Miracle-dz/UniFAR-FTUs huggingface dataset:
High flow nasal cannula effect on pulmonary complications after major elective upper abdominal surgeries: A randomized control study

ABSTRACT Background Postoperative pulmonary complications (PPCs) are a challenge for anesthesiologists, especially following major surgeries. Using a high-flow nasal cannula (HFNC) postoperatively may decrease this challenge. Purpose The study aimed to assess the clinical effect of HFNC after extubation compared with simple face mask oxygen following major elective upper abdominal surgeries regarding PPCs, the need to escalate the respiratory support, days of intensive care unit stay, and days of hospital stay. Methods Eighty adult patients were randomly assigned to two groups (each with 40 patients): group I received HFNC, while group II received a standard oxygen face mask. Five days later, postoperative pulmonary problems were evaluated. Results There was statistically significantly less lung atelectasis in the HFNC group than in the face mask group. The p-value was 0.029. There was no statistically significant difference concerning the need to escalate the respiratory support. The length of hospital and ICU stay days for the HFNC group was statistically significantly lower than for the face mask group. Conclusion HFNC is more efficient than a simple oxygen face mask in lowering lung atelectasis following major upper abdominal procedures, improving oxygenation with decreasing respiratory rate and reducing ICU and hospital days of stay.
Pre-hibernation energy reserves and their consumption during freezing in the moor frog Rana arvalis in Siberia

Abstract For the first time, the pre-hibernation sizes of “storage” organs (liver and fat bodies), the type, concentration and total content of reserve substances (glycogen or lipids) in these organs and muscle tissue, and their change during freezing in freeze tolerant specimens of the moor frog (Rana arvalis) in the Siberian population were studied. In autumn, the relative weight of the liver (hepatosomatic index) in the studied individuals reaches 10%, which is 2–4 times higher than in most species of Eurasian ranid frogs; this determines 2–4 times greater hepatic glycogen stores. The concentration of glycogen in the muscles is about 4.4 times lower than in the liver, but the total storage of glycogen in the muscles is 43–57% of the storage in the liver. The high degree of glycogen degradation upon freezing in both tissues may indicate that it is promising to search for either high levels of glucose or other cryoprotectants than in the ranid frogs studied so far. The content of lipids in the tissues in autumn is small and not completely consumed before freezing. Probably, lipids play an insignificant role in pre-winter metabolism, and are necessary for maintaining activity after overwintering. Thus, the highest freeze tolerance of the moor frog among the Eurasian ranid frogs (−14°C to −16°C in different Siberian populations) may be due to the high relative weight of the liver, which provides a large supply of glycogen before hibernation, the participation of muscle tissue in the deposition of almost a third part of all glycogen the body, significant consumption of glycogen during freezing for cryoprotectants. The patterns of storage and consumption of pre-hibernation energy resources in frogs of the genus Rana differ greatly not only between terrestrial and aquatic hibernators but also between freeze tolerant species.
The South African live events, technical and production services industry’s market position and COVID-19 funding implications

COVID-19 has had a significant economic impact on a global scale. The national lockdown, enacted through the Disaster Management Act 57 of 2002, disrupted multiple economic activities, including that of the Creative and Cultural industries. In the performance and celebrations domain, under which live events (.i.e., theatre and performance) and technical production services (i.e., technical support and services for theatre and performance) resort, the postponement or cancellation of events in the face of the pandemic had a devastating effect on lives and livelihoods. An initiative called #LightSAred, initiated by the South African Communications Industries Association (SACIA) and the Technical Production and Services Association, was one of the private initiatives aimed at extending financial relief to those who earn a living in the technical production and live events industry. However, the lack of reliable data about the industry's market and the impact of COVID-19 was a significant challenge in resource development and allocation. In response, the Sun Circle Group, a media company that services the live entertainment and professional audio-visual industries in South Africa, conducted an extensive online survey of businesses in this industry. For this study, permission has been obtained from the Sun Circle Group to analyse the secondary data set. Situated within the literature on the creative economy, analysing the secondary industry data in this article offers an understanding of the market position and perceived financial implications of the COVID-19 pandemic on the Live Events, Technical and Production Services industry. The results of this research support advocacy for a long-term national strategy to secure livelihoods and the sustainability of not only the Live Events, Technical and Production Services industry, but the CCIs as a whole.
On the degree of convergence of the Gram-Charlier series

