Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Disability-Adjusted Life Years among Patients Presenting with End-Stage Liver Disease

Introduction: Disability-adjusted life years (DALYs) is a multidimensional metric utilized to quantify specific disease burdens. It has the potential to highlight both fatal and non-fatal outcomes of disease and thus help in policymaking and health resource allocation. Chronic liver disease, secondary to preventable causes, is one of the main contributors to morbidity and mortality. It demands the attention of researchers and policymakers alike. The primary aim of this study was to quantify the disease burden due to end-stage liver disease in terms of years of life lost (YLL), years lost to disability (YLD), and DALYs. Arch Intern Med Res 2021; 4 (1): 031-042 DOI: 10.26502/aimr.0052 Archives of Internal Medicine Research 32 Materials and methods: This was a descriptive caseseries study conducted over a period of six months between September 2019 and February 2020 at a tertiary care hospital in Lahore, Pakistan. All patients presenting with end-stage liver disease were interviewed. The YLL were predicted by using the Child-Pugh score’s estimation of years of life left. Chronic Liver Disease Questionnaire (CLDQ) was used to assess the disabilities of the patients along with disability weights from the Global Burden of Disease (GBD) study to calculate the YLD. All statistical analysis was conducted using Statistical Package for Social Sciences (SPSS) version 23.0. Results: 18 patients who presented with end-stage liver disease had 32.8 (95% CI: 25.2-40.5) mean DALYs. The mean age of presentation was 51.1 (95%CI: 42.759.4) years. A significant negative correlation was found between age and DALYs (r=-0.94, p<0.001). The mean YLL was 31.5 (95%CI: 23.5-39.5) and the mean YLD was 1.34 (95%CI: 0.58-2.11). Most patients presented with decompensated chronic liver disease (DCLD) during the fifth and sixth decade of life. No significant correlation was found between gender and DALYs (r = 0.208, p=0.407). The most common adjusted disabilities were muscle cramps, fatigue, difficulty sleeping at night, hematemesis, jaundice, fluid in the abdomen, and abdominal pain. Conclusions: In accordance with the findings of this study, 18 patients with end-stage liver disease lost an estimated 591.22 DALYs which represents approximately 39.1% of the normal life span, if these patients were a member of a standardized model population with a life expectancy at birth equal to that of the world’s longest-surviving population i.e. Japan. YLL contributes 96% of the total DALYs which indicates that the ability of the end-stage liver disease to cause mortality is much more significant than its ability to cause morbidity. Our research also indicates that out of 100 patients with end-stage liver disease, 39 lifetimes are lost.
A Novel Lightweight Authentication Protocol for Emergency Vehicle Avoidance in VANETs

The delay of vehicle emergency has led to many serious consequences. A series of studies has been carried out in the field of information security in vehicular ad hoc networks (VANETs). However, open issues such as the authentication of emergency vehicle (EV) avoidance are remaining unsolved. In this article, we propose a novel lightweight authentication protocol to avoid EVs in VANETs. In our protocol, after completing the first mutual authentication with the nearest roadside unit (RSU), EV can complete the mutual identity authentication with the subsequent RSUs without repeating cumbersome calculations. Additionally, EV is required to verify the legitimacy of the driver’s identity when starting to avoid some illegal driving behavior. The RSUs will broadcast avoidance information to ordinary vehicles in their jurisdiction to remind them to clear a temporary emergency lane for EVs in advance. With temporary emergency lanes, emergent mission delays due to traffic congestion could be reduced. The security analysis and efficient analysis prove that our protocol is practical and efficient against attacks, such as impersonation attacks, device theft attacks, reputation attacks, etc.
Pursuing competitiveness: A comparative study of commercial beekeepers

ABSTRACT This empirical study examines how commercial beekeepers operating in the New Zealand and the United Kingdom are working to improve their firms’ competitiveness, namely, through innovating and adding value to their honey production, and what they perceive to be the strengths, weaknesses, opportunities, and threats (SWOT) within the context of their business. An online questionnaire was employed to gather data from beekeepers operating in the United Kingdom and New Zealand. While both groups perceived innovation in similar ways, they differed regarding equipment and infrastructure development, with New Zealand beekeepers more strategically involved in this area. Similarly, both commonalities and significant differences were revealed concerning adding value and regarding aspects related to the SWOT framework. These findings have important implications, for instance, in highlighting the importance of identifying strategies that, regardless of beekeepers’ geographical context, can help improve the competitiveness of their operations and their industry.
A Crystal-Less BLE Transmitter With Clock Recovery From GFSK-Modulated BLE Packets

