Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Implementation of an Evidence-Based Guideline for Spinal Cord Injury/Disorder Patients Requiring Colonoscopy

Practice Problem: Colorectal cancer is one of the leading causes of preventable cancer death in the United States. Spinal cord injury/disorder (SCI/D) patients present with unique challenges for maximizing bowel prep and successful attainment of screening and therapeutic colonoscopy procedures. Current practice for bowel prep regimen does not take into consideration the specific needs of the SCI/D population resulting in significant patient dissatisfaction. PICOT: The PICOT question that guided this project was in adult patients with spinal cord injuries/disorders requiring colonoscopy (P), how does the development and implementation of evidence-based guideline for the care of the spinal cord injury/disorder patient requiring colonoscopy (I) compared to usual practice (C) affect the rate of first attempt successful colonoscopy procedure completion (O) within eight weeks (T). Evidence: SCI/D patients resulting neurogenic bowel increases difficulty with standard bowel prep tolerance. Quality bowel preparation is required for successful colonoscopy with inadequate bowel preparations present in 20-25% of all colonoscopies (Johnson et al., 2014). Evidence supports a clinical guideline for bowel preparation adapted to the needs of the SCI/D population. Intervention: Development and implementation of an SCI/D bowel prep guideline enhanced clinical decision support and evidence-based tools for improved bowel prep with initial attempt. Outcome: The rate of first-time colonoscopies for patients with SCI/D with the guideline improved by over 214% over pre-guideline time. Conclusion: The evidenced-based guideline reinforced clinical practice for the SCI/D population related to their unique requirements. Clinically significant improvement was noted in successful bowel prep completion, first attempt colonoscopy completion, improved access to the endoscopy suite, and reduced length of stay. All combined improved both patient and provider satisfaction with the evidence-based practice change.
Fiber Optic Sensors for Bridge Monitoring

Advances in the production of optical fibers made possible the recent development of innovative sensing systems for the health monitoring of civil structures. The main reasons for this development are the reduced weight and dimensions of fiber optic sensors, the strong immunity to electromagnetic interference, the improved environmental resistance and the scale flexibility for small-gauge and long-gauge measurements. These systems can provide high-resolution and measurement capabilities that are not feasible with conventional technologies. In addition, they can be manufactured at a low cost and they offer a number of key advantages, including the ability to multiplex an appreciable number of sensors along a single fiber and interrogate such systems over large distances. For these reasons, it is evident that fiber optic sensors will change the instrumentation industry in the same way fiber optics has revolutionized communications. This paper provides an overview of the intensity modulated and spectrometric fiber optic sensors and techniques to assess the condition of existing structures in order to enhance the durability of the new bridges, increasing lifetime and reliability and decreasing maintenance activities. Application of these sensors to monitoring strain, temperature, inclination, acceleration, load measurements, ice detection, vehicles speeds and weights, and corrosion and cracking of reinforced and prestressed concrete structures will be described.
Application of Due Process in Recruitment and Selection of Personnel into the Federal Civil Service. Part 1

This study was conducted to investigate the constraint to the effective application of due process in the recruitment and selection of personnel into the federal civil service. Four objectives and four research questions guided the study. A sampling technique was used in carrying out the work. A total number of three hundred (300) respondents were used for the study. The instruments for data collection were a questionnaire and observation checklist. Three hundred (300) copies of the questionnaire were distributed to the staff of the Federal Civil Service Commission (FCSC), Abuja and two hundred and seventy-six (276) were returned representing a 92% return rate. The frequency table and Mean were the statistical measures employed for the data analysis. The findings revealed that there were no strategies or methods of recruitment and selection of staff into the federal civil service. However, the findings also revealed that practices such as political interference and corruption during recruitment and selection in federal civil service tend to undermine the principle of due process. Based on the findings, it was recommended that the federal civil service commission should formulate sound policies and practices that will minimize the degree of politicization and corruption in the recruitment and selection of staff into the federal civil service; make use of modern sources and techniques of recruitment and selection such as, E-recruitment process and Information Communication Technology (ICT)-based selection resources as their source of recruitment and selection; and develop strategies or methods that will result in the effective application of due process in their recruitment and selection exercises.
Optimal design of a vibration-based energy harvester using magnetostrictive material (MsM)

