Miracle-dz/UniFAR-FTUs huggingface dataset:
TURBULENT DRAG REDUCTION BY TRAVELING WAVES OF SPANWISE FORCING

Several techniques based on spanwise focing were introduced in the last decade [2, 8] in the form of traveling waves of spanwise forcing as generalization of the spanwise-wall oscillation technique to reduce skin-friction drag in a turbulent channel ﬂow. Here we examine all their variants (including one that has never been considered before), by addressing the type of forcing (wall movement versus body force) as well as the traveling direction (streamwise versus spanwise) of the waves. We carry out a DNS-based study within an uniﬁed framework, to compare their capability to reduce skin-friction drag and, more importantly, net energy savings. The present results conﬁrm the potential for drag reductions for every considered forcing. The best-performing spanwise traveling wave, in terms of either drag reduction or net energy saving, is found to be the one with inﬁnite wavelength, i.e. still the spanwise wall oscillation. The streamwise-traveling waves consistently offer the best performance, especially in terms of net savings. The conditions under which body-force based control can be meaningfully compared to wall based control are discussed.
Sensitivity and Specificity of Otoacustic Emissions in Newly Healthy Births without Risk Factors Journal of Neonatal and Pediatric Medicine

Introduction: The World Health Organization reports an incidence of hypoacusis of 5/1000 live births; 2.1% of the world population suffers from a hearing deficit. In Mexico, the Human Communication Institute of the Ministry of Health estimates that 5,600 are born with hearing loss per year. Undiagnosed hearing loss has adverse effects on language, social, emotional, cognitive, academic and professional development. Objective: To verify the sensitivity and specificity of Hearing Otoacoustic emissions in healthy newborns without risk factors. Material and Methods: Prospective study with a probabilistic, descriptive, transversal, quasi experimental and analytical design. We studied 815 healthy newborns without risk factors. EOA and Brainstem Auditory Evoked Potentials were performed with the BERAphone equipment. Sensitivity, specificity, Negative Predictive Value and Positive Predictive Value were determined, using the ROC curve. The AUC value was determined, Pearson’s X2 test was used, and Fisher’s Exact Test was used for the distribution of both tests. Results: 1630 auditory tests were performed. A sensitivity of 63.64% and a specificity of 98.95%, an AUC of 0.805%, VPP 29.17% and VPN 99.75%, LH +60.60% and LH -0.37% of all the tests were detected. The right ear had a sensitivity of 40.0% and a specificity of 98.64%; In the left ear sensitivity of 83.33% and specificity of 99.26%. Conclusions: Otacoustic emissions in newborns without risk factors have a regular sensitivity and high specificity.
The relation between object area and accuracy for a modern mobile convolutional object detector

Object detectors, much like humans, perform less well on small than on large objects. Because of this, the object size distribution of a dataset inﬂuences the average precision a network achieves on that dataset. Therefore, the object size/precision curve of a network might be a better way to compare convolutional object detectors than the average precision over an entire dataset. In this paper we measure the relationship between object size and accuracy for a modern mobile convolutional object detector. We verify that this relationship holds for a different dataset, and that the dataset object size distribution inﬂuences the average precision over the entire dataset. We conclude that the object size/accuracy curve might contain more information about a network’s performance than the average precision over an entire dataset.
Strategic plurality in intergenerationalhand-over Incubation and succession strategies in family ownership

