Miracle-dz/UniFAR-FTUs huggingface dataset:
Representation Learning on Graphs by Integrating Content and Structure Information

The problem of representation learning on graph can be difficult due to limited knowledge of training data and large presence of missing edges. Real-world social networks do not provide complete information about the network due to hidden information and privacy constraints. In such scenarios, typical representation learning methods are not able to capture network information effectively. In order to make them more useful, any available feature information can be used in addition to the network structure. In this paper, we aim to learn better representations by exploiting both content (or feature) information of nodes and structural information of the network. Our approach leverages generative adversarial networks to learn embedding for generator and discriminator in a minimax game. While the generator estimates the neighborhood of a node, the discriminator distinguishes between the presence or absence of a link for a pair of nodes. We demonstrate the effectiveness of our approach on five real-world publicly available datasets on the problems of link prediction and node classification. On both tasks, we achieve significant gains, outperforming current state-of-the-art methods by considerable margins. Our code is available on Github 1.
A neurocomputational model for prostate carcinoma detection

Current guidelines for prostate carcinoma screening rely primarily on the digital rectal examination (DRE) and prostate specific antigen (PSA). Well described patient risk factors for prostate carcinoma also include age, ethnicity, family history, and complexed PSA. However, due to the nonlinear relation of each of these variables with prostate carcinoma, it is difficult to predict reliably each patient's risk based on linear univariate analysis. The authors investigated a neural network to model the risk of prostate carcinoma by seven readily available clinical features.
Detailed Placement for IR Drop Mitigation by Power Staple Insertion in Sub-10nm VLSI

Power Delivery Network (PDN) is one of the most challenging topics in modern VLSI design. Due to aggressive technology node scaling, resistance of back-end-of-line (BEOL) layers increases dramatically in sub-10nm VLSI, causing high supply voltage (IR) drop. To solve this problem, pre-placed or post-placed power staples are inserted in pin-access layers to connect adjacent power rails and reduce PDN resistance, at the cost of reduced routing flexibility, or reduced power staple insertion opportunity. In this work, we propose dynamic programming-based single-row and double-row detailed placement optimizations to maximize the power staple insertion in a post-placement flow. We further propose metaheuristics to improve the quality of result. Compared to the traditional post-placement flow, we achieve up to 13.2% (10mV ) reduction in IR drop, with almost no WNS degradation.
Mentally Retarded Children

soon. Indecision or haste or the forcing of medication will only fan the flames of fear and uncertainty (&dquo;If there is nothing wrong ivith me, why must I take medicine,&dquo; they will wonder) and prolong both the distress and the attack itself. The only physical measure to use is ~~8y inhalation ; this is easy to administer by rebreathing into a paper bag, and is such a commonplace practice as a treatment for hiccups that it does not alarm impressionable teenagers. Hysteria is clearly easier to recognize after a public event such as a rock ’n roll concert, but this and the &dquo;hyperventilation syndrome&dquo; must always be considered when groups of girls in their earlyF teens begin to collapse for no apparent reascrr~. -~~~~~as C. FAIGEL, M.D., 123 York Street, New ~3caven. , Connecticut 06511.
Proteomic profiling reveals a catalogue of new candidate proteins for human skin aging

Abstract: Studies of skin aging are usually performed at the genomic level by investigating differentially regulated genes identified through subtractive hybridization or microarray analyses. In contrast, relatively few studies have investigated changes in protein expression of aged skin using proteomic profiling by two‐dimensional (2‐D) gel electrophoresis and mass spectrometry, although this approach at the protein level is suggested to reflect more accurately the aging phenotype. We undertook such a proteomic analysis of intrinsic human skin aging by quantifying proteins extracted and fluorescently labeled from sun‐protected human foreskin samples pooled from ‘young’ and ‘old’ men. In addition, we analyzed these candidate gene products by 1‐D and 2‐D western blotting to obtain corroborative protein expression data, and by both real‐time PCR (RT‐PCR) and microarray analyses to confirm expression at the mRNA level. We discovered 30 putative proteins for skin aging, including previously unrecognized, post‐translationally regulated candidates such as phosphatidyl‐ethanolamine binding protein (PEBP) and carbonic anhydrase 1 (CA1).
2012 revised International Chapel Hill Consensus Conference Nomenclature of Vasculitides.

