest themes. Conclusions Apoptosis after SCI may cause the ultimate neurological damages. Development of novel treatments for secondary SCI mainly depends on a better understanding of apoptosis-related mechanisms in molecular and cellular levels. Such therapeutic interventions involve the application of anti-apoptotic agents, free radical scavengers, as well as anti-inflammatory drugs, which can be targeted to inhibit core events in cellular and molecular injury cascades pathway.