Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Random Forwarding Actions for Information Diffusion over Mobile Social Networks

Modeling information diffusion over social networks has attracted a lot of attention from both academia and industry. Based on universal generating function method and discrete stress-strength interference theory, a novel method is proposed to model the users’ random forwarding actions, and the most susceptible users are extracted. The effect of a user on information diffusion is quantified as node susceptibility (NS), and NS is defined as the probability that quantity of information (message) the user forwards is larger than that he receives. The model can address three questions: which users are most susceptible, which types of information they are most susceptible to, and when they are most susceptible. The solutions of these questions are very helpful for the practitioners. A case study is used to illustrate the feasibility and practicality of the proposed model.
Leaf classification using marginalized shape context and shape+texture dual-path deep convolutional neural network

Identifying plant species based on photographs of their leaves is an important problem in computer vision and biology. Previous approaches for leaf image classification typically rely on hand-crafted shape features or texture features. In contrast, we propose a dual-path deep convolutional neural network (CNN) to (i) learn joint feature representations for leaf images, exploiting their shape and texture characteristics, and (ii) optimize these features for the classification task. We compare our CNN approach against (i) vanilla CNN classifiers and (ii) popular hand-crafted shape features, including a novel shape-context based feature that is extremely computationally efficient, which we call the marginalized shape context. Our results on three large public datasets demonstrate that our dual-path CNN leads to higher accuracy and consistency than the state of the art.
Magnetic nanoparticles for selective heating of magnetically labelled cells in culture: preliminary investigation

The minimally invasive elimination of tumours using heating as a therapeutic agent is an emerging technology in medical applications. Particularly, the intratumoural application of magnetic nanoparticles as potential heating sources when exposed to an alternating magnetic field has been demonstrated. The present work deals with the estimation of the basic relationships when the magnetic material has access and binds to structures on cell membranes of target cells at the tumour region, particularly as a consequence of administration through tumour supplying vessels. Therefore, using mouse endothelial cells in culture, the binding of dextran coated magnetic nanoparticles (mean hydrodynamic particle diameter 65 nm) was modelled using the periodate method. The efficacy of cell labelling was demonstrated by magnetorelaxometry (MRX)—a selective method for the detection of only those magnetic nanoparticles that were immobilized—as well as by electron microscopy and iron staining. The amount of iron immobilized on cells was found to be 153 ± 56 µg Fe per 1 × 107 cells as determined by atomic absorption spectrometry. Moreover, after exposure of those 1 × 107 labelled cells to an alternating magnetic field (frequency 410 kHz, amplitude 11 kA m−1) for 5 min, temperature increases of 2 °C were achieved. The consequences of particle immobilization are reflected by the results of the measurements related to the specific heating power (SHP) of the magnetic material. Basically, the heating potential is explained by the superposition of Brown and Neel relaxation while for immobilized nanoparticles the Brown contribution is absent. In the long term the data could open the door to targeted magnetic heating after further optimization of the heating potential of magnetic material as well as after functionalization with biomolecules which recognize specific structures on the surface of cells at the target region.
Subjective Cognitive Impairment, Depressive Symptoms, and Fatigue after a TIA or Transient Neurological Attack: A Prospective Study

Introduction Subjective cognitive impairment (SCI), depressive symptoms, and fatigue are common after stroke and are associated with reduced quality of life. We prospectively investigated their prevalence and course after a transient ischemic attack (TIA) or nonfocal transient neurological attack (TNA) and the association with diffusion-weighted imaging (DWI) lesions. Methods The Cognitive Failures Questionnaire, Hospital Anxiety and Depression Scale, and Subjective Fatigue subscale from the Checklist Individual Strength were used to assess subjective complaints shortly after TIA or TNA and six months later. With repeated measure analysis, the associations between DWI lesion presence or clinical diagnosis (TIA or TNA) and subjective complaints over time were determined. Results We included 103 patients (28 DWI positive). At baseline, SCI and fatigue were less severe in DWI positive than in DWI negative patients, whereas at follow-up, there were no differences. SCI (p = 0.02) and fatigue (p = 0.01) increased in severity only in DWI positive patients. There were no differences between TIA and TNA. Conclusions Subjective complaints are highly prevalent in TIA and TNA patients. The short-term prognosis is not different between DWI-positive and DWI negative patients, but SCI and fatigue increase in severity within six months after the event when an initial DWI lesion is present.
A review of social networking service (SNS) research in communication journals from 2006 to 2011

