Miracle-dz/UniFAR-FTUs huggingface dataset:
Object Detection based on Convolutional Neural Network

In this paper, we develop a new approach for detecting multiple objects from images based on convolutional neural networks (CNNs). In our model, we first adopt the edge box algorithm to generate region proposals from edge maps for each image, and perform forward passing of all the proposals through a fine-tuned CaffeNet model. Then we get the CNNs score for each proposal by extracting the output of softmax which is the last layer of CNN. Next, the proposals are merged for each class independently by the greedy nonmaximum suppression (NMS) algorithm. At last, we evaluate the mean average precision (mAP) for each class. The mAP of our model on PASCAL 2007 test dataset is 37.38%. We also discuss how to further improve the performance based on our model in this paper.
Price shocks in disaster: the Great Kantō Earthquake in Japan,1923

This paper tests the operation of markets in the wake of a sudden exogenous shock in prewar Japan, the Great Kantō Earthquake of 1923. Using a unique monthly wholesale price dataset of provincial cities, we found that the earthquake had a positive impact on the price of rice and timber in the sample cities. Our results also indicate that the wholesale price of rice in cities in the northeast of Japan, which were more closely integrated with the affected region, experienced more significant price rises than those in western Japan. Nevertheless, although further research using retail as opposed to wholesale prices of goods is needed, these preliminary findings suggest that the diffusion of price instability outwards from the affected region was on a lesser scale than might have been expected.
O knee, where art thou? Patient-reported outcomes and physical performance in individuals with acute knee injury.

11 Populärvetenskaplig sammanfattning . 13 Definitions and abbreviations . 15 Definitions . 15 Abbreviations . 16 List of studies . 19 Introduction . 21 Knee injury . 21 Epidemiology . 21 Anatomy and biomechanics . 22 Treatment . 22 Outcomes after knee injury . 23 Patient-reported outcomes measures . 24 Measures of physical performance . 25 Patient-reported outcomes or physical performance? 26 Measurement properties of outcome measures . 27 Rationale of the thesis . 30 Aims of the thesis . 33 Overall aims . 33 Specific aims . 33 Methods . 35 Study designs and cohorts . 35 The Knee Injury data . 36 The KANON data . 38 Participants in studies I-IV . 40 Outcome measures . 41 Patient-reported outcome measures, PROMs (I-IV) . 41 Knee-specific PROMs (I-IV) . 41 Generic PROM (II) . 43 Comparative PROMs (I and II) . 43 Performance-based outcome measures (III and IV) . 45 Translation and cross-cultural adaptation of the ARS . 47 Data analyses . 48 Studies I and II. 49 Study III . 50 Study IV . 50 Ethics . 51 Results . 53 Study I . 53 Translation, cross-cultural adaptation and validation of the ARS . 53 Studies I and II . 55 Responsiveness of knee-specific and generic PROMs . 55 Studies III and IV . 56 Knee-specific PROs . 56 Associations between physical performance and knee-specific PROs 57 Discussion . 59 Evaluation of measurement properties . 59 Cross-cultural adaptation and validation of the Activity Rating Scale for disorders of the knee (ARS) . 59 Responsiveness of knee-specific and generic PROMs . 60 Associations between physical performance and knee-specific PROs . 63 Associations at 3 years after ACL injury . 63 Associations over time . 63 Associations between treatment strategy and knee-related self-efficacy after ACL injury . 66 Methodological considerations and limitations . 67 Clinical implications . 71 Conclusions . 73 Acknowledgements . 75 References . 77
Total lesion glycolysis on FDG-PET/CT before salvage surgery predicts survival in laryngeal or pharyngeal cancer