In this article, we present a crystal-less Bluetooth low-energy (BLE) transmitter using RF reference recovery directly from GFSK-modulated BLE packets. In order to achieve fast frequency calibration from modulated signals and reduce interference from other BLE users, the transceiver consists of a back-channel wake-up receiver, a clock-recovery receiver, a transmitter, and a dual-all-digital phase-locked loop (ADPLL) frequency synthesizer for system wake-up, clock-recovery, packet transmission, and frequency calibration. An embedded averaging processing unit in the loop filter of the ADPLL is proposed to retrieve accurate frequency information from GFSK-modulated signals. A prototype chip is fabricated in 40-nm CMOS for verification. The crystal-less transmitter with clock recovery meets all BLE requirements for SIR, making this a robust solution for removing the crystal even in densely populated networks.
Accuracy of Three Interterminal Capacitance Models for SiC Power MOSFETs Under Fast Switching

This article presents a comprehensive analysis of nonlinear voltage-dependent capacitances of vertical silicon carbide power MOSFETs with lateral channel, focusing specifically on fast switching transients. The capacitance-voltage (<italic>C-V</italic>) device characteristics, (<inline-formula><tex-math notation="LaTeX">$C_{\rm {gs}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$C_{\rm {gd}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$C_{\rm {ds}}$</tex-math></inline-formula>), being dependent on both <inline-formula><tex-math notation="LaTeX">$V_{\rm {gs}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$V_{\rm {ds}}$</tex-math></inline-formula>, are extracted by means of two-dimensional technology computer aided design simulations for a commercially available device in both <sc>off</sc>- and <sc>on</sc>-state modes. Different compact models for the power MOSFET are investigated, each employing a three interterminal capacitance model as typically used in power electronics. The performed analysis provides a detailed explanation for the importance of taking into account the dependence of <inline-formula><tex-math notation="LaTeX">$C_{\rm {gd}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$C_{\rm {gs}}$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$C_{\rm {ds}}$</tex-math></inline-formula> on both of the voltages <inline-formula><tex-math notation="LaTeX">$V_{\rm {gs}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$V_{\rm {ds}}$</tex-math></inline-formula>. This is especially important for fast switching transients (in the range of 10 ns) in order to accurately predict switching losses, driver losses, current, and voltage slopes, as well as current and voltage delays. As direct measurements for <inline-formula><tex-math notation="LaTeX">$C_{\rm {gd}}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$C_{\rm {gs}}$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$C_{\rm {ds}}$</tex-math></inline-formula> in dependence of both <inline-formula><tex-math notation="LaTeX">$V_{\rm {gs}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$V_{\rm {ds}}$</tex-math></inline-formula> are highly demanding, the results presented in this article increase the understanding of both the underlying effects as well as of the tradeoffs between accuracy and computational complexity made by simplifying device models. In turn, this information is highly beneficial for enabling accurate and computationally efficient automated design procedures for power electronics.
Nodding detection system based on head motion and voice rhythm

Human beings communicate using more than verbal communication. To communicate smoothly, humans tend to use nonverbal information such as nodding during embodied interactions. Nodding is a form of affirmative gesture that is commonly used by humans worldwide while communicating with each other. The accurate detection of nodding is expected to support communication, analyze a conversation scene, and facilitate embodied interaction. In contrast, nodding is known to be related not only to the motion of the head but also to the rhythm of the voice. By using both head motion and voice rhythms, nodding can be estimated more accurately than methods that use only head motion or voice rhythms. Therefore, in this study, we develop a nodding detection system based on head motion and voice rhythm. In this system, the head motion of the listener is measured using face tracking. Then, the nodding motion is estimated using a neural network for head motion. Furthermore, the neural networks estimate the timings at which the listener is nodding by using the voice of the speaker. Subsequently, the nodding is estimated using logical OR and logical AND based on outputs of the head movement and speech rhythm neural networks. In addition, a neural network that integrates head motion and voice rhythm is developed. Furthermore, the effectiveness of the developed methods is demonstrated through evaluation experiments.
Research on the Construction of Comprehensive Practice Platform for Big Data Analysis of E-commerce under the Environment of Internet of Things

Due to the rapid development and wide application of Internet information technology, there is an urgent need for e-commerce talents in various industries. Internship is an important part of on-the-job training in universities, which helps to provide outstanding talents for the society, and internship management system can ensure the quality of internship. Under the Internet of Things environment, a new comprehensive practice platform for big data analysis is constructed, and high-quality e-commerce talents in society are trained on the basis of overall research, so as to give full play to their roles and functions. Practice has proved that the comprehensive practice platform of e-commerce big data analysis can improve the quality of education and students' ability.
A Network-Based Explanation of Perceived Inequality

