Miracle-dz/UniFAR-FTUs huggingface dataset:
Guidelines for Analysis of Investments in Bicycle Facilities

This report presents methodologies and tools to estimate the cost of various bicycle facilities and for evaluating their potential value and benefits. The results will help transportation planners make effective decisions on integrating bicycle facilities into their overall transportation plans and on a project-by-project basis. In the past, planners and stakeholders have been faced with considerable challenges in trying to estimate the benefits of bicycle facilities. The authors have developed criteria for identifying benefits that will be useful and effective for urban transportation planning, and they have provided a systematic method to estimate both direct benefits to the users of the facilities and indirect benefits to the community. The research described in the report has been used to develop a set of web-based guidelines available on the Internet at http://www.bicyclinginfo. org/bikecost/ that provide a step-by-step worksheet for estimating costs, demands, and benefits associated with specific facilities under consideration.
Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review (Preprint)

BACKGROUND Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions. OBJECTIVE This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs. METHODS A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included. RESULTS A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health. CONCLUSIONS Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions. CLINICALTRIAL
Synthesis, Characterization of Liposomes Modified with Biosurfactant MEL-A Loading Betulinic Acid and Its Anticancer Effect in HepG2 Cell

As a novel natural compound delivery system, liposomes are capable of incorporating lipophilic bioactive compounds with enhanced compound solubility, stability and bioavailability, and have been successfully translated into real-time clinical applications. To construct the soy phosphatidylcholine (SPC)–cholesterol (Chol) liposome system, the optimal formulation was investigated as 3:1 of SPC to Chol, 10% mannosylerythritol lipid-A (MEL-A) and 1% betulinic acid. Results show that liposomes with or without betulinic acid or MEL-A are able to inhibit the proliferation of HepG2 cells with a dose-effect relation remarkably. In addition, the modification of MEL-A in liposomes can significantly promote cell apoptosis and strengthen the destruction of mitochondrial membrane potential in HepG2 cells. Liposomes containing MEL-A and betulinic acid have exhibited excellent anticancer activity, which provide factual basis for the development of MEL-A in the anti-cancer applications. These results provide a design thought to develop delivery liposome systems carrying betulinic acid with enhanced functional and pharmaceutical attributes.
Brandenburg University of Technology (BTU) Cottbus

Model checking is a fully automated approach to formal verification. The main problem of model checking is the state explosion. A number of techniques has been introduced to deal with the problem. Considering Petri Nets, the most efforts have been done on analysis of safe (1-bounded) place/transition nets. Many tools successfully implementing different techniques are available, but there are too few tools supporting efficient analysis of bounded, but not 1-bounded P/T Nets. This paper is a report on the implementation of a symbolic CTL model checker for bounded P/T nets that is based on Interval Decision Diagrams. The implementation supports inhibitor arcs as well as state space construction for a set of initial markings.
Prognostic Accuracy of the Afterload-related Cardiac Performance for 7-day Mortality Among Critical Ill Patients With Septic Shock

BackgroundSeptic patients with cardiac impairment are with high mortality. Afterload-related cardiac performance (ACP), as a new tool for diagnostic septic cardiomyopathy (SCM), still needs to be evaluated its impact on the prognosis for patients with septic shock. MethodsIn this observational retrospective study, 119 patients with septic shock undertaken PiCCO monitoring were evaluated for the effects of ACP on 7-day mortality, ICU mortality and hospital mortality. The ability of ACP, cardiac index (CI) and left ventricular ejection fraction (LVEF) to discriminate between survivors and non-survivors was tested by comparing the area under the receiver operating characteristic curve (AUROC) analysis. Multivariable logistic regression and Cox proportional hazards regression analyses were performed to assess the associations of ACP with 7-day mortality. Curve estimation was used to describe the relationship between hazard ratio (HR) of death and ACP.ResultsACP assessed at 12 hours (ACP12h) after septic shock [AUROC 0.86 (95% CI 0.79 to 0.93), P < 0.001] demonstrated significantly greater discrimination for 7-day mortality than CI [AUROC 0.67 (95% CI 0.57 to 0.78), P = 0.001 ] and LVEF [AUROC 0.53 (95% CI 0.43 to 0.64), P = 0.58] (all P < 0.001). Similarly, when adjusted with gender, APACHEII score, VIS and MAP as possible confounders, ACP12h still outperformed both CI12h and LVEF for discrimination of 7-day mortality (both P < 0.001). The superior discriminatory performance of ACP12h over both CI12h and LVEF was further maintained when considering ICU mortality and hospital mortality when considered in isolation or adjusted with the baseline prediction. Compared with normal ACP, HR for slight, moderate and severe impairment were 4.84 (1.96 to 11.96), 12.13 (4.83 to 30.43) and 32.70 (7.76 to 137.86), respectively. After adjustment for risk factor, decrease ACP still associated with increasing 7-day mortality (P = 0.001). Exponential relationship was observed between ACP12h and HR of 7-day death.ConclusionsOur results suggested that ACP may serve as a new tool for diagnosing SCM. In addition, the assessment of ACP at 12 hours after septic shock in ICU significantly improves 7-day mortality, ICU mortality and hospital mortality predictions when compared to CI and LVEF.
A Pilot Prospective Study of Plasma Cell free DNA Whole Genome Sequencing Identi ed Chromosome 7p Copy Number Gains is a Speci c Biomarker for Early Lung Cancer detection

