A simple construction method for sequentially tidying up 2D online freehand sketches

This paper presents a novel constructive approach to sequentially tidying up 2D online freehand sketches for further 3D interpretation in a conceptual design system. Upon receiving a sketch stroke, the system first identifies it as a 2D primitive and then automatically infers its 2D geometric constraints related to previous 2D geometry (if any). Based on recognized 2D constraints, the identified geometry will be modified accordingly to meet its constraints. The modification is realized in one or two sequent geometric constructions in consistence with its degrees of freedom. This method can produce 2D configurations without iterative procedures to solve constraint equations. It is simple and easy to use for a real-time application. Several examples are tested and discussed

Моливдовулы έπί τοῦ μαγγλαβίου из Болгарии

В статье публикуются печати έπί τοῦ μαγγλαβίου, которые хранятся в музеях и частных коллекциях Болгарии: 1. Григорий, протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 2. Евфимиан, императорский спафарий и έπί τοῦ μαγγλαβίου (IX-X вв.). 3. Феодор Радин, императорский протоспафарий и έπί τοῦ μαγγλαβίου(Хв.). 4. Катакалон ... (?),императорский протоспафарий и έπί τοῦ μαγγλαβίου (Х-Х1 вв.). 5. Лев, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 6. Лев Мукат, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 7. Мариан, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 8. Михаил, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 9. Николай, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X-XI вв.). 10. Петр, императорский протоспафарий и έπί τοῦ μαγγλαβίου(X в.). 11. Филоматес, императорский протоспафарий и έπί τοῦ μαγγλαβίου (X в.). 12. Хотомир, императорский спафарокандидат и έπί τοῦ μαγγλαβίου (IX-X вв.)

Multimodal Convolutional Neural Networks to Detect Fetal Compromise During Labor and Delivery

The gold standard to assess whether a baby is at risk of oxygen deprivation during childbirth, is monitoring continuously the fetal heart rate with cardiotocography (CTG). The aim is to identify babies that could benefit from an emergency operative delivery (e.g., Cesarean section), in order to prevent death or permanent brain injury. The long, dynamic and complex CTG patterns are poorly understood and known to have high false positive and false negative rates. Visual interpretation by clinicians is challenging and reliable accurate fetal monitoring in labor remains an enormous unmet medical need. In this work, we applied deep learning methods to achieve data-driven automated CTG evaluation. Multimodal Convolutional Neural Network (MCNN) and Stacked MCNN models were used to analyze the largest available database of routinely collected CTG and linked clinical data (comprising more than 35000 births). We also assessed in detail the impact of the signal quality on the MCNN performance. On a large hold-out testing set from Oxford (n= 4429 births), MCNN improved the prediction of cord acidemia at birth when compared with Clinical Practice and previous computerized approaches. On two external datasets, MCNN demonstrated better performance compared to current feature extraction-based methods. Our group is the first to apply deep learning for the analysis of CTG. We conclude that MCNN hold potential for the prediction of cord acidemia at birth and further work is warranted. Despite the advances, our deep learning models are currently not suitable for the detection of severe fetal injury in the absence of cord acidemia - a heterogeneous, small, and poorly understood group. We suggest that the most promising way forward are hybrid approaches to CTG interpretation in labor, in which different diagnostic models can estimate the risk for different types of fetal compromise, incorporating clinical knowledge with data-driven analyses

Multifunctional Cotton Impregnated with Multilayer Chitosan/Lignin Nanocoating and Ag Nanoparticles

he demand for clothes with antimicrobial and UV protective properties is continually growing. In an attempt to develop a simple and efficient treatment for cotton fabrics, layer-by-layer deposition of chitosan and magnesium lignosulfonate followed by in situ synthesis of Ag nanoparticles (NPs) was performed. Magnesium lignosulfonate acts as a stabilizing agent and UV blocker while NaBH4 is applied as a reducing agent. The influence of the number of bilayers (4 and 12) and the initial concentration of AgNO3 solution (10 mM and 20 mM) on UV protection factor (UPF) and antimicrobial activity against Gram-negative bacteria Escherichia coli, Grampositive bacteria Staphylococcus aureus and yeast Candida albicans was studied. The presence of nanocoating on the surface of cotton fabric is confirmed by FTIR and XPS analyses. XPS and FESEM analyses reveal a successful synthesis of Ag NPs on the surface of cotton fibers with an average dimension of 35 nm. A four bilayer coating is sufficient to reach maximum 50+ UV protection. Maximum reduction of all investigated microorganisms is achieved with 12 bilayers and application of 20 mM AgNO3 solution

