Dictyostelium discoideum is gaining increasing attention as a model organism for the study of calcium binding and calmodulin function in basic biological events as well as human diseases. After a short overview of calcium-binding proteins, the structure of Dictyostelium calmodulin and the conformational changes effected by calcium ion binding to its four EF hands is compared to its human counterpart, emphasizing the highly conserved nature of this central regulatory protein. The calcium-dependent and -independent motifs involved in calmodulin binding to target proteins are discussed with examples of the diversity of calmodulin binding proteins that have been studied in this amoebozoan. The methods used to identify and characterize calmodulin binding proteins is covered followed by the ways Dictyostelium is currently being used as a system to study several neurodegenerative diseases and how it could serve as a model for studying calmodulinopathies such as those associated with specific types of heart arrythmia. Because of its rapid developmental cycles, its genetic tractability, and a richly endowed stock center, Dictyostelium is in a position to become a leader in the field of calmodulin research.

ICEpMERPH, the first integrative conjugative element [ICE] of the SXT/R391 family isolated in the United Kingdom and Europe was analyzed to determine the nature of its adaptive functions, its genetic structure and homology to related elements normally found in pathogenic Vibrio or Proteus species. Whole Genome Sequencing of Escherichia coli isolate KH802 [which contains the ICE pMERPH] was carried out using Illumina sequencing technology. ICEpMERPH has a size of 110 Kb and has 112 putative open reading frames [ORFs], the “Hotspot regions” of the element were found to contain putative restriction digestion systems, insertion sequences and heavy metal resistance genes that encode resistance to mercury, as previously reported but also surprisingly to arsenate. A novel arsenate resistance system was identified in Hotspot 4 of the element, and unrelated to other SXT/R391 elements. This arsenate resistance system is potentially linked to two genes, orf 69, encoding an organoarsenical efflux MFS transporter-like protein related to ArsJ and orf70, encoding an NAD-dependent glyceraldehyde-3-phosphate dehydrogenase. Phenotypic analysis using isogenic strains of AB1157 with and without the ICE revealed resistance to low levels of arsenate in the range 15-25 mM. This novel, low level resistance may have an important adaptive function in polluted environments, which often contain low levels of arsenate contamination. Bioinformatic analysis on the novel determinant and the phylogeny of ICEpMERPH is presented.

Physical-law based models are widely utilized in the aerospace industry. One such use is to provide flight dynamics models for use in flight simulators. For human-in-the-loop use, such simulators must run in real-time. Due to the complex physics of rotorcraft flight, to meet this real-time requirement, simplifications to the underlying physics sometimes have to be applied to the model, leading to model response errors in the predictions compared to the real vehicle. This study investigated whether a machine-learning technique could be employed to provide rotorcraft dynamic response predictions, with the ultimate aim of this model taking over when the physics-based model's accuracy degrades. In the current work, a machine-learning technique was employed to train a model to predict the dynamic response of a rotorcraft. Machine learning was facilitated using a Gaussian Process (GP) non-linear autoregressive model, which predicted the on-axis pitch rate, roll rate, yaw rate and heave responses of a Bo105 rotorcraft. A variational sparse GP model was then developed to reduce the computational cost of implementing the approach on large data sets. It was found that both of the GP models were able to provide accurate on-axis response predictions, particularly when the input contained all four control inceptors and one lagged on-axis response term. The predictions made showed improvement compared to a corresponding physics-based model. The reduction of training data to one-third (rotational axes) or one-half (heave axis) resulted in only minor degradation of the GP model predictions.

Accurate forecasting of wind power generation plays a key role in improving the operation and management of a power system network and thereby its reliability and security. However, predicting wind power is complex due to the existence of high non-linearity in wind speed that eventually relies on prevailing weather conditions. In this paper, a novel hybrid deep learning model is proposed to improve the prediction accuracy of very short-term wind power generation for the Bodangora Wind Farm located in New South Wales, Australia. The hybrid model consists of convolutional layers, gated recurrent unit (GRU) layers and a fully connected neural network. The convolutional layers have the ability to automatically learn complex features from raw data while the GRU layers are capable of directly learning multiple parallel sequences of input data. The data sets of five-minute intervals from the wind farm are used in case studies to demonstrate the effectiveness of the proposed model against other advanced existing models, including long short-term memory (LSTM), GRU, autoregressive integrated moving average (ARIMA) and support vector machine (SVM), which are tuned to optimise outcome. It is observed that the hybrid deep learning model exhibits superior performance over other forecasting models to improve the accuracy of wind power forecasting, numerically, up to 1.59 per cent in mean absolute error, 3.73 per cent in root mean square error and 8.13 per cent in mean absolute percentage error.

Although energy management of a microgrid is generally performed using a day-ahead scheduling method, its effectiveness has been questioned by the research community due to the existence of high uncertainty in renewable power generation, power demand and electricity market. As a result, real-time energy management schemes are recently developed to minimise the operating cost of a microgrid while high uncertainty presents in the network. This paper develops modified particle swarm optimisation (MPSO) algorithms to solve optimisation problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high uncertainty to effectively minimise the operational cost of the microgrid. The optimisation problems are formulated for real-time and scheduling approaches, and solution methods are developed to solve the problems. It is observed that the scheduling program demonstrates superior performance in all the cases, including uncertainty in prediction, as compared to the other energy management approaches, although solutions have significant deviations due to prediction errors.

Urban trees are often more sun- and wind-exposed than their forest-grown counterparts. These environmental differences can impact how many species grow – impacting trunk taper, crown spread, branch architecture, and other aspects of tree form. Given these differences, windthrow models derived from traditional forest production data sources may not be appropriate for urban forest management. Additionally, visual abnormalities historically labeled as “defects” in timber production may not have a significant impact on tree failure potential. In this study, we look at urban tree failures associated with Hurricane Irma in Tampa, Florida, USA. We used spatial analysis to determine if patterns of failure existed among our inventoried trees. We also looked at risk assessment data to determine which visual defects were the most common and the most likely to be associated with branch or whole-tree failure. Results indicate that there was no spatial pattern associated with the observed tree failures – trees failed or withstood the storm as individuals. While some defects like decay and dead wood were associated with increased tree failure, other defects like weak branch unions and poor branch architecture were less problematic.

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow (OPF) problem and is called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution (DE) operator in a single algorithmic framework. Additionally, an adaptive method (AM) is proposed to update the number of solutions evolved by each DE operator based on both the diversity of population and quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering the intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results and thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%.

This article explores the significant parallels between big tobacco companies and major social networking sites regarding their influence on public health and society. While acknowledging the fundamental differences in their products and services, the paper scrutinises both industries through five primary lenses: addiction, misinformation, lack of regulation, harm to public health, and youth targeting. Both industries exhibit addictive characteristics, have faced criticism for the spread of misinformation, operate with limited regulation and transparency, and have raised concerns about targeting young demographics. Moreover, the potential harm to public health is a significant concern, with tobacco leading to well-established physical health issues. At the same time, excessive social media use has been linked to psychological harm, particularly among young users. The comparison underscores the necessity for greater regulation and oversight of social media companies, highlighting the urgent need for more comprehensive policies to mitigate potential harm and safeguard public health in the digital age.

The spectra currently emerging from modern ground- and space-based astronomical instruments are of exceptionally high quality and resolution. To meaningfully analyse these spectra researchers utilise complex modelling codes to replicate the observations. The main inputs to these codes are atomic data such as excitation and photoionisation cross sections as well as radiative transition probabilities, energy levels and line strengths. In this publication the current capabilities of the numerical methods and computer packages used in the generation of these data are discussed. Particular emphasis is given to Fe-peak species and the heavy systems of tungsten and molybdenum. Some of the results presented to highlight certain issues and/or advances have already been published in the literature, while other sections present, for the first time, new recently evaluated atomic data.

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

Diabetic retinopathy is the most common microvascular complication of diabetes mellitus and one of the leading causes of blindness globally. Due to the progressive nature of the disease, earlier detection and timely treatment can lead to substantial reductions in the incidence of irreversible vision-loss. Artificial intelligence (AI) screening systems have offered clinically acceptable and quicker results in detecting diabetic retinopathy from retinal fundus and optical coherence tomography (OCT) images. Thus, this systematic review and meta-analysis of relevant investigations was performed to document the performance of AI screening systems that were applied to fundus and OCT images of patients from diverse geographic locations including North America, Europe, Africa, Asia, and Australia. A systematic literature search on Medline, Global Health, and PubMed was performed and studies published between October 2015 and January 2020 were included. The search strategy was based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines, and AI-based investigations were mandatory for studies inclusion. The abstracts, titles, and full-texts of potentially eligible studies were screened against inclusion and exclusion criteria. Twenty-one studies were included in this systematic review; 18 met inclusion criteria for the meta-analysis. The pooled sensitivity of the evaluated AI screening systems in detecting diabetic retinopathy was 0.93 (95% CI: 0.92-0.94) and the specificity was 0.88 (95% CI: 0.86-0.89). The included studies detailed training and external validation datasets, criteria for diabetic retinopathy case ascertainment, imaging modalities, DR-grading scales, and compared AI results to those of human graders (e.g., ophthalmologists, retinal specialists, trained nurses, and other healthcare providers) as a reference standard. The findings of this study showed that the majority AI screening systems demonstrated clinically acceptable levels of sensitivity and specificity for detecting referable diabetic retinopathy from retinal fundus and OCT photographs. Further improvement depends on the continual development of novel algorithms with large and gradable sets of images for training and validation. If cost-effectiveness ratios can be optimized, AI can become a financially sustainable and clinically effective intervention that can be incorporated into the healthcare systems of low-to-middle income countries (LMICs) and geographically remote locations. Combining screening technologies with treatment interventions such as anti-VEGF therapy, acellular capillary laser treatment, and vitreoretinal surgery can lead to substantial reductions in the incidence of irreversible vision-loss due to proliferative diabetic retinopathy.