2012 Revised International Chapel Hill Consensus Conference Nomenclature of Vasculitides J. Jennette;R. Falk;P. Bacon;N. Basu;M. Cid;F. Ferrario;L. Flores-Suarez;W. Gross;L. Guillevin;E. Hagen;G. Hoffman;D. Jayne;C. Kallenberg;P. Lamprecht;C. Langford;R. Luqmani;A. Mahr;E. Matteson;P. Merkel;S. Ozen;C. Pusey;N. Rasmussen;A. Rees;D. Scott;U. Specks;J. Stone;K. Takahashi;R. Watts; Arthritis & Rheumatism
Optimal Allocation of Online Content Combination Pricing under Mixed Revenue Mode

The development of Internet makes the rapid expansion of the business model based on providing online content service to online users. In recent years, the promotion of the payment model has brought new profit increasing point for content service providers. Single-on-demand payment and bundling subscription payment are widely used payment methods. If the two modes are combined, the service providers will often get more benefits. So in the mixed revenue model, online content service providers need to decide how to set a reasonable price for each charge mode in order to maximize expected revenue. In this paper, the user’s value estimation model is constructed based on time preference theory and loss aversion theory. Furthermore, the variable neighborhood search algorithm is used to simulate and verify the optimal pricing strategy of various charging model combinations.
Design of Highly Linear Broadband Continuous Mode GaN MMIC Power Amplifiers for 5G

In this paper, we present a design approach for broadband harmonic-tuned monolithic microwave integrated circuit (MMIC) power amplifiers (PAs). Two harmonic matching networks are proposed for the realization of continuous class-B and class-F modes in an integrated PA. A design procedure is developed for integrated PAs using these matching networks to achieve high linearity, broadband operation, and compact chip area, in the presence of parasitic components and the physical limitations of the MMIC process. Two proof-of-concept fully integrated PAs are implemented in a 0.25- $\mu \text{m}$ GaN-on-SiC process. Output power of 34.2–36.4 dBm with 40% to 49% power-added efficiency (PAE) is achieved in 4.2–7.0 GHz (51.6% fractional bandwidth), from the continuous class-B PA with only 1.5-mm2 chip area. Furthermore, the continuous class-F PA achieves 36.2 dBm output power and 52% PAE at 5.0 GHz. The PAs are also characterized using QAM signals with wide bandwidth, in order to evaluate their performance for 5G wireless applications. For a 64-QAM signal with 100-MHz bandwidth and 8 dB peak-to-average power ratio (PAPR), the continuous class-B PA achieves 29.3 dBm average output power, 28% average PAE, and −25dB (5.5%) error vector magnitude (EVM). The continuous class-F PA, tested using a 200 MHz 256 QAM signal with 8.5 dB PAPR, provides an average output power of 28.5 dBm, average PAE of 27%, and −28 dB (4%) EVM, without any pre-distortion.
Metformin administration is more effective when non-obese patients with polycystic ovary syndrome show both hyperandrogenism and hyperinsulinemia

Background. Polycystic ovary syndrome (PCOS) is a common endocrine disease that is frequently observed to be related to increased insulin resistance independent of body weight. The use of insulin-sensitizer compounds, such as metformin, permits great improvement of such metabolic abnormality, restoring ovarian function and gonadal steroid synthesis and reducing insulin resistance. Aim. On this basis we aimed to evaluate a group of non-obese amenorrheic PCOS patients before and after 6 months of metformin administration (500 mg orally twice daily) to better understand upon which basis of clinical and endocrine parameters metformin administration might be chosen as a putative therapeutic tool. Method. A group of non-obese PCOS patients (n = 42) was enrolled after informed consent. They underwent an oral glucose tolerance test for insulin, glucose and C-peptide levels and provided blood samples for determination of plasma levels of luteinizing hormone (LH), follicle-stimulating hormone, prolactin, estradiol, androstenedione, 17-hydroxyprogesterone, insulin, cortisol and testosterone levels on two occasions: before and on day 7 of the first menstrual cycle occurring after the 5th month of treatment. Results. Plasma LH, estradiol, insulin and C-peptide were decreased significantly by metformin treatment in the entire group of PCOS patients. When subdividing PCOS patients according to insulin sensitivity (i.e. hyper- and normoinsulinemic subjects), a greater rate of positive endocrine changes was observed in hyperinsulinemic patients and the highest rate was observed in hyperinsulinemic hyperandrogenic subjects. Menstrual cyclicity was recovered in all patients under treatment. Conclusions. Our data show that metformin modulates ovarian function and greatly affects LH secretion through reduction of the hyperandrogenic condition. The highest rate of endocrine changes was observed in the hyperinsulinemic hyperandrogenic non-obese PCOS patients. Our study demonstrates that metformin administration is more appropriate in hyperinsulinemic hyperandrogenic non-obese PCOS patients.
Dinnertime and bedtime routines and rituals in families with a young child with an autism spectrum disorder.

