Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Multiuser Equalizer for mmWave Massive MIMO GFDM Systems

In this paper, we propose a hybrid multiuser equalizer combined with low complexity hybrid precoder for wideband millimeter-wave massive MIMO systems. We consider a generalized frequency division multiplexing (GFDM) modulation scheme, which is a new digital non-orthogonal multi-carrier modulation, aiming to achieve higher spectral efficiency, better control of out-of-band (OOB) emissions, and obtain a reduction in peak to average power ratio (PAPR) compared to OFDM. At the transmitter side, a simple yet efficient pure analog precoder is applied. At the base station, the hybrid multiuser linear equalizer is optimized by minimizing the mean square error between the hybrid approach and the full digital counterpart. The analog phase shifters have constant amplitude being constant over the bandwidth due to the hardware constraints. The results show that the performance of the proposed hybrid scheme is very close to the full digital counterpart as the number of RF chains increases.
Processing Time Reduction for JPEG Compression Using Pixel Array Conversion

Across the autonomous driver-less car industry, remote vehicle control systems have received increased attention. To maintain the performance of these systems, image compression is necessary to reduce time-delay to less than 33 ms. This paper proposes a methodology for reducing the processing time of image compression by adapting the pixel array conversion algorithm. This study shows that our methodology shortens the compression process time to 28.9 ms, which meets the latency requirement of remote control systems.
Fog-Enabled Industrial WSNs to Monitor Asynchronous Electric Motors

Recently, Industrial Wireless Sensor Networks (IWSN) have gained a lot of interest from both research and industry communities as an evolution of WSN specifically tailored for Industry 4.0 applications and their requirements. Thanks to the set of benefits IWSN technology introduces, it is considered to be a sustainable solution for industrial system monitoring. Yet, this approach has several drawbacks stemming from the limited resources (i.e., compute and storage) available on-board network devices. Although Cloud-based WSN data management solutions are widely adopted, issues related to this approach persist (e.g., high latency, bandwidth consumption, storage costs). This paper introduces an innovative platform enhancing IWSN architectures by adding a processing layer at the network edge: an approach that follows the Fog Computing paradigm. Remote management and programmability of the Fog layer are only some of the most challenging requirements. We show how our approach is suitable for industrial scenarios by applying it to a representative use case, i.e., the monitoring of asynchronous electric motors.
Using Decision Diagrams of Special Kind for Compactification of Conflict Data Bases Generated by CDCL SAT Solvers

In the paper we propose new algorithms for constructing compact representations of databases of conflict clauses accumulated by state-of-the-art CDCL SAT solvers. These algorithms use the Decision Diagrams of a special kind (the so-called Disjunctive Diagrams). We consider several families of hard SAT instances and use them to compare the implementations of the proposed algorithms and the well-known CUDD package that uses Zero-Suppressed Binary Decision Diagrams (ZBDD) for solving similar problems. The computational experiments clearly show that our algorithm that uses Disjunctive Diagrams has better effectiveness compared to CUDD.
Measurement and 3D Simulation Study of Shielding Properties of HV Connectors used in Electric and Hybrid Vehicles

This paper is devoted to the experimental validation of the 3D modeling approach for studying the shielding properties of high voltage (HV) connectors used in electric and hybrid vehicles with an arbitrary number, shape, size and location of apertures. The 3D simulation model is based on the method of moments (MoM), and novelty is in special implementation of Mitzner surface impedance boundary conditions (SIBC) for nested regions bounded by thin material sheets with apertures. This implementation implies the so-called null-field approach. Both measured and simulated results for the transfer impedance of prototype models of the HV connectors are presented and compared for various numbers and shapes of apertures.
One-Shot Voice Conversion Algorithm Based on Representations Separation

