LLukas22/scidocs huggingface dataset:
Extending the Design Space in Industrial Manufacturing Through Mobile Projection

This paper illustrates design opportunities for future systems in industrial manufacturing based on mobile projectors. We present a projection-based augmented reality (AR) assembly assistance system that supports users in the production process by projecting picking and assembly information into the physical workspace. Based on insights gained with a first prototype system using a stationary projector, we consider the availability of mobile projectors and the extended design space as a huge opportunity for AR applications in industrial manufacturing. Within this paper, we describe design ideas for extending our concept and for applying mobile projection in the context of industrial manufacturing.
Can balance in children with cerebral palsy improve through use of an activity promoting computer game?

INTRODUCTION
This study aimed to evaluate if use of an activity promoting computer game, used in the home (Nintendo Wii Fit; Nintendo Co Ltd, Japan), could influence balance related outcome measures in children with cerebral palsy.


METHOD
Eighteen children with hemiplegic or diplegic cerebral palsy were recruited for the study. A randomised cross-over design was used with children tested at baseline, after five weeks of playing Wii Fit games and after five weeks without any intervention. Outcome measures of interest included: performance on the modified sensory organisation test, reactive balance test and rhythmic weight shift test.


RESULTS
No significant difference was observed between testing occasions for any of the balance measures investigated (p > 0.05).


CONCLUSION
Our results suggest that use of a Nintendo Wii balance board and Wii Fit software for a minimum of thirty minutes per day in the patient's own home, over a five week period, is not effective as a balance training tool in children with cerebral palsy.
Physico-chemical and surface characterization of adsorbent prepared from groundnut shell by ZnCl2 activation and its ability to adsorb colour

Physico-chemical and surface characterization of activated carbon prepared from groundnut shell, an abundantly available carbonaceous solid waste from oil processing mills in India, by chemical activation were carried out. The effect of various activation conditions viz. time, temperature and ZnCl2 / char ratio on the % yield of product and adsorption efficiency in terms of iodine number was studied. Changes in surface morphology of char before and after activation were examined by scanning electron microscopy which showed well developed pore structure in activated carbon demonstrating corrosive effect of ZnCl2. Surface modifications through chemical changes were studied by FTIR spectroscopy which showed considerable development and increase of surface functional groups in activated carbon as compared to char. The developed adsorbent was utilized for the removal of acid dye from aqueous solution and its adsorption capacity was found to be 55.5 mg/g of the adsorbent for 100 ppm initial concentration of dye solution. Adsorption parameters for Freundlich and Langmuir isotherm models were examined for dye adsorption and for the validity of models to analyze the equilibrium data, it was found that Freundlich model fitted better than Langmuir. The results indicate that Groundnut Shell based Powdered Activated Carbon (GSPAC) could be employed as low-cost alternative adsorbent to commercial activated carbon in the wastewater treatment for removal of acid dyes.
Big Data Privacy Preservation and Security Protection

. ABSTRACT: Big data is a term utilized for huge informational indexes that have more changed and complex structure. These attributes normally correspond with extra troubles in storing, examining and applying further methods or extricating outcomes. Notwithstanding, there is a conspicuous inconsistency between the security and privacy of big data and across the utilization of big data. This paper concentrates on privacy and security worries in big data. There has been various security safeguarding systems created for security insurance at various stages (for instance, data storage, data generation, and data processing) of a big data life cycle. The objective of this paper is to give the privacy protection and security in big data.
A survey of maneuvering target tracking: approximation techniques for nonlinear filtering

This is a part of Part VI (nonlinear filtering) of a series of papers that provide a comprehensive survey of techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I [52] and Part II [48] deal with target motion models. Part III [49], Part IV [50], and Part V [51] cover measurement models, maneuver detection based techniques, and multiple-model methods, respectively. This part surveys approximation techniques for point estimation of nonlinear dynamic systems that are general, applicable to a wide spectrum of nonlinear filtering problems, especially those in the context of maneuvering target tracking. Three classes of such techniques are surveyed here: function approximation, moment approximation, and stochastic model approximation.
Marine Pharmacology in 2012–2013: Marine Compounds with Antibacterial, Antidiabetic, Antifungal, Anti-Inflammatory, Antiprotozoal, Antituberculosis, and Antiviral Activities; Affecting the Immune and Nervous Systems, and Other Miscellaneous Mechanisms of Action †

