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CoVID-19 has been linked to long-term consequences on several human body organs, including lung ailments, kidney malfunctions, heart dysrhythmia, alterations in brain nutrient levels, psychological difficulties, abrupt changes in blood pressure, and more. Because of the considerable variety in the impacts on different body parts, researchers find it challenging to create models that can incorporate these effects for treatment recommendations and future disease prevention scenarios. Thus, this article examines some of the most recently proposed models for identifying the impacts of CoVID19 on various human organs. This review examines the underlying theories in terms of clinical nuances, functional advantages, contextual limits, and potential empirical applications. Based on this discussion, researchers will be able to find the best models for detecting particular diseases on specific body parts. It was discovered that hybrid bioinspired models, when paired with deep learning-based classification algorithms, can effectively detect these impacts. This text also parametrically analyses these models in terms of accuracy, precision, and recall, allowing readers to select the best models for their performance-specific use cases. To expand on this discussion, this book evaluates a unique CoVID19 Classification Rank Metric (CCRM) that integrates these factors for thorough model identification. Based on this criteria, researchers will be able to develop appropriate models for clinical scenarios that have high accuracy, low delay, and scalability while costing less. [ABSTRACT FROM AUTHOR]

Copyright of Nankai Business Review is the property of Nankai Business Review Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pounded yam is the most popular traditional yam food product in West Africa, especially Nigeria. Development of a motorized yam pounder is a step towards minimizing intensive human labor, usually involved in the process of preparing pounded yam, while still preserving nutrients and flavor. The machine that has been designed comprises a shaft, blades, 1 HP electric motor, pulley system, cooking and pounding chambers and support frame. The components were carefully selected, fabricated and assembled. Experimental runs were conducted to evaluate the performance of the machine by pounding some weighted quantities of cooked yam. The results showed that it took the machine an average of 34 minutes to cook 0.62 kg of yam and 40 seconds to produce hot and smooth textured pounded yam. The pounded yam produced by this machine is of better quality when compared with the traditional or manual method. It can thus be concluded that the machine performed efficiently and effectively, and minimized labor requirements, when compared with the manual method of preparing pounded yam. [ABSTRACT FROM AUTHOR]

Businesses rely heavily on review analysis of consumer feedback and reviews when making decisions. This research examines fifteen years' worth of hotel evaluations to learn more about the opinions of visitors and how they relate to review scores in various years and regions. After the dataset was cleansed to concentrate on reviews written in English, TextBlob was used to analyze sentiment and classify the reviews as positive, neutral, or negative. The results validate using sentiment analysis in conjunction with numerical ratings, which show a positive link between more excellent ratings and positive sentiment scores. A significant drop in sentiment scores following the 2008-2009 recession emphasizes how the global financial crisis affected the hospitality sector. Significant differences in guest feelings between cities, states, and nations are shown by geographic analysis, underscoring the necessity of region-specific approaches. Sentiment distribution and trends were revealed via intricate visualizations such as heat maps, box plots, scatter plots, and histograms. To improve guest happiness, the study uses an understanding of geographical variations. These results give hotel management a solid framework for raising customer satisfaction and loyalty, customizing marketing campaigns, and enhancing service quality. For deeper insights, future studies may investigate more sophisticated NLP techniques. [ABSTRACT FROM AUTHOR]

Wind energy systems are based on synchronous machines, which can support high-speed rotation cases due to possible high-speed values of incoming winds. The machines used are affiliated with permanent magnet machines, whereas speed detection can become difficult. This complication appears when high incoming wind speed values increase the motor temperature, which in turn can influence motor parameters, and especially the stator resistance. This can impact the proposed speed software estimator robustness. The proposed high-speed estimator algorithm is based on the Model Reference Adaptive System (MRAS) estimation method, which can be used for motor speed estimation. This concept includes the reactive power model, which ensures the robustness of the estimator when facing any possible stator resistance variation, even at very high speeds. [ABSTRACT FROM AUTHOR]

This paper aims to analyse the ambiguous relationship with modernity of the holiday spaces in the Third Reich. The Kraft durch Freude (KdF) and the Hitlerjugend, the two major Nazi organisations dedicated to normalising the leisure time of the Reich's subjects, were protagonists of architectural experiences characterised by opposing conceptions of modernity. Two radically opposed architectural models seem to emerge from the KdF Seebad Prora seaside resort and from the ideal layout of the camp recommended by the Hitlerjugend manuals: the machine and the camp. The analysis and comparison of these two models define an opportunity to investigate the complexity of the totalitarian spatial ecosystem by analysing its two-faced approach to modernity, its structural link with the regime and the contemporary perception of its difficult heritage, attempting to dispel certain prejudices and oversimplifications regarding Nazi Germany's planning.