Across income groups and countries, the public perception of economic inequality and many other macroeconomic variables such as inflation or unemployment rates is spectacularly wrong. These misperceptions have far-reaching consequences, as it is perceived inequality, not actual inequality informing redistributive preferences. The prevalence of this phenomenon is independent of social class and welfare regime, which suggests the existence of a common mechanism behind public perceptions. We propose a network-based explanation of perceived inequality building on recent advances in random geometric graph theory. The literature has identified several stylised facts on how individual perceptions respond to actual inequality and how these biases vary systematically along the income distribution. Our generating mechanism can replicate all of them simultaneously. It also produces social networks that exhibit salient features of real-world networks; namely, they cannot be statistically distinguished from small-world networks, testifying to the robustness of our approach. Our results, therefore, suggest that homophilic segregation is a promising candidate to explain inequality perceptions with strong implications for theories of consumption behaviour.
Blockchain-Based Key Management Scheme in Fog-Enabled IoT Systems

There are a number of benefits associated with the deployment of fog computing, for example, by analyzing and computing data from Internet-of-Things (IoT) devices at the fog nodes reduce the bandwidth, computational, and storage overheads at the cloud servers and improve user quality of experience (e.g., due to reduced latency). However, there are also additional security implications and requirements. For example, secure keys are needed to establish secure channels among these distributed fog nodes. Therefore, to facilitate fog nodes in managing secure keys and establishing secure group channels, we present a novel fog system and propose a blockchain-based group key management scheme that builds on an earlier work. We also design a new resource authentication mechanism based on Proof of Work (PoW), and when deployed in our fog system facilitates resource authentication (i.e., a fog node in a fog system can evaluate the capability of a fog device’s computing power before the device is permitted to enter the system). Findings from our simulations and secure analysis demonstrate the utility of our system.
E-government in the Era of Globalization and the Health Crisis caused by the Covid-19 Pandemic, between Standards and Innovation

Research background:E-government has started from the challenges of new technologies by providing e-services to its citizens and has expanded today in more and more fields, including communication with citizens, budget management, macroeconomic forecasts, etc. If we accept the definition according to which eGovernment (or e-government) is an applicability of information technology for the provision of administrative services, information exchange, communication transactions, integration of various electronic systems and autonomous services between government and citizen (G2C), government and business environment (G2B), government and government (G2G) as well as for the processes and interactions of administrative staff in the entire infrastructure of the administration, and through e-government, government services are available to citizens in a convenient, efficient and transparent way, then we will accept and the conclusions of the same research that considers that in e-government there are no identifiable barriers.Purpose of the article:Through this paper we aim to highlight the current economic realities and how some governments have understood to use technology during the pandemic.Methods:The research methodology is based on documentary analysis. The bibliographic study, the secondary analysis of the data, the observation and the analysis complete the documentary analysis and allowed us to obtain some conclusive results.Findings & Value added:The pandemic health crisis has further pushed the limits of technology, which has been transformed into a true universal panacea for solving relatively vital economic activities for a national economy in a global context. A first finding was that the pandemic accelerated the need for digital governance. However, the modalities of action remain open.
A Wide Dynamic Range Multi-Sensor ROIC for Portable Environmental Monitoring Systems With Two-Step Self-Optimization Schemes

This article presents a wide-dynamic-range multi-sensor readout interface for portable environmental monitoring systems with two-step self-optimization schemes. It proposes two-step self-optimization methods of adaptive range detection and coarse self-cancelation (CSC) for current-type sensor interfaces, and range-based path control and current DAC-based correlated double sampling (CDS) for resistive sensing interfaces. Their digital conversions are provided by two kinds of high-resolution ADCs, namely, an incremental <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> current detector and a two-step SAR- <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> ADC. The proposed ROIC prototype is fabricated in a 180-nm CMOS process, achieving a dynamic range (DR) of 136.5 dB and 160.9 dB, and a maximum SNR of 109.8 dB and 108.6 dB for current and resistance detection, respectively. For system-level feasibility, an environmental monitoring system prototype based on the ROIC is also manufactured and functionally verified by integrating two kinds of in-house micro-electro-mechanical systems (MEMS) sensor devices, the MCU, and the Bluetooth module, supporting wireless air quality and water pollution monitoring capabilities.
One-Step Methods to Fabricate Durable Superhydrophobic Coatings for Flexible Electronic Sensors

Inspired by lotus leaves in nature, superhydrophobic surfaces have attracted extensive attention in many fields. However, their complex preparation process, poor durability and high cost seriously restrict their large-scale application in industrial production. Based on the good flexibility and durability of carbon nanofibers, several simple modifier-free one-step approaches were adopted to fabricate a durable CNF/PVDF/PDMS conductive superhydrophobic coating. The fabricated coating not only possesses good superhydrophobicity to many kinds of liquids, but also has excellent self-cleaning and anti-fouling properties. In addition, the superhydrophobicity of the obtained multifunctional coating is stable even after harsh bending fatigue deformation, long immersion times and high-temperature treatment. Due to its strong adhesion and excellent conductivity, the CNF/PVDF/PDMS coating displays reliable mechanical stability and superior sensitivity. These distinct features make the obtained conductive superhydrophobic coating a good candidate for multifunctional smart sensors, with great application prospects in gesture detectors, waterproof wearable electronics and health monitors.
Poverty estimation at the county level by combining LuoJia1-01 nighttime light data and points of interest

