Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning features for action recognition and identity with deep belief networks

Feature extraction is a crucial part of computer vision. In this paper, we present a novel method that can automatically extract relevant features from video for action recognition and identity of human who makes the action, in single framework. We propose a watermark embedding in a video to represent a human identity as a 2-D wavelet transform. The feature extraction consists of a Deep Belief Network (DBN) on Discrete Fourier Transforms (DFTs) of the tracked features in a video. We then use the activations of the trained network as inputs for a non-linear Support Vector Machine (SVM) classifier. In particular, the learned features are used to solve the task of action recognition and identity. The method significantly reduces computational cost without scarifying any recognition accuracy. We test our algorithm on the KTH human motion dataset. Our results reflect the promise of our approach. Moreover, we obtain high classification accuracy on the KTH dataset that compares favorably against state-of-the-art action classifiers using hand-designed features.
Workplace Exposures and the Risk of Amyotrophic Lateral Sclerosis

Background Occupation has been suggested to play a role in amyotrophic lateral sclerosis (ALS) etiology, but detailed information on the importance of specific workplace exposures is lacking. Objectives Our aim was to assess the relationship between workplace exposures and the risk of ALS and to evaluate potential interactions between these exposures and smoking. Methods We conducted a case–control study in New England between 1993 and 1996, comprising 109 cases and 253 controls who completed a structured interview covering occupations and workplace exposures. Unconditional logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for ALS. Analyses were conducted among the entire study population and after stratification by smoking. Results We observed a higher risk of ALS for construction workers excluding supervisors (OR = 2.9; 95% CI, 1.2–7.2) and precision metal workers (OR = 3.5; 95% CI, 1.2–10.5). Self-reported exposures to paint strippers; cutting, cooling, or lubricating oils; antifreeze or coolants; mineral or white spirits; and dry cleaning agents each appeared to be associated with a 60–90% higher risk. Specific chemicals related to a > 50% increase in risk of ALS included aliphatic chlorinated hydrocarbons, glycols, glycol ethers, and hexane. Relative risks associated with these workplace exposures and chemicals were greater among nonsmokers and persisted in mutually adjusted models. Conclusions Our data suggest that certain occupations and workplace exposures may be associated with increased risk of ALS. These results need to be confirmed in independent populations.
Effect of Potassium and Calcium Application on Yield, Yield Components and Qualitative Characteristics of Peanut (Arachis hypogaea L.) In Guilan Province, Iran

3 Abstract: In order to investigate the effect of calcium and potassium application on yield and yield components of peanut (Arachis hypogaea L.) in 2009 an experiment was conducted in factorial arrangement as a randomized complete block design with three replications in kyashahr port located at the eastern of Guilan, Iran. Two factors were used in this study including potassium rates in 4 levels (0, 30, 60 and 90 kg/h from potassium sulfate) and calcium rates in 4 levels (0, 30, 60 and 90 kg/h from gypsum). Results showed that the application of calcium had significant effect on pod yield, kernel yield and oil content, So that applying of 90 kg.h calcium form gypsum 1 performed considerably better than the rest. But applying of these fertilizers had no significant effect on protein content of peanut kernel. The yield of pod and kernel also increased with increasing of calcium application along with potassium. The highest yield of pod (5650 kg.h ) and kernel (4622kg.h ) were obtained form 90kg 11 calcium form gypsum. The highest oil content (46.22%) was obtained in 90 kg calcium and 30 kg potassium (interaction effect). According to the results of the present study it could be said that the efficient application of fertilizers, especially potassium along with essential elements such as calcium and sulfur is an important factor for increasing of growth and yield of peanut. Therefore, consideration of suitable proportion of calcium and potassium can have acceptable yield of peanut.
Self Disclosure of Aceh Facebook-Addicted Users

Facebook is the most prominent social media platforms offering various attractive and captivated features. It is common to observe its users become addicted and incessantly spend an excessive amount of their time on this site. Like other addictions, Facebook addiction also has negative consequences on daily lives of its users and it often affects their face-to-face communication. This study aims to investigate the influence of Facebook addiction towards self-disclosure as the key determiner in the interpersonal communication. It used a descriptive quantitative method using a cross-sectional survey of 122 university students selected by quota sampling technique. The data were analyzed with independent sample t-test using the SPSS version 22 software to examine the difference of selfdisclosure between high and low Facebook addicted groups. Findings reveal that the users with high level of Facebook addictions are more likely to have low self-disclosure than those with the low level of Facebook addictions. Keywords— self-disclosure; Facebook; addiction; social media; face-to-face communication
Influenza pneumonia: a descriptive study.

