Smartphones in ecology and evolution: a guide for the app‐rehensive

Smartphones and their apps (application software) are now used by millions of people worldwide and represent a powerful combination of sensors, information transfer, and computing power that deserves better exploitation by ecological and evolutionary researchers. We outline the development process for research apps, provide contrasting case studies for two new research apps, and scan the research horizon to suggest how apps can contribute to the rapid collection, interpretation, and dissemination of data in ecology and evolutionary biology. We emphasize that the usefulness of an app relies heavily on the development process, recommend that app developers are engaged with the process at the earliest possible stage, and commend efforts to create open‐source software scaffolds on which customized apps can be built by nonexperts. We conclude that smartphones and their apps could replace many traditional handheld sensors, calculators, and data storage devices in ecological and evolutionary research. We identify their potential use in the high‐throughput collection, analysis, and storage of complex ecological information.     

How smartphones are changing the face of mobile and participatory healthcare: an overview,with example from eCAALYX

The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of health and healthcare smartphone apps (applications) on the market today, including emerging trends and market uptake. Platforms available today include Android, Apple iOS, RIM BlackBerry, Symbian, and Windows (Windows Mobile 6.x and the emerging Windows Phone 7 platform). The paper covers apps targeting both laypersons/patients and healthcare professionals in various scenarios, e.g., health, fitness and lifestyle education and management apps; ambient assisted living apps; continuing professional education tools; and apps for public health surveillance. Among the surveyed apps are those assisting in chronic disease management, whether as standalone apps or part of a BAN (Body Area Network) and remote server configuration. We describe in detail the development of a smartphone app within eCAALYX (Enhanced Complete Ambient Assisted Living Experiment, 2009-2012), an EU-funded project for older people with multiple chronic conditions. The eCAALYX Android smartphone app receives input from a BAN (a patient-wearable smart garment with wireless health sensors) and the GPS (Global Positioning System) location sensor in the smartphone, and communicates over the Internet with a remote server accessible by healthcare professionals who are in charge of the remote monitoring and management of the older patient with multiple chronic conditions. Finally, we briefly discuss barriers to adoption of health and healthcare smartphone apps (e.g., cost, network bandwidth and battery power efficiency, usability, privacy issues, etc.), as well as some workarounds to mitigate those barriers.     

国内8款常用植物识别软件的识别能力评价

随着智能手机和人工智能技术的发展, 以手机app为载体的植物识别软件慢慢走进公众生活、科普活动和科研活动的各个方面。植物识别app的识别正确率是决定其使用价值和用户体验的关键因素。目前, 国内应用市场上有许多植物识别app, 它们的开发目的和应用范围各异, 软件本身的关注点、数据库来源、算法、硬件要求也存在很大差异。对于不同人群, 植物识别app有不同的意义, 如对于科研人员来说, 识别能力强的app是提高效率的一大工具; 对植物爱好者来说, 具一定准确率的识别app可以作为入门的工具。因此, 对各app的识别能力进行分析与评价显得尤为重要。本文选取了8款常用的app, 分别对400张已准确鉴定的植物图片进行识别, 其中干旱半干旱区、温带、热带和亚热带4个区各选取100张。这些图片共计122科164属340种, 涵盖了乔木、灌木、草本、草质藤本和木质藤本5种生长型, 包含23种国家级保护植物。种、属、科准确识别正确分别计4分、2分、1分, 以此标准对软件识别能力按总得分进行排序, 正确率得分由高到低依次为花帮主、百度识图、花伴侣、形色、花卉识别、植物识别、发现识花、微软识花。     

burial (version 1.0): a method for testing genetic similarity within small groups of individuals using fragmentary data sets

Biologists are frequently facing the problem of dealing with data sets with a small amount of data and a high proportion of missing information. We were particularly interested in analysing fragmentary data sets generated by the application of molecular methods in palaeoanthropology in order to determine whether individuals are genetically related. In this note, we announce the release of the software burial (version 1.0) to test the null hypothesis that the observed grouping of individuals at a particular burial site reflects random placement of genotypes. The proposed test, however, can also be applied to data sets whose objects can be grouped according to nongenetic criteria such as the style of clothing, the kind of burial gifts or cultural artefacts. The C + + source code and binary executables for Windows and Linux are available for download at: http://www.uni‐tuebingen.de/uni/bcm/BURIAL/index.html .     