The peer-reviewed marine pharmacology literature from 2012 to 2013 was systematically reviewed, consistent with the 1998-2011 reviews of this series. Marine pharmacology research from 2012 to 2013, conducted by scientists from 42 countries in addition to the United States, reported findings on the preclinical pharmacology of 257 marine compounds. The preclinical pharmacology of compounds isolated from marine organisms revealed antibacterial, antifungal, antiprotozoal, antituberculosis, antiviral and anthelmitic pharmacological activities for 113 marine natural products. In addition, 75 marine compounds were reported to have antidiabetic and anti-inflammatory activities and affect the immune and nervous system. Finally, 69 marine compounds were shown to display miscellaneous mechanisms of action which could contribute to novel pharmacological classes. Thus, in 2012-2013, the preclinical marine natural product pharmacology pipeline provided novel pharmacology and lead compounds to the clinical marine pharmaceutical pipeline, and contributed significantly to potentially novel therapeutic approaches to several global disease categories.
A prospective study of febrile neutropenia in pediatric cancer patients in Jordan.

OBJECTIVE
To describe the characteristics and clinical course of febrile neutropenia (FN) in pediatric patients admitted to a comprehensive cancer center in Jordan.


METHODS
This is a 6-month prospective observational study. Patients admitted with FN were identified. Patient demographics, duration since last chemotherapy, use of granulocyte colony-stimulating factor, presence of central lines, transfer to the intensive care unit, length of hospital stay, mortality, and the results of all cultures were recorded.


RESULTS
One hundred and nine episodes for 88 patients were included, with a median age of 6 years (range, 1 to 19 y) and 55% were females. Median duration since last chemotherapy was 7 days (range, 1 to 33 d); median duration of hospital stay was 7 days (range, 1 to 81 d). Transfer to the intensive care unit was required for 11% of episodes, and there were no deaths. Positive cultures were reported in 18.4% episodes. Pathogens isolated were gram-positive organisms (50%), gram-negative organisms (20%), viral (25%), and fungal (5%). Positive blood cultures were significantly more in episodes with central lines compared with those with no central lines (P=0.04).


CONCLUSIONS
FN episodes had favorable outcomes and were mostly associated with negative cultures. There were differences between the microbiologic profiles reported in this study, compared with what has been previously described.
Cyber Threat Intelligence – Issue and Challenges

Received Jan 9, 2018 Revised Mar 2, 2018 Accepted Mar 18, 2018 Today threat landscape evolving at the rapid rate with much organization continuously face complex and malicious cyber threats. Cybercriminal equipped by better skill, organized and well-funded than before. Cyber Threat Intelligence (CTI) has become a hot topic and being under consideration for many organization to counter the rise of cyber-attacks. The aim of this paper is to review the existing research related to CTI. Through the literature review process, the most basic question of what CTI is examines by comparing existing definitions to find common ground or disagreements. It is found that both organization and vendors lack a complete understanding of what information is considered to be CTI, hence more research is needed in order to define CTI. This paper also identified current CTI product and services that include threat intelligence data feeds, threat intelligence standards and tools that being used in CTI. There is an effort by specific industry to shared only relevance threat intelligence data feeds such as Financial Services Information Sharing and Analysis Center (FS-ISAC) that collaborate on critical security threats facing by global financial services sector only. While research and development center such as MITRE working in developing a standards format (e.g.; STIX, TAXII, CybOX) for threat intelligence sharing to solve interoperability issue between threat sharing peers. Based on the review for CTI definition, standards and tools, this paper identifies four research challenges in cyber threat intelligence and analyses contemporary work carried out in each. With an organization flooded with voluminous of threat data, the requirement for qualified threat data analyst to fully utilize CTI and turn the data into actionable intelligence become more important than ever. The data quality is not a new issue but with the growing adoption of CTI, further research in this area is needed
Real-Time Detection of Solder-Joint Faults in Operational Field Programmable Gate Arrays

In this paper we present two sensors for real-time detection of solder-joint faults in programmed, operational field programmable gate arrays (FPGAs), especially those FPGAs in ball grid array (BGA) packages. The first sensor uses a method in-situ within the FPGA and the second sensor uses a method external to the FPGA. Initial testing indicates the first method is capable of detecting high-resistance faults of 100 Omega or lower and which last one-half a clock period or longer. A prototype of the second method detected high-resistance faults of at least 150 Omega that lasted as low as 25 ns.
Linking agricultural investments to growth and poverty: An economywide approach applied to Mozambique

