Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the identification of cancer in young people: A scoping review

ABSTRACT Introduction: The challenges of achieving timely cancer diagnosis in adolescents and young adults are recognised. However, contributing factors and associated clinical and psychosocial outcomes are poorly understood. Areas covered: We present a scoping review of existing evidence into time intervals to diagnosis and potential mechanisms influencing the identification of cancer symptoms and impact on a timely diagnosis. Charting data using Walters ‘pathways to treatment’ we summarise the diagnostic pathway into four interval categories: appraisal, help-seeking, diagnostic, and pre-treatment, and illustrate where evidence exists and where unanswered questions remain. Expert commentary: Whilst the research base has expanded over the last decade in cancer care there continues to be limited research that reveals the complexity of the timeliness of diagnosis in this population. There are unique issues facing this age group in terms of rarity of cancer, complexity of symptoms and problems with healthcare system access that create a constellation of challenges. We offer explanations for diagnostic difficulties in this age group, and explain how, with the limited available evidence, we are still seeking solutions to what is a uniquely complex problem.
Editorial: HBsAg serum levels in HBeAg‐negative chronic HBV infection—is it a matter of genotype? Authors’ reply

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Speaker-Follower Models for Vision-and-Language Navigation

Navigation guided by natural language instructions presents a challenging reasoning problem for instruction followers. Natural language instructions typically identify only a few high-level decisions and landmarks rather than complete low-level motor behaviors; much of the missing information must be inferred based on perceptual context. In machine learning settings, this is doubly challenging: it is difficult to collect enough annotated data to enable learning of this reasoning process from scratch, and also difficult to implement the reasoning process using generic sequence models. Here we describe an approach to vision-and-language navigation that addresses both these issues with an embedded speaker model. We use this speaker model to (1) synthesize new instructions for data augmentation and to (2) implement pragmatic reasoning, which evaluates how well candidate action sequences explain an instruction. Both steps are supported by a panoramic action space that reflects the granularity of human-generated instructions. Experiments show that all three components of this approach---speaker-driven data augmentation, pragmatic reasoning and panoramic action space---dramatically improve the performance of a baseline instruction follower, more than doubling the success rate over the best existing approach on a standard benchmark.
Thymoquinone recovers learning function in a rat model of Alzheimer’s disease

Objective: Alzheimer's disease is a neurodegenerative disorder characterized by accumulation of amyloid beta in the hippocampus. In recent decades, herbal medicine has been widely used to treat many neurodegenerative disorders,as in comparison to conventional drugs, herbal remedies exert minimal side effects. Here, the effects of thymoquinone, as the main active component of Nigella sativa, on passive avoidance memory in rat model of Alzheimer’s disease, were evaluated. Materials and Methods: Hippocampal injection of amyloid beta (Aβ) was used to induce Alzheimer’s disease in male Wistar rats, followed by intra peritoneal administrations of 5 and 10 mg/kg thymoquinone on a daily basis for 4 weeks. Animals were subjected to fear learning behavior in passive avoidance test and histopathological analysis of the hippocampus was done. Shuttle box test was used to evaluate the condition studying memory. Thioflavin-S and Hematoxylin and Eosine staining were done to confirm Aβ plaque formation and to evaluate the effect of thymoquinone on the pyramidal cells in the hippocampal CA1 region. Results: Amyloid beta caused cognitive dysfunction reflected by increasing initial and step-through latency along with plaque formation and degeneration of pyramidal cells in the hippocampus. Thymoquinone administration ameliorated this effect by significant reductions in plaque formation in CA1 region of the hippocampus and increased latency time. It also increased the number of surviving neurons in the hippocampus. Conclusion: It seems that thymoquinone improved learning function in a rat model of Alzheimer’s disease. Thus, thymoquinone could be possibly used as an anti-neurodegenerative agent for protecting hippocampal neurons against neurotoxic effects of Aβ in patients with Alzheimer’s disease.
On the robot path planning using cloud computing for large grid maps

Global path planning consists in finding the optimal path for a mobile robot with the lowest cost in the minimum amount of time, without colliding with the obstacles scattered in the workspace. In this paper, we investigate the benefits of offloading path planning algorithms to be executed in the cloud rather than in the robot. The contribution consists in developing a vertex-centric implementation of RA∗ [1], a version of A∗ that we developed for grid maps and that was proven to be much faster than A∗, using the distributed graph processing framework Giraph that rely on Hadoop. We also developed a centralized cloud-based C++ implementation of the algorithm for benchmarking and comparison purposes. Experimental results on a real cloud shows that the distributed graph processing Giraph fails to provide faster execution as compared to centralized C++ implementation for different map sizes and configuration due to non-real time properties of Hadoop.
Surface activated bonding of Au/Ta layers after degas annealing for MEMS packaging

