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Hypertension or high blood pressure is also called a “silent killer” that may lead to serious damage to the heart and kidney. The worst case can result in sudden death. Unbalanced diets are one of the risk factors for hypertension. Previous studies have proven that diet plays a significant role in influencing hypertension patient condition. Proper planning on the selection of diets needs to be done to control food intake for this cardiovascular disease patient. This study aims to formulate a mathematical model of diet planning for hypertension patients. Specifically, this study attempts to determine the amount of nutrients need by hypertension patients, to find the cost of the food combination, and to identify the best model between linear programming and integer programming. The research model included 10 types of food groups with 200 variables based on Malaysian recipes and developed a mathematical model using two programming techniques; linear programming and integer programming. The finding showed that the solution provided by the entire programming method has met the constraints and requirements of the food group. The results from the integer programming approach would offer optimal and efficient alternatives to diet planning for patients with hypertension. It can serve as a guideline for hypertension patients on type of food to eat and the correct amount of serving to complete their nutritional plan.

Electrogastroenterography is a field that studies the condition of the gastrointestinal tract. Electrophysiological signals contain artifacts that are not directly related to the activity of the organism, and the filtration of such artifacts is an important issue. Electrogastroenterography is a field that studies the condition of the gastrointestinal tract. This method is associated with radiography, ultrasound, endoscopy. In these methods, electrical signals are taken from the surface of the abdominal cavity. For this purpose, the issues of elimination of artifactors, processing and analysis of signals on the example of electrogastroenterograms for processing and measurement of electrophysiological signals were considered. Keywords:Electrogastroenterography, non-stationary signals, electrophysiological signals, computer processing, wavelet conversion, frequency modulation, wavelet Morle function

Objective. To develop methods for a rapid distance computer diagnosis of COVID-19 based on the analysis of breath sounds. It is known that changes in breath sounds can be the indicators of respiratory organs diseases. Computer analysis of these sounds can indicate their typical changes caused by COVID-19, and can be used for a rapid preliminary diagnosis of this disease. Materials and methods. The method of fast Fourier transform (FFT) was used for computer analysis of breath sounds, recorded near the mouth of 14 COVID-19 patients (aged 1880 years) and 17 healthy volunteers (aged 548 years). The frequency of breath sound records ranged from 44 to 96 kHz. Unlike the conventional methods of computer analysis for diagnosis of diseases based on respiratory sound studying, we offer to test a high-frequency part of FFT (20006000 kHz). Results. While comparing the breath sound FFT in patients and healthy volunteers, we developed the methods for COVID-19 computer diagnosis and determined the numerical criteria in patients and healthy persons. These criteria do not depend on sex and age of the examined persons. Conclusions. The offered computer methods based on the analysis of breath sound FFT in patients and volunteers permit to diagnose COVID -19 with relatively high diagnostic parameters. These methods can be used in development of noninvasive means for preliminary self-express diagnosis of COVID-19.

Разработана методика, обеспечивающая полный спектр организации работ по программированию микроконтроллера MDR32F9Q2I, которая позволяет получить, в частности, системы управления и мониторинга источников вторичного электроснабжения. Программирование микроконтроллера, построенного на базе высокопроизводительного процессорного RISC ядра ARM, производилось в интегрированной среде разработки Eclipse IDE в операционной системе Windows 10 Pro. Интегрированная среда разработки Eclipse выбрана как наиболее удобная и доступная среда, поддерживает всевозможные типы языков программирования и непрерывную компиляцию. В настоящее время 16- и 32-битные микроконтроллеры быстро набирают популярность в сфере промышленных задач. Их применение обусловлено постоянно возрастающей сложностью задач, жесткими требованиями к производительности интегрируемых контроллеров управления, необходимостью иметь в электронных устройствах развитые органы пользовательского управления. Представленный стенд для моделирования, использующий интерфейсный мост между шинами I2C и 1-Wire - DS2482-100, преобразует протоколы между управляющим I2C микроконтроллером (мастером) и ведомыми 1-Wire устройствами, а также контролирует скорости нарастания и уменьшения напряжения в линии. Основой для написания класса DS2482 являются заголовочные файлы Arduino.h и OneWire.h, которые находятся в свободном доступе In this article, we developed a technique that provides a full range of organization of works on programming the MDR32F9Q2I microcontroller, which allows you to obtain control and monitoring systems for secondary power supply sources. The microcontroller based on the high-performance ARM RISC processor core was programmed in the Eclipse IDE on the Windows 10 Pro operating system. We chose the Eclipse integrated development environment as the most convenient and accessible environment, it supports all kinds of programming languages and continuous compilation. Currently, 16- and 32-bit microcontrollers are rapidly gaining popularity in the field of industrial tasks. Their use is due to the ever-increasing complexity of tasks, stringent requirements for the performance of integrated controllers, the need to have advanced user controls in electronic devices. We present a simulation stand that uses an interface bridge between the I2C and 1-Wire buses - DS2482-100, converts protocols between the I2C microcontroller (master) and 1-Wire slaves, and also controls the voltage rise and fall rates in the line. The basis for writing the DS2482 class is the Arduino.h and OneWire.h header files, which are freely available