Current epidemiological data reports that adults aged 65 years and older comprise the most vulnerable age group with the highest proportion of CAP-attributable hospitalizations. Pneumococcal vaccine efficacy (VE) has been shown to decrease over time, contributing to increasing incidence rates of CAP. A holistic evaluation of age, sex, seasonality, and VE are is conducted in this systematic review and meta-analysis of 12 prospective and retrospective cohort studies. The findings suggest that incidence and age are positively associated and that incidence in females is more often reported to be higher in females than in males. In studies that observed seasonality of CAP, high seasons and low seasons were reported to be in winter and summer months, respectively. Lastly, studies that reviewed the effect of vaccination on incidence consistently found decreased observance of CAP in elderly adults following reception of PCV13 or PPSV23. However, one study suggested that such vaccinations may have decreased effectiveness in elderly populations and that research examining potential explanations for this require further investigation. Furthermore, distinct diagnostic and case ascertainment standards, descriptive measures, and methods of prevention and treatment of CAP used across the US are outlined in this review. Public health guidance such as encouraging the reception of pneumococcal vaccinations and mask-wearing during high seasons of CAP, and communicating the risks of not adhering to the aforementioned preventative measures can facilitate an effort to reduce the incidence of CAP and its associated adverse outcomes in the US elderly population.

This is a study on fractals existing in music. The application case is the composition DIAPHONIES of Michael Paouris. Sliding-window fractal analysis indicate areas of continuous fractality dipped in non-fractal areas of possibly deterministic and stochastic nature. Diverging cases of pronounced non-fractal areas are addressed and also areas of mixed fractality and non-fractality. Many segments exhibit persistency-P (2

The rapid expansion of social media and instant messaging applications, such as WhatsApp, has transformed how individuals and organizations communicate and engage. This think piece explores the potential of integrating WhatsApp as a customer relationship management (w-CRM) tool within the education sector to foster and sustain long-term relationships among students, teaching staff, and non-teaching staff. By leveraging real-time features and the widespread use of WhatsApp, educational institutions can create a more interactive and dynamic learning environment, benefiting all stakeholders involved. The literature highlights the importance of establishing clear frameworks for mutual engagement and interaction and the potential of w-CRM to improve communication between students' families and educational institutions. There are potential risks associated with the pervasive use of WhatsApp, and call for future research to explore strategies for mitigating these risks while maximizing the benefits of w-CRM in the education sector. Longitudinal studies are recommended to evaluate the long-term impact of w-CRM on stakeholder relationships, student outcomes, and overall institutional performance.

In this work, anchoring of cinchona derivatives to trifunctional cores (hub approach) was demonstrated to obtain size-enlarged organocatalysts. By modifying the cinchona skeleton in different positions, we prepared four C3-symmetric size-enlarged cinchona derivatives (hub-cinchonas), which were tested as organocatalysts and their catalytic activities were compared with the parent cinchona (hydroquinine) catalyst. We showed that in the hydroxyalkylation reaction of indole, hydroquinine provides good enantioselectivities (up to 73% ee), while the four new size-enlarged derivatives gave significantly lower values (up to 29% ee) in this reaction. Anchoring cinchonas to trifunctional cores was found to facilitate nanofiltration-supported catalyst recovery using PolarClean alternative solvent. The C3-symmetric size-enlarged organocatalysts were completely rejected by all the applied membranes, whereas the separation of hydroquinine was found to be insufficient using organic solvent nanofiltration. Furthermore, the asymmetric catalysis was successfully demonstrated in the case of Michael reaction of 1,3-diketones and trans-β-nitrostyrene using Hub3-cinchona (up to 96% ee) as a result of the positive effect of the C3-symmetric structure using a bulkier substrate. This means an increased selectivity of the catalyst in comparison to hydroquinine in the latter Michael reaction.

The COVID-19 pandemic has caused unprecedented challenges in the care of children with cerebral palsy (CP) and other neuromuscular complex chronic conditions (NCCC). The purpose of this study was to explore the direct impact of the COVID-19 pandemic on healthcare delivery. From May to August 2020, medical professionals caring for CP and NCCC patients across multiple countries and disciplines completed a self-administered cross-sectional survey comparing practices before and during the COVID-19 pandemic. Of the 79 healthcare workers from 8 countries who participated—predominantly pediatric orthopedic surgeons (32%), pediatricians (30%), and pediatric physiatrists (23%)—most felt that caring for NCCC patients during the pandemic presented with unique difficulties and reported a significant decrease in in-person NCCC clinic volume (p<0.001), multidisciplinary appointments (p<0.001), surgical cases (p=0.005), and botulinum toxin/phenol injections. Most providers affirmed that institutional guidelines for perioperative emergent/urgent and elective procedures, workplace settings, and technology were modified to accommodate the ongoing public health crisis. Usage of telemedicine significantly increased for NCCC patient visits (p<0.001). During the COVID-19 pandemic, many children with NCCC lost access to routine, multidisciplinary care. Telemedicine became an integral part of communication and management. In the setting of the COVID-19 pandemic and threat of future healthcare disruptions, these data lay the foundation for trending the evolution of healthcare delivery and accelerating best practice guidelines for children with CP and NCCC.

Doxorubicin (Dox) is a commonly used chemotherapeutic that can adversely affect skeletal muscle, including causing muscle atrophy. Dox is known to induce an event known as mitochondrial permeability transition (MPT) in cardiac muscle and this plays an important role in Dox-mediated cardiac toxicity. Further to this, recent evidence identifies MPT as a mechanism of atrophy in skeletal muscle, suggesting that MPT may underlie some of the Dox-related toxicity in skeletal muscle. To test this hypothesis, we used cultured human primary myotubes, C2C12 myotubes, and single adult mouse flexor digitorum brevis (FDB) muscle fibers in experiments involving Dox treatment with or without inhibitors of MPT. Dox treatment of myotubes caused myonuclear translocation of the mitochondrial protein apoptosis inducing factor (AIF) and increased mitochondrial reactive oxygen species (mROS), consistent with the known consequences of MPT. Furthermore, Dox caused atrophy in C2C12 myotubes grown on patterned plates, human primary myotubes, and single muscle fibers from adult mice. Notably, Dox-induced atrophy could be prevented by a wide variety of agents that inhibit MPT, as well as by inhibiting mROS or Caspase 3. In conclusion, our results indicate that MPT plays an important role in driving Dox-mediated skeletal muscle atrophy.

The aim of this systematic review and meta-analysis is to evaluate the prevalence of depression, anxiety, insomnia, stress, PTSD, and distress in Chinese healthcare workers (HCWs) and the changes in prevalence before and after the peak incidence of COVID-19 in China. 20 cross-sectional studies assessing the aforementioned psychological outcomes were included. Eligible studies were searched from the following databases: PubMed, Scopus, and Web of Science. Comparative analysis based on the time period of the included studies was conducted to assess changes in prevalence before and after peak incidence. Additionally, subgroup analyses based on study quality, province, survey tools, gender and healthcare profession, frontline or non-frontline working status, and severity of psychological outcomes were conducted to evaluate the prevalence of outcomes across various study methods, geographic regions, and professions. The findings of this study suggest that the overall prevalence of depression, anxiety, insomnia, stress, PTSD, and distress before peak incidence were 36.2%, 34.2%, 22.4%, 31.3%, 9.8%, and 56.7% as opposed to 31.8%, 24.1%, 34.4%, 59.0%, 20.9%, and 40.7% after the peak. The higher prevalence of depression, anxiety, and distress prior to the peak incidence of COVID-19 in China and of insomnia, stress, and PTSD thereafter serve as evidence that the mental health decline of HCWs is dynamic and should be addressed with adaptive approaches that provide tailored treatments.

The state of community lock-down due to COVID-19 pandemic caused restricted movements of people. There are existing evidence of the negative impact of quarantine and isolation to the mental health of a person in different contexts. A scoping review of literature using Google Scholar was conducted to discover records about the public mental health while in a community quarantine due to COVID-19 pandemic. A methodological approach suggested by Arksey and O’Malley was utilized. It comprised (a) identifying the research questions, (b) identifying relevant literatures, (c) selecting literature, (d) charting the extracted data, and (e) summarizing, analyzing, and reporting the results. As of April 17, 2020, there were only 4 original articles found that discuss psychosocial aspect of the COVID-19 crisis. After an online survey, they present evidence that (1) there is an outward change in the people’s behavior toward self-care during the pandemic and (2) trusting the community governing bodies can minimize the level of anxiety and stress. Other literatures found are original articles in preprint (n=8), letters, commentaries, editorial (n=6), review paper (n=4), and WHO guideline (n=1). It is evident that the psychosocial aspect of COVID-19 crisis needs more attention from the scholars and a large research gap can be lessened trough expansion of online platforms.

Soccer is the most played sport worldwide, with over 265 million participants. It is an incredibly demanding sport, with many different technical skills and physical loads placed on the body. This makes post-match recovery strategies amongst high level soccer players of great importance. The aim of this review is to summarize the existing literature on stretching for post-match recovery, examining its relation to injury prevention, Delayed Onset Muscle Soreness (DOMS), and performance. Scientific evidence of the highest quality and relevance was extracted and reviewed. Despite its common practice, evidence does not support static stretching as a modality to improve recovery post-match amongst soccer players. Larger trials with important outcome measures are needed to determine if a post-match stretching regimen to facilitate recovery exists.

Coronavirus disease of 2019 (COVID-19) is the clinical manifestation of the respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While primarily recognized as a respiratory disease, it is clear that COVID-19 is systemic illness impacting multiple organ systems. One defining clinical feature of COVID-19 has been the high incidence of thrombotic events. The underlying processes and risk factors for the occurrence of thrombotic events in COVID-19 remain inadequately understood. While severe bacterial, viral or fungal infections are well recognized to activate the coagulation system, COVID-19 associated coagulopathy is likely to have unique mechanistic features. Inflammatory-driven processes are likely primary drivers of coagulopathy in COVID-19, but the exact mechanisms linking inflammation to dysregulated hemostasis and thrombosis are yet to be delineated. Cumulative findings of microvascular thrombosis has raised question if the endothelium and microvasculature should be a point of investigative focus. Von Willebrand Factor (VWF) and its protease, ADAMTS13 play important role in the maintenance of microvascular hemostasis. In inflammatory conditions, imbalanced VWF-ADAMTS13 characterized by elevated VWF levels and inhibited and/or reduced activity of ADAMTS13 has been reported. Also, an imbalance between ADAMTS13 activity and VWF antigen is associated with organ dysfunction and death in patients with systemic inflammation. A thorough understanding of VWF-ADAMTS13 interactions during early and advanced phases of COVID-19 could help better define the pathophysiology, guide thromboprophylaxis and treatment and improve clinical prognosis.

