Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrospective study on mixed neuroendocrine non-neuroendocrine neoplasms from five European centres

BACKGROUND Mixed neuroendocrine non-neuroendocrine neoplasm (MiNEN) is a rare diagnosis, mainly encountered in the gastro-entero-pancreatic tract. There is limited knowledge of its epidemiology, prognosis and biology, and the best management for affected patients is still to be defined. AIM To investigate clinical-pathological characteristics, treatment modalities and survival outcomes of a retrospective cohort of patients with a diagnosis of MiNEN. METHODS Consecutive patients with a histologically proven diagnosis of MiNEN were identified at 5 European centres. Patient data were retrospectively collected from medical records. Pathological samples were reviewed to ascertain compliance with the 2017 World Health Organisation definition of MiNEN. Tumour responses to systemic treatment were assessed according to the Response Evaluation Criteria in Solid Tumours 1.1. Kaplan-Meier analysis was applied to estimate survival outcomes. Associations between clinical-pathological characteristics and survival outcomes were explored using Log-rank test for equality of survivors functions (univariate) and Cox-regression analysis (multivariable). RESULTS Sixty-nine consecutive patients identified; Median age at diagnosis: 64 years. Males: 63.8%. Localised disease (curable): 53.6%. Commonest sites of origin: colon-rectum (43.5%) and oesophagus/oesophagogastric junction (15.9%). The neuroendocrine component was; predominant in 58.6%, poorly differentiated in 86.3%, and large cell in 81.25%, of cases analysed. Most distant metastases analysed (73.4%) were occupied only by a poorly differentiated neuroendocrine component. Ninety-four percent of patients with localised disease underwent curative surgery; 53% also received perioperative treatment, most often in line with protocols for adenocarcinomas from the same sites of origin. Chemotherapy was offered to most patients (68.1%) with advanced disease, and followed protocols for pure neuroendocrine carcinomas or adenocarcinomas in equal proportion. In localised cases, median recurrence free survival (RFS); 14.0 mo (95%CI: 9.2-24.4), and median overall survival (OS): 28.6 mo (95%CI: 18.3-41.1). On univariate analysis, receipt of perioperative treatment (vs surgery alone) did not improve RFS (P = 0.375), or OS (P = 0.240). In advanced cases, median progression free survival (PFS); 5.6 mo (95%CI: 4.4-7.4), and median OS; 9.0 mo (95%CI: 5.2-13.4). On univariate analysis, receipt of palliative active treatment (vs best supportive care) prolonged PFS and OS (both, P < 0.001). CONCLUSION MiNEN is most commonly driven by a poorly differentiated neuroendocrine component, and has poor prognosis. Advances in its biological understanding are needed to identify effective treatments and improve patient outcomes.
Improving Design of Library Management System using Design Patterns

Designing a system is perhaps the most critical factor affecting the quality of the software. No design methodology reduces the process of design to a sequence of mechanical steps. It only provides guidelines to aid the designer during the design process. Fortunately, GOF [2] and other researchers proposed many design patterns that give us solution of general design problems. Design decisions of experienced designers are recorded in form of design patterns. Thus each design pattern focuses on a particular object-oriented design problem or issue. If these design patterns are used by a novice designer, the obtained system design would be much better. In this paper, we designed a very simple library management system using object oriented approach without design patterns. All the defects are shown and this design is improved using few design patterns. We used three design patterns: Factory, Facade and Template Design Patterns in this study. Keywords: System Design, Design problems, Design Patterns, Facade, Factory, Template
Monitoring Cardiovascular Disease Progression

Cardiovascular disease management guidelines and therapeutic trials are traditionally driven by efforts to reduce morbid events over a finite period of time, often the 10-year outcome that forms the basis for most algorithms aimed at defining risk [1,2]. This relatively short interval in a person’s life mandates that trials focus on advanced disease with high shortterm morbidity that will make it possible to identify a favorable effect of an intervention. This restriction makes it impractical to study early disease, when an intervention might be dramatically effective in prolonging life but will have too few morbid events over 5 or 10-year period of time to demonstrate effectiveness of therapy.
Understanding the psychosocial impact of cancer in adolescence and young adulthood: a mixed-methods assessment of the perspectives of patients, survivors, and healthcare professionals

49 Introduction . 50 Methods. 56 Study Setting . 56 Participants . 56 Pre-test/Post-test Design . 57 Recruitment . 57 Procedure . 57 Measures . 58 Characterizing the sample . 58 Assessing AYAO understanding pre and post-film . 58 Assessing learning post-film . 60 Quantitative Data Coding and Analysis . 60 Hypothesis one and two . 60 Qualitative Data Coding and Analysis . 61 Hypothesis three. 63 Results . 63 Characterizing the Sample . 63 Hypothesis one and two. 66 Qualitative Analyses . 70 Hypothesis three. 70 Discussion . 82 Future Research . 85
Increasing levels of hypoxia in prostate carcinoma correlate significantly with increasing clinical stage and patient age: an Eppendorf pO(2) study.

