Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Bearing-Fault Classification Method Based on Deep Learning*

Bearing fault signal detection plays a vital role in the industrial field, which directly affects the performance and safety of mechanical equipment. The application of CNN (convolutional neural network) for fault signal detection is an emerging method, but this method does not work well on one-dimensional data such as bearing fault signals, mainly because the features of the one-dimensional signal are not distinct compared to the image signal. Secondly, due to the limitation of the special situation, the data of the bearing signal is less, which makes it hard for the deep learning model to fit and converge well. To solve the above problems, this paper proposes a CNN based on improved softmax-loss (ISM-CNN). The constructed CNN can learn more subtle features from the bearing signals, thereby improving the accuracy of bearing signal classification. Besides, the algorithm proposed in this paper expands the training data set to a certain extent, so that the parameters of the ISM-CNN can be better fitted. We validate the effectiveness of the proposed algorithm on the CWRU open dataset and give ablation experiments to prove it. In the 97-category complex bearing signal generation scenario, the proposed algorithm achieves 95% accuracy.
Association between the FABP2 Ala54Thr and CRP+1059C/G polymorphisms and small dense LDL level in patients with atherosclerosis: a case–control study

Abstract Background The polymorphisms of fatty acid-binding protein 2 (FABP2) and C-reactive protein (CRP) might act as genetic risk factors for atherosclerosis. The study aimed to investigate the relationship between FABP2 Ala54Thr and CRP+1059C/G polymorphisms and atherosclerosis as well as the association of Small dense-LDL (sd-LDL). Methods A total of 255 subjects (125 controls and 130 patients) were included. The FABP2 and CRP polymorphisms were determined by PCR-RFLP and AS-PCR methods, respectively. Sd-LDL was measured based on Hirano et al method. Results There were no significant distinctions between the patient and control groups concerning FABP2 and CRP polymorphisms (p > .05). No significant relationship was observed between studied polymorphisms and sd-LDL level in the patient group (p > .05). However, patients group had higher level of sd-LDL compared to controls (p < .05). Conclusion FABP2 Ala54Thr and CRP+1059G/C polymorphisms were not associated with atherosclerosis and sd-LDL level. However, the increased sd-LDL level was known as a risk factor for atherosclerosis.
GROWTH RATE, BODY SIZE, SEXUAL DIMORPHISM AND MORPHOMETRIC VARIATION IN FOUR POPULATIONS OF PAINTED TURTLES (CHRYSEMYS PICTA BELLII) FROM NEBRASKA

-I studied variation in individual growth rate, body size, sexual size dimorphism and morphometry in two sandhill lake and two Platte River floodplain populations of painted turtles from western Nebraska. Individual growth rate of juveniles and mean adult body size were greater in the sandhills populations than in the floodplain populations. Comparisons of mean individual growth rates of juveniles reported here and mean population egg size reported for these populations in an earlier study support predictions for the evolution of offspring size. Females were larger than males and sexual dimorphism was greatest in populations with relatively slow individual growth rates, a pattern that is inconsistent with the findings for other local populations of painted and closely related slider turtles. Body sizeadjusted carapace width, shell height and plastron length varied significantly within and between sexes and populations. Interpopulational variation in shell width and height are hypothesized to be related to variation in clutch frequency or to differences in hydrodynamics between lake and riverine systems.
Control of gummy stem blight in watermelon through different management systems = Controle da podridão gomosa em melancia através de diferentes sistemas de manejo

Gummy stem blight, caused by Didymella bryoniae (Auersw.) Rehn, is a disease that affects the productivity of watermelon leading to losses exceeding 40%. This study aimed at evaluating the efficiency of different production systems in the control of watermelon gummy stem blight in order to establish effective methods to combat the disease. The following treatments were applied: conventional management, integrated management and organic production. Mineral fertilizer was applied to conventional and integrated management, whereas in organic production was used the cattle manure. There was application of fungicides and insecticides in commercial doses in conventional and integrated management, and the application was according to monitoring in integrated management. No fungicide or insecticide was applied to organic production. The disease severity was assessed by rating scale. The experimental design was randomized blocks. The severity of gummy stem blight increased substantially during fruit formation. Watermelon plants grown with integrated management showed lower levels of disease severity, while plants in organic production exhibited higher severity levels. We conclude that the management based on judicious monitoring in field is the best way to attain appropriate phytosanitary quality for the watermelon crop in Tocantins State, Brazil.
A Systematic Literature Review of Machine Learning-Based Disease Profiling and Personalized Treatment