BACKGROUND/AIM Routines are thought to be critical in laying the foundation for ritual development, and in turn rituals are considered important for forming a strong and healthy family unit. This article provides a description of the experiences of dinnertime and bedtime routines and rituals in Australian families with a young child with an Autism Spectrum Disorder (ASD), as well as common challenges experienced. METHODS Fourteen Australian mothers with a young child with an ASD between the ages of two and five years were interviewed about their performance of dinnertime and bedtime routines and rituals and their perceptions of both occupations. Descriptive qualitative interviews were audio taped and transcribed. Transcripts were analysed using thematic content analysis. RESULTS Two overarching themes emerged, including 'centred on ASD' and 'ASD alters meaning'. Mothers' descriptions revealed that families with a young child with an ASD experienced unstructured and chaotic routines at dinnertime. In contrast, bedtime involved the performance of more structured, and at times, non-functional routines. Moreover, dinnertime was bereft of meaningful interactions and rituals, whereas bedtime contained some positive meaningful interactions and rituals. CONCLUSIONS Occupational therapists need to consider supporting mothers and the child with an ASD in enhancing their participation within all aspects of family life, by encouraging them to develop structured and more predictable dinnertime and bedtime routines inclusive of all family members. In doing so, this action will support mothers to develop a strong and cohesive family unit.
New Approach to Determine DDoS Attack Patterns on SCADA System Using Machine Learning

Recently, the importance of Supervisory Control and Data Acquisition (SCADA) systems has grown for many industries around the world. These systems are controlling many vital infrastructures such as grids of power, plants, and water treatment systems. In fact, nowadays SCADA systems cannot be isolated from the public and thus being more vulnerable and exposed to many malicious attacks. Several studies have reviewed the latest developments in cyber-security risks for SCADA systems and found that many factors are responsible for increasing the amount and the level of risks on modern control systems. Among such factors are the network architecture and the reliance on standard technologies that have known vulnerabilities. In this paper, we attempt to improve a framework of SCADA system against Distributed Denial of Service (DDoS) attacks using three machine learning algorithms (i) J48; (ii) Naive Bayes; (iii) Random Forest to determine the attack patterns. These algorithms were trained and evaluated on KDDCup’99 dataset. The preprocessing phase of the dataset was conducted based on the goal of the paper and the obtained results showed that the best classification is obtained using Random Forest classifier (RF) with 99.99% accuracy rate, while Naïve Bayes classifier has the lowest accuracy rate of 97.74%.
A Virtual Rider for Motorcycles: Maneuver Regulation of a Multi-Body Vehicle Model

This work develops a virtual rider that can be used to make a multi-body two-wheeled vehicle follow a specified ground path with a prescribed velocity profile. The virtual rider system is based on a simplified motorcycle model, the sliding plane motorcycle, which is composed of a single rigid body with two ground contact points. This reduced order nonlinear system was presented in an earlier work, together with a dynamic inversion procedure for computing a state-control trajectory corresponding to the desired task. This dynamic inversion procedure is combined in this work with a maneuver regulation controller to yield a nonlinear feedback control strategy. A transverse coordinate system that is consistent with the mechanical symmetries of ground vehicles is constructed and used in the development of the maneuver regulation controller. An inverse optimal control strategy, which also exploits the mechanical symmetries, is developed to shape the dynamic response of the closed loop system. Numerical results with the virtual rider driving a multi-body vehicle through a demanding maneuver with lateral accelerations reaching 1 g are presented.
[Status on knowledge, attitudes, behavior regarding nutrition and food safety among 4-6 grade students from Chinas' two poverty-stricken counties].