BACKGROUND. The purpose of this study was to analyze the extent of hypoxia in prostate carcinoma tumors using the Eppendorf pO 2 microelectrode and correlate this with pretreatment characteristics and prognostic factors. METHODS. Custom-made Eppendorf pO 2 microelectrodes were used to obtain pO 2 measurements from the pathologically involved region of the prostate (as determined by the pretreatment sextant biopsies) as well as from a region of normal muscle for comparison. Each set of measurements comprised approximately 100 separate readings of pO 2 , for a total of 10,804 individual measurements. Fifty-five patients with localized prostate carcinoma were studied: Forty-one patients received brachytherapy implants, and 14 patients underwent radical prostatectomy. The pO 2 measurements were obtained in the operating room by using a sterile technique under spinal anesthesia for the brachytherapy group and under general anesthesia for the surgery group. The Eppendorf histograms were recorded and described by the median pO 2 , mean pO 2 , and percentage < 5 mm Hg and < 10 mm Hg. A multivariate mixed-effects analysis for the prediction of tumor oxygenation was performed and included the following covariates: type of tissue (prostate vs. muscle), type of treatment (implant vs. surgery) and/or anesthesia (spinal vs. general), prostate specific antigen level, disease stage, patient age and race, tumor grade, tumor volume, perineural invasion, and hormonal therapy. RESULTS. Due to differences in patient characteristics and the anesthesia employed, control measurements were obtained from normal muscle (in all but two patients). This internal comparison showed that the oxygen measurements from the pathologically involved portion of the prostate were significantly lower (average median pO 2 , 9.9 mm Hg) compared with the measurements normal muscle (average median pO 2 , 28.6 mm Hg; P < 0.0001). A multivariate, linear, mixed analysis demonstrated that, among all of the patients, the significant predictors of oxygenation were tissue (prostate vs. muscle) and anesthesia (spinal vs. general) or treatment (implant vs. surgery). Among the brachytherapy (spinal anesthesia) patients, the significant predictors of pO 2 were tissue type, disease stage, and patient age. There were no significant predictors of oxygenation in the surgical (general anesthesia) group. CONCLUSIONS. This study, employing in vivo electrode oxygen measurements, demonstrated that hypoxia exists in prostate carcinoma tumors. A dramatic effect of anesthesia was observed, likely due to modulation of polarography in the presence of fluorine. Within the group of brachytherapy (spinal anesthesia) patients, increasing levels of hypoxia (within prostatic tissue) correlated significantly with increasing clinical stage and patient age. More patients will be accrued to this prospective study to further correlate the oxygenation status in prostate carcinoma tumors with known prognostic factors and, ultimately, treatment outcome.
The role of task repetition in L2 acquisition

The use of tasks in language teaching has been demonstrated to be beneficial as it provides learners with the opportunity to develop their interlanguage by means of conversational interaction. However, as tasks are meaning-based activities, task-based language teaching has been criticized for disregarding the formal aspects of language. Recent research on second language acquisition has included variables in task design which allow learners enrolled in communicative language learning courses to develop both meaning and form in their second language (L2). Task repetition, which consists in the repetition of the same or slightly altered task at intervals of time, is one of these variables and the focus of the present paper. The aim of the paper is to show, from a theoretical and empirical perspective, that task repetition encourages learners to focus on the form of their speech and thus, to develop their L2 in terms of overall proficiency, complexity, accuracy, and fluency among others. This will be done by summarizing the most important research on the effects of task repetition in second language acquisition in different settings (second language vs. foreign language contexts) and with different participants (adult learners and child learners). Furthermore, and in order to offer the reader a full picture of the role of task repetition in language learning, the paper presents some interesting emerging research lines on the topic, such as the application of task repetition to writing tasks, individual differences and the relationship between task repetition and working memory capacity, and, finally, learners’ and teachers’ perceptions. As will be shown, the findings reported in these studies support the freeing-up effect of task repetition and, thus, that task repetition facilitates L2 acquisition. In view of these results, one could recommend that task repetition be included among the activities used in language classrooms, especially in task-based language teaching contexts.
Improving the container planning (process), by means of a planning tool

The LSP in this thesis is experiencing an increase in workload. Also, their container planning (process) is not optimal. The goal of this thesis is to digitise and automate part of the planning process, to improve both the planning and the process. After analysing the current process and its problems, a solution was drawn up. The solution is a planning tool which digitise part of the planning process and which calculates a time window for each container.
The Effect of Virtual Reality Training on Learning and Kinematics Characteristics of Dart Throwing

