Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnesium Intake Predicts Bone Turnover in Postmenopausal Black South African Women

This prospective study investigated the association between nutrient intake, dietary patterns, and changes in bone turnover and bone mineral density (BMD) in postmenopausal urban black South African women over two years. These women (n = 144) underwent BMD measurements at the distal radius, lumbar spine, femoral neck (FN), as well as a biochemical analysis which included the parathyroid hormone (PTH), 25-hydroxyvitamin D, C-Telopeptide of type I collagen (CTX-1) in 2010 and 2012. Their dietary intake was assessed in 2010 using a food frequency questionnaire, and sociodemographic and health information was collected. Four dietary patterns explained 54.4% of the variance of dietary intake, namely staple foods and processed meats, home cooking, snacking, and high sugar. Dietary magnesium negatively correlated with CTx-1 in 2012 (r = −0.21, p = 0.02), calcium correlated with distal radius BMD in 2010 (r = 0.22, p = 0.01) and 2012 (r = 0.24, p = 0.005), and the snacking dietary pattern score correlated with FN BMD in 2010 (r = 0.18, p = 0.03) and 2012 (r = 0.21, p = 0.02). The baseline CTx-1 and dietary magnesium intake predicted 22% of the variance in percentage change of CTx-1 over two years (p < 0.001). The magnesium intake predicted short-term bone resorption over two years.
Acute kidney injury, seizures, and hypertonic hyponatremia secondary to mannitol intoxication in a dog.

OBJECTIVE To describe a case of mannitol overdose associated with acute kidney injury (AKI), hypertonic hyponatremia, and neurologic abnormalities in a dog. CASE SUMMARY A 10-year-old intact male Shiba Inu dog was referred to the emergency service of a veterinary teaching hospital for inappetence and acute onset of seizures. The dog had received 2 IV boluses of 3 g/kg of mannitol in less than 24 hours for a glaucoma crisis. Twelve hours after the second injection, the dog became inappetant and developed 2 generalized seizures. Seizure activity was treated with diazepam (0.5 mg/kg IV). Serum biochemistry profile showed severe hyponatremia and hypochloremia, mild hypokalemia, marked increased creatinine (381 µmol/L [44-133 µmol/L]) and moderately increased BUN (13.8 mmol/L [1.6-10.9 mmol/L]). Urinalysis revealed a urine specific gravity of 1.018, glucosuria, proteinuria, pigmenturia and the presence of vacuolized tubular epithelial cells. A presumptive diagnosis of mannitol intoxication was made based on the high dose of mannitol, severe hyponatremia, neurological abnormalities suggestive of intracranial disease, AKI, and urine cytology. Initial calculated plasma osmolality was 263.4 mOsm/kg and measured plasma osmolality was 332 mOsm/kg with an osmolal gap of 68.6 mOsm/kg, confirming the presence of an unmeasured solute attributed to mannitol. Treatment consisted of fluid therapy and supportive care. On day 3, osmolal gap had resolved and serum creatinine concentration returned to normal within 12 days. NEW OR UNIQUE INFORMATION PROVIDED Mannitol intoxication has been reported in human medicine. This case report is, to our knowledge, the first to describe AKI, hypertonic hyponatremia, and neurological abnormalities secondary to mannitol overdose in a dog.
Improving drug discovery using image-based multiparametric analysis of the epigenetic landscape

High-content phenotypic screening has become the approach of choice for drug discovery due to its ability to extract drug-specific multi-layered data. In the field of epigenetics, such screening methods have suffered from a lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach, Microscopic Imaging of Epigenetic Landscapes (MIEL), which captures the nuclear staining patterns of epigenetic marks and employs machine learning to accurately distinguish between such patterns. We validated the MIEL platform across multiple cells lines and using dose-response curves, to insure the fidelity and robustness of this approach for high content high throughput drug discovery. Focusing on noncytotoxic glioblastoma treatments, we demonstrated that MIEL can identify and classify epigenetically active drugs. Furthermore, we show MIEL was able to accurately rank candidate drugs by their ability to produce desired epigenetic alterations consistent with increased sensitivity to chemotherapeutic agents or with induction of glioblastoma differentiation.
The Effect of Membership in the Council of Adult and Experiential Learning on the Quality of Prior Learning Assessment Services in Senior Level Institutions Accredited by the Southern Association of Schools and Colleges

