Excessive Intensity Research Articles

Effect of scavenge port angles on flow distribution and performance of swirl-loop scavenging in 2-stroke aircraft diesel engine

Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles αgeom and βgeom. For reinforcement of scavenging on cross-sections and meridian planes, αgeom value of 27° and βgeom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent.

Mechanism of magnetic field condition on deformation behavior of sheet metal using a property-adjustable flexible-die

To provide intelligent control options during sheet metal forming process, magnetorheological (MR) fluid has been applied as a property-adjustable flexible-die. However, the mechanism of the magnetic field effect on the sheet deformation behavior is not clear yet. In this paper, to clarify the deformation mechanism, the bulging behavior of thin-walled Al1060-O sheet was systematically investigated through experiment and numerical simulation. Special attention was paid to the effect of magnetic field on loading curve, bulge dome height, and thickness strain distribution. Results showed that the maximum bulging force increased obviously with the increase of magnetic flux density. The bulge dome height and thickness strain were influenced by magnetic field condition and magnetic particle content synthetically. Appropriate magnetic field condition and magnetic particle content can improve formability. However, excessive magnetic flux intensity and magnetic particle volume fraction, for example, B = 0.20 T and φ = 46%, would lead to premature rupture. Finite element analysis was adopted to assist in explaining the bulging behavior. Detailed analysis indicated that the flow stress variations caused by magnetic field affect the stress states, velocity distribution of MR fluid, and sheet/MR fluid contact condition, further leading to different stress and strain distribution of sheet metal. Finally it causes the great difference in specimen geometry and wall thickness distribution.

System relations between word-building types of verbs with the meaning of negative consequences of action

The article is devoted to the description of the system relations between word-building types corresponding to the aktionsart with the meaning of negative consequences of action. This is a group of prefixal and confixal verbs where the negative effects of an action are caused by excessive intensity or duration of action. The study of aktionsart with the meaning of negative consequences of action is of great interest first of all for they express the complex of aspectual meanings and it is essential to identify what creates such a complex semantics. Secondly, the semantics of negative consequences itself should be specified. Multiplicity of the mentioned aktionsarts confirms that semantics of negative consequences of action is relevant for the Russian language and for the whole Russian linguistic worldview. It is noteworthy to determine possible system relations arising between the verbs of the mentioned aktionsarts. The purpose of the article is to identify possible system relations arising between verbs of the specified manners of action. While the study methods of observation, description, functional and semantic analysis, component analysis were used. As a material for the study, examples from works by Russian writers selected from the Russian National Corpus (S.A. Alexievich. V.P. Astafyev, V.V. Bykov. F.M. Dostoyevsky, A.I. Kuprin, O.A. Slavnikova, V.I. Shukshin) were used. The conducted research elicited possible relations of word-building synonymy between different word-building types when identical word-building meanings are expressed by derivatives with different affixes and with a common derivative base. This type of word-formative synonymy is revealed in the framework of total aktionsart (with prefixes iz- and vy-) and excessive-multiple aktionsart (with confixes iz-...-sya and vy-...-sya). Amid the various word-formative types with the same prefix the relationships of enantiosemy (verbs with the prefixes ob-, za-, na-) were revealed as well. Opposite meanings of increase and diminution of action intensity arise in case the prefix is combined with different groups of motivating verbs. The reasons of this phenomenon are established.

Empathy, Alexithymia, and Theory of Mind in Borderline Personality Disorder.

The purpose of this research was to determine the differences in empathy, alexithymia features, and theory of mind between healthy controls and patients with borderline personality disorder (BPD). Thirty-five patients with BPD and 35 healthy controls were included in the study. To measure the clinical variables, the Empathy Quotient (EQ), Reading the Mind in the Eyes Test (RMET), Toronto Alexithymia Scale (TAS-20), Barratt Impulsivity Scale-11 (BIS-11), and Beck Depression Inventory (BDI) were applied. We found that the BPD group had significantly worse total RMET and neutral RMET scores than the control group. There were no differences in the EQ scores between the BPD and control groups. The patients with BPD were more alexithymic than the controls, and alexithymia and depression scores predicted BPD status. Patients with BPD who have difficulty identifying their own emotions tend to display deficits in perceptions of facial emotions, which, in turn, may lead to misperceptions of social signals and thus contribute to excessive emotional intensity and tension in social situations. The study results reveal that alexithymia and depression are important variables in predicting BPD traits.