To analyze the state of the art of machine learning-based disease profiling and personalized treatments, we review the relevant literature included in top peer-reviewed journals and evaluate the coverage according to the ICD-11 framework. We identify advantages, but also research needs and limitations within the ICD-11 disease categories to foster the adaptation of these new E-health technologies.
MXenes-Based Bioanalytical Sensors: Design, Characterization, and Applications

MXenes are recently developed 2D layered nanomaterials that provide unique capabilities for bioanalytical applications. These include high metallic conductivity, large surface area, hydrophilicity, high ion transport properties, low diffusion barrier, biocompatibility, and ease of surface functionalization. MXenes are composed of transition metal carbides, nitrides, or carbonitrides and have a general formula Mn+1Xn, where M is an early transition metal while X is carbon and/or nitrogen. Due to their unique features, MXenes have attracted significant attention in fields such as clean energy production, electronics, fuel cells, supercapacitors, and catalysis. Their composition and layered structure make MXenes attractive for biosensing applications. The high conductivity allows these materials to be used in the design of electrochemical biosensors and the multilayered configuration makes them an efficient immobilization matrix for the retention of activity of the immobilized biomolecules. These properties are applicable to many biosensing systems and applications. This review describes the progress made on the use and application of MXenes in the development of electrochemical and optical biosensors and highlights future needs and opportunities in this field. In particular, opportunities for developing wearable sensors and systems with integrated biomolecule recognition are highlighted.
Trabecular bone in domestic dogs and wolves: Implications for understanding human self‐domestication

The process of domestication is complex and results in significant morphological, cognitive, and physiological changes. In canids, some of the traits indicative of domestication of domestic dogs compared to their wild counterparts the wolves are prosociality toward humans, reduced stress hormone levels, and reduced cranial capacity. Research suggests that selection for prosociality among dogs resulted in morphological changes such as reduction in cranial capacity, juvenilization of the face, and overall gracile morphology. Interestingly, similar features have been described in modern humans compared to extinct species of Homo, for example, Neanderthals. Therefore, the human self‐domestication hypothesis has been proposed to partially explain the gracile modern human skeleton. Specifically, that as modern humans settled in communities, there was increased selection for prosociality (intergroup cooperation); and one of the by‐products of this selection was the evolution of a gracile skeleton, including a slight reduction in cranial capacity, reduced brow ridge and tooth size, and low trabecular bone fraction (TBF). However, TBF variation has not been tested between domestic dogs and wolves, who underwent self‐domestication. Thus, this study tests the hypothesis that dogs have low TBF as a consequence of domestication compared to their wild counterparts, the wolves, by comparing TBF in the hindlimbs—proximal femur and distal tibia‐ of the two species. Wilcoxon rank sum tests show that dogs have lower TBF values than wolves in both elements. These preliminary results add to the literature documenting changes in self‐domesticated species and provide a potential analog to further the understanding of self‐domestication.
Chromothripsis in Human Breast Cancer

These findings identify chromothripsis as a major driving event in human breast cancer. Chromothripsis is a form of genome instability by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosomes. Widely assumed to be an early event in tumor development, this phenomenon plays a prominent role in tumor onset. In this study, an analysis of chromothripsis in 252 human breast cancers from two patient cohorts (149 metastatic breast cancers, 63 untreated primary tumors, 29 local relapses, and 11 longitudinal pairs) using whole-genome and whole-exome sequencing reveals that chromothripsis affects a substantial proportion of human breast cancers, with a prevalence over 60% in a cohort of metastatic cases and 25% in a cohort comprising predominantly luminal breast cancers. In the vast majority of cases, multiple chromosomes per tumor were affected, with most chromothriptic events on chromosomes 11 and 17 including, among other significantly altered drivers, CCND1, ERBB2, CDK12, and BRCA1. Importantly, chromothripsis generated recurrent fusions that drove tumor development. Chromothripsis-related rearrangements were linked with univocal mutational signatures, with clusters of point mutations due to kataegis in close proximity to the genomic breakpoints and with the activation of specific signaling pathways. Analyzing the temporal order of events in tumors with and without chromothripsis as well as longitudinal analysis of chromothriptic patterns in tumor pairs offered important insights into the role of chromothriptic chromosomes in tumor evolution. Significance: These findings identify chromothripsis as a major driving event in human breast cancer.
Novice Designers meet Visual Analogy: distance-aware thinking and behaviors

This paper investigates how design processes are influenced by visual analogy when designers refer to visual elements with different distances. It is found that when facing long-distance visual elements designers concerns more on external shapes. During design thinking, those designers prefer to pay more attention on connecting visual elements with design objectives and they usually focus on designing micro details instead of outputting new design concepts. Therefore, during practical design processes, the designers are able to establish a connection of the design targets and design elements with proper distances.
Physical Modeling of p-Type Fluorinated Al-Doped Tin-Oxide Thin Film Transistors