OBJECTIVE To describe the clinical features and complications of patients hospitalized with influenza during the 1999-2000 influenza season. METHODS We reviewed all cases of patients with influenza admitted to a large metropolitan referral hospital during the 1999-2000 season. RESULTS Thirty-five adult patients (15 men and 20 women) tested positive for influenza A by direct enzyme immunoassay. A fourfold to sevenfold increase in the number of influenza cases was observed over previous years. Most patients had serious comorbid illnesses (88%), such as diabetes and chronic respiratory and heart disease. Seventeen patients developed pneumonia; these patients tended to be older (mean +/- SD, 63 +/- 13 years vs 51 +/- 19 years, respectively; p = 0.04) and had a higher incidence of chronic lung disease (41% vs 6%, respectively; p = 0.02) than the patients without pneumonia. Shortness of breath was the only symptom that distinguished patients with pneumonia from those with an upper respiratory tract illness alone. Antiviral treatment was begun 4 +/- 3 days from initiation of symptoms in patients with pneumonia and consisted of oseltamivir (35.2%), rimantadine (5.8%), or a combination of both (17.6%). Respiratory and/or blood culture results were positive in five patients (29%), Staphylococcus aureus was isolated in five patients, and Streptococcus pneumoniae was isolated in one patient. Ten of the patients with pneumonia (58.8%) were admitted to the ICU, and 5 patients (29%) died. The length of ICU stay and mechanical ventilation were 28 +/- 26 days and 21.5 +/- 20.5 days, respectively. Death in most pneumonia patients was attributed to respiratory failure. CONCLUSION The recognized number of hospital admissions for influenza increased fourfold to sevenfold over previous years, most likely due to the implementation of rapid diagnostic tests for influenza. Patients with signs and symptoms of influenza and shortness of breath should undergo chest radiography. Hospitalization of patients with influenza pneumonia occurred in both previously healthy and immunocompromised patients and had a high mortality. S aureus was the most common bacterial isolate in patients with influenza pneumonia. Empiric antibiotics with staphylococcal activity should be used pending culture results in patients with influenza pneumonia. The effectiveness of oseltamivir and rimantadine in treating patients with influenza pneumonia remains to be determined.
Weyl-type hybrid subconvexity bounds for twisted $L$-functions and Heegner points on shrinking sets

We prove a Weyl-type subconvexity bound for the central value of the $L$-function of a Hecke-Maass form or a holomorphic Hecke eigenform twisted by a quadratic Dirichlet character, uniform in the archimedean parameter as well as the twisting parameter. A similar hybrid bound holds for quadratic Dirichlet $L$-functions, improving on a result of Heath-Brown. As a consequence of these new bounds, we obtain explicit estimates for the number of Heegner points of large odd discriminant in shrinking sets.
Successive Interference Cancellation Detection for Multicode STBC-MIMO Systems

Space-time block coded (STBC) multiple-input- multiple-output (MIMO) systems in conjunction with orthogonal frequency division multiplexing (OFDM) and multicode spread spectrum techniques can provide flexibility in the diversity-multiplexing gain tradeoff. It is worth noting that multicode operation can provide additional degrees of freedom in the code domain to achieve high data rates. Furthermore, we propose in this paper a parallel arbitrated successive interference cancellation (PASIC) scheme, which utilize a certain number of conventional SIC detectors with different ordering sequences in parallel and then combines the soft output of each individual SIC to achieve performance gains. Simulation results show the proposed approach can achieve a bit error rate (BER) performance that is very close to the optimal maximum-likelihood (ML) decoding. However, the complexity of this approach is linear with the number of SIC components.
MENTAL HEALTH LITERACY OF SCHOOL-AGED CHILDREN IN LAMPANG PROVINCE

Background: Mental health literacy (MHL) is associated with the likelihood of sustaining mental health illness, and an ability to prevent and reduce the severity of mental health problems. School-age children experience physical and cognitive changes which can affect their psychological wellbeing. Promoting mental health literacy among school-age children is therefore important in order to promote psychological wellbeing and prevent mental health problems. Objective: To describe mental health literacy among school- age children in Lampang province and to compare mental health literacy between children live with their biological parents and children living with other people. Methods: The sample consisted of 406 primary school students aged 10-12 years old in Lampang province. The study took place between January-March 2017. The instrument was self-rating mental health literacy consisting of three domains: mental health knowledge, mental health attitude, and mental health efficacy. Descriptive statistics and independent t-test were used for data analysis. Results: Mental health literacy among school-age children in Lampang province was at a moderate level. With regards to individual domains, mental health knowledge, mental health attitude, and mental health efficacy were at a moderate overall mental health literacy between children living with parents and those living with others. Conclusion and Recommendations: The results of this study which revealed moderate level of mental health literacy among school-aged children warrant educational interventions to promote mental health literacy among this population. These interventions may target the children, parents and teachers.
Sensory supernatural experiences in autism