Hongjie Yu Department of Thoracic Surgery, the First A liated Hospital of Soochow University Xiaojun Yu (  18362738721@163.com ) The First A liated Hospital of Soochow University https://orcid.org/0000-0002-7318-0220 Jia Tang Department of Thoracic Surgery, First A liated Hospital of Soochow University Xun Lu Department of Thoracic Surgery, First A liated Hospital of Soochow University Haitao Ma Department of Thoracic Surgery,First A liated Hospital of Soochow University
An exploratory investigation into factors affecting class attendance in a hospitality management module.

The research investigates various factors that influence student class attendance in a Hospitality Management module. Using survey questionnaires, the research aimed to determine factors that may negatively affect class attendance of first year students. The research was embarked upon to determine reasons for students not attending class as a possible variable for low throughput and high dropout rates. The research findings will indicate which factors affects class attendance the most in a Hospitality Management module. The data was analysed according to biographical information, external factors influencing class attendance, students’ motivation, respondents’ perceptions and internal factors to the institution. The biographical information does not play a factor in absenteeism. External factors do play a very small factor in nonattendance, what but no a significant role. The research found that motivation, respondents’ perceptions and internal factors to the institution do play a role in nonattendance in group of students.
A model personal energy meter

Every day each of us consumes a significant amount of energy, both directly through transport, heating and use of appliances, and indirectly from our needs for the production of food, manufacture of goods and provision of services. This dissertation investigates a personal energy meter which can record and apportion an individual’s energy usage in order to supply baseline information and incentives for reducing our environmental impact. If the energy costs of large shared resources are split evenly without regard for individual consumption each person minimises his own losses by taking advantage of others. Context awareness offers the potential to change this balance and apportion energy costs to those who cause them to be incurred. This dissertation explores how sensor systems installed in many buildings today can be used to apportion energy consumption between users, including an evaluation of a range of strategies in a case study and elaboration of the overriding principles that are generally applicable. It also shows how second-order estimators combined with location data can provide a proxy for fine-grained sensing. A key ingredient for apportionment mechanisms is data on energy usage. This may come from metering devices or buildings directly, or from profiling devices and using secondary indicators to infer their power state. A mechanism for profiling devices to determine the energy costs of specific activities, particularly applicable to shared programmable devices is presented which can make this process simpler and more accurate. By combining crowdsourced building-inventory information and a simple building energy model it is possible to estimate an individual’s energy use disaggregated by device class with very little direct sensing. Contextual information provides crucial cues for apportioning the use and energy costs of resources, and one of the most valuable sources from which to infer context is location. A key ingredient for a personal energy meter is a low cost, low infrastructure location system that can be deployed on a truly global scale. This dissertation presents a description and evaluation of the new concept of inquiry-free Bluetooth tracking that has the potential to offer indoor location information with significantly less infrastructure and calibration than other systems. Finally, a suitable architecture for a personal energy meter on a global scale is demonstrated using a mobile phone application to aggregate energy feeds based on the case studies and technologies developed.
Maternal pre-pregnancy underweight as a risk factor for mother and child: analysis of the birth cohort Survey of Neonates in Pomerania I