The degree of convergence of Fourier series and of polynomial approximations has been extensively studied by Jackson,t and similar investigations have been made for series of Legendre polynomials,j for Sturm-Liouville series,? for Laplace's series,jj for Birkhoff's series,? and for other related problems. ** In all these cases the interval over which the convergence applies is finite. It is therefore of interest to inquire what are the corresponding facts in a case where the interval is infinite. Such a case is afforded by the Gram-Charlier series, which, in addition to having an infinite interval, is of interest and importance as a mathematical statement of the law of errorst t and because of its application to the representation of frequency functions. In the following pages we propose to examine the degree of convergence of the Gram-Charlier series and associated expansions, principally from the point of view of developments in characteristic solutions of homogeneous linear differential systems, a procedure which correlates the work closely with the previously cited papers on degree of convergence. The results obtained indicate that the Gram-Charlier series converges in general more slowly than the Fourier series for a similar function in a finite interval. Roughly speaking we may summarize the situation as follows: when the remainder after n terms of a Fourier series is O(1/nk) the remainder after n terms of the Gram-Charlier series is O(1/nkI2). 1. If we denote the normal probability function by Oo(x) and its derivative of order n by 4n(x), then
Techniques for In Vivo Assessment of Corneal Biomechanics

To assess the structural integrity of the cornea, non-invasive methods are needed for the local measurement of its mechanical properties. Among a number of established techniques and their associated advantages and disadvantages, Brillouin spectroscopy is still a relatively new technique, capa-ble of determining the compressive modulus of biological tissue, specifically the cornea, in vivo. In the present paper, these various existing and developing technologies for corneal biomechanics are discussed and correlated.
User Mobility Dataset for 5G Networks Based on GPS Geolocation

Geolocation technology is the most exciting area of advancement in 5G, leveraging massive sources of accurate location data to provide users with effective location-positioning services and applications. As research on user mobility prediction is steadily growing in the context of 5G networks, the need for available mobility-related data is of utmost importance to support the development and evaluation of new individual mobility patterns. This paper presents a novel mobility dataset generation method for 5G networks based on users' GPS trajectory data. First, we propose aggregating the user's GPS trajectories and modeling his location history by a mobility graph representing the set of cell base stations he passed through. Second, we implement the proposed modeling approach to build a custom mobility dataset and provide a detailed description of our methodology. The generated dataset relies on mobility traces from the real-world Geolife dataset and contains the mobility graph records of 128 users. Finally, we discuss selected use cases for which we believe our dataset would be valuable.
Optimal Bipartite Consensus Control for Unknown Coopetition Multi-agent Systems with Time-delay via Reinforcement Learning Method

In this article, a data-driven optimal bipartite consensus control (OBCC) scheme is proposed for unknown heterogeneous multi-agent systems (MASs) with time-delay via reinforcement learning (RL) algorithm. A directed signed graph is established to construct MASs with cooperative and competitive relationships, and model reduction method is developed to transform MASs with time-delay into a delay-free MASs. Then, based on Bellman’s optimal principle, a policy iteration method is utilized to design OBCC strategy. Further, based on Q-function, a model-free Q-function policy iteration algorithm is proposed to solve the OBCC problem for unknown MASs. And, only using input-output states of MASs to tackle the OBCC solution via RL algorithm, and it is implemented by actor-critic neural networks (NNs). Finally, simulation results are given to validate the feasibility and efficiency of the proposed algorithm.
Sidewinder: Snake Robot’s Stereo Vision System for Rescue in Collapsed Debris at Disaster Sites

In this paper, the authors present Sidewinder, a unique stereo vision system for snake-shaped robots operating in search and rescue scenarios. The robot should navigate the environment by finding and passing through narrow spaces (i.e., forward vision task) and search for persons in need of rescue (i.e., panoramic vision task). Therefore, we propose two types of image mapping methods to generate respectively input images for stereo visual SLAM and person detection. This work presents preliminary results using Sidewinder's images as input for the ORS-SLAM2 for localization and mapping, and YOLO-v3, for person detection.
Forming Tip Electrodes on 3D Neural Probe Arrays Using Electroplated Photoresist

We present a new fabrication technique that provides a repeatable, uniform, and time-saving method for exposing and metallizing tip electrodes in out-of-plane neural probe arrays. In order to form active electrode sites for neural recording or stimulation, the insulation layers covering the electrodes must be selectively removed. In this process, an electroplated photoresist (EP) is used to conformally coat three-dimensional (3D) insulated silicon needles, followed by exposure and development of the resist. The resist is then used as a mask layer to remove insulation layers only around the tip of the needles. EP has several advantages as a masking layer, including uniform coverage, low deposition temperature, wide thickness range, chemical stability, and easy removal. We have used this method to de-insulate the tips of 0.5-1.5 mm long, $20\ \mu\mathrm{m}$-diameter silicon needles in a 3D neural recording array. We have simulated the electroplating process on these arrays using COMSOL to determine the feasibility of the technology.
Lane Change Style Identification for Natural Driving Environments