The development of industrial hemp production necessitates the creation of new technical means and methods, and the refinement of technological approaches for cultivating and harvesting this crop. The harvesting process requires special attention, which is determined by the characteristics of this crop, the stems of which contain strong fibers making it difficult to cut them. The article discusses the efficiency of using the machine that was developed and manufactured for spring harvesting of hemp stalks. The parameters of the hemp stalks windrow were considered, taking into account the factors affecting its quality. In addition, there were selected the parameters to asses the quality of the resulting windrow. The research was carried out using probability theory and statistical methods. Through experimental studies, the functionality of the developed and manufactured machine was confirmed. It was established that the machine facilitates the formation of a uniform windrow from hemp stalks, with the skew cutting angle not exceeding 17˚, which allows it to be collected with a baler, minimizing the risk of clogging. [ABSTRACT FROM AUTHOR]

Pineapple processing involves peeling, coring and slicing of pineapple. A simple manual pineapple processing machine was developed to enhance the crude method of processing pineapple using just the knife and to reduce musculoskeletal problems associated with processing large quantity of pineapples with the knife. Hence, the objective of this paper is to design and develop a manual pineapple processing machine capable of peeling, coring and slicing pineapples to be utilized by small and medium enterprises (SME) using Response Surface Method (RSM) and validated using desirability plots. The results of actual and predicted response surface plots confirms pineapple sample weight 1.35 kg, diameter 60, height 110 mm with efficiency of 94.81% as the optimal variables. The desirability plot validated these results with response of 1.47, 0.17, 0.06, 0.22 kg weights of peeled, peel and core of pineapple removed, respectively, machine peeling efficiency at 87.29% as optimal at 11 seconds. At these optimal conditions, the actual efficiency realized was 94.81%. The differences within the actual and predicted valuations were lower and not significant statistically, which implied that selected model efficiently predicted the peeling efficiency of the machine. Center Composite Design Rotatable (CCDR) was employed to initiate 20 experimental processes. [ABSTRACT FROM AUTHOR]

Forests provide crucial ecosystem services and are increasingly threatened by invasive plant species. The spread of these invasive species has affected biodiversity and has become a trending topic due to its impact on both endemic species and biodiversity. Therefore, it is imperative to implement conservation measures to protect native species such as mapping and monitoring invasive plant species in the forest realm. Mapping understory herb invasive plant species within forest categories is challenging, for example species such as Ageratum conyzoides and Cassia tora do not occur in distinct clusters, making them difficult to distinguish from the surrounding forest. In this paper, phenology plays a vital role for analysing the separability of both inter and intra-species discrimination to examine temporal curves for different vegetation indices that affect plant growth during the green and senescence periods. Machine learning algorithms, including regression tree-based algorithms, decision tree-based algorithms, and probabilistic algorithms, were used to determine the most effective algorithm for pixel-based classification. Support Vector Machine (SVM) classifier was the most effective method, with an overall accuracy of this classifier was calculated as 90.28% and a kappa of 0.88. The findings indicate that machine learning algorithms remain effective for pixel-based classification of understory invasive plant species from forest class. Thus, this study shows a technical method to distinguish invasive plant species from forest class which can help forest managers to locate invasion sites to eradicate them and conserve native biodiversity. [ABSTRACT FROM AUTHOR]

This research is based on the modeling, internal structure analysis, and automation of a cassava grinding machine. For the design, the single-cylinder grinder was chosen due to its advantages, notably simplicity and versatility. The grinding method used in this type of grinder is compression. The mechanical design and simulation software first allowed for the design of the grinder and then for performing static analyses under three loads (P1 = 10000N, P2 = 15000N, and P3 = 20000N). The results of these tests led to the selection of P3 = 20000N as the straightening load, with a maximum stress value in the static analysis of 88,18 MPa and a maximum deformation of 0,000358 under the force of load P3. Additionally, the frequency analysis distinguished five resonance modes. The results for each mode concluded that no resonance would affect the machine, thus ensuring stable operation. Furthermore, fatigue, frequency, and safety factor studies showed that the machine could withstand a load of m3 = 2000 kg without damage, with a service life of 1e+09 cycles. Considering the total number of life cycles, which is 1e+09 cycles, this means that the machine will have a service life of 347000 years, with a total grinding output of 2e+12 kg of cassava and 5840000 kg per year. The factor of safety is FoS = 1,78, indicating a sufficient margin for safe operating conditions. The automation of the grinder was carried out using a GRAFCET model and a sophisticated human-machine interface (HMI), providing an additional safety point for the machine and allowing the operator to monitor the operation via a simple graphical interface. This automation enables continuous operation with minimal human intervention, thereby improving the efficiency and safety of the cassava grinding process. [ABSTRACT FROM AUTHOR]