The application of the Jamus Tea motif batik theme in the interior design of Candi Loka Restaurant in Ngawi is an effort to accommodate the needs of visitors to the Jamus Tea Plantation tourism object to enjoy the processed tea. This work aims to create a comfortable interior design of Candi Loka Restaurant and apply a contemporary style. In this work, the theme of the Jamus Tea batik motif is applied through the Kurtz programming method. The result of this work is the interior design of Candi Loka Restaurant, which includes lobby facilities, dining area, teashop, workshop and education area, management office, kitchen, rest area, warehouse, prayer room, and toilet. The results of this work can be a reference for interior designers in designing contemporary interior concepts based on local wisdom

Reading is one of the basic skills that must be mastered by everyone. However, the reading rate of people in Indonesia is very low. In fact, literacy conditions in Indonesia are now in crisis, which is also called a literacy emergency. Increasing interest in reading in the younger generation in Indonesia today is really important amidst so many technologies that are very rapidly developing. Therefore, Indonesia is currently so active at making movements to increase interest in reading. The purpose of this Community Library is to increase the reading interest of Indonesian people while providing adequate facilities for reading for the community. The design of Community Library uses architectural programming method. The process of this method is divided into two stages consisting of preparing a program that is an activity of analyzing data that led to architectural problems and designing designs that can solve problems. The digitalization of books can be used as a way to increase the children and adults interest in reading again. However, that still feels lacking, because it requires a more efficient steps that can further influence the interest in reading and attract the attention of the public to e interested in reading. One way to attract the reading interest of public to be interested in reading is to turn the library into a creative reading place. This is what underlies the thought of the Community Library. Creating a Community Library with the concept of Recreation Space is expected to help change people's view of reading which was boring to be fun. The design is a comfortable, varied, and fun reading space with complete facilities.

This letter describes the design optimization of a flash memory cell that uses source-induced band-to-band hot electron (SIBE) injection programming method. The programming efficiency is determined by the tunneling current to the floating gate, which is shown to be dependent with the gate length covered width. Optimal gate length covered width is empirically studied in this work through simulation, and we are able to observe more than an order of magnitude increase in the programming efficiency which tremendously reducing the total power consumption of the flash memory.

The subject of this research is the interdisciplinary legal and computer research tools and methods. The authors substantiate the interdisciplinary (legal-computational) methodology for automated analysis and assessment of qualitative changes in legislation and law enforcement practice. Interim results of the research project that are of methodological nature and cover methodological paradigm, principles, means and methods of scientific research are provided. The formulated conclusions represent a summary of heuristic search and computational experiments carried out in the domain field of administrative tort law, as well as comprehension of the process and results of research from both, legal and computer perspectives. Explanation is given to the interdisciplinary paradigm in the indicated methodological area. Leaning on the empirical evidence and observations, the author formulates the three research principles: principle of heterogeneity of domain, principle of discreteness of legal practice, and principle of identity of the model. As the key research tools, the author substantiates and tests in computational experiments the scientific information-analytical system, mathematical and social indicators have been developed, justified and tested in computational experiments. Computer methods (knowledge modeling, natural language processing, machine learning) that ensure automation of identification and usage of indicators mate with the dogmatic method, systemic analysis and expert assessment responsible for legal interpretation of computations. The legal and computer tools are determined for identification and usage of the principal indicators. In conclusion, the author outlines a number of problems and restrictions determined in the course of the conducted research.

It is examined how to use digital facial anthropometry for scientific and practical problems; from biometry up to its different applications including medicine, biology, genetics, pattern recognition, and criminalistics. The presented review includes a brief history of anthropometry (as a descriptive and comparative science, the subject of investigation of which is Homo sapiens) and its transformation into modern computer methods for facial anthropometry. Concepts on face morphotype and phenotype; problems on morphology and morphometry as a basic means of facial digital anthropometry; quantitative and qualitative methods for estimating facial characteristics and parameters; problems for searching for associations between gene patterns in the genome and a man’s facial features; problems for estimating facial attractiveness; correlation between facial anthropometry and “Chernov’s faces” and with cognitive computer graphics used in practical medicine; human facial phenomenon and the problems with emotions, sex, and psychical type recognition; special cases for recognizing facial images (FIs), and methods for their solutions in the frames of digital facial anthropometry and examples of its solution are presented in the paper. The prediction on the close correlation between facial anthropometry and the Internet of Things as a modern world surrounded by a person in the 21st century is determined.