The reaction of arylidene-α-amino esters with electrophilic alkenes to yield the Michael type addition compounds is optimized using several phosphines as organocatalysts. The transformation is very complicated due to the generation of several final compounds, including those derived from the 1,3-dipolar cycloadditions. For this reason, the selection of the reaction conditions is a very complex task and the slow addition of the acrylic system is very important to complete the reaction. The study of the variation of the structural components of the starting imino ester is performed as well as the expansion of other electron-poor alkenes. The crude products have a purity higher than 90% in most cases without any purification. A plausible mechanism is detailed based on the bibliography and the experimental results. The synthesis of pyroglutamate entities, after reduction of the imino group and cyclization, is performed in high yields. In addition, the hydrolysis of the imino group, under acidic media, represents a direct access to glutamate surrogates.

In both managed and unmanaged forests, termites are functionally important members of the dead-wood-associated (saproxylic) insect community. However, little is known about regional-scale environmental drivers of geographic distributions of termite species, and how these environmental factors impact co-occurrence among congeneric species. Here we focus on the southern Appalachian Mountains—a well-known center of endemism for forest biota—and use Ecological Niche Modeling (ENM) to examine the distributions of three species of Reticulitermes termites (i.e., R. flavipes, R. virginicus, and R. malletei). To overcome deficiencies in public databases, ENMs were underpinned by field-collected high-resolution occurrence records coupled with molecular taxonomic species identification. Spatial overlap among areas of predicted occurrence of each species was mapped, and aspects of niche similarity were quantified. We also identified environmental factors that most strongly contribute to among-species differences in occupancy. Overall, we found that R. flavipes and R. virginicus showed significant niche divergence, which was primarily driven by dry-season precipitation. Also, all three species were most likely to co-occur in the mid-latitudes of the study area (i.e., northern Alabama and Georgia, eastern Tennessee and western North Carolina), which is an area of considerable topographic complexity. This work provides important baseline information for follow-up studies of local-scale drivers of these species’ distributions. It also identifies specific geographic areas where future assessments of the frequency of true syntopy vs. micro-allopatry, and associated interspecific competitive interactions, should be focused.

Molecular autism research is evolving towards a biopsychosocial framework that is more informed by autistic experiences. In this context, research aims are moving away from correcting external autistic behaviors and towards alleviating internal distress. Autism Spectrum Conditions (ASCs) are associated with high rates of depression, suicidality and other comorbid psychopathologies, but this relationship is poorly understood. Here, we integrate emerging characterizations of internal autistic experiences within a molecular framework to yield insight into the prevalence of psychopathology in ASC. We demonstrate that descriptions of social camouflaging and autistic burnout resonate closely with the accepted definitions for early life stress (ELS) and chronic adolescent stress (CAS). We propose that social camouflaging could be considered a distinct form of CAS that contributes to allostatic overload, culminating in a pathophysiological state that is experienced as autistic burnout. Autistic burnout is thought to contribute to psychopathology via psychological and physiological mechanisms, but these remain largely unexplored by molecular researchers. Building on converging fields in molecular neuroscience, we discuss the substantial evidence implicating mitochondrial dysfunction in ASC to propose a novel role for mitochondrial allostatic load in the relationship between autism and psychopathology. An interplay between mitochondrial, neuroimmune and neuroendocrine signaling is increasingly implicated in stress-related psychopathologies, and these molecular players are also associated with neurodevelopmental, neurophysiological and neurochemical aspects of ASC etiology. Together, this suggests an increased exposure and underlying molecular susceptibility to ELS that increases the risk of psychopathology in ASC. This article describes an integrative framework shaped by autistic experiences that highlights novel avenues for molecular research into mechanisms that directly affect the quality of life and well-being of autistic individuals. Moreover, this framework emphasizes the need for increased access to diagnoses, accommodations, and resources to improve mental health outcomes in autism.

Disruptive selection arises when extreme phenotypes have a fitness advantage compared to more intermediate phenotypes. Theory and evidence suggest that intraspecific resource competition is a key driver of disruptive selection. However, while competition can be indirect (exploitative) or direct (interference), the role of interference competition in disruptive selection has not been tested, and most models of disruptive selection assume exploitative competition. We experimentally investigated whether the type of competition affects the outcome of competitive interactions using a system where disruptive selection is common: Mexican spadefoot toads (Spea multiplicata). Spea tadpoles develop into alternative resource-use phenotypes: carnivores, which consume fairy shrimp and other tadpoles, and omnivores, which feed on algae and detritus. Tadpoles intermediate in phenotype have low fitness when competition is intense, as they are outcompeted by the specialized tadpoles. Our experiments revealed that the presence of carnivores significantly decreased foraging behavior in intermediate tadpoles, and that intermediate tadpoles had significantly lower growth rates in interference competition treatments with carnivores but not with omnivores. Interference competition may therefore be important in driving disruptive selection. As carnivore tadpoles are also cannibalistic, the ‘fear’ effect may have a greater impact on intermediate tadpoles than exploitative competition alone, similarly to non-consumptive effects in predator-prey or intraguild relationships.

This review discusses a broad range of recent advances (2013-2017) of chemical imaging using electrochemical methods, with a particular focus on techniques that have been applied to study cellular processes, or techniques that show promise for use in this field in the future. Non-scanning techniques such as microelectrode arrays (MEAs) offer high time-resolution (< 10 ms) imaging, however at reduced spatial resolution. In contrast, scanning electrochemical probe microscopies (SEPMs) offer higher spatial resolution (as low as a few nm per pixel) imaging, with images collected typically over many minutes. Recent significant research efforts to improve the spatial resolution of SEPMs using nanoscale probes, and to improve the temporal resolution using fast scanning have resulted in movie (multiple frame) imaging with frame rates as low as a few seconds per image. Many SEPM techniques lack chemical specificity or have poor selectivity (defined by the choice of applied potential for redox-active species). This can be improved using multifunctional probes, ion-selective electrodes and tip-integrated biosensors, although additional effort may be required to preserve sensor performance after miniaturization of these probes. We discuss advances to the field of electrochemical imaging, and technological developments which are anticipated to extend the range of processes that can be studied. This includes imaging cellular processes with increased sensor selectivity and at much improved spatiotemporal resolution than has been previously customary.

One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training system. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrate good potential as a monitoring tool for orchard management.

The philosophy of testing statistical hypothesis is a natural consequence and functional extension of mathematical analysis of Probability. Along with the concept of recurrence when applied to random sequences and functions, it leads to the analysis of a priori and posterior which implies testing statistical hypothesis. Testing statistical hypothesis also involves algebraic, functional and dimensional considerations, which are found in the works of Laplace. Aspects of mathematical analysis such as universality of solutions, Laws of Large Numbers, Entropy, Information, and various functional dependencies are the main factors explained in the five properties that lead to implication of testing statistical hypothesis. Various interesting examples with modern scientific significance from genetics, astrophysics, and other areas give methodological access to answers of different problems and phenomena which are involved in the logic of testing statistical hypothesis.

Gap junctions (GJ) and connexins play integral roles in cellular physiology and have been found to be involved in multiple pathophysiological states from cancer to cardiovascular disease. Studies over the last 60 years have demonstrated the utility of altering GJ signaling pathways in experimental models, which has led to them being attractive targets for therapeutic intervention. A number of different mechanisms have been proposed to regulate GJ signaling, including channel blocking, enhancing channel open state, and disrupting protein-protein interactions. The primary mechanism for this has been through the design of numerous peptides as therapeutics, that are either currently in early development or are in various stages of clinical trials. Despite over 25 years of research into connexin targeting peptides, the overall mechanisms of action are still poorly understood. In this overview, we discuss published connexin targeting peptides, their reported mechanisms of action and the potential for these molecules in the treatment of disease.

An efficient stereoselective three-component reaction for the synthesis of spiro[4H-chromene-3,3’-oxindole] derivatives was realized through an organocatalyzed cascade Knoevenagel/Michael/cyclization reaction using a quinidine-derived squaramide as the catalyst. Under the optimized conditions, the reactions of isatins, malononitrile, and sesamol yield the desired spirooxindoles in good yields (75–87%) and moderate to high ee values (up to 90% ee). Two pairs of selected enantiomers were subjected to evaluate their antiproliferative activities on three types of human cancer cell lines using the MTT assay. The results indicated that stereoselectivity and electrical effect showed significant impact on activity. Enanotiomer R-3f exhibited optimal cytotoxic activity against U2OS cell line, which was close to the inhibitory activity of positive control, Adriamycin.

The steady state tube furnace (SSTF) (ISO/TS 19700) was used to assess the effects altering the reaction zone of a flame had on smoke toxicity measurements. The gas inlet of the apparatus was modified to allow for a mixture of nitrogen and air to be introduced into the system. The volume of air used in each test remained at 2 L min-1 , and additional volumes of nitrogen were varied between tests altering the total volume of gas used in the primary gas inlet. The chosen conditions were representative of under-ventilated flaming by using a restricted oxygen environment. The research shows that the increase in volume flow of gas over a sample increased the smoke toxicity of the materials tested (CO and HCN). When increasing the volume of the primary air-flow through the tube furnace, the flow causes thinning of the flame zone in the apparatus and results in gaseous species spending less time in the reaction zone, resulting in less time available for chemical reactions to occur. This resulted in less complete combustion occurring, and hence an increased yield of measured products of incomplete combustion (CO and HCN), and a decreased yield of products of complete combustion (CO2).

