Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of apolipoprotein M and its association with adiponectin in an obese mouse model

The aim of the present study was to explore the association between apolipoprotein M (ApoM) and adiponectin, and the underlying mechanism, via observation of ApoM expression in an obese mouse model. For in vivo experiments, mice were randomly distributed into four groups: Control group, obese group, obese group treated with adiponectin, and normal group treated with adiponectin. Body weight, plasma adiponectin, blood glucose and fasting insulin were measured and visceral adipose tissue was weighed at the end of the experiment. ApoM and transcription factor forkhead box A2 (Foxa2) mRNA expression in the mouse liver was evaluated and the protein level of ApoM detected. For in vitro experiments, an insulin-resistant (IR) hepatic cell model was established by inducing the HepG2 cell line with a high concentration of insulin. Following treatment with adiponectin, changes in ApoM and Foxa2 mRNA expression and ApoM protein expression were evaluated in the control and IR HepG2 cells. Results demonstrated that compared with the control group, body weight, visceral adipose tissue weight, blood glucose, fasting insulin and insulin-resistance index (HOMA-IR) were significantly increased in the obese group, whilst plasma adiponectin, ApoM mRNA expression, Foxa2 mRNA expression and ApoM protein in the mouse liver were all significantly decreased. Following intervention with adiponectin in obese mice, blood glucose, insulin and HOMA-IR were significantly decreased, whilst plasma adiponectin, ApoM mRNA expression, Foxa2 mRNA expression and ApoM protein were all significantly increased. However, no significant difference was observed in visceral adipose tissue weight following the intervention of adiponectin in obese mice. In vitro, in the absence of intervention, ApoM and Foxa2 mRNA expression and ApoM protein expression were significantly lower in IR HepG2 cells compared with HepG2 cells. Following intervention with adiponectin on IR HepG2 cells, ApoM and Foxa2 mRNA expression and ApoM protein expression were significantly increased. However, the intervention did not have any effect on HepG2 cells. In conclusion, intervention with adiponectin elevated ApoM mRNA expression, potentially via relieving IR and upregulating Foxa2 mRNA expression.
Biomarkers and smart intracranial devices for the diagnosis, treatment, and monitoring of high-grade gliomas: a review of the literature and future prospects

Abstract Glioblastoma (GBM) is the most common primary brain neoplasm with median overall survival (OS) around 15 months. There is a dearth of effective monitoring strategies for patients with high-grade gliomas. Relying on magnetic resonance images of brain has its challenges, and repeated brain biopsies add significant morbidity. Hence, it is imperative to establish a less invasive way to diagnose, monitor, and guide management of patients with high-grade gliomas. Currently, multiple biomarkers are in various phases of development and include tissue, serum, cerebrospinal fluid (CSF), and imaging biomarkers. Here we review and summarize the potential biomarkers found in blood and CSF, including extracellular macromolecules, extracellular vesicles, circulating tumor cells, immune cells, endothelial cells, and endothelial progenitor cells. The ability to detect tumor-specific biomarkers in blood and CSF will potentially not only reduce the need for repeated brain biopsies but also provide valuable information about the heterogeneity of tumor, response to current treatment, and identify disease resistance. This review also details the status and potential scope of brain tumor-related cranial devices and implants including Ommaya reservoir, microelectromechanical systems-based depot device, Alzet mini-osmotic pump, Metronomic Biofeedback Pump (MBP), ipsum G1 implant, ultra-thin needle implant, and putative devices. An ideal smart cranial implant will overcome the blood-brain barrier, deliver various drugs, provide access to brain tissue, and potentially measure and monitor levels of various biomarkers.
Ataxias cerebelosas hereditarias: principales avances neurofisiológicos, clínicos y genéticos

El termino ataxias cerebelosas hereditarias comprende un amplio espectro de trastornos neurologicos en los cuales la ataxia es el sintoma principal. Conforman un complejo grupo de entidades cuyo reconocimiento es esencial para el correcto asesoramiento genetico, el adecuado control clinico y, en algunos casos, el apropiado abordaje terapeutico. La riqueza clinico-semiologica y los avances en la biologia molecular han convertido a las ataxias hereditarias en uno de los temas mas apasionantes de la neurologia. El diagnostico clinico de los subtipos de ataxias es complicado, por la prominente superposicion de fenotipos entre los subtipos geneticos. En este articulo abordamos los principales avances neurofisiologicos, clinicos y geneticos de las ataxias cerebelosas hereditarias. Palabras clave: ataxias cerebelosas hereditarias, asesoramiento genetico, biologia molecular, fenotipos.
Human action recognition in videos with local representation

