Miracle-dz/UniFAR-FTUs huggingface dataset:
Cancer-specific survival by stage of bladder and urinary tract cancers and factors collected by Mallorca Cancer Registry associated to survival.

Background: Information about survival by stage in bladder cancer is scarce. Objectives: 1) to find out the distribution of bladder and urinary tract cancers by stage; 2) to determine cancer-specific survival by stage of bladder and urinary tract cancers; 3) to identify factors that explain and predict the likelihood of survival and the risk of dying from these cancers.Methods: Incident bladder and urinary tract cancer cases diagnosed between 2006 and 2011 were identified through the Mallorca Cancer Registry. Inclusion criteria: cases with codes C65–C68 (ICD-O 3) with any behaviour. DCO cases were excluded. We collected: sex; age; date and method of diagnosis; histology (ICD-O 3); T, N, M and stage at the time of diagnosis; and date of follow-up or death. End of follow up was 31 December 2015. Multiple imputation (MI) was performed to estimate cases with unknown stage. Actuarial and Kaplan-Meier methods and Cox regression models were used.Results: 2060 cases were identified. 15% were women and 65.2% were 65 years or older. 3.7% had no stage (benign or undetermined behaviour) and 12.5% had unknown stage. After MI, 35.7% were in stage Ta (non-invasive papillary carcinoma), 3.1% in stage Tis (carcinoma in situ), 33.3% in stage I, 11.9 % in Stage II, 4.7% in stage III, and 11.1% in stage IV. Survival was 73% at 5 years. Survival by stage: 98% at stage Ta, 88% at stage Tis, 84% at stage I, 44% at stage II, 33% at stage III, and 7% at stage IV. The Cox model showed that age, histology, and stage were associated with survival.Conclusion: Bladder and urinary tract cancers survival vary greatly with stage. The percentage of non-invasive cancers was high. Stage, age and histology are associated to survival, but sex has no association.
DOT1L Methyltransferase Activity Preserves SOX2-Enhancer Accessibility And Prevents Activation of Repressed Genes In Murine Stem Cells

Background During cellular differentiation, the chromatin landscape changes dynamically and contributes to the activation of cell-type specific transcriptional programs. Disruptor of telomeric silencing 1-like (DOT1L) is a histone methyltransferase that mediates mono-, di- and trimethylation of lysine 79 of histone H3 (H3K79me1, 2, 3). Its enzymatic activity is critical for driving cellular differentiation into cardiomyocytes, chondrocytes and neurons, from embryonic or other type of stem cells in physiological settings. Ectopic localization of DOT1L in MLL-rearranged leukemias is causative for leukemogenesis and relapse. Little is known about the causal relevance of DOT1L methyltransferase activity in the global chromatin context and how its enzymatic function affects transcriptional and global chromatin states. Recent reports conducted in leukemia cell models have suggested that deposition of H3K79me2 may be critical to preserve histone H3K27 acetylation (ac) and enhancer activity, and to sustain expression of highly transcribed genes. If and to what extent DOT1L affects chromatin states and enhancer activity during physiological differentiation processes is currently unknown. Results We measure global changes of seven histone modifications during the differentiation process via high-throughput and quantitative ChIP-seq in an in-vitro neuronal differentiation model of mouse embryonic stem cells (mESC). We observe that H3K27ac globally decreases, whereas H3K79me2 globally increases during differentiation, while other modifications remain globally unaltered. Pharmacological inhibition of DOT1L in mESC and mESC-derived neural progenitors results in decreased expression of highly transcribed genes and increased expression of normally repressed genes. Acute DOT1L inhibition primes neural progenitors towards a mature differentiation state. Transcriptional downregulation associates with decreased accessibility of enhancers specifically bound by the master regulator SOX2. Conclusions In-vitro neuronal differentiation couples with a genome-wide accumulation of H3K79me2, never described previously in mammalian cells. Acute inhibition of DOT1L is sufficient to initiate a defined transcriptional program, which biases the transcriptome of neural progenitor cells towards neuronal differentiation. H3K79me2 is not generally causative for maintaining transcriptional levels at a genome-wide scale. In contrast, DOT1L inactivation reduces the chromatin accessibility of enhancers bound by SOX2 in-vivo, thereby reducing the expression level of a restricted number of genes. Our work establishes that DOT1L activity gates differentiation of progenitors by allowing SOX2-dependent transcription of stemness programs.
A direct sampling method to an inverse medium scattering problem

