Miracle-dz/UniFAR-FTUs huggingface dataset:
MedCo: Enabling Privacy-Conscious Exploration of Distributed Clinical and Genomic Data

Being able to share large amounts of sensitive clinical and genomic data across several institutions is crucial for precision medicine to scale up. Unfor- tunately, existing solutions only partially address this challenge and are still unable to provide the strong privacy and security guarantees required by regulations (e.g., HIPAA, GDPR). As a result, currently only very limited datasets of non-sensitive and moderately useful information can be shared. In this paper, we introduce MedCo, the first operational system that enables an investigator to explore sensi- tive medical information distributed at several sites and protected with collective homomorphic encryption. MedCo builds on top of established and widespread technology from the biomedical informatics community, such as i2b2 and SHRINE, and relies on state-of-the-art secure protocols for processing encrypted distributed data and complying with regulations. As such, MedCo can be easily adopted by clinical sites thus paving the way to new unexplored data-sharing use cases. We tested MedCo in a real network of three institutions (EPFL, UNIL and CHUV) by focusing on an oncology use-case with real somatic mutations and clinical tumor data. The relatively low overhead introduced by MedCo shows that it represents a concrete and scalable solution for sharing privacy-conscious medical data.
Real-time observation of initial stages of copper film growth on silicon oxide using reflection high-energy electron diffraction

We have studied, in real time, the evolution of a thin (less than 200A) copper film deposited onto an oxidized silicon surface using reflection high-energy electron diffraction. We show that quantitative measurements of island size and shape as functions of time are possible and the results are presented. While the film texture is initially random, texture competition leads to an absence of the low-energy (111) and (200) oriented grains for later times. It is also found that the film surface is composed of facets that increase in size with time. This behavior is explained in terms of facet coalescence.
Scaling laws for the slumping of a Bingham plastic fluid

Bingham plastics exhibit complex behaviors, depending on both geometrical and rheological factors, and are difficult to characterize systematically. This is particularly true in the case of transient flows, where solidlike and fluidlike behaviors coexist in an intermittent fashion. The aim of this contribution is to study the slump of Bingham columns under gravity, while varying systematically and independently both the geometry of the system and the rheological parameters. To do so, numerical experiments are carried out in two dimensions with a non-Newtonian Navier–Stokes code, the Gerris flow solver, using a volume-of-fluid approach. We are able to determine the slump height and the spreading of the column after motion ceased. These characteristics are related to the rheological properties and initial shape through scaling relationships. The results are compared with previous scalings and prediction from the literature. A discussion ensues on the importance of the normalization choice and of unambiguous.
Operative Outcome of Interlocking Intramedullary Nailing With Reaming for the Treatment of Open Tibial Shaft fractures : A Clinical Study

Context: Compound fractures of tibia pose a significant challenge to orthopaedic surgeons due to its precarious blood supply, subcutaneous location and poor soft tissue coverage, leading to various complications. This study evaluates the operative outcomes of interlocking intramedullary nailing with reaming for open tibial shaft fractures. Aims: To study the clinical, radiological and functional outcomes, and complications associated with the procedure. Materials and methods: Interlocking Intramedullary Nailing of 30 cases of open tibialdiaphyseal fractures and evaluation of the results. Statistical Analysis Used:Patients evaluated clinically and radiologically, at regular intervals. Results: Out of 30 patients, according to the Lysholm Knee Scoring system, 20 cases had excellent, 8 had good, and 2 had fair outcomes. Radiological union was achieved in 17-20 weeks. Complication rate was 16.67%. Conclusions: Reamed intramedullary nailing for treatment of open tibial shaft fractures is an excellent option, producing biomechanical stability and facilitating rapid rehabilitation in compound diaphysealtibial fractures.
COMBINATION MATHEMATICAL DISTANCE MEASURE APPROACH FOR SOME IMAGE PROCESSING APPLICATIONS

