Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated annotation of imaging experiments via multi-label classification

We provide baseline performance tests of common problem transformations and machine learning (text mining) methods applied to the problem of automatically classifying or labeling multi-label biomedical research literature. Label terms are from the CogPO ontology, the text corpora are abstracts of published papers, and the methods use the performance of a human expert’s knowledge as training data. We aim to replicates of published papers, and the methods use the performance of a human expert’s knowledge as training data. We aim to replicate the expert’s annotation of labels for the experimental stimuli, cognitive paradigm class, response types, and other relevant dimensions of the experiments. Specific problem transformations tested are the binary relevance and label powerset methods. We use several standard machine learning methods: naive Bayes, k-nearest neighbors, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. This collection of results demonstrates what can be achieved with off-the-shelf software components, little to no pre-processing of raw text, and no serious attempts at optimization. Any more sophisticated methods for automated annotation of neuroimaging experimental methods would need to perform at or above the performance levels demonstrated here to be worth serious consideration as a practical method.
A Review on Various Issues and Applications in Wireless Sensor Networks

: With the enormous advancement in the field of embedded computer and sensor technology, Wireless Sensor Networks (WSNs) have made remarkable impact in today’s world. These WSNs consist of several thousands of sensor nodes deployed randomly, are capable of sensing, actuating, and communicating the collected information. Since wireless sensor networks are constrained by cost, scalability, topology change and power consumption, new technologies are being considered to overcome these and many other issues. This paper focuses on types of WSNs along with ways to overcome these challenges in respective WSNs and need of appropriate sensor for achieving specific application requirement. Use of efficient approach to achieve certain performance parameters has been highlighted.
Assessment of Radioactive Iodine Treatment of Hyperthyroidism in Sudanese Patients

Hyperthyroidism is considered as one of common pathological problem associated with thyroid gland, in which thyroid hormone level were increased. This a prospective study attended to assess the role of thyroid ablation using I-131 in treatment of hyperthyroidism in Sudanese population, A 120 patient were treated by using of I131 at radiation and isotopes center of Khartoum in period from 2012 to 2014. Imaging procedure was done using Tc99m radiopharmaceutical where the Tc99m/ Mo99m Generator was used to produce Tc99m, dose caliber and Dual head Gama camera was used to scan these patient. The level of thyroid hormone were recorded before, and after 3, 6, 9, and 12 month after treatment in order to assess the decrement level of these hormone and therefore performing a quantitative assessment of hyperthyroidism treatment, the result showed that the mean value of these hormones was 6.9, 4.2, 2.8, and 2.5 (nmol/L) for T3, 222.1, 134, 119, 119.2 and 113.4 (nmol/L) for T4, and 0.37, 6.34, 5.3, 2.8, and 2.3 (nmol/L) for TSH respectively. Pair sample two tailed test was performed; a significant difference between the thyroid hormone level was noted before the RAI treatment and after 3, 6, 9, and 12 month later after the treatment, at Confidence level of (CL=95%) and (p value= 0.05), the test were significant at P= 0.000. Causative disease of hyperthyroid function found to be due to Graves’ disease in 45 patient (54%) of the collected samples, 28 (23.3%) by TMNG, 30 (25%) due to Diffuse toxic goiter and 6.7% related to the autonomous toxic nodules. This study concludes the hyperthyroidism treatment using I131 considered effective and cause significant difference in thyroid hormone level after treatment.
Adaptive Gamification for Learning Environments