Background: Numerous studies proposed the improvement of movement skills on sport-context by virtual reality interaction. Objectives: The purpose of this study was investigating the effect of virtual reality on dart throwing performance and kinematics. Methods: A total of 24 healthy junior high school boy students (aged = 13.54, SD = 0.50) participated in a virtual reality game of dart throwing in the Iranian academic year of 1396-97. We investigated the mean radial error and bivariate variable error to measure performance outcomes, and preparation time, throwing time, maximum flexion angle, release time angle, and angular velocity to measure movement kinematics. The X-box Kinect (Microsoft, USA) body movement track, standard dart board (unicorn ELIPSE HD) and Casio High-Speed camera (EX-ZR1000, China) sampling at 240 Hz were used to measure performance and capture dominant upper limb motion during dart throwing play. Before exporting data to SPSS 25, Kinovea and MATLAB R2015b were used to analyze videos and smoothing data. Repeated measure ANOVA was used to analyze variables separately. Results: The results showed that virtual reality intervention was significantly effective on performance and movement kinematics. Mean radial error (P = 0.004) decreased from 19.67 ± 6.20 in the pre-test to 17.46 ± 5.81 in the acquisition, and 14.75 ± 4.01 in the post-test. Bivariate variable error (P = 0.001) decreased from 11.46 ± 1.21 in the pre-test to 11.20 ± 1.56 in the acquisition, and 10.03 ± 1.11 in the post-test. Other kinematics factors showed the significant difference in phases. Conclusions: These findings suggest that virtual reality can be applied as an effective instrument in discrete motor skill learning.
Interactive Behavior of an Immigrant Group on Mobile Instant Messenger-Based SNS: Textual Research on Topic-Centered Interactivity

ABSTRACT This article outlines a study on user interaction behavior in a KakaoTalk chat room group that was formed by Chinese immigrant women in South Korea. To study the interaction of mobile instant messenger-based social network services (MIM SNS) users, this study adopted a textual research method based on the perspective of topic-centered interactivity. The study analyzed the correlativity between SNS users’ online frequency triggered by demand-induced motivation and content-induced motivation and characterized the topics of users with different activeness in the behaviors of proposing and responding to topics. The results of this study not only provide constructive references for practitioners on the issue of how to use the SNS of immigrants to exert their sociality and usability in the dissemination of immigration policies and the social management of immigrants, but also confirm the operability and value of the methods used in this study.
Band bending profile and band offset extraction at semiconductor-metal interfaces

The band alignment of semiconductor-metal interfaces plays a vital role in modern electronics, but remains difficult to predict theoretically and measure experimentally. For interfaces with strong band bending a main difficulty originates from the in-built potentials which lead to broadened and shifted band spectra in spectroscopy measurements. In this work we present a method to resolve the band alignment of buried semiconductor-metal interfaces using core level photoemission spectroscopy and self-consistent electronic structure simulations. As a proof of principle we apply the method to a clean in-situ grown InAs(100)/Al interface, a system with a strong in-built band bending. Due to the high signal-to-noise ratio of the core level spectra the proposed methodology can be used on previously inaccessible semiconductor-metal interfaces and support targeted design of novel hybrid devices and form the foundation for a interface parameter database for specified synthesis processes of semiconductor-metal systems.
A Fundamental Bound on Performance of Non-Intrusive Load Monitoring with Application to Smart Meter Privacy

We prove that the expected estimation error of non-intrusive load monitoring algorithms is lower bounded by the trace of the inverse of the cross-correlation matrix between the derivatives of the load profiles of the appliances. We use this fundamental bound to develop privacy-preserving policies. Particularly, we devise a load-scheduling policy by maximizing the lower bound on the expected estimation error of non-intrusive load monitoring algorithms.
A new algorithm for graph center computation and graph partitioning according to the distance to the center

We propose a new algorithm for finding the center of a graph, as well as the rank of each node in the hierarchy of distances to the center. In other words, our algorithm allows to partition the graph according to nodes distance to the center. Moreover, the algorithm is parallelizable. We compare the performances of our algorithm with the ones of Floyd-Warshall algorithm, which is traditionally used for these purposes. We show that, for a large variety of graphs, our algorithm outperforms the Floyd-Warshall algorithm.
Discovery of a very young high-mass X-ray binary associated with the supernova remnant MCSNR J0513-6724 in the LMC