Purpose – With strategy-as-practice theory the authors explore successful business-owning families hand-over of roles to the next generation. The authors argue for the usefulness of strategy-as-practice theory in exploring the complexity and plurality of best practices in intergenerational hand-over. The paper aims to discuss these issues. Design/methodology/approach – A cross-cultural in-depth case study with best practice cases from China, Germany, Sweden, England, Tanzania, Israel and the USA, based on in-depth interviews of family members and non-family employees. Findings – The authors identified three different succession patterns: a “ monolithic practice, ” a distributed leadership hand-over, and active ownership with a non-family managing director/CEO. Two other types of hand-over practices were categorized as incubator patterns that formed a part of, or replaced, what we traditionally see as a hand-over of roles. Families would switch between these practices. Research limitations/implications – Surprisingly, a monolithic succession practice (a one-company-one-leadership role) was rarely used. Quantitative and qualitative research should consider, as should advisors to family owners and family businesses, the plurality of succession practices. Education should explore a variation of succession and how the dynamic of gender influences the process. Practical implications – Giving practitioners, such as research and practitioner, an overview of strategic options so as to explore these in a client or research case. Social implications – Adding the notions that the family is an incubator for new entrepreneurship makes it possible to show how not only sector or public policy generate new ventures. That family as source of entrepreneurship has been well established in the field but it mainstream policy thinking the family is not seen as such a source. Originality/value – The paper offers an integrative model of the complexity of hand-over practices of ownership and leadership roles. It shows how these practices are fundamental for understanding how a family ’ s ownership and their leadership of businesses and new entrepreneurship develops. second generation in serial our like our a little more assertive, as I am. Hasse is like this, and approaches social situations a different way (Sweden; CEO, third generation).
Automatic Image Annotation using Ontology

Semantic annotation of images is choosing appropriate labels for images with extracting effective and hidden feature in pictures, in the proposed method features has extracted from image after segmentation. In addition to the inherent and conceptual features, spatial features of each segments and relation between them are also considered. Then these features with fuzzy rules are trained and in this train we use hierarchical structure for describing and labeling the images that in each of the levels in hierarchical structure used from SVM classification. Results on the images of Imageclef database (this database is classified with hierarchical structure) show the proposed method of image annotation in addition to reducing the complexity of the classification increased accuracy compared to the another methods by approximately 5%.
Emergence ofSalmonella Blockley, possible association with long-term reactive arthritis, and antimicrobial resistance

We previously reported the case of a patient who became ill with Salmonella serotype Blockley after eating a chicken meal and who was still suffering symptoms of salmonella-reactive arthritis 10 years after the initial infection. The immunolo-gical consequences of infection were of concern and prompted a literature review because of the possibility that Salmonella Blockley may be more likely to cause long-term illness in certain patients than more common serovars. The review revealed the additional cause for concern of plasmid-borne extended spectrum beta-lactamases and the high frequency of integron-associated multidrug resistance in some isolates. The serovar was described in 1955 in the USA and Europe. It has become common in South East Asia and recently has been reported more often in Europe. A review of reactive arthritis outbreaks shows that information on the incidence and duration of the condition caused by serovars other than Salmonella serotype Enteritidis and Salmonella serotype Typhimurium is very limited. Rheumatologists can assist microbiologists and epidemiologists by reporting relevant cases of long-term reactive arthritis.
Stabilization of a Two-Wheeled Mobile Pendulum System using LQG and Fuzzy Control Techniques

—This paper studies the control performances of modern and soft-computing based control solutions. Namely, the stabilization of a naturally unstable mechatronic system will be elaborated using linear-quadratic-Gaussian and cascade-connected fuzzy control schemes. The mechatronic system is a special mobile robot (so called two-wheeled mobile pendulum system) that has only two contact points with the supporting surface and its center of mass is located under the wheel axis. Due to this mechanical structure, the inner body (which acts as a pendulum between the wheels) tends to oscillate during the translational motion of the robot, thus the application of feedback control is essential in order to stabilize the dynamical system. In the first part of the paper, the mechatronic system and the corresponding mathematical model are introduced, while in the second part the aforementioned control solutions are designed for the plant. The achieved control performances are analyzed both in simulation environment and on the real mechatronic system. At the end of the paper, a performance assessment of the elaborated control solutions is given based on transient response and error integral measurements.
FOXO1 COMPETES WITH CHREBP AND INHIBITS TXNIP TRANSCRIPTION IN PANCREATIC BETA CELLS

Background: Control of thioredoxin-interacting protein (TXNIP) expression is critical for pancreatic beta cell survival. Results: FOXO1 binds to the TXNIP promoter; blocks ChREBP occupancy and inhibits glucose-induced beta cell TXNIP transcription. 1 and type 2 diabetes in mice (10, 11). These results suggest
Data-Mining Techniques for Routing Attacks in Wireless Sensor Networks