Fabrication, physical modeling and dynamic response of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-type Al-doped SnO<sub><italic>x</italic></sub> active channel thin film transistors (TFTs) are presented for the potential application of ultra-high definition (UHD) displays. After deposition of Al-doped SnO<sub><italic>x</italic></sub> active layer using reactive co-sputtering, the channel was treated with plasma fluorination which improve the device performance of high <inline-formula> <tex-math notation="LaTeX">$I_{ON}/I_{OFF}$ </tex-math></inline-formula> ratio of > 10<sup>6</sup>, low subthreshold swing of ~100 mV/dec and high field-effect mobility (<inline-formula> <tex-math notation="LaTeX">$\mu _{FE}$ </tex-math></inline-formula>) of 4.8 <inline-formula> <tex-math notation="LaTeX">$cm^{2}V^{-1}s^{-1}$ </tex-math></inline-formula>. To understand the origin of such high performance, physical modeling and numerical simulations were performed using density of state (DOS) model of defects/traps of oxide semiconductor. This model describes the modifications of donor-like tail states and acceptor-like Gaussian defect states due to Al doping on SnO<sub><italic>x</italic></sub> and fluorine treatment. To evaluate the device performance for UHD large scale displays, the dynamic responses of <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-type TFT pixel circuit for various requirements are simulated with physical models. These results suggest that the Al-doped SnO<sub><italic>x</italic></sub> TFTs are potential candidates for future high-definition displays and many applications in transparent electronics.
A Novel Detection and Recognition Method for Continuous Hand Gesture Using FMCW Radar

In this article, a novel method for continuous hand gesture detection and recognition is proposed based on a frequency modulated continuous wave (FMCW) radar. Firstly, we adopt the 2-Dimensional Fast Fourier Transform (2D-FFT) to estimate the range and Doppler parameters of the hand gesture raw data, and construct the range-time map (RTM) and Doppler-time map (DTM). Meanwhile, we apply the Multiple Signal Classification (MUSIC) algorithm to calculate the angle and construct the angle-time map (ATM). Secondly, a hand gesture detection method is proposed to segment the continuous hand gestures using a decision threshold. Thirdly, the central time-frequency trajectory of each hand gesture spectrogram is clustered using the $k$ -means algorithm, and then the Fusion Dynamic Time Warping (FDTW) algorithm is presented to recognize the hand gestures. Finally, experiments show that the accuracy of the proposed hand gesture detection method can reach 96.17%. The hand gesture average recognition accuracy of the proposed FDTW algorithm is 95.83%, while its time complexity is reduced by more than 50%.
Mental health of frontline healthcare workers exposed to COVID-19 in Egypt: A call for action

Background: World Health Organization (WHO) declared Coronavirus disease 2019 (COVID-19) as a pandemic in March 2020. Such widespread outbreaks are associated with adverse mental health consequences. Aims: To evaluate mental health outcomes among Egyptian healthcare workers (HCW) treating patients with confirmed or suspected Coronavirus Disease 2019 (COVID-19) to direct the promotion of mental wellbeing, by screening for symptoms of anxiety, insomnia, depression and stress, and analyzing potential risk factors. Methods: This cross-sectional, hospital-based survey study collected demographic data and mental health measurements from 502 HCW dealing with COVID-19. HCW were surveyed in 20 hospitals (Fever, Chest, and Quarantine hospitals) in different parts of Egypt, in April and May 2020. Results: Among the 502 HCW surveyed; 60.0% were physicians, 16.1% were specialized nurses, and 23.9% were non-specialized nurses. About 35.3% worked in chest hospitals, 17.5% in fever hospitals, and 47.2% in quarantine hospitals. A considerable proportion of HCW had symptoms of anxiety, insomnia, depression, and stress. Females were at higher risk of experiencing symptoms of severe anxiety (odds ratio [OR], 1.85; 95% CI, 1.12–3.05; p = .016), severe depression (OR, 2.013; 95% CI, 1.17–3.4; p = .011), and severe stress (OR, 2.68; 95% CI, 1.5–4.6; p < .001). Fever hospital workers were at higher risk of severe depression (OR, 1.52; 95% CI, 1.11–2.09; p < .01), compared to Quarantine hospital workers. Conclusion: Ensuring proper mental health support for HCW is an important component of public health measures for addressing the COVID-19 epidemic and safeguarding the continuity of appropriate medical service.
Load-Aware and Mobility-Aware Flow Rules Management in Software Defined Vehicular Access Networks