Diffuse excessive high signal intensity on term equivalent MRI does not predict disability: a systematic review and meta-analysis

ObjectiveTo evaluate whether diffuse excessive high signal intensity (DEHSI) on term equivalent age MRI (TEA-MRI) predicts disability in preterm infants.DesignThis is a systematic review and meta-analysis. Medline, EMBASE, Cochrane Library,...

Objectively Diagnosed Diffuse White Matter Abnormality at Term Is an Independent Predictor of Cognitive and Language Outcomes in Infants Born Very Preterm

To externally validate the independent value of objectively diagnosed diffuse white matter abnormality (DWMA; also known as diffuse excessive high signal intensity) volume to predict neurodevelopmental outcomes in very preterm infants (≤31weeks of gestational age). A prospective, multicenter, regional population-based cohort study in 98 very preterm infants without severe brain injury on magnetic resonance imaging (MRI). DWMA volume was diagnosed objectively on structural MRI at term-equivalent age using our published algorithm. Multivariable linear regression was used to assess the value of DWMA volume to predict cognitive and language scores on the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) at 2years corrected age. Of the infants who returned for follow-up (n=74), the mean (SD) gestational age was 28.2 (2.4) weeks, and 42 (56.8%) were boys. In bivariable analyses, DWMA volume was a significant predictor of Bayley-III cognitive and language scores. In multivariable analyses, controlling for known predictors of Bayley-III scores (ie, socioeconomic status, gestational age, sex, and global brain abnormality score), DWMA volume remained a significant predictor of cognitive (P<.001) and language (P=.04) scores at 2years. When dichotomized, objectively diagnosed severe DWMA was a significant predictor of cognitive and language impairments, whereas visual qualitative diagnosis of DWMA was a poor predictor. In this multicenter, prospective cohort study, we externally validated our previous findings that objectively diagnosed DWMA is an independent predictor of cognitive and language development in very preterm infants. We also demonstrated again that visually-diagnosed DWMA is not predictive of neurodevelopmental outcomes.

Development of primary school students’ speech-cognitive activity through visual modeling at literacy classes

This paper deals with the urgent problem of primary school students speech-cognitive activity development through an active inclusion of various types of visual modeling in the educational process at literacy classes. Today, the number of children in Russia who are not ready for systematic education exceeds 32%. The researchers consider that excessive intensity of the educational process and the mismatch of technologies and techniques used in teaching to their age and functional capabilities are among the factors negatively affecting the neuropsychic health of primary school students. There are also various deviations and health problems that impede speech skills development by traditional methods. Analyzing the data of the Ministry of Health of the Russian Federation and the Federal State Autonomous Institution National Health Medical Research Center for Children on the health status of children aged 6 to 8, school practice as well as scientific and methodological literature on the research topic, the author comes to the conclusion that it is possible and necessary to use a method of visual modeling working with children studying by correctional programs as well as by basic ones, implementing a differentiated approach to learning.

Antecedents of Objectively Diagnosed Diffuse White Matter Abnormality in Very Preterm Infants