OBJECTIVE Cochlear implant (CI) technology and techniques have advanced over the years. There has not been the same degree of change in programming and there remains a lack of standardization techniques. The purpose of this study is to compare performance in cochlear implant subjects using experienced clinician (EC) standard programming methods versus an Artificial Intelligence, FOX based algorithm for programming. STUDY DESIGN Prospective, nonrandomized, multicenter study using within-subject experimental design SETTING:: Tertiary referral centers. PATIENTS Fifty-five adult patients with ≥ 3 months experience with a Nucleus 5, 6, Kanso, or 7 series sound processor. INTERVENTION Therapeutic Main Outcome Measures: CNC words and AzBio sentences in noise (+10 dB SNR) tests were administered in a soundproof booth followed by a direct connect psychoacoustic battery using the EC program. Tests were repeated 1 month later using the optimized FOX program. Subjective measures of patient satisfaction were also measured. RESULTS Performance for the EC program was compared to the FOX program for both measures. Group mean results revealed equivalent performance (Kruskal-Wallis ANOVA p = 0.934) with both programming methods. While some patients had better performance with the FOX method and some performed more poorly, the majority had equivalent performance and preferred the FOX system. CONCLUSION The study demonstrated that on average, FOX outcomes are equivalent to those using traditional programming techniques. In addition, the FOX programming method can effect standardization across centers and increase access for many individuals who could benefit.

Based on multi-objective programming method, this paper reviews the previous research on the problem of government guarantees in the project financing, and puts forward the importance of the research on project selection of government guarantee in Build-Operate-Transfer (BOT) or Public Private Partnership (PPP) project finance. Through the analysis of the selection criteria of guarantee project, we find that the selection problem of government guarantee of BOT/PPP infrastructure projects is essentially a multi-objective decision problem. Moreover, we establish a chance-constrained objective programming model for the government to make the decision to guarantee project selection.

Over the last half-century, continuous development in all fields of science and technology has changed society’s aspirations in several respects. Computers have proved to be the most daunting and revolutionary in many respects, since they are rooted in a design and abstraction tradition that is radically different from biology. In recent decades, computational biology has grown in importance as a field of research in biological sciences. Computational biology sheds new light on critical research methods and how to apply them to overcome nature’s problems. Bioinformatics is the basis for the biology of structures. The application of computing and information technology to solve biological problems is likely to play an important role in the 21st-century, similar to the role played by molecular biology in biological science. In general over the last quarter-century, computing and information technology has become increasingly integrated into biological research. Since then, computer methods and tools have been used in a wide range of biological studies.

Learning computer programming is a good way to develop Computational Thinking, but many students assumed that computer programming is a complicated subject, which leads toward their disinterest in computer science. We believe that this assumption can be overcome if the students were introduced to the concept of programming earlier during preschool years. The best programming method for children to learn programming is the tangible programming method but current Malaysian preschool syllabus does not contain a framework for preschoolers to learn tangible programming. This paper introduces the developmentally-appropriate Learn Programming Framework (LPF) for preschoolers to learn programming concepts. The structured syllabus in LPF involves a series of controlled-play activities to be used with the novel tangible board game. Once the framework has been successfully implemented, extensive evaluation of LPF will be done to test its effectiveness in teaching children about programming

One of the most common diseases among women is breast cancer, the early diagnosis of which is of paramount importance. Given the time-consuming nature of the diagnosis process of the disease, using new methods such as computer science is extremely important for early detection of the condition. Today, the main emphasis is on the science of data mining as one of the computer methods in the field of diagnosis. In the present study, we used data mining as a combination of feature selection method by Gray Wolf Optimization (GWO) and support vector machine (SVM), which is a new technique with high accuracy compared to other methods in this classification, to increase the accuracy of breast cancer diagnosis. The UCI dataset and functional parameters and various statistical criteria were applied to evaluate the proposed method and assess the validity of the results in MATLAB, respectively. Application of the proposed method increased the improvement of the evaluated criteria, which increased the accuracy of diagnosis by 27.68%, compared to former works in the field. As such, it could be concluded that the proposed method had a higher ability to diagnose breast cancer, compared to previous techniques.

