Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning, characterization, and expression analysis of the CHITINASE gene family in Helice tientsinensis

Chitinase is a kind of glycoside hydrolase which is widely distributed in nature and encoded by multiple genes to catalyze the decomposition of chitin, which plays an important role in the molting and pathogen defense of crustaceans. However, the research on chitinase in crustaceans is mainly focused on a few species with economic value. In this study, full-length cDNA sequences of the HtCHT1, HtCHT3 and HtCHT4 genes were cloned from the mudflat crab Helice tientsinensis by RACE, and the sequences were analyzed. The results showed that the full-length 2,229 bp of HtCHT1 gene encoded 627 amino acids, while the full-length 2,191 bp of HtCHT3 gene produced 489 amino acids, and the full-length 3,312 bp of HtCHT4 gene encoded 664 amino acids. Bioinformatics analysis showed that all the obtained chitinase proteins had the glycosyl hydrolase family 18 (GH18) catalytic domain and chitin-binding domain (ChtBD2), furthermore, HtCHT1 and HtCHT4 proteins had signal peptide domains at N-terminal. Phylogenetic analysis showed that different types of chitinase were clustered, and HtCHTs were closely related to chitinases in the Eriocheir sinensis. Expression profile analysis showed that the HtCHT1, HtCHT3 and HtCHT4 were significantly expressed in hepatopancreas. Furthermore, the expression of three genes was significantly up-regulated in hepatopancreas after the Vibrio parahaemolyticus challenge. These results suggested that HtCHT1, HtCHT3 and HtCHT4 were belonged to the CHITINASE gene family in H. tientsinensis and were potentially involved in the antibacterial immune response. This study provides essential information for further research of chitinase in H. tientsinensis and even crustaceans.
A 100–180-GHz Coaxial Frequency Tripler Based on Copper Additive Manufacturing

This article presents a wideband coaxial D-band frequency tripler fabricated by copper additive manufacturing (AM). The central part of the tripler consists of two waveguide–coaxial transitions, a coaxial low-pass filter, an antiparallel Schottky diode chip, and an output impedance matching network. Most constitutions, except for the diode chip, are monolithically fabricated in one piece. The diode chip with additional thermal paths is specially designed to obtain a good thermal performance and better power handling. To facilitate the measurement, a waveguide fixture is also designed to convert the ports to standard waveguide ports (WR-19 and WR-6.5). The measurements show that the maximum output power of the tripler is 9.44 mW with about 182 mW of input power at 147 GHz and its 3-dB bandwidth is 45.2% from 108 to 171 GHz. Additionally, the tripler delivers $>$ 1.87 mW of output power and better than 10 dB of return loss over the 100–180-GHz range. To the best of authors’ knowledge, this is the first AM coaxial ultra-wideband frequency multiplier reported in the open literature.
A High-Parallelism RRAM-Based Compute-In-Memory Macro With Intrinsic Impedance Boosting and In-ADC Computing

Resistive random access memory (RRAM) is considered to be a promising compute-in-memory (CIM) platform; however, they tend to lose energy efficiency quickly in high-throughput and high-resolution cases. Instead of using access transistors as switches, this work explores their analog characteristics as common-gate current buffers. So the cell current can be minimized and the output impedance is boosted. The idea of In-ADC Computing (IAC) is also proposed to further decrease the complexity of the peripheral circuits. Benefiting from the proposed ideas, a pretrained VGG-8 network based on the CIFAR-10 dataset can be implemented, and an accuracy of 87.2% is achieved with 8.9 TOPS/W energy efficiency (for 8-bit multiply-and-accumulate (MAC) operation), demonstrating that the proposed techniques enable low-distortion partial sum results while still being able to operate in a power-efficient way.
A novel Block Bi‐diagonalization based pre‐coding scheme for bit error reduction in mutiple input multiple output‐orthogonal frequency division multiplexing