In order to achieve accurate clustering and effective identification of driver lane changing style in natural driving environment, a driver lane changing style identification method for natural driving environment is proposed. Firstly, the improved hausdorff distance is used to perform spectral clustering and distinguish the lane change trajectory data. Nine parameters, such as vehicle transverse and longitudinal velocity and acceleration are selected to characterize the driver's lane-changing behavior. As well, the principal component analysis method is used to reduce the dimension of the characteristic data and synthesize the characteristic parameters that characterize the lane-changing style. Clustering and analyzing dimensionality-reduced feature data is then performed using the K-means, which is clustered out into three categories: aggressive lane changing style, cautious lane changing style and common lane changing style. Finally, the neural network is trained to realize the identification of lane changing style. According to the results derived from the identification of the HighD data set, the method can accurately detect the driver's lane-changing style, with an identification rate of 95.8%.
Transfer Molding Wire Sweep Improvement in QFP Packages by Mold Plunger Tips Design

Transfer molding is a plastic encapsulation conventional method for electronic components, which can be seen such as in semiconductors, where the cavity is filled with melted resin by using a plunger. The multi plunger system was developed and used in more than a decade to supply resin from multiple holes when injecting resin into the cavity can greatly shorten the resin molding cycle and increase productivity. However, in QFP (Quad Flat Packages), wire sweep still the main challenge facing especially for the side gate transfer molding. After the plunger injected the EMC (Epoxy molding compound) into units on leadframe, there was flashes remain inside pot and plunger. These excess flashes remained was sticky and stubborn, which difficult to remove by mold vacuum cleaning system. If these flashes keep remain, it will potentially block the mold gate and disturb the mold flow into cavity resulting in wire sweep. Simulation been done to compare the mold flow behavior, while the change of the plunger tips design from flat type to chamfer type had been studied in order to minimize these excess flashes remain at the end of transfer filling process and improve the wire sweep. Evaluation also been performed to confirm the workability and effectiveness on the chamfer plunger type design towards the wire sweep improvement. Wire looping optimization for critical wires also been performed to continue improve wire sweep in QFP side gate molding from above 11 percent to within 5 percent.
Leader-Follower Multiagent Systems Containment with Prescribed Instant

In this paper, the prescribed-instant stability control is proposed and utilized in the leader-follower multiagent system with a directed communication topology. The proposed prescribed-instant stability ensures the settling time is exactly equal to the prescribed time instant. Therefore, the specific time instant at which the system containment is established can be manipulated as per our will. This result is of great significance in some complex multiagent system cooperation tasks. The proof of the main result is demonstrated by the Lyapunov method, Specifically, the settling time is clamped from two sides to the selected time instant. Apart from the theoretical proof, a numerical simulation is also presented to validate the proposed method.
Flexible Multilayer Tactile Sensor on a Soft Robotic Fingertip

Tactile sensing is an integral aspect of interacting with our environment, where textural information can be essential to properly manipulate objects. Soft robotic fingers are compliant biomimetic solutions for upper-limb prosthesis. Therefore, adding tactile sensing capabilities such as texture discrimination on a soft robotic finger can create a compliant and precise prosthetic hand for an amputee. In this study, we emulate a human fingertip by incorporating a flexible, biomimetic, and multilayered tactile sensor into a soft robotic fingertip for a texture discrimination task where thirteen textures were passively palpated. The sensor was able to achieve a texture classification accuracy of 97.12% when the sensor output was neuromorphically encoded to mimic the receptors in human skin. This work is a step in the direction of a more human-like prosthetic hand to help enhance amputees' perception and interaction with their environment.
Towards a sustainable outcomes-based education guided by knowledge management system: expoleIT design and development roadmap

Knowledge management (KM) is the most significant element for innovation and sustainability. Successful outcomes-based education (OBE) adoption requires sustainable quality practices including careful planning and active collaboration among stakeholders by higher education institutions (HEIs). Decomposed from the problems, the design parameters of a knowledge management system (KMS) incorporate the arrangement and use of a messaging module utilized for imparting and spreading information to an organization; authoring, evaluation, and profiling modules utilized for a collaborative advancement and dispersal of information; and a digital library and an academic profiling module utilized for storing, retrieving and mining the institutional OBE knowledge. Essentially, to develop the HEI’s KM practices, the KMS framework was intended to enlighten the stakeholders on whose knowledge, what sort of knowledge, how, and why they need to oversee OBE knowledge. Given the ISO 9241-11 norm, the expoleIT website was effective, efficient, and acknowledged by the participants in their specific set of purposes. The participants need more time to adapt to the system and some of the stakeholders are novice users in using this kind of system. The institution shall start its journey to curriculum excellence with this roadmap as it hit the road with its OBE implementation activities. While data mining techniques, like decision trees, can improve curriculum development in higher education, future work includes incorporating it into the website to help teachers and trainers in constructive alignment when building an OBE syllabus. Likewise, when grouping students for capstone projects and other activities.
Heat transfer in granular materials: effects of nonlinear heat conduction and viscous dissipation

In this paper, we study the heat transfer in a one‐dimensional fully developed flow of granular materials down a heated inclined plane. For the heat flux vector, we use a recently derived constitutive equation that reflects the dependence of the heat flux vector on the temperature gradient, the density gradient, and the velocity gradient in an appropriate frame invariant formulation. We use two different boundary conditions at the inclined surface: a constant temperature boundary condition and an adiabatic condition. A parametric study is performed to examine the effects of the material dimensionless parameters. The derived governing equations are coupled nonlinear second‐order ordinary differential equations, which are solved numerically, and the results are shown for the temperature, volume fraction, and velocity profiles. Copyright © 2013 John Wiley & Sons, Ltd.
Ionic polymer metal composite-based microfluidic flow sensor for bio-MEMS applications

Sensing flow rates in structured microenvironments like lab-on-chip (LOC) and organ-on-chip (OoC) is crucial to assess important parameters such as transport of media and molecules of interest. So far, these micro-electromechanical systems for biology (bio-MEMS) mostly rely on flow sensing systems based on thermal sensors. However, thermal flow sensing has limitations, since the measurement principle, which is based on generation of heat, can negatively affect the biological system by increasing the fluid temperature above physiological conditions. To overcome this issue, we propose a novel electro-mechanical flow sensor centered around the deformation of a cantilever made of a thin and biocompatible ionic electroactive polymer. The polymer, called ionic polymer metal composite (IPMC), is doped with ions naturally present in most cell media for LOC and OoC devices. Unlike already existing cantilever-based systems which rely on piezo sensitive materials, our IPMC-based flow sensor shows durability in wet environment. We were able to successfully measure pulsatile flow induced by pipetting with flowrate gradually increasing from $10\mu\mathrm{L}/\mathrm{s}$ to $40\ \mu\mathrm{L}/\mathrm{s}$. The proposed flow sensor shows good sensing capabilities (4.78 $\text{mV}/(\mu\mathrm{L}/\mathrm{s}))$ with a linear behavior in the studied range. This work sets a milestone for using flexible, electroactive materials for sensing applications in delicate biological microenvironments.
A Distance Based Freshness Evaluation Method for Oyster Monitoring by Electronic Nose

Oysters have high nutritional value and will rapidly inactivated when they leave their native environment, which makes the detection and evaluation of oyster freshness value much. To make the oyster monitoring noninvasive, a distance-based freshness evaluation method by electronic nose is proposed. Oyster samples of different degrees of freshness at storage conditions were tested for 8 consecutive days using a laboratory-developed electronic nose. Features were extracted and downscaled by Principal Component Analysis (PCA). Taking the sample of day 1 as the base, the Euclidean distance between the samples of following days and the base was proposed as the degree of deviation of freshness. Results prove the method interesting to evaluate the oyster freshness noninvasive.
GatorByte: A Water-Quality Mapping Buoy for Locating Watershed Pollution Sources

Currently, many available water resource monitoring systems and data loggers can be cost-prohibitive and are limited in spatial scale. These systems are frequently deployable as unattended stations or used as a handheld device. Hence, locating pollutant sources is difficult and relies on inference and watershed modeling. GatorByte is a mobile water-quality monitoring platform for collecting spatiotemporal water quality data. The GatorByte platform includes a data logger, a cloud-based server, and visualization tools. It uses low-cost sensors, components, a 3D-printed enclosure, and a Printed Circuit Board. The data logger uses a 4G-capable Arduino for real-time reporting of the sensor data. Currently, the GatorByte houses sensors for measuring pH, temperature, dissolved oxygen, and electroconductivity. The data logger also includes micro-SD storage and a Bluetooth module for on-field diagnostics. The buoy includes a GPS module for recording the location for every set of sensor readings and tracking the buoy in real-time. Using GatorByte, recording of variations in water quality data in both temporal and spatial dimensions can be achieved in a cost-effective and reliable manner, enabling quick detection and resolution of pollution events.
Machine Learning Approaches for Student Performance Prediction

India's Education system is very old and due to a large population of students in India, there are some serious issues in analyzing and predicting students' performance. In the Indian Context, every institution has its own set of standards for evaluating student success, there is no proper procedure for monitoring and analyzing a student's performance and progress. One of the major factors is lack of research in existing prediction approaches, making it difficult to determine the optimal prediction methodology for visualizing student academic growth and performance. Another reason could be the lack of research into the areas that can affect students' academic performance and achievement. In this paper, focus is given on additional external factors like geographical location, parent education, health status etc. that can affect a students' performances apart from the grades in any course. That will be more effective in visualizing and analyzing student's performance. For experimental work, data has been collected from UCI repository and results are obtained from two different machine learning algorithms (KNN and Logistic Regression). Performance analysis is also done for these two algorithms based on accuracy level of results as well as with some existing work.