In this study, an optimal vibration-based energy harvesting system using magnetostrictive material (MsM) was designed and tested to enable the powering of a wireless sensor. In particular, the conversion efficiency, converting from magnetic to electric energy, is approximately modeled from the magnetic field induced by the beam vibration. A number of factors that affect the output power such as the number of MsM layers, coil design and load matching are analyzed and explored in the design optimization. From the measurements, the open-circuit voltage can reach 1.5 V when the MsM cantilever beam operates at the second natural frequency 324 Hz. The AC output power is 970 µW, giving a power density of 279 µW cm − 3. The attempt to use electrical reactive components (either inductors or capacitors) to resonate the system at any frequency has also been analyzed and tested experimentally. The results showed that this approach is not feasible to optimize the power. Since the MsM device has low output voltage characteristics, a full-wave quadrupler has been designed to boost the rectified output voltage. To deliver the maximum output power to the load, a complex conjugate impedance matching between the load and the MsM device is implemented using a discontinuous conduction mode (DCM) buck-boost converter. The DC output power after the voltage quadrupler reaches 705 µW and the corresponding power density is 202 µW cm − 3. The output power delivered to a lithium rechargeable battery is around 630 µW, independent of the load resistance.
Pulsed Laser Deposition and Laser-Induced Backward Transfer to Modify Polydimethylsiloxane

Polydimethylsiloxane (PDMS) is a silicone-elastomer that owes its large application in the field of stretchable electronics to its chemical and thermal stability, transparency, flexibility, non-toxicity, compatibility, and low cost. PDMS is a versatile material because it can be used both as an elastic substrate and, after functionalization, as an active material for the design of stretchable electronics. One possible route for the functionalization of PDMS, thus becoming an active material together with numerous metals and semiconductors, is the embedding of conductive nanomaterials. Presently, pulsed laser deposition (PLD) and laser-induced backward transfer (LIBT) are used to deposit carbon- based material on polydimethylsiloxane. In this study, we explore and compare the surface treatments, advantages, and disadvantages of both different employed techniques in different environments. The modification of the wettability, elasticity, morphology, composition, and optical characteristics of polydimethylsiloxane will be evaluated by surface techniques such as scanning electron microscopy, Rutherford backscattering spectrometry, and the sessile drop method.
Towards Generating Financial Reports from Tabular Data Using Transformers

Financial reports are commonplace in the business world, but are long and tedious to produce. These reports mostly consist of tables with written sections describing these tables. Automating the process of creating these reports, even partially has the potential to save a company time and resources that could be spent on more creative tasks. We implement a transformer network to solve the task of generating this text. By generating matching pairs between tables and sentences found in financial documents, we created a dataset for our transformer. We were able to achieve promising results, with the final model reaching a BLEU score of 63.3. Generated sentences are natural, grammatically correct and mostly faithful to the information found in the tables.
Noether’s theorem for Herglotz type variational problems utilizing complex fractional derivatives

This is a review article which elaborates the results presented in [1], where the variational principle of Herglotz type with a Lagrangian that depends on fractional derivatives of both real and complex orders is formulated and the invariance of this principle under the action of a local group of symmetries is determined. The conservation law for the corresponding fractional Euler Lagrange equation is obtained and a sequence of approximations of a fractional Euler-Lagrange equation by systems of integer order equations established and analyzed.
Enriching Academia-Corporate Loop (ACL)—A Corporate Social Responsibility Initiative

Corporate sector utilises societal resources. It is thus the duty of corporate sector to give back to the society in any form, which we know as corporate social responsibility. When we talk in this context, we generally take into account activities like educating the poor, helping old age homes, going green, reducing waste, sponsoring sports activities, giving donations etc. The problem of not getting employable manpower is a major issue of concern among the corporates. In this paper we propose a new dimension to corporate social responsibility—“Enhancing employability”. By this the Academia-Corporate Loop (ACL) can be enriched. In our study we conduct a schedule amongst white collar employees of organizations in Delhi/NCR and record their responses. On this basis, we check the acceptability of this concept in corporates’ mind and propose an action plan to bridge this gap statistically.
Open Government Data

Story Slides Slide 1 W3C eGovernment Community: Data Science Slide 2 Agenda Slide 3 The Changing Landscape of Federal Information Technology Slide 4 Cloud: SOA, Semantic, & Data Science: September 10-11th Slide 5 Opportunities for Data Science Slide 6 Discussion 1 Slide 7 Discussion 2 Slide 8 Discussion 3 Slide 9 Discussion 4 Slide 10 Discussion 5 Spotfire Dashboard Research Notes Joshua Tauberer’s Blog Open Government Data 1 Big Data Meets Open Government Figure 1 The New Federal Register 2.0 Figure 2 This animated visualization of live wind speeds and directions Figure 3 Data is like refrigerator poetry Figure 4 http://www.GovTrack. us Figure 5 John Oliver parodies Schoolhouse Rock’s “I’m Just a Bill” References 1 2 3 4 5 6 7
Dynamic optimization of a biped model: Energetic walking gaits with different mechanical and gait parameters

