Development of a Prototype Plant for the Heat Treatment of Workpieces with Preferably Bainitic Properties

In vehicle construction, components with high tensile strengths are used, especially in the chassis area. At the same time, these components must have high toughness and be insensitive to cracking. For this purpose, hardened and tempered but also salt-bainitized components are used. The associated usual process chain after steel production consists of forming processes with subsequent cooling of the forging blanks and subsequent heat treatment with renewed heating to set the required material properties. From an energy point of view, heat treatment from the forging heat is desirable, which in addition to shortening the process chain is also associated with a reduction in CO2 emissions. A prototype system for controlled bainitization has been developed, which implements the heat treatment immediately after hot forming by utilizing the still existing forming temperature. Here, a controlled spray field generates both a quenching and an isothermal holding phase. Various sensors generate input variables to cool the workpieces in a controlled manner. This paper gives an overview of the system technology, realized cooling curves and the resulting hardness.

Processing deteriorated beet. Part 2: Preventive and process measures

This paper describes the different methodologies which can be used to deal with the technological impact of deteriorated beet on processing. The procedure developed by EU sugar beet research institutes to protect long-term stored beet against the outside weather conditions is considered a necessary preventive measure to limit beet deterioration. In addition, a wide range of process measures is available to handle incoming deteriorated beet material in beet sugar manufacture. The specific dextran processing problems associated with frost-damaged beet cannot normally be solved by the usual process measures and require the addition of the rather expensive enzyme dextranase. A few alternative processes which could either improve or even enable the processing of deteriorated beet are briefly discussed. The financial consequences of processing deteriorated beet on the manufacturing costs of white sugar are outlined. Finally, the point is explained at which processing of very badly affected beet is supposed to be technologically as well as economically unacceptable.

Honorrhoid stomatitis

Klepper (Derm. Woch., 1925, no. 39) describes an interesting case of gonorrhoid stomatitis in a hospital nurse with a history of recurrent aphthous stomatitis. 4 days after the usual relapse, the patient began to care for the child suffering from gonoblenorrhea, and after the next 4 days, she had a sudden deterioration of the usual process in the mouth: severe pain while eating, swelling of the tongue, fever, sores near the tip of the tongue, in the corner of the mouth and along the edge of the lower gum, with severe inflammation. Gonococci were found in smears and cultures of ulcer discharge. This case is interesting, as it contradicts the old ideas about the immunity of the oral mucosa of adults in relation to gonorrhoid infection.

Optimization of tool design parameters for thread tapping process of Ti-6Al-4V

Thread tapping is one of the most important machining processes. Although thread tapping is a usual process and has been used for decades, the process still needs improvement for promising materials such as titanium alloys to increase the performance of the process. Titanium alloys are known as difficult-to-cut materials due to their low heat conductivity and elastic modulus. The aim of the work presented in this paper is to optimize the tapping tool primary design parameters for Ti-6Al-4V. The most influential tool design parameters on the process were selected as the rake angle, helical flute angle, chamfer angle, and tool coating. Optimization of the tool design parameters was made by considering the results of the experimental work. Two levels of each parameter were chosen. Taguchi L8 orthogonal array was used as the design of experiment. Tapping tool temperature and tapping torque were determined as the process outputs. According to the results, the optimized tool design parameters were found as 6° rake angle, 12° helical flute angle, 14° chamfer angle, and TiCN coating.

On the Normalization of Interval Data

The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on numeric data? A straightforward answer is that it is enough to apply a correct interval arithmetic, since the normalized exact value will be enclosed in the resulting “normalized” interval. This paper shows that this approach is not enough since the resulting “normalized” interval can be even wider than the input intervals. So, we propose a pair of axioms that must be satisfied by an interval arithmetic in order to be applied in the normalization of intervals. We show how some known interval arithmetics behave with respect to these axioms. The paper ends with a discussion about the current paradigm of interval computations.

Detection of Pneumonia from X-Ray Images Using Convolutional Neural Networks

Pneumonia is an infection which is caused by bacteria or viruses. Early diagnosis is critical to treat the disease successfully without delaying the treatment much. In most of the cases and as per the usual process the patient with pneumonia-like symptoms can be dragonized via frontal and lateral chest x-ray images, which are then seen over by the naked eye by doctors or radiologists. The diagnoses can be misleading and confusing as the appearance of the disease can be unclear in X-ray images and can put the doctor in a dilemma, as the features may not be visible clearly via naked eyes. That is why computer-aided diagnosis is generally required to guide clinicians. The model is based upon the convolutional neural network architecture, wherein pre-processed images are fed to the developed network layers and trained to provide us results with high accuracy of 94.3%, a precision rate of 93.18%, recall of 98.20% and an F1 score of 95.63%. The objective of the work is to design a model that can provide fast and accurate analysis which not only may save diagnosis cost, but also provide invaluable time for the doctors to begin the treatment if the disease is detected early.

Evidence Linking Protein Misfolding to Quality Control in Progressive Neurodegenerative Diseases

Several proteolytic systems including ubiquitin (Ub)-proteasome system (UPS), chaperonemediated autophagy (CMA), and macroautophagy are used by the mammalian cells to remove misfolded proteins (MPs). UPS mediates degradation of most of the MPs, where Ub-conjugated substrates are deubiquitinated, unfolded, and passed through the proteasome’s narrow chamber, and eventually break into smaller peptides. It has been observed that the substrates that show a specific degradation signal, the KFERQ sequence motif, can be delivered to and go through CMA-mediated degradation in lysosomes. Macroautophagy can help in the degradation of substrates that are prone to aggregation and resistant to both the CMA and UPS. In the aforesaid case, cargoes are separated into autophagosomes before lysosomal hydrolase-mediated degradation. Even though the majority of the aggregated and MPs in the human proteome can be removed via cellular protein quality control (PQC), some mutant and native proteins tend to aggregate into β-sheet-rich oligomers that exhibit resistance to all identified proteolytic processes and can, therefore, grow into extracellular plaques or inclusion bodies. Indeed, the buildup of protease-resistant aggregated and MPs is a usual process underlying various protein misfolding disorders, including neurodegenerative diseases (NDs) for example Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and prion diseases. In this article, we have focused on the contribution of PQC in the degradation of pathogenic proteins in NDs.

CLASSIFICATION OF CUSTOMER COMPLAINTS ON INSTAGRAM COMMENTS USING NAÏVE BAYES ALGORITHM WITH N-GRAM FEATURE EXTENSION

Customer complaints about the company can be used as a form of self-evaluation and performance that has been carried out by the company, based on customer complaints the company can find out the weaknesses that exist in the company and fix them. The forms of submitting customer complaints are very diverse, currently not only by telephone, but customers also submit suggestions or complaints, customers can submit suggestions or complaints via electronic mail or e-mail or forums in cyberspace that are indeed created by product-producing companies to accommodate various complaints, suggestions, and direct criticism from consumers, especially social media that are free to express opinions on the delivery services used. Instagram is a social media that is more inclined towards images and on the other hand, has captions and comments text, a study is needed for the problem of customer complaints from shipping service users on an Instagram account of a delivery service company. Based on this background, a solution is needed in solving problems for text mining classification using Naïve Bayes with SMOTE techniques and N-Gram feature extraction with the usual process for text mining so that it can produce Naïve Bayes and SMOTE accuracy with an accuracy of 88.54%, before implementation. N-Gram and the accuracy rate increased by 1.44% after the N-Gram Term was applied to 89.98% by using a dataset of 776 Instagram comment text records that had to preprocess text.

International Academy for Systems and Cybernetic Sciences (IASCYS): The first awards of the International Prize