Over the past 20 years there has been a dramatic increase in the number of adults enrolling in institutions of higher education across America. Adult students presently constitute nearly one-half of all undergraduate enrollment. This influx of adults has generated interest in nontraditional programs, including external degree programs, degree completion programs, and prior learning assessment programs. The purpose of this study was to determine if an association existed between membership in the Council for Adult and Experiential Learning (CAEL) and quality in prior learning assessment services as provided by senior level institutions in the Southern Association of Colleges and Schools accrediting region. CAEL has been a pioneer in developing adult degree programs and commissioned Urban Whitaker in 1989 to define the standards for quality in such programs. A survey instrument utilizing these standards, principles, and procedures as the criteria for quality prior learning assessment services was mailed to a random sample of CAEL member and non-member institutions in the Southern Association accrediting region. Member and non-member responses were compared utilizing the Chi-square statistical analysis to determine any differences.
Gaze and body cues interplay during interactive requests

Although observing other’s gaze and body movements provides a crucial source of information to successfully interact with other people, it remains unclear whether observers weigh differently these cues and whether the convergence of gaze and body’s directions determines facilitation effects. Here we aim to shed more light on this issue by testing the reliance upon these cues from both a behavioral and a neurophysiological perspective in a social interactive context. In Experiment 1, we manipulated the convergence between the direction of an actor’s upper limb movement and gaze direction while he attempts to socially interact with the participants observing the scene. We determined the direction of gaze as well as the duration of participants’ ocular fixations during the observation of the scene. In Experiment 2, we measured and correlated the effect of the body/gaze manipulation on corticospinal excitability and on the readiness to interact—a disposition to engage in social situations. Eye-tracking data revealed that participants fixated chiefly the actor’s head when his hand and gaze directions were divergent. Possibly a strategy to disambiguate the scene. Whereas participants mainly fixated the actor’s hand when he performed an interactive request toward the participants. From a neurophysiological point of view, the more participants felt involved in the interaction, the lower was motor preparation in the muscle potentially needed to fulfill the actor’s request. We contend that social contexts are more likely to elicit motor preparation compared to non-social ones, and that muscular inhibition is a necessary mechanism in order to prevent unwanted overt reactions during action observation tasks.
Should I Be Tested for Cancer?: Maybe Not and Here's Why

Acknowledgments Introduction: The conventional wisdom about cancer testing and what this book is about PART I. PROBLEMS YOU SHOULD KNOW ABOUT 1. It is unlikely that you will benefit 2. You may have a "cancer scare" and face an endless cycle of testing 3. You may receive unnecessary treatment 4. You may find a cancer you would rather not know about 5. Your pathologist may say it's cancer, while others say it's not 6. Your doctor may get distracted from other issues that are more important to you PART II. BECOMING A BETTER-EDUCATED CONSUMER 7. Understand the culture of medicine (and why we are pushed to test) 8. Understand the statistics of cancer (and why five-year survival is the world's most misleading number) 9. Understand the limits to research--even genetic research (and why it is hard to be sure there really are benefits to screening) 10. Develop a strategy that works for you Appendix: Summary of cancers discussed in this book Glossary Notes Index
Proliferative fibrocystic lesions in association with carcinoma breast- Study of mastectomy specimens

