Miracle-dz/UniFAR-FTUs huggingface dataset:
Young students as participants in school health in promotion: An intervention study in a swedish elementary school

Abstract Objectives. The aim was to analyse if young students could be substantive participants in a healthpromoting school project. The specific aims were to analyse the changes the students proposed in their school environment, how these changes were prioritized by a school health committee and to discuss the students’ proposals and the changes from a health and gender perspective. Study design. An intervention project was carried out in an elementary school with students (about 150) in Grades 1 through 6. The intervention included small-group discussions about health promoting factors, following a health education model referred to as ‘It’s your decision. ’ At the last of 6 discussions, the students made suggestions for health-promoting changes in their school environment. A health committee was established with students and staff for the purpose of initiating changes based on the proposals. Methods. A content analysis was used to analyse the proposals and the protocols developed by the health committee. Results. The analysis showed 6 categories of the students’ proposals: social climate, influence on schoolwork, structure and orderliness, security, physical environment and food for well-being. Their priorities corresponded to the students’ categories, but had an additional category regarding health education. Conclusions. Principles that guide promoting good health in schools can be put into action among students as young as those in Grades 1 through 6. Future challenges include how to convey experiences and knowledge to other schools and how to evaluate if inequalities in health because of gender, class and ethnicity can be reduced through the focus on empowerment and participation.
Poisson limit of an inhomogeneous nearly critical INAR(1) model

An inhomogeneous first-order integer-valued autoregressive (INAR(1)) process is investigated, where the autoregressive type coefficient converges to one and the immigration mean tends to zero at appropriate speeds. It is shown that the process converges weakly to a Poisson or a compound Poisson distribution.
Collecting Semantic Data from Amazon ’ s Mechanical Turk for a Lexical Knowledge Resource in a Text to Picture Generating System

WordsEye is a system for converting from English text into three-dimensional graphical scenes that represent that text. At the core of WordsEye is the Scenario-Based Lexical Knowledge Resource (SBLR), a unified knowledge base and representational system for expressing lexical and real-world knowledge needed to depict scenes from text. This paper explores information collection methods for building the SBLR, using Amazon’s Mechanical Turk (AMT) and manual normalization of raw AMT data. The paper follows with a review of existing relations in the SBLR and classification of the AMT data SBLR semantic relations. Since manual annotation is a time-consuming and expensive approach, we also explored the use of automatic normalization of AMT data through WordNet similarity measures and log-odds and log-likelihood ratios extracted from large corpora.
Posttranscriptional deregulation of Src due to aberrant miR34a and miR203 contributes to gastric cancer development

Gastric cancer remains the main cause of cancer death all around the world, and upregulated activation of the nonreceptor tyrosine kinase c-SRC (SRC) is a key player in the development. In this study, we found that expression of Src is also increased in clinical gastric cancer samples, with the protein level increased more significantly than that at the RNA level. Further study revealed that miR34a and miR203, two tumor suppressive miRNAs, inversely correlate with the expression of Src. Restoration of miR34a and miR203 decreased Src expression in gastric cancer cell lines, which in turn inhibited cell growth and cell migration. In summary, our study here revealed that posttranscriptional regulation of Src contributes to the deregulated cell growth and metastasis in gastric cancer, and targeting Src by miR34a or miR203 mimics would be a promising strategy in therapy. [BMB Reports 2013; 46(6): 316-321]
5 Simulation Speed-up Methods

We discussed in class the commands plot, points, lines, legend, along with the graphical parameters type (= " p " points, " n " none, " l " lines, " b " both), xlab, ylab, main, xlim, ylim, pch, lty. These and lots more can be studied by invoking the help window on " par " once the Splus help is started. An extended example, for you to repeat and study, is given in the Handouts directory of the course web-page We have already discussed thls e mechanics of (Uniform) pseudo-random number generation. Most interesting applications of Simulation or the 'Monte Carlo Method' in applied probability and statistics concern evaluation of expectations of combinations of random variables and stochastic-process tra-jectories E (f ((Z(t), t > 0), Y 1 , Y 2 ,. )) (1) which are (much) too complicated to evaluate or approximate analytically. The function f will often be an indicator for occurrence of a particular event within a single realization of a data structure. In useful statistical and probabilistic simulations, there is usually need to simulate complicated data structures or large batches with a view to tabulating relative frequencies of occurrence, sometimes of relatively rare events such as those associated with type I and type II errors in statistical hypothesis tests. This can be slow, not only because of the need for looping in Splus, but because of complicated dependencies among data or nontrivial analyses for each simulated batch of data. There are several well-recognized methods for speeding up generation of random data, especially with respect to specific purposes involving uncommon events. Two good general references (the first of which is much longer and more detailed, and the second of which will serve us later as a reference 43
A Framework of Co-creating Business Values for IT Services

