Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognizing Automatic Link Establishment Behaviors of a Short-Wave Radio Station by an Improved Unidimensional DenseNet

It is difficult to recognize Automatic Link Establishment (ALE) behaviors of a short-wave radio station, if we do not acquire the radio station’s communication protocol standard. A method is proposed to recognize different ALE behaviors by using an improved unidimensional DenseNet. In this work, we directly recognize ALE signals in physical layer without the radio station’s communication protocol standard. Hence, we can avoid difficulties in demodulation, decryption and so on. Actually, the original DenseNet is used extensively in the field of computer vision, so the original DenseNet is firstly adapted for the unidimensional input. And then, two parallel dense blocks are used in our improved unidimensional DenseNet, which could improve the capability of network to extract ALE signals’ deep features. The experimental results show that the proposed method is able to recognize different ALE behaviors of a short-wave radio station. And improved DenseNet has better recognition performance than simple DenseNet. The simple DenseNet only contains one dense block. Finally, the results of comparison experiments also show that some classic networks have worse performance in ALE behaviors recognition, such as LeNet-5, ResNet-34, and DenseNet-121.
Effectiveness of ICF-based multidisciplinary rehabilitation approach with serial assessment and discussion using the ICF rehabilitation set in a convalescent rehabilitation ward

This study was aimed to determine the effectiveness of the International Classification of Functioning, Disability and Health (ICF)-based multidisciplinary rehabilitation approach with serial assessment and discussion with the ICF rehabilitation set. This prospective cohort study included consecutive patients admitted to the convalescent rehabilitation ward during the period between 1 August 2017 and 30 September 2018. Serial assessment and discussion with the ICF rehabilitation set every 2 weeks in each patient commenced from 1 April 2018. We analyzed the difference in the Extension Index of the ICF rehabilitation set between the periods before the assessment of the ICF rehabilitation set (prior period) and after that (post-period). The change of the Extension Index of the ICF rehabilitation set was higher in patients of the post-period group (n = 59) compared with those of the prior period group (n = 45) (mean 31.6, SD 18.5 vs. mean 17.3, SD 18.4, respectively; 95% confidence interval for the difference 7.0–21.5). Multiple regression analysis showed that serial assessment by the ICF rehabilitation set was independently associated with the improvement of the Extension Index. Multidisciplinary rehabilitation approach combined with serial assessment and discussion using the ICF rehabilitation set was associated with favorable recovery. Our study highlighted the effectiveness of ICF-based multidisciplinary rehabilitation in a clinical setting.
Culture studies on Ulvella lens and Ulvella setchellii

The life histories of Ulvella lens and U. setchellii were studied in culture. Both species have quadriflagellate zoospores. This means that there is no remaining difference between Ulvella and Pseudulvella. Plants grown in sea water without any additions developed hairs. It is suggested that Ochlochaete lentiformis is a later synonym of Ulvella lens.
Using a Domain Ontology to Bridge the Gap between User Intention and Expression in Natural Language Queries

Many systems try to convert a request in natural language into a structured query, but formulating a good query can be cognitively challenging for users. We propose an ontology-based approach to answer questions in natural language about facts stored in a knowledge base, and answer them through data visualizations. To bridge the gap between the user intention and the expression of their query in natural language, our approach enriches the set of answers by generating related questions, allowing the discovery of new information. We apply our approach to the Movies and TV Series domain and with queries and answers in Portuguese. To validate our natural language search engine, we have built a dataset of questions in Portuguese to measure precision, recall, and f-score. To evaluate the method to enrich the answers we conducted a questionnairebased study to measure the users’ preferences about the recommended questions. Finally, we conducted an experimental user study to evaluate the delivery mechanism of our proposal.
A simple modification of sphenopalatine block for post-dural puncture headache

We hypothesised DP during epidural catheter insertion might have occurred which caused PDPH. The epidural drug infusion was stopped. On examination, the patient was afebrile and had no focal neurological deficits. The patient was advised to lie supine with 10° Trendelenburg position and oral acetaminophen 650 mg with 50 mg caffeine thrice a day was prescribed. The patient had brisk urine output which was replenished as per renal transplant protocols. The epidural catheter was left in situ.
Indirect, Non-Thermal Atmospheric Plasma Promotes Bacterial Killing In Vitro and Wound Disinfection In Vivo Using Monogenic and Polygenic Models of Type 2 Diabetes (Without Adverse Metabolic Complications).