Miglioramento della percezione del parlato in condizioni di silenzio e rumore mediante il metodo FAP (Frequency-Allocation Programming) personalizzato.L’obiettivo di questo studio è la valutazione della discriminazione verbale da parte di soggetti esperti portatori di impianto cocleare con impostazioni MAP standard, utilizzando le tabelle predefinite di allocazione di frequenza con un MAP di frequenza ottimizzato. Questo è uno studio osservazionale, trasversale e quantitativo su 50 adulti con impianto cocleare, 20 bilaterali e 30 monolaterali. 23 maschi (46%) e 27 femmine (54%). Tutti i soggetti erano maggiorenni. Le differenze tra i valori medi di soglia nell’audiometria tonale in campo libero sono risultati statisticamente significativi nei pazienti impiantati sia monolateralmente che bilateralmente; risultati simili sono stati ottenuti nei test bisillabici nei pazienti impiantati sia monolateralmente che bilateralmente (p0,005). I pazienti che hanno utilizzato il metodo di allocazione di frequenza, che assegna le frequenze sulla base di quelle fondamentali, hanno mostrato una percezione delle parole bisillabiche e delle frasi libere in quiete e nel rumore migliore rispetto ai pazienti con dispositivo precedentemente regolato con tecniche standard. Il metodo può essere applicato a diversi processori e utilizzato con differenti strategie di stimolazione. Permette la riduzione degli attuali livelli di intensità così come un aumento del range dinamico e migliora la qualità della rappresentazione del segnale.The objective of this study is the evaluation of speech recognition of experienced CI recipients with standard MAP settings using the default frequency-allocation tables with the optimised frequency-allocation MAP. This is an observational, cross-sectional and quantitative-approach study on 50 adult cochlear implant recipients, 20 bilateral and 30 unilateral implant recipients. 23 men (46%) and 27 women (54%). All subjects were ≥ 18 years old. Differences between the means of the thresholds in tone audiometry in free fields were statistically significant in both unilaterally and bilaterally implanted patients; similar results were obtained between average benefits in disyllabic for both unilaterally and bilaterally implanted patients (p0.005). The differences between the means of scores were statistically significant for unilaterally and bilaterally implanted patients, similarly occurred with the average in HINT test between standard SRT50% programming and frequency allocation fitting (p0.005). Patients using the frequency allocation method, which assigns frequencies based on fundamental frequencies, showed better perception of disyllabic words and open-set sentences in quiet and in noise than patients previously fitted with standard fitting techniques. The method can be applied to different processors and used with different strategies of stimulation. It allows reduction of current intensity levels as well as an increase in the dynamic range and improves the quality of the representation of the signal.

This paper presents a method to couple FEM meshes with ordinary state-based peridynamic grids. It generates a computational tool that is as efficient as computer methods based on classical continuu...

X-ray computer methods of research (projection microfocus radiography and microtomography), which are used to study the problem of hidden defects of seeds and investigate its impact on sowing quality, have been considered. The description and main characteristics of technical means that were used to obtain digital two-dimensional and three-dimensional (tomographic) X-ray images of seeds have been given and the possible ways of their quantitative computer processing and analysis have been discussed. Conclusions about the abilities of the methods of projection microfocus radiography and microtomography to study the features of the internal structures of a seed that are related to the violation of its integrity have been formulated.

The work presents the results of preliminary strength design of a thin-walled structure based on double-tee section loaded with a torsion moment. One of the solutions to this problem is considered, in which the torsional box is introduced in the central part. Then, one constructs a series of solution variants that differ in the torsional box length. In the design one uses the method of statically admissible discontinuous stress fields (SADSF) assuming the condition of equalized equivalent stress in the limit state. The work is complemented with elastic FEM analyses of one of the solution variants. Using this example, one shows good load-carrying properties of structures designed with the SADSF method, and proves that they could be several times better than the properties of structures designed with traditional or intuitive ways.

The authors developed and tested diagnostic instruments (a computer testing system) aimed at the identification of prospective teachers’ readiness for continuous professional self-development by the following criteria: the awareness of necessity for purposeful continuous professional self-development; the level of acquired professional knowledge, integrative and theoretical training; the formation of abilities and practical skills for professional self-development; practical training; a set of individual and psychological qualities important for continuous professional self-development and future professional activity in general; the focus on self-analysis, self-assessment of professional self-development. The developed survey “Diagnostics of Readiness for Professional Self-development” includes original parts of questionnaires and tests, which were creatively redesigned and adapted according to the research. Among them: “Dispositive Characteristic of Self-development of Personality”, “Diagnostics of Success Motivation”, “Diagnostics of Self-development Needs”, “Motivation of Professional Activity”, Cattell’s 16 PF-questionnaire, and others. For the purpose of implementing the authors’ concept, the technology of prospective teachers’ training for continuous professional self-development is developed. This technology is considered to be a system of contents, principles, methods, forms, substantiated organizational and pedagogical conditions that provides implementation of the authors’ concept and guarantees achievement of the planned results – increasing the level of prospective teachers’ readiness for continuous professional self-development. After the implementation of the technology, the computer diagnostics was applied again. The results of the final diagnostics showed the effectiveness of the training technology of the prospective teacher for continuous professional self-development and the computer method “Diagnostics of Readiness for Professional Self-development”.

