Miracle-dz/UniFAR-FTUs huggingface dataset:
DIVA-HisDB: A Precisely Annotated Large Dataset of Challenging Medieval Manuscripts

This paper introduces a publicly available historical manuscript database DIVA-HisDB for the evaluation of several Document Image Analysis (DIA) tasks. The database consists of 150 annotated pages of three different medieval manuscripts with challenging layouts. Furthermore, we provide a layout analysis ground-truth which has been iterated on, reviewed, and refined by an expert in medieval studies. DIVA-HisDB and the ground truth can be used for training and evaluating DIA tasks, such as layout analysis, text line segmentation, binarization and writer identification. Layout analysis results of several representative baseline technologies are also presented in order to help researchers evaluate their methods and advance the frontiers of complex historical manuscripts analysis. An optimized state-of-the-art Convolutional Auto-Encoder (CAE) performs with around 95% accuracy, demonstrating that for this challenging layout there is much room for improvement. Finally, we show that existing text line segmentation methods fail due to interlinear and marginal text elements.
Buckling analysis of two-and three-layer delaminated beams with and without bridging.

Delamination has been a subject of concern in engineering applications of layer structures. Buckling of two and three layer beams with asymmetrically located delaminations is studied in terms of newly introduced nondimensionalized axial and bending stiffnesses. Effective- slenderness ratio (ESR), another nondimensionalized parameter is also introduced in the analysis. The close form solution can serve as a benchmark for other numerical schemes for these problems of delaminations. Further, bridging effects are considered to study the buckling analysis of two layer delaminated beams as an eigenvalue problem by using Rayleigh-Ritz energy method. Results show that bridging was found to be effective for the cases of shallow delamination with moderate length and for the deep and long delamination. The ESR is found to be a controlling parameter of the buckling behavior for delaminated beams with and without bridging. Finally, finite element analyses are performed and a good correlation is observed between the theoretical and numerical results.
Imaging visco-elastic properties of soft tissue with ultrasound

T h i s thesis describes a system to measure the mechanical properties of soft tissue. T h e mechanica l properties depend on the type of tissue (e.g. fat, muscle, b lood) and the presence of disease or pathology. For example, i t has been known that many cancers, such as ca rc inoma of the breast a n d the prostate, appear as ha rd nodules. M a n u a l pa lpa t ion is wide ly used for detect ing these nodules but detection by pa lpa t ion is restr icted to large tumors that reside relat ively close to an accessible surface. Cur ren t imaging devices such as computed tomography, magnetic resonance imaging and u l t rasound are not d i rec t ly capable of measuring the mechanical properties of tissue. A n emerging research topic, called elastography, a ims to produce a new type of image that depicts mechanical properties of tissue. T h e basic pr inc ip le is to excite mo t ion i n a tissue, record the mot ion w i t h an imaging device, and then estimate the mechanical properties from the recorded data . T h i s thesis presents a new approach based on this pr inciple where a computer-control led v ib ra to r induces mo t ion over a range of frequencies s imultaneously and the resul t ing displacement is recorded at mul t ip le locat ions and t ime instants w i t h a sequence of u l t rasound images. T w o methods are proposed for es t imat ing mechanical properties such as stiffness, damping , and mass, from the recorded data . In the first method , the tissue is modeled by using mass elements at different locat ions connected to each other by springs and dampers. These elements represent the loca l mass, stiffness, and damping of the tissue. T h e equat ion of mot ion for the proposed one dimensional model is solved to extract these parameters. T h e second me thod performs a transfer function analysis of the tissue mot ion . A c c o r d i n g to this method, the tissue dynamics between two locations a long the axis of mot ion is considered as a l inear dynamic system. T h e transfer function between the two locations is obta ined by spectra l analysis w i t h the recorded mot ion used as inputs and outputs . T h e shape of the transfer funct ion can then
Deep Online Video Stabilization