This article describes the transition of an undirected active network, used for numerical and logical analysis, and made up of communicating operators and nodes, and being self-extensible, into a network of semantic structures, and the extensions necessary to handle language. The network, called Active Structure, was infused with knowledge in the form of tens of thousands of definitions taken from a human-readable dictionary. Where the dictionary fell short, from circularity, lack of a hierarchical form for its senses and sub senses, or inadequate detail around verbs, the entries were extensively curated. The result is a machine which has access to every meaning of every word in its vocabulary, and needs to manage the right meaning for every use of a word, a task that our unconscious minds now handle. To demonstrate that such a network can aspire to human-level tasks, we have begun loading an Anti-Money Laundering Act so that the machine can devise and test strategies against money launderers. There is a higher goal being aimed at, the breaking of the Four Pieces Limit. That is, the network is not intended to save money on human cognitive labor, but to raise an absurdly low limit on it.

The eastern subterranean termite, Reticulitermes flavipes, currently inhabits previously glaciated regions of the northeastern U.S., as well as the unglaciated southern Appalachian Mountains and surrounding areas. We hypothesized that Pleistocene climatic fluctuations have influenced the distribution of R. flavipes, and thus the evolutionary history of the species. We estimated contemporary and historical geographic distributions of R. flavipes by constructing Species Distribution Models (SDM). We also inferred the evolutionary and demographic history of the species using mitochondrial (cytochrome oxidase I and II) and nuclear (endo-beta-1,4-glucanase) DNA sequence data. To do this, genetic populations were delineated using Bayesian spatial genetic clustering, competing hypotheses about population divergence were assessed using approximate Bayesian computation (ABC), and changes in population size were estimated using Bayesian skyline plots. SDMs identified areas in the north with suitable habitat during the transition from the Last Interglacial to the Last Glacial Maximum, as well as an expanding distribution from the mid-Holocene to the present. Genetic analyses identified three geographically cohesive populations, corresponding with northern, central, and southern portions of the study region. Based on ABC analyses, divergence between the Northern and Southern populations was the oldest, estimated to have occurred 64.80 thousand years ago (kya), which corresponds with the timing of available habitat in the north. The Central and Northern populations diverged in the mid-Holocene, 8.63 kya, after which the Central population continued to expand. Accordingly, phylogeographic patterns of R. flavipes in the southern Appalachians appear to have been strongly influenced by glacial-interglacial climate change.

Iterated games, in which the same economic interaction is repeatedly played between the same agents, are an important framework for understanding the effectiveness of strategic choices over time. To date very little work has applied information theory to the information sets used by agents in order to decide what action to take next in such strategic situations. This article looks at the mutual information between previous game states and an agent's next action by introducing two new classes of games: ’invertible games’ and ‘cyclical games'. By explicitly expanding out the mutual information between past states and the next action we show under what circumstances these expressions can be simplified. These information measures are then applied to the Traveler's Dilemma game and the Prisoner's Dilemma game, the Prisoner's Dilemma being invertible, to illustrate their use. In the Prisoner's Dilemma a novel connection is made between the computational principles of logic gates and both the structure of games and the agents' decision strategies. This approach is applied to the cyclical game Matching Pennies to analyse the foundations of a behavioural ambiguity between two well studied strategies: ‘Tit-for-Tat' and ’Win-Stay, Lose-Switch'.

Technological advancements in the Internet of Things (IoT), unmanned aerial vehicles (UAVs), and novel technological tools have transformed disaster management practices from localized approaches to a global framework. These innovations necessitate a unified understanding and application of diverse methodologies at an international level, ensuring they are accessible and operational across different sectors. This integration is crucial not only for technical personnel but also for medical teams, who play a pivotal role in disaster response and management. By fostering a comprehensive grasp of these methods, we can enhance coordination, efficiency, and effectiveness in addressing disasters on a global scale. The authors aimed to provide a comprehensive overview of emerging techniques that are driving shifts in strategic approaches and treatment technologies. Recognized as a domain of continuous research and development, this overview, by necessity, remains an incomplete snapshot of an evolving field. It highlights the dynamic nature of technological and strategic advancements, underscoring the importance of ongoing investigation and innovation to stay abreast of current trends and future directions. The article also highlights the importance of international collaboration beyond societal and national boundaries A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Large blocks and boulders of banded iron formation and massive hematite up to 40 x 27 x 6 m and in excess of 10,000 metric tonnes were detached from outcrop of the Wilgie Mia Formation during the ca 2.20 Ga marine transgression at the base of the Paleoproterozoic Windplain Group, and deposited in a broad band on the wave-cut surface 900 to 1200 m to the east. At the same time sand and shingle was scoured from the sea floor, leaving remnants only on the western side of the Wilgie Mia Formation and on the eastern sides of the boulders. Evidence suggesting that the blocks were detached and transported and the sea floor scoured by a tsunami bore with a height of at least 40 m is provided by (1) the deposition of the blocks indicates transportation by a unidirectional sub-horizontal force, whereas the smaller boulders are randomly oriented (2) 900 -1200m separating the BIF outcrop and the blocks (3) the absence of the basal conglomerate between the blocks (4) the blocks and boulders rest directly on the wave-cut surface of deeply weathered amphibolites (5) the blocks and boulders are surrounded and overlain by fine-grained sandstone of the Windplain Group.

Bioprospecting native Australian plants offers potential discovery of latent and novel bioactive compounds. Promising cytotoxic and antibacterial activity of methanolic extracts of Pittosporum angustifolium and Terminalia ferdinandiana led to further fractionation and isolation using our laboratory’s bioassay guided fractionation protocol. Hence, the aim of this study was to further evaluate the bioactivity of the fractions and subfractions and characterize bioactive compounds using liquid chromatography mass spectroscopy (LC-MS/MS) and gas chromatography MS (GC-MS). Compounds tentatively identified in P. angustifolium Fraction 1 using LC-ESI-QTOF-MS/MS were chlorogenic acid and/or neochlorogenic acid, bergapten, berberine, 8’-epitanegool and rosmarinic acid. GC-MS analysis data showed the presence of around 100 compounds, mainly comprising of carboxylic acids, sugars, sugar alcohols, amino acids, and monoalkylglycerols. Furthermore, the fractions obtained from T. ferdinandiana flesh extracts showed no cytotoxicity, except against HT29 cell lines, and only Fraction 2 exhibited some antibacterial activity. The reduced bioactivity observed in the T. ferdinandiana fractions could be attributed to the potential loss of synergy as compounds become separated within the fractions. As a result, further fractionation, and separation of compounds in these samples were not pursued. However, additional dose-dependent studies are warranted to validate the bioactivity of T. ferdinandiana flesh fractions, particularly since this is an understudied species. Moreover, LC-MS/GC-MS studies confirm the presence of bioactive compounds in P. angustifolium Fraction 1/subfractions which helps to explain the significant acute anti-cancer activity of this plant. The screening process designed in this study has the potential to pave the way for developing scientifically validated phytochemical/bioactivity information on ethnomedicinal plants, thereby facilitating further bioprospecting efforts, and supporting the discovery of novel drugs in modern medicine.

A Mitochondrial dysfunction and oxidative stress are major contributors to the pathophysiology of neurodegenerative diseases, including Alzheimer’s disease (AD). However, the mechanisms driving mitochondrial dysfunction and oxidative stress are unclear. Familial AD (fAD) is an early onset form of AD caused primarily by mutations in the presenilin-encoding genes. Previously, using Caenorhabditis elegans as a model system to study presenilin function, we found that loss of C. elegans presenilin orthologue, SEL-12, results in elevated mitochondrial and cytosolic calcium levels. Here, we provide evidence that elevated neuronal mitochondrial generated reactive oxygen species (ROS) and subsequent neurodegeneration in sel-12 mutants are a consequence of the increase of mitochondrial calcium levels and not cytosolic calcium levels. We also identify mTORC1 signaling as a critical factor in sustaining high ROS in sel-12 mutants in part through its repression of the ROS scavenging system SKN-1/Nrf. Our study reveals that SEL-12/presenilin loss disrupts neuronal ROS homeostasis by increasing mitochondrial ROS generation and elevating mTORC1 signaling, which exacerbates this imbalance by suppressing SKN-1/Nrf antioxidant activity.

Smart manufacturing encompasses a category of manufacturing that employs computer-integrated capabilities and technologies to enhance supply chain optimization, production efficiency, and recyclability. Yet limited studies have been conducted to optimize these prospects from the perspective of low resource countries where such innovative studies have not been adequately explored. This paper aims to examine the implications of smart manufacturing practices (Smart Procurement, Smart Supply Chain, Smart Production Planning and Control, Automation and Industrial Robot, and Supply Chain Configuration) on pro-environmental behaviour and develop a baseline moderated mediation model to explain the relationship between smart manufacturing and pro-environmental behaviour with a role of green dynamic capability, and environmental orientation. This study is anchored on quantitative research approach, deductive reasoning, and explanatory design. Cross – sectional survey data have been obtained from 382 manufacturing companies in Ghana. Our hypotheses have been tested using Structural Equation Modelling and SMART-PLS version 3.8.9. The study has revealed that smart manufacturing practices significantly and positively relate to pro-environmental behaviour. Moreover, green dynamic capability and environmental orientation moderate the relationship between smart manufacturing and pro-environmental behaviour. The implications of the study include the emergence of a baseline model to guide policymakers, practitioners, and academicians to explain the relationship between smart manufacturing and sustainable manufacturing in the context of developing countries. Again, the social implication of the study includes the realisation of decent job and economic growth, responsible consumption and production as well as actions taken to combat climate change.

