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Rapid and pervasive digitization of innovation processes and outcomes has upended extant theories on innovation management by calling into question fundamental assumptions about the definitional boundaries for innovation, agency for innovation, and the relationship between innovation processes and outcomes. There is a critical need for novel theorizing on digital innovation management that does not rely on such assumptions and draws on the rich and rapidly emerging research on digital technologies. We offer suggestions for such theorizing in the form of four new theorizing logics, or elements, that are likely to be valuable in constructing more accurate explanations of innovation processes and outcomes in an increasingly digital world. These logics can open new avenues for researchers to contribute to this important area. Our suggestions in this paper, coupled with the six research notes included in the special issue on digital innovation management, seek to offer a broader foundation for reinventing innovation management research in a digital world.

Pre-clinical markers of Parkinson's Disease (PD) are needed, and to be relevant in pre-clinical disease, they should be quantifiably abnormal in early disease as well. Handwriting is impaired early in PD and can be evaluated using computerized analysis of drawn spirals, capturing kinematic, dynamic, and spatial abnormalities and calculating indices that quantify motor performance and disability. Digitized spiral drawing correlates with motor scores and may be more sensitive in detecting early changes than subjective ratings. However, whether changes in spiral drawing are abnormal compared with controls and whether changes are detected in early PD are unknown. 138 PD subjects (50 with early PD) and 150 controls drew spirals on a digitizing tablet, generating x, y, z (pressure) data-coordinates and time. Derived indices corresponded to overall spiral execution (severity), shape and kinematic irregularity (second order smoothness, first order zero-crossing), tightness, mean speed and variability of spiral width. Linear mixed effect adjusted models comparing these indices and cross-validation were performed. Receiver operating characteristic analysis was applied to examine discriminative validity of combined indices. All indices were significantly different between PD cases and controls, except for zero-crossing. A model using all indices had high discriminative validity (sensitivity = 0.86, specificity = 0.81). Discriminative validity was maintained in patients with early PD. Spiral analysis accurately discriminates subjects with PD and early PD from controls supporting a role as a promising quantitative biomarker. Further assessment is needed to determine whether spiral changes are PD specific compared with other disorders and if present in pre-clinical PD.

Longitude sectorality and latitudinal zonality of morpholithogenesis on the coast of Sakhalin is the result of the unique geographical position of the island, which is a zone of mutual influences and interactions of neighboring geosystems of the subarctic Sea of Okhotsk and the moderately cold northern part of the Sea of Japan – a contact geographical structure. Based on the digitizing of maps of morphogenetic types of shores, modern morpholithodynamic settings and lithological complexes of the coast, geomorphological and morphodynamic differences of the shores of Sakhalin Island are shown, the eastern shores of which have a subarctic appearance, and the western shores are washed by the temperate sea.

High-throughput phenotyping technologies have become an increasingly important topic of crop science in recent years. Various sensors and data acquisition approaches have been applied to acquire the phenotyping traits. It is quite confusing for crop phenotyping researchers to determine an appropriate way for their application. In this study, three representative three-dimensional (3D) data acquisition approaches, including 3D laser scanning, multi-view stereo (MVS) reconstruction, and 3D digitizing, were evaluated for maize plant phenotyping in multi growth stages. Phenotyping traits accuracy, post-processing difficulty, device cost, data acquisition efficiency, and automation were considered during the evaluation process. 3D scanning provided satisfactory point clouds for medium and high maize plants with acceptable efficiency, while the results were not satisfactory for small maize plants. The equipment used in 3D scanning is expensive, but is highly automatic. MVS reconstruction provided satisfactory point clouds for small and medium plants, and point deviations were observed in upper parts of higher plants. MVS data acquisition, using low-cost cameras, exhibited the highest efficiency among the three evaluated approaches. The one-by-one pipeline data acquisition pattern allows the use of MVS high-throughput in further phenotyping platforms. Undoubtedly, enhancement of point cloud processing technologies is required to improve the extracted phenotyping traits accuracy for both 3D scanning and MVS reconstruction. Finally, 3D digitizing was time-consuming and labor intensive. However, it does not depend on any post-processing algorithms to extract phenotyping parameters and reliable phenotyping traits could be derived. The promising accuracy of 3D digitizing is a better verification choice for other 3D phenotyping approaches. Our study provides clear reference about phenotyping data acquisition of maize plants, especially for the affordable and portable field phenotyping platforms to be developed.