Background: The prevalence of pre-pregnancy underweight (BMI (body mass index) <18.5 kg/m²) varies between 3% in Europe and 17% in Asia. Illness and low socioeconomic status may be associated with pre-pregnancy underweight which then may result in adverse pregnancy and neonatal outcome.Methods: We analysed pre-pregnancy BMI categories using data from the population-based birth cohort Survey of Neonates in Pomerania 2002-2008 (SNiP) in north-eastern Germany. Multivariable regression analyses adjusted for confounding were used to investigate a) socio-economic risk factors for underweight before pregnancy and b) associations of underweight with pregnancy and neonatal outcomes.Results: Chronic pre-pregnancy diseases were not more frequent in underweight pregnant women. Bivariate analyses showed that underweight women were younger by three years (p<0.001), smoked twice as often (p<0.001), and less likely graduated from high school (p<0.001) compared to women with normal weight. The former were more often unemployed (p<0.001) and had lower available net-income (p<0.001). However, multivariable regression analysis adjusted for confounders revealed that only a younger age (0.90 (0.88-0.92) and smoking (RR 2.52 (1.89-3.41) remained associated with underweight. Compared to women with normal pre-pregnancy BMI, underweight women had an increased risk of premature labour (OR = 1.74; 95% CI: 1.29-2.36) and a reduced placental weight. No association was found between pregnancy-induced hypertension, gestational diabetes, preeclampsia, mode of birth and pre-pregnancy underweight. The offspring of underweight women had an increased risk of late preterm birth (OR = 1.79; 95% CI: 1.17-2.73) or birth with birth weight <2500g (OR = 1.99; 95% CI: 1.24-3.21). Conclusions: Smoking during pregnancy and a younger age were identified as risk factors for maternal pre-pregnancy underweight which then was associated with preterm birth and low birth weight. Targeted measures like smoking cessation programs and counselling young women about the risk of staying too slim particularly for the offspring may improve outcome.
The New Pioneers: The Men and Women Who Are Transforming the Workplace and Marketplace

Contents Introduction: The Age of Adaptation 1. Being in Business Trade and technology are fundamentally human. 2. Everyone a Middleman Why the new rules favor the small and connected. 3. "Have It Your Way" The customer is the common denominator. 4. What Am I Bid? A revolutionary economy demands radical pricing. 5. From Planning to Playing How agility and identity nurture innovation and trust. 6. Nobody's as Smart as Everybody Knowledge and self-organization flourish at the edge of chaos. 7. All Together Now How common purpose comes to life. 8. Money and Motivation Where people yearn to perform. 9. At Home in the Economy The reunion of family and work. 10. "All My Sons" Will business save society? Notes Annotated Bibliography Acknowledgments Index
Analysis and design of wideband voltage controlled oscillatorsusing self-oscillating active inductors.

Voltage controlled oscillators (VCOs) are essential components of RF circuits used in transmitters and receivers as sources of carrier waves with variable frequencies. This, together with a rapid development of microelectronic circuits, led to an extensive research on integrated implementations of the oscillator circuits. One of the known approaches to oscillator design employs resonators with active inductors electronic circuits simulating the behavior of passive inductors using only transistors and capacitors. Such resonators occupy only a fraction of the silicon area necessary for a passive inductor, and thus allow to use chip area more eectively. The downsides of the active inductor approach include: power consumption and noise introduced by transistors. This thesis presents a new approach to active inductor oscillator design using selfoscillating active inductor circuits. The instability necessary to start oscillations is provided by the use of a passive RC network rather than a power consuming external circuit employed in the standard oscillator approach. As a result, total power consumption of the oscillator is improved. Although, some of the active inductors with RC circuits has been reported in the literature, there has been no attempt to utilise this technique in wideband voltage controlled oscillator design. For this reason, the dissertation presents a thorough investigation of self-oscillating active inductor circuits, providing a new set of design rules and related trade-os. This includes: a complete small signal model of the oscillator, sensitivity analysis, large signal behavior of the circuit and phase noise model. The presented theory is conrmed by extensive simulations of wideband CMOS VCO circuit for various temperatures and process variations. The obtained results prove that active inductor oscillator performance is obtained without the use of standard active compensation circuits. Finally, the concept of self-oscillating active inductor has been employed to simple and fast OOK (On-Off Keying) transmitter showing energy eciency comparable to the state of the art implementations reported in the literature.
Client-oriented Projects: GIS Course Design with the Potential to Serve Multiple Constituents

Abstract Project-based learning geared toward a client provides the instructor with an applied method for classroom teaching. This article provides detailed information on how to incorporate project-based assignments into public administration courses. Student evaluations indicate that students perceive their learning to be more effective when it is project-based and client- or real-world oriented. This article looks at the integration of project-based assignments to coursework even when there is no identified “real” client.
Cloud Computing Organizational Benefits : A Managerial concern