Recently, interest in Investigator Initiated Trials (IIT)/Investigator Initiated Studies (IIS) in pharmaceuticals and medicine has increased. The relevance of such trials is due, on the one hand, to increased knowledge of diseases pathogenesis, potential targets for drug exposure, and on the other, the development of technologies, primarily the Internet and computer methods that create opportunities for organizing collaboration, the collection and processing of information. Almost all participants in the process of creating new drugs and treatments – pharmaceutical companies, regulatory authorities, associations of doctors and patients – have realized the importance of supporting IIT and developed mechanisms for this. The purpose of this article is to review new trends in IIT in the world and the possibilities for conducting them in Russia, and also exchange of experience in the development, approval and implementation of international IIT in our country.

Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people’s life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are compared against each other and output results confirm superiority and effective performance of the robust fuzzy model in the water allocation problem. Also, output results of the extended model show its accurate performance that results in applicability of the model as a strong planning tool in real world cases.

Drug resistance of pathogenic bacteria has become increasingly serious due to the abuse of antibiotics in recent years. Researchers have found that cell wall lyases are effective antibacterial agents that can specifically recognize target bacteria and degrade bacterial peptidoglycan. Traditional wet experiments are usually expensive, time-consuming and laborious for the identification of lyases. Therefore, there is an urgent need to develop prediction tools based on computer methods to identify lyases quickly and accurately. In this paper, a new predictor, CWLy-RF, is proposed based on the random forest (RF) algorithm to identify cell wall lyases. In this method, we combined three features, namely, 400D, 188D and the composition of k-spaced amino acid group pairs, using mixed-feature representation methods. Afterward, we improved the feature representation ability with the selected top 100 features by using the information gain method and trained a predictive model using RF. The constructed prediction model is evaluated by using 10-fold cross-validation. The accuracy obtained was 96.09%, the AUC was 0.993, the MCC was 0.922, the sensitivity was 94.92%, and the specificity was 97.32%. We have proved that the proposed predictor CWLy-RF is superior to other latest models, and it will hopefully become an effective and useful tool for identifying lyases.

Welcome to this Special Issue of Taylor & Francis’s Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualisation (TCIV) journal dedicated to the 2021 joint edition of the Au...

The paper takes the realization process of an artificial intelligence speech recognition system that can recognize numbers 0-9 as an example, and elaborates the basic principles and key technologies of isolated words speech recognition for specific people based on DTW big data algorithm. It includes a detailed discussion on the voice endpoint detection method, the characteristic parameter calculation method and the realization of the DTW big data algorithm. Finally, the programming method and experimental results under MATLAB are given.

In the neurobiological mechanism of Parkinson’s Disease (PD), a certain part of the brain called the Subthalamic Nucleus (STN) becomes overactive. This pathologically increased activity inhibits other regions of the brain, causing many symptoms observed in PD patients. The hyperactivity of the STN can be lowered using a special electrical stimulating electrode. In the neurosurgical treatment of Parkinson’s Disease (PD), the goal is the precise placement of such electrode within the Subthalamic Nucleus. As STN does not significantly differ from adjacent structures on images provided by the CT or MRI, these standard techniques of medical imaging can provide only the approximate localization of the STN. The final localization of the STN has to be pinpointed during surgery. For this, typically, three to five very thin electrodes are inserted into the patient’s brain and advanced towards the expected STN location given by CT and MRI. Electrodes in measured steps approach, traverse, and exit out of the STN. At each step, the neurobiological activity of brain tissue surrounding the leads of the electrodes is recorded. By careful analysis of recordings provided by these electrodes, it is possible to discriminate which recordings were recorded within the STN. This, in turn, gives the extent of the STN in the 3D space on trajectories of the recording electrodes.

A distance sensor system was used as wireless danger signal detector system controlled by Arduino programming that was detected any potential danger coming in target range. The system operated by sending signals based on the sensor reading. The purpose of the safety system was to increase the safety procedure and precaution for maintenance workers that currently doing their job at the emergency lane of the highway. In certain range of radar sensor detection, when the potential danger or accident was detected to approach, the sensor send the signal to the system and carried out the duty as medium of sending alarm caution in three ways, which were through sound, vibration and visual.