The IT industry traditionally offers system services to user companies. The services which integrate software and hardware products are geared toward product-based business models. However, with the emergence of cloud computing, users’ in-house systems and applications are virtualized on the net, and are replaced with ones provided through outsourcing services. The alternative systems will be combinations of service functions of their companies’ and of outsourcers’. This will relieve user companies from their legacy systems, allowing them to concentrate on their competence and to develop new business models effectively. In order to meet this trend, IT vendors should focus not only on the values of platform development but also on those of creating business opportunities. They need to share users’ business goals and collaborate with them to enhance their business values. This paper proposes a framework and supporting tools to co-create business values between IT vendors and clients through the business lifecycle, showing the results from partly applying them to the early stages of development of e-learning services.
Using a digital camera to teach the physics of light

3/4 digital cameras capable of 24-bit color (16.8 million colors) provide a unique and relatively inexpensive tool for teaching the physics of light. Many students are familiar with colors obtained by mixing different colors of paint. These color combinations represent subtractive color. Projected light, such as that emanating from the sun and reflected by objects, combines to form different additive colors. The concept of additive color may be more difficult for students to grasp because experimenting with this concept is perhaps more difficult in comparison to mixing paints. Yet, color televisions and computer monitors rely on the concept of additive color to display their many different colors. This paper shows how a digital camera may be used to demonstrate the concept of additive color and apply this concept for scientific investigation. The intended audience is K-12 educators, moreover instructors of college-level science courses that target nonscience majors.
Timing closure through a globally synchronous, timing partitioned design methodology

A method to mitigate timing problems due to global wire delays is proposed. The method follows closely a fully synchronous design flow and utilizes only hue digital lihraly elements. The design is partitioned into isochronous blocks at system level, where a few clockicycles latency is inserted between the isochronous blocks. This latency is then utilized to automatically mitigate unknown global wire delays, unknown global clock skews and other timing uncertainties occurring in hackend design. The new method is expected to considerably reduce the timing closure effort in large high frequency digital designs in deep submicron technologies.
Simulation and performance evaluation of free space optic transmission system

Free Space Optics (FSO) is an emerging technology of this generation. FSO uses air as a medium for transmission channel. Free-space optics technology is an alternative of fiber optics technology. The main advantages of FSO communication system are it requires less installation time and it can save the required costs significantly compared to the implementation of fiber optics without losing the capability to send high data rates. In this paper we have designed a DWDM system using FSO channel. The designed system is using Mach-Zehnder modulator as it modulates the electrical signal directly into optical signal. The performance of the FSO transmission system is evaluated in terms of Q factor and BER values. The DWDM system using FSO channel is evaluated for high data rates i.e. 1Gbps to 10Gbps.The system performance is analyzed in terms of power transmitted and received using power meter.
Personality traits, work experience and GPA as predictors of Career Adaptability in College

Career adaptability is becoming a more and more important psychosocial construct in career counseling. It refers to the capability to adapt and mange career tasks and challenges. The main goal of the current paper was to investigate the effects of socio-demographic characteristics, work experience, GPA and HEXACO-60 on career adaptability, and its subscales (concerns, control, curiosity, confidence). Data was collected from 328 college students, from the Babeş-Bolyai University, Cluj-Napoca. The main aim of the study was to investigate whether the HEXACO-60 is as useful as the Big5. The six dimensions test is also a good predictor of career adaptability, except for the Emotionality dimension. In this sample, work experience was not a predictor for career adaptability, even if they were correlated. Career adaptability only in Step 2 was predicted by GPA, while in step 3 by father’s educational level. Our findings support that HEXACO-60 personality inventory is useful for understanding and revealing the predictors of career adaptability.
High Speed 3D IR Scanner for Home Service Robots