As new vaccines reduce P. falciparum (Pf) cases, clinicians can focus on rescuing more children with cerebral malaria (CM). Adjunctive “therapeutically-rational exchange transfusion” (T-REX) refers to using special “Pf-resistant” donor red blood cells (RBCs) that secrete nano-sized RBC extracellular vesicles (EVs). Can some RBC EVs rapidly dislodge Pf-infected RBCs (iRBCs) sequestered in blood vessels and reduce inflammation? Does post-exchange “rebound parasitemia” reflect sequestration-reversal? We reviewed case-reports, EV and liposome studies, expert perspectives, and time-sequence data. In the AQUAMAT study, median coma-recovery time was 20 hours for artesunate. In contrast, a CM patient treated with type-O T-REX quickly began speaking (during the procedure). For other rapid-recovery CM patients, donor RBC variables had not been specified. Despite rapid Pf-killing, drugs need 20 hours to substantially reduce iRBC cytoadhesion while EVs can selectively bind distant inflamed tissues within 15 minutes. RBCs stressed by blood-bank storage and Pf infection secrete EVs. Post-exchange “rebound parasitemia” can occur within 60 minutes and may reflect release of sequestered iRBCs. Sequestration-reversal can be assessed by monitoring Pf parasitemia and total Pf biomass. New data suggest clinicians, working with transfusion- and laboratory-medicine physicians, can, and should, assess T-REX options and publish their findings to help clarify how RBC EVs may serve as therapeutic “decoy ligands.”

Forest plantations have a large potential for carbon sequestration, playing an important role in the global carbon cycle. However, despite the huge amount of research carried out worldwide, the absolute contribution of industrial forest plantations is still incomplete for some parts of the world. To contribute to bridge this gap, we calculated the amount of C stock in three fast growing forest species in Chile. Relevant C pools (above-ground and below-ground biomass, forest floor, and soil) were considered for this analysis. Across the industrial plantation forests of Chile, carbon accumulated in the above-ground biomass was 181–212 Mg · ha−1 for Pinus radiata, 147–180 Mg · ha−1 for Eucalyptus nitens, and 95–117 Mg · ha−1 for Eucalyptus globulus (age 20–24 years for P.radiata and 10–14 years for Eucalyptus). Our results agree with other studies showing that 30%–50% of the total C stock is stored in the soil. Total C stocks were for 343 Mg · ha−1 for P.radiata, 352 Mg · ha−1 for E.nitens, and 254 Mg · ha−1 for E. gloubulus, also at the end of a typical rotation. The carbon pool in the forest floor was found to be significantly lower (less than 4% of the total) when compared to the other pools and showed large spatial variability. We conclude that industrial forest plantations are a valuable tool to reduce atmospheric CO2 and mitigate climate change. Given the contribution of soils to total carbon stocks, special attention should be paid to forest management activities that affect the soil organic carbon pool.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

Starting from acid chlorides, alkynes, tryptamines, and acroyl chloride, 21 densely substituted tetrahydro-beta-carbolines are prepared in a four-component one-pot reaction. In this study, the aza-Michael addition step to generate intermediate enaminones is optimized in the presence of ytterbium triflate. Moreover, apart from acroyl chloride, all reactants can be deployed in almost equimolar ratios, which increases the atom economy of the sequence. For mechanistic rationali-zation, the concluding aza-anellation was investigated by DFT calculations on potential inter-mediates and corresponding activation energies, revealing that the aza-anellation rather pro-ceeds via ene-reaction than via electrocyclization.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

Oilseed plants of the Brassicaceae plant family are cultivated for food, feed and industrial purposes on large-scale in Europe. This review gives an overview of current market-oriented applications of new genomic techniques (NGTs) in relevant Brassicaceae oilseed crops based on a literature survey. In this respect, changes in oil quality, yield, growth and resistance to biotic and abiotic stress are goals in oilseed rape (B. napus) and camelina (C. sativa). Environmental risk assessment scenarios are developed for specific NGT applications in Brassicaceae oilseed crops with either a changed oil composition or with fitness related traits. In case of a changed oil composition an increase or decrease of polyunsaturated fatty acids (PUFA) demonstrates risks for health and survival of pollinators. In case of fitness related traits other risks were identified, i. e. an increased risk of spread and persistence of NGT plants. Furthermore, there are indications for potential disturbance of interactions with the environment, involving signalling pathways and reaction to stress conditions. It is shown that for a comprehensive risk assessment the technological potential of NGTs, the plants’ biology and the scale of releases have to be considered in combination. Therefore, the release of NGT plants into the environment for agricultural purposes will require risk assessment and monitoring of single traits as well as of combinatorial and long-term cumulative effects. In addition, risk management should develop concepts and measures to control and potentially restrict the scale of releases. This is especially relevant for NGT Brassicaceae in Europe which is a centre of diversity of this plant family.

Mild traumatic brain injury (mTBI) is the most common brain injury, seen in sports, falls, vehicle, or workplace injuries. Concussion is the most common type of mTBI. Assessment of impairments from concussion are evolving, with oculomotor testing suggested as a key component in a multi-modality diagnostic protocol. The aim of this study was to evaluate the reliability of one eye-tracking system, the EyeGuide Focus. Seventy-five healthy adolescent and adult participants (adolescents: n=28; female=11, male=17, mean age 16.5 ± 1.4 years; adults n=47; female=22; male=25, mean age 26.7 ± 7.0 years) completed three repetitions of the EyeGuide Focus within the one session. Intraclass correlation coefficient (ICC) analysis showed the EyeGuide Focus had overall good reliability (ICC 0.79, 95%CI: 0.70, 0.86). However, a familiarization effect showing improvements in subsequent trials was noticeable in both cohorts (p<0.001) with adolescent participants showing greater familiarisation effects than adults. No differences were observed between sexes (p=0.69). Overall, the EyeGuide Focus was found to be reliable, but the observation of familiarization effects suggests that a standardized protocol of a minimum of three trials be employed, similar to other eye-movement testing applications.

The concept of a Social License to Operate (SLO) has become increasingly important in the sustainability literature in recent years. Having its origins in the business discourse of the mining industry with respect to limiting opposition to mining projects, the notion of a social contract above and beyond legal requirements has since become applied across a number of different industries. Despite the concepts adoption confusion exists over the practices and outcomes of SLO, and particularly the nature of engagement. Given this situation it is surprising that not more attention to the role of marketing, and social marketing in particular, in operationalizing the concept. The paper discusses the potential of social marketing to contribute to SLO. Economic, political and social relations are complex in SLO and exchange is intricate in such relational environments. A community-based social marketing orientation is proposed as a means to improve exchange relations and enhance engagement. Seven models of SLO related social marketing models are discussed with community-based social marketing and adaptive co-marketing models being regarded as the most positive for the achievement of an SLO. Potential barriers to adoption of these approaches are noted.

Purpose: This study aims to provide a foundational understanding of patient-centric perceptions of telemedicine implementation in rural Minnesota. Methods: This retrospective cohort study utilized a mail questionnaire to assess patient attitudes and behaviors regarding telemedicine during the emergency response to COVID-19. The target population was patients of a Primary Care clinic in eastern Minnesota. Descriptive statistics were used to assess respondents’ level of agreement with survey items scored on a 0-10 scale. Results: A majority of the respondents indicated that they were satisfied with using telemedicine (73.96%); that they gained an additional sense of control over their health condition due to the availability of telemedicine (52.08%); that they would support the use of telemedicine in the future (61.05%); that telemedicine increased access to care (65.63%); telemedicine was preferred over the clinic (61.46%), and that they would purchase new equipment to increase the utility of telemedicine services (54.17%). 51.04% of the respondents indicated a 10/10 level of satisfaction with telemedicine services. 48.96% indicated the strongest level of disagreement related to difficulty using telemedicine or a preference for in-person clinical appointments. Conclusions: Patients were found to have favorable perceptions of telemedicine overall. Though providers continue to recognize the benefit of face-to-face visits, their patients show an increased predilection for virtual care and telemedicine will likely remain an essential tool for providers to reach patients who would otherwise choose not to seek care.

Eye movements support memory encoding by binding distinct elements of the visual world into coherent representations. However, the role of eye movements in memory retrieval is less clear. We propose that eye movements play a functional role in retrieval by reinstating the encoding context. By overtly shifting attention in a manner that broadly recapitulates the spatial locations and temporal order of encoded content, eye movements facilitate access to, and reactivation of, associated details. Such mnemonic gaze reinstatement may be obligatorily recruited when task demands exceed cognitive resources, as is often observed in older adults. We review research linking gaze reinstatement to retrieval, describe the neural integration between the oculomotor and memory systems, and discuss implications for models of oculomotor control, memory, and aging.

Vibrational overtones in deeply bound molecules are sensitive probes for variation of the proton-to-electron mass ratio μ. In nonpolar molecules, these overtones may be driven as two-photon transitions. Here, we present procedures for experiments with O₂⁺, including state-preparation through photoionization, a two-photon probe, and detection. We calculate transition dipole moments between all X²П_g vibrational levels and those of the A²П_u excited electronic state. Using these dipole moments, we calculate two-photon transition rates and AC-Stark-shift systematics for the overtones. We estimate other systematic effects and statistical precision. Two-photon vibrational transitions in O₂⁺ provide multiple routes to improved searches for μ variation.

Viral infections, such as those caused by Herpes Simplex Virus-1 (HSV-1) and SARS-CoV-2, affect millions of people each year. However, there are few antiviral drugs that can effectively treat these infections. The standard approach in the development of antiviral drugs involves the identification of a unique viral target, followed by the design of an agent that addresses that target. Antimicrobial peptides (AMPs) represent a novel source of potential antiviral drugs. AMPs have been shown to inactivate numerous different enveloped viruses through the disruption of their viral envelopes. However, the clinical development of AMPs as antimicrobial therapeutics has been hampered by a number of factors, especially their structure as peptides. We have examined the antiviral potential of peptoid mimics of AMPs (sequence-specific N-substituted glycine oligomers). These peptoids have the distinct advantage of being insensitive to proteases, and also exhibit increased bioavailability and stability. Our results demonstrate that several peptoids exhibit potent in vitro antiviral activity against both HSV-1 and SARS-CoV-2 when incubated prior to infection. Visualization by cryo-EM shows viral envelope disruption similar to what has been observed with AMP activity against other viruses. This suggests a common or biomimetic mechanism, possibly due to the differences between the phospholipid head group makeup of viral envelopes and host cell membranes. Furthermore, we observed no cytotoxicity against primary cultures of oral epithelial cells, thus underscoring the potential of this class of molecules as safe and effective broad-spectrum antiviral agents.