In this work we present a novel sampling method for time harmonic inverse medium scattering problems. It provides a simple tool to directly estimate the shape of the unknown scatterers (inhomogeneous media), and it is applicable even when the measured data are only available for one or two incident directions. A mathematical derivation is provided for its validation. Two- and three-dimensional numerical simulations are presented, which show that the method is accurate even with a few sets of scattered field data, computationally efficient, and very robust with respect to noises in the data.
MARINE BIOLOGY Summer Bloom of Coccolithophorids in the Northeastern Black Sea

On the basis of the observations performed in June–July 2004, the main parameters of the coccolithophorid blooming are described. Emiliania huxleyi was the dominant species. Its maximum abundance amounted to 1.5–6.0 × 10 6 cells l –1 . High concentrations occurred throughout the entire area studied (up to 70 miles from the shore). The main share of the population was confined to a thin upper mixed layer. The population of this alga is characterized by two types of cells: calcified (with coccoliths) and naked (lacking coccoliths). Cells of the latter type were mainly observed under the seasonal pycnocline layer, while those of the former type prevailed in the surface layer. The coccolithophorid biomass in the surface layer averaged 180 mg/m 3 throughout the study area. Experiments aimed at determining the dark adaptation of phytoplankton revealed no inhibition of photosynthesis in the upper water layers under coccolithophorid domination. Experimental data indicate a dependence of the Emiliania huxleyi population development on the phosphorus concentrations.
Analysis on Students’ Computer Self-Efficacy Instrument

Abstract This study aims to investigate students’ computer self-efficacy in online education in sociology course at the Department of Educational Technology, Faculty of Education Science, Universitas Negeri Makassar. This paper reports analysis of an instrument used in our study. The instrument in this present study was developed to measure computer self-efficacy of students in online education. The instrument of the study was adapted from Computer User Self-Efficacy (CUSE) scale. The instrument was measured by weighting the scale, testing the validity and the reliability. The measurement result shows that 15 items were dismissed because it has no fixed scale intervals. The validity score of the instrument is valid because it is above 0.30. The research scale is moving from 0.336 to 0.747. Furthermore, all items in the computer self-efficacy instrument are reliable since the Cronbach's Alpha coefficient (0.930) is 0.7. Keywords: instrument analysis, computer self-efficacy, instrument development, cuse scale
Successful Sweep Jamming Rate Determination of MPSK Modulated RCIED Activation Message Signals

This paper presents the development of the method for accurate successful jamming rate calculation when MPSK modulated RCIED activation message is jammed using sweep signal. Opposite to classical methods of error modelling where it is taken that only one bit in a symbol may be altered, it is supposed in this paper that any number of bits in a symbol is the subject of eventual modification. The derived formulas are achieved for QPSK, 8PSK and 16PSK modulated signals jamming. The results calculated by these formulas are verified and obtained by our originally developed simulation method. The results of calculation and simulation agree very well and the maximum difference between calculated and simulated successful jamming rate for any of three analyzed jamming methods and any level ratio between activation message signal and jamming signal does not overcome 1.1%. It is proved that successful jamming rate tends to maximum value 0.5 when jamming signal power increases and that only 20% lower successful jamming rate value is obtained for less than 7dB higher jamming signal level than it is the level of RCIED activation signal. These results point out that it is not necessary to apply too high emission power to achieve acceptable jamming effect. As a consequence, jammer practical implementation is easier and its dimensions are smaller.
A Hybrid Technique for Brain Tumor Detection and Classification

