Miracle-dz/UniFAR-FTUs huggingface dataset:
3$, BASED PROTOCOL ENGINEERING AND VISUALIZATION FOR EDUCATION )3$. 1 CASE STUDY

)N THIS PAPER AN EDUCATIONAL CASE STUDY IS PRESENTED THAT SHOWS THE COMBINED USE OF 3$, FOR SYSTEM DESIGN AND A GRAPHICAL ENVIRONMENT FOR SIMULATION VISUALIZATION 4HIS CASE STUDY IS EMBEDDED IN AN 3$, LABORATORY COURSE THAT HAS BEEN DEVELOPED AT THE )NSTITUTE FOR #OMMUNICATION . ETWORKS OF THE 4ECHNICAL 5NIVERSITY OF -UNICH ! FTER AN BRIEF OVERVIEW OVER THE LABORATORY COURSE THE PAPER PRESENTS THE CASE STUDY WHICH ACTUALLY IS THE FINAL AND LARGEST EXERCISE OF THE COURSE 4HE EXAMPLE IS BASED ON THE 3$, DESCRIPTION OF THE )3$. SIGNALING PROTOCOL 1 4HE WELL KNOWN FUNCTIONALITY OF THE PROTOCOL MAKES IT A GOOD EXAMPLE FOR THE USE OF 3$, IN PROTOCOL DESIGN 4HE CASE STUDY ALSO DEALS WITH THE INTEGRATION OF 3$, DEFINED SYSTEMS IN AN EXTERNAL ENVIRONMENT IN THIS CASE A 4CL 4K BASED GRAPHICAL USER INTERFACE 4HE PAPER CONCLUDES WITH A REPORT ON THE EXPERIENCES GAINED FROM THE LABORATORY COURSE AND THE CASE STUDY
Three Li-rich K Giants: IRAS 12327−6523, 13539−4153, and 17596−3952

We report on spectroscopic analyses of three K giants previously suggested to be Li-rich: IRAS 12327-6523, 13539-4153, and 17596-3952. High-resolution optical spectra and the LTE model atmospheres are used to derive the stellar parameters (Teff, log g, [Fe/H]), elemental abundances, and the isotopic ratio 12C/13C. IRAS 13539-4153 shows an extremely high Li abundance of log ϵ(Li) ≈ 4.2, a value 10 times greater than the present Li abundance in the local interstellar medium. This is the third highest Li abundance yet reported for a K giant. IRAS 12327-6523 shows a Li abundance of log ϵ(Li) ≈ 1.4. IRAS 17596-3952 is a rapidly rotating (V sin i ≈ 35 km s-1) K giant with log ϵ(Li) ≈ 2.2. Infrared photometry shows the presence of an IR excess, suggesting mass loss. A comparison is made between these three stars and previously recognized Li-rich giants.
When we want them to fear us: The motivation to influence outgroup emotions in collective action

Prior work has shown that the experience of group-based emotions can motivate disadvantaged group members to engage in collective action. In the current research, we tested whether such action can also be driven by the motivation to induce certain emotions among the outgroup to the extent that disadvantaged group members believe this would help them attain their social change goals. We tested this hypothesis in three studies (two correlational and one experimental) within the context of the Israeli–Palestinian conflict. Study 1 showed that individuals’ motivation to induce outgroup regret was associated with nonviolent collective action tendencies, whereas the motivation to induce outgroup fear was related to violent action. Study 2 moved beyond Study 1 by assessing corrective and punitive goals of social change. We found that preferences for inducing outgroup regret mediated the relationship between endorsement of corrective goals and nonviolent action tendencies, whereas preferences for outgroup fear mediated the relationship between punitive goals and violent action. Study 3 provided experimental support for the causal effect of goals on emotion motivations and collective action tendencies. Together, our findings are in line with the notion of instrumental emotion regulation as applied to collective action.
Towards the Production of Second Generation Ethanol from Sugarcane Bagasse in Brazil