Nylon is a type of plastic made into thin sheets or bags and used often as transference sheets for water proof packaging. The ease of cutting and sealing a nylon material, especially during mass production of nylon bags, has necessitated automating the process. This paper develops an affordable and effective low-cost semi-automatic nylon cutting and sealing machine that can be utilized by small-scale businesses. The 900 x 400 x 350 mm machine comprises sealing and cutting filament, transformer with wires, teflon tape, micro switch, electric motor, transmission shaft, aluminum casing, mild steel stand and microcontroller. The components were optimized for durability, yet simple one operator use and portability for small-scale business settings. A transmission shaft size 25.4 mm in diameter and 850 mm in length is placed on the machine. The size of the shaft is selected according to the size of the electric motor. Structural analysis through testing validated the structural integrity of key parts. The yield stress was 380 N/mm2 and the safety factor was considered to be 2, so the working stress was 190 N/mm2 and the permissible shear stress was 100.71 N/mm². The performance testing showed that the prototype semi-automatic cutting and sealing machine has efficiency of 80% while cutting and sealing nylon at a rate of 700 bags per hour. These results confirm the machine's ability to overcome the limitations of laborious manual methods through a continuous, high-output cutting and sealing process. Further, the machine is functional and possesses high performance efficiency with reasonable degree of accuracy. [ABSTRACT FROM AUTHOR]

Nowadays, plastic waste is one of the most pressing issues, especially in developing countries. Plastic waste comes from everyday products such as plastic food boxes, plastic bottles, disposable products, or plastc straws causing negative effects on the environment. On the other hand, grass straws are eco-friendly and safe and can be easily found in Southeast Asian countries such as Vietnam, Indonesia, and Malaysia. However, the process of grass straw production is implemented manually, resulting in low productivity and unsafe labor conditions. Among the stages of producing grass straws, cleaning the core of the straw is the most important because it determines its quality. Aiming to automate the grass straw production process, this paper introduces the first grass straw core cleaning machine in the world. [ABSTRACT FROM AUTHOR]

Traditional library management systems primarily focus on cataloguing and organizing resources, which creates challenges in fulfilling modern expectations for personalized user experiences. These systems depend on standardized classification and metadata-based search mechanisms, leading to limited support for personalized recommendations. As a result, users often encounter static interactions that are less engaging. The heavy reliance on librarian-mediated assistance, while beneficial, lacks scalability and the ability to provide real-time, tailored recommendations. As the demand for user-centric experiences increases, libraries are increasingly adopting Artificial Intelligence (AI) technologies, such as machine learning (ML) and natural language processing (NLP), to enhance resource discoverability and offer personalized recommendations. This paper reviews existing literature on both traditional and AI-driven library management systems, highlighting the transformative potential of AI in delivering tailored recommendations through advanced algorithms and behavioural data analysis. AI enables libraries to adapt dynamically to user preferences, academic focuses, and interaction patterns, ultimately enhancing user satisfaction and engagement. The review also addresses challenges, such as data privacy concerns and resource constraints, faced by libraries in implementing AI-based solutions. [ABSTRACT FROM AUTHOR]

The digitization of production systems has revolutionized industrial monitoring. Analyzing real-time bottom-up data enables the dynamic monitoring of industrial processes. Data are collected in various types, like video frames and time signals. This article focuses on leveraging images from a vision system to monitor the manufacturing process on a computer numerical control (CNC) lathe machine. We propose a method for designing and integrating these video modules on the edge of a production line. This approach detects the presence of raw parts, measures process parameters, assesses tool status, and checks roughness in real time using image processing techniques. The efficiency is evaluated by checking the deployment, the accuracy, the responsiveness, and the limitations. Finally, a perspective is offered to use the metadata off the edge in a more complex artificial-intelligence (AI) method for predictive maintenance. [ABSTRACT FROM AUTHOR]

