Miracle-dz/UniFAR-FTUs huggingface dataset:
GAN augmentation for multiclass image classification using hemorrhage detection as a case-study

Abstract. Purpose: In recent years, the development and exploration of deeper and more complex deep learning models has been on the rise. However, the availability of large heterogeneous datasets to support efficient training of deep learning models is lacking. While linear image transformations for augmentation have been used traditionally, the recent development of generative adversarial networks (GANs) could theoretically allow us to generate an infinite amount of data from the real distribution to support deep learning model training. Recently, the Radiological Society of North America (RSNA) curated a multiclass hemorrhage detection challenge dataset that includes over 800,000 images for hemorrhage detection, but all high-performing models were trained using traditional data augmentation techniques. Given a wide variety of selections, the augmentation for image classification often follows a trial-and-error policy. Approach: We designed conditional DCGAN (cDCGAN) and in parallel trained multiple popular GAN models to use as online augmentations and compared them to traditional augmentation methods for the hemorrhage case study. Results: Our experimentations show that the super-minority, epidural hemorrhages with cDCGAN augmentation presented a minimum of 2 × improvement in their performance against the traditionally augmented model using the same classifier configuration. Conclusion: This shows that for complex and imbalanced datasets, traditional data imbalancing solutions may not be sufficient and require more complex and diverse data augmentation methods such as GANs to solve.
Implementation of a virtual reality design review application using vision-based gesture recognition technology

Classification societies date back to the second half of the 18th century, where marine insurers developed a system for independent technical assessment of the ships presented to them for insurance cover. Today, a major part of a classification society’s responsibilities is to review the designs of enormous maritime vessels. This usually involves working with big and complex 3D models and 3D tools, but without support to do many of the tasks required in a design review. As a consequence, the workflow is often just partially digital, and many important tasks, such as annotating or commentating on aspects of the models, are done on paper. DNV GL, the world’s largest maritime classification society, is interested in digitalizing this process more, and make it more interactive and efficient by utilizing an application that allows for virtual design review meetings in the 3D models. In these virtual design review meetings, the designer and reviewer could remotely interact, survey the model together, and annotate it instead of model-printouts. As the sense of scale is important in a 3D model review, virtual reality technology is deemed promising as it gives a unique sense of scale and a depth, which is hard to match by regular 2D screens. DNV GL is also interested in alternate interaction methods, as mouse and keyboard can have some limitation when working in 3D environments. Gesture Recognition Technology has been of special interest as this can potentially offer unique approaches to working with 3D models. This thesis implements such a design review application using state-ofthe-art virtual realityand vision-based gesture recognition technologies, coupled with the Unity game engine, a popular cross-platform game development platform and software framework. After discussing these technologies’ theoretical foundations, the thesis reviews the requirements and design of the design review application, in addition to documenting its implementation and evaluating its performance by conducting user tests. In the implemented design review application the user is able to navigate 3D models, annotate them and perform various other actions, all performed by gestures.
Optical correlator for textile web defect detection

Cost-effective optical correlators are now available for industrial applications. One such application field is the real-time automatic inspection of textile web, in which the high data throughput of the optical correlator over-performs that of the electronic computer. Two approaches for defect enhancement using of wavelet and Wiener filters are proposed. The band-pass wavelet filter is designed to give higher weights in the frequency band, where the energy of defect is higher than that of the web, and to suppress the zero, first and all higher diffracted orders. The Wiener filters are designed based on an average defect shape, with the web texture considered as noise. Using the technique developed at INO (National Optics Institute), a set up of the Vander Lugt type correlator demonstrates experimentally the relevancy of the algorithms. Simulation and optical results are presented.
MIMO Antenna Selection Using Binary Search Algorithm

A practical antenna selection (AS) scheme is investigated for downlink multiuser massive multiple input multiple output (MIMO) networks where a base station (BS) is equipped with many antennas (N) and communicates with K mobile stations (MSs) simultaneously. In the proposed antenna selection technique, S antennas (S≤N) are selected for transmission based on the knowledge of channel coefficients of each MS for reducing the number of RF chains which mainly induce cost increase in terms of size, hardware, and power. In the proposed AS technique, a BS first ranks antenna elements according to the sum of their channel gains to all MSs. Then, the BS computes the downlink sum-rate with S consecutive antenna elements in the ordered set, where the subset consisting of S consecutive antennas is called a window . The BS selects the window resulting in the highest sum-rate. The selected S antenna elements are used for transmitting signals to multiple users, while the remaining (N−S) antenna elements are turned off for the time slot. Therefore, the proposed AS technique requires only (N−S+1) sum-rate computations, while the optimal AS technique involves N S computations. We analyze downlink sum-rate with the proposed AS technique and compare it with that of a reference system with the same number of antenna elements without AS.
A Study on Nonvisual Effects of Natural Light Environment in a Maternity Ward of a Hospital in Cold Area