The MIMO‐OFDM increases spectral efficiency without the use of channel state information (CSI). However, the bit error rate (BER) in the MIMO‐OFDM model increases dramatically due to the increase in nonlinear distortion in the power amplifier (PA). In this research, a novel pre‐coder integrated MIMO‐OFDM technology is designed for effective BER reduction, and its performance is analyzed. The discrete wavelet‐based OFDM system is one of the key ideas to present good orthogonal by emphasizing orthogonal wavelets. It helps to mitigate inter‐symbol interference (ISI) and noise within the channel by extending the bandwidth (BW) compared to conventional OFDM systems. But, DWT‐OFDM highly suffered due to downsampling, which degrades system efficiency. To overcome this, a redundant discrete wavelet transform (RDWT) is proposed in this article to enhance spectral efficiency. For modulation, 16‐bit quadrature amplitude modulation (QAM) is introduced in this work. In addition to this, a block bi‐diagonalization (BBD) pre‐coder technique is proposed to mitigate unwanted noise and interference in the MIMO‐OFDM system. The performance measures such as ergodic sum capacity, BER, throughput, average jitter noise power, mean square error (MSE), and power consumption are analyzed using the MATLAB platform. The proposed method obtains the ergodic sum capacity of 6.25 bps/Hz, a BER of 0.021, a throughput of 95.2%, MSE of −0.47, and a power consumption of 1.15 μW. The simulative results prove the efficacy of the proposed method.
The effects of sampling and instrument orientation on LiDAR data from crop plots

Wheat is one of the most widely consumed grains in the world and improving its yield, especially under severe climate conditions, is of great importance to world food security. Phenotyping methods can evaluate plants according to their different traits, such as yield and growth characteristics. Assessing the vertical stand structure of plants can provide valuable information about plant productivity and processes, mainly if this trait can be tracked throughout the plant’s growth. Light Detection And Ranging (LiDAR) is a method capable of gathering three-dimensional data from wheat field trials and is potentially suitable for providing non-destructive, high-throughput estimations of the vertical stand structure of plants. The current study considers LiDAR and focuses on investigating the effects of sub-sampling plot data and data collection parameters on the canopy vertical profile (CVP). The CVP is a normalized, ground-referenced histogram of LiDAR point cloud data representing a plot or other spatial domain. The effects of sub-sampling of plot data, the angular field of view (FOV) of the LiDAR and LiDAR scan line orientation on the CVP were investigated. Analysis of spatial sub-sampling effects on CVP showed that at least 144000 random points (600 scan lines) or an area equivalent to three plants along the row were adequate to characterize the overall CVP of the aggregate plot. A comparison of CVPs obtained from LiDAR data for different FOV showed that CVPs varied with the angular range of the LiDAR data, with narrow ranges having a larger proportion of returns in the upper canopy and a lower proportion of returns in the lower part of the canopy. These findings will be necessary to establish minimum plot and sample sizes and compare data from studies where scan direction or field of view differ. These advancements will aid in making comparisons and inform best practices for using close-range LiDAR in phenotypic studies in crop breeding and physiology research.
Therapeutic Plasma Exchange for the Treatment of Hyperthyroidism: Approach to the Patient with Thyrotoxicosis or Antithyroid-Drugs Induced Agranulocytosis

Primary hyperthyroidism is an endocrine disorder characterized by excessive thyroid hormone synthesis and secretion by the thyroid gland. Clinical manifestations of hyperthyroidism can vary from subclinical to overt forms. In rare cases, hyperthyroidism may represent a clinical emergency, requiring admission to an intensive care unit due to an acute and severe exacerbation of thyrotoxicosis, known as a thyroid storm. First-line treatment of hyperthyroidism is almost always based on medical therapy (with thioamides, beta-adrenergic blocking agents, glucocorticoids), radioactive iodine or total thyroidectomy, tailored to the patient’s diagnosis. In cases of failure/intolerance/adverse events or contraindication to these therapies, as well as in life-threatening situations, including a thyroid storm, it is necessary to consider an alternative treatment with extracorporeal systems, such as therapeutic plasma exchange (TPE). This approach can promptly resolve severe conditions by removing circulating thyroid hormones. Here we described two different applications of TPE in clinical practice: the first case is an example of thyrotoxicosis due to amiodarone treatment, while the second one is an example of a severe adverse event to antithyroid drugs (agranulocytosis induced by methimazole).
Validation of the influence of biosignals on performance of machine learning algorithms for sleep stage classification