This thesis targets recognition of human actions in videos. Action recognition can be defined as the ability to determine whether a given action occurs in the video. This problem is complicated due to the high complexity of human actions such as appearance variation, motion pattern variation, occlusions, etc. Recent advancements in either hand-crafted or deep-learning methods significantly improved action recognition accuracy. But there are many open questions, which keep action recognition task far from being solved. Current state-of-the-art methods achieved satisfactory results mostly base on features, which focus on a local spatio-temporal neighborhood. But human actions are complex, thus the following question that should be answered is how to model a relationship between local features, especially in spatio-temporal context. In this thesis, we propose 2 methods which try to answer that challenging problem. In the first method, we propose to measure a pairwise relationship between features with Brownian Covariance. In the second method, we propose to model spatial-layout of features \wrt person bounding box, achieving better or similar results as skeleton based methods. Our methods are generic and can improve both hand-crafted and deep-learning based methods. Another open question is whether 3D information can improve action recognition. Currently, most of the state-of-the-art methods work on RGB data, which is missing 3D information. In addition, many methods use 3D information only to obtain body joints, which is still challenging to obtain. In this thesis, we show that 3D information can be used not only for joints detection. We propose a novel descriptor which introduces 3D trajectories computed on RGB-D information. Finally, we claim that ability to process a video in real-time will be a key factor in future action recognition applications. All methods proposed in this thesis are ready to work in real-time. We proved our claim empirically by building a real-time action detection system, which was successfully adapted by Toyota company in their robotic systems. In the evaluation part, we focus particularly on daily living actions -- performed by people in their daily self-care routine. In the scope of our interest are actions like eating, drinking, cooking. Recognition of such actions is particularly important for patient monitoring systems in hospitals and nursing homes. Daily living action recognition is also a key component of assistive robots. To evaluate the methods proposed in this thesis we created a large-scale dataset, which consists of 160~hours of video footage of 20~senior people. The videos were recorded in 3~different rooms by 7~RGB-D sensors. We have annotated the videos with 28 action classes. The actions in the dataset are performed in un-acted and unsupervised way, thus the dataset introduces real-world challenges, absent in many public datasets. Finally, we have also evaluated our methods on publicly available datasets: CAD60, CAD120 and MSRDailyActivity3D. Our experiments show that the methods proposed in this thesis improve state-of-the-art results.
Nutrition, Hygiene and Stimulation Education for Impoverished Mothers in Rural Uganda: Effect on Maternal Depression Symptoms and Their Associations to Child Development Outcomes

Optimal nutrition improves child development, and impaired development is associated with maternal depression symptoms, in particular in low resource settings. In this follow-up of an open cluster-randomized education trial, we examined its effects among mothers in rural Uganda on their depression symptoms and the association of these symptoms to child development. The education comprised complementary feeding, stimulation, and hygiene. We assessed 77 intervention mothers and 78 controls using Beck Depression Inventory-II (BDI-II) and Center for Epidemiologic Studies Depression Scale (CES-D) scores. Child development was assessed with Bayley Scales of Infant and Toddler Development-III (BSID-III) composite scores for cognitive, language and motor development. Compared to controls, the intervention reduced depression symptoms’ scores with mean (95% CI) differences: −8.26 (−11.49 to −1.13, p = 0.0001) and −6.54; (−8.69 to −2.99, p = 0.004) for BDI II at 20–24 and 36 months, respectively. Similar results were obtained with CES-D. There was a negative association of BDI-II scores and BSID-III cognitive and language scores at 20–24 (p = 0.01 and 0.008, respectively) and 36 months (p = 0.017 and 0.001, respectively). CES-D associations with BSID-III cognitive and language scores showed similar trends. BSID-III motor scores were associated with depression scores at 36 months for both BDI-II and CES-D (p = 0.043 and 0.028, respectively). In conclusion, the group education was associated with reduced maternal depression scores. Moreover, the depression scores were inversely associated with child cognitive and language development outcomes.
Incorporating Oral Health Care in Pediatric Primary Care Practice