BackgroundDiffuse white matter abnormality (diffuse excessive high signal intensity) is the most common finding on structural brain magnetic resonance imaging (MRI) at term-equivalent age in very preterm infants. Yet, there remains a large gap in our understanding of the etiology of diffuse white matter abnormality. Our objective was to evaluate perinatal and neonatal inflammation-associated antecedents of diffuse white matter abnormality on MRI. MethodsWe prospectively enrolled 110 very preterm infants born at ≤31 weeks gestational age and collected data on multiple perinatal/neonatal exposures, especially inflammation initiating-illnesses. We performed structural MRI at term-equivalent age and quantified the volume of diffuse white matter abnormality objectively. Multivariable regression was used to identify clinical antecedents of diffuse white matter abnormality. ResultsThe mean (S.D.) birth gestational age of the final study sample of 98 very preterm infants was 28.3 (2.5) weeks. Multiple inflammation initiating-illnesses were associated with diffuse white matter abnormality in univariate analyses. In multivariable linear regression analyses controlling for gestational age, severe retinopathy of prematurity (P < 0.001) and bronchopulmonary dysplasia (P = 0.006) were independent risk factors, whereas maternal treatment with 17-hydroxyprogesterone (P < 0.001) was protective of later development of objectively quantified diffuse white matter abnormality. ConclusionsWe identified several perinatal and neonatal antecedent clinical factors associated with diffuse white matter abnormality. Although we found some support for inflammation as a common underlying mechanism, larger studies are needed to validate inflammation as a potential common pathway to the development of diffuse white matter abnormality in very preterm infants.

Overcoming the barriers to the implementation of more efficient productive strategies in small enterprises

PurposeThe purpose of this paper is to elaborate an empirical model of how small, family-owned companies can overcome the barriers that have been shown in different disciplines to hinder the implementation of lean production in this category of enterprises.Design/methodology/approachA multiple case study involving five carefully selected small manufacturing firms operating in Northern Italy was conducted through interviews with key managers and visits inside plants. This data was integrated by a specific seminar and by interviews with unions and training specialists.FindingsThe resulting empirical model highlights the significance of social relations among small entrepreneurs in overcoming any lack of commitment towards lean changes, the role of consultants and practical training in breaking the barrier of resource constraints and the channelling and control of employee involvement to encourage their participation in lean activities. Unions, when present, also play a role in preventing situations of excessive work intensity. Important variants within this common model also emerged among small firms on the grounds of their structure (e.g. size), product market conditions and managerial choices.Practical implicationsKnowledge on how to overcome the barriers to lean production implementation can help social actors both inside and outside of differently characterised small firms which are implementing, or intending to implement, the lean approach.Originality/valueThere is no existing literature on the subject of successful application of lean methods in small enterprises. The uniqueness of this paper’s contribution is reinforced by its broad analytical perspective on the lean system, stemming from an interdisciplinary analysis of different bodies of literature, including management, operations, human resources and employment relations in line with the definition of the lean system.

Biotechnological Assessment of Culture Conditions on the Stress-Induced Carotenoid Production of Dunaliella salina and Growth Kinetics of Chlorophyceae Microalgae Strains

Microalgae are potential sources of a wide range of bioproducts. It is essential to choose the proper microalgae strain and culture condition to achieve an efficient production. The production yield of carotenoids by Dunaliella salina under the stress-induced culture conditions of nitrogen deprivation and excessive light intensity was evaluated. Also, a survey at laboratorial scale of the growth kinetics under different culture conditions of photoperiod, aeration, and agitation was performed for the seven species of green microalgae Ankistrodesmus fusiformis, Chlamydocapsa bacillus, Desmodesmus brasiliensis, Kirchneriella lunaris, Pseudokirchneriella subcapitata, and Scenedesmus obliquus. As a result, aeration of atmospheric air is enough to improve the growth kinetics of the seven species studied. Production of carotenoids was enhanced under stress by excessive light intensity. Although D. salina does not grow effectively under nitrogen deprivation, this stress condition may be used to quickly stimulate carotenoid production once the culture reaches a high cellular population.