National agricultural investment plans in developing countries are expected to be evidence-based, reflect broad development processes, and measure contributions to high-level outcomes, such as economic growth and poverty reduction. We propose an economywide systems-approach that combines ex post household econometric analysis (using propensity score matching) of investment impacts with ex ante modeling of growth and poverty linkages (using a spatially-disaggregated dynamic computable general equilibrium model). We apply this approach retrospectively to Mozambique. Simulation results indicate that the country's investment plan from 2012 to 2017 would not achieve national growth targets, despite doubling public spending on agriculture. Rather than increasing spending, the government should have reallocated resources towards agricultural research and extension, instead of irrigation and fertilizer subsidies. Providing extension services to smallholders is most effective at raising growth and reducing poverty in all regions of the country. Investing in irrigation was more likely benefit growth in the country's southern region due to less favorable agroecological conditions. These conclusions are robust across assumptions about investment efficiency. As demonstrated in Mozambique, our approach provides a consistent framework for evaluating ex ante sector-wide agricultural investment plans based on growth, poverty and regional equity considerations. Our approach complements household-level evaluations by enhancing their relevance for national planning.
A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization.

In 1912, Max Wertheimer published his paper on phi motion, widely recognized as the start of Gestalt psychology. Because of its continued relevance in modern psychology, this centennial anniversary is an excellent opportunity to take stock of what Gestalt psychology has offered and how it has changed since its inception. We first introduce the key findings and ideas in the Berlin school of Gestalt psychology, and then briefly sketch its development, rise, and fall. Next, we discuss its empirical and conceptual problems, and indicate how they are addressed in contemporary research on perceptual grouping and figure-ground organization. In particular, we review the principles of grouping, both classical (e.g., proximity, similarity, common fate, good continuation, closure, symmetry, parallelism) and new (e.g., synchrony, common region, element and uniform connectedness), and their role in contour integration and completion. We then review classic and new image-based principles of figure-ground organization, how it is influenced by past experience and attention, and how it relates to shape and depth perception. After an integrated review of the neural mechanisms involved in contour grouping, border ownership, and figure-ground perception, we conclude by evaluating what modern vision science has offered compared to traditional Gestalt psychology, whether we can speak of a Gestalt revival, and where the remaining limitations and challenges lie. A better integration of this research tradition with the rest of vision science requires further progress regarding the conceptual and theoretical foundations of the Gestalt approach, which is the focus of a second review article.
FDG-PET for clinical use

Positron emission tomography (PET) is the most powerful molecular imaging technique currently available for clinical use. Because deranged tumour metabolism is a common finding in many malignancies, PET is frequently used for tissue characterisation, staging and therapy control. Four previous consensus studies in Germany, performed up to 1997, have established indications for fluorine-18 fluoro-2-deoxy-D-glucose (FDG) PET in oncology, neurology and cardiology. More than 10,000 references on FDG-PET have been published in the meantime, mostly on oncological issues. Therefore, it was the aim of the present paper to provide an update on the clinical use of FDG-PET in oncology. For this purpose a systematic literature search was performed in all common medical literature databases. All hits were manually checked and abstracts, case reports, technically oriented papers and reviews were excluded from analysis. A questionnaire comprising 24 items was developed for standardised quality assessment according to evidence-based medicine (EBM) criteria. We selected 533 papers for further review by an interdisciplinary panel of 58 experts from oncology, radiology and nuclear medicine. Clinical use was judged according to the following grading scheme: 1a, established clinical use; 1b, clinical use probable; 2, useful in individual cases; 3, not yet assessable owing to missing or incomplete data; 4, clinical use rare (either as inferred from theoretical considerations or as demonstrated by published studies). Of the 533 papers selected, 122 references with 7,092 documented patients fulfilled the EBM criteria for detailed review. The results of these studies were tabulated and are available at www.nucmed-ulm.de. Clinical indications (grade 1a or 1b) were established for differentiating benign from malignant lesions in pulmonary nodules, pancreatic masses and residual masses after chemotherapy in malignant lymphoma. Staging was improved by FDG-PET in oesophageal cancer, breast cancer, head and neck cancer, lung cancer, malignant lymphoma and malignant melanoma. Effectiveness of radio- and/or chemotherapy could be better controlled in Hodgkin's disease and high-grade non-Hodgkin's lymphoma. Restaging was improved in relapsing thyroid cancer, colorectal cancer, head and neck cancer, lung cancer and malignant melanoma. In summary, the efficiency of FDG-PET was studied in several thousand patients with malignant tumours and was found to be well documented in the international high-quality peer-reviewed literature. There are clear-cut clinical indications for FDG-PET in diagnosis, staging and therapy control, and the technique can help to improve the management of many patients with cancer.
Coordinating the Generation of Signs in Multiple Modalities in an Affective Agent