This paper presents the Meta-Collaborative Workstation concept and a gesture-based robot program builder software named MEGURU. The software is ROS-based, and it is publicly available on GitHub. A hand-gestures language has been developed to create a fast and easy to use communication method, where single-hand gestures are combined to create composed Commands, allowing the user to create a customized, powerful, and flexible Gestures Dictionary. Gestures are recognized using an R-FCN Object Detector model fine-tuned on a custom dataset developed for this work. The system has been tested in two experiments. The first one was aimed at evaluating the user experience of people of different age, sex, and professional background concerning the proposed communication method. The second one was aimed at comparing the traditional teach pendant programming method and MEGURU in the task of assembling a small Moka coffee maker. The results of both experiments highlight that MEGURU is a promising robot programming method, especially for non-expert users.

Now experimental investigations based on the methods of natural sciences allows us to register the dynamics of processes in biological systems. The results may be represented by various ways, in particular as digital images or signals. The application of mathematical and computer methods of image analysis opens up possibilities to obtain numerical data that characterize real processes and helps to estimate the biological system state, which is important in medical practice. We apply image analysis to study changes in a biological system state. Our experiments on some classes of biomedical preparations including ones obtained by sensitive crystallization and capillary dynamolysis methods resulted in obtaining numerical characteristics which allows us to distinct images from different classes,( such as acute and chronic inflammatory processes, benign and malignant tumors, etc.) and may be considered as classifying signs.

Chemists have to a large extent gained their knowledge by doing experiments and thus gather data. By putting various data together and then analyzing them, chemists have fostered their understanding of chemistry. Since the 1960s, computer methods have been developed to perform this process from data to information to knowledge. Simultaneously, methods were developed for assisting chemists in solving their fundamental questions such as the prediction of chemical, physical, or biological properties, the design of organic syntheses, and the elucidation of the structure of molecules. This eventually led to a discipline of its own: chemoinformatics. Chemoinformatics has found important applications in the fields of drug discovery, analytical chemistry, organic chemistry, agrichemical research, food science, regulatory science, material science, and process control. From its inception, chemoinformatics has utilized methods from artificial intelligence, an approach that has recently gained more momentum., Artificial Intelligence (AI) methods learn from data and thus find an ideal application field in chemistry. AI can thereby build on 60 years of developments in chemoinformatics on computer methods for the representation and analysis of chemical information such as database management, property prediction, synthesis design, and structure analysis.

To cut automotive upholsteries by using a robot, it is needed to compose a user program which is required to teach the robot in order to complete the task. For the purpose of studying the programming method, the water-cutting KUKA robot to cut automotive upholsteries used in Brilliance Jinbei is used as the research object. This paper probes into the problems and influencing factors to be considered in the overall design of program structure and the programming of main program and sub-program, and a good deal of work need to be carried out and solved on the spot according to objective conditions after the completion of main program and sub-program, which is program debugging. The research conclusion on robot programming method is of great significance to an enterprise's process optimization and trial-manufacture of new products.

BackgroundRespiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate of characteristic sound changes caused by COVID-19 and can be used for diagnosis of this illness.PurposeThe communication aim is development of fast remote computer-assistance diagnosis of COVID-19, based on analysis of respiratory sounds.Materials and MethodsFast Fourier transform (FFT) was applied for analyses of respiratory sounds recorded near the mouth of 9 COVID-19 patients and 4 healthy volunteers. Sampling rate was 48 kHz.ResultsComparing of FFT spectrums of the respiratory sounds of the patients and volunteers we proposed numerical healthy-ill criterions.ConclusionsThe proposed computer method, based on analysis of the FFT spectrums of respiratory sounds of the patients and volunteers, allows one to automatically diagnose COVID-19 with sufficiently high diagnostic values. This method can be applied at development of noninvasive self-testing kits for COVID-19.

1. Bone Structures, Implants and Validation Methods 2. Bone Re-modelling and Damage Mechanics 3. Soft Tissue Analysis and Respiratory Models 4. Musculoskeletal Models, Ligament Analysis and Human Body Impact 5. Image Analysis, Surgical Simulation and Clinical Applications of Modelling 6. Generic Techniques and Tissue Identification 7. Dental Implants, Materials and Orthodontic/Mandibular Mechanics 8. Cardiovascular and Biofluid Mechanics