A novel atmospheric plasma device that uses indirect, non-thermal plasma generated from room air is being studied for its effects on wound disinfection in animal wounds of monogenic and polygenic murine models of type 2 diabetes. As a proof-of-concept report, the goal of this study was to demonstrate the efficacy and safety of the indirect non-thermal plasma (INTP) device in disinfecting polycarbonate filters established with Pseudomonas aeruginosa (PAO1) biofilms as well as wound disinfection in diabetic murine wounds. Dorsal excisional wounds in BALB/c, polygenic TALLYHO, and monogenic db/db mice established with PAO1 infection all demonstrated a 3-log colony-forming unit (CFU) reduction when subjected to a course of 20-minute INTP treatments. Importantly, blood glucose and body weights in these animals were not significantly impacted by plasma treatment over the study period. Plasma safety was also analyzed via complete blood count and comprehensive metabolic panels, showing no deleterious systemic effects after three consecutive days of 20-minute plasma applications. Therefore, the results obtained demonstrated (i) the Pseudomonas aeruginosa isolates were highly sensitive to INTP in-vitro, (ii) CFU reduction of infectious Pseudomonas in wounds of diabetic mice after INTP treatment is far superior to that of non-treated infected wounds, and (iii) the application of INTP shows no indication of toxic effects. Our results are consistent with indirect non-thermal atmospheric plasma as a promising adjunct to disinfecting wounds.
Colonization of a host tree by herbivorous insects under a changing climate

Climate warming has been predicted to increase the abundance of herbivorous insects. Together with concurrent poleward shifts in many insect species this may increase herbivore pressure on plants. However, the manner in which plants at higher latitudes become colonized by herbivorous insects in the future is unknown. We established a translocation experiment using 26 micropropagated silver birch Betula pendula genotypes from six populations originating from 60°N to 67°N, to study the susceptibility of the translocated birches to local herbivores. The birches were planted at three different latitudes in Finland (60°N, 62°N and 67°N). We studied the effect of source population and latitudinal translocation on herbivore density, species richness, and community composition among the genotypes growing in the same environmental conditions in two years; 2011 and 2012. The source population explained the variation in the herbivore density only in 2012, whereas latitudinal translocation did not affect herbivore density. Variation in species richness was not explained by the source population or by the latitudinal translocation. At two of the study sites, the similarity of the herbivore communities among the populations decreased with increasing latitudinal distance of the source populations, possibly because birch populations that grow geographically closer to each other are genetically more similar, and therefore support a more similar composition of the arthropod community. All birch genotypes were colonized by local herbivores, suggesting that as herbivores shift their ranges polewards, they are able to colonize novel host-plant genotypes. This enables compositional changes in insect communities on their host plants in the future, which in turn, might affect total herbivory and eventually, plant growth.
Diet of the squid Loligo forbesi Steenstrup (Cephalopoda: Loliginidae) in Irish waters

Stomach contents of Loligo forbesi obtained from commercial landings and research cruises in Irish waters and the Irish Sea were examined. A total of 62.3% of stomachs were empty. Fish remains occurred in 73.7% of all full or partially full stomachs, with crustaceans and cephalopods occurring in 26.4% and 7.5% respectively, L. forbesi was found to consume a wide range of fish and crustacean prey. Sagittal otoliths were used to identify fish species, and vertebrate to identify families. The most frequent species by per cent occurrence sprat (Sprattus sprattus), poor cod (Trisopterus minutus), Norway pout (T. esmarkii), and transparent goby (Aphia minuta). Crustaceans were the main prey item is squid of less than 100 mm mantle length, together with small clupeids and gobies. the predominant prey of medium-sized squid (100–220 mm) was found to be gadoid and clupeid fish, while gadoids and other cephalopods were the main prey of larger squid (>220 mm). Seasonal differences in the diet were apparent but were shown to be influenced by seasonal changes in squid size.
Two hits to the renin‐angiotensin system may play a key role in severe COVID‐19

The spike glycoprotein on the virion surface docking onto the angiotensin‐converting enzyme (ACE) 2 dimer is an essential step in the process of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection in human cells—involves downregulation of ACE2 expression with systemic renin‐angiotensin system (RAS) imbalance and promotion of multi‐organ damage. In general, the RAS induces vasoconstriction, hypertension, inflammation, fibrosis, and proliferation via the ACE/Ang II/Ang II type 1 receptor (AT1R) axis and induces the opposite effects via the ACE2/Ang (1‐7)/Mas axis. The RAS may be activated by chronic inflammation in hypertension, diabetes, obesity, and cancer. SARS‐CoV‐2 induces the ACE2 internalization and shedding, leading to the inactivation of the ACE2/Ang (1‐7)/Mas axis. Therefore, we hypothesize that two hits to the RAS drives COVID‐19 progression. In brief, the first hit originates from chronic inflammation activating the ACE/Ang II/AT1R axis, and the second originates from the COVID‐19 infection inactivating the ACE2/Ang (1‐7)/Mas axis. Moreover, the two hits to the RAS may be the primary reason for increased mortality in patients with COVID‐19 who have comorbidities and may serve as a therapeutic target for COVID‐19 treatment.
EFFECTS OF CHILDCARE ON SOCIOEMOTIONAL ADJUSTMENT 1 Do Time in Childcare and Peer Group Exposure Predict Poor Socioemotional Adjustment in Norway?