Brain tumors unapologetically kill if not detected and treated on time. Early detection is crucial because of their rapid and inconsistent growth rate but is difficult as symptoms appear clearly only in the advanced stages. MRI provides complete image of the brain structure. Optimal brain tumor segmentation and feature extraction gives us all the required information such as size, type and location of the tumor, which leads to proper diagnosis and treatment. This paper puts forth a methodology encompassing the essential sequence of algorithms for detection, segmentation and classification of brain tumors as well as includes a fused method for pre- processing , which is then followed by the use of adaptive k-means for segmentation. Furthermore, Morphological operations are performed and finally we conclude by feature extraction with GLCM and classification using a PNN.
An Overview on Sentiment Mining for Stock Market prediction

A growing body of research and practical applications employ social media data as a proxy for the complex behavior of investors in financial markets. This paper provides an overview of academic research related to the link between social media and financial markets in order to give insight into future works and challenges on investor sentiment analysis. The theoretical rationale of this relationship is predominantly defined by behavioral finance. Behavioral finance shows that emotions have a considerable impact on individual behavior. Researchers of this discipline contradict the standard model of efficient markets and considers irrational factors like investors sentiment and public mood as influential for asset pricing and financial market volatility. In this context, social media is a novel tool enabling the collection of data about such behavioral factors.
Cryptanalysis of Protocol for Heterogeneous Wireless Sensor Networks for the Internet of Things Environment

Access and connectivity to everything on the Inter-net of Things are closely tied to the wireless sensor network environment. In an IoT environment, a user can access a desired single sensor node without first connecting to the gateway node. Chen et al. proposed an efficient and safe protocol in this environment. Unfortunately, their plans have security weakness.We describe the protocol proposed by Chen et al. and describe two attack techniques for that protocol. The first is that it is vulnerable to password guessing attacks. Also, their protocols cannot defend against session key attacks. Finally, this paper proves that the target protocol is unsafe.
On Efficient Concatenation of LDPC Codes With Constrained Codes

In this article, an efficient concatenation of error correction codes with constrained codes is proposed. Generally, constrained codes are designed to match specified channels, whereas error correction coding schemes are designed to correct the channel errors. Both play important roles to ensure the integrity of data in data storage systems. In this study, we first investigate the design of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-constrained codes combined with a low-density parity-check (LDPC) code, and then we extend the idea to the design of dc-free <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-constrained LDPC codes. Simulation results show that the proposed designs achieve an improved bit error rate (BER) performance, compared to prior art schemes. In particular, the proposed design for the dc-free <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-constrained codes not only fully eliminates the effect of error propagation in a reverse configuration but also achieves significant dc suppression.
Onboard Detection and Localization of Drones Using Depth Maps

Obstacle avoidance is a key feature for safe drone navigation. While solutions are already commercially available for static obstacle avoidance, systems enabling avoidance of dynamic objects, such as drones, are much harder to develop due to the efficient perception, planning and control capabilities required, particularly in small drones with constrained takeoff weights. For reasonable performance, obstacle detection systems should be capable of running in real-time, with sufficient field-of-view (FOV) and detection range, and ideally providing relative position estimates of potential obstacles. In this work, we achieve all of these requirements by proposing a novel strategy to perform onboard drone detection and localization using depth maps. We integrate it on a small quadrotor, thoroughly evaluate its performance through several flight experiments, and demonstrate its capability to simultaneously detect and localize drones of different sizes and shapes. In particular, our stereo-based approach runs onboard a small drone at 16 Hz, detecting drones at a maximum distance of 8 meters, with a maximum error of 10% of the distance and at relative speeds up to 2.3 m/s. The approach is directly applicable to other 3D sensing technologies with higher range and accuracy, such as 3D LIDAR.
Three-Dimensional Imaging of Selenium and Chlorine Distributions in Highly Efficient Selenium-Graded Cadmium Telluride Solar Cells