Direct measurement of strain within muscle is important for understanding muscle function in health and disease. Current technology (kinematics, dynamometry, electromyography) provides limited ability to measure strain within muscle. Regional fiber orientation and length are related with active/passive strain within muscle. Currently, ultrasound imaging provides the only non-invasive means of observing regional fiber orientation within muscle during dynamic tasks. Previous attempts to automatically estimate fiber orientation from ultrasound are not adequate, often requiring manual region selection, feature engineering, providing low-resolution estimations (one angle per muscle), and deep muscles are often not attempted. Here, we propose deconvolutional neural networks (DCNN) for estimating fiber orientation at the pixel-level. Dynamic ultrasound images sequences of the calf muscles were acquired (25 Hz) from 8 healthy volunteers (4 male, ages: 25–36, median 30). A combination of expert annotation and interpolation/extrapolation provided labels of regional fiber orientation for each image. We then trained DCNNs both with and without dropout using leave one out cross-validation. Our results demonstrated robust estimation of regional fiber orientation with approximately 3° error, which was an improvement on previous methods. The methods presented here provide new potential to study muscle in disease and health.

At 12:28 UTC (8:28 PM, local time) on 15 January 2023, a shallow, moderate earthquake with a magnitude (Mw) of 4.7 and a depth of one (1) kilometer shook the northern part of Leyte Island in the central part of the Philippines. The ground shaking was felt at PHIVOLCS Earthquake Intensity Scale (PEIS) VI, (very strong) equivalent to Modified Mercalli Intensity (MMI) VI in areas along the strike of the Leyte segment of the Philippine Fault. Even though this earthquake is classified as moderate in size, significant geologic, structural, and socio-economic impacts were documented. Most of the earthquake impacts that include surface rupture, liquefaction, and mass movements are limited near the epicentral area. The earthquake produced an 8-km-long surface rupture, the first documented rupture generated by a magnitude &lt;6 along the Philippine Fault, and is unusual in other surface rupturing earthquakes worldwide. It injured 18 persons and damaged 434 residential buildings and 26 public infrastructures which amounts to about 500 thousand US dollars. Structural damages were caused by surface rupture and/or poor engineering construction practices. Analysis of the seismic waveform and recorded peak ground acceleration (PGA) suggests that the subsurface geology influenced the ground motion amplification in an area near the epicenter. Based on the hypocenter, focal mechanism solution, aftershock distribution, and actual field observation, the causative fault for this event is the northern end of the Philippine Fault – Leyte segment. Moderate in size, this earthquake emphasizes the need and importance of documenting moderate-sized earthquakes as a tool and guide for medium and long-term earthquake risk assessment and resiliency.

Repurposing previously approved drugs may fast track the route to clinic for potential senotherapeutics and improves the inefficiency of the clinical drug development pipeline. We carried out a repurposing screen of 240 clinically approved molecules in human primary dermal fibroblasts for effects on CDKN2A expression. Molecules demonstrating effects on CDKN2A expression underwent secondary screening for senescence-associated beta galactosidase (SAB) activity, based on effect size, direction and/or molecule identity. Selected molecules then underwent a more detailed assessment of senescence phenotypes including proliferation, apoptosis, DNA damage, senescence-associated secretory phenotype (SASP) expression and regulators of alternative splicing. A selection of the molecules demonstrating effects on senescence were then used in a new bioinformatic structure-function screen to identify common structural motifs. 90 molecules displayed altered CDKN2A expression at one or other dose, of which 15 also displayed effects on SAB positivity in primary human dermal fibroblasts. Of these, three were associated with increased SAB activity, and 11 with reduced activity. The female synthetic sex hormones; diethylstilboestrol, ethynyl estradiol and levonorgestrel; were all associated with a reduction in aspects of the senescence phenotype in male cells, with no effects visible in female cells. Finally, we identified that the 30 compounds that decreased CDKN2A activity the most had a common substructure linked to this function. Our results suggest that several drugs licenced for other indications may warrant exploration as future senotherapies, but that different donors and potentially different sexes may respond differently to senotherapeutic compounds. This underlines the importance of consideration of donor-related characteristics when designing drug screening platforms.

We address the problem of finding a unique graph embedding that best describes a graph's "topology". This issue is of particular interest in the chemistry of materials. Graphs that admit a tiling in 3-dimensional Euclidean space are termed tessellate, those that do not decussate. We give examples of decussate and tessellate graphs that are finite and 3-periodic. We conjecture that a graph has at most one tessellate embedding. We give reasons for considering this the default "topology" of periodic graphs.

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction scenarios in a complex river basin, under conditions of climate change. The modeling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low streamflow conditions, compared to a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high resolution climate model data from the UKCP18 project with future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of surface water abstraction of public water supply in the downstream region: maximum licensed withdraw, 50 % authorized abstractions, monthly time series with 1% increase of water use, and maximum water withdraw year based on historical records repeated every year with 1% increase of water use, to estimate the unmet demands and streamflow requirement. This modeling approach can be used in other river basins to manage scenarios of supply and demand.

Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, and muscle kinetics and kinematics, from wearable sensor data. The use of physical models for estimation of these quantities often requires many wearable devices making practical implementation more difficult. However, regression techniques may provide a viable alternative by allowing the use of a reduced number of sensors for estimating biomechanical time-series. Herein, we review 46 articles that used regression algorithms to estimate joint, segment, and muscle kinematics and kinetics. We present a high-level comparison of the many different techniques identified and discuss the implications of our findings concerning practical implementation and further improving estimation accuracy. In particular, we found that several studies report the incorporation of domain knowledge often yielded superior performance. Further, most models were trained on small datasets in which case nonparametric regression often performed best. No models were open-sourced, and most were subject-specific and not validated on impaired populations. Future research should focus on developing open-source algorithms using complementary physics-based and machine learning techniques that are validated in clinically impaired populations. This approach may further improve estimation performance and reduce barriers to clinical adoption.

We developed a set of novel machine learning algorithms with the goal of producing transparent models (i.e. understandable-by-humans) while also flexibly accounting for nonlinearity and interactions. Our methods are based on ranked sparsity, and allow for flexibility and user-control in varying the shade of the opacity of black-box machine learning methods. In this work, we put our new ranked sparsity algorithms (as implemented in our new open-source R package, sparseR) to the test in a predictive model bakeoff on a diverse set of simulated and real-world data sets from the Penn Machine Learning Benchmarks database, including both regression and classification problems. We evaluate the extent to which our new human-centered algorithms can attain predictive accuracy that rivals popular black-box approaches such as neural networks, random forests, and SVMs, while also producing more interpretable models. Using out-of-bag error as a meta-outcome, we describe the properties of data sets in which human-centered approaches can perform as well as or better than black-box approaches. We find, interpretable approaches predicted optimally or within 5% of the optimal method in most real-world data sets. We provide a strong rationale for including human-centered transparent algorithms such as ours in predictive modeling applications.

Trees provide key ecosystem services, but the health and sustainability of these plants is under increasing biotic and abiotic threat, including from the growing incidences of non-native invasive plant pests (including pathogens). The island of Ireland (Ireland and Northern Ireland) is generally accepted to have a high plant health status, in part due to its island status and because of the national and international regulations aimed at protecting plant health. To establish a baseline of the current pest threats to tree health for the island of Ireland, the literature and unpublished sources were reviewed to produce a dataset of pests of trees on the island of Ireland. The dataset contains 396 records of pests of trees on the island of Ireland, the majority of pests being arthropods and fungi, and indicating potentially more than 44 non-native pest introductions. The reliability of many (378) of the records was judged to be high, therefore the dataset provides a robust assessment of the state of pests of trees recorded on the island of Ireland. We analyse this dataset and review the history of plant pest invasions, including (i) discussion on notable native and non-native pests of trees, (ii) pest interceptions at borders and (iii) pests and climate change. The dataset establishes an important baseline for the knowledge of plant pests on the island of Ireland, and will be a valuable resource for future plant health research and policy making.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

This work investigated the isothermal holding time dependence of the densification, microstructure, weight loss and tensile properties of Fe-Mn-Si powder compacts. Elemental Fe, Mn and Si powder mixtures with a nominal composition of Fe-28Mn-3Si (in weight percent) were ball milled for 5h and subsequently pressed under a uniaxial pressure of 400 MPa. The compacted Fe-Mn-Si powder mixtures were sintered at 1200 ℃ for 0, 1, 2 and 3 h, respectively. In general, the density, weight loss and tensile properties increased with the increase of isothermal holding time. A significant increase in density, weight loss and tensile properties occurred in the compacts isothermally holding for 1 h, as compared to those with no isothermal holding. However, further extension of isothermal holding time (2 and 3 h) only played a limited role in promoting the density and tensile properties. The weight loss of the sintered compacts was mianly caused by the sublimation of Mn in Mn depletion region on the surface layer of the sintered Fe-Mn-Si compacts. The length of the Mn depletion region increased as isothermal holding time increased. A single α-Fe phase was detected on the surface of all the sintered compacts, and the locations beyond the Mn depletion region were comprised of a dual dominant γ-austenite and minor ε-martensite.

Accurate and timely testing has become an essential measure in combatting the COVID-19 global pandemic. Currently, polymerase chain reaction (PCR) based assays are the most relied on methods for SARS-CoV-2 detection. This traditional workflow involves a viral RNA extraction from the viral transport media storing nasopharyngeal swabs collected from patients, followed by PCR based detection. While accurate, this methodology is time consuming and resource heavy, causing for delays in receiving results or limited access to testing. Herein, we demonstrate a validated method for SARS-CoV-2 detection from viral transport media using a two-step, direct-to-PCR workflow revolving around shaker-mill homogenization. This method completely bypasses the extraction steps of the traditional workflow, replacing it with 30 seconds of mechanical disruption sufficient to allow for COVID-19 detection with a 96.43% sensitivity and 100% specificity when compared to traditional extraction to PCR based methods.