We investigated whether 18F-fluorodeoxyglucose uptake parameters using positron emission tomography combined with computed tomography predicts several survival outcomes, including lung metastasis-free survival, in patients with laryngeal or pharyngeal cancer who underwent salvage surgery. The maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis were calculated as 18F-fluorodeoxyglucose uptake parameters in 51 patients with laryngeal or pharyngeal cancer before salvage surgery. In univariate analysis, the maximum standardized uptake value ≥ 22.8, metabolic tumor volume ≥ 2.4, and total lesion glycolysis ≥ 5.4 were significantly correlated with shorter overall survival. In multivariate analysis with adjustment for clinical stage, patients with total lesion glycolysis ≥ 5.4 exhibited significantly shorter overall survival. Furthermore, total lesion glycolysis ≥ 5.4 was significantly correlated with shorter disease-specific survival, distant metastasis-free survival, and lung metastasis-free survival in univariate analysis. In conclusion, total lesion glycolysis predicts the survival outcomes including lung metastasis in patients with laryngeal or pharyngeal cancer who underwent salvage surgery.
Automatic Generation of Security Argument Graphs

Graph-based assessment formalisms have proven to be useful in the safety, dependability, and security communities to help stakeholders manage risk and maintain appropriate documentation throughout the system lifecycle. In this paper, we propose a set of methods to automatically construct security argument graphs, a graphical formalism that integrates various security-related information to argue about the security level of a system. Our approach is to generate the graph in a progressive manner by exploiting logical relationships among pieces of diverse input information. Using those emergent argument patterns as a starting point, we define a set of extension templates that can be applied iteratively to grow a security argument graph. Using a scenario from the electric power sector, we demonstrate the graph generation process and highlight its application for system security evaluation in our prototype software tool, Cyber SAGE.
ELIMINATION OF REDUNDANT EMAILS

Source code and Test data – 1 CD ii Abstract Email is using by hundred of millions of people worldwide. Unfortunately, the widespread use of email has given rise to several problems. Redundant email is one of them. In this project we are exploring a solution to that problem by examining the applicability of duplicate detection method in eliminating redundant emails. Following fingerprint technique, we have developed a Duplicate Detection component used in our email program. We also invent a new collision-free hash function that encodes more information in a single hash value. Finally we present and discuss the result of our evaluation on various types of redundant emails. Several experiments conducted during the development of project are also included.
Reliability-Centric Analysis of Offloaded Computation in Cooperative Wearable Applications

Motivated by the unprecedented penetration of mobile communications technology, this work carefully brings into perspective the challenges related to heterogeneous communications and offloaded computation operating in cases of fault-tolerant computation, computing, and caching. We specifically focus on the emerging augmented reality applications that require reliable delegation of the computing and caching functionality to proximate resource-rich devices. The corresponding mathematical model proposed in this work becomes of value to assess system-level reliability in cases where one or more nearby collaborating nodes become temporarily unavailable. Our produced analytical and simulation results corroborate the asymptotic insensitivity of the stationary reliability of the system in question (under the “fast” recovery of its elements) to the type of the “repair” time distribution, thus supporting the fault-tolerant system operation.
A remedy design of PI controller for liquid level control

In the industrial, the level of liquid control in the tank is important. Level control in the tank can be done by manipulating the liquid flow rate, in order to obtain the appropriate level of the liquid set point. For that required selection of control mode and tuning method accordingly. Despite its popularity, PI (Proportional-Integral) control tuned with Ziegler-Nichols method, suffers from weird oscillation. In this paper, a remedy for PI controller is proposed with and the St. Clair method. As results, based on the level control of manipulated value (MV), the output trend is obtained with 0% oscillation change, the rise time is 1.71 seconds, and the settling time is 4.9 seconds. It shows a level control system with PI control and St. Clair is able to make the system stable against MV.
Understanding User Tradeoffs for Search in Encrypted Communication