In this paper the researcher presents a Combination mathematical Distance Measure approach for Image Encryption; it had been applied on different images . The aim of this method to protect the images by encryption them. The proposed method is depending on find a new distance between image pixels by using interpolation. The study data base consists of (40 images) of different types (color images and gray images) with different formats(. jpg, .bmp, .tif , .gif, . png ). The Proposed method gave more accurate results, stronger encoding of images and high encryption efficiency via using the performance evaluation factors to evaluate labor standards and proved the successfulness of this high encryption ratios method of. MATLAB® 2010 software had been highly relied in this study.
Phylogenomic reconstruction of transcriptome data confirms the basal position of Prodoxidae moths within the order Lepidoptera

Yucca moths (Prodoxidae) have long been considered by taxonomists to be basally positioned within the Lepidoptera in the superfamily Adeloidea. Recently, phylogenomic reconstructions of ordinal lepidopteran relationships using transcriptome data confirmed the basal position of the Adeloidea and the positioning of the Tegeticula pollinating yucca moths within the superfamily. However, to date, no phylogenetic studies have been conducted attempting to position the Prodoxus bogus yucca moths using whole genome data. We incorporated our own transcriptome libraries into publicly available lepidopteran data in order to phylogenetically confirm the evolutionary position of the Prodoxidae within the Lepidoptera and to assess the position of Prodoxus relative to Tegeticula. Our phylotranscriptomic reconstruction verified the Prodoxidae as the sister taxa to the basal Adelidae (Adeloidea), and Prodoxus as sister to Tegeticula. However, topological relationships among our four focal Tegeticula species contradicted recent findings from RAD-seq analyses. We show that this apparent paradox is in fact an artefact of the phylogenetic methods employed in building the ordinal level phylogeny (i.e. sequence alignment based on the first two nucleotide positions only) and that the true Tegeticula relationships are recovered by using all three nucleotide base positions to correctly infer more recent evolutionary events. Our work shows the utility of next-generation sequencing (NGS) technologies whilst highlighting some technical considerations that may confound phylogenetic interpretation according to taxonomic scale. We add to the growing consensus that NGS techniques offer a prime opportunity to elucidate previously challenging questions in evolutionary biology.
Exploring Architectures for CNN-Based Word Spotting

The goal in word spotting is to retrieve parts of document images which are relevant with respect to a certain user-defined query. The recent past has seen attribute-based Convolutional Neural Networks take over this field of research. As is common for other fields of computer vision, the CNNs used for this task are already considerably deep. The question that arises, however, is: How complex does a CNN have to be for word spotting? Are increasingly deeper models giving increasingly better results or does performance behave asymptotically for these architectures? On the other hand, can similar results be obtained with a much smaller CNN? The goal of this paper is to give an answer to these questions. Therefore, the recently successful TPP-PHOCNet will be compared to a Residual Network, a Densely Connected Convolutional Network and a LeNet architecture empirically. As will be seen in the evaluation, a complex model can be beneficial for word spotting on harder tasks such as the IAM Offline Database but gives no advantage for easier benchmarks such as the George Washington Database.
PIDS: A Behavioral Framework for Analysis and Detection of Network Printer Attacks

Nowadays, every organization might be attacked through its network printers. The malicious exploitation of printing protocols is a dangerous and underestimated threat against every printer today. This article presents PIDS (Printers’ IDS), an intrusion detection system for detecting attacks on printing protocols. PIDS continuously captures various features and events obtained from traffic produced by printing protocols in order to detect attacks. As part of this research, we conducted thousands of automatic and manual printing protocol attacks on various printers and recorded thousands of the printers’ benign network sessions. Then we applied various supervised machine learning algorithms to classify the collected data as normal (benign) or abnormal (malicious). We evaluated several detection algorithms in order to obtain the best detection results for malicious protocol traffic of printers. Our empirical results suggest that the proposed framework is effective in detecting printing protocol attacks, providing an accuracy of 99.9 with negligible false-positive rate.
Fictional Narratives 1 Running Head : Fictional narratives cultivate Fictional Narratives Cultivate Just World Beliefs