Software for analysing ion mobility mass spectrometry data to improve peptide identification

The development of ion mobility (IM) MS instruments has the capability to provide an added dimension to peptide analysis pipelines in proteomics, but, as yet, there are few software tools available for analysing such data. IM can be used to provide additional separation of parent ions or product ions following fragmentation. In this work, we have created a set of software tools that are capable of converting three dimensional IM data generated from analysis of fragment ions into a variety of formats used in proteomics. We demonstrate that IM can be used to calculate the charge state of a fragment ion, demonstrating the potential to improve peptide identification by excluding non-informative ions from a database search. We also provide preliminary evidence of structural differences between b and y ions for certain peptide sequences but not others. All software tools and data sets are made available in the public domain at http://code.google.com/p/ion-mobility-ms-tools/.     

mHealth: A Strategic Field without a Solid Scientific Soul. A Systematic Review of Pain-Related Apps

Background

Mobile health (mHealth) has undergone exponential growth in recent years. Patients and healthcare professionals are increasingly using health-related applications, at the same time as concerns about ethical issues, bias, conflicts of interest and privacy are emerging. The general aim of this paper is to provide an overview of the current state of development of mHealth.

Methods and Findings

To exemplify the issues, we made a systematic review of the pain-related apps available in scientific databases (Medline, Web of Science, Gale, Psycinfo, etc.) and the main application shops (App Store, Blackberry App World, Google Play, Nokia Store and Windows Phone Store). Only applications (designed for both patients and clinicians) focused on pain education, assessment and treatment were included. Of the 47 papers published on 34 apps in scientific databases, none were available in the app shops. A total of 283 pain-related apps were found in the five shops searched, but no articles have been published on these apps. The main limitation of this review is that we did not look at all stores in all countries.

Conclusions

There is a huge gap between the scientific and commercial faces of mHealth. Specific efforts are needed to facilitate knowledge translation and regulate commercial health-related apps.     

gPGA: GPU Accelerated Population Genetics Analyses

Background

The isolation with migration (IM) model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC) simulations of gene genealogies. But computational burden of IM program has placed limits on its application.

Methodology

With strong computational power, Graphics Processing Unit (GPU) has been widely used in many fields. In this article, we present an effective implementation of IM program on one GPU based on Compute Unified Device Architecture (CUDA), which we call gPGA.

Conclusions

Compared with IM program, gPGA can achieve up to 52.30X speedup on one GPU. The evaluation results demonstrate that it allows datasets to be analyzed effectively and rapidly for research on divergence population genetics. The software is freely available with source code at https://github.com/chunbaozhou/gPGA.     

Data Processing System (DPS) software with experimental design,statistical analysis and data mining developed for use in entomological research

Abstract A comprehensive but simple‐to‐use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology.     

The efficacy of smartphone‐based mental health interventions for depressive symptoms: a meta‐analysis of randomized controlled trials

The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi‐sector investment along with wide‐scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta‐analysis of smartphone apps for depressive symptoms. An electronic database search in May 2017 identified 18 eligible randomized controlled trials of 22 smartphone apps, with outcome data from 3,414 participants. Depressive symptoms were reduced significantly more from smartphone apps than control conditions (g=0.38, 95% CI: 0.24‐0.52, p<0.001), with no evidence of publication bias. Smartphone interventions had a moderate positive effect in comparison to inactive controls (g=0.56, 95% CI: 0.38‐0.74), but only a small effect in comparison to active control conditions (g=0.22, 95% CI: 0.10‐0.33). Effects from smartphone‐only interventions were greater than from interventions which incorporated other human/computerized aspects along the smartphone component, although the difference was not statistically significant. The studies of cognitive training apps had a significantly smaller effect size on depression outcomes (p=0.004) than those of apps focusing on mental health. The use of mood monitoring softwares, or interventions based on cognitive behavioral therapy, or apps incorporating aspects of mindfulness training, did not affect significantly study effect sizes. Overall, these results indicate that smartphone devices are a promising self‐management tool for depression. Future research should aim to distil which aspects of these technologies produce beneficial effects, and for which populations.     

GUIdock: Using Docker Containers with a Common Graphics User Interface to Address the Reproducibility of Research

Reproducibility is vital in science. For complex computational methods, it is often necessary, not just to recreate the code, but also the software and hardware environment to reproduce results. Virtual machines, and container software such as Docker, make it possible to reproduce the exact environment regardless of the underlying hardware and operating system. However, workflows that use Graphical User Interfaces (GUIs) remain difficult to replicate on different host systems as there is no high level graphical software layer common to all platforms. GUIdock allows for the facile distribution of a systems biology application along with its graphics environment. Complex graphics based workflows, ubiquitous in systems biology, can now be easily exported and reproduced on many different platforms. GUIdock uses Docker, an open source project that provides a container with only the absolutely necessary software dependencies and configures a common X Windows (X11) graphic interface on Linux, Macintosh and Windows platforms. As proof of concept, we present a Docker package that contains a Bioconductor application written in R and C++ called networkBMA for gene network inference. Our package also includes Cytoscape, a java-based platform with a graphical user interface for visualizing and analyzing gene networks, and the CyNetworkBMA app, a Cytoscape app that allows the use of networkBMA via the user-friendly Cytoscape interface.     