Thanks to the discovery of human eye photoreceptor cells, ipGRC and human nonvisual channels, the nonvisual effects of light have gradually come to our vision and been rationally utilized. Along with this trend, people have expanded their demand for the light environment to both visual and nonvisual needs from only visual needs. With a good natural daylighting, parturients will find their psychological pressure and physiological pain relieved, their rehabilitation rate increased, and they get rehabilitated more quickly. This study was carried out in a representative maternity ward in Harbin based on the latest research results on nonvisual effects at home and abroad. Specifically, the nonvisual effects on the natural light environment in the ward throughout the year were simulated and analyzed from the aspects of equivalent melanopic lux (EML), stimulus frequency (Stim.freq), and circadian effective area (CEA). During the study, natural light in the ward was measured on site, and the evaluation tool and workflow of nonvisual effects were created with the aid of Grasshopper modeling platform, Ladybug+Honeybee, and VB script editor. The results show that the nonvisual effects of natural light on the body of parturients gradually weaken as they further go inside the ward. What is worse, in the most unfavorable all-overcast condition, daylighting on beds far away from the window does not meet the stimulus of human circadian rhythm from April to August. Therefore, additional light is required. The wards have the best nonvisual natural light environment when they are south facing and have a window to floor ratio of 0.3.
Predictors of the Third (Booster) Dose of COVID-19 Vaccine Intention among the Healthcare Workers in Saudi Arabia: An Online Cross-Sectional Survey

Objective: The COVID-19 pandemic is still continuing throughout the world, with newer genetic variants regularly appearing from different parts of the world. Considering the waning of immunity against COVID-19 infection even with two doses of the COVID-19 vaccine, regulatory authorities have authorised booster COVID-19 vaccination in many countries, especially for vulnerable populations, including healthcare workers. The current study analysed factors predicting the third (booster) dose of COVID-19 vaccine intention, including the health belief model (HBM), among the healthcare workers in Saudi Arabia. Methods: The current study was a cross-sectional online survey performed from 1st October 2021 to 30th November 2021, using a questionnaire prepared in GoogleTM form among healthcare workers in Saudi Arabia. The questionnaire asked demographic factors, COVID-19 experience of participants, subjective assessment of health, intention of COVID-19 booster dose vaccination, preferences for local/foreign-made vaccines, and health belief of the study population related to COVID-19 infection and COVID-19 booster dose. Results: This study received 2059 complete responses. The study population reported mixed health belief with respect to the susceptibility of COVID-19 infection, and higher health belief perception regarding the severity. The perceptions of the study participants regarding the benefits of COVID-19 booster dose were positive. There were few barriers to COVID-19 booster dose expressed by study participants. A total of 1464 (71.1%) study participants reported positive intent for receiving a COVID-19 booster dose. The study showed significant association between definite intention to receive a booster dose and nationality (p = 0.001), marital status (p = 0.017), gender (p < 0.001), education level (p = 0.001), monthly income (p < 0.001), and co-morbid medical illness (p = 0.045). The perception of the COVID-19 booster vaccine as a good idea to minimise worries about getting COVID-19 (OR = 2.28, CI 1.89–2.76), and perceptions that receiving the third (booster) dose reduces the risk of COVID-19 infection and associated complications (OR= 2.69, CI = 2.17–3.34), of the perceived benefit construct of HBM, predicted significantly higher definite intention to receive a booster dose. The concern with the safety of the vaccine (OR= 0.40, CI 0.34–0.47) under the perceived barriers construct of HBM predicted as significantly higher no definite intention to receive a booster dose. Conclusions: The results of the present study can guide policy makers in their efforts to promote booster doses of COVID-19 vaccination among the healthcare workers in Saudi Arabia.
Negative Associations of Stress and Anxiety Levels With Cytotoxic and Regulatory Natural Killer Cell Frequency in Chronic Tinnitus