OBJECTIVE To investigating knowledge, attitudes, current behavior among primary school students on nutrition and food safety in two State-level poverty-stricken counties, and to explore the best educational model on nutrition and food safety. METHODS 478 pupils at 4-6 grades were selected, using the method of stratified cluster sampling and questionnaire. RESULTS The average score on knowledge was 18.66 ± 3.75, with the qualified rate as 61.09% (the highest was 60.6%). The average score in the section of attitude was 5.82±1.50. More than 97% of the students agreed that it was necessary to receive knowledge on nutrition and food safety. The average score of behavior was 8.52±2.56. CONCLUSION Rate of awareness on knowledge of nutrition and food safety had greatly improved among the students under study. Their habit tended to be more regular. However, we also noticed the gap between knowledge and behavior on this issue.
Controlled trial of fluorouracil and low-dose leucovorin given for 6 months as postoperative adjuvant therapy for colon cancer.

PURPOSE The goal of this study was to determine the efficacy of intensive-course fluorouracil (5FU) plus low-dose leucovorin given for 6 months following potentially curative resection of colon cancer. PATIENTS AND METHODS Three hundred seventeen patients with high-risk stage II or stage III colon cancer were randomly assigned 3 to 4 weeks following surgery to receive either (1) chemotherapy with six cycles of 5FU (425 mg/m2) plus leucovorin (20 mg/m2) by rapid intravenous injection daily for 5 consecutive days every 4 to 5 weeks, or (2) observation. RESULTS The median follow-up duration is 72 months for patients still alive. Patients who received postoperative 5FU plus leucovorin experienced significant improvement in time to relapse (P < .01) and survival (P = .02) compared with control patients treated with surgery alone. Stomatitis, diarrhea, and leukopenia were the predominant chemotherapy toxicities. There were no treatment-related deaths. CONCLUSION These results indicate that intensive-course 5FU plus low-dose leucovorin is effective in preventing tumor relapse and improving survival in patients with high-risk colon cancer. These benefits were seen with only six cycles of treatment, using low-dose leucovorin in combination with 5FU on a schedule convenient for outpatient administration.
Suspected Pediatric Ingestions: Effectiveness of Immunoassay Screens vs. Gas Chromatography/Mass Spectroscopy in the Detection of Drugs and Chemicals

Abstract Rapid and accurate analytical testing can be of great value when determining treatment for pediatric patients suspected of ingesting an unknown chemical. Though often overlooked, gas chromatography/mass spectroscopy (GC/MS) can be a valuable resource in emergency toxicology testing. In a recent 24‐month period (July 1999–June 2001), the Analytical Toxicology Laboratory at the University of Mississippi Medical Center, Jackson, MS, compared the results of GC/MS analysis to results obtained by immunoassay testing. The laboratory tested 139 urine samples referred for STAT toxicology testing from the hospital's Pediatric Emergency Department. All samples were tested in parallel using an immunoassay technique (EMIT®) and GC/MS. With analysis by immunoassay, 17.3% of the samples were positive for a drug of abuse. The number of positive drug classes ranged from 0 to 2 per sample (mean 0.17 ± 0.43) using immunoassay. With analysis by GC/MS, drugs were detected in 88.5% of the samples. The number of drugs detected ranged from 0 to 11 per sample (mean 2.2 ± 1.8) with GC/MS. A total of 64 different pharmaceuticals were identified by GC/MS. This study shows that analysis by GC/MS offers the clinician a more comprehensive view into the exposure of the pediatric patient presenting with an unknown chemical ingestion.
Isolation of High Density Lipoprotein Subclasses by Electrofiltration and Their Chemical Components