Brazil and the United States produce ethanol mainly from sugarcane and starch from corn and other grains, respectively, but neither resource are sufficient to make a major impact on world petroleum usage. The so-called first generation (1G) biofuel industry appears unsustainable in view of the potential stress that their production places on food commodities. On the other hand, second generation (2G) biofuels produced from cheaper and abundant plant biomass residues, has been viewed as one plausible solution to this problem [1]. Cellulose and hemicellulose fractions from lignocellulosic residues make up more than two-thirds of the typical biomass composition and their conversion into ethanol (or other chemicals) by an economical, environmental and feasible fermentation process would be possible due to the increasing power of modern biotechnology and (bio)-process engineering [2].
Topological Analysis of Wireless Networks

Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 Form Approved OMB No. 0704-0188 The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 3. DATES COVERED (From To)
ECONOMIC WELLBEING AND WHERE WE LIVE: ACCOUNTING FOR GEOGRAPHIC COST-OF-LIVING DIFFERENCES

Regional cost-of-living differences affect the quality of life that individuals and families experience in different metropolitan areas. Yet, lack of metropolitan cost-of-living indexes has left analysts without the ability to make accurate cost-of-living adjustments to measures of economic wellbeing. We evaluate seven alternative inter-regional cost-of-living measures based on four criteria: (1) their data collection methodologies, (2) the variables included in cost-ofliving measurement, (3) their accuracy in measuring the cost-of-living experiences of high-, lowand moderate-income populations, and (4) the measures' availability and affordability. We then applied one of the indices for illustrative purposes to various metropolitan area data sets, including median household income, the number of people living in poverty, and family eligibility for the Free and Reduced Price School Lunch and Head Start programs to illustrate some of the policy impacts of adjusting economic indicators of wellbeing for geographic cost-ofliving differentials.
Ainda Existe Espaço para o Tratamento Conservador nas Fraturas Complexas da Diáfise do Úmero

The humeral shaft fractures account for about 1-3% of all the fractures, and about 20% of the humeral fracture is a bimodal occurrence of fractures, with the highest incidence in the third and seventh decade of life, associated with high and low energy trauma respectively. In high-energy trauma, such as in sports or traffic accident is more common in men. The low-energy traumas, such as falls, are more frequent in women over 50 years old. Most of shaft fractures, including long oblique and comminuted humeral can be treated with cast. The trend is the surgical treatment even for fractures once treated conservatively were obtained good functional results.
Comparative study between cervical cerclage and vaginal progesterone for the prevention of preterm birth in women with a history of preterm birth and a sonographic short cervix: A randomized trial

Objective: This randomized controlled trial aimed to compare cervical cerclage and vaginal progesterone for the prevention of preterm birth with a sonographic short cervix in the mid-trimester, singleton gestation and previous preterm birth. Study design: Women with high-risk factors for preterm birth (history of previous preterm labour/ second trimester loss [>16weeks or <37 weeks gestation], short cervical length (<25mm) on ultrasound at 16 to 24weeks gestation, and Previous prophylactic cervical cerclage) were screened through TVU (Transvaginal Ultrasound) of cervix every two weeks between 14 – 24 weeks. The eligible women with sonographic short cervix <25mm in the mid trimester, singleton gestation and previous spontaneous PTB <37 weeks of gestation were randomized either to cervical cerclage group (McDonald cerclage) or vaginal progesterone group (200mg vaginal progesterone suppository to be inserted at night. Treatment was continued until either delivery, 37 weeks of gestation or development of premature rupture of membranes. Primary outcome measure was PTB <34 weeks gestation. Result: One hundred women were assigned randomly. Both interventions were associated with a statistically significant reduction in the risk of preterm birth <34 weeks of gestation ((p=0.001). Comparing using cervical cerclage and vaginal progesterone, showed that no statistical significant difference in reducing preterm birth or adverse perinatal outcomes. Conclusion: It was concluded that the vaginal progesterone is effective as cervical cerclage in prevention premature labor but its use is preferable in clinical because it’s non-invasive technique and less cost. These results should be confirmed by large sample trial. [Mohamed Abd Elzaher, Mohamed Ali and Mohamed Bedewi. Comparative study between cervical cerclage and vaginal progesterone for the prevention of preterm birth in women with a history of preterm birth and a sonographic short cervix: A randomized trial. Life Sci J 2014;11(6):17-23]. (ISSN:1097-8135). http://www.lifesciencesite. com. 3
STRAINED VIRTUAL MOVEMENT FIELD