Background Sleep stage identification is critical in multiple areas (e.g. medicine or psychology) to diagnose sleep-related disorders. Previous studies have reported that the performance of machine learning algorithms can be changed depending on the biosignals and feature-extraction processes in sleep stage classification. Methods To compare as many conditions as possible, 414 experimental conditions were applied, considering the combination of different biosignals, biosignal length, and window length. Five biosignals in polysomnography (i.e. electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), electrooculogram left, and electrooculogram right) were used to identify optimal signal combinations for classification. In addition, three different signal-length conditions and six different window-length conditions were applied. The validity of each condition was examined via classification performance from the XGBoost classifiers trained using 10-fold cross-validation. Furthermore, results considering feature importance were examined to validate the experimental results in terms of model explanation. Results The combination of EEG + EMG + ECG with a 40 s window and 120 s signal length resulted in the best classification performance (precision: 0.853, recall: 0.855, F1-score: 0.853, and accuracy: 0.853). Compared to other conditions and feature importance results, EEG signals showed a relatively higher importance for classification in the present study. Conclusion We determined the optimal biosignal and window conditions for the feature-extraction process in machine learning algorithm-based sleep stage classification. Our experimental results inform researchers in the future conduct of related studies. To generalize our results, more diverse methodologies and conditions should be applied in future studies.
Salt-Affected Rocket Plants as a Possible Source of Glucosinolates

Soil salinity can have various negative consequences on agricultural products, from their quality and production to their aesthetic traits. In this work, the possibility to use salt-affected vegetables, that otherwise would be discarded, as a source of nutraceuticals was explored. To this aim, rocket plants, a vegetable featuring bioactive compounds such as glucosinolates, were exposed to increasing NaCl concentrations in hydroponics and analysed for their content in bioactive compounds. Salt levels higher than 68 mM produced rocket plants that did not comply with European Union regulations and would therefore be considered a waste product. Anyway, our findings, obtained by Liquid Chromatography-High Resolution Mass Spectrometry, demonstrated a significant increase in glucosinolates levels in such salt-affected plants. opening the opportunity for a second life of these market discarded products to be recycled as glucosinolates source. Furthermore, an optimal situation was found at NaCl 34 mM in which not only were the aesthetic traits of rocket plants not affected, but also the plants revealed a significant enrichment in glucosinolates. This can be considered an advantageous situation in which the resulting vegetables still appealed to the market and showed improved nutraceutical aspects.
The Method of Fundamental Solutions for the Impulse Responses Reconstruction in Arbitrarily Shaped Plates

Summary In the present paper, impulse responses of thin isotropic plates of arbitrary shape and linear boundary conditions are determined from a set of measurements enclosing the area of interest. The used approach derives from the Method of Fundamental Solutions considering virtual monopolar sources in order to reconstruct the free vibration of the plate. The originality of this work lies in the practical deployment of this method: the collocation points are set in the plate and not at its boundaries as usually employed in eigenanalysis context. Also, an alternative formulation is presented for which only the relative placements of the virtual sources and the collocation points are needed to determine the weighting coe ﬃ cients, without knowing the shape of the plate and its boundary conditions. Several measurements with 3 kinds of plates have been achieved and the results highlight the remarkable robustness of the proposed formulations even for plate of complicated shape with various boundary conditions.
CpG 1018 Is an Effective Adjuvant for Influenza Nucleoprotein