The effects of seasons on chrysanthemum flower (Chrysanthemum indicum) production in Sleman Regency, Yogyakarta, Indonesia

Chrysanthemum is a type of cut-flower that has commercial value and popular in Indonesia. Economically, Chrysanthemum has the potential for the export commodities and expected to increase in the future. One fruitfulness factor of Chrysanthemum cultivation is determined by season. The risk factors of Chrysanthemum production need to be studied, particularly season factor. This research aims to find out the optimum season for Chrysanthemum production and how to anticipate the impacts of climate change or seasonal factors on Chrysanthemum flower production and to discover the main factors of Chrysanthemum production. The research was carried out in Sleman Regency. The analytical method used was the Cobb-Douglas production function model. The results show that seasons affected Chrysanthemum flower production. The highest Chrysanthemum production occurred in the dry season. It is better for the farmer to cultivate Chrysanthemum in the dry season to reduce the risk of production. Protection houses are needed to protect plants from excessive heat intensity and strong winds during the rainy season as the impacts of climate change.

Exercise Fatigue Detection Algorithm Based on Video Image Information Extraction

Excessive psychological pressure, long working hours, and excessive labor intensity can make people exhausted and affect people's cognition and motor function. Detecting the fatigue state of athletes can prevent excessive fatigue and sports injuries. This article chooses the adaptive median filter method to smooth the image and remove the noise, and uses the adaptive threshold light equalization method to adjust the image's light equalization. According to the admission and rejection criteria of the Sequential Forward Floating Selection (SFFS) algorithm, different feature parameter combinations are used to build a fatigue motion detection model based on Support Vector Machine (SVM). Taking the classification performance of the built SVM detection model as the evaluation criterion, and using the sequence floating forward selection algorithm as the search strategy, the fatigue characteristic parameter optimization selection algorithm is established. The algorithm is used to reduce the dimensionality of the full set of fatigue feature parameters, and the optimal feature subset of fatigue motion is extracted. Based on the paired sample t-test and the analysis of variance method, it analyzes and quantifies the comprehensive influence of individual athlete differences and fatigue exercise on sports behavior and eye movement characteristics. An adaptive detection model is built based on personality parameters, and the design idea of the fatigue feature extraction network is analyzed. In order to make full use of the information of the feature vector output by the fully connected layer, the new network designs two fully connected layers to extract feature vectors. Two types are output by the Softmax loss function, which can directly determine whether the athlete is in a fatigue state. Based on the PERCLOS (Percentage of Eyelid Closure Over the Pupil over time) criterion, this article completes the construction of the fatigue motion sample set, and classifies the face images with more than 80% eyes closed as fatigue samples. This method can apply the PERCLOS criterion to the training of the convolutional neural network, so that it can recognize the fatigue state of the face based on the comprehensive facial features and improve the robustness of the algorithm.

Augustine on Loving Too Much

Abstract The article analyzes the friendship narratives contained in Books Two, Three and Four of Augustine’s Confessions, treating them not as biographical accounts, but as illustrations of Augustine’s philosophical ideas, namely, the fall of the soul and the role played in it by love. All those narratives seem to describe a homoerotic dimension of friendship. It is argued that making such homoerotic friendship, and not heterosexual love between man and woman, an allegory of the fall of the soul enables Augustine to show better the mechanism of the fall, namely, its excessive intensity and the fact that it perverts a naturally good relationship of the soul with the whole of creation.

The Prediction and Error Correction of Physiological Sign During Exercise Using Bayesian Combined Predictor and Naive Bayesian Classifier

Physiological signs monitored by wearable devices can reflect human body burden and exercise intensity. Due to the risk, avoidance of excessive intensity of exercise, energy-saving requirement, and other factors, it is of great necessity to predict physiological sign values for the monitoring of the human body during exercise. Most available works have used a single model for prediction of physiological signs which has a bad performance with a greater prediction error. In this light, we formalize a multistep prediction scheme for physiological signs during exercise using the Bayesian combined predictor and propose an error correction mechanism to correct the accumulated error generated in the prediction process using a naive Bayesian model. Finally, we evaluate the performance of the proposed scheme using actual monitored data of several exercisers. The simulation results show that our scheme outperforms all available schemes on the performance of prediction error.