Introduction Deep brain stimulation (DBS) is an established treatment for Parkinson's disease (PD). Clinicians face various challenges in adjusting stimulation parameters and configurations in clinical DBS settings owing to inexperience, time constraints, and recent advances in DBS technology that have expanded the number of possible contact configurations. We aimed to assess the efficacy of a closed-loop algorithm (CLA) for the DBS-programming method using external motion sensor-based motor assessments in patients with PD. Methods In this randomized, double-blind, crossover study, we enrolled 12 patients who underwent eight-ring-contact DBS lead implantations bilaterally in the subthalamic nucleus. The DBS settings of the participants were programmed using a standard of care (SOC) and CLA method. The clinical effects of both programming methods were assessed in a randomized crossover fashion. The outcomes were evaluated using the Unified Parkinson's Disease Scale part III (UPDRS-III) and sensor-based scores for baseline (medication-off/stimulation-off) and both programming methods. The number of programming steps required for each programming method was also recorded. Results The UPDRS-III scores and sensor-based scores were significantly improved by SOC and CLA settings compared to the baseline. No statistical difference was observed between SOC and CLA. The programming steps were significantly reduced in the CLA settings compared to those in the SOC. No serious adverse events were observed. Conclusion CLA can optimize DBS settings prospectively with similar therapeutic benefits as that of the SOC and reduce the number of programming steps. Automated optimization of DBS settings would reduce the burden of programming for both clinicians and patients.

Aim: Our purpose with this study is to determine the most effective and suitable cochlear implant programming method for CI users’ implants to experience quality hearing and for the users to achieve efficiency from their implants. Materials and Methods:Twenty-five cochlear implant users with post lingual progressive hearing loss were included in the study. Twelve electrodes’ ART (auditory nerve response telemetry) thresholds were determined and were statistically analyzed to be evaluated in the study. For 12 electrodes whose AutoART threshold was determined, the MCLs (most comfortable loudness) were determined behaviorally. Results: No correlations were found between the 12 electrodes and AutoART. It was seen that there was a correlation between the pure tone average obtained from 500-1000-2000 and 4000Hz and the speech reception threshold. Conclusion: The use of two test batteries together to determine thresholds can be helpful in the programming of the speech processor. The more audiologists work with cochlear implant patients and do programming, the more they accumulate data and gain occupational experience. With the occupational experience acquired in this manner, more accurate programming can be done.

In Viticulture, visual inspection of the plant is a necessary task for measuring relevant variables. In many cases, these visual inspections are susceptible to automation through computer vision methods. Bud detection is one such visual task, central for the measurement of important variables such as: measurement of bud sunlight exposure, autonomous pruning, bud counting, type-of-bud classification, bud geometric characterization, internode length, bud area, and bud development stage, among others. This paper presents a computer method for grapevine bud detection based on a Fully Convolutional Networks MobileNet architecture (FCN-MN). To validate its performance, this architecture was compared in the detection task with a strong method for bud detection, Scanning Windows (SW) based on a patch classifier, showing improvements over three aspects of detection: segmentation, correspondence identification and localization. The best version of FCN-MN showed a detection F1-measure of $88.6\%$ (for true positives defined as detected components whose intersection-over-union with the true bud is above $0.5$), and false positives that are small and near the true bud. Splits -- false positives overlapping the true bud -- showed a mean segmentation precision of $89.3\% (21.7)$, while false alarms -- false positives not overlapping the true bud -- showed a mean pixel area of only $8\%$ the area of a true bud, and a distance (between mass centers) of $1.1$ true bud diameters. The paper concludes by discussing how these results for FCN-MN would produce sufficiently accurate measurements of bud variables such as bud number, bud area, and internode length, suggesting a good performance in a practical setup., Comment: Revised version submitted to Journal of Computers and Electronics in Agriculture November 13, 2020

International audience; 3D reconstruction from low-dose Bi-Planar X-Rays (BPXR) is a rising practice in clinical routine.However, this process is time consuming and highly depends on the user. This study aims topartially automate the process for the femur, thus decreasing reconstruction time and increasingrobustness. As a training set, 50 femurs are segmented from CT scans together with 120 BPXRreconstructions. From this dataset, an initial solution for the bony contours is defined throughGaussian Process Regression (GPR), using eight digitized landmarks. This initial solution is projectedon both x-rays and automatically adjusted using an adapted Minimal Path Algorithm (MPA). Toevaluate this method, CT-scans were acquired from 20 cadaveric femurs. For each sample, the CTbasedreconstruction is compared to the one automatically generated from the digitally reconstructedradiographs. Euclidean distances between femur reconstructions and the segmented CTdata are on average 1.0 mm with a Root Mean Square Error (RMSE) of 0.8 mm. Femoral torsionerrors are assessed: the bias is lower than 0.1° with a 95% confidence interval of 4.8°. The proposedmethod substantially improves 3D reconstructions from BPXR, as it enables a fast and reliablereconstruction, without the need for manual adjustments, which is essential in clinical routine.