This paper introduces the hardware platform of the structured light processing based on depth imaging to perform a 3D modeling of cluttered workspace for home service robots. We have discovered that the degradation of precision and robustness comes mainly from the overlapping of multiple codes in the signal received at a camera pixel. Considering the criticality of separating the overlapped codes to precision and robustness, we proposed a novel signal separation code, referred to here as "Hierarchically Orthogonal Code (HOC)," for depth imaging. The proposed HOC algorithm was implemented by using hardware platform which applies the Xilinx XC2V6000 FPGA to perform a real time 3D modeling and the invisible IR (Infrared) pattern lights to eliminate any inconveniences for the home environment. The experimental results have shown that the proposed HOC algorithm significantly enhances the robustness and precision in depth imaging, compared to the best known conventional approaches. Furthermore, after we processed the HOC algorithm implemented on our hardware platform, the results showed that it required 34ms of time to generate one 3D image. This processing time is about 24 times faster than the same implementation of HOC algorithm using software, and the real-time processing is realized.
Efficient Molecular Marker Design Using the MaizeGDB Mo17 SNPs and Indels Track

Positional cloning in maize (Zea mays) requires development of markers in the region of interest. We found that primers designed to amplify annotated insertion–deletion polymorphisms of seven base pairs or greater between B73 and Mo17 produce polymorphic markers at a 97% frequency with 49% of the products showing co-dominant fragment length polymorphisms. When the same polymorphisms are used to develop markers for B73 and W22 or Mo17 and W22 mapping populations, 22% and 31% of markers are co-dominant, respectively. There are 38,223 Indel polymorphisms that can be converted to markers providing high-density coverage throughout the maize genome. This strategy significantly increases the efficiency of marker development for fine-mapping in maize.
Cosmological lower bound on the circuit complexity of a small problem in logic

An exponential lower bound on the circuit complexity of deciding the weak monadic second-order theory of one successor (WS1S) is proved. Circuits are built from binary operations, or 2-input gates, which compute arbitrary Boolean functions. In particular, to decide the truth of logical formulas of length at most 610 in this second-order language requires a circuit containing at least 10125 gates. So even if each gate were the size of a proton, the circuit would not fit in the known universe. This result and its proof, due to both authors, originally appeared in 1974 in the Ph.D. thesis of the first author. In this article, the proof is given, the result is put in historical perspective, and the result is extended to probabilistic circuits. *
A Single-Item Inventory Model for a Nonstationary Demand Process

In this paper, we consider an adaptive base-stock policy for a single-item inventory system, where the demand process is nonstationary. In particular, the demand process is an integrated moving average process of order (0, 1, 1), for which an exponential-weighted moving average provides the optimal forecast. For the assumed control policy we characterize the inventory random variable and use this to find the safety stock requirements for the system. From this characterization, we see that the required inventory, both in absolute terms and as it depends on the replenishment lead-time, behaves much differently for this case of nonstationary demand compared with stationary demand. We then show how the single-item model extends to a multi-stage, or supply-chain context; in particular we see that the demand process for the upstream stage is not only nonstationary but also more variable than that for the downstream stage. We also show that for this model there is no value from letting the upstream stages see the exogenous demand. The paper concludes with some observations about the practical implications of this work.
A two-stage simulated annealing logical topology reconfiguration in IP over WDM networks

WDM optical networks represent the direction to the future high capacity wide-area network applications. By reconfiguring the logical topology, network resources utilization can be optimized corresponding to the traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. We consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balance between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually given as a mixed integer linear programming, but it grows intractable with increasing size of network. Here we propose a simulated annealing approach to determine the target topology with a smaller logical topology change and satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity by tuning this threshold to a feasible value. For an effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.
An Overview of Environmental Design Relationship with School Bullying and Future Crime

This article presents an overview of how environmental design is related with school bullying and future crime. Through a discussion of findings from previous studies, gaps in criminology knowledge on the bully-design link and future crime will be highlighted. Bullying is a serious social problem that can affect and impact a student’s future. The previous studies had indicated the link between bullying behaviour and future crime for the bully and the victim. In conclusion, this article will emphasise the need for future research in environmental design and bullying behaviour.Keywords: Environmental design; School bullying; Criminality; CrimeeISSN: 2398-4287 © 2019. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: https://doi.org/10.21834/e-bpj.v4i10. 1631
Disparities in use of a personal health record in a managed care organization.