Au thin films with atomically smooth surfaces on Cr or Ta underlayers were bonded after a degas annealing treatment for MEMS packaging. In the case of bonding after the degas annealing step at 200 °C for 600 s in vacuum, the Cr/Au films were poorly bonded though the Ta/Au films were strongly bonded. This is because Cr2O3 was formed on the Cr/Au film surface during the degas annealing step, but Ta was absent on the Ta/Au film after the degas annealing step. We expected that packaging with Ta/Au sealing layers allows low-temperature MEMS-packaging process after degas annealing.
CEACAM6 is associated with osteosarcoma metastasis and facilitates epithelial–mesenchymal transition in osteosarcoma cells

Background Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) is a member of CEACAM family and has been reported to be upregulated in various types of human cancer and involved in tumor progression and metastasis. However, the biological roles and clinical significances of CEACAM6 in osteosarcoma still remain to be elucidated. Materials and methods Real-timePCR, immunohistochemistry and Western blot analysis were used to determine CEACAM6 expression in osteosarcoma cell lines and clinical specimens. Then the clinical relevance of CEACAM6 was analyzed in osteosarcoma. The function of CEACAM6 in osteosarcoma was examined by wound-healing and cell invasion assays, and expression levels of epithelial–mesenchymal transition markers. Results In the present study, we found that CEACAM6 was markedly upregulated in metastatic osteosarcoma tissues when compared with the nonmetastatic osteosarcoma tissues. Upregulation of CEACAM6 was significantly associated with lung metastasis status (P=0.006) in patients with osteosarcoma. Survival analyses suggested that osteosarcoma patients with high CEACAM6 expression had a significantly shorter overall survival time and lung metastasis-free survival time than those with low CEACAM6 expression. Knockdown of CEACAM6 inhibits osteosarcoma cell migration and invasion. Moreover, silencing CEACAM6 suppressed osteosarcoma cells epithelial–mesenchymal transition. Conclusion Taken together, this study suggests that CEACAM6 might be a promising biomarker and a potential therapeutic target for the treatment of metastatic osteosarcoma.
Using Transferred Deep Model in Combination with Prior Features to Localize Multi-style Ship License Numbers in Nature Scenes

Ship License Numbers (SLNs) localization is an important part of waterway intelligent transportation systems. Unfortunately, this issue has been neglected for a long time. In this paper, we present an effective approach for localizing multi-style SLNs in nature scenes. The problem of locating SLNs is posed as the detection of character sequences which possess SLNs prior features. First, faced with the difficulty of no training data, a transfer learning-based deep convolutional neural network is designed to detect character sequences in SLNs. In the second step, to accurately locate SLNs from the detected character sequences, the prior features of SLNs are considered. Three SLNs prior features are summarized. An SLNs region generating algorithm and a low-level similarity-based fake SLNs filtering algorithm are presented, respectively. The accurate positions of the SLNs in the input image are obtained in this stage. The proposed approach is finally tested on ZJUSHIPS950 dataset. The approach achieves a FPPI of 0.42 and a F-measure of 0.614 on 1374 labeled SLNs, surpassing several related methods by a large margin. Controlled experiment results also prove the impressive performances of the proposed SLNs region generating and fake SLNs filtering algorithms.
The magnetic record of inorganic fly ash deposition in lake sediments and ombrotrophic peats

Interest in identifying a geological marker signifying the starting point for the Anthropocene has prompted an exploration of the stratigraphic record of inorganic particulates generated by industrial activities. Magnetic measurements of recent lake sediments and ombrotrophic peats are here used to reconstruct the history of deposition of inorganic fly-ash spheres resulting mainly from solid fuel combustion and metal smelting. The chronologies used have been based on moss-increment counting, radioisotope dating and pollen analysis. The sites come from the United Kingdom, Scandinavia and North America. In several cases where detailed chronologies of both fly-ash deposition and local industry can be compared, the sequence of concentration-linked magnetic measurements appears to capture accurately the record of industrial development despite incontrovertible evidence from other peat-based records for some selective dissolution of magnetic minerals. The dates at which magnetic concentration increases begin range from the 16th century in the peat profiles around the head of Morecambe Bay, South Cumbria, in North-West England where early iron manufacture using charcoal-fuelled bloomery hearths is well documented, to the mid-20th century at the remotest sites in Arctic Scandinavia. The lake sediment profiles used here come mainly from the United Kingdom and, in most cases, they date increases to the late 19th century or the first decades of the 20th century. Any attempt to use the magnetic record of fly-ash deposition in lake sediments and/or peats to mark the date chosen as the onset of the Anthropocene would require careful choice of site location and archive, bearing in mind the issue of selective magnetic mineral dissolution.
Time-Weighted LSTM Model with Redefined Labeling for Stock Trend Prediction