End-to-end message encryption is the only way to achieve absolute message privacy. However, searching over end-to-end encrypted messages is complicated. Several popular instant messaging tools (e.g., WhatsApp, iMessage) circumvent this inconvenience by storing the search index locally on the devices. Another approach, called searchable encryption, allows users to search encrypted messages without storing the search index locally. These approaches have inherent tradeoffs between usability and security properties, yet little is known about how general users value these tradeoffs, especially in the context of email rather than instant messaging. In this paper, we systematize these tradeoffs in order to identify key feature differences. We use these differences as the basis for a choice-based conjoint analysis experiment focused on email (n=160), in which participants make a series of choices between email services with competing features. The results allow us to quantify the relative importance of each feature. We find that users indicate high relative importance for increasing privacy and minimizing local storage requirements. While privacy is more important overall, local storage is more important than adding additional marginal privacy after an initial improvement. These results suggest that local indexing, which provides more privacy, may often be appropriate for encrypted email, but that searchable encryption, which limits local storage, may also hold promise for some users.
Immunoinformatic Approaches in Epitope Prediction for Vaccine Designing against Viral infections

Epitope prediction of immunogens using bioinformatic approaches is supposed to bring a revolution in vaccine development. Computer based prediction tools has reduced both the number of validation experiments and time for epitope prediction. A number of epitope prediction tools are now available on the web, and bioinformatics-based prediction of CTL epitopes has gained huge popularity in drug designing. For a vaccine to be successful against the viral infections, it needs to ideally stimulate humoral or cellular immune responses. The in silico search mainly focuses for individual immunogenic components that can target different arms of the immune system. Peptide based drug can be designed by targeting the protein, involved in stimulating the host cell immune system. Perspectives in this field are presented in the present review.
Craniofacial birth defects: The role of neural crest cells in the etiology and pathogenesis of Treacher Collins syndrome and the potential for prevention

Of all the babies born with birth defects, approximately one‐third display anomalies of the head and face [Gorlin et al., 1990 ] including cleft lip, cleft palate, small or absent facial and skull bones and improperly formed nose, eyes, ears, and teeth. Craniofacial disorders are a primary cause of infant mortality and have serious lifetime functional, esthetic, and social consequences that are devastating to both children and parents alike. Comprehensive surgery, dental care, psychological counseling, and rehabilitation can help ameliorate‐specific problems but at great cost over many years which dramatically affects national health care budgets. For example, the Center for Disease Control and Prevention estimates that the lifetime cost of treating the children born each year with cleft lip and/or cleft palate alone to be US$697 million. Treating craniofacial malformations, of which in excess of 700 distinct syndromes have been described, through comprehensive, well‐coordinated and integrated strategies can provide satisfactory management of individual conditions, however, the results are often variable and rarely fully corrective. Therefore, better techniques for tissue repair and regeneration need to be developed and therapeutic avenues of prevention need to be explored in order to eliminate the devastating consequences of head and facial birth defects. To do this requires a thorough understanding of the normal events that control craniofacial development during embryogenesis. This review therefore focuses on recent advances in our understanding of the basic etiology and pathogenesis of a rare craniofacial disorder known as Treacher Collins syndrome and emerging prospects for prevention that may have broad application to congenital craniofacial birth defects. © 2010 Wiley‐Liss, Inc.
In the Spotlight