Rheumatological Diseases and Sleep: Somnological Aspects of Diagnostics and Therapy

70 % of patients suffering from rheumatological diseases report poor sleep quality, numerous awakenings at night and non-restorative sleep. More than 20 % of these patients are found to have primary sleep disorders such as obstructive sleep apnoea (OSA) and the restless legs syndrome (RLS). Primary and secondary sleep disorders may increase symptoms associated with rheumatological diseases, e. g. excessive daytime sleepiness, fatigue, depression, pain intensity, and disease activity. Vice versa, pain intensity and inflammatory markers worsen sleep quality. In patients with rheumatic diseases, obesity as well as disease-related skeletal characteristics may be predisposing factors for obstructive sleep apnoea. The restless legs syndrome, which frequently occurs in rheumatological diseases, lowers sleep quality due to a sensory stimulus and periodic leg movements causing sleep fragmentation. Somnological diagnostic investigation consists of sleep-related questionnaires and scales. Objective tests are used to measure reaction time and vigilance. Sleep-related breathing and movement disorders can be identified with screening devices and polygrafic monitoring. A final polysomnografic sleep study is necessary to make the diagnosis and to initiate a specific treatment and follow-up examinations. Sleep disorders associated with rheumatological diseases may be treated with behavioural and drug therapies. Drug therapy is commonly used in the management of insomnia and RLS. Most cases of OSAS can be treated with CPAP or UPS devices. Interdisciplinary cooperation in the fields of somnology and rheumatology may improve treatment in RA patients.

Can cooperation drive the success of suppliers in B2B crowdsourcing innovation projects? A large scale data perspective

Crowdsourcing innovation projects (CIPs), that enterprises outsource the non-core projects to outside individuals or organizations for innovation, are critical forms for business to business (B2B) innovative service collaboration. Based on value network theory, this paper investigates whether cooperation is a critical influencer of supplier performance and examines how suppliers in CIPs can achieve and maximize value capturing under the customer value dominant condition. Large-scale data is collected from >110,000 CIPs suppliers from 2010 to August 2018 on Kaggle, one of the most well-known crowdsourcing platforms. According to econometric calculation results: 1) Suppliers' predominant capabilities and resources contribute to their workforce and financial performance improvement. 2) Excessive competition intensity has a negative impact on suppliers' performance. 3) The cooperation between suppliers is extremely important for their performance. More detailed, the accumulation of cooperation experience, the increase of partners and the heterogeneity of members in the organization have positive impact on suppliers' workforce and financial performance. The results demonstrate that for suppliers in the CIPs platform, cooperative is more optimal than competitive. The cooperation is more significant when the needs of customers are gaining more and more attention. Therefore, suppliers should explore a more flexible way of cooperation to achieve value capture. Subsequently the value balance between demanders and suppliers can be achieved.

Адаптаційні резерви у партнерських пологах

Studying the causes of excessive intensity of the influence of stress factors is an urgent task of modern medicine, therefore, the scientific substantiation of the technology of partner birth will optimize obstetric and perinatal consequences and improve the psychoemotional adaptation of the mother. The objective: to study the stress of the adaptive reserves of the body in partners with partner births. Materials and methods. Surveyed: Group I 30 mothers of women in childbirth who acted as partners in childbirth; ІІ group – 30 husbands of women in childbirth; 30 husbands who visited their wives who were in separate pathology of pregnancy for prenatal preparation in the period of pregnancy of 38–40 weeks, comprised the control group. A survey was conducted using the Teylor, Spіelberger scales and the San Test definition. Results. The described correlation relationships between the levels of tension of psychoemotional adaptive abilities in husbands and mothers of women in childbirth at partner births. A significant difference was revealed in some psychological factors and behavioral reactions. Conclusion. Delivery partners have a high psychoemotional load. Husbands have a significantly greater psycho-emotional load acting as a partner in childbirth in relation to mothers-partners. Key words: cesarean section, psychoemotional state, pregnancy, childbirth, J. Teylor, Ch. Spielberger, SAN-test.

COOPERATION OR COOPETITION STRATEGY: WHAT IS THE BEST STRATEGY FACE TO COMPETITION’ INTENSITY AND STRATEGIC CAPABILITIES?