Various techniques have been applied to predict stock market trends. However, the results are not quite satisfactory due to stock market’s complexity. Many approaches either lack a clear and reasonable definition of trend or neglect the uniqueness of time attribute in stock data, treating them like other attributes, and use one-size-fits-all models to solve such a typical time-series problem. In this paper, we attempted to exploit the time attribute of stock data to improve prediction accuracy. Firstly, instead of treating data indiscriminately, we used time weight function to carefully assign weights to data according to their temporal nearness towards the data to be predicted. Secondly, the stock trend definitions were formally given by referencing financial theories and best practices. Lastly, Long Short-Term Memory (LSTM) network was customized to discover the underlying temporal dependencies in data. The trials of different time-weighted functions showed that the relation between the importance of data and their time-series is not constant. Instead, it falls within linear and quadratic, roughly a quasilinear function. Equipped with the time-weighted function, LSTM outperformed other models and can be generalized to other stock indexes. In the test with CSI 300 index, we achieved 83.91% in accuracy when fed with the redefined trends.
Some Neighbourhood Approaches for the Antenna Positioning Problem

The problem of positioning antennas in cellular networks is a known problem in the field of telecommunications. It consists of selecting from a set of candidate sites, the best locations to install the base stations in order to maximize the network coverage while minimizing the number of the used stations. In theory, the problem is NP-hard. To solve it in practice, we propose in this work the adaptation of two metaheuristics based on the local search that are the Iterated Local Search (ILS) and the Breakout Local Search (BLS) and provide a new algorithm inspired from both the ILS and the BLS algorithms. The latter is based on a local search process and a perturbation in the exploration of the search space. It is distinguished by its mechanism of reinitialization of the search and by its way of generating a new starting solution. To validate our approach, we have implemented, tested and compared these algorithms to several other methods on a real instance of the problem. The experimental results obtained show that the proposed approach improves the performance of these methods in most of the cases. Index Terms—Network design, Antenna Positioning Problem, Optimization, Metaheuristic, Local Search.
Positive impact of brentuximab vedotin on overall survival of patients with classical Hodgkin lymphoma who relapse or progress after autologous stem cell transplantation: A nationwide analysis

The outcome of patients with relapsed/refractory classical Hodgkin lymphoma (R/R cHL) after autologous stem cell transplantation (auto‐SCT) is poor. Recently, the anti‐CD30 monoclonal antibody‐drug conjugate, brentuximab vedotin (BV), has shown remarkable activity in the setting of R/R cHL. In the pivotal phase II study, BV produced an overall response rate of 75% and a median progression‐free survival of 6.7 months. Although these results have been reproduced by large registry studies, the impact of BV on the overall survival (OS) of patients with R/R cHL has not been addressed so far. The aim of this study was to examine the impact of BV on OS in the setting of post auto‐SCT R/R cHL. Analysis was performed in a group of patients with R/R cHL after a previous auto‐SCT reported in the Greek registry during the last 2 decades. By using a multivariate model and censoring patients at the time of subsequent allo‐SCT or treatment with immune checkpoint inhibitors, we showed that treatment with BV in the posttransplant relapse setting has a positive impact on the outcome and results in significant improvement of OS. To our knowledge, this the first published study, addressing the impact of BV on the OS in the setting of posttransplant relapse.
Effect of Oral Valproic Acid vs Placebo for Vision Loss in Patients With Autosomal Dominant Retinitis Pigmentosa: A Randomized Phase 2 Multicenter Placebo-Controlled Clinical Trial

Importance There are no approved drug treatments for autosomal dominant retinitis pigmentosa, a relentlessly progressive cause of adult and childhood blindness. Objectives To evaluate the potential efficacy and assess the safety of orally administered valproic acid (VPA) in the treatment of autosomal dominant retinitis pigmentosa. Design, Setting, and Participants Multicenter, phase 2, prospective, interventional, placebo-controlled, double-masked randomized clinical trial. The study took place in 6 US academic retinal degeneration centers. Individuals with genetically characterized autosomal dominant retinitis pigmentosa were randomly assigned to receive treatment or placebo for 12 months. Analyses were intention-to-treat. Interventions Oral VPA 500 mg to 1000 mg daily for 12 months or placebo. Main Outcomes and Measures The primary outcome measure was determined prior to study initiation as the change in visual field area (assessed by the III4e isopter, semiautomated kinetic perimetry) between baseline and month 12. Results The mean (SD) age of the 90 participants was 50.4 (11.6) years. Forty-four (48.9%) were women, 87 (96.7%) were white, and 79 (87.8%) were non-Hispanic. Seventy-nine participants (87.8%) completed the study (42 [95.5%] received placebo and 37 [80.4%] received VPA). Forty-two (46.7%) had a rhodopsin mutation. Most adverse events were mild, although 7 serious adverse events unrelated to VPA were reported. The difference between the VPA and placebo arms for mean change in the primary outcome was −150.43 degree2 (95% CI, −290.5 to −10.03; P = .035). Conclusions and Relevance This negative value indicates that the VPA arm had worse outcomes than the placebo group. This study brings to light the key methodological considerations that should be applied to the rigorous evaluation of treatments for these conditions. This study does not provide support for the use of VPA in the treatment of autosomal dominant retinitis pigmentosa. Trial Registration ClinicalTrials.gov Identifier: NCT01233609
Interpregnancy weight change and adverse pregnancy outcomes: a systematic review and meta-analysis