Endometriosis is an estrogen-dependent inflammatory disease characterized by the presence of endometrium-like tissue growth in sites outside the uterine cavity. It is often associated with chronic pelvic pain, pain during intercourse, and infertility and is believed to afflict 5% to 10% of women of reproductive age in the United States alone. Although the etiology for the multiple variations of the disease presentation is far from being completely understood, it is generally accepted that it has both an endocrine and an immune component. The first somehow leads to the endometrial growth, which once established, progresses and promotes the development of adhesive disease powered by chronic inflammation in the peritoneal cavity. The lack of knowledge regarding the basis of endometriosis and its relationship with adhesion formation, in combination with the burden that these 2 conditions convey to the individuals affected and the society in general, has led to several studies, many of which previously published in Reproductive Sciences. Once again, in the current issue, Stocks et al revisit the topic to determine the role of the inflammatory pathway activation in the development of adhesions in an endometriosis background. Given that adhesions are commonly associated with an endometriosis diagnosis and are especially prone to occur following surgery to alleviate the disease, Stocks and colleagues used endometriosis chimeric mouse models for their study, which were ovariectomized and placed on estradiol-releasing silastic capsules. Sixteen hours following surgery, the mice received peritoneal injections of human endometrial tissue fragments or endometrial tissue conditioned media (CM) from women with or without endometriosis. A subset of mice receiving CM was also treated with interleukin-1 receptor antagonist (IL-1ra). The results obtained by Stocks and colleagues show that peritoneal injection of endometrial tissue fragments close to the time of surgery results in extensive adhesion formation, independent of the origin of the tissue received. Importantly, however, adhesion formation was significantly higher in mice receiving CM from patients with endometriosis as compared to the ones receiving CM from the controls. Interestingly, when mice were co-treated with IL-1ra, adhesion formation was dramatically decreased. In addition, cytokine bead array analysis of endometrial CM showed increased expression of IL-1b in patients with endometriosis as compared to the controls. Altogether, the data presented by Stocks and colleagues suggest that the enhanced expression of IL-1b in women with endometriosis could be at the basis of their increased susceptibility to develop postsurgical adhesions. These findings suggest that inflammatory activation mediators, in particular IL-1b, could prove to be an appropriate target to design new therapeutic strategies to prevent postsurgical adhesion formation in the peritoneal cavity of patients with endometriosis.
Monopolar capacitive coupled Radiofrequency (mcRF) and ultrasound-guided Platelet Rich Plasma (PRP) give similar results in the treatment of enthesopathies: 18-Month follow-up

Introduction: Emergent technologies, i.e., monopolar capacitive coupled Radiofrequency (mcRF) and Platelet Rich Plasma (PRP) are now available to treat conditions characterized by a failed Wound Healing Response. Both mcRF and PRP positively influence the chemical/cellular inflammatory cascade to promote healing. mcRF application results in temperature elevation at the targeted structure up to 50℃ stimulating heat shock proteins, thus inciting the Wound Healing Response. Ultrasound-guided PRP injections results in an inflammatory/reparative reaction through cytokinin release. Methods: Sixty-eight patients who have failed previous conservative treatment for tendinopathies and chronic ligament conditions of the elbow, hip, knee and ankle/foot, were treated either with mcRF or PRP. Treatments were delivered directly by the investigator, and patients were followed prospectively for an average of 19.7 months (range 15 to 24 months). Results: Average age for the mcRF cohort was 53 years (range 17 to 88). Average age for the PRP group was 58 (range 19 to 90). The male to female ratio for both groups was 1/1. 33 of 42 patients treated with mcRF experienced marked improvement (78%), while in the PRP group 19 of 26 patients experienced marked improvement (73%) as self-assessed by study subjects. Discussion/Conclusion: Results of this study are in agreement with reports on the use of both technologies; however, this is the first time that a side-by-side comparison is established. PRP and mcRF represent a new approach to musculoskeletal pathology; both modalities aim at inducing a biological response and are considered at the frontier of regenerative therapeutics. The high safety profile suggests that these, non-invasive (mcRF) and minimally invasive (PRP), office-based alternatives for the management of musculoskeletal conditions are valuable tools and should be used in accordance with a clear understanding of the underlying pathology.
Linarite – a quasi-critical J 1-J 2 chain

Eron Cemal, Mechthild Enderle, Reinhard K. Kremer, Björn F̊ak, Eric Ressouche, Mariya V. Gvozdikova, Mike E. Zhitomirsky, and Tim Ziman 5 Institut Laue-Langevin, CS 20156, 38042 Grenoble Cedex 9, France Max-Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany Université Grenoble Alpes, CEA, INAC, MEM, F-38000 Grenoble, France CEA, INAC-PHELIQS, F-38000 Grenoble, France LPMMC, UMR-5493, Université Grenoble Alpes and CNRS, 38042 Grenoble, France (Dated: June 23, 2018)
Sketch-a-Classifier: Sketch-Based Photo Classifier Generation