Introduction People are presenting with chronic musculoskeletal pain at a younger age, and many fulfil criteria for fibromyalgia. We have recently shown a strong association between fibromyalgia symptoms and autistic traits in a self-selected community population, with the relationship mediated in part by the presence of hypermobility. Many respondents also described food sensitivities and intolerances. This study explores relationships between food issues and fibromyalgia symptoms in this population Methods The study used a nonexperimental, correlational design with data collected from a volunteer sample of 442 adults (aged 18-60) who completed online self-report questionnaires assessing each of fibromyalgia symptoms (ACR criteria), autistic traits (RAADS score) and hypermobility (Beighton’s test). Subjects were also asked to record any food sensitivities, allergies, or intolerances, along with their consequences. Correlation analyses and linear regressions were used to test the relationships between these features and each of fibromyalgia, autistic traits and hypermobility. Data was analysed using parametric and non-parametric techniques to assess the strength and significance of relationships, causes of variance and the potential mediating effect of food-related symptoms in the correlation between fibromyalgia features and autistic traits Results Our self-selected community population had a mean age of 24 years and was 77% female. The prevalence of fibromyalgia, autistic traits and hypermobility was 40%, 65% and 44% respectively. Half of all subjects reported food sensitivity and 31% reported food intolerance. The incidence of food-related symptoms was higher among subjects who met criteria for fibromyalgia than those who reported autistic traits or hypermobility. Food sensitivity and food intolerance were both more significantly associated with fibromyalgia (r=0.24, p>0.001 and r=0.38, p>0.001) than with autistic traits (r=0.15, p>0.01 and r=0.17, p>0.01). Discussion This is the first community study to provide evidence for a direct association between features of fibromyalgia and reported food intolerance and sensitivity. Although self-selected, the findings in our predominantly young population suggest that gluten and lactose consumption may be associated with higher levels of musculoskeletal pain. Avoidance of these foodstuffs was commonly reported to reduce symptoms. Dietary adjustment may merit further investigation as a therapeutic modality for some patients with fibromyalgia.

Aluminum, a contentious trace element found in the environment, has been demonstrated to have harmful effects on both humans and animals. In contrast, Sempervivum tectorum, an evergreen plant, has been found to offer numerous beneficial effects for both humans and animals. Therefore, this study aims to assess the protective effect of S. tectorum on certain reproductive biomarkers in male rats exposed to aluminum. Thirty-five Wistar rats were randomly divided into five groups: NTC (no-treatment control) received distilled water; NC (negative control) received drinking water containing 1 mg/L aluminum sulfate (AS); E1 received 1 mg/L AS along with an 8% S. tectorum extract; PC (positive control) received only 8% S. tectorum extract; E2 received 1 mg/L AS for three months followed by 8% extract for one month. The study analyzed testosterone, LH, FSH, body weight, and the histological structure of the testis, epididymis, and prostate, as well as the levels of zinc, manganese, copper, and iron in these organs. Significant decreases in body weight, testis, and epididymis size were observed in the aluminum-exposed groups compared to the control, whereas these decreases were not significant in the S. tectorum-treated groups compared to the control. Aluminum exposure led to significant decreases in testosterone and LH levels, with FSH levels showing a non-significant decrease in males, which were mitigated significantly by the administration of the plant extract. Histological analysis revealed alterations in the testis, epididymis, and prostate of the AS-exposed groups, including necrosis of seminiferous tubule epithelium and Leydig cells in the testis, and basal epithelial necrosis in the epididymis and prostate. Aluminum levels increased in all organs studied, while levels of zinc, copper, iron, and manganese decreased, showing a negative and significant correlation with aluminum levels. The aqueous extract of S. tectorum demonstrated a protective effect on certain studied biomarkers in male rats affected by aluminum exposure.

Dengue is one the most significant mosquito-borne viral diseases globally, with its prevalence extending across tropical and subtropical regions, exerting a considerable financial strain on health systems. Despite decades of research leading to the development of a vaccine implemented in endemic countries, its usage remains restricted to a fraction of the population at risk of contracting dengue. Due to these limitations, there is a growing focus on research aimed at unraveling the cellular mechanisms crucial for Dengue virus (DENV) infection to pinpoint potential host targets. Multiple studies propose a pivotal role of cytoskeletal remodeling in DENV infection. Specifically, DENV alters the organization of actin to facilitate viral entry, replication, and release. In this study, we investigated the involvement of the protein c-Abl, a kinase crucial in actin dynamics, in the context of DENV infection. Our findings suggest that either silencing or pharmacological inhibition of the kinase c-Abl leads to accumulation of dengue ENV protein in vitro, associated with actin remodeling. These results illuminate cellular mechanisms that could serve as potential therapeutic alternatives for dengue management.

Transfer learning has proven to be a valuable technique for deploying machine learning models on edge devices and embedded systems. By leveraging pre-trained models and fine-tuning them on specific tasks, practitioners can effectively adapt existing models to the constraints and requirements of their application. In the process of adapting an existing model, a practitioner may make adjustments to the model architecture, including the input layers, output layers, and intermediate layers. In this study, we examine the effects of these adjustments on the runtime and energy performance of an edge processor performing inferences. Based on our observations, we make recommendations for how to adjust convolutional neural networks during transfer learning to maintain runtime performance. We observe that the Edge TPU is generally more efficient than a CPU at performing inferences on convolutional neural networks, and continues to outperform a CPU as the depth and width of the convolutional network increases. We explore multiple strategies for adjusting the input and output layers of an existing model and demonstrate important performance cliffs for practitioners to consider when modifying a convolutional neural network model.

According to Landauer’s principle, the energy of a particle may be used to record or erase N number of information bits within the thermal bath. The maximum number of information N recorded by the particle in the heat bath is found to be inversely proportional to its temperature T. If at least one bit of information is transferred from the particle to the medium, then the particle might exchange information with the medium. Therefore for at least one bit of information, the limiting mass that can carry or transform information assuming a temperature T= 2.73 K is equal to m = 4.71810-40 kg which is many orders of magnitude smaller that the masse of most of today’s elementary particles. Next, using the corresponding temperature of a graviton relic and assuming at least one bit of information the corresponding graviton mass is calculated and from that, a relation for the number of information N carried by a graviton as a function of the graviton mass mgr is derived. Furthermore, the range of information number contained in a graviton is also calculated for the given range of graviton mass as given by Nieto and Goldhaber, from which we find that the range of the graviton is inversely proportional to the information number N. Finally, treating the gravitons as harmonic oscillators in an enclosure of size R we derive the range of a graviton as a function of the cosmological parameters in the present era

This paper will discuss Data, Information, Knowledge, and Wisdom, which is commonly referred to as DIKW. The DIKW Pyramid Model that is often referenced in both academics and practitioner circles will be discussed and shown to be faulty on several levels, including. a lack of definitional agreement. A new DIKW framework will be proposed that focuses on what the DIKW elements do in the way humans think, not what they are by definition. Information as a replacement for wasted physical resources in goal-oriented tasks will be a central organizing point. The paper will move the DIKW discussion to the computer-based concept of Digital Twins (DTs) and its augmentation of how we can use DIKW to be more effective and efficient. This will especially be the case as we move to Intelligent Digital Twins (IDT) with Artificial Intelligence (AI).

By using a systems biological perspective and available literature on human social interaction, grouping, and cohesiveness, a new coherent model is proposed that integrates existing social integration and neurobiological research into a theoretical neurobiological framework of personality and social interaction. This model allows for the coherent analysis of complex social systems and interactions within them, and proposes a framework for estimating group cohesiveness and evaluating group structures in order to build and organize optimized social groups. This „Neurobiological-Associative“ model proposes two primary feedback loops, with environmental conditioning (learning) being sorted into an associative model that modulates interaction with the social environment, and which impacts the second feedback loop involving the individuals' neurobiological capacity. In this paper, the concept of neurobiological capacity is developed and based upon contemporary research on intelligence, personality, and social behavior with a focus on the oxytocin, serotonin, and dopamine systems. The basis of social exclusion and group structure is thus, expressed in the very most simple terms, neurobiological compatibility and risk assessment modulated by an internal associative model.

Existence of hybrid electric vehicles nowadays is one of the emerging technologies worldwide. Different countries are using this technology on their transportation, and nowadays, a lot of other countries are gradually adapting on using this kind of innovation in their transport system. Philippines is among these countries which aims to have a sustainable mobility by embracing the use of hybrid - electric vehicles but still lots of consumers are lacking awareness on this technology. Lack of information on the social, environmental, and economic potential benefits are among the main issues of Philippines consumers that really affect its uptake. The goal of this study was to evaluate the consumer’s perception and purchase intention on the transition of hybrid - electric vehicles for sustainable mobility and transportation here in the Philippines. It aimed to assess consumer awareness with hybrid - electric vehicles and its potential benefits to human beings in terms of social, environmental, and economic aspects. The study also gauged the impact of this perception on consumer’s purchase intention on hybrid - electric vehicles. These objectives were attained using the Descriptive Statistics and Correlation Analysis. Using these methods, the results revealed that majority of the consumers believed on the positive benefits of transitioning to hybrid - electric vehicles in terms of social, environmental, and economic aspects. This study also showed that these benefits have high impact on the consumer’s intention of buying or having a hybrid – electric vehicle. Electric vehicle is one of the most effective measure of decarbonizing the transport system. Furthermore, government and automotive businesses must strengthen their drive in spreading awareness of hybrid – electric vehicle’s benefits to consumers to further support country’s effort for development.