Context: Software industry is looking for new methods and opportunities to reduce the project management problems and operational costs. Cloud Computing concept is providing answers to these problems. Cloud Computing is made possible with the availability of high internet bandwidth. Cloud Computing is providing wide range of various services to varied customer base. Cloud Computing has some key elements such as on-demand services, large pool of configurable computing resources and minimal management effort to the users. The software organizations are looking for cloud benefits to address the project management problems. Objectives: The study is to identify various cloud benefits for addressing project management problems faced by software industry. The study is also investigates various challenges or problems faced by the organizations while using cloud computing environment. The solutions or suggestions to overcome these identified cloud challenges are also produced in this study. Cloud benefits across different cloud types also found during this study. Methods: Systematic literature review is conducted across eight databases to find different cloud benefits and challenges for the organizations to address the project management problems. Interview study is conducted across industrial experts working in cloud computing environment. Interview study is to check the status of cloud benefits and challenges found through systematic literature review and find new additions. The solutions and suggestions are also found to address the cloud challenges through both methodologies. Results: A total of 21 cloud benefits and 12 challenges found across 43 primary studies through systematic literature review. 26 cloud benefits and 14 cloud challenges found through interview study among 7 cloud computing industry experts. 6 cloud benefits and 2 cloud challenges found through this study are not available in existing literature. Cloud benefits across different types are also discussed in this study. Conclusion: This study identifies various cloud benefits and cloud challenges for organizations to address project management problems. Cloud utilizing organization has to differentiate its project management problems for identifying cloud type. Cloud utilizing organization has to take care of the challenges at the time of writing Service Level Agreements (SLAs) with the help of third party organization.
Impact of Cooperative Systems on Drivers’ Car-Following Behavior

In-vehicle technologies and co-operative services are designed to ultimately reduce congestion and increase traffic safety. This paper investigates the impact of an infrastructure-to-vehicle co-operative system on drivers’ car-following behavior. Car following behavior, which describes the behavior of a vehicle while following the vehicle in front of it, has a significant impact on traffic performance, safety, and air pollution. In addition, it is an essential component of microsimulation models. Twenty nine test drivers drove an instrumented vehicle twice with and without the system. Trajectory data of each vehicle and the vehicle in front were collected. Car-following models were estimated for both cases, with and without the system, and the results of the two models were compared. The results show that co-operative systems have a positive impact on drivers’ car-following behavior. The system harmonizes the driving behavior of drivers and reduces the range of acceleration and deceleration differences among them. The impact of the system is larger on older drivers compared to younger drivers.
The Dynamic Enterprise: Tools for Turning Chaos into Strategy and Strategy into Action

PrefaceThe AuthorsPrologue: The Gift of Perspective Part One: Facing Chaos 1. Exponential Change and the New Business Environment 2. Leveraging Chaos: The Dynamic Enterprise Part Two: From Chaos to Strategy 3. An Overview of Enterprise Development 4. Seeing the Whole: The Enterprise as a Dynamic System 5. Creating a Shared Vision of the Future Enterprise 6. Understanding the Past, the Present, and the Change Required 7. Understanding the Nature of Change: Business and Organizational Life Cycles 8. Mobilizing the Three Essential Drivers for Change Part Three: From Strategy to Performance 9. Creating the Enterprise Development Workplan
Symbolic Recurrence Analysis of RR Interval to Detect Atrial Fibrillation

Atrial fibrillation (AF) is a sustained cardiac arrhythmia associated with stroke, heart failure, and related health conditions. Though easily diagnosed upon presentation in a clinical setting, the transient and/or intermittent emergence of AF episodes present diagnostic and clinical monitoring challenges that would ideally be met with automated ambulatory monitoring and detection. Current approaches to address these needs, commonly available both in smartphone applications and dedicated technologies, combine electrocardiogram (ECG) sensors with predictive algorithms to detect AF. These methods typically require extensive preprocessing, preliminary signal analysis, and the integration of a wide and complex array of features for the detection of AF events, and are consequently vulnerable to over-fitting. In this paper, we introduce the application of symbolic recurrence quantification analysis (SRQA) for the study of ECG signals and detection of AF events, which requires minimal pre-processing and allows the construction of highly accurate predictive algorithms from relatively few features. In addition, this approach is robust against commonly-encountered signal processing challenges that are expected in ambulatory monitoring contexts, including noisy and non-stationary data. We demonstrate the application of this method to yield a highly accurate predictive algorithm, which at optimal threshold values is 97.9% sensitive, 97.6% specific, and 97.7% accurate in classifying AF signals. To confirm the robust generalizability of this approach, we further evaluated its performance in the implementation of a 10-fold cross-validation paradigm, yielding 97.4% accuracy. In sum, these findings emphasize the robust utility of SRQA for the analysis of ECG signals and detection of AF. To the best of our knowledge, the proposed model is the first to incorporate symbolic analysis for AF beat detection.