This paper describes the creativity, design, and construction of a customized sago machine with a kneading pipe, filter, storage tank, and shredder. The main objective of this innovation is to maximize the conversion of sago stems into superior starch. Sago, an essential food staple in many areas, is typically processed by hand, which results in tedious and time-consuming processes. This project focuses on developing an automated and efficient system to drastically increase productivity and the simplicity of use and transform the sago processing sector. [ABSTRACT FROM AUTHOR]

Arobotic system refers to a mechanized apparatus, often controllable remotely or programmable via a computer, that is capable of executing various tasks. These machines can be directed by an external control source. While some robots mimic human-like features, most are designed primarily for functionality rather than appearance. They encompass a wide range, from humanoid models like Honda's Advanced Step in Innovative Mobility and TOSY's Ping Pong Playing Robot to specialized industrial, medical, or assistance robots, such as those used in surgery. Over time, robotic capabilities have advanced significantly. Modern robots exhibit a broad range of movements and actions, mirroring many tasks performed by humans in daily life. However, despite these advancements, certain crucial operations, such as ladder climbing, which is essential for surveillance, security, and accessing elevated materials, remain challenging for current robotic systems. As part of our project dissertation, we aim to develop a specialized machine capable of climbing ladders. Our design incorporates mechanisms for lower-arm locking, upper-arm advancement and reverse, and upper-arm locking to facilitate this essential function. [ABSTRACT FROM AUTHOR]

This research investigated the computer aided engineering performance analysis of a lathe machine spindle using field generated data. The Excel 360x1000 lathe in the FUPRE workshop has been used for numerous students training and project experiments using non-optimal settings, without evaluation of the spindle performance, productivity, and product surface finishing. This study analyzed the interaction between input [spindle speed, depth of cut and feed] and response [material removal rate and surface roughness of machined part] parameters, as well as evaluates the integrity of the lathe spindle during turning of AISI 1085 work-piece using carbide inserts. RSM was used for the design of the experiment and optimization of the process to obtain maximum material removal rate and minimal surface roughness. The turning process was also to modeled, utilizing maximum generated cutting forces acting on the spindle during machining to ascertain its resilience. Optimization of the dependent and independent variables proffered the best solution based on set constraints with a desirability of 0.788. The conducted Finite element analysis [static, dynamic, and fatigue] yielded spindle maximum deflection of 0.01432mm, maximum von mises stress of 18840000N/m^2, least natural frequency of 898.64Hz, and spindle remaining fatigue life of 100 million cycles. These findings infer that the lathe spindle is robust and optimal responses were achieved at a specific input configuration. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Filosofía (0185-3481) is the property of Universidad Iberoamericana Cuidad de Mexico and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The area of computer numerical control (CNC) machines has grown fast, and their use has risen significantly in recent years. This article presents the design and development of a CNC writing machine that uses an Arduino, a motor driver, a stepper motor, and a servo motor. The machine is meant to create 2D designs and write in numerous input languages using 3-axis simultaneous interpolated operations. The suggested machine is low-cost, simple to build, and can be operated with merely G codes. The performance of the CNC writing machine was assessed by testing it on a range of solid surfaces, including paper, cardboard, and wood. The results reveal that the machine can generate high-quality text and images with great accuracy and consistency. The proposed machine's ability to write in several input languages makes it appropriate for various applications, including art, design, and engineering.

This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.

It is essential to formulate appropriate feeding pellets with the required nutrient compositions for poultry animals to meet the growing demand for protein through the provision of eggs and meat. Forming the required feed concentrates into pellet-mash requires a pelletizing machine, which is, in most cases, very expensive for the local farmers due to the high foreign exchange rate. Based on this, the study focuses on the development of a simple and affordable pelletizing machine from locally sourced materials. The machine consists of a frame, hopper, die roller, pelletizer, and internal combustion (5.5 hp), and it was run at 950, 600, and 450 revolutions per minute. The formation and discharge of pellets from the machine increased with the pelletizing efficiency (Pe) of 70.3% to 84.6% at a moisture content (MC) of 15.8% to 27.1%, and the Pe decreased at a moisture content above 29.0%. Also, the drying temperature (DT) has a significant effect on the pellet moisture content (MC) and bulk density at P > 0.05. The effects of weather conditions on pellets produced using the COOI24m pelletizer were assessed in this study. The analysis showed that changes in weather conditions had an insignificant effect on the quality and properties of the pellets. The machine is highly recommended for use by small-scale livestock farmers for the local production of pellet-mash of different compositions because of its affordability, ease of use, and high working efficiency.