In spite of their effectiveness, learning environments often fail to engage users and end up under-used. Many studies show that gamification of learning environments can enhance learners’ motivation to use learning environments. However, learners react differently to specific game mechanics and little is known about how to adapt gaming features to learners’ profiles. In this paper, we propose a process for adapting gaming features based on a player model. This model is inspired from existing player typologies and types of gamification elements. Our approach is implemented in a learning environment with five different gaming features, and evaluated with 266 participants. The main results of this study show that, amongst the most engaged learners (i.e., learners who use the environment the longest), those with adapted gaming features spend significantly more time in the learning environment. Furthermore, learners with features that are not adapted have a higher level of amotivation. These results support the relevance of adapting gaming features to enhance learners’ engagement, and provide cues on means to implement adaptation mechanisms.
Experimental Study of Buoyancy Induced Flow and Heat Transfer Through Uniformly Heated Vertical Tube Air Heater

The present work is aimed at studying the effect of different system parameters on the heat transfer on vertical circular tube air heater. They include tube length, tube diameter, and heat flux supplied. Constant heat flux boundary condition is created on the tube surface. Experiment is conducted to investigate the effect of different system parameter on heat transfer and buoyancy induced flow. The heat transfer coefficient was found increasing with increase in heat flux supplied, but it reduces with increase in diameter of the tube and its length. The air outlet temperature was found increasing with increase in heat flux, tube length but reduces with increase in tube diameter. Nusselt number is calculated and was found well within 10% of the results given in the literature.
Persistence to disease-modifying therapies for multiple sclerosis in a Canadian cohort

Purpose To examine the long-term persistence to the first-line injectable disease-modifying therapies (DMTs) for multiple sclerosis (MS) and to identify the factors associated with nonpersistence. Patients and methods We used population-based administrative data from Manitoba, Canada. All adult subjects who were diagnosed with MS and dispensed a first-line injectable DMT (beta-interferon-1b, beta-interferon-1a, and glatiramer acetate) between 1996 and 2011 and had a minimum of 1 year of follow-up were included. The primary outcome was the median time to discontinuation of any DMT. The associations between potential predictors and persistence were estimated using multivariable Cox-proportional hazard models. Results Overall, 721 subjects were followed for a median of 7.8 years (interquartile range 6.1). The median time to discontinuation of all first-line DMTs was 4.2 years (25th and 75th percentile: 1.7, 10.6 years). Of the 451 (62.6%) subjects who discontinued their DMT during the study period, 259 (57.4%) eventually resumed or restarted a DMT. Subjects who were younger when starting a DMT, had prior MS-related hospitalizations, were more recently diagnosed with MS, or had a greater lag time between their MS diagnosis and DMT initiation were more likely to discontinue therapy. Conclusion Over half of the individuals receiving a DMT for MS in Manitoba remained on therapy for at least 4 years. DMT discontinuation occurred in 60% of the cohort, but most restarted a DMT within 1 year. While not all of the factors identified with discontinuing DMT are modifiable, they may help practitioners enhance MS care by identifying individuals who may be at particular risk for DMT discontinuation.
Numerical simulation of X-wing type biplane flapping wings in 3D using the immersed boundary method

The numerical simulation of an insect-sized ‘X-wing’ type biplane flapping wing configuration is performed in 3D using an immersed boundary method solver at Reynolds numbers equal to 1000 (1 k) and 5 k, based on the wing's root chord length. This X-wing type flapping configuration draws its inspiration from Delfly, a bio-inspired ornithopter MAV which has two pairs of wings flapping in anti-phase in a biplane configuration. The objective of the present investigation is to assess the aerodynamic performance when the original Delfly flapping wing micro-aerial vehicle (FMAV) is reduced to the size of an insect. Results show that the X-wing configuration gives more than twice the average thrust compared with only flapping the upper pair of wings of the X-wing. However, the X-wing's average thrust is only 40% that of the upper wing flapping at twice the stroke angle. Despite this, the increased stability which results from the smaller lift and moment variation of the X-wing configuration makes it more suited for sharp image capture and recognition. These advantages make the X-wing configuration an attractive alternative design for insect-sized FMAVS compared to the single wing configuration. In the Reynolds number comparison, the vorticity iso-surface plot at a Reynolds number of 5 k revealed smaller, finer vortical structures compared to the simulation at 1 k, due to vortices’ breakup. In comparison, the force output difference is much smaller between Re = 1 k and 5 k. Increasing the body inclination angle generates a uniform leading edge vortex instead of a conical one along the wingspan, giving higher lift. Understanding the force variation as the body inclination angle increases will allow FMAV designers to optimize the thrust and lift ratio for higher efficiency under different operational requirements. Lastly, increasing the spanwise flexibility of the wings increases the thrust slightly but decreases the efficiency. The thrust result is similar to one of the spanwise studies, but the efficiency result contradicts it, indicating that other flapping parameters are involved as well. Results from this study provide a deeper understanding of the underlying aerodynamics of the X-wing type, which will help to improve the performance of insect-sized FMAVs using this unique configuration.
Chapter 2 Biological Response Modifier in Cancer Immunotherapy