Video stabilization technique is essential for most hand-held captured videos due to high-frequency shakes. Several 2D-, 2.5D- and 3D-based stabilization techniques are well studied, but to our knowledge, no solutions based on deep neural networks had been proposed. The reason for this is mostly the shortage of training data, as well as the challenge of modeling the problem using neural networks. In this paper, we solve the video stabilization problem using a convolutional neural network (ConvNet). Instead of dealing with offline holistic camera path smoothing based on feature matching, we focus on low-latency real-time camera path smoothing without explicitly representing the camera path. Our network, called StabNet, learns a transformation for each input unsteady frame progressively along the time-line, while creating a more stable latent camera path. To train the network, we create a dataset of synchronized steady/unsteady video pairs via a well designed hand-held hardware. Experimental results shows that the proposed online method (without using future frames) performs comparatively to traditional offline video stabilization methods, while running about 30 times faster. Further, the proposed StabNet is able to handle night-time and blurry videos, where existing methods fail in robust feature matching.
Knowledge-Based Conformer Generation Using the Cambridge Structural Database

Fast generation of plausible molecular conformations is central to molecular modeling. This paper presents an approach to conformer generation that makes extensive use of the information available in the Cambridge Structural Database. By using geometric distributions derived from the Cambridge Structural Database, it is possible to create biologically relevant conformations in the majority of cases analyzed. The paper compares the performance of the approach with previously published evaluations, and presents some cases where the method fails. The method appears to show significantly improved performance in reproduction of the conformations of structures observed in the Cambridge Structural Database and the Protein Data Bank as compared to other published methods of a similar speed.
Breastfeeding: a reproductive factor able to reduce the risk of luminal B breast cancer in premenopausal White women

In the medical literature, the role of breastfeeding and reproductive factors in the risk of breast carcinoma is still an open debate in premenopausal women. We highlight the role of breastfeeding and reproductive factors in luminal A and luminal B, the most frequent breast cancers. This case–control study analyzes a White premenopausal population of 286 breast cancer patients, divided into molecular subtypes, and 578 controls matched by age. Multivariate logistic regression models were used to assess the relationships of breastfeeding and other reproductive factors (age at menarche, parity, age at first pregnancy, number of children) with the risk of breast cancers. Among the variables examined, reproductive factors did not alter the risk of cancer, whereas breastfeeding up to 12 months was a significant protective factor against luminal B breast cancer (multivariate odds ratio: 0.22, 95% confidence interval: 0.09–0.59, P=0.002). In contrast, luminal A cases did not significantly correlate with breastfeeding or other reproductive factors. Breastfeeding up to 12 months is strongly protective against the more aggressive luminal B, but not against the less aggressive luminal A breast cancer in premenopausal White women.
Spatial clustering of drug-resistant tuberculosis in Hlabisa subdistrict, KwaZulu-Natal, 2011–2015

SETTING: Incidence rates of tuberculosis (TB) in South Africa are among the highest in the world, and drug resistance is a major concern. Understanding geographic variations in disease may guide targeted interventions. OBJECTIVE: To characterise the spatial distribution of drug-resistant TB (DR-TB) in a rural area of KwaZulu-Natal, South Africa, and to test for clustering. DESIGN: This was a cross-sectional analysis of DR-TB patients managed at a rural district hospital from 2011 to 2015. We mapped all patients in hospital data to local areas, and then linked to a population-based demographic surveillance system to map the patients to individual homesteads. We used kernel density estimation to visualise the distribution of disease and tested for clustering using spatial scan statistics. RESULTS: There were 489 patients with DR-TB in the subdistrict; 111 lived in the smaller demographic surveillance area. Spatial clustering analysis identified a high-risk cluster (relative risk of DR-TB inside vs. outside cluster 3.0, P <0.001) in the south-east, a region characterised by high population density and a high prevalence of human immunodeficiency virus infection. CONCLUSION: We have demonstrated evidence of a geographic high-risk cluster of DR-TB. This suggests that targeting interventions to spatial areas of highest risk, where transmission may be ongoing, could be effective.
Restoration of Muscle Glycogen and Functional Capacity: Role of Post-Exercise Carbohydrate and Protein Co-Ingestion