This article presents a review of the scholarship on social networking services (SNS) in the period from 2006 to 2011. Through a full scan of the academic output published in six high-ranking communication journals listed in the Social Science Citation Index (SSCI) within the six-year period, 84 directly relevant articles were identified. The study summarizes the objects of study, methodological preferences, and thematic patterns of recent SNS research. Challenges to the field and several reflections are addressed. The findings provide not only an overview of current ongoing research trends but also insights for future studies.
An outbreak of high-level azithromycin resistant Neisseria gonorrhoeae in England

Objectives To investigate a potential outbreak of high-level azithromycin resistant (HL-AziR) gonococcal infections diagnosed in eight patients attending a sexual health clinic in Leeds, North England, between November 2014 and March 2015. Methods Eight cases of infection with gonococci exhibiting azithromycin minimum inhibitory concentrations (MICs) ≥256 mg/L were identified from patients in Leeds as part of the routine service provided by the Sexually Transmitted Bacteria Reference Unit. All patient records were reviewed to collate epidemiological and clinical information including evaluation of patient management. Whole-genome sequencing (WGS) was performed on seven gonococcal isolates to determine Neisseria gonorrhoeae multiantigen sequence type (NG-MAST), WGS comparison and mutations in the 23S rRNA genes. Results All patients were heterosexual (five male, three female) from a range of ethnic backgrounds and from the Leeds area. Three patients were linked by partner notification. All patients were infected at genital sites and two women had pharyngeal infection also. Six patients received the recommended first-line therapy for uncomplicated gonorrhoea, one was treated for pelvic inflammatory disease and one received spectinomycin followed later by ciprofloxacin. Test of cure was achieved in seven patients and confirmed successful eradication. All seven isolates sequenced were identical by NG-MAST and WGS comparison, and contained an A2143G mutation in all four 23S rRNA alleles. Conclusions Epidemiological and microbiological investigations confirm that an outbreak of a gonococcal strain showing HL-AziR is ongoing in the North of England. Every effort should be made to identify and curtail dissemination of this strain as it presents a significant threat to the current recommended front-line dual therapy.
Adaptive Power Allocation Schemes for Spectrum Sharing in Interference-Alignment-Based Cognitive Radio Networks

Interference alignment (IA) is a promising technique for interference management and can be applied to spectrum sharing in cognitive radio (CR) networks. However, the sum rate may fall short of the theoretical maximum, particularly at low signal-to-noise ratio (SNR), and the quality of service (QoS) of the primary user (PU) may not be guaranteed. In addition, power allocation (PA) in IA-based CR networks is largely ignored, which can further improve its performance. Thus, in this paper, PA in IA-based CR networks is studied. To guarantee the QoS requirement of the PU, its minimal transmitted power is derived. Then, we propose three PA algorithms to maximize the throughput of secondary users (SUs), the energy efficiency (EE) of the network, and the requirements of SUs, respectively, while guaranteeing the QoS of the PU. To reduce the complexity, the closed-form solutions of these algorithms are further studied in detail. The outage probability of the PU according to its rate threshold is also derived to analyze the performance of these algorithms. Moreover, we propose a transmission-mode adaptation scheme to further improve the PU's performance when its QoS requirement cannot be guaranteed at low SNR, and it can be easily combined with the proposed PA algorithms. Simulation results are presented to show the effectiveness of the proposed adaptive PA algorithms for IA-based CR networks.
AmbientGAN: Generative models from lossy measurements