Background: Breast cancer remains a global health problem with an increasing incidence. Proliferative breast diseases are recognized as one of the risk factors in the development of carcinoma. The study was undertaken to know the frequency of proliferative fibrocystic lesions in association with breast carcinomas in mastectomy specimens. Material and methods: The present study included 100 cases of mastectomies for carcinoma breast at Kempegowda Institute of Medical Sciences, Bangalore from August 2010 to July 2013. The tumor and the surrounding breast tissue were studied grossly and microscopically for any co-existing neoplastic and non neoplastic lesions like epithelial hyperplasia, cystic change, apocrine metaplasia, fibrosis and adenosis. Results: The study included 100 cases of breast carcinomas. The predominant type of carcinoma (85%) was infiltrating ductal carcinoma-no specific type. Proliferative breast lesions were noted in 38 cases (38%), nonproliferative breast lesions in 27 cases (27%) and there were no changes in 35 cases (35%). Of 38 cases, proliferative lesions with atypia were noted in 20 cases and proliferative lesions without atypia were noted in 18 cases. Conclusion: Proliferative lesions in the breast carry an increased risk of developing malignancies especially when there is atypia. Women, who have been diagnosed as having proliferative breast disease, require careful follow-up, with annual mammographic screening being mandatory for women with atypical hyperplasia
The effect of parasite antigen on experimentally induced ‘asthma’ in lambs

The effect of parasite antigen on experimentally induced ‘asthma’ in lambs by Omega Yaw Amoafo There is a worldwide consensus that the incidence of asthma and allergy is exhibiting a rising trend in western societies. There is also epidemiological evidence that New Zealand children raised on farms are less likely to experience asthma than those in urban environments. The aims of this study were to firstly set up a sheep model for the study of asthma and secondly, examine the effect of intrauterine and neonatal inoculation of an asthmacausing allergen [house dust mite (HDM) Dermatophagoides pteronyssinus] or helminth antigen [Trichostrongylus colubriformis L3 (TCL3)] on the development of experimentally induced ‘asthma’ in sheep. Feti or neonates of twin-bearing ewes (n=22) were treated with TCL3, HDM or PBS (control) given by lavage following hysterectomy (prenatal). At ten months of age, these lambs with additional control lambs (n=6) were sensitized by the subcutaneous inoculation of HDM and later challenged intra-bronchially with HDM, using a fibre-optic bronchoscope. At birth, lambs treated in utero with HDM antigen had the highest levels of HDM-specific IgE compared with lambs treated prenatally with TCL3 or PBS. HDM-specific IgE levels for the different treatment groups decreased significantly over the 4 week postnatal period but not their HDMspecific IgG1.Twin lambs (control and treated) showed similar levels of specific–HDM antibody after suckling from the same ewe. At 10 months of age following sensitization and challenge, there were no significant differences among white blood cells of the peripheral blood but cytology of bronchoaveolar lavage fluid following challenge showed that treatment with HDM antigen had a significant (P=0.003) effect on increasing lymphocyte percentage in the left lung of the experimental sheep but not in the right (PBS treated) lung.
Analgésicos coadyuvantes para el tratamiento del dolor crónico

For several decades the discovery of the effectiveness for the treatment of pain with drugs whose creation had other aims, opened the door to new opportunities to diminish the suffering of patients and to improve its quality of life. The first drugs that were used were tricyclic antidepressants and later this use was extended to anticonvulsivants, anesthetics, bisphosphonates, antidepressives, serotonin and norepinephrine reuptake inhibitors, among others. In spite of this, effectiveness for pain control is very variable, according to the type of pathology and in some cases of associated diseases. Therefore is necessary to do an analysis of each patient to define the suitable drug and the necessity of several active principles that complement to each other. It`s important not to forget that the approach to a patient with pain, specially a chronic one, must be interdisciplinary involving the areas of mental health and the rehabilitation, looking for to avoid complications, majors incapacities and to obtain the best social and work adaptation of patients.
Aqueous extract of Lavandula Angustifolia alter protein expression in alzheimer rats