The importance of post-exercise recovery nutrition has been well described in recent years, leading to its incorporation as an integral part of training regimes in both athletes and active individuals. Muscle glycogen depletion during an initial prolonged exercise bout is a main factor in the onset of fatigue and so the replenishment of glycogen stores may be important for recovery of functional capacity. Nevertheless, nutritional considerations for optimal short-term (3–6 h) recovery remain incompletely elucidated, particularly surrounding the precise amount of specific types of nutrients required. Current nutritional guidelines to maximise muscle glycogen availability within limited recovery are provided under the assumption that similar fatigue mechanisms (i.e., muscle glycogen depletion) are involved during a repeated exercise bout. Indeed, recent data support the notion that muscle glycogen availability is a determinant of subsequent endurance capacity following limited recovery. Thus, carbohydrate ingestion can be utilised to influence the restoration of endurance capacity following exhaustive exercise. One strategy with the potential to accelerate muscle glycogen resynthesis and/or functional capacity beyond merely ingesting adequate carbohydrate is the co-ingestion of added protein. While numerous studies have been instigated, a consensus that is related to the influence of carbohydrate-protein ingestion in maximising muscle glycogen during short-term recovery and repeated exercise capacity has not been established. When considered collectively, carbohydrate intake during limited recovery appears to primarily determine muscle glycogen resynthesis and repeated exercise capacity. Thus, when the goal is to optimise repeated exercise capacity following short-term recovery, ingesting carbohydrate at an amount of ≥1.2 g kg body mass−1·h−1 can maximise muscle glycogen repletion. The addition of protein to carbohydrate during post-exercise recovery may be beneficial under circumstances when carbohydrate ingestion is sub-optimal (≤0.8 g kg body mass−1·h−1) for effective restoration of muscle glycogen and repeated exercise capacity.
Phoenix: Peer-to-Peer Location Based Notification in Mobile Networks

Location Based Notification (LBN) aims to alert the users in a target area with the information of interest to them. With a wide range of applications, LBN has been gaining more and more attraction among wireless users and service providers. The mainstream centralized solution based on cellular networks may incur high service cost. In this paper, we present an innovative scheme called Phoenix, which does not rely on any infrastructure, to implement for location based notification service. In our design, devices (users) across the target area form a dynamic peer-to-peer network, where a user can be a message source, a message carrier, or a message subscriber. When a user meets the message carrier, the user can get a copy of the message. Phoenix keeps messages of interest being circulated in the target area, hence users are being notified. To achieve desired notification performance, Phoenix adaptively controls when a user should take the carrier role and help disseminating a message in order to keep the message ``alive", given the fact that message carriers may leave the target area and drop the message. Extensive simulations have been conducted to show the efficacy of Phoenix notification system.
Complications néonatales des extractions instrumentales Neonatal outcomes after instrumental vaginal delivery

Résumé De pratique courante, les extractions instrumentales permettent de réduire la mortalité et la morbidité de fœtus en détresse mais sont en contrepartie grevées d’une morbidité néonatale propre non négligeable. Peu de ces complications sont cependant spécifiques de la technique utilisée et un bon nombre d’entre elles peuvent se rencontrer en cas d’accouchement normal. Indépendamment d’un facteur de risque surajouté, parfois responsable de la décision de l’instrumentation, la mortalité postnatale n’est pas augmentée par l’utilisation de forceps ou de ventouse. Les principales complications de ces deux techniques sont les hémorragies extra et intra-crâniennes. Ces dernières sont le plus souvent résolutives et ne s’associent pas à un pronostic neurologique péjoratif. Cependant, peu d’études longitudinales sont disponibles dans la littérature sur le devenir neuropsychologique à long terme. Les complications traumatiques liées à l’utilisation du forceps telles que les paralysies du nerf facial et les embarrures sont plus spécifiques, mais le plus souvent sans conséquences fonctionnelles à moyen et long terme. Les principales complications à long terme s’observent en cas de sur-risques associés tel qu’une anoxie périnatale. Le type de la ventouse utilisée et l’emploi selon des règles strictes prédéfinies de la ventouse ou du forceps influencent l’incidence des complications néonatales. Bien que parfois contradictoires, les études sur le degré d’innocuité de la ventouse et du forceps ne peuvent conclure à la supériorité d’une technique sur l’autre. En conclusion, la décision d’une extraction instrumentale pour des raisons fœtales ou maternelles est associée à des complications néonatales le plus souvent non spécifiques et dont les conséquences sur la morbidité néonatale sont à court terme. © 2008 Elsevier Massons SAS. Tous droits réservés.
Far-infrared optical transmission through asymmetrical ferroelectric films