OBJECTIVE Personal health records (PHRs) can increase patient access to health care information. However, use of PHRs may be unequal by race/ethnicity. DESIGN The authors conducted a 2-year cohort study (2005-2007) assessing differences in rates of registration with KP.org, a component of the Kaiser Permanente electronic health record (EHR). MEASUREMENTS At baseline, 1,777 25-59 year old Kaiser Permanente Georgia enrollees, who had not registered with KP.org, responded to a mixed mode (written or Internet) survey. Baseline, EHR, and KP.org data were linked. Time to KP.org registration by race from 10/1/05 (with censoring for disenrollment from Kaiser Permanente) was adjusted for baseline education, comorbidity, patient activation, and completion of the baseline survey online vs. by paper using Cox proportional hazards. RESULTS Of 1,777, 34.7% (616) registered with KP.org between Oct 2005 and Nov 2007. Median time to registering a KP.org account was 409 days. Among African Americans, 30.1% registered, compared with 41.7% of whites (p < 0.01). In the hazards model, African Americans were again less likely to register than whites (hazard ratio [HR] = 0.652, 95% CI: 0.549-0.776) despite adjustment. Those with baseline Internet access were more likely to register (HR = 1.629, 95% CI: 1.294-2.050), and a significant educational gradient was also observed (more likely registration with higher educational levels). CONCLUSIONS Differences in education, income, and Internet access did not account for the disparities in PHR registration by race. In the short-term, attempts to improve patient access to health care with PHRs may not ameliorate prevailing disparities between African Americans and whites.
The Interactive Influence of External and Internal Governance on Risk Taking and Outcomes: The Importance of CEO Career Concerns

We study the effects of multi-layered governance on firm risk by focusing on the interaction of two types of career concerns. Two Delaware court decisions, the validation of poison pill defenses (the Unitrin decision) implemented by staggered boards (the Wallace decision), reduced takeover-related career concerns. CEO age influences the response of Delaware firms to these shocks. Older CEOs in newly insulated firms reduce risk, while their younger counterparts increase risk. Ex-post, the differential behavior among young Delaware CEOs appears to be rewarded with abnormally positive stock performance and better future career outcomes. We conclude that there is important variation in the effects of governance on firm (CEO) behavior, driven by multiple facets of career concerns.
A Class of ADMM-based Algorithms for Multi-block Separable Convex Programming

When the alternating direction method of multipliers (ADMM) is directly extended to a multi-block separable convex minimization model whose objective function is the sum of more than two functions without coupled variables, it was recently shown that the convergence is not guaranteed. Despite of the lack of convergence, the direct extension of ADMM is empirically efficient for many applications. Thus we are interested in such an algorithm that can be implemented as easily as the direct extension of ADMM, while with comparable or even better numerical performance and guaranteed convergence. In this paper, we suggest correcting the output of the direct extension of ADMM slightly by a simple correction step. The correction step is simple in the sense that it is completely free from step-size computing and its step size is bounded away from zero for any iterate. A prototype algorithm in this prediction-correction framework is proposed; and a unified and easily checkable condition to ensure the convergence of this prototype algorithm is given. Theoretically, we show the contraction property, prove the global convergence and establish the worst-case convergence rate measured by the iteration complexity for this prototype algorithm. The analysis is conducted in the variational inequality context. Then, based on this prototype algorithm, we propose a class of specific ADMM-based algorithms and verify their numerical efficiency by an image decomposition problem.
A joint Bayesian forecasting model of judgment and observed data : Working paper 2012: 4

This paper presents a new approach that aims to incorporate prior judgmental forecasts into a statistical forecasting model. The result is a set of forecasts that are consistent with both the judgment and latest observations. The approach is based on constructing a model with a combined dataset where the expert forecasts and the historical data are described by means of corresponding regression equations. Model estimation is done using numeric Bayesian analysis. Semiparametric methods are used to ensure finding adequate forecasts without any prior knowledge of the specific type of the trend function. The expert forecasts can be provided as estimates of future time series values or as estimates of total or average values over any particular time intervals. Empirical analysis has shown that the approach is operable in practical settings. Compared to standard methods of combining, the approach is more flexible and in empirical comparisons proves to be more accurate.