We report the discovery of a very young high-mass X-ray binary (HMXB) system associated with the supernova remnant (SNR) MCSNR J0513-6724 in the Large Magellanic Cloud (LMC), using XMM–Newton X-ray observations. The HMXB is located at the geometrical centre of extended soft X-ray emission, which we confirm as an SNR. The HMXB spectrum is consistent with an absorbed power law with spectral index ∼1.6 and a luminosity of 7 × 1033 erg s−1 (0.2–12 keV). Tentative X-ray pulsations are observed with a periodicity of 4.4 s and the OGLE I-band light curve of the optical counterpart from more than 17.5 yr reveals a period of 2.2324 ± 0.0003 d, which we interpret as the orbital period of the binary system. The X-ray spectrum of the SNR is consistent with non-equilibrium shock models as expected for young/less evolved SNRs. From the derived ionization time-scale we estimate the age of the SNR to be <6 kyr. The association of the HMXB with the SNR makes it the youngest HMXB, in the earliest evolutionary stage known to date. An HMXB as young as this can switch on as an accreting pulsar only when the spin period has reached a critical value. Under this assumption, we obtain an upper limit to the magnetic field of <5 × 1011 G. This implies several interesting possibilities including magnetic field burial, possibly by an episode of post-supernova hyper-critical accretion. Since these fields are expected to diffuse out on a time-scale of 103–104 yr, the discovery of a very young HMXB can provide us the unique opportunity to observe the evolution of the observable magnetic field for the first time in X-ray binaries.
Continuous comagnetometry using transversely polarized Xe isotopes

We demonstrate a transversely polarized spin-exchange pumped noble gas comagnetometer which suppresses systematic errors from longitudinal polarization. Rb atoms as well as $^{131}$Xe and $^{129}$Xe nuclei are simultaneously polarized perpendicular to a pulsed bias field. Both Xe isotopes' nuclear magnetic resonance conditions are simultaneously satisfied by frequency modulation of the pulse repetition rate. The Rb atoms detect the Xe precession. We highlight the importance of magnetometer phase shifts when performing comagnetometry. For detection of non-magnetic spin-dependent interactions the sensing bandwidth is 1 Hz, the white-noise level is 7 $\mu$Hz /$\sqrt{\text{Hz}}$, and the bias stability is $\approx1$ $\mu$Hz.
Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data

The prediction of epileptic seizure has always been extremely challenging in medical domain. However, as the development of computer technology, the application of machine learning introduced new ideas for seizure forecasting. Applying machine learning model onto the predication of epileptic seizure could help us obtain a better result and there have been plenty of scientists who have been doing such works so that there are sufficient medical data provided for researchers to do training of machine learning models.
Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation

Convolutional networks are not aware of an object's geometric variations, which leads to inefficient utilization of model and data capacity. To overcome this issue, recent works on deformation modeling seek to spatially reconfigure the data towards a common arrangement such that semantic recognition suffers less from deformation. This is typically done by augmenting static operators with learned free-form sampling grids in the image space, dynamically tuned to the data and task for adapting the receptive field. Yet adapting the receptive field does not quite reach the actual goal -- what really matters to the network is the "effective" receptive field (ERF), which reflects how much each pixel contributes. It is thus natural to design other approaches to adapt the ERF directly during runtime. In this work, we instantiate one possible solution as Deformable Kernels (DKs), a family of novel and generic convolutional operators for handling object deformations by directly adapting the ERF while leaving the receptive field untouched. At the heart of our method is the ability to resample the original kernel space towards recovering the deformation of objects. This approach is justified with theoretical insights that the ERF is strictly determined by data sampling locations and kernel values. We implement DKs as generic drop-in replacements of rigid kernels and conduct a series of empirical studies whose results conform with our theories. Over several tasks and standard base models, our approach compares favorably against prior works that adapt during runtime. In addition, further experiments suggest a working mechanism orthogonal and complementary to previous works.
Exploiting Structural and Semantic Context for Commonsense Knowledge Base Completion

Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC and ConceptNet) poses unique challenges compared to the much studied conventional knowledge bases (e.g., Freebase). Commonsense knowledge graphs use free-form text to represent nodes, resulting in orders of magnitude more nodes compared to conventional KBs ( ∼18x more nodes in ATOMIC compared to Freebase (FB15K237)). Importantly, this implies significantly sparser graph structures — a major challenge for existing KB completion methods that assume densely connected graphs over a relatively smaller set of nodes. In this paper, we present novel KB completion models that can address these challenges by exploiting the structural and semantic context of nodes. Specifically, we investigate two key ideas: (1) learning from local graph structure, using graph convolutional networks and automatic graph densification and (2) transfer learning from pre-trained language models to knowledge graphs for enhanced contextual representation of knowledge. We describe our method to incorporate information from both these sources in a joint model and provide the first empirical results for KB completion on ATOMIC and evaluation with ranking metrics on ConceptNet. Our results demonstrate the effectiveness of language model representations in boosting link prediction performance and the advantages of learning from local graph structure (+1.5 points in MRR for ConceptNet) when training on subgraphs for computational efficiency. Further analysis on model predictions shines light on the types of commonsense knowledge that language models capture well.