To ensure high performance for vehicular access networks, Software Defined Networking (SDN) technology is an efficient solution offering programmability, flexibility and a centralized view of the network. Nevertheless, to guarantee an efficient mobility management, some improvements are needed. In particular, a limitation on the number of exchanges between SDN controller and network devices and a better flow tables’ management are required. To achieve that, the ideas of flow rules’ pre-deployment and mobility-aware management of flow rules’ lifetime have been proposed. However, existing approaches have two major limitations: accuracy and adaptability. Indeed, network load (accuracy) and network devices’ feedbacks (adaptability) are not considered, two factors impacting flow rules management. That is why, in this paper, we define a state-based approach using connection/disconnection information reported by network devices to improve adaptability. Moreover, we propose a mobility-aware and load-aware flow rules management to improve accuracy. Finally, we specify a new flow rules’ pre-deployment policy based on flow tables occupancy rate, vehicles mobility and SDN control channel load. The evaluations carried out confirm the benefits of the approach, compared to existing solutions, both in terms of recovery delay, control overhead, hard timeout calculation and flow table occupancy.
Effects of Human Disturbance on the Breeding Success of Gulls

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Efficient sensory coding of multidimensional stimuli

According to the efficient coding hypothesis, sensory systems are adapted to maximize their ability to encode information about the environment. Sensory neurons play a key role in encoding by selectively modulating their firing rate for a subset of all possible stimuli. This pattern of modulation is often summarized via a tuning curve. The optimally efficient distribution of tuning curves has been calculated in variety of ways for one-dimensional (1-D) stimuli. However, many sensory neurons encode multiple stimulus dimensions simultaneously. It remains unclear how applicable existing models of 1-D tuning curves are for neurons tuned across multiple dimensions. We describe a mathematical generalization that builds on prior work in 1-D to predict optimally efficient multidimensional tuning curves. Our results have implications for interpreting observed properties of neuronal populations. For example, our results suggest that not all tuning curve attributes (such as gain and bandwidth) are equally useful for evaluating the encoding efficiency of a population.
Violence against older women: A systematic review of qualitative literature

The majority of the existing evidence-base on violence against women focuses on women of reproductive age (15–49), and globally there is sparse evidence concerning patterns of and types of violence against women aged 50 and older. Improved understanding of differing patterns and dynamics of violence older women experienced is needed to ensure appropriate policy or programmatic responses. To address these gaps in the evidence, we conducted a systematic review of qualitative literature on violence against older women, including any form of violence against women, rather than adopting a specific theoretical framework on what types of violence or perpetrators should be included from the outset, and focusing specifically on qualitative studies, to explore the nature and dynamics of violence against older women from the perspective of women. Following pre-planned searches of 11 electronic databases, two authors screened all identified titles, abstracts and relevant full texts for inclusion in the review. We extracted data from 52 manuscripts identified for inclusion, and conducted quality assessment and thematic synthesis from the key findings of the included studies. Results indicated that the vast majority of included studies were conducted in high-income contexts, and did not contain adequate information on study setting and context. Thematic synthesis identified several central themes, including the intersection between ageing and perceptions of, experiences of and response to violence; the centrality of social and gender norms in shaping older women’s experiences of violence; the cumulative physical and mental health impact of exposure to lifelong violence, and that specific barriers exist for older women accessing community supports and health services to address violence victimization. Our findings indicated that violence against older women is prevalent and has significant impacts on physical and mental well-being of older women. Implications for policy and programmatic response, as well as future research directions, are highlighted.
Energy-Aware Cross-Layer Offloading in Fog-RANs Using Network Coded Device Cooperation

This paper studies a Fog Radio Access Network (F-RAN) architecture that utilises the increasing storage and device-to-device communication capacities of users’ smart devices (referred to as F-UEs) in order to reduce the time that the central processing unit (referred to as BBU) has to spend to serve these F-UEs and thus, increases the system’s capacity. Indeed, these F-UEs can employ these capacities in cooperatively serving each other’s file requests, as long as the F-UEs have the files in their storage, rather than always receiving them through the BBU. In addition, network coding (NC) can be employed to minimize the communications among the F-UEs and from the BBU to further offload the BBU resources and reduce the energy consumed in F-UEs’ cooperation. This paper develops an algorithm for scheduling the file encoding and transmissions both among half-duplex F-UEs and from the BBU to minimise the consumed time-frequency resources from the BBU given constraints on the energy consumed by each F-UE for their cooperation to help preserve their battery life. The influence of the energy constraint on BBU offloading is investigated and the performance of the system under a variety of settings is evaluated through extensive simulations. The benefit of using NC is shown and the ability of the F-UEs to transmit with different power levels is also studied and shown to considerably impact the number of cooperating F-UEs and the BBU offloading.