Natural fiber processing is the type of fiber as raw materials for textile or other industries that can be obtained directly from nature. In the Indonesian automotive industry, the manufacture of parts in vehicles is Polypropylene high impact (PPHI). An example of an existing part is a CVT slide piece made with a mixed polymer composite material from PPHI and pineapple leaf fiber. Pineapple leaf fibers with small sizes are needed so that the mixing of polymer composites is good. Therefore modern technology is required to process pineapple leaf fibers. This final project makes a natural fiber powder machine for processing natural fiber, namely scavenging. The research methodology used is a prescriptive design method. The design results produce a natural fiber powder machine (pineapple leaf fiber) for polymer composite materials with long size specifications of 420 mm long, 300 mm wide, and 582 mm high. The production capacity of the natural fiber storage machine is 5 kg/h. The source of the engine drive is a 1 HP AC electric motor with a rev of 2800 rpm. The transmission system uses a V-belt with a drive shaft 30 mm in diameter. The frame construction is made of a 35x35x5 mm profile with ST42 material and knives using S45C material (AISI 1045) with a thickness of 10 mm. It uses nine dynamic blades and six sharp plane fixed blades in a 30-degree active blade and a 60-degree fixed blade.

The study aimed to look into how dairy cattle rearing in Russia and the USSR got technical and technological support in the first half of the twentieth century. At the start of the 20th century, two-thirds of Russian agriculture were small peasant farms. They used manual labor and did not need the costly machines. The consolidation of farms was very slow. Yet it laid the foundation for a shift to mechanized livestock production. The First World War, which began in 1914, followed by the Revolution and the Civil War halted for years the technical development of Russia's agricultural production. In late 20s, the Soviet Union already faced the challenge of producing more agricultural goods. This increase could be possible by starting highly mechanized agricultural enterprises. By 1931, “Soyuzselstroy”, an All-Union Agricultural Construction Association, had prepared standard designs of dairy cattle farms for 100 and 200 heads. They provided for mechanization of main processes of cow housing and care. In 1930-1940, scientists and engineers of the All-Union Institute of Mechanization (VIM) and its branches undertook the creation of cattle farming machinery. This period saw the development and manufacture of a number of machines that made livestock farmers labor easier. The work on setting standards for designing the cow barns started. By 1939, VIM had designed a system of machines and test edit in collective farms. The need for specialized organizations to help collective farms to install and put into operation the livestock equipment became evident. At the same time, training of agricultural engineers started in Leningrad, Moscow and other USSR cities. A Decree by the Council of People's Commissars of the Soviet Union dated July 8, 1939, set a delivery plan of machines and units for livestock farming in 1940. Thus, by 1941 the conditions were created for integrated mechanization of main labor-intensive processes in national animal husbandry. Those days agricultural ecology was not in the focus. With no widespread production of mineral fertilizers in place, application of all manure to soil posed no environmental risk.

Copyright of Foreign Literature Studies is the property of Foreign Literature Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents a novel algorithm for the development of stability charts. The second-order differential homogeneous equation describing a double salient reluctance machine with a capacitance connected to its stator winding is transformed into hill's equation. The circuit components are the stator coil time-varying inductance of a double salient reluctance machine, capacitance and resistance. All these are modeled by hill's equation. The double salient reluctance machine acts as an energy conversion system. The maximum and minimum inductance of the energy conversion system is measured in laboratory by inductance, capacitance, and resistance (LCR) meter. These values help to determine the inductance modulation index. The inductance modulation indetx, the characteristic constant and the characteristic parameter obtained from modeling equations are used in the MATLAB/Simulink model. The MATLAB/Simulink simulations generate stable and unstable oscillations to form stability charts. The proposed stability charts are in good agreement with the Ince-Stritt stability chart, which is widely applied in physics, mechanics and in electrical engineering, especially where the state of stability of a system or an electric oscillatory circuit is to be determined. [ABSTRACT FROM AUTHOR]

