Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer Vision in Self-Steering Tractors

Automatic navigation of agricultural machinery is an important aspect of Smart Farming. Intelligent agricultural machinery applications increasingly rely on machine vision algorithms to guarantee enhanced in-field navigation accuracy by precisely locating the crop lines and mapping the navigation routes of vehicles in real-time. This work presents an overview of vision-based tractor systems. More specifically, this work deals with (1) the system architecture, (2) the safety of usage, (3) the most commonly faced navigation errors, (4) the navigation control system of tractors and presents (5) state-of-the-art image processing algorithms for in-field navigation route mapping. In recent research, stereovision systems emerge as superior to monocular systems for real-time in-field navigation, demonstrating higher stability and control accuracy, especially in extensive crops such as cotton, sunflower, maize, etc. A detailed overview is provided for each topic with illustrative examples that focus on specific agricultural applications. Several computer vision algorithms based on different optical sensors have been developed for autonomous navigation in structured or semi-structured environments, such as orchards, yet are affected by illumination variations. The usage of multispectral imaging can overcome the encountered limitations of noise in images and successfully extract navigation paths in orchards by using a combination of the trees’ foliage with the background of the sky. Concisely, this work reviews the current status of self-steering agricultural vehicles and presents all basic guidelines for adapting computer vision in autonomous in-field navigation.
The Effect of Performance Impact on the Integrity Management of Electronic Medical Records

Lack of systematic records management is directly linked to the persistence of corruption and fraud. Experts in financial management control have recognised and acknowledged the fact that well-managed record systems are vital to the success of most anti-corruption strategies. Records provide verifiable evidence of fraud that can lead investigators to the root of corruption. Well-managed records can thus act as a cost effective deterrent. The records must be maintained to ensure that they are complete and they must be protected against unauthorised or accidental alteration. Integrity is the quality of confirming that the records have not been altered and that all authorised actions undertaken with a record, such as electronic opening, reading and filing have been managed and documented in accordance with established business requirements. In reality, records management functions are often neglected in the government administration system. Management of electronic medical records (EMR) is becoming more complicated with the usage of wireless network technology to create, manage and share patients' information. The wireless network offers new potential for corruption and fraud from authorised personnel with the ability to create, alter and delete records electronically. In addition, there is no single universal framework for assessing the integrity management of electronic medical records (EMR) in a trusted digital repository to curb abuse and fraudulent activities. This study investigates the integrity management of EMR in selected Malaysian government hospitals. Questionnaire-style surveys were administered to medical records personnel to gather data. The findings showed that integrity was the primary factor in the efficient management of EMR and was strongly associated with EMR management and performance impact. The study was significant to hospital administrators, records personnel and medical practitioners to realize a necessity for integrity management of electronic medical records.
Application of multi-objective optimization in the design and operation of industrial catalytic reactors and processes

Optimization in engineering is the search for the “best” solution to a specific problem. Criteria to determine whether the solution is the “best” or not vary widely and are defined by an engineer (researcher) based on their experience, the problem’s objectives, common sense, etc. For example, while optimizing the performance of a synthesis reactor, it’s often desired to maximize the possible yield of the final product; or in the case of equipment design, it is common to reduce the total cost while keeping a unit’s performance at the desired level. Engineering optimization can be classified by the number of objectives: either single-objective optimization (SOO) or multi-objective optimization (MOO). The SOO approach has a longer history. Essentially, it is based on the formulation of a unified function that represents the overall effect. Most of the objective functions in SOO are related to the economic efficiency of the process or unit. A classical example is the optimization of insulation thickness. Insulation saves money through reduced heat loss, but insulation can be very costly at the same time. One has to compare the total cost of new insulation with the savings from energy losses to find an optimal thickness; the ratio between these two factors can be an objective function to be minimized (Figure 1) [1]. It can be said that SOO methods are mainly aimed at a search for an extreme point (minimum or maximum) in a search space.
Estimation of rice yield through weather factors in a dry sub-humid region

Rice is staple cereal for a vast population in the country. Naturally it is, therefore, grown in varied climates from per-humid to semi-arid areas. An attempt has been made in this paper to identify weather factors and their duration, which exert influence on the crop growth and the yield for rice grown in the southwestern parts of Madhya Pradesh, a typical dry sub-humid area. Correlation technique has been adopted for this purpose. Apart from routine meteorological parameters, extent to which monthly water need of the plant (i.e., evapotranspiration) is met by monthly rainfall and called efficiency ratio has also been introduced in the analysis. This analysis thus brings out relationship between crop during its various growth phases with important weather parameters. The parameters chosen are then utilised to obtain a linear multiple regression. The coefficient of determination obtained was 0.90 explaining 81 per cent of the yield variation.
Research on bottom dead center(B.D.C) of high speed precision press