As the Wireless sensor networks are getting complex, with the increasing deployment of wirelesssensor devices and networks, security becomes a critical challenge for sensor networks. In this work, a technique is proposed to detect anomaly nodes in WSN using association with rules and applying clustering algorithm to improve routing in wireless sensor networks. The scheme uses the ANN algorithm to extract traffic patterns from both routing table and network traffic packets and subsequently the K-means cluster algorithm adaptively generates a detection model. Through the combination of these two algorithms, routing attacks can be detected effectively and automatically. The proposed work has improved to detect the attacks which were not identified with the other methods. The detection scheme proposed works with no priori knowledge and is efficient to identify routing attacks in various different wireless sensor networks.
Semantic Indexing based on Focus of Attention Extended by Weakly Supervised Learning

—Semantic INdexing (SIN) is the task to detect concepts like Person and Car in video shots. One main obstacle in SIN is the abundant information contained in a shot where not only a target concept to be detected but also many other concepts are displayed. In consequence, the detection of the target concept is adversely affected by other irrelevant concepts. To overcome this, we enhance SIN based on a human brain mechanism to effectively select important regions in the shot. Speciﬁcally, SIN is integrated with Focus of Attention (FoA) which identiﬁes salient regions that attract user’s attention. The feature of a shot is extracted by weighting regions based on their saliencies, so as to suppress effects of irrelevant regions and emphasise the region of the target concept. In this integration, it is laborious to prepare salient region annotation that assists detecting salient regions most likely to contain the target concept. Thus, we extend FoA using Weakly Supervised Learning (WSL) to generate salient region annotation only from shots annotated with the presence or absence of the target concept. Moreover, rather than the target concept, other concepts are more salient in several shots. Features of these shots falsely emphasise concepts other than the target. Hence, we develop a ﬁltering method to eliminate shots where the target concept is unlikely to be salient. Experimental results show the effectiveness for each of our contributions, that is, SIN using FoA, FoA extended by WSL, and ﬁltering
Spectral Methods for Dimensionality Reduction

How can we search for low dimensional structure in high dimensional data? If the data is mainly confined to a low dimensional subspace, then simple linear methods can be used to discover the subspace and estimate its dimensionality. More generally, though, if the data lies on (or near) a low dimensional submanifold, then its structure may be highly nonlinear, and linear methods are bound to fail. Spectral methods have recently emerged as a powerful tool for nonlinear dimensionality reduction and manifold learning. These methods are able to reveal low dimensional structure in high dimensional data from the top or bottom eigenvectors of specially constructed matrices. To analyze data that lies on a low dimensional submanifold, the matrices are constructed from sparse weighted graphs whose vertices represent input patterns and whose edges indicate neighborhood relations. The main computations for manifold learning are based on tractable, polynomial-time optimizations, such as shortest path problems, least squares fits, semidefinite programming, and matrix diagonalization. This chapter provides an overview of unsupervised learning algorithms that can be viewed as spectral methods for linear and nonlinear dimensionality reduction.
RESOLVING THE ENIGMA OF T2DIABETES MELLITUS ON SPERMIOGRAM AND FUNCTIONAL STATUS OF SPERMATOZOA

Type2 Diabetes mellitus represents a spectrum of metabolic disorders affect all the physiological system including reproduction. The increase in the number of diabetics diagnosed at a young age has coincided with worldwide concerns over male infertility. Available literature on seminogram of diabetic individuals is controversial with many lacunae till date. To have better translucency of the concept in Indian context the present study was undertaken to compare sperm parameters and functional status of spermatozoa of diabetic and non diabetic men. Semen analysis and function tests have been carried out according to World Health Organization guidelines. Our results showed strong association of type2 diabetic conditions with reduced vitality, nuclear chromatin decondensation and hypoosmatic swelling of spermatozoa but other factors of spermiogram and acrosome intactness test has negative correlations. Ageing of the individuals also has negative correlation with disease, therefore from this time it is necessary to evaluate spermiogram of young age individuals with type2 diabetes mellitus quite often along with duration of the disease, glycemic control, presence of complications, and types of treatment used.
Online supplement to ` Speeding up MCMC by E cient Data Subsampling ' S 1