The study examines a comprehensive analysis of the frequency and impact of machine-related fatal accidents at road construction sites in the Niger Delta region of Nigeria, with the aim of understanding their repercussions for workers and the environment. Additionally, the research aims to identify effective strategies for preventing such accidents. The study utilizes a quantitative research design and employs a purposive sampling technique to distribute 300 well-structured questionnaires designed to gather detailed information on the causes and consequences of fatalities and accidents at road construction sites. The findings of the study demonstrate that various factors, such as workers' use of drugs and alcohol, prolonged work hours, use of faulty tools and machinery, as well as negligent and risky behaviour, significantly increase the susceptibility of workers to fatal accidents and loss of life. Consequently, this contributes to heightened stress, anxiety, and fear among workers, negatively impacting their productivity and overall performance. The study identifies several effective preventive measures, including the implementation of traffic control protocols, regular inspection and maintenance of equipment, and stringent safety regulations within work zones, as well as the establishment of clear communication protocols. Furthermore, the research emphasizes the importance of close monitoring and providing counselling to machinery operators to instigate a change in their attitudes and behaviours, consequently averting accidents. In conclusion, the research strongly advocates for the reduction of the risk of machine fatalities at road construction sites by universally implementing and rigorously adhering to the highlighted measures by all stakeholders in the construction industry. [ABSTRACT FROM AUTHOR]

Onion detopping is one of the unit operations involved in the cultivation of onion crop. Manual onion detopping is time consuming and highly drudgery. Therefore, an onion detopping machine was designed and developed for higher efficiency. An efficient detopping mechanism designed to achieve the maximum performance parameters in terms of detopping efficiency, per cent damage of onion bulbs and capacity of the onion detopping machine. By considering the crop parameters and functional requirement, four types of shearing designs of detopping tool namely, lead screw, square shaft with two cutting edges, square shaft with four cutting edges and helical roller were designed, developed and evaluated. Among four different shearing mechanisms, the helical roller type detopping tool was found to be effective in detopping the onion leaves. The helical roller type detopping tool had a detopping efficiency (98.44±1.07%), per cent damage (2.05±0.45%), conveying efficiency (97.60±1.02 %) and capacity (372.60±13.95 kg/h), respectively. [ABSTRACT FROM AUTHOR]

Starting from the short story In the Penal Colony, the article sets out to investigate the idea of power and law in Kafka and its implications with the device of violence and guilt. It deals with a power that distances itself as much from the theories of legal and political self-representation delivered to us by the modern tradition as from the deconstructive theories of power and government that have been widely affirmed in the last century. However, alongside the features of discontinuity, lines of continuity with formalist theory are also evident, especially in relation to its repressive and sanctioning aspects, centered on people's lives and bodies. [ABSTRACT FROM AUTHOR]

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning process. However, most of the currently used techniques for evaluating cognitive levels rely on labour-intensive and time-consuming manual coding. In this study, we explore the machine learning (ML) algorithms and taxonomy of Bloom's cognitive levels to explore features that affect learner's cognitive level in online assessments and the ability to automatically predict learner's cognitive level and thus, come up with a recommendation or pedagogical intervention to improve learner's acquisition. The analysis of 15,182 learners' assessments of a specific learning concept affirms the effectiveness of our approach. We attain an accuracy of 82.21% using ML algorithms. These results are very encouraging and have implications for how automated cognitive-level analysis tools for online learning will be developed in the future. [ABSTRACT FROM AUTHOR]

This paper concerns the identification of current communication technologies and software functionalities from the field of digitalization and Industry 4.0, from the point of view of benefits and applicability for the machine manufacturer. To identify the relevant technologies and functionalities, research was carried out in both the descriptive and statistical literature. As a result, both technologies that are currently the most widely distributed, as well as eleven IT functionalities relevant to mechanical engineers, were identified and described in terms of their application and implementation. Furthermore, a knowledge gap was identified in the area of industry transfer in the field of Industry 4.0/digitalization. [ABSTRACT FROM AUTHOR]

From early Greek philosophers to Descartes' machinic metaphors of humans-as-machines, to the emergence of physical machine-like humans, the intersections of the human body with machines circle back through hundreds of years of debates on human-technology relationships. We live in an age when robots are becoming increasingly human-like with artificial intelligence that mimics and sometimes exceeds our own. At the same time, we humans are adopting cyborg-like modifications to improve ourselves through biological, mechanical, and computer technologies. This conceptual paper presents a historical overview of the human-machine merger as both a metaphor and material reality. We show that the body has no intrinsic meaning for its distinct social constructions in technophilic and bioconservativist perspectives. This leads to a critical need for discussions about the issues related to dehumanization and personhood. These two topics must inform future research efforts to explore a future when current concepts of humanness may not hold anymore. [ABSTRACT FROM AUTHOR]