Abstract Alzheimer’s disease (AD) is the most common form of dementia has become one of the most severe progressive socio-economical and medical burdens facing countries all over the world. The drugs are currently available just able to delay the symptom progression of disease. This study try to evaluate protein profile of the effects of aqueous extract of lavender ( Lavandula angustifolia ) on spatial performance of AD rats. Male Wistar rats were first divided into control and AD groups. Rat model of AD was established by intracerebroventricular injection of 10 mg Ab 1-42 20 d prior to administration of the lavender extract. Rats in both groups (control (CO) and Alzheimeric (ALZ) rats that did not receive the herbal extract) were then introduced to task learning in Morris water maze. After the first stage of spatial learning, control (CE200) and AD (AE200) animals received 200 mg/kg of the lavender extract. Hippocampus tissues of four groups are separated and protein profile was determined by 2DE. By using progenesis same spot software totally 950 spots are detected in 4 gel groups. The CO and ALZ displayed different performance in learning the spatial task. 111 proteins just express in CO group. This is illustrated that inducing of Alzheimer could suppress expression of 111 proteins while it can express 67 new proteins. The lavender treated animals in both control and Alzheimer groups demonstrated a tendency of better function in memory consolidation. Progressive Effect of lavender extract on spatial memory and maze learning task can be clear by finding difference gene expression in both ALZ and AE200 groups. 49 protein spots were observed in ALZ but not in AE200, in contrary, 26 proteins were only observed in AE200 but not in ALZ group. Comparison between CO and CE200 groups show that CE200 spent less time locating the hidden platform. This positive influence maybe refers to present 80 new proteins that expressed and 104 protein that suppressed in CE200. Direct effect of lavender on AD rats refer to 16 spots newly expressed and 36 spot that suppressed. These findings can disclose that efficiency of lavender on improving memory and learning in normal and alzheimric brain related to suppression and expression of some principal proteins. Applying more proteomics techniques to better understanding of protein changes at the system level can lead to the development of new drug treatments for dementia.
Impact of Saliency and Gaze Features on Visual Control: Gaze-Saliency Interest Estimator

Predicting user intent from gaze presents a challenging question for developing real-time interactive systems like interactive search engine, implicit annotations of large datasets or intelligent robot behavior. Indeed, solutions to annotate easily large sets of images while reducing the burden of annotators is a key aspect for current machine learning techniques. We propose in this paper to design an estimator of the user interest for a given visual content based on eye-tracker feature analysis. We revise existing gaze-based interest estimator, and analyze the impact of the intrinsic saliency of the content displayed for interest estimation. We first explore low-level saliency prediction and propose a new gaze and saliency interest estimator. Experimental results show the advantage of our method for the annotation task in a weakly supervised context. In partic- ular, we extend previous evaluation criteria on new experimental protocol displaying four images by frame as a first step towards "Google Image search-like" interfaces. Our Gaze and Saliency Inter-est Estimator (GSIE) reaches an overall accuracy of 83% in average of user interest prediction. If we consider the accuracy reached in a limited time, the GSIE is 70% in average within about 500ms and 80% in average within 1000ms. This result confirms our GSIE as an efficient real-time visual control solution.
Research on User Clustering Algorithm Based on Software System User Behavior Trajectory

This paper studies and analyzes software system user behavior, proposes a clustering algorithm based on user behavior trajectory data. Through a series of data processing steps, the original user access and operation data are transformed into user behavior trajectory matrix, and the behavior trajectory matrix is normalized. Based on the generated user behavior trajectory matrix, the user behavior information contained in the matrix is quantified, and the concrete steps of user behavior clustering algorithm are proposed. According to this clustering algorithm, the similarity between user behavior trajectories can be calculated, and the users can be clustered according to the set similarity threshold. For users clustered in the same type, these users have similar access or operation habits. Experiment shows that the algorithm has good clustering effect and applicability.
Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning

How to restore back-lit images still remains a challenging task. State-of-the-art methods in this field are based on supervised learning and thus they are usually restricted to specific training data. In this paper, we propose a "zero-shot" scheme for back-lit image restoration, which exploits the power of deep learning, but does not rely on any prior image examples or prior training. Specifically, we train a small image-specific CNN, namely ExCNet (short for Exposure Correction Network) at test time, to estimate the "S-curve" that best fits the test back-lit image. Once the S-curve is estimated, the test image can be then restored straightforwardly. ExCNet can adapt itself to different settings per image. This makes our approach widely applicable to different shooting scenes and kinds of back-lighting conditions. Statistical studies performed on 1512 real back-lit images demonstrate that our approach can outperform the competitors by a large margin. To the best of our knowledge, our scheme is the first unsupervised CNN-based back-lit image restoration method. To make the results reproducible, the source code is available at https://cslinzhang.github. io/ExCNet/.
Deep Reinforcement Learning for Vehicular Edge Computing

The development of smart vehicles brings drivers and passengers a comfortable and safe environment. Various emerging applications are promising to enrich users’ traveling experiences and daily life. However, how to execute computing-intensive applications on resource-constrained vehicles still faces huge challenges. In this article, we construct an intelligent offloading system for vehicular edge computing by leveraging deep reinforcement learning. First, both the communication and computation states are modelled by finite Markov chains. Moreover, the task scheduling and resource allocation strategy is formulated as a joint optimization problem to maximize users’ Quality of Experience (QoE). Due to its complexity, the original problem is further divided into two sub-optimization problems. A two-sided matching scheme and a deep reinforcement learning approach are developed to schedule offloading requests and allocate network resources, respectively. Performance evaluations illustrate the effectiveness and superiority of our constructed system.
CupHunt: Gamification of Social Interaction

Public places are used for many people to pass by without interacting with one another. Introducing a game to be played to this area could create a sense of fulfillment. CupHunt is a casual game which main purpose is to have people interact with one another, providing them with a satisfied feeling. It requires little to no explanation for people to understand and sessions are short, so people can easily play the game in little time. The user experience has been evaluated to show the game's effects
Traffic Sign Recognition Based on Joint Convolutional Neural Network Model

This paper takes the automatic driving technology as the research background, and studies the algorithm and model of traffic sign recognition. Traffic sign recognition is the basis of automatic driving. This paper takes common traffic signs as the research object, and uses the current international standard traffic sign image database GTSRB as the data set of this paper. According to the development status of deep learning and image recognition technology in recent years, this paper analyzes and compares several different image recognition models in ImageNet competition. Based on these experimental results, a new joint network model is proposed, which overcomes some The shortcomings of the existing model, using the model to test on the GTSRB data set, can be found that the model has faster training convergence speed and better recognition accuracy for the GTSRB data set.
A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition

Sensing signal quality affects signal processing efficiency, feature extraction, and learning accuracy. An efficient and accurate assessment of sensing system signal quality is essential for 1) large-scale cyber-physical system deployment and 2) datasets sharing and comparison. In this paper, we present a signal quality assessment -- S-score -- for vibration-based human sensing applications from two aspects -- the hardware implementation and the deployment structure. The 1) signal-to-noise ratio and 2) the signal frequency response consistency over 2.1) sensing hardware, and 2.2) deployment structure are essential factors for structural vibration sensing signal evaluation. The S-score metrics combines these factors to a value between 0 and 1 with application-oriented weights. We compared the proposed metrics to two baselines, and our metrics achieved the highest correlation to the system performance, which is the indicator of the data quality.
Development of an Acoustic AR Gamification System to Support Physical Exercise

In recent years, running has become increasingly popular as an effective exercise activity which could help improve and maintain one's physical health. However, it is generally difficult to motivate people to adhere to their fitness regimens and persist in such activities. To help address this problem, we developed a Gamified Acoustic AR running support system where we use the previous running records of a user to project a "Virtual runner" into an augmented reality space for runners to compete against. The presence of the virtual runner is conveyed through the sound of running footsteps and breathing: users hear the sound of the virtual runner while they are running and are able to virtually compete against themselves in real time. In this paper, we describe how such a system could be implemented and discuss the results of an experiment study which highlights the effectiveness of our Gamified AR system.