Biological response modifiers (BRMs) emerge as a lay of new compounds or approaches used in improving cancer immunotherapy. Evidences highlight that cytokines, Toll-like receptor (TLR) signaling, and noncoding RNAs are of crucial roles in modulating antitumor immune response and cancer-related chronic inflammation, and BRMs based on them have been explored. In particular, besides some cytokines like IFN-α and IL-2, several Toll-like receptor (TLR) agonists like BCG, MPL, and imiquimod are also licensed to be used in patients with several malignancies nowadays, and the first artificial small noncoding RNA (microRNA) mimic, MXR34, has entered phase I clinical study against liver cancer, implying their potential application in cancer therapy. According to amounts of original data, this chapter will review the regulatory roles of TLR signaling, some noncoding RNAs, and several key cytokines in cancer and cancer-related immune response, as well as the clinical cases in cancer therapy based on them. R. Liu • L. Wang • J. Yang • Y. Deng • E. Huang • J. Qian • Z. Lu • X. Jiang • D. Zhang • Y. Chu (*) Department of Immunology, Key Laboratory of Medical Molecular Virology of MOE/MOH, School of Basic Medical Sciences, Fudan University, No.138, Yi Xue Yuan Rd., mail box 226, Shanghai 200032, People’s Republic of China Biotherapy Research Center, Fudan University, Shanghai 200032, China e-mail: yiweichu@fudan.edu. cn F. Luo Biotherapy Research Center, Fudan University, Shanghai 200032, China Department of Digestive Diseases of Huashan Hospital, Fudan University, Shanghai, China X. Liu Department of Immunology, Key Laboratory of Medical Molecular Virology of MOE/MOH, School of Basic Medical Sciences, Fudan University, No.138, Yi Xue Yuan Rd., mail box 226, Shanghai 200032, People’s Republic of China Department of Dermatology, Shenzhen Hospital, Peking University, Shenzhen, Guangdong 518036, China © Springer Science+Business Media Dordrecht 2016 S. Zhang (ed.), Progress in Cancer Immunotherapy, Advances in Experimental Medicine and Biology 909, DOI 10.1007/978-94-017-7555-7_2 69
Neural fitted actor-critic

A novel reinforcement learning algorithm that deals with both continuous state and action spaces is proposed. Domain knowledge requirements are kept minimal by using non-linear estimators and since the algorithm does not need prior trajectories or known goal states. The new actor-critic algorithm is on-policy, offline and model-free. It considers discrete time, stationary policies, and maximizes the discounted sum of rewards. Experimental results on two common environments, showing the good performance of the proposed algorithm, are presented.
Identification of CSF biomarkers by proteomics in Guillain-Barré syndrome