Current influenza vaccines mainly induce neutralizing antibodies against the highly variable surface antigen hemagglutinin and require annual manufacturing and immunization. Different from surface antigens, intracellular nucleoprotein (NP) is highly conserved and has been an attractive target to develop universal T cell vaccines against influenza. Yet, influenza NP protein mainly induces humoral immune responses and lacks the ability to induce potent cytotoxic T lymphocyte (CTL) responses, key for the success of universal T cell vaccines. This study compared CpG 1018 and AddaVax to enhance recombinant NP-induced CTL responses and protection in murine models. CpG 1018 was explored to boost intradermal NP immunization, while AddaVax was explored to boost intramuscular NP immunization due to the high risk of AddaVax adjuvant to induce significant local reactions following intradermal delivery. We found CpG 1018 was highly effective to enhance NP-induced humoral and cellular immune responses superior to AddaVax adjuvant. Furthermore, CpG 1018 potentiated Th1-biased antibody responses, while AddaVax enhanced Th1/Th2-balanced antibody responses. CpG 1018 significantly enhanced IFNγ-secreting Th1 cells, while AddaVax adjuvant significantly increased IL4-secreting Th2 cells. Influenza NP immunization in the presence of CpG 1018 induced significant protection against lethal viral challenges, while influenza NP immunization in the presence of AddaVax failed to elicit significant protection. Our data validated CpG 1018 as an effective adjuvant to enhance influenza NP-induced CTL responses and protection.
Motion Sensor–Based Fall Prevention for Senior Care: A Hidden Markov Model with Generative Adversarial Network Approach

Whereas modern medicine has enabled humans to live longer and more robust lives, recent years have seen a significant increase in chronic care costs. The prevention of threats to mobility is critical for chronic disease management. Researchers and physicians often analyze data from wearable motion sensor–based information systems (IS) to prevent falls. However, prior studies on fall prevention often achieve suboptimal performance because of their limited capacities in modeling data distributions. In this study, we adopt the computational design science paradigm to develop a novel fall prevention framework, which includes the hidden Markov model with generative adversarial network (HMM-GAN) that extracts temporal and sequential patterns from sensor signals and recognizes snippet states and a logistic regression that utilizes the snippet states and determines whether and when to trigger protective devices to prevent fall injuries. We evaluate the proposed framework against prevailing fall-prevention models and the HMM-GAN component against state-of-the-art sensor analytics models on large-scale data sets. Through an in-depth case study, we demonstrate how the proposed framework can lead to significantly reduced potentially catastrophic falls. Besides practical health information technology contributions, HMM-GAN offers methodological contributions to the IS knowledge base for scholars designing novel IT artifacts for healthcare applications.
Storms and Lightning Activity in Greece during the Warm Periods of 2003–06

Abstract Lightning activity over Greece during the warm season (May–September) of the years 2003–06 is investigated in relation to the synoptic meteorological conditions that prevailed in the region. The study is based on the use of cloud-to-ground lightning activity data from the Met Office Arrival Time Difference system and upper-air analyses from the European Centre for Medium-Range Weather Forecasts. Analysis of the spatial variability of lightning shows that the highest “relative” flash densities are observed in northern and western Greece and in central and western Peloponnissos. The relative flash density is correlated with elevation: it increases with elevation along the slopes of terrain features. The study of the synoptic patterns related to lightning is based on the analysis of 60 active days and 60 inactive days in terms of lightning activity over Greece. The days with high lightning activity are characterized by a short-wave trough at the 500-hPa level over the Ionian Sea. On the other hand, .
Professional burnout in Staff of Mental Units: The Role of Working Conditions

Aim of this study is to investigate the level of professional burnout of mental health employees and to investigate the possible influence of various mental health factors on professional burnout. A cross-sectional methodology was employed to this study. A cohort of 217 employees who work in mental health settings in Greece was recruited. Data were collected with a three – part structured questionnaire consisted by questions on personal, professional and demographic data of the respondents, questions whose answers will give the profile of the working conditions and the Maslach Burnout inventory. The average age was (39.00 ± 8.19) years, 75.11 % were women, 60.2 % declared married, 47.5 % of the sample members have graduated from higher education institutes (and as for the profession 63.13 % are nurses, 14.28 % doctors and 22.59 % other specialties. Burnout levels were found to be can moderate, with the occupation, in particular nursing, understanding the context and purpose of work and cooperation between professionals, being aggravating factors. Research findings have shown moderate levels of burnout and several factors have been found to have an impact. Experience has been found as the most important factor for mental health sector.
Multitemporal spectroscopy for crop stress detection using band selection methods