The accuracy of stampings and die life are affected by B.D. C precision which is the key technical index of high-speed precision press.The main factors of B.D. C precision are rotational speed,temperature,press rigidity,static balance pressure and so on.The impact of the elements of B.D. C precision was quantitatively analyzed by building test system of B.D. C or using B.D. C instrumentation.Methods of B.D. C precision's controlling were briefly introduced,these methods were B.D. C dynamically adjustment,controlling displacements due to the change of velocity and temperature and simplifing the transmission line.
Research on Influence on Fatigue Life Attenuation Based Corrosion Damage Characterization Factors

Corrosion damage characterization factors of LY12CZ aluminum alloy were filtrated using MIT(Mean Impact Value)method.Five corrosion damage characterization factors were obtained,which has significant influence on fatigue life attenuation.The functions of cumulative corrosion fatigue life and cumulative fatigue life attenuation rate were defined.The cumulative corrosion fatigue life model was established and its accuracy was verified.Corrosion damage characterization factors and the cumulative fatigue life attenuation function were taken as specimen.The fatigue lives of LY12CZ aluminum alloy of different service time were predicted with BP neural network and LMS algorithm.The results were than compared with experimentation results.It was proved that the error generated by BP neural network and LMS algorithm can be accepted in engineering.
Contrast-Associated Acute Kidney Injury: Advances and Challenges

Abstract A decrease in renal function that follows intravascular administration of contrast medium (CM) within a few days is reported as contrast-induced acute kidney injury (CI-AKI). In clinical practice, the imaging procedure is frequently deferred when clinicians consider that the renal risks caused by CM outweigh the benefits of enhanced imaging. However, with an in-depth understanding of AKI and contrast medium, scholars have realized that the decrease in renal function after CM is caused by contrast medium factors and noncontrast medium factors (such as anemia and hemodynamic instability). Therefore, acute kidney injury caused by CM has been overestimated in the past. The term “contrast-associated acute kidney injury (CA-AKI)” has been increasingly used to indicate AKI after intravascular administration of contrast medium compared with CI-AKI. CA-AKI can increase the risk of death and chronic kidney disease. However, its pathophysiological mechanism has not been fully elucidated, and the effectiveness of various preventive and therapeutic measures have been questioned. These present challenges for us. In this article, we will review the diagnostic criteria, epidemiology, risk factors, pathophysiological mechanisms and treatment of CA-AKI to provide optimized imaging procedures in clinical practice.
Capacitor voltage balancing strategy based on sub-module capacitor voltage estimation for modular multilevel converters

The modular multilevel converter (MMC) is expected to be used extensively in high-voltage direct current (HVDC) transmission networks because of its superior characteristics over the line-commutated converter (LCC). A key issue of concern is balancing sub-module capacitor voltages in the MMCs, which is critical for the correct operation of these converters. The majority of voltage balancing techniques proposed thus far require that the measurement of the capacitor voltages use a reliable measuring system. This can increase the capital cost of the converters. This paper presents a voltage balancing strategy based on capacitor voltage estimation using the adaptive linear neuron (ADALINE) algorithm. The proposed estimation unit requires only three voltage sensors per phase for the arm reactors and the output phase voltages. Measurements of sub-module capacitor voltages and associated communication links with the central controller are not needed. The proposed strategy can be applied to MMC systems that contain a large number of sub-modules. The method uses PSCAD/EMTDC, with particular focus on dynamic performance under a variety of operating conditions.
Time-of-Day Circadian Modulation of Grape-Seed Procyanidin Extract (GSPE) in Hepatic Mitochondrial Dynamics in Cafeteria-Diet-Induced Obese Rats