The purpose of the present study was to screen for differentially expressed proteins in the cerebrospinal fluid (CSF) of patients with Guillain-Barré syndrome (GBS). The identification of differentially expressed protein can provide new targets for understanding the pathogenic mechanism, early clinical diagnosis, prognosis and for measuring the effectiveness of interventions. We enrolled 50 GBS patients and 50 meningitis patients (control group) to compare protein expression in CSF. The GBS cases included 28 cases of acute inflammatory demyelinating polyneuropathy (AIDP) and 22 cases of acute motor axonal neuropathy (AMAN). We then performed two-dimensional differential in-gel electrophoresis combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to identify the differentially expressed proteins. The expression levels were validated by ELISA, and their accuracy, sensitivity, and specificity in GBS diagnosis were analyzed by the receiver operating characteristic curve. Three differentially expressed proteins were identified, including the upregulated haptoglobin (Hp) and heat shock protein 70 (Hsp70), and downregulated cystatin C. There were no significant differences between the AIDP and AMAN patients in the positive rates and quantitative expression levels of the three differentially expressed proteins. The accuracy of Hp in the diagnosis of GBS was 0.835, sensitivity was 86.7%, and specificity was 88.2%. The accuracy of cystatin C in the diagnosis of GBS was 0.827, sensitivity was 85.5%, and specificity was 89.7%. The accuracy of Hsp70 in the diagnosis of GBS was 0.841, its sensitivity was 87.8%, and its specificity was 92.3%. Hp and Hsp70 are significantly increased, and cystatin C is downregulated in CSF of GBS patients, which provides important biomarkers for early GBS diagnosis, although these proteins cannot distinguish AIDP and AMAN.
Susceptibility Testing of Medically Important Parasites

SUMMARY In the last 2 decades, renewed attention to neglected tropical diseases (NTDs) has spurred the development of antiparasitic agents, especially in light of emerging drug resistance. The need for new drugs has required in vitro screening methods using parasite culture. Furthermore, clinical laboratories sought to correlate in vitro susceptibility methods with treatment outcomes, most notably with malaria. Parasites with their various life cycles present greater complexity than bacteria, for which standardized susceptibility methods exist. This review catalogs the state-of-the-art methodologies used to evaluate the effects of drugs on key human parasites from the point of view of drug discovery as well as the need for laboratory methods that correlate with clinical outcomes.
Competencies , Scope of Practice in Disaster

This paper reviews the literature pertaining the core competencies in disaster nursing. This paper discusses competing issues of core competencies in disaster nursing; nursing education and competencies, nurses’ perspectives on competencies in disaster nursing, nurses’ experience and competencies in disaster nursing, and the need for specific competencies for each type of disaster. The appropriate standardized framework for disaster nursing core competencies should be utilized in the nursing practice worldwide and the ICN framework appears to be the most practical so far.
Mentor Texts: Models to Improve False Beginners’ Writing Skills

This research was to find out the effects of mentor texts on students’ ability to write a descriptive paragraph. Changes in the content and organization of their paragraphs were examined closely. As many as 35 students majoring in nursing who were enrolled in an English class participated in this research. In the class, the students learned to write a descriptive paragraph using some mentor texts which served to help them learn identifying and writing a topic sentence, supporting sentences, and a concluding sentence. The texts also provided them with models to make a paragraph have unity and coherence. The data were collected from the student’ paragraphs produced before and after the learning process and the paragraph they wrote in the delayed posttest. A survey was also distributed at the end of their English class to collect their responses on the use of mentor texts in their learning process. The findings of this research indicated that mentor texts indeed had positive effects on the students’ ability to write a descriptive paragraph. Their awareness to include a topic sentence, details, unity, a concluding sentence, and transition signals in their paragraph was found to significantly develop. In addition, mentor texts enhanced the students’ confidence, interest, and motivation in writing.
Link prediction by exploiting network formation games in exchangeable graphs