Voice Conversion (VC) is a method of converting the source speaker’s speech into the target speaker’s speech without changing the source speaker’s speech content. The current VC methods have the following problems: (1) they are only applicable to a limited number of speakers, not to any speakers, as a result, the application scenarios are greatly restricted; (2) the representation (feature) separation(RS) effect of the current mainstream technology is not ideal on the source speaker speech and the target speaker speech; and (3) the voice conversion quality of most models is unsatisfactory, and hence needs to be improved. Therefore, in this paper, we constructed a one-shot VC model of Representation Separation, called RS-VC model, implemented by the encoder-decoder structure. The encoder is composed of a content encoder and a speaker encoder. The content encoder separates the content information of the source speaker voice and generates a content representation. The speaker encoder separates the target speaker information of the target speaker voice and generates a speaker representation. The decoder synthesizes the content representation and the speaker representation to generate the converted voice. In this paper, we obtained the optimized speaker verification model SVIGEN2E (Speaker Verification with Instance Normalization using Generalized End-to-End loss) by improving the speaker verification (SV) model. The model SVIGEN2E is used as the speaker encoder. This speaker encoder needs to be trained in advance prior to RS-VC model training, and the pre-trained model of SVINGE2E directly extracts speaker representation of the target speaker’s voice, and is used for training and testing RS-VC model. A progressive training method is proposed then for training RS-VC model. Experiments show that the progressive training method can effectively improve the quality of the converted voice. Compared with the basic speaker verification model, both SVINGE2E and RS-VC deliver the impressive improvements in EER (Equal Error Rate).
Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients

Vital signs historically served as the primary method to triage patients and resources for trauma and emergency care, but have failed to provide clinically-meaningful predictive information about patient clinical status. In this review, a framework is presented that focuses on potential wearable sensor technologies that can harness necessary electronic physiological signal integration with a current state-of-the-art predictive machine-learning algorithm that provides early clinical assessment of hypovolemia status to impact patient outcome. The ability to study the physiology of hemorrhage using a human model of progressive central hypovolemia led to the development of a novel machine-learning algorithm known as the compensatory reserve measurement (CRM). Greater sensitivity, specificity, and diagnostic accuracy to detect hemorrhage and onset of decompensated shock has been demonstrated by the CRM when compared to all standard vital signs and hemodynamic variables. The development of CRM revealed that continuous measurements of changes in arterial waveform features represented the most integrated signal of physiological compensation for conditions of reduced systemic oxygen delivery. In this review, detailed analysis of sensor technologies that include photoplethysmography, tonometry, ultrasound-based blood pressure, and cardiogenic vibration are identified as potential candidates for harnessing arterial waveform analog features required for real-time calculation of CRM. The integration of wearable sensors with the CRM algorithm provides a potentially powerful medical monitoring advancement to save civilian and military lives in emergency medical settings.
Functionally Graded Scaffolds with Programmable Pore Size Distribution Based on Triply Periodic Minimal Surface Fabricated by Selective Laser Melting

Functional graded materials are gaining increasing attention in tissue engineering (TE) due to their superior mechanical properties and high biocompatibility. Triply periodic minimal surface (TPMS) has the capability to produce smooth surfaces and interconnectivity, which are very essential for bone scaffolds. To further enhance the versatility of TPMS, a parametric design method for functionally graded scaffold (FGS) with programmable pore size distribution is proposed in this study. Combining the relative density and unit cell size, the effect of design parameters on the pore size was also considered to effectively govern the distribution of pores in generating FGS. We made use of Gyroid to generate different types of FGS, which were then fabricated using selective laser melting (SLM), followed by investigation and comparison of their structural characteristics and mechanical properties. Their morphological features could be effectively controlled, indicating that TPMS was an effective way to achieve functional gradients which had bone-mimicking architectures. In terms of mechanical performance, the proposed FGS could achieve similar mechanical response under compression tests compared to the reference FGS with the same range of density gradient. The proposed method with control over pore size allows for effectively generating porous scaffolds with tailored properties which are potentially adopted in various fields.
Design of a special crawler crane for substation