S1.1. Local data clusters. Let z and Nc denote the centroid and the number of observations in cluster c, respectively. Note that ∑K c=1Nc = n and we take K n. Algorithm S1 is an easily implemented clustering algorithm. The maximum distance between an observation and the cluster is a user de ned input. The clustering is a one-time cost whose output can be stored for future use, and is easily sequentially updated as new data arrives. For models with a categorical response, we cluster separately for each category (i.e. zi = xi). The radius can be chosen by simple trial and error to roughly target a preferred K/n ratio. Like any clustering method, Algorithm S1 eventually su ers from the curse of dimensionality in large dimensional data spaces: however, high-dimensional data tends to cluster on a subspace so the e ective dimension may be substantially smaller. Moreover, as discussed in Section 3.7, with a reasonably large p we can still allow for sparse clusters at the cost of having a large variance of our estimator because we can e ectively reduce the O(m−2) error by increasing the subsample size m.
Saturation Throughput Analysis in IEEE 802.11 DCF using semi-Markov Model

A semi-Markov model to analyze the saturation throughput of the IEEE 802.11 Distributed Coordination Function (DCF) is proposed in this letter. Compared to the Markov model [2], the number of states is reduced and the backoﬀ process is simpliﬁed by the semi-Markov model. Furthermore, this model considers both transmission errors and packet retry limit as speciﬁed in the 802.11 standard. This analytical model is validated by using the NS-2 simulator and more close to the simulation results.
Application of Solar Thermal Energy to Processes D3.1 Preliminary design of Sundial for AMTP

Document Summary Information Grant Agreement No.: 884411 Acronym: ASTEP WP: WP 3 – Application of the SunDial Technology to the ASTEP Concept Task: Task 3.1 – Basic design of Sundial for AMTP Deliverable ID: D3.1 – Preliminary design of Sundial for AMTP Submission date: 2021-11-13 Due date: 2021-10-31 Owner: A Rovira (UNED) Participants: R Abbas (UPM), R Barbero (UNED), MJ Montes (UNED), M Muñoz (UNED), A Rovira (UNED) Dissemination level: Public Reviewers: José Muñoz (UPCT), Vassiliki Drosou (CRES) Approver: Antonio Rovira (UNED)
CMAR_A_260986 7761..7770

1Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China; 2Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, People’s Republic of China Objective: To develop novel models for predicting extracapsular extension (EPE), seminal vesicle invasion (SVI), or upgrading in prostate cancer (PCa) patients using clinical parameters, biparametric magnetic resonance imaging (bp-MRI), and transrectal ultrasonography (TRUS)-guided systematic biopsies. Patients and Methods: We retrospectively collected data from PCa patients who underwent standard (12-core) systematic biopsy and radical prostatectomy. To develop predictive models, the following variables were included in multivariable logistic regression analyses: total prostatespecific antigen (TPSA), central transition zone volume (CTZV), prostate-specific antigen (PSAD), maximum diameter of the index lesion at bp-MRI, EPE at bp-MRI, SVI at bp-MRI, biopsy Gleason grade group, and number of positive biopsy cores. Three risk calculators were built based on the coefficients of the logit function. The area under the curve (AUC) was applied to determine the models with the highest discrimination. Decision curve analyses (DCAs) were performed to evaluate the net benefit of each risk calculator. Results: A total of 222 patients were included in this study. Overall, 83 (37.4%), 75 (33.8%), and 107 (48.2%) patients had EPE, SVI, and upgrading at final pathology, respectively. The addition of bp-MRI data improved the discrimination of models for predicting SVI (0.807 vs 0.816) and upgrading (0.548 vs 0.625) but not EPE (0.766 vs 0.763). Similarly, models including clinical parameters, bp-MRI data, and information on systematic biopsies achieved the highest AUC in the prediction of EPE (0.842), SVI (0.913), and upgrading (0.794), and the three corresponding risk calculators yielded the highest net benefit. Conclusion: We developed three easy-to-use risk calculators for the prediction of adverse pathological features based on patient clinical parameters, bp-MRI data, and information on systematic biopsies. This may be greatly beneficial to urologists in the decision-making process for PCa patients.
Edinburgh Explorer Progress in paleoclimate modeling