Major susceptibility to alterations in liver function (e.g., hepatic steatosis) in a prone environment due to circadian misalignments represents a common consequence of recent sociobiological behavior (i.e., food excess and sleep deprivation). Natural compounds and, more concisely, polyphenols have been shown as an interesting tool for fighting against metabolic syndrome and related consequences. Furthermore, mitochondria have been identified as an important target for mediation of the health effects of these compounds. Additionally, mitochondrial function and dynamics are strongly regulated in a circadian way. Thus, we wondered whether some of the beneficial effects of grape-seed procyanidin extract (GSPE) on metabolic syndrome could be mediated by a circadian modulation of mitochondrial homeostasis. For this purpose, rats were subjected to “standard”, “cafeteria” and “cafeteria diet + GSPE” treatments (n = 4/group) for 9 weeks (the last 4 weeks, GSPE/vehicle) of treatment, administering the extract/vehicle at diurnal or nocturnal times (ZT0 or ZT12). For circadian assessment, one hour after turning the light on (ZT1), animals were sacrificed every 6 h (ZT1, ZT7, ZT13 and ZT19). Interestingly, GSPE was able to restore the rhythm on clock hepatic genes (Bmal1, Per2, Cry1, Rorα), as this correction was more evident in nocturnal treatment. Additionally, during nocturnal treatment, an increase in hepatic fusion genes and a decrease in fission genes were observed. Regarding mitochondrial complex activity, there was a strong effect of cafeteria diet at nearly all ZTs, and GSPE was able to restore activity at discrete ZTs, mainly in the diurnal treatment (ZT0). Furthermore, a differential behavior was observed in tricarboxylic acid (TCA) metabolites between GSPE diurnal and nocturnal administration times. Therefore, GSPE may serve as a nutritional preventive strategy in the recovery of hepatic-related metabolic disease by modulating mitochondrial dynamics, which is concomitant to the restoration of the hepatic circadian machinery.
Modeling of Intralogistic Processes for the Implementation of Warehouse Management Systems

Due to the growing complexity of intralogistics systems, the use of warehouse management systems (WMS) is becoming increasingly attractive for companies. As an often business-critical management system of internal material flows, however, their implementation or change is complex and carries risks. Especially the insufficient knowledge of companies about their own processes leads to a high capacity and cost burden due to the time-consuming involvement of their own experts and, often, also contracted WMS consultants. In this context, models and modeling methods are gaining additional importance. But, particularly in intralogistics, with its special demands and characteristics, there is a lack of methodological support for mapping and transferring process knowledge appropriate for the WMS implementation. The consequences, besides a low level of acceptance among the affected employees, are project aborts and production downtimes. This paper discusses experiences from industrial practice during the implementation of WMS and takes the position that a supporting method is urgently required in this context. Therefore, we propose the development of a modeling language for mapping intralogistic processes in line with the requirements for the implementation of WMS as well as procedural method components that support the generation and transmission of the process
The Landscape of Nanovectors for Modulation in Cancer Immunotherapy

Immunotherapy represents a promising strategy for the treatment of cancer, which functions via the reprogramming and activation of antitumor immunity. However, adverse events resulting from immunotherapy that are related to the low specificity of tumor cell-targeting represent a limitation of immunotherapy’s efficacy. The potential of nanotechnologies is represented by the possibilities of immunotherapeutical agents being carried by nanoparticles with various material types, shapes, sizes, coated ligands, associated loading methods, hydrophilicities, elasticities, and biocompatibilities. In this review, the principal types of nanovectors (nanopharmaceutics and bioinspired nanoparticles) are summarized along with the shortcomings in nanoparticle delivery and the main factors that modulate efficacy (the EPR effect, protein coronas, and microbiota). The mechanisms by which nanovectors can target cancer cells, the tumor immune microenvironment (TIME), and the peripheral immune system are also presented. A possible mathematical model for the cellular communication mechanisms related to exosomes as nanocarriers is proposed.
Swarm Unmanned Aerial Vehicles (SUAVs): A Comprehensive Analysis of Localization, Recent Aspects, and Future Trends

Within the last decade, Swarm Unmanned Aerial Vehicles (SUAVs) are booming and growing at a surprisingly rapid pace. From military combat, environmental surveillance, and air transport to the blossoming public entertainment sector, there is a wide range of UAV applications. For these above use cases, the accurate location of the target of interest can be requested/queried, which is very important for their mission accomplishment. In the case of GPS-armed SUAVs, this is an easy task. However, the GPS signal can be obscured, affected by environmental conditions, or suppressive jamming. Therefore, location information needs to be improved/assisted by some other localization techniques, which constitutes the main scope of this article. Besides, with the advancements in localization, guidance, and communication technologies; future SUAVs will be operating autonomously by distributing tasks and coordinating the operation of many UAVs. Thus, UAV to UAV communication is presented as it constitutes the SUAV’s autonomous coordination ability. In addition, future research directions and open challenges that need to be addressed, including autonomous SUAVs, are also discussed.
Knowledge, Attitudes, and Perception towards COVID-19 Vaccination among the Adult Population: A Cross-Sectional Study in Turkey