In order to be believable, embodied conversational agents (ECAs) must show expression of emotions in a consistent and natural looking way across modalities. The ECA has to be able to display coordinated signs of emotion during realistic emotional behaviour. Such a capability requires one to study and represent emotions and coordination of modalities during non-basic realistic human behaviour, to define languages for representing such behaviours to be displayed by the ECA, to have access to mono-modal representations such as gesture repositories. This chapter is concerned about coordinating the generation of signs in multiple modalities in such an affective agent. Designers of an affective agent need to know how it should coordinate its facial expression, speech, gestures and other modalities in view of showing emotion. This synchronisation of modalities is a main feature of emotions.
Deep CNN Ensemble with Data Augmentation for Object Detection

We report on the methods used in our recent DeepEnsembleCoco submission to the PASCAL VOC 2012 challenge, which achieves state-of-theart performance on the object detection task. Our method is a variant of the R-CNN model proposed by Girshick et al. [4] with two key improvements to training and evaluation. First, our method constructs an ensemble of deep CNN models with different architectures that are complementary to each other. Second, we augment the PASCAL VOC training set with images from the Microsoft COCO dataset to significantly enlarge the amount training data. Importantly, we select a subset of the Microsoft COCO images to be consistent with the PASCAL VOC task. Results on the PASCAL VOC evaluation server show that our proposed method outperform all previous methods on the PASCAL VOC 2012 detection task at time of submission.
Tools for teaching introductory programming: what works?

1. SUMMARY In the past decade educators have developed a myriad of tools to help novices learn to program. Different tools emerge as new features or combinations of features are employed. In this panel we consider the features of recent tools that have garnered significant interest in the computer science education community. These including narrative tools which support programming to tell a story (e.g., Alice [6], Jeroo [8]), visual programming tools which support the construction of programs through a drag-and-drop interface (e.g., JPie [3], Alice [6], Karel Universe), flow-model tools (e.g., Raptor [1], Iconic Programmer [2], VisualLogic) which construct programs through connecting program elements to represent order of computation, specialized output realizations (e.g., Lego Mindstorms [5], JES [7]) that provide execution feedback in nontextual ways, like multimedia or kinesthetic robotics, and tiered language tools (e.g., ProfessorJ [4], RoboLab) in which novices can use more sophisticated versions of a language as their expertise develops.
Treating adolescent drug abuse: a randomized trial comparing multidimensional family therapy and cognitive behavior therapy.

AIM
To examine the efficacy of two adolescent drug abuse treatments: individual cognitive behavioral therapy (CBT) and multidimensional family therapy (MDFT).


DESIGN
A 2 (treatment condition) x 4 (time) repeated-measures intent-to-treat randomized design. Data were gathered at baseline, termination, 6 and 12 months post-termination. Analyses used latent growth curve modeling.


SETTING
Community-based drug abuse clinic in the northeastern United States.


PARTICIPANTS
A total of 224 youth, primarily male (81%), African American (72%), from low-income single-parent homes (58%) with an average age of 15 years were recruited into the study. All youth were drug users, with 75% meeting DSM-IV criteria for cannabis dependence and 13% meeting criteria for abuse.


MEASUREMENTS
Five outcomes were measured: (i) substance use problem severity; (ii) 30-day frequency of cannabis use; (iii) 30-day frequency of alcohol use; (iv) 30-day frequency of other drug use; and (v) 30-day abstinence.


FINDINGS
Both treatments produced significant decreases in cannabis consumption and slightly significant reductions in alcohol use, but there were no treatment differences in reducing frequency of cannabis and alcohol use. Significant treatment effects were found favoring MDFT on substance use problem severity, other drug use and minimal use (zero or one occasion of use) of all substances, and these effects continued to 12 months following treatment termination.


CONCLUSION
Both interventions are promising treatments. Consistent with previous controlled trials, MDFT is distinguished by the sustainability of treatment effects.
Microservices in Practice, Part 1: Reality Check and Service Design

Service-oriented architecture (SOA) and microservices insiders Mike Amundsen, James Lewis, and Nicolai Josuttis share their experiences and predictions with department editors Cesare Pautasso and Olaf Zimmermann.