Manufacturing industry profoundly impact economic and societal progress. As being a commonly accepted term for research centers and universities, the Industry 4.0 initiative has received a splendid attention of the business and research community. Although the idea is not new and was on the agenda of academic research in many years with different perceptions, the term “Industry 4.0” is just launched and well accepted to some extend not only in academic life but also in the industrial society as well. While academic research focuses on understanding and defining the concept and trying to develop related systems, business models and respective methodologies, industry, on the other hand, focuses its attention on the change of industrial machine suits and intelligent products as well as potential customers on this progress. It is therefore important for the companies to primarily understand the features and content of the Industry 4.0 for potential transformation from machine dominant manufacturing to digital manufacturing. In order to achieve a successful transformation, they should clearly review their positions and respective potentials against basic requirements set forward for Industry 4.0 standard. This will allow them to generate a well-defined road map. There has been several approaches and discussions going on along this line, a several road maps are already proposed. Some of those are reviewed in this paper. However, the literature clearly indicates the lack of respective assessment methodologies. Since the implementation and applications of related theorems and definitions outlined for the 4th industrial revolution is not mature enough for most of the reel life implementations, a systematic approach for making respective assessments and evaluations seems to be urgently required for those who are intending to speed this transformation up. It is now main responsibility of the research community to developed technological infrastructure with physical systems, management models, business models as well as some well-defined Industry 4.0 scenarios in order to make the life for the practitioners easy. It is estimated by the experts that the Industry 4.0 and related progress along this line will have an enormous effect on social life. As outlined in the introduction, some social transformation is also expected. It is assumed that the robots will be more dominant in manufacturing, implanted technologies, cooperating and coordinating machines, self-decision-making systems, autonom problem solvers, learning machines, 3D printing etc. will dominate the production process. Wearable internet, big data analysis, sensor based life, smart city implementations or similar applications will be the main concern of the community. This social transformation will naturally trigger the manufacturing society to improve their manufacturing suits to cope with the customer requirements and sustain competitive advantage. A summary of the potential progress along this line is reviewed in introduction of the paper. It is so obvious that the future manufacturing systems will have a different vision composed of products, intelligence, communications and information network. This will bring about new business models to be dominant in industrial life. Another important issue to take into account is that the time span of this so-called revolution will be so short triggering a continues transformation process to yield some new industrial areas to emerge. This clearly puts a big pressure on manufacturers to learn, understand, design and implement the transformation process. Since the main motivation for finding the best way to follow this transformation, a comprehensive literature review will generate a remarkable support. This paper presents such a review for highlighting the progress and aims to help improve the awareness on the best experiences. It is intended to provide a clear idea for those wishing to generate a road map for digitizing the respective manufacturing suits. By presenting this review it is also intended to provide a hands-on library of Industry 4.0 to both academics as well as industrial practitioners. The top 100 headings, abstracts and key words (i.e. a total of 619 publications of any kind) for each search term were independently analyzed in order to ensure the reliability of the review process. Note that, this exhaustive literature review provides a concrete definition of Industry 4.0 and defines its six design principles such as interoperability, virtualization, local, real-time talent, service orientation and modularity. It seems that these principles have taken the attention of the scientists to carry out more variety of research on the subject and to develop implementable and appropriate scenarios. A comprehensive taxonomy of Industry 4.0 can also be developed through analyzing the results of this review.

