Economic and agronomic impact assessment of wheat straw based alkyl polyglucoside produced using green chemical approaches

Results from a previous environmental impact assessment highlight the potential for the proposed process, that converts low-value agricultural residue (wheat straw) into a high-value biosurfactant, to result in significant (>75%) GHG savings, relative to the commercial candidate derived from palm kernel and wheat grain. This was achieved via the use of low-energy techniques like supercritical CO2 extraction, low-temperature microwave and in-situ fractionation of platform chemicals. Despite the environmental benefits, process commercialization relies on the economic feasibility of the production. Adopting a ‘cradle-to-gate’ life cycle costing approach, this paper has quantified the economic feasibility and resource efficiency characteristics of producing wheat-straw based APG, via the previously suggested green low-waste generating processes. Here, we undertook economic analysis of a wheat straw-derived APG production pathway, in comparison to palm-kernel and wheat-grain APG. Total processing costs were determined to range between $0.92-$1.87 per kg of wheat straw-APG demonstrating relatively better output service quality and energy efficiency, while conventional APG costs $1.95-$2.87 per kg, highlighting the significant potential of the residue-derived pathway to be scaled to commercial-level. In addition, a semi-quantitative assessment of the demand-based implications of adopting and scaling-up the green process, in the current context and practices of wheat cultivation was also undertaken. Potential agronomic impact that might be result from such scale-up scenarios, focusing on the effect of conventional residue incorporation practiced by farmers was assessed in detail to encourage farmers opt for informed choices and also to encourage both environmentally and economically sustainable systems-thinking

Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201

Formation of Super-Earths

Super-Earths are the most abundant planets known to date and are characterized by having sizes between that of Earth and Neptune, typical orbital periods of less than 100 days and gaseous envelopes that are often massive enough to significantly contribute to the planet's overall radius. Furthermore, super-Earths regularly appear in tightly-packed multiple-planet systems, but resonant configurations in such systems are rare. This chapters summarizes current super-Earth formation theories. It starts from the formation of rocky cores and subsequent accretion of gaseous envelopes. We follow the thermal evolution of newly formed super-Earths and discuss their atmospheric mass loss due to disk dispersal, photoevaporation, core-cooling and collisions. We conclude with a comparison of observations and theoretical predictions, highlighting that even super-Earths that appear as barren rocky cores today likely formed with primordial hydrogen and helium envelopes and discuss some paths forward for the future.Comment: Invited review accepted for publication in the 'Handbook of Exoplanets,' Planet Formation section, Springer Reference Works, Juan Antonio Belmonte and Hans Deeg, Ed

Traumatic brain injury: a comparison of diffusion and volumetric magnetic resonance imaging measures

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate-severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed

Comparisons of host mitochondrial, nuclear and endosymbiont bacterial genes reveal cryptic fig wasp species and the effects of Wolbachia on host mtDNA evolution and diversity

Background Figs and fig-pollinating wasp species usually display a highly specific one-to-one association. However, more and more studies have revealed that the "one-to-one" rule has been broken. Co-pollinators have been reported, but we do not yet know how they evolve. They may evolve from insect speciation induced or facilitated by Wolbachia which can manipulate host reproduction and induce reproductive isolation. In addition, Wolbachia can affect host mitochondrial DNA evolution, because of the linkage between Wolbachia and associated mitochondrial haplotypes, and thus confound host phylogeny based on mtDNA. Previous research has shown that fig wasps have the highest incidence of Wolbachia infection in all insect taxa, and Wolbachia may have great influence on fig wasp biology. Therefore, we look forward to understanding the influence of Wolbachia on mitochondrial DNA evolution and speciation in fig wasps. Results We surveyed 76 pollinator wasp specimens from nine Ficus microcarpa trees each growing at a different location in Hainan and Fujian Provinces, China. We found that all wasps were morphologically identified as Eupristina verticillata, but diverged into three clades with 4.22-5.28% mtDNA divergence and 2.29-20.72% nuclear gene divergence. We also found very strong concordance between E. verticillata clades and Wolbachia infection status, and the predicted effects of Wolbachia on both mtDNA diversity and evolution by decreasing mitochondrial haplotypes. Conclusions Our study reveals that the pollinating wasp E. verticillata on F. microcarpa has diverged into three cryptic species, and Wolbachia may have a role in this divergence. The results also indicate that Wolbachia strains infecting E. verticillata have likely resulted in selective sweeps on host mitochondrial DNA