We provide a novel thinking of regularization neural networks. We smooth the objective of neural networks w.r. t small adversarial perturbations of the inputs. Different from previous works, we assume the adversarial perturbations are caused by the movement field. When the magnitude of movement field approaches 0, we call it virtual movement field. By introducing the movement field, we cast the problem of finding adversarial perturbations into the problem of finding adversarial movement field. By adding proper geometrical constraints to the movement field, such smoothness can be approximated in closed-form by solving a min-max problem and its geometric meaning is clear. We define the approximated smoothness as the regularization term. We derive three regularization terms as running examples which measure the smoothness w.r. t shift, rotation and scale respectively by adding different constraints. We evaluate our methods on synthetic data, MNIST and CIFAR-10. Experimental results show that our proposed method can significantly improve the baseline neural networks. Compared with the state of the art regularization methods, proposed method achieves a tradeoff between accuracy and geometrical interpretability as well as computational cost.
On the mechanics of biopolymer networks

In this thesis, we study the mechanical properties of biopolymer networks. We discuss which of these properties can be described by continuum approaches and which features, on the contrary, require consideration of the discrete nature or the topology of the network. For this purpose, we combine theoretical modeling with extensive numerical simulations. In Chapter 2, we study the elasticity of disordered networks of rigid filaments connected by flexible crosslinks that are modeled as wormlike chains. Under the assumption of affine deformations in the limit of infinite crosslink density, we show analytically that the nonlinear elastic regime in 1- and 2-dimensional networks is characterized by power-law scaling of the elastic modulus with the stress. In contrast, 3-dimensional networks show an exponential dependence of the modulus on stress. Independent of dimensionality, if the crosslink density is finite, we show that the only persistent scaling exponent is that of the single wormlike chain. Our theoretical considerations are accompanied by extensive quasistatic simulations of 3-dimensional networks, which are in agreement with the analytical theory, and show additional features like prestress and the formation of force chains. In Chapter 3, we study the distribution of forces in random spring networks on the unit circle by applying a combination of probabilistic theory and numerical computations. Using graph theory, we find that taking into account network topology is crucial to correctly capture force distributions in mechanical equilibrium. In particular, we show that application of a mean field approach results in significant deviations from the correct solution, especially for sparsely connected networks.
Improvement of image quality in computed tomography via data fusion

For most real-world applications of computed tomography (CT) the quality of image reconstruction from measured projections is reduced by artifacts from a number of sources. Especially for large sized objects, such as turbine blades, it is often not possible to fully penetrate the object in specific directions. The corresponding measured projections are additionally affected by secondary radiation caused by scattering. This manifests itself as smearing and blurring artifacts in the reconstructed image and is specifically perceivable at concave edges in the case of turbine blades. By means of data fusion we are able to supplement and correct the missing data from the CT scan and improve the reconstructed image quality. As additional modalities a 3-D scanner as well as ultrasonic testing are available. A 3-D scanner can provide the complete surface information of the object simultaneously with the CT acquisition. A specific ultrasonic imaging technique called synthetic aperture focusing technique is used to obtain further data of the interior structure. In this contribution we present a general framework, how this additional data can be embedded in the CT reconstruction. This framework consists of a superiorized version of the simultaneous algebraic reconstruction technique (SART). The concept of superiorization is a new technique for constrained optimization and steers the algorithm to additionally fulfill the a priori given information from ultrasonic testing and 3-D scanning. Furthermore, our algorithm is able to handle additional data from the same modality but with different acquisition parameters. This means it is possible to incorporate another CT projection data set into our reconstruction as it is relevant in dual energy measurements for example. Applying this framework on a turbine blade model, the apparent smearing and blurring artifacts can be reduced significantly.
PREDICTION OF CO2 FUTURE PRICES FOR ENERGY RISK MANAGEMENT VIA NEURAL NETWORK ADAPTED STOCHASTIC PROCESSES