Generalized Venn diagrams: a new method of visualizing complex genetic set relations

MOTIVATION: Microarray experiments generate vast amounts of data. The unknown or only partially known functional context of differentially expressed genes may be assessed by querying the Gene Ontology database via GOMiner. Resulting tree representations are difficult to interpret and are not suited for visualization of this type of data. Methods are needed to effectively visualize these complex set relationships. RESULTS: We present a visualization approach for set relationships based on Venn diagrams. The proposed extension enhances the usual notion of Venn diagrams by incorporating set size information. The cardinality of the sets and intersection sets is represented by their corresponding circle (polygon) sizes. To avoid local minima, solutions to this problem are sought by evolutionary optimization. This generalized Venn diagram approach has been implemented as an interactive Java application (VennMaster) specifically designed for use with GOMiner in the context of the Gene Ontology database. AVAILABILITY: VennMaster is platform-independent (Java 1.4.2) and has been tested on Windows (XP, 2000), Mac OS X, and Linux. Supplementary information and the software (free for non-commercial use) are available at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/vennm together with a user documentation. CONTACT: hans.kestler@medizin.uni-ulm.de.     

Modular PC-based data acquisition and processing system for biological signals]

The data acquisition system described here is designed for biomedical research and permits the recording of up to eight biological signals simultaneously. A personal computer using the Windows 95 operating system is employed for data monitoring, data processing and analysis during experiments. The system has been designed for reliability, economy, flexibility and ease of handling, with the aim of achieving universal application. To avoid interface incompatibility, problems with transfer protocols and the data formats of commercially available products, analog signals are used for further processing. The individual input channels are electrically isolated from one another and the PC to avoid ground loops, and for reasons of safety. An isolated voltage supply is available for pre-amplifiers and bridges. A bandwidth of 0-5 kHz and the maximum sampling rate of 12.5 kHz suffice to pick up higher frequency signals such as EMG and ENG. The modular software and hardware concepts permit the use of almost any desktop or laptop PC as a central processing unit. The PC handless documentation, data acquisition, data analysis and the preparation of publications. If needed, further analytical functions can be added in modular form. Finally, the option of saving data in the ASCII format permits processing of results with such standard software packages as Excel, Access, Matlab and Origin.     

An analysis approach for high-field fMRI data from awake non-human primates

fMRI experiments with awake non-human primates (NHP) have seen a surge of applications in recent years. However, the standard fMRI analysis tools designed for human experiments are not optimal for analysis of NHP fMRI data collected at high fields. There are several reasons for this, including the trial-based nature of NHP experiments, with inter-trial periods being of no interest, and segmentation artefacts and distortions that may result from field changes due to movement. We demonstrate an approach that allows us to address some of these issues consisting of the following steps: 1) Trial-based experimental design. 2) Careful control of subject movement. 3) Computer-assisted selection of trials devoid of artefacts and animal motion. 4) Nonrigid between-trial and rigid within-trial realignment of concatenated data from temporally separated trials and sessions. 5) Linear interpolation of inter-trial intervals and high-pass filtering of temporally continuous data 6) Removal of interpolated data and reconcatenation of datasets before statistical analysis with SPM. We have implemented a software toolbox, fMRI Sandbox (http://code.google.com/p/fmri-sandbox/), for semi-automated application of these processing steps that interfaces with SPM software. Here, we demonstrate that our methodology provides significant improvements for the analysis of awake monkey fMRI data acquired at high-field. The method may also be useful for clinical applications with subjects that are unwilling or unable to remain motionless for the whole duration of a functional scan.     

The viral era: New biotechnologies give humans an unprecedented control over Nature and require appropriate safeguards

New biotechnologies such as gene drives and engineered viruses herald a viral era that would give humans exceptional power over any organism at the level of the genotype. Subject Categories: Synthetic Biology & Biotechnology, S&S: Economics & Business, Ecology

We are entering a new phase in our relationship with nature: after mechanization, automation and digitalization, a new era of autonomous technical objects is dawning. The most advanced of these technologies are characterized by viral behaviour. The COVID‐19 pandemic has again aptly demonstrated the power of viral systems: not only because of the SARS‐CoV‐2 virus'' ability to jump into and rapidly spread among the human population while wreaking havoc with human societies, but also because some of the vaccines developed against the virus are themselves based on viruses. Both developments give us some ideas of the possible impact of new biotechnologies that aim to create artefacts with viral behaviour in order to shape and control our natural environment. In this essay, the focus is on the use of genetically engineered organisms and the genetic manipulation of wild species. This change has a more direct relationship to our natural environment than autonomous software artefacts such as computer apps or digital viruses that “live” in their artificial “ecosystems” of information‐processing devices. The development of artificial biological systems will therefore require new methods for monitoring and intervention given their potential to autonomously spread within natural ecosystems.     