A novel long non-coding natural antisense RNA is a negative regulator of Nos1 gene expression

Long non-coding natural antisense transcripts (NATs) are widespread in eukaryotic species. Although recent studies indicate that long NATs are engaged in the regulation of gene expression, the precise functional roles of the vast majority of them are unknown. Here we report that a long NAT (Mm-antiNos1 RNA) complementary to mRNA encoding the neuronal isoform of nitric oxide synthase (Nos1) is expressed in the mouse brain and is transcribed from the non-template strand of the Nos1 locus. Nos1 produces nitric oxide (NO), a major signaling molecule in the CNS implicated in many important functions including neuronal differentiation and memory formation. We show that the newly discovered NAT negatively regulates Nos1 gene expression. Moreover, our quantitative studies of the temporal expression profiles of Mm-antiNos1 RNA in the mouse brain during embryonic development and postnatal life indicate that it may be involved in the regulation of NO-dependent neurogenesis

Development of the Prevent for Work questionnaire (P4Wq) for assessment of musculoskeletal risk in the workplace: part 1-literature review and domains selection

Objective This study aims to define appropriate domains and items for the development of a self-administered questionnaire to assess the risk of developing work-related musculoskeletal disorder (WMSD) and the risk of its progression to chronicity. Design Literature review and survey study. Setting and participants A literature review and a two-round interview with 15 experts in musculoskeletal pain were performed to identify the available domains for WMSD assessment. Interventions and outcome To ensure quality, only validated questionnaires were included for the Delphi process. A three-round Delphi method, with three round steps, was used to select the most pertinent and relevant domains and items. Results Nine questionnaires were identified through the expert discussion and literature review, comprising 38 candidate domains and 504 items. In the first round of the Delphi group, 17 domains reached more than 70% agreement and were selected. In the second round, 10 domains were rejected, while 11 were selected to complete the pool of domains. In the third and final round, 89 items belonging to 28 domains were defined as significant to develop a WMSDs risk assessment questionnaire. Conclusions No specific risk assessment questionnaires for WMSDs were identified from the literature. WMSD risk of presence and chronicity can be defined by an assessment tool based on the biopsychosocial model and the fear-avoidance components of chronic pain. The present study provides the formulation and operationalisation of the constructs in domains and items needed for developing and validating the questionnaire

Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research

Despite the many positive outcomes, excessive mobile phone use is now often associated with potentially harmful and/or disturbing behaviors (e.g., symptoms of deregulated use, negative impact on various aspects of daily life such as relationship problems, and work intrusion). Problematic mobile phone use (PMPU) has generally been considered as a behavioral addiction that shares many features with more established drug addictions. In light of the most recent data, the current paper reviews the validity of the behavioral addiction model when applied to PMPU. On the whole, it is argued that the evidence supporting PMPU as an addictive behavior is scarce. In particular, it lacks studies that definitively show behavioral and neurobiological similarities between mobile phone addiction and other types of legitimate addictive behaviors. Given this context, an integrative pathway model is proposed that aims to provide a theoretical framework to guide future research in the field of PMPU. This model highlights that PMPU is a heterogeneous and multi-faceted condition

Assessing Internet addiction using the parsimonious Internet addiction components model - a preliminary study [forthcoming]

Internet usage has grown exponentially over the last decade. Research indicates that excessive Internet use can lead to symptoms associated with addiction. To date, assessment of potential Internet addiction has varied regarding populations studied and instruments used, making reliable prevalence estimations difficult. To overcome the present problems a preliminary study was conducted testing a parsimonious Internet addiction components model based on Griffiths’ addiction components (2005), including salience, mood modification, tolerance, withdrawal, conflict, and relapse. Two validated measures of Internet addiction were used (Compulsive Internet Use Scale [CIUS], Meerkerk et al., 2009, and Assessment for Internet and Computer Game Addiction Scale [AICA-S], Beutel et al., 2010) in two independent samples (ns = 3,105 and 2,257). The fit of the model was analysed using Confirmatory Factor Analysis. Results indicate that the Internet addiction components model fits the data in both samples well. The two sample/two instrument approach provides converging evidence concerning the degree to which the components model can organize the self-reported behavioural components of Internet addiction. Recommendations for future research include a more detailed assessment of tolerance as addiction component