Author note Elisabet Solheim and Lars Wichstrøm, Department of Psychology, and Social Research, Norwegian University of Science and Technology, Trondheim, Norway; Jay Belsky, Department of Human and Community Development, University of California-Davis, United States, Department of Special Education King Abdulaziz University, Jedda, Saudi Arabia, and Department of Psychology, Birkbeck University of London, London, United Kingdom; Turid Suzanne Berg-Nielsen, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
A Deep Learning H2O Framework for Emergency Prediction in Biomedical Big Data

Recently, the design and implementation of new healthcare systems have gained an interest in both industry and academia. The amalgamation between the Internet of Things, cloud, edge computing, and big data helps the proliferation of new scenarios for smart medical services and applications. Deep learning is currently paying a lot of attention for its utilization with big healthcare data. To this end, the main objective of this study is to propose a Deep Learning H<sub>2</sub>O (DLH<sub>2</sub>O) framework for improving the performance and selection of the optimal features to predict emergency cases. The proposed DLH<sub>2</sub>O framework consists of data preprocessing layer, feature selection layer and deep learning layer. The DLH<sub>2</sub>O framework aims to find the optimal subset of features and minimize the error of the classification through a proposed new variant of the Whale Optimization Algorithm (WOA) called ACP-WOA. The proposed changes have been done on the following parameters <inline-formula> <tex-math notation="LaTeX">$a$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$a2$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$A$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> which should affect both exploration and exploitation of WOA. The experiments conducted in order to test the validity of DLH<sub>2</sub>O Framework. In regard to the datasets, five experiments are performed for this purpose. The results demonstrate the superiority of ACP-WOA compared to the other state-of-the-art meta-heuristic algorithms in terms of time, error, and scalability. The proposed ACP-WOA is also tested on CEC2017 benchmark functions and proves its superiority over WOA in terms of accuracy.
Adaptive Multi-Modality Residual Network for Compression Distorted Multi-View Depth Video Enhancement

Compression distorted multi-view video plus depth (MVD) should be enhanced at the receiver side without the original signals, especially the depth maps because they describe the positioning information in 3D space and they are important for subsequent virtual view synthesis. However, challenge arises from how to exploit the contribution from multi-modality priors from neighboring viewpoints, and how to handle the gradient vanishing when textureless depth maps are involved. In this paper, we propose a multi-modality residual network to enhance the quality of compressed multi-view depth video. Taking advantage from high correlation among different viewpoints, depth maps from adjacent views are exploited as guidance for the enhancement of depth video in target view. Color frames in target view are also involved to offer the information object contours, obtaining multi-modality guidance. The proposed network is organized a deep residual network to well eliminate distortion and restore details. Because above multi-modality guidance have different correlations with target depth video and not all information can contribute to the enhancement, an adaptive skip structure is designed to further exploit the contribution from different priors appropriately. Experimental results show that our scheme outperforms other benchmarks and achieves an average 1.935 dB and 0.0227 gains on PSNR and SSIM over all test sequences, respectively. All results on objective, subjective and 3D reconstruction suggest that our method is able to provide superiority performance in practical applications.
An Accurate, Power and Area Efficient 13.33x Charge Pump with Wide-Range Programmability for Biomedical Sensors

A power and area efficient charge pump (CP) with a wide output range is proposed for biomedical applications. The CP powers up the data transmitters in the biomedical sensors at regular intervals of 3ms. It provides a maximum energy of 750nJ to transmitter in 500ns during each transmission cycle. The CP works on 1.8V supply and outputs 7.5V- 24V in steps of 1.2 V. The output inaccuracy of CP is <1% for all programmable outputs with a low leakage current of 380nA in standby mode. The CP include fly MIM-capacitors implemented in metal 5-6, which cover the digital circuitry beneath making it area efficient. The proposed CP is implemented in 180nm BCD process and occupies 0.038 mm2 of active area.
External Pressures Based on Leaf Water Potentials Do Not Induce Xylem Sap to Flow at Rates of Whole Plant Transpiration from Roots of Flooded or Well-drained Tomato and Maize Plants. Impact of Shoot Hydraulic Resistances