Investigation of far-infrared (FIR) spectroscopy for symmetrical ferroelectric (FE) films are discussed theoretically based on the basis of the Tilley-Zeks (TZ) model using Landau free energy expansion, LandauKhalatnikov (LK) equation of motion, and electromagnetic wave equation for the second [1] and first order [2, 3] respectively. Here by using the same model we scrutinized a preliminary result of non-surface effect of FIR spectra behaviour for asymmetrical FE films in both phase transitions incorporating with the effect of refractive index.
Language independent query-by-example spoken term detection using N-best phone sequences and partial matching

In this paper, we propose a partial sequence matching based symbolic search (SS) method for the task of language independent query-by-example spoken term detection. One main drawback of conventional SS approach is the high miss rate for long queries. This is due to high variations in symbol representation of query and search audios, especially in language independent scenario. The successful matching of a query with its instances in search audio becomes exponentially more difficult as the query grows longer. To reduce miss rate, we propose a partial matching strategy, in which all partial phone sequences of a query are used to search for query instances. The partial matching is also suitable for real life applications where exact match is usually not necessary and word prefix, suffix, and order should not affect the search result. When applied to the QUESST 2014 task, results show the partial matching of phone sequences is able to reduce miss rate of long queries significantly compared with conventional full matching method. In addition, for the most challenging inexact matching queries (type 3), it also shows clear advantage over DTW-based methods.
Image Stylization using Depth Information for Hatching and Engraving effects

In this thesis inspired by artists such as Gustave Doré and copperplate engravers, we present a new approach for producing a sketch-type hatching effect as well as engraving art seen in the US dollar bills using depth maps as input. The approach uses the acquired depth to generate pen-and-ink type of strokes that exaggerate surface characteristics of faces and objects. The background on this area is presented with an emphasis on line drawing, pen-and-ink illustrations, engraving art and other artistic styles. The patterns generated are composed of parallel lines that change their directionality smoothly while avoiding intersections between them. The style communicates tone and surface characteristics using curve deformation, thickness, density, and spacing while at the same time adding crosshatching effects. This is achieved with our algorithmic approach which uses the data to perform operations that deforms patterns. The components of our methodology and algorithms are detailed, as well as the equations that govern these effects. This work also presents an array of different results by varying parameters or by rendering variations.
Multiple mutations of lung squamous cell carcinoma shared common mechanisms

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell lung cancers which is the cause of 80% of all lung cancer deaths. The genes that highly mutated in patients with LUSC and their roles played in the tumorigenesis remains unknown. Data of patients with Lung squamous cell carcinoma (LUSC) were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified between control and cancer samples. Patients and controls can be separated by mRNA expression level showing that the between-group variance and totally 1265 genes were differentially expressed between controls and patients. Top genes whose mutations highly occurred in patients with LUSC were identified, most of these genes were shown to be related with tumorigenesis in previous studies. All of the genes mostly mutated were independently correlated with expression levels of all genes. These mutations did not show the trend of co-occurrence. However, the influenced gene of these mutations had overlaps. After studying the intersection of these genes, a group of shared genes were identified. The shared pathways enriched which played critical role in LUSC were identified based on these shared genes. Different mutations had contribution to the progression of LUSC. Though these genes involved different specific mechanisms, most of them may share a common mechanism which is critical for LUSC. The results may suggest a neglected mechanism and also indicate a potential target for therapies.
Diphtheria Toxin-Induced Cell Death Triggers Wnt-Dependent Hair Cell Regeneration in Neonatal Mice