Smartphones and tablets: Reshaping radiation oncologists’ lives

BackgroundSmartphones and tablets are new handheld devices always connected to an information source and capable of providing instant updates, they allow doctors to access the most updated information and provide decision support at the point of care.AimThe practice of radiation oncology has always been a discipline that relies on advanced technology. Smartphones provide substantial processing power, incorporating innovative user interfaces and applications.Materials and methodsThe most popular smartphone and tablet app stores were searched for “radiation oncology” and “oncology” related apps. A web search was also performed searching for smartphones, tablets, oncology, radiology and radiation oncology.ResultsSmartphones and tablets allow rapid access to information in the form of podcasts, apps, protocols, reference texts, recent research and more.ConclusionWith the rapidly changing advances in radiation oncology, the trend toward accessing resources via smartphones and tablets will only increase, future will show if this technology will improve clinical care.     

基于USB数据采集器的膜片钳系统软件设计

为了控制新的基于USB总线的数据采集器进行膜片钳实验,设计和实现了能应用于Windows 2000／XP操作系统的膜片钳系统软件。软件运用面向对象程序设计方法和统一建模语言,实现了封接测试．电压门控和配体门控等实验模式。实验结果表明,该系统软件能够精确控制数据采集器进行高速数据采集,满足细胞生理实验的要求。     

HapMap filter 1.0: a tool to preprocess the HapMap genotypic data for association studies

The International HapMap Project provides a resource of genotypic data on single nucleotide polymorphisms (SNPs), which can be used in various association studies to identify the genetic determinants for phenotypic variations. Prior to the association studies, the HapMap dataset should be preprocessed in order to reduce the computation time and control the multiple testing problem. The less informative SNPs including those with very low genotyping rate and SNPs with rare minor allele frequencies to some extent in one or more population are removed. Some research designs only use SNPs in a subset of HapMap cell lines. Although the HapMap website and other association software packages have provided some basic tools for optimizing these datasets, a fast and user-friendly program to generate the output for filtered genotypic data would be beneficial for association studies. Here, we present a flexible, straight-forward bioinformatics program that can be useful in preparing the HapMap genotypic data for association studies by specifying cell lines and two common filtering criteria: minor allele frequencies and genotyping rate. The software was developed for Microsoft Windows and written in C++. AVAILABILITY: The Windows executable and source code in Microsoft Visual C++ are available at Google Code (http://hapmap-filter-v1.googlecode.com/) or upon request. Their distribution is subject to GNU General Public License v3.     

affylmGUI: a graphical user interface for linear modeling of single channel microarray data

SUMMARY: affylmGUI is a graphical user interface (GUI) to an integrated workflow for Affymetrix microarray data. The user is able to proceed from raw data (CEL files) to QC and pre-processing, and eventually to analysis of differential expression using linear models with empirical Bayes smoothing. Output of the analysis (tables and figures) can be exported to an HTML report. The GUI provides user-friendly access to state-of-the-art methods embodied in the Bioconductor software repository. AVAILABILITY: affylmGUI is an R package freely available from http://www.bioconductor.org. It requires R version 1.9.0 or later and tcl/tk 8.3 or later and has been successfully tested on Windows 2000, Windows XP, Linux (RedHat and Fedora distributions) and Mac OS/X with X11. Further documentation is available at http://bioinf.wehi.edu.au/affylmGUI CONTACT: keith@wehi.edu.au.     

TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data

Mass spectrometry coupled to high-performance liquid chromatography (HPLC-MS) is evolving more quickly than ever. A wide range of different instrument types and experimental setups are commonly used. Modern instruments acquire huge amounts of data, thus requiring tools for an efficient and automated data analysis. Most existing software for analyzing HPLC-MS data is monolithic and tailored toward a specific application. A more flexible alternative consists of pipeline-based tool kits allowing the construction of custom analysis workflows from small building blocks, e.g., the Trans Proteomics Pipeline (TPP) or The OpenMS Proteomics Pipeline (TOPP). One drawback, however, is the hurdle of setting up complex workflows using command line tools. We present TOPPAS, The OpenMS Proteomics Pipeline ASsistant, a graphical user interface (GUI) for rapid composition of HPLC-MS analysis workflows. Workflow construction reduces to simple drag-and-drop of analysis tools and adding connections in between. Integration of external tools into these workflows is possible as well. Once workflows have been developed, they can be deployed in other workflow management systems or batch processing systems in a fully automated fashion. The implementation is portable and has been tested under Windows, Mac OS X, and Linux. TOPPAS is open-source software and available free of charge at http://www.OpenMS.de/TOPPAS .     

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)

Background  

BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality.