Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Frequency Energy Sensing of Communication Signals and Its Application in Co-Channel Interference Suppression

As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network with Device-to-Device communications, where the co-channel interferences are brought and needs to be suppressed. According to the time-frequency energy sensing to the communication signals, the desired signal and the interference signal have different energy concentration areas on the time frequency plane, which provide opportunities to suppress the co-channel interference with time varying filter. This paper analyzes the time-frequency distributions of the Gaussian pulse shaping signals, discusses the effect of the analyzing window length on the time-frequency resolution, exploits the equivalence between the time frequency analysis at the baseband and at the radio front end, and finally reveals the advantages of the proposed masking threshold constrained time varying filter based co-channel interference mitigation method. The pass region for the linear time varying filter is generated according to the time-varying energy characteristics of the I/Q separated 4-QAM pulse shaping signals, where the optimum masking threshold is obtained by the optimum-BER criterion. The proposed co-channel interference suppression method is evaluated in aspect of BER performance, and simulation results show that the proposed method outperforms existing methods with low-pass or band-pass filters.
The effects of dietary supplementation with rumen‐protected amino acids on the expression of several genes involved in the immune system of dairy sheep

Amino acids might be a tool to transform animals from a pro- to an anti-inflammatory phenotype through the downregulation of several genes (TLR-4, NF-κB, TNFa, IL-1β, IL-2, IL-6, IL-8, CCL-5 and CXCL-16) whose expression increases during inflammation. To examine this possibility, each of sixty Chios dairy sheep was assigned to one of the following five dietary treatments: A: basal diet (control group); B: basal diet +6.0 g/head rumen-protected methionine (MetaSmart™ ); C: basal diet +5.0 g/head rumen-protected lysine (LysiGEM™ ); D: basal diet +6.0 g/head MetaSmart™ + 5.0 g/head LysiGEM™ ; and E: basal diet +12.0 g/head MetaSmart™ + 5.0 g/head LysiGEM. The results showed a significant downregulation in the expression of the TLR-4 gene in both the macrophages and the neutrophils of ewes fed rumen-protected amino acids. Significantly lower mRNA transcript accumulation was also observed for the TNFa, IL-1β and CXCL-16 genes in the macrophages and for the IL-1β gene in the neutrophils of ewes supplemented with amino acids. The ewes that received dietary supplementation with rumen-protected lysine alone (C) had significantly lower CCL-5 transcript levels in their macrophages than the ewes fed the other supplemented diets. Diet D enhanced the mRNA expression of the IL-2 gene in ewe neutrophils. Negative correlations were found between: a. TLR-4, TNFa, IL-1β and CXCL-16 gene expression in macrophages and the milk fat and total solids content; b. CCL-5 gene expression in neutrophils and the milk yield and FCM(6%) ; and c. CXCL-16 gene expression and the milk protein content. Moreover, positive correlations were found between the BHBA concentration and the expression of the TLR-4 and CXCL-16 genes in macrophages. In conclusion, the rumen-protected amino acids improved sheep metabolism (as indicated by reduced blood BHBA and urea concentrations), milk chemical composition and immune system function.
Reciprocal Longitudinal Associations Between Adolescents’ Media Consumption and Sleep

ABSTRACT Background/Objective: Associations between adolescents’ sleep and their media consumption have been shown in several cross-sectional studies. However, longitudinal investigations are still sparse and have mainly investigated associations between sleep duration and the usage of TV or computer games. The present study explored reciprocal longitudinal relationships between the consumption of different screen-based media and sleep-related problems in German adolescents. Participants: Four hundred sixty-seven 10- to 17-year-old adolescents participated in the LIFE Child Study in Leipzig, Germany. Methods: The consumption of screen-based media (TV or video, computer and Internet, mobile phones) as well as sleep-related problems (problems at bedtime, sleep behavior problems, daytime sleepiness) were assessed at two time points, 12 months apart. Reciprocal longitudinal relations were assessed by multiple regression analyses. All associations were controlled for age, gender, socioeconomic status, and dependent variables at baseline. Results: The consumption times of the different screen-based media were significantly related. Similarly, the different sleep-related problems showed significant interrelations. Most importantly, the analyses revealed significant associations between a high baseline consumption of computer and Internet with more problems at bedtime, as well as more daytime sleepiness at follow-up. Furthermore, baseline daytime sleepiness was associated with a higher consumption of TV or video at follow-up. Conclusions: These results indicate a mutual dependency of media consumption and sleep over time.
In-Person Interpreter Use and Hospital Length of Stay among Infants with Low Birth Weight