Cochlear hair cells (HCs), the sensory cells that respond to sound, do not regenerate after damage in adult mammals, and their loss is a major cause of deafness. Here we show that HC regeneration in newborn mouse ears occurred spontaneously when the original cells were ablated by treatment with diphtheria toxin (DT) in ears that had been engineered to overexpress the DT receptor, but was not detectable when HCs were ablated in vivo by the aminoglycoside antibiotic neomycin. A variety of Wnts (Wnt1, Wnt2, Wnt2b, Wnt4, Wnt5a, Wnt7b, Wnt9a, Wnt9b, and Wnt11) and Wnt pathway component Krm2 were upregulated after DT damage. Nuclear β-catenin was upregulated in HCs and supporting cells of the DT-damaged cochlea. Pharmacological inhibition of Wnt decreased spontaneous regeneration, confirming a role of Wnt signaling in HC regeneration. Inhibition of Notch signaling further potentiated supporting cell proliferation and HC differentiation that occurred spontaneously. The absence of new HCs in the neomycin ears was correlated to less robust Wnt pathway activation, but the ears subjected to neomycin treatment nonetheless showed increased cell division and HC differentiation after subsequent forced upregulation of β-catenin. These studies suggest, first, that Wnt signaling plays a key role in regeneration, and, second, that the outcome of a regenerative response to damage in the newborn cochlea is determined by reaching a threshold level of Wnt signaling rather than its complete absence or presence. SIGNIFICANCE STATEMENT Sensory HCs of the inner ear do not regenerate in the adult, and their loss is a major cause of deafness. We found that HCs regenerated spontaneously in the newborn mouse after diphtheria toxin (DT)-induced, but not neomycin-induced, HC death. Regeneration depended on activation of Wnt signaling, and regeneration in DT-treated ears correlated to a higher level of Wnt activation than occurred in nonregenerating neomycin-treated ears. This is significant because insufficient regeneration caused by a failure to reach a threshold level of signaling, if true in the adult, has the potential to be exploited for development of clinical approaches for the treatment of deafness caused by HC loss.
Direct multi-scale dual-stream network for pedestrian detection

We propose Direct Multi-scale Dual-stream network (DMDnet) for pedestrian detection. DMDnet takes a full-size image as input and detects pedestrians of various sizes directly without extracting proposals or using resampling. To improve detection accuracy we adopt dual-stream architecture that combines two types of features that are branched off from two different layers. The lower layer observes the proper sizes of receptive fields depending on the scales of pedestrians; the upper layer contains contextual information. The whole network is trained end-to-end. In experiments DMDnet yields state-of-the-art detection accuracy on the Caltech pedestrian benchmark with new annotation, and has quite fast detection speed.
Bayesian methods of confidence interval construction for the population attributable risk from cross‐sectional studies

Population attributable risk measures the public health impact of the removal of a risk factor. To apply this concept to epidemiological data, the calculation of a confidence interval to quantify the uncertainty in the estimate is desirable. However, because perhaps of the confusion surrounding the attributable risk measures, there is no standard confidence interval or variance formula given in the literature. In this paper, we implement a fully Bayesian approach to confidence interval construction of the population attributable risk for cross‐sectional studies. We show that, in comparison with a number of standard Frequentist methods for constructing confidence intervals (i.e. delta, jackknife and bootstrap methods), the Bayesian approach is superior in terms of percent coverage in all except a few cases. This paper also explores the effect of the chosen prior on the coverage and provides alternatives for particular situations. Copyright © 2016 John Wiley & Sons, Ltd.