Objectives To evaluate the effect of interpregnancy body mass index (BMI) change on pregnancy outcomes, including large-for-gestational-age babies (LGA), small-for-gestational-age babies (SGA), macrosomia, gestational diabetes mellitus (GDM) and caesarean section (CS). Design Systematic review and meta-analysis of observational cohort studies. Data sources Literature searches were performed across Cochrane, MEDLINE, EMBASE, CINAHL, Global Health and MIDIRS databases. Study selection Observational cohort studies with participants parity from 0 to 1. Main outcome measures Adjusted ORs (aORs) with 95% CIs were used to evaluate the association between interpregnancy BMI change on five outcomes. Results 925 065 women with singleton births from parity 0 to 1 were included in the meta-analysis of 11 studies selected from 924 identified studies. A substantial increase in interpregnancy BMI (>3 BMI units) was associated with an increased risk of LGA (aOR 1.85, 95% CI 1.71 to 2.00, p<0.001), GDM (aOR 2.28, 95% CI 1.97 to 2.63, p<0.001), macrosomia (aOR 1.54, 95% CI 0.939 to 2.505) and CS (aOR 1.72, 95% CI 1.32 to 2.24, p<0.001) compared with the reference category, and a decreased risk of SGA (aOR 0.83, 95% CI 0.70 to 0.99, p=0.044). An interpregnancy BMI decrease was associated with a decreased risk of LGA births (aOR 0.70, 95% CI 0.55 to 0.90, p<0.001) and GDM (aOR 0.80, 95% CI 0.62 to 1.03), and an increased risk of SGA (aOR 1.31, 95% CI 1.06 to 1.63, p=0.014). Women with a normal BMI (<25kg/m2) at first pregnancy who have a substantial increase in BMI between pregnancies had a higher risk of LGA (aOR 2.10, 95% CI 1.93 to 2.29) and GDM (aOR 3.10, 95% CI 2.74 to 3.50) when compared with a reference than women with a BMI ≥25 kg/m2 at first pregnancy. Conclusions Gaining weight between pregnancies increases risk of developing GDM, CS and LGA, and reduces risk of SGA in the subsequent pregnancy. Losing weight between pregnancies reduces risk of GDM and LGA and increases risk of SGA. Weight stability between first and second pregnancy is advised in order to reduce risk of adverse outcomes. Trial registration number CRD42016041299.
Criteria required for an acceptable point-of-care test for UTI detection: Obtaining consensus using the Delphi technique

Background Urinary Tract Infections (UTIs) are common bacterial infections, second only to respiratory tract infections and particularly prevalent within primary care. Conventional detection of UTIs is culture, however, return of results can take between 24 and 72 hours. The introduction of a point of care (POC) test would allow for more timely identification of UTIs, facilitating improved, targeted treatment. This study aimed to obtain consensus on the criteria required for a POC UTI test, to meet patient need within primary care. Methods Criteria for consideration were compiled by the research team. These criteria were validated through a two-round Delphi process, utilising an expert panel of healthcare professionals from across Europe and United States of America. Using web-based questionnaires, panellists recorded their level of agreement with each criterion based on a 5-point Likert Scale, with space for comments. Using median response, interquartile range and comments provided, criteria were accepted/rejected/revised depending on pre-agreed cut-off scores. Results The first round questionnaire presented thirty-three criteria to the panel, of which 22 were accepted. Consensus was not achieved for the remaining 11 criteria. Following response review, one criterion was removed, while after revision, the remaining 10 criteria entered the second round. Of these, four were subsequently accepted, resulting in 26 criteria considered appropriate for a POC test to detect urinary infections. Conclusion This study generated an approved set of criteria for a POC test to detect urinary infections. Criteria acceptance and comments provided by the healthcare professionals also supports the development of a multiplex point of care UTI test.