There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detection frameworks applied to this problem. DFUC2020 provided participants with a comprehensive dataset consisting of 2,000 images for training and 2,000 images for testing. This paper summarises the results of DFUC2020 by comparing the deep learning-based algorithms proposed by the winning teams: Faster R-CNN, three variants of Faster R-CNN and an ensemble method; YOLOv3; YOLOv5; EfficientDet; and a new Cascade Attention Network. For each deep learning method, we provide a detailed description of model architecture, parameter settings for training and additional stages including pre-processing, data augmentation and post-processing. We provide a comprehensive evaluation for each method. All the methods required a data augmentation stage to increase the number of images available for training and a post-processing stage to remove false positives. The best performance was obtained from Deformable Convolution, a variant of Faster R-CNN, with a mean average precision (mAP) of 0.6940 and an F1-Score of 0.7434. Finally, we demonstrate that the ensemble method based on different deep learning methods can enhanced the F1-Score but not the mAP., Comment: 19 pages, 18 figures, 10 tables

Microfluidic technology is a versatile approach to improve the production of various fine chemicals and materials, where precise and fast size measurement of microdroplets in microscopic images is of pivotal significance for microfluidic device design. With recent developments in convolutional neural networks, we herein proposed a state-of-the-art deep learning-based method to cope with microdroplet size measurement and largely ease manual workload. The proposed method instance-wisely segments microdroplets with deep learning, and then fits their boundaries to obtain precise size distribution curves. Even overlapped droplets and small-sized satellite droplets can be detected and measured, which is not achievable in previous computer methods. Incredibly, diameter measurement error is as small as 0.75 μm, and the measurement efficiency is increased ~ 1000 times compared to manual measuring. This work not only sheds light on intellectual size measurement of microdroplets, but also points out a new way to promote microfluidic technology through deep learning methods.

A clinical and functional examination of the maxillofacial area was performed in 280 patients with the defects of the lateral teeth being replaced with ceramic crown inlays or light-cured composites three years ago. Computer methods were used to assess the articulation, occlusion and tone of the masticatory muscles on the T-Scan III and Bio EMG III devices. In a third of the lateral teeth, an unreasonable increase in indications to composite fillings has been established – when more than 50.0% of the occlusal surface is destroyed. Indicators of dental status are significantly better when using ceram- ic inlays compared with fillings made of composite material in the long term after treatment of multiple caries. Ceramic crown inlays prevent occlusal-articulatory disorders and dysfunction of the masticatory apparatus, characteristic in long-term periods for patients with multiple caries when replacement of lateral teeth defects with fillings made of composite.

At the present time in the research of particulate materials, computer methods that work independently with individual particles are coming to the forefront. One such method is the Discrete Element Method – DEM, which is already widely used. Its usage, however, is complex, mostly due to the input data – what the properties of the researched material are, plus their interaction in processes. And despite the progress, it is still always necessary to validate the experimental equipment and to verify the individual simulations by an experimental measuring or by theoretical knowledge. This study focuses on the verification of the simulation of the mixing of a particulate material with the help of the DEM method, whereby simulations are compared with an experimental measurement and theoretic calculations. The theoretical calculation was carried out by the Novosad model, while the experimental material was granulated polyethylene with strictly defined mechanical-physical properties.

To reduce water conservancy projects’ negative effects on the ecological environment, in this paper, a method is proposed to assess the impact of hydropower stations on the environment in the processes of the flood discharge and energy dissipation. It utilizes the hesitant fuzzy linguistic information to describe the problem's uncertainty and fuzziness, portrays decision maker's satisfaction degree with the increasing marginal utility, and applies the hyperplane to establish a mathematical programming model. Then, the undetermined parameter in the model is discussed, and a decision-making procedure for solving the considered problem is provided. Furthermore, an experiment is designed to verify the availability and reasonability of the proposed method by comparing it with an existing one. Finally, the method is applied to assess the impact of giant hydropower stations’ flood discharge and energy dissipation on the environment in Sichuan, China.

The numbers of detected ions and the beam density dispersions at different depths of plate locations that also cover the Bragg peak region were determined by automatically searching for etched micropores in photographs of surfaces of CR-39 plastic plates exposed to 12C ions with an energy of 216 MeV/amu in a chamber for radiobiological investigations at the TWAC–ITEP accelerator–accumulator facility. A computer method for seeking etched micropores along latent ion tracks in an exposed plastic is described. Frequency distributions of detected ions over microscopic areas of each surface for eight plates have been obtained and compared using a Gaussian function.