Background Depression and anxiety are known to be associated with stress-induced changes in the immune system. Bothersome tinnitus can be related to stress and often co-occurs with depression and anxiety. This study investigates associations of psychological and audiological tinnitus-related factors with inflammatory parameters and immune cell subsets in chronic tinnitus patients as well as treatment-related effects. Methods This longitudinal study of inpatients treated with compact multimodal tinnitus-specific cognitive behavioral therapy included four repeated measurement sessions: baseline (N = 41), treatment end, 7.8-week (N = 35), and 13.8-week follow-up (N = 34). Data collection included audiometric testing, blood sampling, and psychometric questionnaires: Tinnitus Handicap Inventory (THI), Perceived Stress Questionnaire (PSQ-20), and Hospital Anxiety Depression Scale (HADS). Flow cytometry was used to analyze immune cell subsets. Statistical analyses comprised correlation and network analysis (cross-sectional), and linear mixed effect models (longitudinal). Results Bootstrapped network analysis showed negative averaged cross-sectional associations of cytotoxic natural killer (NKc) cell frequency (CD56 + CD16+) and PSQ-20 (−0.21 [−0.48, 0]) and of regulatory natural killer (NKreg) cell frequency (CD56 + CD16dim/−) and HADS anxiety (−0.14 [−0.38, 0]). No significant treatment effects were found. A negative predictive effect of baseline PSQ-20 scores (β = −6.22 [−12.18, −0.26], p = 0.041) and a positive predictive effect of baseline ferritin levels (β = 8.90 [2.76, 15.03], p = 0.004) on NKc cell frequency across the repeated measurement sessions were observed. Conclusion We observed negative relationships between perceived stress levels and NKc cell frequency and between anxiety levels and NKreg cell frequency in chronic tinnitus patients. These exploratory results suggest stress−/anxiety-related immune alterations in bothersome tinnitus but need to be tested in further confirmatory studies with larger sample sizes. The potential of NK cells as biomarkers of emotional distress in chronic tinnitus should be further investigated.
A Viterbi Decoder under Class A Modeled Noise in Shallow Water

A traditional Viterbi decoder is primarily optimized for additive white Gaussian noise (AWGN). With the AWGN channel, it offers good decoding performance. However, the underwater acoustic communication (UAC) channel is extremely complicated. In addition to white noise, there are a variety of artificial and natural impulse noise that occur suddenly. The traditional Viterbi decoder cannot obtain the optimum performance under this case. In order to solve this problem, this paper introduces a novel Viterbi decoder with the impulsive noise, which is considered to be subjected to Middleton Class A distribution in shallow ocean. Since Middleton Class A noise is very complicated, a simplified model is first introduced. Then, the error analysis of simplified model under various parameters is discussed in detail. The analysis shows that the simplified one just leads to slight error. Hereafter, a novel Veterbi decoder using the simplified model is discussed. Compared to a traditional decoder, a preprocessing is just required. The performance of soft decision-based decoder in the Middleton Class A noise channel (MAIN) and AWGN are further compared. Based on our simulations, the new decoder can significantly improve the performance in comparison with conventional one, which further validates our presented method.
Decoupling RNN Training and Testing Observation Intervals for Spectrum Sensing Applications

Recurrent neural networks have been shown to outperform other architectures when processing temporally correlated data, such as from wireless communication signals. However, compared to other architectures, such as convolutional neural networks, recurrent neural networks can suffer from drastically longer training and evaluation times due to their inherent sample-by-sample data processing, while traditional usage of both of these architectures assumes a fixed observation interval during both training and testing, the sample-by-sample processing capabilities of recurrent neural networks opens the door for alternative approaches. Rather than assuming that the testing and observation intervals are equivalent, the observation intervals can be “decoupled” or set independently. This can potentially reduce training times and will allow for trained networks to be adapted to different applications without retraining. This work illustrates the benefits and considerations needed when “decoupling” these observation intervals for spectrum sensing applications, using modulation classification as the example use case. The sample-by-sample processing of RNNs also allows for the relaxation of the typical requirement of a fixed time duration of the signals of interest. Allowing for variable observation intervals is important in real-time applications like cognitive radio where decisions need to be made as quickly and accurately as possible as well as in applications like electronic warfare in which the sequence length of the signal of interest may be unknown. This work examines a real-time post-processing method called “just enough” decision making that allows for variable observation intervals. In particular, this work shows that, intuitively, this method can be leveraged to process less data (i.e., shorter observation intervals) for simpler inputs (less complicated signal types or channel conditions). Less intuitively, this works shows that the “decoupling” is dependent on appropriate training to avoid bias and ensure generalization.
Effect Analysis of Preoperative Intravenous Tranexamic Acid Combined With Intraoperative Immersion in Reducing Perioperative Blood Loss of One Stage Posterior Thoracolumbar Tuberculosis