Background: The coronavirus disease 2019 (COVID-19) pandemic continues to wreak havoc on lives and ravage the world. Several vaccines have been approved for use against COVID-19; however, there may be hesitancy and negative perceptions towards vaccination, which may reduce the willingness to be vaccinated. Further, studies assessing the current perception toward COVID-19 vaccination are scarce. This study aimed to assess community knowledge, attitudes, and perceptions regarding COVID-19 vaccines among the general population of Turkey. Methods: A cross-sectional survey was carried out among 1009 adult participants from the 13–20 April 2021. Demographic data were collected, and attitudes and perceptions toward COVID-19 vaccines were evaluated. A multivariable regression analysis was performed to identify the factors predicting perception towards COVID-19 vaccinations. Results: Just over half of participants were male (52.6%) and the majority of respondents were aged between 30 and 39 years (33.8%). Our study revealed that 62.7% of participants had positive perceptions of COVID-19 vaccines. Logistic regression analysis results showed that older people (≥30 vs. <30) were less likely to have a positive perception towards COVID-19 vaccines (OR = 0.70, 95% CI = 0.51–0.94). We also found participants who had a previous history of influenza vaccines (OR = 2.01, 95% CI = 1.43–2.84), bachelor’s degrees or above (OR = 1.47, 95% CI = 1.12–1.91), and a personal history of COVID-19 (OR = 1.58, 95% CI = 1.10–2.26) were more likely to have a positive perception regarding COVID-19 vaccines. Conclusion: The proportion of the general population in Turkey who believe in COVID-19 vaccine effectiveness is not inferior to that of other countries. However, the low positive perception even among the population applying for vaccination indicates that understanding the perception of the general population and its influencing factors may contribute to developing a strategy for improving vaccination rates by addressing these factors.
Microtremor Vibrations in the Soil Experimental Investigation and FEM Simulation

Vibration problems of the building structures caused by technical seismicity are becoming increasingly topical. The aim of this paper is to show FEM simulation of the spreading wave impact, which causes vibration system consisting of subsoil-structure interaction in microtremor. The results of the experiment together with this theoretical analysis and FEM simulation appear to be effective application for engineering experience. They are also used in assessing and predicting the vibration effects induced by technical seismicity due to traffic. [1].
A Robotic Grasping State Perception Framework with Multi-Phase Tactile Information and Ensemble Learning

Recently, tactile sensing has attracted increasing attention for robotic manipulation. Predicting the grasping stability before lifting objects and detecting the ongoing/onset of slip after lifting objects are two critical and widely studied tasks in robotic tactile manipulation. Previous methods focus on proposing novel neural networks (NN) architectures towards one of the above two tasks and did not consider that the two tasks are employed in two interconnected action-phases, i.e. grasping and lifting. Therefore, we firstly explore the possibility of constructing a multi-phase, multi-output framework to combine the stability prediction before lifting and the slip detection after lifting. Moreover, to %use the limited tactile data efficiently and improve the prediction/detection accuracy, we also proposed to explicitly ensemble different NN architectures using various methods, including attention mechanisms. Our experiments are done with 6 state-of-art NN architectures on two datasets including more than 3000 robotic grasps over 80 objects in total. Our experimental results show that the proposed multi-phase, multi-output model exhibits more reliable and flexible performance than a single phase model. We also show that using the ensemble of different NN architectures is a viable and practical choice to boost the overall performance.
Combination Technique Using Patchwork and Partial Softening to Determine the Collision Toughness and Intrusion Prevention in Side Crash Simulation

Various techniques have been applied to center pillar to enhance collision characteristics during side crash. Among these techniques, the patchwork (PW) was welded to center pillar to strengthen the stiffness and partial softening (PS) was applied to provide ductility. Side crash test was conducted by Insurance Institute for Highway Safety (IIHS) to evaluate collision resistance. But it is hard to evaluate collision toughness and energy distribution flow for each automobile component. In this study, the side crash simulation was performed along with IIHS instruction. The effect of Hot Press Forming (HPF) center pillar with the combination techniques of PW and PS on collision toughness and energy distribution flow was investigated. As a results, the role of PW and PS techniques were verified during side crash. The strain energy and intrusion displacement by PW were improved 10, 7.5% respectively and the plastic deformation energy and intrusion displacement by PS were improved 10%. When PW and PS were applied to the HPF center pillar simultaneously, the synergy effect of PW and PS occurred.
A Home-Based Heart Failure Nursing Intervention Supporting Self-Management and Lives

In the era of a super-aged society, along with the rapid development of medical techniques to treat cardiovascular disease, there are an increasing number of aged patients with heart failure (HF). To cope with this near pandemic, coordinated-HF management combining hospital-based optimal therapy and home-based care is required. Accordingly, the concept of “living with HF” is advocated and is widely accepted as a key to improve patients’ quality of life as well as prognosis. To achieve it, home visiting nursing services are essential. But these services have some difficulties. This chapter shows the importance of promoting self-management for patients with heart failure and intervention strategies in the home care setting.