To ensure timely appropriate care for low-birth-weight (LBW) infants, healthcare providers must communicate effectively with parents, even when language barriers exist. We sought to evaluate whether non-English primary language (NEPL) and professional in-person interpreter use were associated with differential hospital length of stay for LBW infants, who may incur high healthcare costs. We analyzed data for 2047 infants born between 1 January 2008 and 30 April 2013 with weight <2500 g at one hospital with high NEPL prevalence. We evaluated relationships of NEPL and in-person interpreter use on length of stay, adjusting for medical severity. Overall, 396 (19%) had NEPL parents. Fifty-three percent of NEPL parents had documented interpreter use. Length of stay ranged from 1 to 195 days (median 11). Infants of NEPL parents with no interpreter use had a 49% shorter length of stay (adjusted incidence rate ratio (IRR) 0.51, 95% confidence interval (CI) 0.43–0.61) compared to English-speakers. Infants of parents with NEPL and low interpreter use (<25% of hospital days) had a 26% longer length of stay (adjusted IRR 1.26, 95% CI 1.06–1.51). NEPL and high interpreter use (>25% of hospital days) showed a trend for an even longer length of stay. Unmeasured clinical and social/cultural factors may contribute to differences in length of stay.
Assessing the Antioxidant Properties of Larrea tridentata Extract as a Potential Molecular Therapy against Oxidative Stress

Oxidative stress has been linked to neurodegenerative diseases such as Huntington’s, Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis diseases. Larrea tridentata (LT) also known as Creosote Bush is an evergreen shrub found in the Chihuahuan desert which has been used medicinally by Native American tribes in southwestern North America and the Amerindians of South America. However, studies of the antioxidant capacity of the crude extract of LT towards the discovery of novel molecular therapies bearing antioxidants and drug-like properties are lacking. In this study, we assessed the antioxidant properties of Larrea tridentata, collected specifically from the Chihuahuan desert in the region of El Paso del Norte, TX, USA. LT phytochemicals were obtained from three different extracts (ethanol; ethanol: water (60:40) and water). Then the extracts were evaluated in eight different assays (DPPH, ABTS, superoxide; FRAP activity, nitric oxide, phenolic content, UV visible absorption and cytotoxicity in non-cancerous HS27 cells). The three extracts were not affecting the HS27 cells at concentrations up to 120 µg/mL. Among the three extracts, we found that the mixture of ethanol: water (60:40) LT extract has the most efficient antioxidant properties (IC50 (DPPH at 30 min) = 111.7 ± 3.8 μg/mL; IC50 (ABTS) = 8.49 ± 2.28 μg/mL; IC50 (superoxide) = 0.43 ± 0.17 μg/mL; IC50 (NO) = 230.4 ± 130.4 μg/mL; and the highest phenolic content was estimated to 212.46 ± 7.05 mg GAE/L). In addition, there was a strong correlation between phenolic content and the free-radical scavenging activity assays. HPLC-MS study identified nine compounds from the LT-ethanol: water extract including Justicidin B and Beta peltain have been previously reported as secondary metabolites of Larrea tridentata.
Combination of Aronia, Red Ginseng, Shiitake Mushroom and Nattokinase Potentiated Insulin Secretion and Reduced Insulin Resistance with Improving Gut Microbiome Dysbiosis in Insulin Deficient Type 2 Diabetic Rats

The combination of freeze-dried aronia, red ginseng, ultraviolet-irradiated shiitake mushroom and nattokinase (AGM; 3.4:4.1:2.4:0.1) was examined to evaluate its effects on insulin resistance, insulin secretion and the gut microbiome in a non-obese type 2 diabetic animal model. Pancreatectomized (Px) rats were provided high fat diets supplemented with either (1) 0.5 g AGM (AGM-L), (2) 1 g AGM (AGM-H), (3) 1 g dextrin (control), or (4) 1 g dextrin with 120 mg metformin (positive-control) per kg body weight for 12 weeks. AGM (1 g) contained 6.22 mg cyanidin-3-galactose, 2.5 mg ginsenoside Rg3 and 244 mg β-glucan. Px rats had decreased bone mineral density in the lumbar spine and femur and lean body mass in the hip and leg compared to the normal-control and AGM-L and AGM-H prevented the decrease. Visceral fat mass was lower in the control group than the normal-control group and its decrease was smaller with AGM-L and AGM-H. HOMA-IR was lower in descending order of the control, positive-control, AGM-L, AGM-H and normal-control groups. Glucose tolerance deteriorated in the control group and was improved by AGM-L and AGM-H more than in the positive-control group. Glucose tolerance is associated with insulin resistance and insulin secretion. Insulin tolerance indicated insulin resistance was highly impaired in diabetic rats, but it was improved in the ascending order of the positive-control, AGM-L and AGM-H. Insulin secretion capacity, measured by hyperglycemic clamp, was much lower in the control group than the normal-control group and it was improved in the ascending order of the positive-control, AGM-L and AGM-H. Diabetes modulated the composition of the gut microbiome and AGM prevented the modulation of gut microbiome. In conclusion, AGM improved glucose metabolism by potentiating insulin secretion and reducing insulin resistance in insulin deficient type 2 diabetic rats. The improvement of diabetic status alleviated body composition changes and prevented changes of gut microbiome composition.
Deep Manifold Preserving Autoencoder for Classifying Breast Cancer Histopathological Images

Classifying breast cancer histopathological images automatically is an important task in computer assisted pathology analysis. However, extracting informative and non-redundant features for histopathological image classification is challenging due to the appearance variability caused by the heterogeneity of the disease, the tissue preparation, and staining processes. In this paper, we propose a new feature extractor, called deep manifold preserving autoencoder, to learn discriminative features from unlabeled data. Then, we integrate the proposed feature extractor with a softmax classifier to classify breast cancer histopathology images. Specifically, it learns hierarchal features from unlabeled image patches by minimizing the distance between its input and output, and simultaneously preserving the geometric structure of the whole input data set. After the unsupervised training, we connect the encoder layers of the trained deep manifold preserving autoencoder with a softmax classifier to construct a cascade model and fine-tune this deep neural network with labeled training data. The proposed method learns discriminative features by preserving the structure of the input datasets from the manifold learning view and minimizing reconstruction error from the deep learning view from a large amount of unlabeled data. Extensive experiments on the public breast cancer dataset (BreaKHis) demonstrate the effectiveness of the proposed method.
Shared spatiotemporal category representations in biological and artificial deep neural networks

Understanding the computational transformations that enable invariant visual categorization is a fundamental challenge in both systems and cognitive neuroscience. Recently developed deep convolutional neural networks (CNNs) perform visual categorization at accuracies that rival humans, providing neuroscientists with the opportunity to interrogate the series of representational transformations that enable categorization in silico. The goal of the current study is to assess the extent to which sequential visual representations built by a CNN map onto those built in the human brain as assessed by high-density, time-resolved event-related potentials (ERPs). We found correspondence both over time and across the scalp: earlier ERP activity was best explained by early CNN layers at all electrodes. Later neural activity was best explained by the later, conceptual layers of the CNN. This effect was especially true both in frontal and right occipital sites. Together, we conclude that deep artificial neural networks trained to perform scene categorization traverse similar representational stages as the human brain. Thus, examining these networks will allow neuroscientists to better understand the transformations that enable invariant visual categorization.
A Temporal Difference Reinforcement Learning Theory of Emotion: unifying emotion, cognition and adaptive behavior

Emotions are intimately tied to motivation and the adaptation of behavior, and many animal species show evidence of emotions in their behavior. Therefore, emotions must be related to powerful mechanisms that aid survival, and, emotions must be evolutionary continuous phenomena. How and why did emotions evolve in nature, how do events get emotionally appraised, how do emotions relate to cognitive complexity, and, how do they impact behavior and learning? In this article I propose that all emotions are manifestations of reward processing, in particular Temporal Difference (TD) error assessment. Reinforcement Learning (RL) is a powerful computational model for the learning of goal oriented tasks by exploration and feedback. Evidence indicates that RL-like processes exist in many animal species. Key in the processing of feedback in RL is the notion of TD error, the assessment of how much better or worse a situation just became, compared to what was previously expected (or, the estimated gain or loss of utility - or well-being - resulting from new evidence). I propose a TDRL Theory of Emotion and discuss its ramifications for our understanding of emotions in humans, animals and machines, and present psychological, neurobiological and computational evidence in its support.
SYMPTOMS OF ANXIETY AND DEPRESSION, AND QUALITY OF LIFE OF PATIENTS WITH CROHN'S DISEASE.

BACKGROUND Crohn's disease is an idiopathic chronic inflammatory disease. It is classified as an inflammatory bowel disease. Crohn's disease can change patient quality of life, especially during flares. Crohn's disease has been associated with symptoms of anxiety and depression, because the clinical symptoms have a high impact on quality of life. OBJECTIVE To investigate the prevalence of symptoms of anxiety and depression in Brazilian patients diagnosed with Crohn's disease, as well as their quality of life. METHODS A total of 110 Brazilian patients aged 21-59 years, both genders, with Crohn's disease were included. The data were collected through questionnaires. The Hospital Anxiety and Depression Scale (HADS) was used to assess anxiety and depression symptoms. Quality of life was evaluated using the Inflammatory Bowel Disease Questionnaire. Data were analyzed by ANOVA, followed by the Duncan post-hoc test and the multiple linear regression test. RESULTS Of the total, 61.7% of participants reported symptoms of anxiety or depression or both. Regarding quality of life, the majority (43.6%) were classified as "regular" and the minority (3.6%) as "excellent". Multiple linear regression showed that worse quality of life correlated with greater presence of anxiety and depression symptoms (<0.001). CONCLUSION Crohn's disease has considerable impact on quality of life and contributes to the appearance of anxiety and/or depression symptoms.
Patterns of primary healthcare use among female exotic dancers in Baltimore, Maryland

ABSTRACT Female exotic dancers (FEDs) are often exposed to violence-, sex- and drug-related occupational harms and are precluded from employer-based health insurance. We examined access to primary health-care resources, correlates of use, and service needs among a sample of new FEDs (N = 117) working in 22 exotic dance clubs (EDCs) in Baltimore, MD. Self-administered surveys were completed between May and October 2014. Health care measures were aggregated and described, and correlates of use were evaluated using Fisher Exact and Poisson regression with robust variance, adjusting for race/ethnicity. The majority of dancers reported having health insurance (80%), a primary care provider (PCP) (68%), and having visited a PCP (74%). Among dancers with insurance, all were covered by Medicaid. Multivariable regression models demonstrated that having a regular PCP was associated with recent PCP use (adjusted prevalence ratio 1.5; 95% confidence interval: 1.1, 2.1). Despite a high level of health-care coverage and recent visits to PCP, dancers frequently sought services at the emergency department and reported needs for medical care, including mental health support services and drug treatment. Findings highlight that basic access to primary health care is available and used but may not be fully meeting dancers’ complex needs.
Risk Factors for Domestic Violence in Women and Predictors of Development of Mental Disorders in These Women.

Introduction Based on the hypothesis that women who exposed to physical violence had lower education and income levels than those who did not, and those who got married earlier and had marriage with unwanted people had higher psychiatric disorders, the aims of this study were to determine risk factors for domestic violence and predictors of psychiatric impairment in women exposed to domestic violence. Methods We used random selection method and included 400 married women above 18 years of age living in Adiyaman province. Socio-demographic data and exposure to physical violence and sexual coercion for participants were evaluated by a structured questionnaire. Depression scores of the women were evaluated by Beck Depression Inventory (BDI) and anxiety scores were evaluated by Beck Anxiety Inventory (BAI). Suicidal ideas of the subjects were evaluated by 17 item Suicide Intent Scale and their suicide plans, attempts, thoughts, and risk of recurrence were evaluated by 4 item Suicidal Behavior Questionnaire. Results 65,5% of the women (n=262) reported no violence, 19,3% (n=77) reported violence only from their spouses, 5,2% (n=21) reported violence from people other than spouse, and 10% (n=40) reported physical violence from both their spouses and other people. Logistic regression analysis showed that employment status of spouses, presence of medical/psychiatric illness in spouses, the acceptance of the view that 'Husbands can sometimes beat' by women and presence of psychiatric illness in women predicted domestic violence against these women from their spouses. Logistic regression analysis also revealed that education level, and presence of physical or sexual violence from their spouses predicted development of psychiatric disorders in women survivors of domestic violence. Conclusion This study showed that opinion of women about domestic violence, presence of a psychiatric disorder in women, employment status of spouse, and presence of a medical/psychiatric illness in spouse predicted physical violence against these women. In addition, education level of women, and presence of domestic violence from their spouses predicted development of psychiatric disorder. Knowing the factors that trigger physical violence and related psychiatric impairments is really important for development of preventive and therapeutic interventions.
Molecular Characterization of Bovine Leukaemia Virus (BLV) Strains Reveals Existence of Genotype 6 in Cattle in India with evidence of a new subgenotype

Bovine leukaemia virus (BLV) causes enzootic leucosis in cattle and is prevalent worldwide. Although recent studies have shown that BLV strains can be classified into 10 distinct genotypes, no information is available regarding the BLV genotype prevalent in cattle in India. To determine the genetic variability in BLV, in this study, 118 adult dairy cows from three states of India were screened for BLV infection by env gp51-specific ELISA and nested PCR. Of the 33 cows found positive by both PCR and ELISA, 10 selected BLV strains were subjected to molecular characterization. Phylogenetic analyses of partial and full-length env gp51 gene sequences of Indian BLV strains and other geographical diverse BLV strains representing all the 10 genotypes revealed that Indian strains belonged to BLV genotype 6. Although Indian strains showed close genetic proximity with the strains circulating in South America, they were classified into a new subgenotype within genotype 6. Alignment of deduced amino acid sequences in gp51 demonstrated substitutions mainly in conformational epitope G, neutralizing domain 2 and linear epitope D, with a novel mutation (threonine to alanine at residue 252) found in D-epitope of all the Indian BLV strains. Although serological evidence of BLV infection in India has been reported earlier, this study on molecular characterization of BLV strains established the existence of BLV genotype 6 in India. Additionally, the results of this study highlight the importance of genetic analysis of geographically diverse BLV strains to understand BLV global genetic diversity and further studies are required to determine BLV genetic diversity and extent of BLV infection in cattle in India.
Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporation into the building information modelling (BIM). The procedure is based on our previous work, but the algorithms are substantially improved by generalizing the detection to any light surface type, including polygonal and circular shapes, and refining the BIM integration. We validate the complete methodology with a case study at the Mining and Energy Engineering School and achieve reliable results, increasing the successful real-time processing detections while using low computational resources, leading to an accurate, cost-effective and advanced method. The suitability and the adequacy of the method are proved and concluded.