The internal construction site of the substation is narrow, and it is usually necessary to temporarily dismantle and remove the electrical equipment to expand the scope of the power outage in the station, which affects the normal electrical equipment work and increases the maintenance workload. This paper designs a crawler crane for substation construction, which is aimed at the spatial structure layout of the substation and makes full use of the telescopic structure and remote infrared control method to reduce the occupied space and reduce the scope of power outages. It has both a lifting arm and a manned arm, realizing the multifunctional integration of manned and lifted objects. This crane breaks through the limitation of the single structure of the traditional spreader, and can temporarily replace a variety of spreaders for efficient lifting construction.
Antifungal Activity of Aromatic Plants of the Lamiaceae Family in Bread

The antifungal effect of aromatic plants (oregano, thyme, and Satureja) in dry form and as essential oils was evaluated in vitro (in potato dextrose agar (PDA)) and in bread against two phytopathogenic fungi found in food (Aspergillus niger and Penicillium). Gas and liquid chromatography were used to analyze essential oils attained by hydrodistillation of the aerial parts of the aromatic plants and of the dried plant aqueous solutions that were autoclaved for 20 min at 121 °C before analysis. Carvacrol, α-pinene, p-cymene, and γ-terpinene were the main components of the essential oils, whereas carvacrol, rosmarinic and caffeic acids were the main components of the water extracts. In vitro antifungal test results showed that the addition of plants in dry form had great antifungal potential against both fungal strains studied. Penicillium was more sensitive to the presence of aromatic plants than Aspergillus. Among the three plant species tested, thyme was the most potent antifungal against both fungi. For the bread product, all three aromatic plants studied showed inhibitory effects against both fungi. Results presented here suggest that oregano, thyme and Satureja incorporated in a bread recipe possess antimicrobial properties and are a potential source of antimicrobial ingredients for the food industry.
Clearance of human papillomavirus infection in patients with cervical intraepithelial neoplasia

Abstract Background: There are currently no available standard drugs treating human papillomavirus (HPV) infection, especially for patients with low-grade cervical lesion. Several therapies are explored but the results are inconclusive. The objective of this study was to evaluate the efficacy of reported non-invasive treatments in patients with HPV infection and cervical lesions by meta-analysis. Methods: A comprehensive search of prospective and randomized studies published from April 2000 to April 2020 was conducted in electronic databases. The statistical analyses of the pooled risk ratios (RRs) and the corresponding 95% confidence intervals (95% CIs) were performed using the Revman 5.2 software. Results: Twelve articles including 12 randomized controlled studies and 1 prospective controlled randomized pilot study were enrolled. Therapeutic medications included biological and herbal regimen, interferon regimen and probiotics. The meta-analysis showed the experimental treatments had a statistically significant improvement in HPV clearance rate compared with the controls (RR = 0.71, 95% CI [0.63, 0.80], P < .00001); subgroup analyses stratified by regimen categories were consistent with results in the overall group. Treatment using biological and herbal regimen, interferon regimen or probiotics also resulted in a beneficial outcome in regression rate of cervical lesions compared with the controls (RR = 0.55, 95% CI [0.39, 0.79], P = .001). The trend was more favorable in the probiotics than that in the biological and herbal regimen (RR 0.48 vs 0.72). Conclusion: Treatment of biological and herbal regimen, interferon regimen and probiotics benefit patients who have HPV infection and cervical lesions. Both the clearance of HPV and regression of cervical lesions are significant. More studies with less heterogeneity are needed to draw a concrete conclusion.
Genome-wide CRISPR screen identifies noncanonical NF-κB signaling as a regulator of density-dependent proliferation

Epithelial cells possess intrinsic mechanisms to maintain an appropriate cell density for normal tissue morphogenesis and homeostasis. Defects in such mechanisms likely contribute to hyperplasia and cancer initiation. To identify genes that regulate the density-dependent proliferation of murine mammary epithelial cells, we developed a fluorescence-activated cell sorting assay based on FUCCI, which marks different stages of the cell cycle with distinct fluorophores. Using this powerful assay, we performed a genome-wide CRISPR/Cas9 knockout screen, selecting for cells that proliferate normally at low density but continue to divide at high density. Unexpectedly, one top hit was Traf3, a negative regulator of NF-κB signaling that has never previously been linked to density-dependent proliferation. We demonstrate that loss of Traf3 specifically activates non-canonical NF-κB signaling. This in turn triggers an innate immune response and drives cell division independently of known density-dependent proliferation mechanisms, including YAP/TAZ signaling and cyclin kinase inhibitors, by blocking entry into quiescence.
Prevalence of anxiety disorders and subthreshold anxiety throughout later life: Systematic review and meta-analysis.