Energy consumption is one of the problems for bipedal robots walking. For the purpose of studying the parameter effects on the design of energetic walking bipeds with strong adaptability, we use a dynamic optimization method on our new walking model to first investigate the effects of the mechanical parameters, including mass and length distribution, on the walking efficiency. Then, we study the energetic walking gait features with the combinations of walking speed and step length. Our walking model is designed upon Srinivasan’s model. Dynamic optimization is used for a free search with minimal constraints. The results show that the cost of transport of a certain gait increases with the increase in the mass and length distribution parameters, except for that the cost of transport decreases with big length distribution parameter and long step length. We can also find a corresponding range of walking speed and step length, in which the variation in one of the two parameters has no obvious effect on the cost of transport. With fixed mechanical parameters, the cost of transport increases with the increase in the walking speed. There is a speed–step length relationship for walking with minimal cost of transport. The hip torque output strategy is adjusted in two situations to meet the walking requirements.
A Robust Two-Factor User Authentication Scheme-Based ECC for Smart Home in IoT

The unprecedented proliferation of smart home together with wireless sensor networks has enriched human’s daily life. Inevitably, the smart home without the guard of authentication mechanism is bound to bring a series of security issues. Hence, a great number of authentication protocols have been designed to verify the user’s identity and ensure that the data be accessed with authorization in smart home. Recently, (M. Shuai et al., 2019) (Computers & Security, 2019) proposed a two-factor anonymous authentication scheme for smart home and presented that their scheme can be immune to various attacks. However, by careful analysis, we found that (M. Shuai et al.’s, 2019) scheme needed further improvements in session key forward secrecy and against: type-I node capture attack and node impersonation attack. As a going step to this direction, here, we first design a robust two-factor user authentication also for smart home based on the elliptic curve cryptography. Second, we give security proofs to demonstrate that the construction of the proposed scheme can be of user anonymity, session key forward secrecy, and resist all attacks shown in this article. Third, performance comparisons covered in storage/network communication/computation costs are carried out to indicate that our scheme can be comparable to those newly designed schemes, especially, the user and gateway in our scheme need only 352 and 320 bits, respectively.
Application of Intelligent Ultrasound in Real-Time Monitoring of Postoperative Analgesic Nerve Block

In order to monitor the effect of nerve block in postoperative analgesia more accurately, this paper puts forward the application research of ultrasonic real-time intelligent monitoring of nerve block in postoperative analgesia. Ultrasonic real-time intelligent monitoring of nerve block in upper limb surgery, lower limb surgery, and abdominal surgery combined with the nerve stimulator. The experiments show that there are 5 cases of adverse reactions when the nerve stimulator is only used, but no adverse reactions occur when combined with ultrasound-guided block. Continuous subclavian brachial plexus block with the ultrasound-guided nerve stimulator can clearly see the subclavian brachial plexus and its surrounding tissue structure, the direction of needle insertion in the plane, and the diffusion of narcotic drugs. The average success rate of block was up to 95.2%, which was significantly higher than that of nerve stimulator alone, and the success rate of recatheterization after the first failure was also improved. The average postoperative analgesia satisfaction was 85.6%, the average operation time was only 20 min, and the subclavian artery and pleura were avoided effectively. No pneumothorax and other complications occurred. The average success rate of ultrasound-guided subclavicular brachial plexus block in 1-2-year-old children was 97%, which was much higher than the average success rate of nerve stimulator localization with 63%. Ultrasound-guided nerve block not only directly blocks nerves under visual conditions but also helps to observe the structures around nerves and dynamically observe the diffusion of local anesthetics, which can significantly improve the accuracy and success rate of nerve block and reduce the incidence of complications.
Effects of Short-term Mobile Application Use on Weight Reduction for Patients with Type 2 Diabetes

Background The increasing prevalence of type 2 diabetes mellitus (T2DM) has led to a significant health burden. Technological advancements have highlighted the benefits of digital therapeutics for chronic diseases. In this study, we aimed to investigate the effects of a mobile application on weight reduction in patients with T2DM. Methods A total of 48 patients with T2DM was included in this single-center, randomized, controlled trial. In addition to conventional treatment, participants in the intervention group used a mobile application-based self-management system for diet, exercise, and medication adherence. The primary outcome of this study was weight change after 3 months of intervention, and secondary outcomes were metabolic parameters. Results After 12 weeks, no significant differences in body weight change were observed between the intervention and control groups (P=0.229). However, a significant difference was found in waist circumference (WC) between the two groups, wherein the control group showed an increase in WC (from 95.00±8.89 cm to 95.76±9.72 cm), while the intervention group showed a reduction (from 91.93±6.25 cm to 90.75±6.01 cm) with a significant time by group interaction (P=0.016). Additionally, participants with good compliance exhibited a more evident reduction in WC (P=0.037). However, no significant differences were found in other metabolic parameters between the two groups. Conclusion Lifestyle modification using short-term mobile applications effectively reduced WC, especially in patients with good adherence to the application. However, weight reduction was not achieved.
Optimizing Customized Transit Service considering Stochastic Bus Arrival Time