Generative models provide a way to model structure in complex distributions and have been shown to be useful for many tasks of practical interest. However, cur-rent techniques for training generative models require access to fully-observed samples. In many settings, it is expensive or even impossible to obtain fully-observed samples, but economical to obtain partial, noisy observations. We consider the task of learning an implicit generative model given only lossy measurements of samples from the distribution of interest. We show that the true underlying distribution can be provably recovered even in the presence of per-sample information loss for a class of measurement models. Based on this, we propose a new method of training Generative Adversarial Networks (GANs) which we call AmbientGAN. On three benchmark datasets, and for various measurement models, we demonstrate substantial qualitative and quantitative improvements. Generative models trained with our method can obtain 2 - 4 x higher inception scores than the baselines.
Racial and ethnic differences in hospice use among patients with heart failure.

BACKGROUND Heart failure is the leading noncancer diagnosis for patients in hospice care and the leading cause of hospitalization among Medicare beneficiaries. Racial and ethnic differences in hospice patients are well documented for patients with cancer but poorly described for those with heart failure. METHODS On the basis of a national sample of 98 258 Medicare beneficiaries 66 years and older on January 1, 2001, with a diagnosis of heart failure who had at least 1 physician or hospital encounter and who were not enrolled in hospice care between January 1 and December 31, 2000, we determined the effect of race and ethnicity on hospice entry for patients with heart failure in 2001 after adjusting for sociodemographic, clinical, and geographic factors. RESULTS In unadjusted analysis, blacks (odds ratio [OR], 0.52) and Hispanics (0.43) used hospice care for heart failure less than whites. Racial and ethnic differences in patients who received hospice care for heart failure persisted after adjusting for markers of income, urbanicity, severity of illness, local density of hospice use, and medical comorbidity (adjusted OR for blacks, 0.59; 95% confidence interval, 0.47-0.73; and adjusted OR for Hispanics, 0.49; 95% confidence interval, 0.37-0.66; compared with whites). Advanced age, greater comorbidity, emergency department visits, hospitalizations, and greater local density of hospice use were also associated with hospice use. CONCLUSIONS In a national sample of Medicare beneficiaries with heart failure, blacks and Hispanics used hospice care for heart failure less than whites after adjustment for individual and market factors. To understand the mechanisms underlying these findings, further examination of patient preferences and physician referral behavior is needed.
The Impact That Number of Analyzed Metastatic Breast Cancer Lesions Has on Response Assessment by 18F-FDG PET/CT Using PERCIST

The PET Response Criteria in Solid Tumors (PERCIST) are not specific regarding the number of lesions that should be analyzed per patient. This study evaluated how the number of analyzed lesions affects response assessment in metastatic breast cancer. Methods: In 60 patients, response was assessed by the change in SUVpeak, normalized to lean body mass, of the most 18F-FDG–avid lesion (PERCIST 1) and by the change in the sum of normalized SUVpeak for up to 5 lesions (PERCIST 5). The correlation between response by PERCIST and progression-free and disease-specific survival was evaluated. Results: In responders and nonresponders, the respective progression-free survival at 2 y was 37.26% and 6.43% for PERCIST 1 (P < 0.0001) and 33.65% and 7.14% for PERCIST 5 (P < 0.0001) and the respective disease-specific survival at 4 y was 58.96% and 25.44% for PERCIST 1 (P < 0.012) and 59.12% vs 20.01% for PERCIST 5 (P < 0.002). Conclusion: The number of analyzed lesions does not appear to have a major impact on the prognostic value of response assessment with 18F-FDG PET/CT in metastatic breast cancer.
Phenylalanine isotope pulse method to measure effect of sepsis on protein breakdown and membrane transport in the pig.