The most common chronic disease in childhood is dental caries and is more prevalent than asthma and hay fever (HHS, 2000). Data show that in the United States from 2011-2014, 24% of children aged 2-5 years had experienced dental caries in their primary teeth, with 11% having untreated caries (Dye et al., 2017). Primary care clinicians have an important role to play in promoting children’s oral health as much as dentists because they have more contact with children. The purpose of this evidencebased practice project was to integrate an evidence-based oral health program for children in a pediatric primary care practice. A comprehensive literature search utilizing 6 databases and hand search yielded 14 relevant articles. The articles were appraised for quality using the Johns Hopkins Nursing Evidence-Based Practice Research and Non-Research appraisal tools and level of evidence using The Melnyk and FineoutOverholt’s (2015) Hierarchy of Evidence for intervention questions. The participants of the project comprised of 80 children aged from 6-months up to 6 years old received preventive oral health care services over a 3-month time. Interventions included: a) caries risk assessment, b) application of fluoride varnish, c) caregiver education, and d) referrals to a dentist for establishment of dental home and care for children at risk of developing dental caries. The Health Belief Model (Hochbaum, Kegels, & Rosenstock, 1952) and the Iowa Model Revised (Iowa Model Collaborative, 2017) were used to guide the project. Primary outcomes were fluoride varnish application rate, dental referral success rate, and adherence by caregivers to oral health recommendations. Data were collected using a questionnaire and will be analyzed. Implications of this project for practice will be discussed. ORAL HEALTH IN PEDIATRIC PRIMARY CARE PRACTICE 1
Public knowledge, attitude and practice toward diabetes mellitus in Hail region, Saudi Arabia

Background: There is a rapid increase in the number of people with type II diabetes worldwide with many preventable cases. Diabetes control or prevention is partially influenced by the individual’s knowledge, attitude and practice toward the disease. Objective: The aim of this study was to determine the general public knowledge, attitude and practice toward diabetes in the region of Hail, which is located northern of the Saudi capital. Methodology: This is a cross-sectional study conducted during the period of March 2018 until September 2018. We randomly selected participants over the age of 18 years at different locations. Results: A total of 738 participants (428 females and 310 males) with and an age range of 18–61 years and mean age of 35±12 were surveyed. The majority of the participants, regardless of education levels, residence and employment status showed high knowledge of diabetes (82%) and knew that physical activity can positively affect/prevent diabetes. Participant's age was found to have a significant association with participant's knowledge of diabetes with the ≥35 year old group knew the different types of diabetes (p<0.001) and knew that high carbohydrate consumption can increase the risk of diabetes (p<0.001), but only the younger group <18 year old's identified diabetes as a genetic disorder (p<0.001). Conclusion: The high knowledge of the disease and its risk factors were not truly mirrored in the participant’s attitude and practice toward the disease. Therefore, it is quite essential for the local health authorities to implement awareness programs to improve public attitude and practice toward diabetes.
Role of various modalities in the management of compound grade 3A and 3B fractures of tibia

Tibia is most frequent site of an open fracture, with incidence ranging from 49.4% to 63.2%. India has the highest road accident rates in the world one of every forty two vehicle in country had met with an accident. Out of 30 patients 15 patients treated by external fixation and imil nailing and 7 patients by external fixation and ilizarov, 8 patients by ilizarov fixation. Skin grafting done in 12 cases and flap coverage in 4 cases. Over all good to excellent results seen in 20 cases, fair in 6 cases and poor in 4 cases. Early intervention and aggressive soft tissue management in open tibial fractures result in decreased number of procedures, minimal hospital stay and early return to their daily activity.
Open-Ended Measurement of Whole-Body Movement: A Feasibility Study

As the importance of embodiment emerges for psychology, there is a need to advance methodology for measuring the dynamics of movement in an open-ended fashion. Such a tool should be versatile across contexts and track spontaneous and natural movement with minimal constraints. We test the feasibility of a method for measuring whole-body movement over time that attempts to meet this need. We use a motion capture system comprised of two Microsoft Kinect version 2.0 cameras and iPiSoft Motion Capture software, and compare its estimates of magnitude rotational velocity and whole-body movement complexity (multivariate multiscale sample entropy; MMSE) to that of a gold standard motion capture system across a variety of movement sequences. The candidate system satisfactorily estimated the instantaneous velocity of 13 body segments in agreement with the gold standard system across movement sequences demonstrating initial feasibility of this process. Summary calculations of velocity by sequence and MMSE calculations were also in high agreement with the gold standard, crucially suggesting that the candidate system could pick up on the complex dynamics of movement over time. The candidate system was feasible and demonstrates preliminary validity for general use in the tracking of continuous human movement for clinical and experimental psychology. We also provide R code and sample data for the importing and processing of movement data exported from iPiSoft Motion Capture Studio.
Gaps in the evidence for fertility treatment—an analysis of the Cochrane Menstrual Disorders and Subfertility Group database