A fast and precise sensor-based identification of pathogen infestations in wheat stands is essential for the implementation of site-specific fungicide applications. Several works have shown possibilities and limitations for the detection of plant stress using spectral sensor data. Hyperspectral data provide the opportunity to collect spectral reflectance in contiguous bands over a broad range of the electromagnetic spectrum. Individual phenomena like the light absorption of leaf pigments can be examined in detail. The precise knowledge of stress-dependent shifting in certain spectral wavelengths provides great advantages in detecting fungal infections. This study focuses on band selection techniques for hyperspectral data to identify relevant and redundant information in spectra regarding a detection of plant stress caused by pathogens. In a laboratory experiment, five 1 sqm boxes with wheat were multitemporarily measured by a ASD Fieldspec® 3 FR spectroradiometer. Two stands were inoculated with Blumeria graminis - the pathogen causing powdery mildew - and one stand was used to simulate the effect of water deficiency. Two stands were kept healthy as control stands. Daily measurements of the spectral reflectance were taken over a 14-day period. Three ASD Pro Lamps were used to illuminate the plots with constant light. By applying band selection techniques, the three types of different wheat vitality could be accurately differentiated at certain stages. Hyperspectral data can provide precise information about pathogen infestations. The reduction of the spectral dimension of sensor data by means of band selection procedures is an appropriate method to speed up the data supply for precision agriculture.
The Role of Rehabilitation in Arterial Function Properties of Convalescent COVID-19 Patients

Coronavirus disease (COVID-19) is a respiratory disease, although arterial function involvement has been documented. We assess the impact of a post-acute COVID-19 rehabilitation program on endothelium-dependent vasodilation and arterial wall properties. We enrolled 60 convalescent patients from COVID-19 and one-month post-acute disease, who were randomized at a 1:1 ratio in a 3-month cardiopulmonary rehabilitation program (study group) or not (control group). Endothelium-dependent vasodilation was evaluated by flow-mediated dilation (FMD), and arterial wall properties were evaluated by carotid–femoral pulse wave velocity (cf-PWV) and augmentation index (AIx) at 1 month and at 4 months post-acute disease. FMD was significantly improved in both the study (6.2 ± 1.8% vs. 8.6 ± 2.4%, p < 0.001) and control groups (5.9 ± 2.2% vs. 6.6 ± 1.8%, p = 0.009), but the improvement was significantly higher in the study group (rehabilitation) (p < 0.001). PWV was improved in the study group (8.2 ± 1.3 m/s vs. 6.6 ± 1.0 m/s, p < 0.001) but not in the control group (8.9 ± 1.8 m/s vs. 8.8 ± 1.9 m/s, p = 0.74). Similarly, AIx was improved in the study group (25.9 ± 9.8% vs. 21.1 ± 9.3%, p < 0.001) but not in the control group (27.6 ± 9.2% vs. 26.2 ± 9.8 m/s, p = 0.15). Convalescent COVID-19 subjects of the study group (rehabilitation) with increased serum levels of circulating IL-6 had a greater reduction in FMD. Conclusively, a 3-month cardiopulmonary post-acute COVID-19 rehabilitation program improves recovery of endothelium-dependent vasodilation and arteriosclerosis.
The dynamics of an isolated plasma filament at the edge of a toroidal device

The dynamics of an isolated plasma filament (an isolated blob) in the far scrape-off layer (SOL) of a toroidal device is described, with a proper averaging of the geometrical parameters as well as plasma parameters along the filament. The analysis is limited to the magnetohydrodynamic description. The effects of the electrical contact of the filament end with the limiter and of the finite plasma resistivity are also discussed.