The primed-continuous (PC) phenylalanine (Phe) stable isotope infusion methodology is often used as a proxy for measuring whole body protein breakdown (WbPB) in sepsis. It is unclear if WbPB data obtained by an easy-to-use single IV Phe isotope pulse administration (PULSE) are comparable to those by PC. Compartmental modeling with PULSE could provide us more insight in WbPB in sepsis. Therefore, in the present study, we compared PULSE with PC as proxy for WbPB in an instrumented pig model with Pseudomonas aeruginosa-induced severe sepsis (Healthy: n = 9; Sepsis: n = 13). Seventeen hours after sepsis induction, we compared the Wb rate of appearance (WbRa) of Phe obtained by PC (L-[ring-13C6]Phe) and PULSE (L-[15N]Phe) in arterial plasma using LC-MS/MS and (non)compartmental modeling. PULSE-WbRa was highly correlated with PC-WbRa (r = 0.732, P < 0.0001) and WbPB (r = 0.897, P < 0.0001) independent of the septic state. PULSE-WbRa was 1.6 times higher than PC-WbRa (P < 0.001). Compartmental and noncompartmental PULSE modeling provide comparable WbRa values, although compartmental modeling was more sensitive. WbPB was elevated in sepsis (Healthy: 3,378 ± 103; Sepsis: 4,333 ± 160 nmol·kg BW-1·min-1, P = 0.0002). With PULSE, sepsis was characterized by an increase of the metabolic shunting (Healthy: 3,021 ± 347; Sepsis: 4,233 ± 344 nmol·kg BW-1·min-1, P = 0.026). Membrane transport capacity was the same. Both PC and PULSE methods are able to assess changes in WbRa of plasma Phe reflecting WbPB changes with high sensitivity, independent of the (patho)physiological state. The easy-to-use (non)compartmental PULSE reflects better the real WbPB than PC. With PULSE compartmental analysis, we conclude that the membrane transport capacity for amino acids is not compromised in severe sepsis.
Nursing diagnoses related to psychiatric adult inpatient care

AIMS AND OBJECTIVES To detect the prevalence of NANDA-I diagnoses and possible relationships between those and patient characteristics such as gender, age, medical diagnoses and psychiatric specialty/setting. BACKGROUND There is a lack on studies about psychiatric inpatient characteristics and possible relationships among these characteristics with nursing diagnoses. DESIGN A quantitative-descriptive, cross-sectional, completed data sampling study was performed. METHODS The data were collected from the electronic patient record system. Frequencies for the social-demographic data, the prevalence of the NANDA-I diagnoses and the explanatory variables were calculated. RESULTS In total, 410 nursing phenomena were found representing 85 different NANDA-I diagnoses in 312 patients. The NANDA-I diagnosis "Ineffective Coping" was the most frequently stated diagnosis followed by "Ineffective Health Maintenance," "Hopelessness" and "Risk for Other-Directed Violence". Men were more frequently affected by the diagnoses "Ineffective Coping," "Hopelessness," "Risk for Self-Directed Violence," "Defensive Coping" and "Risk for Suicide," whereas the diagnoses "Insomnia," "Chronic Confusion," "Chronic Low Self-Esteem" and "Anxiety" were more common in women. Patients under the age of 45 years were more frequently affected by "Chronic Low Self-Esteem" and "Anxiety" than older patients. "Ineffective Coping" was the most prevalent diagnosis by patients with mental disorders due to psychoactive substance use. Patients with schizophrenia were primarily affected by the diagnoses "Ineffective Coping," "Impaired Social Interaction" and "Chronic Low Self-Esteem. " CONCLUSIONS This study demonstrates the complexity and diversity of nursing care in inpatient psychiatric settings. Patients' gender, age and psychiatric diagnoses and settings are a key factor for specific nursing diagnosis. RELEVANCE TO CLINICAL PRACTICE There are tendencies for relationships between certain nursing diagnosis and patient characteristics in psychiatric adult inpatients. This enhances the specific, extended knowledge for nursing care and its demands in this setting and therefore supports the daily nursing psychiatric care and its needs.
Inertial sensors for assessment of joint angles