Background To investigate the efficacy and safety of preoperative intravenous tranexamic acid (TXA) combined with intraoperative immersion in reducing perioperative blood loss in one-stage posterior thoracolumbar tuberculosis. Methods All patients were divided into four groups: Group A received an intravenous drip of TXA before surgery, group B received multiple local immersions during the operation, group C received an intravenous drip combined with multiple local immersions, and the control group (group CG) were not treated with TXA during the same period. The total blood loss (TBL), intraoperative blood loss (IBL), hidden blood loss (HBL), postoperative drainage volume, maximum hemoglobin drop value (max Hb drop), liver and kidney function, coagulation indexes, blood transfusion rate, hospital stay and incidence of complications were compared among the four groups. Results TBL, IBL, HBL, max Hb drop, POD1 drainage, and POD2 drainage in group A, group B, and group C were significantly lower than those in group CG. TBL, IBL, HBL and max Hb drop were group C < group A < group B < group CG. The drainage volume of group C was significantly lower than that of the other groups. There was no significant difference in blood coagulation index (PT, D-D) or liver and kidney function (ALT, Cr) among the four groups. There was no difference in postoperative hospital stay between group A and group B, but it was significantly lower in group C than in the other three groups. All patients achieved satisfactory bone graft fusion at the last follow-up. Conclusion Preoperative intravenous drip of TXA combined with intraoperative multiple immersion can effectively reduce perioperative blood loss while not increasing the risk of thrombosis without affecting liver and kidney function, coagulation function or tuberculosis prognosis.
Identification of Small-Molecule Inhibitors for Osteosarcoma Targeted Therapy: Synchronizing In Silico, In Vitro, and In Vivo Analyses

Objective: The study aimed to explore a new approach for the treatment of osteosarcoma through combining biomaterials with next-generation small molecule–based targeted therapy. Methods: The model of osteosarcoma was established by 4-hydroxyaminoquinoline 1-oxide (4-HAQO) in mice while the collagen-thermosensitive hydrogel–calcium phosphate (CTC) biocomposites were prepared, and the small molecule inhibitors were virtually screened and synthesized. Then, for the osteosarcoma cell line, MG-63 cells were used to validate our bioinformatic findings in vitro, and the mouse osteosarcoma models were treated by combing CTC composites and small-molecule inhibitors after debridement. Results: Five compounds, namely, ZINC150338698, ZINC14768621, ZINC4217203, ZINC169291448, and ZINC85537017, were found in the ZINK database. Finally, ZINC150338698 was selected for chemical synthesis and experimental verification. The results of the MTT assay and Hoechst staining showed that the small-molecule inhibitor ZINC150338698 could significantly induce MG-63 cell death. Furthermore, CTC composites and ZINC150338698 could repair the bone defects well after the debridement of osteosarcoma. In addition, the biomaterials and small-molecule inhibitors have good biocompatibility and biosafety. Conclusion: Our findings not only offer systems biology approach-based drug target identification but also provide new clues for developing novel treatment methods for future osteosarcoma research.
Study of the interactions of di- and tri-terpenes from Stillingia loranthacea with the enzyme NSP16-NSP10 of SARS-CoV-2

Objetivo: avaliar as interações de di- e tri-terpenos de Stillingia loranthacea com a enzima Objective : This study aimed to evaluate the interactions of di- and tri-terpenes from Stillingia loranthacea with the enzyme NSP16-NSP10 of SARS-CoV-2, important for viral replication. Methods : The molecular docking technique was used to evaluate this interaction. : The analysis showed that the evaluated compounds obtained RMSD values of 0.888 to 1.944 Å and free energy of -6.1 to -9.4 kcal/mol, with the observation of hydrogen bonds, salt bridges, and pi-sulfur, pi-alkyl, and hydrophobic interactions. Conclusion: Thus, the results obtained show the potential of the compounds analyzed against the selected target. Since computer simulations are only an initial step in projects for the development of antiviral drugs, this study provides important data for future research.
Standardizing protocols for determining the cause of mortality in wildlife studies

Abstract Mortality site investigations of telemetered wildlife are important for cause‐specific survival analyses and understanding underlying causes of observed population dynamics. Yet, eroding ecoliteracy and a lack of quality control in data collection can lead researchers to make incorrect conclusions, which may negatively impact management decisions for wildlife populations. We reviewed a random sample of 50 peer‐reviewed studies published between 2000 and 2019 on survival and cause‐specific mortality of ungulates monitored with telemetry devices. This concise review revealed extensive variation in reporting of field procedures, with many studies omitting critical information for the cause of mortality inference. Field protocols used to investigate mortality sites and ascertain the cause of mortality are often minimally described and frequently fail to address how investigators dealt with uncertainty. We outline a step‐by‐step procedure for mortality site investigations of telemetered ungulates, including evidence that should be documented in the field. Specifically, we highlight data that can be useful to differentiate predation from scavenging and more conclusively identify the predator species that killed the ungulate. We also outline how uncertainty in identifying the cause of mortality could be acknowledged and reported. We demonstrate the importance of rigorous protocols and prompt site investigations using data from our 5‐year study on survival and cause‐specific mortality of telemetered mule deer (Odocoileus hemionus) in northern California. Over the course of our study, we visited mortality sites of neonates (n = 91) and adults (n = 23) to ascertain the cause of mortality. Rapid site visitations significantly improved the successful identification of the cause of mortality and confidence levels for neonates. We discuss the need for rigorous and standardized protocols that include measures of confidence for mortality site investigations. We invite reviewers and journal editors to encourage authors to provide supportive information associated with the identification of causes of mortality, including uncertainty.