ABSTRACT This study examines attribution of supernatural agency in 17 Swedish, high functioning young adults on the autism spectrum, who describe sensing presence, feeling touch, and seeing visions without input of somatosensory stimuli. These participants report many more such incidents than the matched, non-autistic group participants, and current research suggests that unusual somatosensory experiences are prevalent in the autistic population. Attribution of invisible agency is understood as a sense-making coping strategy, and it is argued that esoteric content in fantasy literature, movies and computer games explain why these young adults prefer to attribute agency to ghosts, spirits and demons, rather than god(s). The study thereby extends and challenges the study of autism and religiosity by exploring the intersection between autistic embodiment and encultured cognition.
Data Security and Privacy Issues in Swarms of Drones

The unmanned aerial technology is being a major part in several industries such as the military, the emergency response units, and the space exploration, but these fields are targets of some critical data breaches and attacks. Due to the importance and the sensitivity of the data that are transferring through the swarms, the security aspects should be at the highest level. The paper concentrates on analyzing the privacy and the security aspects in swarms of drones and develops new approaches to address the future data security challenges. The primary objective of the research is to develop new approaches in order to enhance the privacy-preservation of the swarms of drones. We compare the two main approaches which are the data aggregation and the seL4 OS in details. The secure data aggregation method is implemented and its effectiveness is evaluated. We implement this method in the swarms of the drone to enhance the data security. In addition to the data aggregation method, the paper also discussed how the seL4 kernel would be employed in the drones.
Competitive factors of electronic dance music festivals with Social Networking Service (SNS) citizenship behaviour of international tourists

This study examined the comparative advantages of prestige service labelling (VIP), online marketing, and image differentiation when applied as marketing strategies to build tourist loyalty as a component of citizenship behaviour. The participants were 220 African tourists attending the World Club Dome Korea 2017 festival event. Following data collection, we conducted a hierarchical regression analysis to determine how VIP, online marketing, and image differentiation influenced tourist social networking service (SNS) citizenship behaviour. The results suggest that VIP and image differentiation to positively predict SNS citizenship behaviour, whereas this was not the case for online marketing. VIP had a higher influence on tourist SNS citizenship behaviour than image differentiation. In summary, strategies to attract tourists with high purchasing power should include prestige service branding with clear image differentiation. This exclusivity could be applied to online ticketing services for their added value to tourism promotion.
Proceedings of the International Conference The Communication of Certainty and Uncertainty: Linguistic, Psychological, Philosophical Aspects

Koestler’s bisociation theory (1964) has been taken into account as the cognitive framework focusing on the ability to make inferences in humor production. Though high elaborative inferences are considered as a ‘valueadded’, it happens that verbal humor is also recognized when it appears as lacking of meaning. Actually, humor is present in everyday conversations, but sometimes it is not assured (i.e. certain) how to detect any humorous gist, especially for outsiders. Through a qualitative analysis, verbal humor in conversation has been explored to highlight its most and less certain aspects. The main purpose of this paper is to point out clues for fun recognition and appreciation in various forms of verbal humor, where the inferential dynamics shifts towards different functions.
Occupancy detection via iBeacon on Android devices for smart building management

Building heating, ventilation, and air conditioning (HVAC) systems are considered to be the main target for energy reduction due to their significant contribution to commercial buildings' energy consumption. Knowing a building's occupancy plays a crucial role in implementing demand-response HVAC. In this paper we propose a new solution based on the iBeacon technology. This solution is different from the previous ones because it leverages on the Bluetooth Low Energy standard, which provides lower power consumption. Moreover, the iBeacon protocol can be used both on iOs systems and Android ones, making this new approach portable. Differently from our previous work based on iOS devices, in this paper we focus on an Android based solution with the aim of increasing the accuracy of the location and the energy efficiency of the entire system. We increased the accuracy by 10% and the energy efficiency by 15%.
Tumor-Infiltrating Immune Cells Are Associated With Prognosis of Gastric Cancer