Thin-film solar modules based on cadmium telluride (CdTe) technology currently produce the world's lowest cost solar electricity. However, the best CdTe modules now contain a cadmium selenium telluride (CST) alloy at the front of the absorber layer. Despite this, research characterizing the behavior of selenium in alloyed CdTe devices is currently very limited. Here we employ advanced secondary ion mass spectrometry measurements to map the three-dimensional distribution of selenium in a graded CST/CdTe device for the first time. We find significant interdiffusion of selenium between the CST and CdTe layers in the cell, primarily out of the CST grain boundaries and up into the CdTe grain boundaries and grain fringes above. This results in significant lateral variations in selenium concentrations across grains and hence also lateral fields, which we estimate using the measured selenium concentrations.
A Survey on Ad Hoc Signal Processing: Applications, Challenges and State-of-the-Art Techniques

In an era of ubiquitous digital devices with built-in microphones and recording capability, distributed microphone arrays of a few digital recording devices are the emerging recording tool in hands-free speech communications and immersive meetings. Such so-called ad hoc microphone arrays can facilitate high-quality spontaneous recording experiences for a wide range of applications and scenarios, though critical challenges have limited their applications. These challenges include unknown and changeable positions of the recording devices and sound sources, resulting in varying time delays of arrival between microphones in the ad hoc array as well as varying recorded sound power levels. This paper reviews state-of-the-art techniques to overcome these issues and provides insight into possible ways to make existing methods more effective and flexible. The focus of this paper is on scenarios in which the microphones are arbitrarily located in an acoustic scene and do not communicate directly or through a fusion centre.
A Soft Pressure Sensor Skin for Hand and Wrist Orthoses

Side effects caused by excessive contact pressure such as discomfort and pressure sores are commonly complained by patients wearing orthoses. These problems leading to low patient compliance decrease the effectiveness of the device. To mitigate side effects, this study describes the design and fabrication of a soft sensor skin with strategically placed 12 sensor units for static contact pressure measurement beneath a hand and wrist orthosis. A Finite Element Model was built to simulate the pressure on the hand of a subject and sensor specifications were obtained from the result to guide the design. By testing the fabricated soft sensor skin on the subject, contact pressure between 0.012 MPa and 0.046 MPa was detected, revealing the maximum pressure at the thumb metacarpophalangeal joint which was the same location of the highest pressure of simulation. In this letter, a new fabrication method combining etching and multi-material additive manufacture was introduced to produce multiple sensor units as a whole. Furthermore, a novel fish-scale structure as the connection among sensors was introduced to stabilize sensor units and reinforce the soft skin. Experimental analysis reported that the sensor signal is repeatable, and the fish-scale structure facilitates baseline resuming of sensor signal during relaxation.
Intelligent Reflecting Surface-aided Phase-Shift Backscatter Communication

Intelligent reflecting surface (IRS) is a 2D surface made up of metasurface, on which passive elements such as varactor diodes interact with incoming electromagnetic waves and manipulate them to behave according to user objectives. Ambient backscatter communication (AmBC) utilizes both ambient RF source and spectrum without additional infrastructure. In this paper, we propose a system that integrates AmBC with IRS technology to overcome the fundamental coverage limitation of conventional backscatter communications. Specifically, we replace the antenna-switching tag with such IRS elements. As IRS is already known to aid in passive beamforming and relaying, we aim to enable secondary information transmission while relaying primary information. A novel idea here is splitting the primary transmitter power to send additional unmodulated carrier along with its message signal. We maximize the spectrum efficiency of the secondary system subject to the minimum spectrum efficiency of the primary system through optimization of the power-splitting factor. Numerical results validate that the IRS-aided backscatter system outperforms conventional ones.
Inferring Human Brain Structural Connectivity Based on Neural Networks