Contemporary deep learning techniques have made image recognition a reasonably reliable technology. However training effective photo classifiers typically takes numerous examples which limits image recognition's scalability and applicability to scenarios where images may not be available. This has motivated investigation into zero-shot learning, which addresses the issue via knowledge transfer from other modalities such as text. In this paper we investigate an alternative approach of synthesizing image classifiers: almost directly from a user's imagination, via freehand sketch. This approach doesn't require the category to be nameable or describable via attributes as per zero-shot learning. We achieve this via training a model regression network to map from free-hand sketch space to the space of photo classifiers. It turns out that this mapping can be learned in a category-agnostic way, allowing photo classifiers for new categories to be synthesized by user with no need for annotated training photos. We also demonstrate that this modality of classifier generation can also be used to enhance the granularity of an existing photo classifier, or as a complement to name-based zero-shot learning.
Multi-Instance Learning with Discriminative Bag Mapping

Multi-instance learning (MIL) is a useful tool for tackling labeling ambiguity in learning because it allows a bag of instances to share one label. Bag mapping transforms a bag into a single instance in a new space via instance selection and has drawn significant attention recently. To date, most existing work is based on the original space, using all instances inside each bag for bag mapping, and the selected instances are not directly tied to an MIL objective. As a result, it is difficult to guarantee the distinguishing capacity of the selected instances in the new bag mapping space. In this paper, we propose a discriminative mapping approach for multi-instance learning (MILDM) that aims to identify the best instances to directly distinguish bags in the new mapping space. Accordingly, each instance bag can be mapped using the selected instances to a new feature space, and hence any generic learning algorithm, such as an instance-based learning algorithm, can be used to derive learning models for multi-instance classification. Experiments and comparisons on eight different types of real-world learning tasks (including 14 data sets) demonstrate that MILDM outperforms the state-of-the-art bag mapping multi-instance learning approaches. Results also confirm that MILDM achieves balanced performance between runtime efficiency and classification effectiveness.
Doping in elite sports in Germany: results of a www survey

Abstract It is still unknown how many top-level athletes use banned drugs or practices. In a www survey, we used the randomized response technique to shed light on this issue. With the question “Have you ever used banned substances or methods in order to enhance your performance? ”, we established a lower interval limit of 25.8% and an upper limit of 48.1%. In the current season we found at the lower end of the scale 20.4% and at the upper end 38.7% of athletes who admit to using illegal drugs or methods. Throughout their whole athletic career, we calculated 51.9% honest non-dopers and in the current season 61.3%.
Scan blindness in one-layer microstrip antenna arrays

The article considers the problem of scan blindness in microstrip antenna arrays leading to the deterioration of radiation pattern for a range of scanning angles. The anticipated future wide implementation of integral antennas for mobile and fixed service communication systems with beamforming and MIMO capabilities requires the analysis of this problem and the means to combat it. Analysis of this problem and a method to determine blind scan angles are given as well as relationship between one-layer dielectric substrate parameters and element spacing is obtained and presented in the form of curves of maximum permissible scan angles.
MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content

In team-based workplaces, reviewing and reflecting on the content from a previously held meeting can lead to better planning and preparation. However, ineffective meeting summaries can impair this process, especially when participants have difficulty remembering what was said and what its context was. To assist with this process, we introduce MeetingVis, a visual narrative-based approach to meeting summarization. MeetingVis is composed of two primary components: (1) a data pipeline that processes the spoken audio from a group discussion, and (2) a visual-based interface that efficiently displays the summarized content. To design MeetingVis, we create a taxonomy of relevant meeting data points, identifying salient elements to promote recall and reflection. These are mapped to an augmented storyline visualization, which combines the display of participant activities, topic evolutions, and task assignments. For evaluation, we conduct a qualitative user study with five groups. Feedback from the study indicates that MeetingVis effectively triggers the recall of subtle details from prior meetings: all study participants were able to remember new details, points, and tasks compared to an unaided, memory-only baseline. This visual-based approaches can also potentially enhance the productivity of both individuals and the whole team.