A conceptual design tool: a sketch and fuzzy logic based system

Abstract: A real-time sketch and fuzzy logic based prototype system for conceptual design has been developed. This system comprises four phases. In the ® rst one, the system accepts the input of online free-hand sketches, and segments them into meaningful parts by using fuzzy knowledge to detect corners and in¯ection points on the sketched curves. The fuzzy knowledge is applied to capture user' s drawing intention in terms of sketching position, direction, speed and acceleration. During the second phase, each segmented subpart (curve) can be classi® ed and identi® ed as one of the following two-dimensional primitives: straight lines, circles, circular arcs, ellipses, elliptical arcs or B-spline curves. Then, two-dimensional topology information (connectivity, unitary constraints and pairwise constraints) is extracted dynamically from the identi® ed two-dimensional primitives. From the extracted information, more accurate two-dimensional geometry can be built up by a two-dimensional geometric constraint solver. The two-dimensional topology and geometry information is then employed to further interpretation of a three-dimensional geometry. The system can not only accept sketched input but also users' interactive input of two-and three-dimensional primitives. This makes it friendly and easier to use, in comparison with`sketched input only' or interactive input only' systems. Finally, examples are given to illustrate the system

Pulse-Shape discrimination with the Counting Test Facility

Pulse shape discrimination (PSD) is one of the most distinctive features of liquid scintillators. Since the introduction of the scintillation techniques in the field of particle detection, many studies have been carried out to characterize intrinsic properties of the most common liquid scintillator mixtures in this respect. Several application methods and algorithms able to achieve optimum discrimination performances have been developed. However, the vast majority of these studies have been performed on samples of small dimensions. The Counting Test Facility, prototype of the solar neutrino experiment Borexino, as a 4 ton spherical scintillation detector immersed in 1000 tons of shielding water, represents a unique opportunity to extend the small-sample PSD studies to a large-volume setup. Specifically, in this work we consider two different liquid scintillation mixtures employed in CTF, illustrating for both the PSD characterization results obtained either with the processing of the scintillation waveform through the optimum Gatti's method, or via a more conventional approach based on the charge content of the scintillation tail. The outcomes of this study, while interesting per se, are also of paramount importance in view of the expected Borexino detector performances, where PSD will be an essential tool in the framework of the background rejection strategy needed to achieve the required sensitivity to the solar neutrino signals.Comment: 39 pages, 17 figures, submitted to Nucl. Instr. Meth.

Medio-Frontal and Anterior Temporal abnormalities in children with attention deficit hyperactivity disorder (ADHD) during an acoustic antisaccade task as revealed by electro-cortical source reconstruction

<p>Abstract</p> <p>Background</p> <p>Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent disorders in children and adolescence. Impulsivity is one of three core symptoms and likely associated with inhibition difficulties. To date the neural correlate of the antisaccade task, a test of response inhibition, has not been studied in children with (or without) ADHD.</p> <p>Methods</p> <p>Antisaccade responses to visual and acoustic cues were examined in nine unmedicated boys with ADHD (mean age 122.44 ± 20.81 months) and 14 healthy control children (mean age 115.64 ± 22.87 months, three girls) while an electroencephalogram (EEG) was recorded. Brain activity before saccade onset was reconstructed using a 23-source-montage.</p> <p>Results</p> <p>When cues were acoustic, children with ADHD had a higher source activity than control children in Medio-Frontal Cortex (MFC) between -230 and -120 ms and in the left-hemispheric Temporal Anterior Cortex (TAC) between -112 and 0 ms before saccade onset, despite both groups performing similarly behaviourally (antisaccades errors and saccade latency). When visual cues were used EEG-activity preceding antisaccades did not differ between groups.</p> <p>Conclusion</p> <p>Children with ADHD exhibit altered functioning of the TAC and MFC during an antisaccade task elicited by acoustic cues. Children with ADHD need more source activation to reach the same behavioural level as control children.</p

Computer-aided DSM-IV-diagnostics – acceptance, use and perceived usefulness in relation to users' learning styles

BACKGROUND: CDSS (computerized decision support system) for medical diagnostics have been studied for long. This study was undertaken to investigate how different preferences of Learning Styles (LS) of psychiatrists might affect acceptance, use and perceived usefulness of a CDSS for diagnostics in psychiatry. METHODS: 49 psychiatrists (specialists and non-specialists) from 3 different clinics volunteered to participate in this study and to use the CDSS to diagnose a paper-based case (based on a real patient). LS, attitudes to CDSS and complementary data were obtained via questionnaires and interviews. To facilitate the study, a special version of the CDSS was created, which automatically could log interaction details. RESULTS: The LS preferences (according to Kolb) of the 49 physicians turned out as follows: 37% were Assimilating, 31% Converging, 27% Accommodating and 6% Diverging. The CDSS under study seemed to favor psychiatrists with abstract conceptualization information perceiving mode (Assimilating and Converging learning styles). A correlation between learning styles preferences and computer skill was found. Positive attitude to computer-aided diagnostics and learning styles preferences was also found to correlate. Using the CDSS, the specialists produced only 1 correct diagnosis and the non-specialists 2 correct diagnoses (median values) as compared to the three predetermined correct diagnoses of the actual case. Only 10% had all three diagnoses correct, 41 % two correct, 47 % one correct and 2 % had no correct diagnose at all. CONCLUSION: Our results indicate that the use of CDSS does not guarantee correct diagnosis and that LS might influence the results. Future research should focus on the possibility to create systems open to individuals with different LS preferences and possibility to create CDSS adapted to the level of expertise of the user