The introduction of customized bus (CB) service intends to expand and elevate existing transit service, which offers an efficient and sustainable alternative to serve commuters. A probabilistic model is proposed to optimize CB service with mixed vehicle sizes in an urban setting considering stochastic bus arrival time and spatiotemporal demand, which minimizes total cost subject to bus capacity and time window constraints. The studied optimization problem is combinatorial with many decision variables including vehicle assignment, bus routes, timetables, and fleet size. A heuristic algorithm is developed, which integrates a hybrid genetic algorithm (HGA) and adaptive destroy-and-repair (ADAR) method. The efficiency of HGA-ADAR is demonstrated through numerical comparisons to the solutions obtained by LINGO and HGA. Numerical instances are carried out, and the results suggested that the probabilistic model considering stochastic bus arrival time is valuable and can dramatically reduce the total cost and early and late arrival penalties. A case study is conducted in which the proposed model is applied to optimize a real-world CB service in Xi’an, China. The relationship between decision variables and model parameters is explored. The impacts of time window and variance of bus arrival time, which significantly affect service reliability, are analysed.
HEALTH RISK ASSESSMENT AND BLACK CARBON: STATE OF ART AND NEW PROSPECTIVES

The characterization of health risks (HRA) in a population due to air pollution is crucial for the development of effective risk management policies and strategies. HRA is a formally required tool by nations as part of the decision-making process for new programs, regulations and policies that affect air quality, so it is important for decision makers to understand what resources are needed and what limitations may exist. In the hazard identification phase at local and urban level, concentration data provided by local monitors are used, but one of the main shortcomings is that population exposure estimates based on these data are often limited by the sparse geographic-temporal coverage of the measurements. Often the HRA evaluation does not take into account the complex chemical composition of the suspended particulate and therefore the different toxicity and oxidation potential associated with it. Current air quality standards for particulate matter (PM) use the mass concentration of PM (PM10, PM2.5) as a metric, but particles from combustion sources are more relevant to human health compared to particles from other sources and the impact of policies to reduce PM from combustion processes, is relatively small when estimating the effects for a reduction in total mass concentration. This research highlights the value of black carbon (BC) particles as a possible additional indicator in the management of air quality in Turin (north Italy), one of the most affected Italian cities by smog where a high number of asthmatics and allergic people are exposed every day to PM concentrations higher than the legal limits. According to the Council on Clean Transportation, Turin is among the top 100 cities in the world with a higher number of deaths due to respiratory diseases caused by transport. BC could be a valuable additional air quality indicator to assess human health risks caused by primary combustion particles.
New magneto-inductive sensing principle and its implementation in sensors for industrial applications

Non-contacting displacement measuring systems are nowadays preferred for industrial position feedback at actuators. The systems are based on various operating principles whose properties determine the potential areas of application. In spite of the large number of solutions available on the market, there still are applications that are inaccessible to any of the familiar transducers. When linear motion in a range of up to 200 mm is involved, compromises almost always have to be made with respect to size, measuring range, durability and costs. The paper presents a worldwide innovation on this field: a new magneto-inductive sensing principle and displacement measuring system especially developed for positioning tasks in the above mentioned range. Due to its flexibility, ruggedness and compact design, it is ideal for numerous industrial applications and even opens up areas for new implementations. Consisting of a slender, rectangular sensor with fully integrated processing electronics and a permanent magnet target, the system converts the target position into an absolute, displacement-proportional voltage and current standard signal.
OVAL'S AUTO-INJECTOR PLATFORM FOR THE DELIVERY OF HIGH-VISCOSITY DRUGS

Drug development pipelines are tending towards increasing numbers of injectable products, and amongst these an ever larger proportion are viscous biologics and sustained-release formulations. Set against this backdrop, Susanna White, Mechanical Engineer, Oval Medical Technologies, and Louisa Harvey, Director, Harvey Medical, and Consultant to Oval, provide an overview of some of the considerations and challenges faced when designing delivery systems for viscous formulations, and describes Oval’s unique high-viscosity drug delivery device platform.