This systematic review and meta-analysis compared prevalence rates for subthreshold anxiety and anxiety disorders in adults aged 55+ and examined if these rates were associated with age. A systematic search and screening procedure resulted in 46 included articles. First, prevalence rates for subthreshold anxiety and anxiety disorders were statistically compared. Subthreshold panic, generalized anxiety and specific phobia were significantly more prevalent than the corresponding clinical disorders. In general, subthreshold anxiety appeared to be at least similarly prevalent to anxiety disorders, although firm conclusions are precluded due to the small number of samples that could be included in the analyses and the large heterogeneity between the reported prevalence rates. Second, using subgroup analyses, pooled prevalence rates for four age groups of older adults (55-64, 65-74, 75-84, 85+) were compared. For specific phobia, the 75-84 and 85+ groups had significantly lower prevalence rates than the 55-64 and 65-74 groups. Posttraumatic stress disorder was significantly more prevalent in the 55-64 group than in the other age groups, and lowest in the 85+ group. No other significant differences between age groups were found. The association between later life subthreshold anxiety and age could not be examined due to a lack of reported information. The main limitation of this study is the small number of samples in the analyses, which limits their power and generalizability. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Synergistic Effects and Sex Differences in Anthropometric Measures of Obesity and Elevated High-Sensitivity C-Reactive Protein Levels

Background: It remains unclear which anthropometric measure best predicts elevated high-sensitivity C-reactive protein (hs-CRP) levels. This study investigated the association and synergistic interaction of two obesity indices with elevated hs-CRP levels in a national sample of Korean adults, stratified by sex. Methods: The present cross-sectional study used data from the 2015–2018 Korea National Health and Nutrition Examination Survey of 18,610 subjects aged ≥20 years after excluding those with missing variables. Multiple logistic regression analyses and chi-squared tests were performed to investigate the association between body mass index (BMI) and waist circumference (WC) with elevated hs-CRP levels. Interaction analysis was used to examine the synergistic effect between BMI and WC on the risk of having elevated hs-CRP levels. Results: Elevated hs-CRP levels exceeding 3 mg/L were present in 9.3% and 7.5% of men and women, respectively. The relationship between each obesity index and elevated hs-CRP levels was significant in women (high WC (odds ratio [OR] = 1.77, 95% confidence interval [CI] = 1.24–2.54), high BMI (OR = 2.08, 95% CI = 1.58–2.74)) but not in men (high WC (OR = 1.19, 95% CI = 0.86–1.64), high BMI (OR = 0.99, 95% CI = 0.77–1.29)). Furthermore, combined measures of the two obesity indices and interaction analysis results revealed a synergistic association in men (OR = 1.57, 95% CI = 1.33–1.85; relative excess risk due to interaction (RERI) = 0.39, 95% CI = −0.09–0.86), and women (OR = 3.70, 95% CI = 3.09–4.43; RERI = 0.85, 95% CI = −0.06–1.75). Conclusion: BMI and WC were significantly associated with a risk of elevated hs-CRP levels in women but not in men. Nevertheless, significant synergistic interactions were seen in combined measures of BMI and WC, regardless of sex. These findings emphasize the need to use both measures of adiposity concurrently in the assessment of obesity and when identifying cardiovascular risk.
Automatic recognition of arrhythmia using a CNN-based broad learning system

