Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Patient-Controlled Analgesia With Tramadol or Morphine After Video-Assisted Thoracoscopic Surgery in Geriatric Patients

Background Although video-assisted thoracoscopic surgery (VATS) is a less invasive technique compared to thoracotomy, patients often experience postoperative pain. Hence, intravenous patient-controlled analgesia (PCA) is frequently used. The geriatric age group constitutes a significant portion of patients undergoing thoracic surgery. However, pain management can often be difficult in elderly patients. In this study, we aimed to examine the pain management techniques applied in geriatric patients who underwent VATS and to compare the efficacy and side effects of PCA with morphine and tramadol. Methodology The following patients were included in this study: aged 65 years and older, those who underwent elective VATS under general anesthesia, and those who underwent thoracic paravertebral block in the operating room for postoperative pain. We recorded diagnoses, demographic data, American Society of Anesthesiologists status, complications developed during the intraoperative or postoperative 24 hours, postoperative rest and cough Visual Analog Scale (VAS), and need for additional analgesics. The patients were divided into the following two groups: those treated with tramadol PCA (tramadol group) and those treated with morphine PCA (morphine group). Results A total of 65 patients were included in this study. Overall, 22 patients were administered tramadol PCA while 43 were administered morphine PCA. There was no statistically significant difference between the groups concerning complications. The 24-hour VAS resting score was statistically significantly lower in patients administered morphine than those administered tramadol (p < 0.05). There was no statistically significant difference between the groups concerning zero-minute, thirty-minute, one-hour, two-hour, six-hour, and twelve-hour VAS resting and cough scores at all times (p > 0.05). Conclusions There was no significant difference in the tramadol and morphine groups concerning analgesic efficacy, patient satisfaction, and side effects among geriatric patients who underwent VATS and were administered intravenous PCA. In our view, both tramadol and morphine can be used safely in geriatric patients requiring intravenous PCA. Moreover, because the 24-hour analgesic efficacy was observed to be better in the morphine group in our study, morphine can be preferred in geriatric patients.
Location-based social networking media for restaurant promotion and food review using mobile application

This paper is focusing on the development of a mobile application for searching restaurants and promotions with location based and social networking features. The main function of the application is to search restaurant information. Other functions are also available in this application such as add restaurant, add promotion, add photo, add food review, and other features including social networking features. The restaurant and promotion searching application will be developed under Android platform. Upon completion of this paper, heuristic evaluation and usability testing have been conducted. The result of both testing shows that the application is highly usable. Even though there are some usability problems discovered, the problems can be eliminated immediately by implementing the recommendations from the expert evaluators and the users as the testers of the application. Further improvement made to the application will ensure that the application can really be beneficial for the users of the application.
DD-FoG: Intelligent Distributed Dynamic FoG Computing Framework

Nowadays, 5G networks are emerged and designed to integrate all the achievements of mobile and fixed communication networks, in which it can provide ultra-high data speeds and enable a broad range of new services with new cloud computing structures such as fog and edge. In spite of this, the complex nature of the system, especially with the varying network conditions, variety of possible mechanisms, hardware, and protocols, makes communication between these technologies challenging. To this end, in this paper, we proposed a new distributed and fog (DD-fog) framework for software development, in which fog and mobile edge computing (MEC) technologies and microservices approach are jointly considered. More specifically, based on the computational and network capabilities, this framework provides a microservices migration between fog structures and elements, in which user query statistics in each of the fog structures are considered. In addition, a new modern solution was proposed for IoT-based application development and deployment, which provides new time constraint services like a tactile internet, autonomous vehicles, etc. Moreover, to maintain quality service delivery services, two different algorithms have been developed to pick load points in the search mechanism for congestion of users and find the fog migration node. Finally, simulation results proved that the proposed framework could reduce the execution time of the microservice function by up to 70% by deploying the rational allocation of resources reasonably.
A Dynamic View on Strategic Resources and Capabilities Applied to an Example from the Manufacturing Strategy Literature

Purpose – The purpose of this paper is to demonstrate the usefulness of a dynamic analysis of the development and management of strategic capabilities and resources in manufacturing. It aims to present dynamic resource/capability systems as a means to understand an issue from manufacturing strategy.Design/methodology/approach – A case study from a standard textbook on manufacturing strategy is used to illustrate the approach that is mainly based on Warren's strategy dynamics. Extensions to this approach are introduced.Findings – Diagrams of dynamic resource/capability systems are valuable tools for understanding issues of interconnected and changing strategic resources and capabilities. Resources and capabilities can be interpreted as stocks in dynamic simulation models following ideas from system dynamics.Research limitations/implications – The exact nature of strategic capabilities and their relationships needs to be further investigated. Approaches need to be developed to measure and to quantify these .
The Effect of Rumination Time on Milk Performance and Methane Emission of Dairy Cows Fed Partial Mixed Ration Based on Maize Silage

Simple Summary Greenhouse gas emission has attracted considerable public attention in recent years, driving the search for genetic, nutritional, and management strategies to reduce methane emissions and increase the sustainability of milk production. Rumination activity has an important function in feed particle size reduction, condition of feeding behavior, and feed intake as well as in stabilizing rumen fluid pH through saliva production. A total of 365 high-yielding Polish Holstein -Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). We showed that a longer rumination time leads to a lower methane emission level. Therefore, strategies that increase chewing activity may be used to reduce the environmental impact of dairy cows production. Abstract The objective of this study was to determine the effect of the rumination time on milk yield and composition as well as methane emission during lactation in high-yielding dairy cows fed a partial mixed ration based on maize silage without pasture access. A total of 365 high-yielding Polish Holstein-Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Methane emission, rumination time, and milk production traits were observed for the period of 12 months. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). Rumination time had no effect on milk yield, energy-corrected milk yield, or fat and protein-corrected milk yield. High rumination time had an effect on lower fat concentration in milk compared with the medium and low rumination groups. The highest daily CH4 production was noted in low rumination cows, which emitted 1.8% more CH4 than medium rumination cows and 4.2% more than high rumination cows. Rumination time affected daily methane production per kg of milk. Cows from the high rumination group produced 2.9% less CH4 per milk unit compared to medium rumination cows and 4.6% in comparison to low rumination cows. Similar observations were noted for daily CH4 production per ECM unit. In conclusion, a longer rumination time is connected with lower methane emission as well as lower methane production per milk unit in high-yielding dairy cows fed a maize silage-based partial mixed ration without pasture access.
A Design Space Exploration Method Using Artificial Neural Networks and Metamodeling

This paper suggests a design space exploration method using Artificial Neural Networks and metamodeling to systematically reduce the design space to a relatively small region. This method consists of three major steps. Firstly, self-organizing maps is employed to analyze design variables and objective function(s) with the original samples as preliminary reduction optimization of the initial large design space. Successively, resampling within the preliminary reduction space, clustering sample points using the fuzzy c-means clustering method with the given number of cluster, and choosing the most attractive cluster to construct kriging model and identify the design optimum within the reduced design space in the last step. The accuracy and validity of proposed methodology is proved by a heat exchanger design problem. It is found that the proposed method can intuitively capture promising design regions in which it is efficient to acquire the global or near-global desigm optimum.
Novel sinusoidal converters with high power factor

This paper proposes a novel sinusoidal converter which improves input power factor and input current waveform without any complicated switching modulation such as a pulse width modulation or a complicated feed-back control. It is composed of a full bridge diode, a pair of capacitors, a pair of inductors and a pair of switching devices. The configuration and control strategy are both simple, however, the sinusoidal converter effectively reduces reactive power and harmonics included in an input line current. Excellent behavior of the proposed converter is verified by theoretical analysis and experimental results. <<ETX>>
A Novel Approach to Determine Static Voltage Stability Limit and Its Improvement Using TCSC and SVC

Determination of the steady state voltage stability is essential in power system operation and planning. Conventional method of finding the maximum or critical loading point (CLP), suffers from huge computational time and iteration. In this paper an adaptive neuro fuzzy inference system (ANFIS) is used to control the step length of a conventional continuation power flow (CPF) method in determining CLP and nose curves (PV – curves). Modal analysis technique is adopted to identify the vulnerable load buses and critical branches of a power system, for the effective placement of FACTS devices. Static VAR Compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC) are used in the identified location to enhance the static voltage stability limit of the power system. The proposed approach is successfully applied to 9 bus, New England 39 bus and IEEE 118 bus system and the results are reported.
"Immunogenicity and Safety of Sinopharm COVID-19 vaccine in young mice"

to prevent infection may be considered a promising way for reduction of the pandemic. Many different vaccines have become obtainable for use in many countries. The present study aims to evaluate the immune response and the safety of Sinopharm COVID-19 vaccine on 14 days old mice. Materials and Methods: Our experimental study was performed on two weeks old mice, selected by random allocation. The mice were divided into three groups of 12. Group one received a single dose of 0.5 ml Sinopharm COVID-19 vaccine, group two received two doses of 0.5 ml Sinopharm COVID-19 vaccine, and group three (control) received two doses of 0.5 ml of 0.9 % NaCl. Results: Our study shows that Sinopharm COVID-19 vaccine is safe and induces good immunity in young mice. Conclusions: The Sinopharm COVID-19 vaccine was safe and immunogenic in 14 days old mice. The two doses of Sinopharm COVID-19 vaccine elicit a safe antibody response in young mice. Further post-marketing toxicity studies are required to assess potential hazards for children to evaluate the histopathological characteristics.
A Unified FPGA Virtualization Framework for General-Purpose Deep Neural Networks in the Cloud

INFerence-as-a-Service (INFaaS) has become a primary workload in the cloud. However, existing FPGA-based Deep Neural Network (DNN) accelerators are mainly optimized for the fastest speed of a single task, while the multi-tenancy of INFaaS has not been explored yet. As the demand for INFaaS keeps growing, simply increasing the number of FPGA-based DNN accelerators is not cost-effective, while merely sharing these single-task optimized DNN accelerators in a time-division multiplexing way could lead to poor isolation and high-performance loss for INFaaS. On the other hand, current cloud-based DNN accelerators have excessive compilation overhead, especially when scaling out to multi-FPGA systems for multi-tenant sharing, leading to unacceptable compilation costs for both offline deployment and online reconfiguration. Therefore, it is far from providing efficient and flexible FPGA virtualization for public and private cloud scenarios. Aiming to solve these problems, we propose a unified virtualization framework for general-purpose deep neural networks in the cloud, enabling multi-tenant sharing for both the Convolution Neural Network (CNN), and the Recurrent Neural Network (RNN) accelerators on a single FPGA. The isolation is enabled by introducing a two-level instruction dispatch module and a multi-core based hardware resources pool. Such designs provide isolated and runtime-programmable hardware resources, which further leads to performance isolation for multi-tenant sharing. On the other hand, to overcome the heavy re-compilation overheads, a tiling-based instruction frame package design and a two-stage static-dynamic compilation, are proposed. Only the lightweight runtime information is re-compiled with ∼1 ms overhead, thus guaranteeing the private cloud’s performance. Finally, the extensive experimental results show that the proposed virtualized solutions achieve up to 3.12× and 6.18× higher throughput in the private cloud compared with the static CNN and RNN baseline designs, respectively.
A Participação da Engenharia nas Atividades de P&D da Indústria de Transformação Brasileira: uma análise a partir da PINTEC

DOI: http://dx.doi. org/10.13071/regec.2317-5087.2013. 2.2. 4647.102-122 Analyzing the structure to hire engineers for technological activities in Brazil is the purpose of this article, which investigates whether the participation of these professionals in P & D in the processing industry has grown. For this, we used the data provided by the Technological Innovation Research (PINTEC). Information allows us to observe the evolution of the effort in P & D and the participation of engineers among the professionals dedicated to the technological activities. Despite the expectation of a structure which strengthens technological activities, with a greater demand for engineers, data show that industry is not constructing a more intensive structure having engineers or P & D activities as a basis.
TEMPORARY INITIAL FEEDING OF LOW-QUALITY CHEAP DIET AS A MANAGEMENT STRATEGY FOR RAISING STARTER BROILERS.

A 5-week experiment was conducted to investigate the effects of temporary initial feeding of low-quality cheap diet on broiler starter performance, to determine if sufficient compensatory growth can be achieved at that phase of broiler production. Seventy-two (72) dayold broiler chicks of Anak strain were randomly distributed into two groups, A and B, using completely randomized design. Each group was replicated 3 times with 12 broiler chicks per replicate and each replicate housed in a pen measuring 1.5 m x 2 m. Broilers in group A were given a standard broiler starter diet continuously for 5 weeks while broilers in group B received a low-quality cheap diet based mainly on palm kernel cake and wheat offal for the first two weeks and then placed on the standard diet for the remaining three weeks of the trial. The birds were weighed at the beginning of the trial and weekly thereafter. The birds in group B recorded relatively less feed intake (28.03 g/day vs 27.10 g/day) and reduced daily body weight gain (18.48 g/day vs 16.87 g/day) in the first 2 weeks of the trial. However, their daily feed intake increased astronomically as from the third week following the withdrawal of the low-quality diet and its replacement with the standard diet. Similarly, their daily body weight gain increased such that at the end of the 5 weeks, they were able to significantly (P<0.05) overtake the birds in group A in final body weights (975.82 g vs 1084.10 g). Economic analysis of the study showed that the feed cost of producing the broilers in group B (N/kg broiler) was N206.04 as against N220.94 for group A, giving a saving of N14.32 per bird.
Dynamic performance limitations for MRAS based sensorless induction motor drives. Part 1: Stability analysis for the closed loop drive

The paper deals with a speed sensorless direct rotor flux orientated vector controlled induction motor drive in which the speed and rotor flux angle are derived from a closed loop MRAS estimator. A small signal stability analysis is carried out on the combined estimator-controller, and allows for the stability effects of incorrect estimator parameters to be studied. The small signal stability analysis is sufficient to show that incorrect parameters give rise to oscillatory drive behaviour that worsens, even to the point of instability, as the closed loop speed bandwidth of the drive is increased. Experimental results are given to validate the analysis. It is concluded that speed and load torque rejection bandwidths comparable to sensored vector controllers cannot be obtained without online parameter tuning.
Simulator Evaluation of Drivers’ Performance on Rural Highways in relation to Drivers’ Visual Attention Demands

Aim of the study is to investigate, by means of a driving simulator experiment, drivers’ performance in terms of lateral position, speed, deceleration, steering angle, and breaking times on a divided two-lane rural highway in relation to drivers’ visual attention (VD). In the experiment, the virtual scene of twenty different geometric alignment sections without traffic and the VD testing were designed. Twenty-three experienced drivers with the calibration of attention capacity participated in a 30 km drive in an interactive fixed-base simulator. Each participant was required to drive with the controlled speed of 60 km/h along the central lane as repeating random number and was evaluated on VD and driving performances. Three different data analysis techniques were used: (a) statistical tests and hypothesis test of curvature change rate (CCR) of the geometric alignments, visual attention demands, and driving performance data, (b) correlation analysis of VD, CCRs, and driving behaviors, and (c) regression analysis of the VD and CCRs. Results have showed that the driving performance can be effectively influenced by the highway alignment and a prediction model built in this study can evaluate the drivers’ visual attention demands before the highway constructed. The interactions among VD, driving behavior, and CCRs were also found.
Forecasting Stock Price Movements Based on Opinion Mining and Sentiment Analysis: An Application of Support Vector Machine and Twitter Data

Today, social media networks are fast and dynamic communication intermediaries that are vital business tools, as well. This study aims to examine the views of those who are involved in Facebook stocks to understand the pattern and opinion about the intended future stock price. Yet another goal of this paper is to create a more accurate forecasting pattern compared to the previous ones. Two datasets are used in this paper; the first contains 1.6 million tweets that have already been emotionally tagged, and the second has all the tweets about Facebook stock in eighty days. We conclude that positive news about a company excites people to have definite opinions about it, which results in encouraging them to buy or keep that specific stock. Also, some news can hurt users' views as most of the time, things get more complicated, and uncertainties make it harder to forecast the direction of stock movement. By using text mining and python programming language, we could create a system to be operable in those situations.
In Vitro and In Silico Kinetic Studies of Patented 1,7-diEthyl and 1,7-diMethyl Aminoalkanol Derivatives as New Inhibitors of Acetylcholinesterase

Two aminoalkanol derivatives of 1,7-diEthyl-8,9-diphenyl-4azatricyclo (5.2.1.02.6) dec-8-ene-3,5,10-trione and two derivatives of 1,7-diMethyl-8,9-diphenyl-4-azatricyclo (5.2.1.02.6) dec-8-ene-3,5,10-trione were evaluated in vitro for their inhibition efficacy of acetylcholinesterase. The Km, Vmax, slope angles of Lineweaver–Burk plots, Ki and IC50 values showed that all four aminoalkanol derivatives are competitive inhibitors of acetylcholinesterase whose inhibitory potency depends, to a varying extent, on the nature of the four different substituents present in the main compound structure. Studies have shown that the most potent acetylcholinesterase inhibitors are derivatives containing isopropylamine and/or methyl substituents in their structure. In contrast, dimethylamine and/or ethyl substituents seem to have a weaker, albeit visible, effect on the inhibitory potency of acetylcholinesterase. Additionally, docking studies suggest that studied compounds binds with the peripheral anionic site and not enter into the catalytic pocket due to the presence of the sterically extended substituent.
An air-to-ground combat survivability model

A survivability model can be a useful component of a tactical support system able to aid fighter pilots to assess the risk of getting hit by enemy fire from ground-based threats. This work identifies three desirable properties of such a model: it should allow for evaluating actions; it should enable domain experts to incorporate their knowledge; and it should represent uncertainties both regarding the locations of the threats as well as their future actions. A survivability model is suggested, which calculates the probability that the aircraft can fly a route unharmed and allows for routes of different lengths to be compared. A domain expert can describe the threats by specifying the risk of getting hit at a position of the route without having to consider the earlier actions of the aircraft and the threats. Three different threat models are suggested and compared. The influence of uncertainties regarding the positions of the threats is studied by calculating the probability density function for the survivability. Different representations that take into account both the uncertainty regarding the present and future situation are discussed. The results indicate that the suggested survivability model could be a useful component of a future tactical support system, even though some further development is needed.