This study aims to decide on the question of the supremacy of coopetition' strategies compared to pure cooperation' strategies according to two explanatory factors both internally and externally. Through a sample of Tunisian industrial firms, the study confirms the simultaneous effect of competitive intensity and strategic capabilities on the nature of the strategy adopted. However, face to competition' intensity, we conclude that strategic capabilities hold the highest weight in explaining coopetition and customer cooperation strategies, but the lowest weight when it comes to supplier cooperation. Also, we show the duality of recourse to the customer cooperation as well as the horizontal coopetition in front of the competition' intensification. Even more, face to excessive competitive intensity, we find, surprisingly, the primacy of recourse to customer cooperation in face to horizontal coopetition. Moreover, our results also show that the strong need for strategic capabilities accentuates the use of coopetition to the detriment of cooperation.Keywords: competitive intensity; strategic capabilities; supplier cooperation; customer cooperation; horizontal coopetition; vertical coopetition.JEL Classification: M10DOI: https://doi.org/10.32479/irmm.8408

Вплив партнерських пологів на адаптаційні можливості роділей

Studying of the reasons of excessive intensity of influence of stressful factors is a relevant problem of modern medicine therefore scientific justification of technology of partner childbirth for optimization of obstetric and perinatal outcomes and psychoemotional adaptation of mother. The objective: studying of tension of adaptation reserves of an organism at partner childbirth. Material and methods. It is inspected: І group – 30 women in labor who gave rise independently, without partner; ІІ group – 30 women in labor at whom as the partner in labor the husband acted; ІІІ group – 30 women in labor who a partner in labor had other family member. It is carried out questioning with use of scales of J. Teylor, Ch. Spіelberger. Results. In article the described correlation relationship between levels of tension of psychoemotional adaptation opportunities at women in labor at partner childbirth. The distinction on some psychological factors and behavioural reactions is revealed. Conclusion. At which at women in labor as the partner in labor not the husband, but other family member acted, psychoemotional tension in relation to childbirth in which increases there was a husband. Key words: psychoemotional state, partner childbirth, adaptation reserves, pregnancy, childbirth, uneasiness level, scale Taylor, scale Spielberg.

Objective and Automated Detection of Diffuse White Matter Abnormality in Preterm Infants Using Deep Convolutional Neural Networks.

Diffuse white matter abnormality (DWMA), or diffuse excessive high signal intensity is observed in 50–80% of very preterm infants at term-equivalent age. It is subjectively defined as higher than normal signal intensity in periventricular and subcortical white matter in comparison to normal unmyelinated white matter on T2-weighted MRI images. Despite the well-documented presence of DWMA, it remains debatable whether DWMA represents pathological tissue injury or a transient developmental phenomenon. Manual tracing of DWMA exhibits poor reliability and reproducibility and unduly increases image processing time. Thus, objective and ideally automatic assessment is critical to accurately elucidate the biologic nature of DWMA. We propose a deep learning approach to automatically identify DWMA regions on T2-weighted MRI images. Specifically, we formulated DWMA detection as an image voxel classification task; that is, the voxels on T2-weighted images are treated as samples and exclusively assigned as DWMA or normal white matter voxel classes. To utilize the spatial information of individual voxels, small image patches centered on the given voxels are retrieved. A deep convolutional neural networks (CNN) model was developed to differentiate DWMA and normal voxels. We tested our deep CNN in multiple validation experiments. First, we examined DWMA detection accuracy of our CNN model using computer simulations. This was followed by in vivo assessments in a cohort of very preterm infants (N = 95) using cross-validation and holdout validation. Finally, we tested our approach on an independent preterm cohort (N = 28) to externally validate our model. Our deep CNN model achieved Dice similarity index values ranging from 0.85 to 0.99 for DWMA detection in the aforementioned validation experiments. Our proposed deep CNN model exhibited significantly better performance than other popular machine learning models. We present an objective and automated approach for accurately identifying DWMA that may facilitate the clinical diagnosis of DWMA in very preterm infants.