An accurate electrocardiogram (ECG) beat classification can benefit the diagnosis of the cardiovascular disease. Currently, automatic ECG classification systems based on deep neural network are useful in the field of ECG recognition. However, most of them are time-consuming in training, less robustness to noise, and need to retrain the entire model when new data are added. To address these problems, we propose an ECG classification algorithm by using a CNN-based broad learning system (CNNBLS) for recognition of arrhythmia. We performed two experiments to evaluate the robustness and incremental learning features of the proposed classification system. In noise robustness experiment, we selected five types of original and denoising abnormal ECGs in the MIT-BIH arrhythmia database, and overall accuracy of the five arrhythmia classifications achieved 98.5% and 98%. In incremental learning experiment, we selected 6 types of abnormal ECGs data in the MIT-BIH arrhythmia database. The accuracy and training time before incremental learning were 97.94% and 21.61 s, and the accuracy and training time after incremental learning with additional 12929 new data were 98.45% and 47.23 s. Experimental results show that our model is a practical ECG recognition method with suitable noise robustness and has superiority in training time while the accuracy is guaranteed.
Time-course analysis reveals that corticosteroids resuscitate diminished CD8+ T cells in COVID-19: a retrospective cohort study

Abstract Objective To illustrate the effect of corticosteroids and heparin, respectively, on coronavirus disease 2019 (COVID-19) patients’ CD8+ T cells and D-dimer. Methods In this retrospective cohort study involving 866 participants diagnosed with COVID-19, patients were grouped by severity. Generalized additive models were established to explore the time-course association of representative parameters of coagulation, inflammation and immunity. Segmented regression was performed to examine the influence of corticosteroids and heparin upon CD8+ T cell and D-dimer, respectively. Results There were 541 moderate, 169 severe and 156 critically ill patients involved in the study. Synchronous changes of levels of NLR, D-dimer and CD8+ T cell in critically ill patients were observed. Administration of methylprednisolone before 14 DFS compared with those after 14 DFS (β = 0.154%, 95% CI=(0, 0.302), p=. 048) or a dose lower than 40 mg per day compared with those equals to 40 mg per day (β = 0.163%, 95% CI=(0.027, 0.295), p=. 020) significantly increased the rising rate of CD8+ T cell in 14–56 DFS. Conclusions The parameters of coagulation, inflammation and immunity were longitudinally correlated, and an early low-dose corticosteroid treatment accelerated the regaining of CD8+ T cell to help battle against SARS-Cov-2 in critical cases of COVID-19.
Carcinogenesis as Side Effects of Iron and Oxygen Utilization: From the Unveiled Truth toward Ultimate Bioengineering

Simple Summary Cancer is a major cause of human mortality worldwide. No life on earth can live without iron. Persistent oxidative stress resulting from continuous use of iron and oxygen may be a fundamental cause of carcinogenesis. Many animal models demonstrated that excess iron may lead to carcinogenesis. This is supported by a variety of human epidemiological data on cancer risk and prognosis. Cancer is basically a disease of the genome with persistently activated oncogenes and inactivated tumor suppressor genes through which iron addiction with ferroptosis-resistance is established. We predict that fine use of nanomaterials and non-thermal plasma may be able to reverse this situation. Abstract Evolution from the first life on earth to humans took ~3.8 billion years. During the time there have been countless struggles among the species. Mycobacterium tuberculosis was the last major uncontrollable species against the human public health worldwide. After the victory with antibiotics, cancer has become the leading cause of death since 1981 in Japan. Considering that life inevitably depends on ceaseless electron transfers through iron and oxygen, we believe that carcinogenesis is intrinsically unavoidable side effects of using iron and oxygen. Many animal models unequivocally revealed that excess iron is a risk for carcinogenesis. This is supported by a variety of human epidemiological data on cancer risk and prognosis. Cancer is basically a disease of the genome with persistently activated oncogenes and inactivated tumor suppressor genes through which iron addiction with ferroptosis-resistance is maintained. Engineering has made a great advance in the past 50 years. In particular, nanotechnology is distinct in that the size of the engineered molecules is similar to that of our biomolecules. While some nano-molecules are found carcinogenic, there are principles to avoid such carcinogenicity with a smart possibility to use nano-molecules to specifically kill cancer cells. Non-thermal plasma is another modality to fight against cancer.