In social network analysis, we often need to predict new links, given some available evidence. This may, for instance, enable us to study user behavior and infer likely new interactions in the near future. Recently, a family of algorithms based on exchangeable graphs has proven effective for link prediction. The network is modeled as an exchangeable array, whose entries can flexibly be traced back to random function priors (e.g., block models, Gaussian Processes). Unfortunately, the burdensome computational complexity of these methods inhibit their application to even just moderate-scale networks. In this paper, we present a novel online training algorithm based on local Gaussian processes on subgraphs, which successfully overcomes this challenge. Moreover, we address the sparsity problem of links in social networks by presenting an improved algorithm based on network formation games. The network formation games we design also shed light on the ambiguity of missing links — not observed vs. non-existing. We evaluate our method against state-of-the-art algorithms on real-world datasets, demonstrating both the effectiveness and the efficiency of our method.
A sociocognitive approach to business ethics: lessons from early industrializing Japan

Understanding transgression of business ethics in developed Western economies is different from that in developing economies where the institutional matrix that frames the market and transactions is in the process of fundamental change. This is particularly so when entrenched historical practices of close business and government interaction continue into the new era. In this environment the study of ethical forbearance may be more illuminating than transgression. Seen from a New Institutional Economics’ perspective on the sociocognitive, our empirical study of Shibusawa Eiichi and Dan Takuma shows that ideology can play an important role in shaping ethical business practice.
The Role of Ethics in Developing Entrepreneurial Ambidexterity

Ambidexterity describes the synergistic combination of exploration and exploitation in organizational learning and innovation. Within entrepreneurial firms, exploration largely maps onto opportunity search and recognition, while exploitation maps onto opportunity exploitation. Yet ambidexterity is hard to achieve, as exploration and exploitation often entail conflicting capabilities and resources. My paper explores the role of ethical values in these processes among founder entrepreneurs. Based on interview data with 30 founder entrepreneurs, the study suggests that stronger ethical values provide a foundation for decision-making and behavior that integrate exploration and exploitation. Ethical values therefore appear to moderate entrepreneurial ambidexterity.
Generating Captions for News Domain

: Many of the search engines deployed on the web retrieve images without analyzing their content, simply by matching their user queries against their collocated textual information. This limits the applicability of search engines, a great deal of work has focused on the development of generating descriptive words for an image automatically. Images are automatically captioned in two stages: Content selection and surface realization. Content selection suggests keywords for the image using image annotation model. Whereas, surface realization technique uses extractive and abstractive methods to generate caption. The approach is to analyze the performance of captioned images using phrases rather than words.
CITRA PERUSAHAAN SEBAGAI VARIABEL PEMODERASI PENGARUH LAYANAN TERHADAP KEPUASAN PASIEN DAN NIAT BERALIH

This study aims to see the effect of service quality from 3 PKU Muhammadiyah Hospital in Jogja, Sleman and Bantul on customer satisfaction and customer switching intention which is moderated by the company's image. This study uses Moderated Regression Analysis (MRA), with a total sample of 111 customers/patients at the Muhammadiyah Yogyakarta Hospital. The data was collected online and offline by purposive sampling technique. This study proves that service quality is the main predictor in increasing customer satisfaction of PKU Muhammadiyah Yogyakarta hospital. However, the test results explain that the company's image is not able to moderate the influence of service quality on the customer satisfaction and switching intention. The results of this study also provide theoretical and practical contributions related to theoretical, methodological and practical issues.
VLIV FISKÁLNÍ POLITIKY NA EKONOMICKÝ RŮST V ZEMÍCH OECD

The aim of the paper is to fi nd out what is the effect of different types of government spending and taxes on economic growth in developed economies. The analysis is performed on a sample of 27 OECD countries in the period 1997-2011. It is based on the neoclassic growth model extended with the level of human capital and fi scal variables. Those include particular types of government spending (according to the COFOG classifi cation) and taxes (according to the OECD classifi cation), and state budget defi cit. From a methodological point of view, panel data estimation is used. We support the view that only some types of government spending are growth-enhancing, and only if they are fi nanced through indirect taxes. However, the results show that only expenditure on defense, education and health, and general public services may be labeled as productive. In addition, we show that direct taxes, especially corporate taxes, negatively affect the growth, also in case they are used to fi nance productive spending.