Cultivation research has identified several misrepresentations on television, and has shown that the more people watch TV, the more their beliefs correspond to the TV world. In recent years, experimental research has demonstrated that fictional narratives are powerful means to change audience beliefs. Theories on the narrative structure of fictional narratives and disposition-based theories of media enjoyment suggest that televised fictional narratives tend to portray the world as a just place. We propose that the amount of fiction watched on television predicts the belief in a just world (BJW). Further, we assume this effect to be compatible with the television use/mean world relationship expressed by cultivation theory. Two cross-sectional studies with N = 128 participants (German sample) and N = 387 participants (Austrian sample) corroborate our assumptions. The self-reported frequency of watching fiction on television was positively related to the BJW, while the general amount of television viewing was positively related to mean and scary world-beliefs. In the German sample, mean world beliefs were also affected by viewing tabloid-style (infotainment) television news.
Tech Report : Efficient Covering for Top-k Filtering in Content-Based Publish / Subscribe Systems

Large-scale applications require a scalable data dissemination service with advanced filtering capabilities. We propose the use of a content-based publish/subscribe system with support for top-k filtering in the context of such applications. We focus on the problem of top-k subscription filtering, where a publication is delivered only to the k best ranked subscribers. The naive approach to perform filtering early at the publisher edge works only if complete knowledge of the subscriptions is available, which is not compatible with the well-established covering optimization in scalable content-based publish/subscribe systems. We propose an efficient rank-cover technique to reconcile top-k subscription filtering with covering. We extend the covering model to support top-k and describe a novel algorithm for forwarding subscriptions to publishers while maintaining correctness. We also establish a framework for supporting different types of ranking semantics and propose an implementation to support fairness. Finally, we compare our solutions to a baseline covering system and perform sensitivity analysis to demonstrate that our optimized rank-cover algorithm retains both covering and fairness while achieving properties advantageous to our targeted workloads. Our optimized solution is scalable and provides over 81% of the covering benefit when k is set at 1% selectivity.
1 Modeling Analytical Streams for Social Business 2 Intelligence 3

Social Business Intelligence (SBI) enables companies to capture strategic information 9 from public social networks. Contrary to traditional Business Intelligence (BI), SBI has to face the 10 high dynamicity of both the social network contents and the company analytical requests, as well 11 as the enormous amount of noisy data. Effective exploitation of these continuous sources of data 12 requires efficient processing of the streamed data to be semantically shaped into insightful facts. In 13 this paper, we propose a multidimensional formalism to represent and evaluate social indicators 14 directly from fact streams derived in turn from social network data. This formalism relies on two 15 main aspects: the semantic representation of facts via Linked Open Data and the support of 16 OLAP-like multidimensional analysis models. Contrary to traditional BI formalisms, we start the 17 process by modeling the required social indicators according to the strategic goals of the company. 18 From these specifications, all the required fact streams are modeled and deployed to trace the 19 indicators. The main advantages of this approach are the easy definition of on-demand social 20 indicators, and the treatment of changing dimensions and metrics through streamed facts. We 21 demonstrate its usefulness by introducing a real scenario user case in the automotive sector. 22
Bid Expression Network Controls Neuronal Cell Fate During Avian Ciliary Ganglion Development

Avian ciliary ganglion (CG) development involves a transient execution phase of apoptosis controlling the final number of neurons, but the time-dependent molecular mechanisms for neuronal cell fate are largely unknown. To elucidate the molecular networks regulating important aspects of parasympathetic neuronal development, a genome-wide expression analysis was performed during multiple stages of avian CG development between embryonic days E6 and E14. The transcriptome data showed a well-defined sequence of events, starting from neuronal migration via neuronal fate cell determination, synaptic transmission, and regulation of synaptic plasticity to growth factor associated signaling. In particular, we extracted a neuronal apoptosis network that characterized the cell death execution phase at E8/E9 and apoptotic cell clearance at E14 by combining the gene time series analysis with network synthesis from the chicken interactome. Network analysis identified TP53 as key regulator and predicted involvement of the BH3 interacting domain death agonist (BID). A virus-based RNAi knockdown approach in vivo showed a crucial impact of BID expression on the execution of ontogenetic programmed cell death (PCD). In contrast, Bcl-XL expression did not impact PCD. Therefore, BID-mediated apoptosis represents a novel cue essential for timing within CG maturation.
Map design for visually impaired people: past, present, and future research