In this paper, two approaches for estimating joint angles are presented: the first one uses only an accelerometer to estimate hip and knee angles on static postures, whereas the second approach fuses information from multiple sensors to dynamically calculate leg range of motion. Static joint angle results were evaluated against goniometer, which is used as a standard at clinics. Dynamic angles results were compared with Kinect joint segmentation, as well as a custom marker-based video tracking algorithm for angle estimation. For both approaches, the errors obtained when compared with reference systems were very low. Results support that inertial sensors are suitable for use in home-based rehabilitation exercises.
Bayesian joint modeling of longitudinal and spatial survival AIDS data

Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time‐to‐event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with non‐linear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002–2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states. Copyright © 2016 John Wiley & Sons, Ltd.
Label‐free monitoring of inflammatory tissue conditions using a carrageenan‐induced acute inflammation rat model

Although the confirmation of inflammatory changes within tissues at the onset of various diseases is critical for the early detection of disease and selection of appropriate treatment, most therapies are based on complex and time‐consuming diagnostic procedures. Raman spectroscopy has the ability to provide non‐invasive, real‐time, chemical bonding analysis through the inelastic scattering of photons. In this study, we evaluate the feasibility of Raman spectroscopy as a new, easy, fast, and accurate diagnostic method to support diagnostic decisions. The molecular changes in carrageenan‐induced acute inflammation rat tissues were assessed by Raman spectroscopy. Volumes of 0 (control), 100, 150, and 200 µL of 1% carrageenan were administered to rat hind paws to control the degree of inflammation. The prominent peaks at [1,062, 1,131] cm−1 and [2,847, 2,881] cm−1 were selected as characteristic measurements corresponding to the C–C stretching vibrational modes and the symmetric and asymmetric C–H (CH2) stretching vibrational modes, respectively. Principal component analysis of the inflammatory Raman spectra enabled graphical representation of the degree of inflammation through principal component loading profiles of inflammatory tissues on a two‐dimensional plot. Therefore, Raman spectroscopy with multivariate statistical analysis represents a promising method for detecting biomolecular responses based on different types of inflammatory tissues.
Intravenous Administration of Manuka Honey Inhibits Tumor Growth and Improves Host Survival When Used in Combination with Chemotherapy in a Melanoma Mouse Model

Manuka honey has been recognized for its anti-bacterial and wound-healing activity but its potential antitumor effect is poorly studied despite the fact that it contains many antioxidant compounds. In this study, we investigated the antiproliferative activity of manuka honey on three different cancer cell lines, murine melanoma (B16.F1) and colorectal carcinoma (CT26) as well as human breast cancer (MCF-7) cells in vitro. The data demonstrate that manuka honey has potent anti-proliferative effect on all three cancer cell lines in a time- and dose-dependent manner, being effective at concentrations as low as 0.6% (w/v). This effect is mediated via the activation of a caspase 9-dependent apoptotic pathway, leading to the induction of caspase 3, reduced Bcl-2 expression, DNA fragmentation and cell death. Combination treatment of cancer cells with manuka and paclitaxel in vitro, however, revealed no evidence of a synergistic action on cancer cell proliferation. Furthermore, we utilized an in vivo syngeneic mouse melanoma model to assess the potential effect of intravenously-administered manuka honey, alone or in combination with paclitaxel, on the growth of established tumors. Our findings indicate that systemic administration of manuka honey was not associated with any alterations in haematological or clinical chemistry values in serum of treated mice, demonstrating its safety profile. Treatment with manuka honey alone resulted in about 33% inhibition of tumor growth, which correlated with histologically observable increase in tumor apoptosis. Although better control of tumor growth was observed in animals treated with paclitaxel alone or in combination with manuka honey (61% inhibition), a dramatic improvement in host survival was seen in the co-treatment group. This highlights a potentially novel role for manuka honey in alleviating chemotherapy-induced toxicity.