BACKGROUND: The randomized controlled trial is considered the best approach to assess the effectiveness of treatments. The aim was to summarize the available evidence and determine gaps in the evidence for clinical decision making in subfertility. METHODS: A search of the Cochrane Library for Menstrual Disorders and Subfertility Group reviews was undertaken and, where the reviews were related to subfertility, the authors' conclusions were appraised and correlated with the results and meta-analysis sections of the reviews. Each review was then categorized as to what extent it had answered the clinical question posed by the reviewers. RESULTS: Of 38 subfertility reviews currently or previously published on the Cochrane Library from the Menstrual Disorders and Subfertility Group, 12 reviews concluded that there was evidence of effectiveness of the interventions studied. There was insufficient evidence of effectiveness in 26 reviews, from which the authors of 23 reviews called for further research. A tabulated summary of the review conclusions is presented. CONCLUSION: Cochrane subfertility reviews have eliminated some gaps in the evidence and highlighted others. Future clinical trial design should focus on adequate power and reporting the major outcome of live-births per couple as well as adverse events.
Computer Security and Software Watermarking Based on Return-oriented Programming

Applications of computer security issues are limited to the operating systems and gadgets used within the computers and all other devices integrated with supercomputers. With the growing number of users, software developers face the software piracy which could affect the computer systems. Currently, the major problem for computers in the different industries is software piracy. Despite many computer security techniques, we have proposed a software watermark design based on return-oriented programming (ROP). Here, the new design of the software watermark is considered as a method in which secure Hash algorithm plays an important role to enhance the performance of the computer security. In this method, we focused on gadgets analysis gadgets categories and a large number of gadgets. In this analysis, we selected Sjeng benchmark and ROP with different approaches. As a theoretical result, resilience and stealthy are compared with existing results. This approach can be useful to improve the application of the computer security laws with legal procedures depended on the proposed computer security algorithms and analysis.
Study on PLC with Switch Management in Intelligent Manufacturing Network

abstract This paper discusses a new solution for switch management in intelligent manufacturing network. It makes PLC (Programmable Logic Controller) communication module have the switch management features and exchange I/O data in manufacturing network. The switch manager has used the chip of the Ethernet switch device 88E6165. The Marvell 88E6165 device embedded in communication devices is a single-chip 6 port gigabit Ethernet switch with five integrated gigabit Ethernet transceivers. It performs the tasks of switch management, a series of services and applications are supported in PLC when it is running in a manufacturing network. It also analyzes the potential network topologies in which our customers may use the communication module and how the communication module’s architecture facilitates these topologies. Actors associated with the switch management service are described further. It proposes a new mechanism to minimize the congestion based on the measure of taking an adaptive decision during transferring multicast messages to handle multicast message growing with industrial Ethernet for manufacturing systems. Proposed approach is to accomplish a device requesting to start and stop the reception of the multicast streams. It joins and leaves message requests through IGMP. Final, an application prototype system contains various devices and the global architecture is proposed to provide transparency between control network and device (IO) network.
Making Pictures, Writing about Pictures, Discussing Pictures and Lecture-Discussion as Teaching Methods in Art History

This article discusses making pictures, writing about pictures, discussing pictures, and lecture-discussion as methods of teaching art history in Finnish Upper Secondary Vocational Education and Training (Qualification in Visual Expression, Study Programmes in Visual and Media Art Photography). A total of 25 students majoring in Visual Expression participated in the research by studying art history using picturebased–visual and verbal–methods and reflecting on their learning experiences. This article introduces the concept of ‘contextual subject-related didactics,’ by which conceptions of contemporary art history, together with the objectives and aims of the curriculum, guide the choice of teaching methods. The article argues that various picture-based teaching methods intertwine reason and emotion, generating profound learning experiences in the field of art history, and developing knowledge of art history and the skills requires to act on the basis of such knowledge. 1 Martikainen: Picture-Based Teaching Methods in Art History Published by CUNY Academic Works, 2017
An efficient hardware implementation of SM4

SM4 is widely used in WLAN WAPI resource restricted devices. This paper proposes an 8-bit iteration structure of SM4 at ultra-low cost, which manages key expansion and encryption working alternately with only one S-Box. Furthermore to minimize the area, on-the-fly key expansion mechanism is utilized to reserve the memory for round keys and constants keys are generated by equation dynamically instead of reading from large look-up table. The area results of its ASIC hardware implementation show that the gate count of our design is only 2.51 K, gaining almost 18.0% area reduction compared to the latest works.
Scalable Feature Selection and Extraction with Applications in Kinase Polypharmacology

OF THESIS Scalable Feature Selection and Extraction with Applications in Kinase Polypharmacology In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in order to decrease the amount of expert knowledge required to model interactions between proteins and drug molecules.