Orientation and mobility are amongst the most important challenges for visually impaired people. Tactile maps can provide them with spatial knowledge of their environment, thereby reducing fear related to travelling in space. To date, raised-line paper maps have been used to make geographic information accessible, but these paper maps have significant limitations with regards to content and the presentation of information. Recent advances in technology may help to design usable interactive maps that overcome such limitations. In this paper, we first review different accessible map concepts. We then present our design of an interactive map prototype, and provide evidence of this interactive map's high user satisfaction and efficiency as compared to a regular raised-line paper map. To conclude, we suggest that advances in interactive technologies (e.g., haptic touch surfaces) provide a unique opportunity to design usable maps in the near future.
Spatial Information Based Image ClassificationUsing Support Vector Machine

Segmentation and classification of images are major task of remote sensing. Active learning approach in combination with machine learning is recently developing for classification of such satellite images. It optimizes the task of collecting the training set samples used for classification. In this paper, a support vector machine is developed for image classification without using active learning approach and with using active learning approach and their performance is compared. Present classification approaches concentrates on spectral features of the image. But for SVM with active learning, we adopt two criteria: spectral and spatial. Experiments are made using high resolution spectral images and the effectiveness of active learning algorithm using both spectral and spatial criteria is observed.
INFORMAL AND FORMAL CARE AMONG SINGLE-LIVING ELDERLY IN EUROPE

K. BOLIN, B. LINDGREN and P. LUNDBORG* LUCHE (Lund University Centre for Health Economics), Lund, Sweden Department of Health Sciences, Lund University, Lund, Sweden Vårdal Institute, Lund University, Lund, Sweden Department of Economics, Lund University, Lund, Sweden e Institute of Economic Research, Lund University, Lund, Sweden Department of Economics, Free University, Amsterdam, The Netherlands Tinbergen Institute, Amsterdam, The Netherlands NETSPAR, The Netherlands
Egg load as a major source of variability in insect foraging and oviposition behavior

Foraging and oviposition behavior of insects directly influences offspring production and fitness, and is therefore particularly amenable to analysis with optimization models. These models have identified two general constraints on female fitness: host availability and egg complement. Research on insect oviposition has thus far focused on external, environmentally-derived cues such as host density and quality. Here we review recent studies and suggest that insects adjust their foraging and oviposition behavior in response to their perceived risk of becoming egg limited
The anti-AChE and anti-proliferative Activities of Glaucium acutidentatum and Glaucium corniculatum Alkaloid Extracts -

In this study, methanol and water extracts of Glaucium acutidentatum and Glaucium corniculatum were analysed for anti-AChE activity on neuronal PC12 cell and anti-proliferative activity on HT-29 and HeLa cancer cells. In this study, total alkaloid, phenol and flavonoid content were analyzed for the determination of active compounds of Glaucium acutidentatum and Glaucium corniculatum. Indeed, methanol and water alkaloid extracts of these plants were evaluated for their anti-AChE activities on NGF-differentiated PC12 cells (dPC12) and anti-proliferative activities on HT-29 and HeLa cancer cells. Our data showed that alkaloid was major compound, the different concentrations of plant extracts had 35-90% in vitro AChE inhibitory activity and 26-54% cellular AChE inhibitory activity and it is dose dependent manner. Furthermore, G. acutidentatum methanolic extracts showed the highest anti-proliferative activity in HT-29 cells (45±5%) Both 1000 μg/ml methanolic extracts showed the maximum anti-proliferative effect in HeLa cells (64±3%). In conclusion, this study has shown that the anti-AChE and anti-proliferative effects of these two plants and the presence of a new AChEi may be effective in AD and cancer.
Improving multidimensional recommender systems using dimensions as virtual items