We tested the hypothesis that leaf water potentials (ψL) are good guides to the positive pneumatic pressure needed to drive water flow through detopped root systems at the rate of whole plant transpiration. Unless sap flows at this rate, solute concentrations and rates of delivery are poor estimates of those carried by the transpiration stream of intact plants. In flooded and well-drained tomato (Lycopersicon esculentum L.) and maize (Zea mays L.) plants, pressures based on ψLproduced flow rates that were two–four times faster than whole plant transpiration. Covering leaves for several hours resulted in a less negative ψL . The smaller pneumatic pressures based on these measurements gave slower sap flow but rates still exceeded whole plant transpiration. The overrun is ascribed to the removal of hydraulic resistance when the shoots were excised for sap collection. In tomato, differences in ψLacross putative sites of resistance, or of increased sap flow when resistances were removed surgically, located major hydraulic resistances in leaf laminae and at stem–petiole junctions. Pneumatic pressures to generate realistic sap flow rates were therefore chosen by reference to experimentally derived pressure–flow curves and not to ψL . An alternative method of sap collection was tested where xylem sap was sampled from whole plants with roots pressurized until hydrostatic water potential of the xylem slightly exceeded atmospheric pressure. Calcium and osmolality concentrations in sap from a cut petiole close to the shoot base of tomato plants were similar to those obtained from detopped plants using pressures that produced transpiration-like flow rates. Sampling from different positions revealed that concentrations and delivery rates of calcium and osmolality decreased as xylem sap was transported upwards through the shoot.
Prediction Models for Automatic Assessment to Students' Freely-written Comments

Tracking students’ learning situations is taking a fundamental place in educational institutions. Thanks to the advances in educational technology, we are able to gather more and more data about students using educational software systems. Analyzing such data helped researchers build models that could predict students’ behaviors and scores. However, in classroom-based settings, teachers and professors find difficulties to perfectly grasp all their students’ learning attitudes. In an approach to address this issue, we asked the students to give freelywritten comments answering predefined questions about their learning experience. Thereafter, professors read these comments and give feedback to each student. Nonetheless, professors find themselves overwhelmed by the number of comments which make this approach not scalable to multiple classes for the same professor. In this paper, we address this issue by building a model that can automatically assess the students’ comments. We use two different approaches. In the first approach, we treat all student comments the same way, regardless of which question they are related to. The second approach consists of building different individual models that analyze students’ comments depending on the question. Experimental results show that the prediction accuracy of assessment to student comments can reach 74%.
Predictors of Non-Surgical Cosmetic Procedure Consideration among Indonesians

The non-surgical cosmetic procedure is defined by ISAPS as an effective and safer procedure for people that want a more subtle improvement, enhancing surgical results or minimize recovery time of a procedure, which often does not require extensive training to perform compared to the surgical sector as it has higher risks. ISAPS reported that the number of non-surgical cosmetic procedures has increased 51.4% from 2011 and 2017. Despite this growth, little is known about factors that prompt the willingness to consider non-surgical cosmetic procedures. Addressing this issue, this study focuses on facets of objectified body consciousness (i.e., body surveillance, body shame, appearance anxiety) and tripartite influence model features (i.e., appearance pressure, internalization through comparison, body dissatisfaction) combined with the Theory of Planned Behavior (i.e., attitude and intention) towards considerations of non-surgical cosmetic procedures. The study is conducted through online quantitative questionnares adopted from previous researches, on a sample size of 271 Indonesians based on Cochran’s formula, specifically those living in Jakarta. In line with previous research on similar practices of beauty industry (e.g., cosmetic surgery), analyses indicated that non-surgical cosmetic procedure consideration was related to the objectified body consciousness and most of the tripartite influence features. Findings highlighted that body shame and facial appearance concern is the strongest predictor. These findings will be able to help marketers to account for variability in willingness to consider non-surgical cosmetic procedure and aligned their strategies accordingly and effectively.
Deep Video Prediction Network-ased Inter-Frame Coding in HEVC

In this paper, we propose a novel Convolutional Neural Network (CNN) based video coding technique using a video prediction network (VPN) to support enhanced motion prediction in High Efficiency Video Coding (HEVC). Specifically, we design a CNN VPN to generate a virtual reference frame (VRF), which is synthesized using previously coded frames, to improve coding efficiency. The proposed VPN uses two sub-VPN architectures in cascade to predict the current frame in the same time instance. The VRF is expected to have higher temporal correlation than a conventional reference frame, and, thus it is substituted for a conventional reference frame. The proposed technique is incorporated into the HEVC inter-coding framework. Particularly, the VRF is managed in a HEVC reference picture list, so that each prediction unit (PU) can choose a better prediction signal through Rate-Distortion optimization without any additional side information. Furthermore, we modify the HEVC inter-prediction mechanisms of Advanced Motion Vector Prediction and Merge modes adaptively when the current PU uses the VRF as a reference frame. In this manner, the proposed technique can exploit the PU-wise multi-hypothesis prediction techniques in HEVC. Since the proposed VPN can perform both the video interpolation and extrapolation, it can be used for Random Access (RA) and Low Delay B (LD) coding configurations. It is shown in experimental results that the proposed technique provides −2.9% and −5.7% coding gains, respectively, in RA and LD coding configurations as compared to the HEVC reference software, HM 16.6 version.