For the first time the International Academy for Systems and Cybernetic Sciences, IASCYS, ( http://iascys.org), has awarded the Charles François International Prize, during the 10thUES-EUS Congress (http://ues-eus.eu), in Brussels, Belgium, Europe. The first step of the procedure was the nomination of interesting papers through asking for the reviewing process by all IASCYS Academicians. So, 6 weeks before the start of the meeting, a booklet of 40 abstracts, all previously anonymously peer-reviewed by the scientific committee of the congress, and each as a 1 page of text, with neither author(s) name(s), nor affiliation(s) or references, was sent to all Academicians. After a 1 month delay, 10 papers of people from 9 Countries (Algeria, Belgium, Denmark, France, Germany, Greece, Italy, Portugal, Russia), have been nominated by Academicians, by e-mails replies. After the congress organizers have proposed as jurors a team of 3 systems scientists who all are speaking both French and English (the official formal languages of the UES-EUS congress), an equal number of 3 Academicians, who are as well fluent in English, French and other languages, attended as the IASCYS part of the jury. After this key step of peers pre-selection, the second step, during the meeting in Brussels, was for all 6 jurors to listen and participate to the corresponding talks-debate for each of the selected papers, in order to rank the top 3 of the most promising works, and then to reflect on the final ranking for the award. The jurors were anonymous. The listening process was the usual process of talk (20 min) and questions (10 min) with the public as in every congress, but also with personal no-formal discussion of jurors with the nominated persons. The first Charles François International Prize of the Academy (gold medal) was awarded to Julio LABORDE, a young Chilean research engineer who is working in the International industrial firm 'Insight Signals'. He is also a student in the prestigious École Pratique des Hautes Études, in Paris, France. His talk was about "Extraction of Information from Agent Base Models. A new pre-topological metric for controlling the propagation of crises." It took place during the 'Methods and tools for risk management of complex socio-technical systems'session. No discussion, his work was the most promising work of the congress. His work was the most promising work of this congress of the European Union for Systemics.This second step allows also, after a debate, to award 3 second places (3 silver medals). They all got the Charles François tutorial in Systems Science on a USB stick and they all, gold and silver medals (Figure 1), will have a certificate of ranking. But, all of them, will get their certificates of award/ranking only after their paper proof will be corrected and accepted. The other 3 certificated persons, silver medals, are (by alphabetic order): -Mick ASHBY, a research engineer in computing sciences who is working for IBM in Germany. His work was about the application of a new paradigm 'The Ethical Regulator Theorem'; -Tjorven HARMSEN, a very young Swedish women who is in Ph. D. in the Leibniz Institute for Research on Society and Space, in Berlin (Germany). Her work was ab out 'Crisis as Social Autocatalysis. On the emergence and Utilization of Opportunities' (a very promising talk, a young researcher to follow; and -Daniela TERRILE, a women who is Professor in the Department of Design at the Polytechnic Institute of Milano, Italy. Her work was about 'Applications of the Target Constellation Model'. 2 other works were also very interesting but one was not into the book of abstracts (it was not peer-reviewed), the other one was into it but it was not pre-selected. No process is perfect. But the rule is the rule: no peer-reviewing, no preselection, means no competition. The important point is that few of the 'preselected and nominated, but not ranked in the top 3' participants said they will attend the next one edition of the Prize in Morocco. And other young researchers said they will do their best to attend another occurrence of the Prize. The Prize was opened to strengthen multi-disciplinary research and the multi-language communication of recent results, towards a worldwide education in Cybernetics and Systems Thinking (Bricage, 2017), which are aims of the Academy (Bricage, 2014). “Want to influence the world? Map reveals the best languages to speak.” (Ronen et al., 2014). On the IASCYS website you will find the rules of the Prize, in English, Spanish, French and Russian.

Drug Repurposing and New Therapeutic Strategies for SARS-CoV-2 Disease Using a Novel Molecular Modeling-AI Hybrid Workflow

<p>The recent<b> </b>outbreak of the novel coronavirus (SARS-CoV-2) poses a significant challenge to the scientific and medical communities to find immediate treatments. The usual process of identifying viable molecules and transforming them into a safe and effective drug takes 10-15 years, with around 5 years of that time spent in preclinical research and development alone. The fastest strategy is to identify existing drugs or late-stage clinical molecules (originally intended for other therapeutic targets) that already have some level of efficacy. To this end, we tasked our novel molecular modeling-AI hybrid computational platform with finding potential inhibitors of the SARS-CoV-2 main protease (M^pro, 3CL^pro). Over 13,000 FDA-approved drugs and clinical candidates (represented by just under 30,000 protomers) were examined. This effort resulted in the identification of several promising molecules. Moreover, it provided insight into key chemical motifs surely to be beneficial in the design of future inhibitors. Finally, it facilitated a unique perspective into other potentially therapeutic targets and pathways for SARS-CoV-2.</p>