A central and fundamental issue in cognitive neuroscience is to comprehend the relationship between human brain functional and structural connectivity. Previous studies normally focus on the relationship by predicting functional connectivity from structural connectivity and show there is a cohesive correlation between the two types of networks. In this paper, we investigate the relation by revealing the true anatomical connections from the functional correlations using multi-layer neural networks, which is trained to learn the intrinsic mapping mechanism and recover some missed connections with diffusion magnetic resonance imaging (dMRI) tractography, particularly the cross-hemispheric homotopic connections. We execute the method to a dataset with 246 brain areas acquired from 147 subjects. The results show that around 65% of the average intrahemispheric structural connections are correctly inferred.
Artificial Intelligence based Intelligent Storage Device for Commoners

An exhaustive investigation has been performed in the field of artificial intelligent since last few decades. Moreover, sophisticated gadgets have also been designed based on those algorithms in an efficient fashion. In this article, an intelligent model is designed to reduce food wastage and hunger problem in a competent fashion. A hardware model of a refrigerator is also made where the needy commoners can come and take food they need to fulfil their hunger. The model only responds if a human stands in front of it. If it finds any other living creature other than human is standing then it shows no response. Furthermore, system exhibits no response if same human being appears twice within next 12 hours.
Three-Terminal Tandem Solar Cells With a Back-Contact-Type Bottom Cell Bonded Using Conductive Metal Nanoparticle Arrays

To address three-terminal tandem solar cells composed of a back-contact-type Si bottom cell, which, in principle, has a tolerance against spectral variation, we fabricate the three-terminal GaAs/Si tandem device bonded using conductive metal nanoparticle arrays and measure the power extraction. A power equivalent to the sum of the power generated by the top and bottom subcells is extracted even under varying spectral conditions, which indicates advantages in three-terminal tandem solar cells with a back-contact-type bottom cell for terrestrial applications.
Clinical Trial Simulation: Modeling and Practical Considerations

As clinical trials are increasingly globalized with complex footprints over hundreds of sites worldwide, sponsors and contract research organizations constantly seek to make better and faster decisions on their investigational products, and drug supply planning must evolve to ensure efficient, effective supply chain for every study. This endeavor is challenging due to unique characteristics of multi-center trials including randomization schemes for multiple treatment arms, finite recruitment target (that is, across all sites, only a finite number of subjects need be satisfied) and uncertainty in recruitment rates, etc. Simulation has great potential for being the ideal tool which companies can utilize to make better decisions with considerations to both supply chain risks and costs. To achieve this goal, it is important to understand the specifics of clinical trial supply chains. Built upon this knowledge, our paper provides an advanced tutorial on modeling and practical considerations in clinical supply simulation.
Using a Modified Elliot Transfer Function on the Hysteresis G Model Coupled to a 3-D FEM Code

In a previous article, the ferromagnetic hysteresis G model was proposed. One of the relevant advantages of the G model is its simplicity compared with classical methods. Here, we present the first steps to insert the model in a 3-D finite-element code. This model uses analytical curves to describe the hysteresis loop. Also, as a contribution, the Elliot transfer function is modified on the way it matches the experimental B(H) curves with good accuracy. Therefore, the main goal here is to investigate its robustness and accuracy when treating the benchmark case Testing Electromagnetic Analysis Methods (TEAM) Problem Number 32. Initially, the G model is presented in a succinct way. Then, the parameter characterization of the modified Elliot transfer function is explained and discussed. This modified Elliot function, coupled with a 3-D FE code, is compared with a similar implementation using the Jiles–Atherton method and experimental data.
Automatic colon polyp classification using Convolutional Neural Network: A Case Study at Basque Country

In this paper, a database generated from the contribution of Urduliz and Biodonostia Hospitals was used, which includes 785 images. The objective is to identify in which category of the Paris classification each image is. 5 ResNet50, ResNet101, Xception, VGG19, and Inception V3 models were used. The model with the best results is ResNet50 with accuracy of 87.1 %, Precision 87.1 %, Recall 87.1 %, F1-Score 87.1 % and Specificity 93 %. In this article, we propose a frame of reference for a set of neural network models, which offers a method for the classification of polypoid or sessile lesions that includes the categorization of Paris.