Abstract The exact role of high density lipoprotein in atheroprotection is not well understood yet due to its complex nature; it comprises more than ten subclasses that vary in size, composition, and function. Isolation and characterization of these subclasses is an important step for further studies addressing their functions in health and disease. In this work, we present a novel method that is relatively simple and efficient for isolation of high density lipoprotein subclasses. The method depends on fractional filtration of the subclasses through a preformed gel membrane system under the effect of an electric field, where the stepwise isolation of the subclasses depends on differences in their rates of migration in polyacrylamide gel. Using this design, we were able to isolate seven high density lipoprotein subclasses with relative molecular masses of 42,000–50,000; 71,000; 103,000; 124,000; 150,000; 182,000; and 219,000. All the subclasses contained apolipoprotein A-I, phosphatidylcholine, sphingomyelin, free cholesterol, esterified cholesterol, and triacylglycerols. Some fractions of some samples contained the apolipoproteins A-II, C-I, C-II, C-III, and E. A subclass of molecular mass of 106,000 was identified and isolated from a healthy young subject that contained albumin and apoA-I with some free and esterified cholesterol, but with no triacylglycerols. This electrofiltration technique offers a novel tool for isolating pure native high density lipoprotein subclasses in a concentrated form that can be used directly for detailed studies of their physicochemical and physiological properties.
A Comparative of Neural Network with Metaheuristics for Electricity Consumption Forecast Modelling

This paper attempted to study the efficiency of Artificial Neural Network (ANN) with metaheuristic algorithms for electricity consumption modeling in Thailand. The objective was to compare the study between ANN with Backpropagation algorithm (ANN-BP) and ANN combined with different metaheuristic algorithms: ANN with Harmony Search (ANN-HS), ANN with Artificial Bee Colony (ANN-ABC), ANN with Teaching-Learning-Based Optimization (ANN-TLBO) and ANN with Jaya Algorithms (ANN-JA) models. The models selected Population, Gross Domestic Product (GDP), Imports of goods and services, Exports of goods and services as inputs. The experiment results showed that the ANN-TLBO model had optimal efficiency, while ANN-JA was one of the competitive metaheuristic algorithms that could be implemented to modelling for use in future studies.
Limb girdle muscular dystrophies: classification, clinical spectrum and emerging therapies.

PURPOSE OF REVIEW The aim of the study was to describe the clinical spectrum of limb girdle muscular dystrophies (LGMDs), the pitfalls of the current classification system for LGMDs, and emerging therapies for these conditions. RECENT FINDINGS Close to half of all LGMD subtypes have been discovered within the last 6 years of the 21-year-period in which the current classification system for LGMD has existed. The number of letters for annotation of new recessive LGMD conditions is exhausted, and multiple already classified LGMDs do not strictly fulfill diagnostic criteria for LGMD or are registered in other classification systems for muscle disease. On the contrary, diseases that fulfill classical criteria for LGMD have found no place in the LGMD classification system. These shortcomings call for revision/creation of a new classification system for LGMD. The rapidly expanding gene sequencing capabilities have helped to speed up new LGMD discoveries, and unveiled pheno-/genotype relations. Parallel to this progress in identifying new LGMD subtypes, emerging therapies for LGMDs are under way, but no disease-specific treatment is yet available for nonexperimental use. SUMMARY The field of LGMD is rapidly developing from a diagnostic and therapeutic viewpoint, but a uniform and universally agreed classification system for LGMDs is needed.
Feasibility of Using Early Mesencephalic Neural Plate for Intracerebral Grafting

The purpose of this study was to elucidate the biological significance and the possibility of intracerebral grafting of neuroepithelial stem cells derived from the mesencephalic neural plate. Immunohistological studies of embryonic day 10.5 (E10.5) Wister rats revealed strong nestin expression in the mesencephalic part of the neural plate. Mesencephalic neural plates removed from E10.5 rats were processed to either tissue or cell dissociation culture. They were cultured in vitro under various conditions and were analyzed 7 days after the primary culture. When they were cultured as a tissue, cell proliferation and differentiation into neurons extending long neurites were obvious in a serum-free medium, in a medium containing 3% serum, and in a medium containing 20 ng/ml epidermal growth factor. On the other hand, in a medium containing 10 ng/ml basic fibroblast growth factor (bFGF), both vigorous cell proliferation and sphere formation were recognized. Furthermore, marked neurite growth was rarely seen in this culture. When they were plated in a dissociation culture, cell proliferation and neurosphere generation were also recognized only in a medium containing bFGF, depending on the initial cell concentration. The spheres, generated 7 days after the primary cell culture, were positively stained by nestin. These data suggested that bFGF was able to amplify the stem cell population present in the mesencephalic neural plate derived from early embryos. This might make it possible to obtain a large number of stem cells as donor material for neural transplantation on demand.