AbstractImmune cells contribute to determining the prognosis of gastric cancer. However, their exact role is less clear.We determined the prognostic significance of different immune cells in intratumoral tissue (T), stromal tissue (S), and adjacent normal tissue (N) of 166 gastric cancer cases and their interactions, including CD3+, CD4+, CD8+, CD57+, CD68+, CD66b+, and Foxp3+ cells, and established an effective prognostic nomogram based on the immune reactions.We found high densities of TCD3+, TCD4+, TCD8+, SCD3+, SCD4+, SCD57+, SCD66b+, and NFoxp3+ cells, as well as high TCD8+/SCD8+ ratio, TCD68+/SCD68+ ratio, TCD3+/TFoxp3+ ratio, TCD4+/TFoxp3+ ratio, TCD8+/TFoxp3+ ratio, SCD3+/SFoxp3+ ratio, and SCD4+/SCD8+ ratio were associated with better survival, whereas high densities of TCD66b+, TFoxp3+, SFoxp3+ and NCD66b+ cells as well as high TCD57+/SCD57+ ratio, TCD66b+/SCD66b+ ratio, SCD8+/SFoxp3+ ratio, and TFoxp3+/NFoxp3+ ratio were associated with significantly worse outcome. Multivariate analysis indicated that tumor size, longitudinal tumor location, N stage, TCD68+/SCD68+ ratio, TCD8+/TFoxp3+ ratio, density of TFoxp3+ cells, and TCD66b+/SCD66b+ ratio were independent prognostic factors, which were all selected into the nomogram. The calibration curve for likelihood of survival demonstrated favorable consistency between predictive value of the nomogram and actual observation. The C-index (0.83, 95% CI: 0.78 to 0.87) of our nomogram for predicting prognosis was significantly higher than that of TNM staging system (0.70). Collectively, high TCD68+/SCD68+ ratio and TCD8+/TFoxp3+ ratio were associated with improved overall survival, whereas high density of TFoxp3+ cells and TCD66b+/SCD66b+ ratio demonstrated poor overall survival, which are promising independent predictors for overall survival in gastric cancer.
On asymptotic structure in compressed sensing

This paper demonstrates how new principles of compressed sensing, namely asymptotic incoherence, asymptotic sparsity and multilevel sampling, can be utilised to better understand underlying phenomena in practical compressed sensing and improve results in real-world applications. The contribution of the paper is fourfold: First, it explains how the sampling strategy depends not only on the signal sparsity but also on its structure, and shows how to design effective sampling strategies utilising this. Second, it demonstrates that the optimal sampling strategy and the efficiency of compressed sensing also depends on the resolution of the problem, and shows how this phenomenon markedly affects compressed sensing results and how to exploit it. Third, as the new framework also fits analog (infinite dimensional) models that govern many inverse problems in practice, the paper describes how it can be used to yield substantial improvements. Fourth, by using multilevel sampling, which exploits the structure of the signal, the paper explains how one can outperform random Gaussian/Bernoulli sampling even when the classical $l^1$ recovery algorithm is replaced by modified algorithms which aim to exploit structure such as model based or Bayesian compressed sensing or approximate message passaging. This final observation raises the question whether universality is desirable even when such matrices are applicable. Examples of practical applications investigated in this paper include Magnetic Resonance Imaging (MRI), Electron Microscopy (EM), Compressive Imaging (CI) and Fluorescence Microscopy (FM). For the latter, a new compressed sensing approach is also presented.
Deep Learning Models for Retinal Blood Vessels Segmentation: A Review

This paper presents a comprehensive review of the principle and application of deep learning in retinal image analysis. Many eye diseases often lead to blindness in the absence of proper clinical diagnosis and medical treatment. For example, diabetic retinopathy (DR) is one such disease in which the retinal blood vessels of human eyes are damaged. The ophthalmologists diagnose DR based on their professional knowledge, that is labor intensive. With the advances in image processing and artificial intelligence, computer vision-based techniques have been applied rapidly and widely in the field of medical images analysis and are becoming a better way to advance ophthalmology in practice. Such approaches utilize accurate visual analysis to identify the abnormality of blood vessels with improved performance over manual procedures. More recently, machine learning, in particular, deep learning, has been successfully implemented in this area. In this paper, we focus on recent advances in deep learning methods for retinal image analysis. We review the related publications since 1982, which include more than 80 papers for retinal vessels detections in the research scope spanning from segmentation to classification. Although deep learning has been successfully implemented in other areas, we found only 17 papers so far focus on retinal blood vessel segmentation. This paper characterizes each deep learning based segmentation method as described in the literature. Analyzing along with the limitations and advantages of each method. In the end, we offer some recommendations for future improvement for retinal image analysis.
An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera from normal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal–accuracy 96.00%, error 4.00%; AA vs. normal–accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.