This paper briefly surveys areas of paleoclimate modeling notable for recent progress. New ideas, in- cluding hypotheses giving a pivotal role to sea ice, have revitalized the low-order models used to simulate the time evolution of glacial cycles through the Pleistocene, a prohibitive length of time for comprehensive general circulation models (GCMs). In a recent breakthrough, however, GCMs have succeeded in simulating the onset of glaciations. This occurs at times (most recently, 115 kyr B . P .) when high northern latitudes are cold enough to maintain a snow cover and tropical latitudes are warm, enhancing the moisture source. More generally, the improvement in models has allowed simulations of key periods such as the Last Glacial Maximum and the mid-Holocene that compare more favorably and in more detail with paleoproxy data. These models now simulate ENSO cycles, and some of them have been shown to reproduce the reduction of ENSO activity observed in the early to middle Holocene. Modeling studies have demonstrated that the reduction is a response to the altered orbital configuration at that time. An urgent challenge for paleocli- mate modeling is to explain and to simulate the abrupt changes observed during glacial epochs (i.e., Dansgaard–Oescher cycles, Heinrich events, and the Younger Dryas). Efforts have begun to simulate the last millennium. Over this time the forcing due to orbital variations is less important than the radiance changes due to volcanic eruptions and variations in solar output. Simulations of these natural variations test the models relied on for future climate change projections. They provide better estimates of the internal and naturally forced variability at centennial time scales, elucidating how unusual the recent global temperature trends are.
PROCESS ECONOMIZATION OF ORGANIC AND INORGANIC NITROGEN SOURCE IN SUBMERGED MEDIA FOR ALKALINE PROTEASE PRODUCTION FROM ASPERGILLUS AWAMORI

Protease constitutes a large and complex group of enzymes that plays an important nutritional and regulatory role in nature. Proteases are (physiologically) necessary for living organisms; they are ubiquitous and found in a wide diversity of sources. Protease production were carried out by using supplementation of organic and inorganic nitrogen sources such as Beef extract, Yeast extract and peptone at concentrations ranging from 0.25% to 1.25% with increments of 0.25% and also different inorganic nitrogen sources like Ammonium chloride and ammonium sulphate at concentrations ranging from 0.025% to 0.125% with increments of 0.025%. The peptone (1%) produced 3.15 IU were best organic nitrogen source and ammonium sulphate (0.025%) appear to be good inorganic nitrogen source under submerged fermentation process and showed 2.98 IU by using Aspergillus awamorii KGSR12.
Alzheimer’s and Parkinson’s Disease Alzheimer’s Disease and Sleep Disorders: A Descriptive Study of Actigraphic and Clinical Presentation Based on Neuropsychiatric Inventory

Sleep disorders are very common in Alzheimer’s disease. This study describes the clinical and actigraphic aspects of the sleep pattern of 41 Alzheimer’s disease patients identified with sleep disorders by means of the neuropsychiatric inventory. The clinical protocol used to assess sleep quality included eight categories of sleep complaints. In addition, each caregiver rated his/her own distress level according to a five-point scale. The most common primary sleep disorders found among elderly participants were: to wake caregivers during the night (n = 39; 95.1%) and to get up during the night (n = 33; 80.4%). Actigraphic measures confirmed the clinical observation with the nighttime total sleep time = 311.2 ± 91.6 minutes, awakenings = 25.9 ± 8.7 per night and nighttime wake after sleep onset = 198.5 ± 78.4 minutes. Subjects compensated the lack of sleep at night by sleeping and napping during the day: daytime total sleep time = 152.6 ± 97.3 minutes and naps = 32.2 ± 15.8 per day. Most caregivers (70.7%) rated their distress level as moderate/extreme. The authors advocate that further studies and trials focused on the profile of patients, the methods described and types of sleep disorders should be carried out. actigraphic aspects of the of characterize