Abstract Energy risk management requires an efficient prediction of CO2 future prices. We apply a neural network calibrated stochastic model to predict day ahead future prices suitable for risk management with a given time horizon (e.g. 10 business days). The model is training neural perceptron layers to learn the weights of historical time series points within a past horizon equal to the the memory depth (e.g. previous 10 business days). With this weights, the parameters of the stochastic model are optimized, and the day ahead carbon future price is computed. Iterating these steps, we obtain price forecasts, which demonstrate the learning efficiency of our method, which essentially corresponds to a stochastic process with time-dependent parameters, the dynamics of the parameters being themselves learned continuously by the neural network. The back propagation in training the previous weights is limited by the memory depth. The latter is the analogue of the maximal time lag of an autoregressive processes.
Biophotonic Technique to Study Muscle Tissue Metabolism of Athletes

ABSTRACT. Near-infrared spectroscopy is an affordable technology that can be used in monitoring muscle oxygenation in exercise and sport setting. In this study, we presented a portable, wireless, multichannel near-infrared spectroscopy device for real-time monitoring of muscle activity. Wireless communication was applied to data transmission in order to avoid cumbersome wires, and the whole system is highly integrated. We took special care to eliminate motion artifact when designing the near-infrared spectroscopy sensor for attachment to human skin. In addition, the system is designed with a high sampling rate so as to monitor rapid oxygenation changes during muscle activity. The wireless near-infrared spectroscopy sensor was designed using commercially available electronic components that were mounted onto a 4-layer rigid-flexible printed circuit board. We performed in vivo experiments including arterial occlusion and isometric voluntary forearm muscle contraction among wrestlers and demonstrated that the system can effectively monitor muscle oxygenation parameters, even in exercise.
Executive Influence, Poverty Experience and Corporate Social Responsibility—Based on Empirical Evidence of Chinese A - Share Listed Companies

Taking 2012-2015 Chinese A-Share listed companies as the research object, this paper studies the impact of executive influence and poverty experience on the performance of corporate social responsibility. The results show that: executive influence is positively correlated with performance of corporate social responsibility, the higher the executive influence, the better corporate social responsibility is; compared with non-state-owned enterprises, executive influence has more influence on the performance of social responsibility of state-owned enterprises. poverty experience is positively correlated with performance of corporate social responsibility, the higher the poverty experience, the better corporate social responsibility is. Further research found that: executive poverty experience helps to strengthen the positive correlation between executive influence and corporate social responsibility, we should pay attention to the role of executive influence, at the same time cannot be ignored the effect of executive poverty on promoting the performance of corporate social responsibility.
Lived experience of women diagnosed with breast cancer: A qualitative study