The past decade has yielded more biodiversity observations from community science than the past century of traditional scientific collection. This rapid influx of data is promising for overcoming critical biodiversity data shortfalls, but we also have vast untapped resources held in undigitized natural history collections. Yet, the ability of these undigitized collections to fill data gaps, especially compared against the constant accumulation of community science data, remains unclear. Here, we compare how well community science (iNaturalist) observations and digitized herbarium specimens represent the diversity, distributions, and modeling needs of vascular plants in Canada. We find that, despite having only a third as many records, herbarium specimens capture more taxonomic, phylogenetic, and functional diversity and more efficiently capture species’ environmental niches. As such, the digitization of Canada’s 7.3M remaining specimens has the potential to more than quintuple our ability to model biodiversity. In contrast, it would require over 27M more iNaturalist observations to produce similar benefits. Our findings indicate that digitizing Earth’s remaining herbarium specimens is likely an efficient, feasible, and potentially critical investment when it comes to improving our ability to predict and protect biodiversity into the future. Here, the authors compare the diversity of vascular plants found in community science observations and digitized herbarium specimens, finding that with only one-third the records, herbaria still capture more data by several metrics.

The William and Lynda Steere Herbarium of The New York Botanical Garden has been digitizing specimens since 1995. At first, digitization included only specimen label data transcription, but specimen imaging was added in 1999. Over the years, computer technology has changed greatly, and consequently so have the hardware, software and workflow for accomplishing this work. Rapid digitization techniques developed mostly during the past five years have allowed a doubling in the rate at which specimens are digitized. Approximately 2.5 million specimens have been databased and 1.4 million have been digitally photographed. These data are served through the Garden's C. V. Starr Virtual Herbarium and are shared through other data portals as well. Completion of the digitization of all American specimens (roughly five million) is projected by 2021.

The science of taxonomy, albeit being fundamental for all organismic research, has been underfunded and undervalued for about two generations. We analyze how this could happen, particularly in times of a biodiversity crisis, when we have increased awareness amongst the population and decision makers that knowledge about species we share the planet with is indispensable for finding solutions. We identify five major issues: the habit of holding taxonomy in low esteem; the focus on inappropriate publication metrics in evaluating scientific output; the excessive focus on innovative technology in evaluating scientific relevance; shifting priorities in natural history museums away from their traditional strengths; and changing attitudes towards specimen collecting and increasing legislation regulating collecting and international exchange of specimens. To transform taxonomy into a thriving science again, we urgently suggest significantly increasing baseline funding for permanent positions in taxonomy, particularly in natural history museums; reviving taxonomic research and teaching in universities at the tenured professor level; strongly increasing soft money for integrative taxonomy projects; refraining using journal-based metrics for evaluating individual researchers and scientific output and instead focusing on quality; installing governmental support for open access publishing; focusing digitizing efforts to the most useful parts of collections, freeing resources for improving data quality by improving identifications; requiring natural history museums to focus on collection-based research; and ending the trend of prohibitive legislation towards scientific collecting and international exchange of taxonomic specimens, and instead building legal frameworks supportive of biodiversity research.

The main aim of the present study was to explore the value of several measures of handwriting in the study of motor abnormalities in patients with bipolar or psychotic disorders. 54 adult participants with a schizophrenia spectrum disorder or bipolar disorder and 44 matched healthy controls, participated in the study. Participants were asked to copy a handwriting pattern consisting of four loops, with an inking pen on a digitizing tablet. We collected a number of classical, non-linear and geometrical measures of handwriting. The handwriting of patients was characterized by a significant decrease in velocity and acceleration and an increase in the length, disfluency and pressure with respect to controls. Concerning non-linear measures, we found significant differences between patients and controls in the Sample Entropy of velocity and pressure, Lempel-Ziv of velocity and pressure, and Higuchi Fractal Dimension of pressure. Finally, Lacunarity, a measure of geometrical heterogeneity, was significantly greater in handwriting patterns from patients than from controls. We did not find differences in any handwriting measure on function of the specific diagnosis or the antipsychotic dose. Results indicate that participants with a schizophrenia spectrum disorder or bipolar disorder exhibit significant motor impairments and that these impairments can be readily quantified using measures of handwriting movements. Besides, they suggest that motor abnormalities are a core feature of several mental disorders and they seem to be unrelated to the pharmacological treatment.