Abstract To reduce poverty, it is important to obtain accurate information on poverty conditions in a timely manner. Previous studies indicated that nighttime light products are helpful for poverty estimation. However, there exist no studies that have investigated the potential of LuoJia1-01, a new-generation nighttime light satellite with a much finer resolution (∼130 m), for analyzing poverty. In addition, nighttime light data may not reflect daytime-only socio-economic activities. To address these problems, our study first compared the performance of LuoJia1-01 and NPP-VIIRS products in poverty estimation. Next, we incorporated point of interest (POI) information so that daytime-only socio-economic activities can be considered. Our experiments indicated that LuoJia1-01 performs slightly better than NPP-VIIRS in terms of poverty estimation at county level. More importantly, we revealed that the combination of POIs and nighttime light products can moderately increase the average estimation accuracies. These findings are expected to support poverty monitoring over large regions for long periods, which cannot be fulfilled by traditional household surveys and census.
IN VITRO ANTIMALARIAL ACTIVITY OF LEAVE PETROLEUM ETHER EXTRACT OF FICUS SYCOMORUS PLANT

In vitro anti-malarial activity of petroleum ether extracts of Ficus sycomorus leaves was investigated using Candle Jar method. The extractions were carried out through activity guided fractionation. Petroleum ether extract has the highest activity, at the concentration of 1mg and 0.5mg with percentage growth inhibition of (33.12 and 31.9%) respectively. These results suggest that the leaves of Ficus sycomorus plant have significant antimalarial activity and that the antiplasmodial agents might be as a result of the extract fractionated using the petroleum.
Apport de techniques couplées (diffusion de rayonnements, résonance magnétique, vélocimétrie ultrasonore) à la rhéologie

De nombreux systemes multiphasiques (suspensions de particules colloidales et non-colloidales, systemes polymeres, systemes auto-organises de tensio-actifs .) sont constitues d'entites qui ont la capacite de s'organiser et de former des structures a differentes echelles. Ces systemes presentent des comportements rheologiques complexes qui necessitent de coupler differentes techniques a la rheometrie traditionnelle, tant pour rendre compte de l'organisation macroscopique de ces materiaux et mesurer ainsi leur comportement rheologique dans des conditions correctes, que pour comprendre l'organisation structurale induite par l'ecoulement ou au repos a differentes echelles. Cet article fait le point sur les apports de trois techniques (diffusion de rayonnements, resonance magnetique nucleaire, velocimetrie ultrasonore) a la caracterisation du comportement en ecoulement de fluides complexes. Apres un descriptif de chaque technique, des exemples permettent d'illustrer l'apport de chacune. Ainsi, l'interet des techniques de diffusion de rayonnements (rayons X, neutrons, lumiere) est de permettre d'avoir des informations sur un meme materiau sur une large gamme d'echelles, allant du nanometre au micron. La rheometrie par RMN et la rheo-velocimetrie ultrasonore permettent entre autre de mettre en evidence des heterogeneites d'ecoulement et de structure, a travers notamment la mesure des profils de vitesse dont la connaissance permet de determiner le comportement rheologique du materiau dans des conditions d'ecoulement ou la rheometrie traditionnelle ne peut pas etre appliquee.
Object-Level Semantic Map Construction for Dynamic Scenes

Visual simultaneous localization and mapping (SLAM) is challenging in dynamic environments as moving objects can impair camera pose tracking and mapping. This paper introduces a method for robust dense bject-level SLAM in dynamic environments that takes a live stream of RGB-D frame data as input, detects moving objects, and segments the scene into different objects while simultaneously tracking and reconstructing their 3D structures. This approach provides a new method of dynamic object detection, which integrates prior knowledge of the object model database constructed, object-oriented 3D tracking against the camera pose, and the association between the instance segmentation results on the current frame data and an object database to find dynamic objects in the current frame. By leveraging the 3D static model for frame-to-model alignment, as well as dynamic object culling, the camera motion estimation reduced the overall drift. According to the camera pose accuracy and instance segmentation results, an object-level semantic map representation was constructed for the world map. The experimental results obtained using the TUM RGB-D dataset, which compares the proposed method to the related state-of-the-art approaches, demonstrating that our method achieves similar performance in static scenes and improved accuracy and robustness in dynamic scenes.