According to WHO, one in every eight women will be diagnosed with breast cancer in their life time [1]. India stands first among other countries in breast cancer mortality [3], not only the estimates of breast cancer are creating frustration among women; the disease itself creates the feeling of worry and dread. Knowing the subjective feelings, experiences and expectations will highlight the importance of quality health care and better coping to the disease. Adequate delivery of need based care to breast cancer patients can be achieved through knowing the feeling, experience and expectations of women diagnosed with breast cancer. A study on lived experiences of women diagnosed with breast cancer in a selected hospital at Mangalore was conducted to explore the experiences and feelings of the women diagnosed with breast cancer. Materials and Methods: A qualitative approach & phenomenological research design was adopted in this study. Women who were diagnosed with breast cancer for minimum of one year irrespective of their treatment who met the inclusion criteria and attended oncology unit of Justice K S Hedge Charitable Hospital, Mangalore were selected as the samples through the purposive sampling method. Instead, women who were suffering from breast cancer with multiple organ metastasis and women who had undergone surgery two weeks prior to the data collection were excluded from the study. After receiving the ethical clearance from Nitte University and the consent from the study subjects, the researcher interviewed them by using preset semi-structured open ended questions and tape recorded the conversations. Each interview lasted for about 30 – 40minutes. The recordings were transcribed verbatim. Data got saturated with 6 samples. Results: Colaizzi’s data analysis framework was used to analyze9 the transcribed data and from the analysis, six themes emerged and they were: 1. Ignorance 2. Awareness on the deteriorating physical changes 3. Powerlessness and death anxiety 4. Dysfunctional family process 5. Readiness for enhanced coping 6. Willingness for self-recognition and identity Conclusion: The findings emphasized the necessity of nurse’s care and concern for subjective aspects in women with breast cancer. It also helped to expose the hidden aspects of the need for concern and time for sharing the feelings in case of such dreadful illness which in turn many times brings ideas for better coping and improves the quality of life and that was agreed upon by many other former researchers.
AN OVERVIEW OF ECHOCARDIOGRAPHY FOR EXAMINATION OF CARDIAC STRUCTURES Christine Lee 13 AN OVERVIEW OF THE DEVELOPMENT OF PET-CT Jerzy Cholewa 19 THE COMBINATION OF ARTIFICIAL INTELLIGENCE AND BIOMEDICAL IMAGING: IMPROVING THE EFFICIENCY OF DIAGNOSIS

The interdisciplinary relationship emerging between medical and engineering professionals has led to innovative technological advancements. In particular, the medical imaging field has been steadily growing with the emergence of advanced visualization methods, such as 3D printing and virtual reality. By taking two-dimensional images from traditional volumetric imaging techniques it becomes possible to construct a three-dimensional model. 3D printing and virtual reality allow physicians to have tangible and explorable landscapes of patient anatomy. By incorporating virtual reality techniques, many companies, for example 3D Systems, have been able to create training simulations that are geared towards better educating the future class of health care professionals. These advanced visualization techniques are becoming commonplace for pre-operative planning and for patient education.
Don’t Drop the Topic - The Role of the Prompt in Argument Identification in Student Writing

In this paper, we explore the role of topic information in student essays from an argument mining perspective. We cluster a recently released corpus through topic modeling into prompts and train argument identification models on different data settings. Results show that, given the same amount of training data, prompt-specific training performs better than cross-prompt training. However, the advantage can be overcome by introducing large amounts of cross-prompt training data.
Antennal lobe of the honeybee

The antennal lobe (AL) of an insect is the functional analog of the olfactory bulb in mammals. The fi rst-level synaptic interaction between large numbers of multiple-type olfactory receptor neurons (ORNs) serves the function of reliable coding of a vast range of general odors, the fast identifi cation of an odor, the selective coding of mixtures of compounds, and the separation between odor identity and odor concentration. Honeybees learn and discriminate a seemingly unlimited number of odors (natural and artifi cial), categorize odor mixtures as unique stimuli, identify odors within 250 ms, and generalize odors according to the respective combinatorial glomerulus activity patterns in the AL (Galizia and Menzel, 2000 ). Therefore, the AL is the fi rst-order neuropil serving basic functions of odor discrimination, categorization, generalization, and learning. The social life of the honeybee is guided by a range of well-described pheromones. No difference between general odor and pheromone coding was found so far with the exception of the queen pheromone coding in males (drone bees) (Sandoz et al., 2007 ). We fi rst describe the internal organization of the AL, its inputs, and its outputs. Then we analyze the local circuit of a prototypical glomerulus.