The first multidimensional algorithm for recommender systems is the well known combined reduction-based, which treats additional dimensions as labels for segmenting/filtering sessions, using the segmented sessions to build the recommendation model. This algorithm only uses the additional dimensions when it outperforms the traditional two-dimensional algorithm. Otherwise, it reverts to the traditional two-dimensional algorithm to generate the top-N recommendations. In this paper, we propose to improve the combined reduction-based algorithm by using the DaVI approach, which handles additional dimensions as virtual items. Incorporating the DaVI approach into the combined reductionbased, the multidimensional algorithm uses the additional dimensions not only as labels for segmenting sessions but also as virtual items to improve the recommendation model. The empirical results demonstrate that our proposal reduces the needs of reverting to the traditional two-dimensional algorithm to generate the top-N recommendations, increasing the performance of the combined reduction-based algorithm.
Age and size of migrating Atlantic salmon, Salmo salar L., and sea trout, Salmo trutta L., smolts in Lithuanian rivers

Abstract The aim of the present study was to determine the mean size and age of migrating salmon, Salmo salar L. , and sea trout, Salmo trutta L. , smolts in three rivers of the Nemunas River drainage area from different climatic sub-regions in Lithuania. Research indicates there were significant differences of migrating fish age and size between stocked and natural smolt populations. In natural populations salmon and sea trout smolts aged 2+ dominated, but up to 82% of all migrating smolts of the stocked population in Siesartis River were aged 1+. The artificially-reared salmon and sea trout smolts in the Siesartis River were significantly larger than wild fish in the 1+ age group of migrants, and, accordingly, they reached smolt size and were ready to migrate earlier. The high density of salmonid parrs in the Siesartis River and intraspecific competition could have also prompted 1+ age group smolts to migrate. It is hypothesized that the phenomenon of early smolt migration in the Siesartis River could have been a local adaptation to the long migration route, or it could have resulted from density-dependent competition caused by imbalanced stocking programs.
Ranking Rate Control and Rhythm Control Therapies for Heart Failure Patients With Atrial Fibrillation: A Network Meta-Analysis of Randomized Controlled Trials

Background: Rate control and rhythm control have demonstrated similar benefits for heart failure (HF) patients with atrial fibrillation (AF), but no study has attempted to rank their benefits. We aim to conduct a network metaanalysis of the efficacies of rate control and rhythm control therapies for HF patient with AF. Methods: We searched PubMed, Embase, and Cochrane Library with various combinations of “rate control”, “rhythm control”, “atrial fibrillation” and “heart failure”. The retrieved records were screened by “Patient- Intervention-Control-Outcome” principle. The eligible randomized controlled trials were extracted for basic characteristics, outcomes data, and synthesized with random-effects model. Results: Eleven trials involving 2,086 patients and 8 rate control and rhythm control therapies were included. The interventions for all-cause mortality reduction were ranked as follows: catheter ablation (mean rank [MR] 2.3, surface under the cumulative ranking curves [SUCRA] 81.1%), atrioventricular node ablation and pacemaker (MR 3.1, SUCRA 70.0%), β-blocker (MR 3.9, SUCRA 58.8%), optimal medical treatment (MR 3.9, SUCRA 57.9%), amiodarone (MR 4.3, SUCRA 52.9%), placebo (MR 4.5, SUCRA 50.3%), digoxin (MR 6.8, SUCRA 16.7%), β- blocker and/or digoxin (MR 7.1, SUCRA 12.2%). Conclusion: In HF patients with AF, catheter ablation may be the most effective therapy for rate control and rhythm control, while digoxin is probably harmful.