Considering that life on earth evolved about 3.7 billion years ago, vertebrates are young, appearing in the fossil record during the Cambrian explosion about 542 to 515 million years ago. Results from sequence analyses of genomes from bacteria, yeast, plants, invertebrates and vertebrates indicate that receptors for adrenal steroids (aldosterone, cortisol), and sex steroids (estrogen, progesterone, testosterone) also are young, with an estrogen receptor and a 3-ketosteroid receptor first appearing in basal chordates (cephalochordates: amphioxus), which are close ancestors of vertebrates. Through gene duplication and divergence of the 3-ketosteroid receptor, receptors that respond to androgens, glucocorticoids, mineralocorticoids and progestins evolved in vertebrates. Thus, an ancestral progesterone receptor and an ancestral corticoid receptor, the common ancestor of the glucocorticoid and mineralocorticoid receptors, evolved in jawless vertebrates (cyclostomes: lampreys, hagfish). This was followed by evolution of an androgen receptor, distinct glucocorticoid and mineralocorticoid receptors and estrogen receptor-α and -β in cartilaginous fishes (gnathostomes: sharks). Further evolution of mineralocorticoid signaling occurred with the evolution of aldosterone synthase in lungfish, a forerunner of terrestrial vertebrates. Adrenal and sex steroid receptors are not found in echinoderms: and hemichordates, which are ancestors in the lineage of cephalochordates and vertebrates. The evolution of steroid receptors at key nodes in the evolution of vertebrates, in which steroid receptors act as master switches to regulate differentiation, development, reproduction, immune responses, electrolyte homeostasis and stress responses, argues for an important role for steroid receptors in the evolutionary success of vertebrates, considering that the human genome contains about 22,000 genes, which is not much larger than genomes of invertebrates, such as Caenorhabditis elegans (~18,000 genes) and Drosophila (~14,000 genes).

There is much concern about disruption of endocrine physiology regulated by steroid hormones in humans, other terrestrial vertebrates and fish by industrial chemicals, such as bisphenol A, and pesticides, such as DDT. These endocrine-disrupting chemicals influence steroid-mediated physiology in humans and other vertebrates by competing with steroids for receptor binding sites, disrupting diverse responses involved in reproduction, development and differentiation. Here I discuss that due to evolution of the progesterone receptor (PR) and mineralocorticoid receptor (MR) after ray-finned fish and terrestrial vertebrates diverged from a common ancestor, each receptor evolved to respond to different steroids in ray-finned fish and terrestrial vertebrates. In elephant shark, a cartilaginous fish, ancestral to ray-finned fish and terrestrial vertebrates, both progesterone and 17,20-beta-dihydroxy-progesterone activate the PR. During the evolution of ray-finned fish and terrestrial vertebrates, the PR in terrestrial vertebrates continued responding to progesterone and evolved to weakly respond to 17,20-beta-dihydroxy-progesterone. In contrast, the physiological progestin for the PR in zebrafish and other ray-finned fish is 17,20-beta-dihydroxy-progesterone, and ray-finned fish PR responds weakly to progesterone. The MR in fish and terrestrial vertebrates also diverged to have different responses to progesterone. Progesterone is a potent agonist for elephant shark MR, zebrafish MR and other fish MRs, in contrast to progesterone’s opposite activity as an antagonist for aldosterone, the physiological mineralocorticoid for human MR. These different physiological ligands for fish and terrestrial vertebrate PR and MR need to be considered in applying data for their disruption by chemicals in fish and terrestrial vertebrates to each other.

The spillover of the terrorist activities of Boko Haram, a Nigerian jihadi group, into Cameroon’s northern region has resulted in security challenges and humanitarian activity opportunities for Christian churches. The insurgents have attacked and destroyed churches, abducted Christians, worsened Muslim-Christian relations, and caused a humanitarian crisis. Aggregately, these ensuing phenomena have adversely affected Christian churches in this region, triggering an aura of responses: coping strategies, humanitarian work among refugees, and inter-faith dialogue. These responses are predicated on Christianity’s potential as a resource for peace, compassion, and love. In this study we emphasize the role of Christian churches in dealing with the Boko Haram insurgency. It opens up with a contextualization of Boko Haram in Cameroon’s north. This is followed by an examination of the brutality meted out on Christians and church property. The final section is an examination of the spiritual, humanitarian and relief services provided by Christian churches. The paper argues that although Christian churches have suffered at the hands of Boko Haram insurgents, they have engaged in various beneficial responses underpinned by the Christian values of peace and love.

Background: The UK dairy sheep industry is relatively small but growing, particularly for cheese and yogurt products. Anecdotally, sheep milk (SM) is better tolerated by humans than cows’ milk and could have environmental as well as health benefits. All milk contains sub-micron particles called extracellular vesicles (EV) which are mainly derived from the mammary epithelium. Physiologically, milk derived EV are thought to aid development of infant immunity and the microbiome but may also have health benefits to adult humans. Methods: Using sequential ultracentrifugation vesicles of &lt;1µm (LEV) followed by &lt;200nm (sEV) were isolated from six individual sheep during mid lactation. RNA was extracted and microRNA analysed by RTqPCR for sequences previously identified in cows’ milk. Human THP-1 monocytes were differentiated into macrophages and incubated with SM-derived LEV and sEV in the presence of pro-inflammatory LPS to measure effects on secretion of the chemokine CCL-2 or in the presence of DMNQ and fluorescent dihydrorhodamine-1,2,3 to measure reactive oxygen species. Results: LEV induced an increase in ROS in both monocytes and macrophages, whilst sEV decreased DMNQ-mediated ROS in macrophages but not monocytes. Interestingly, the LEV did not induce CCL2 release, however they increased LPS-induced CCL2 secretion in monocytes but not macrophages. miR26a, miR92a, miR125b, miR155, miR223, were identified in both sEV and LEV by RT-qPCR and could be responsible for modulation of ROS and CCL2 expression. Conclusions: These findings suggest that sheep milk can influence human monocyte/macrophage responses and so is worthy of further investigation for its potential human and non-human animal health benefits.

Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV) have paved the way to accessible remote sensing tools for farmers. This paper describes the comparison of two popular off-the-shelf sUAVs: 3DR Iris and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every second for two minutes. The position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. Results showed that both sUAV performed well in both the hovering test and the rectilinear motion test. This demonstrates that both sUAVs can be used for agricultural monitoring.

Modern gastroenterology, which occupies the pages of scientific journals without alternative, began as an initiative of manufacturers of diagnostic equipment. For widespread advertising, they selected practical doctors who were not familiar with the methodology of science and superficial knowledge of physiology. This is how a group led by DeMeester arose, which in 1976 published the DeMeester score, i.e., the normal limit for esophageal pH monitoring. pH <4, less than 4% of the time per day was considered normal, i.e., it was unreasonably claimed that such reflux is physiological. This article proves that this study was carried out with numerous methodological errors, which led to an erroneous conclusion. For a long time, pH monitoring was considered the gold standard and with its help hypotheses were proposed that form the basis of modern gastroenterology. The article proves the fallacy of 13 hypotheses, which are presented as theories. Numerous articles using pH monitoring have publicized this method. Practitioners became "great scientists", equipment manufacturers became successful businessmen. Over time, they found other groups of practitioners to promote devices for impedance ph monitoring, high-resolution manometry, and many others. At the same time, a network of reviewers who believe in the infallibility of the luminaries do not allow studies that contradict their faith to be published. Thus, fundamental science was destroyed, which alone could assess the harm of false research both for science and for patients. Conclusion This study provides a list of hypotheses, that were previously considered theories, but since scientific evidence has proven these assumptions to be false, they should be excluded from subsequent use and citation.

Statistical modeling lies at the heart of product design and development throughout numerous engineering disciplines, especially since processing large amounts of data has become increasingly ubiquitous. While mathematical statistics provide elegant guidance pertaining to the question of whether or not some particular underlying modeling assumptions are justified and appropriate, when pursuing a more comprehensive assessment of product design and development other considerations often increase in significance. Therefore, we will examine and analyze the tedious interactions and implications of statistical modeling choices and product liability exposure. To the best of our knowledge, this paper is the first to draw attention to and explore some often overlooked or oversimplified dangers and pitfalls that enter the equation when product design heavily relies on statistical modeling. In particular, through a diligent analysis of both statistical and legal aspects we will explore how statistically optimal procedures may yield far from optimal outcomes in terms of product liability when applied to actual real life problems and why suboptimal nonparametric or robust approaches may constitute better alternatives.

The HER2 overexpression occurs in 10–20% of breast cancer patients. HER2+ tumors are characterized by increase in Ki67, early relapse and increased metastasis. There is little known about factors influencing early stages of HER2- tumorigenesis and diagnostic markers. Previously, it was shown that deletion of NEDD9 in mouse models of HER2 cancer interferes with tumor growth, but the role of NEDD9 upregulation is currently unexplored. We report that NEDD9 is overexpressed in a significant subset of HER2+ breast cancers and correlates with limited response to anti-HER2 therapy. To investigate the mechanisms through which NEDD9 influences HER2-dependent tumorigenesis, we generated MMTV-Cre-NEDD9 transgenic mice. The analysis of mammary glands shows extensive ductal epithelium hyperplasia, increased branching, and terminal end bud expansion. The addition of oncogene Erbb2 (neu) leads to development of early hyperplastic benign lesions earlier (~16 weeks) with a significantly shorter latency than the control mice. Similarly, NEDD9 upregulation in MCF10A-derived acini leads to hyperplasia like DCIS. This phenotype is associated with activation of ERK1/2 and AURKA kinases leading to an increased proliferation of luminal cells. These findings indicate that NEDD9 is setting permissive conditions for HER2-induced tumorigenesis, thus identifying this protein as a potential diagnostic marker for early detection.

Problem solving is one of the most important components of the human cognition that affects for ages the progress of the human society. Mathematical modelling is a special type of problem solving concerning problems related to science or everyday life situations. The present study is a review of the author’s earlier works on problem solving and mathematical modelling from the scope of Education. Its real goal is that it presents in a systematic way and in a few pages only the results of many years research on the subject. This helps the reader to get a comprehensive idea about a very important topic belonging to the core of Mathematics Education, which is very useful to those wanting to study deeper the subject and get directions for further research in the area.

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more “clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient’s cancer cells. Achilles Therapeutics is currently the only company specifically targeting clonal mutations. However, they are doing so with tumor-derived T cells. To address the potential limitations of immunotherapy, I have devised another approach for exploiting clonal mutations, which I call “Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement” (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

SETMAR is a protein lysine methyltransferase that is involved in several DNA processes, including DNA repair via the non-homologous end joining (NHEJ) pathway, regulation of gene expression, illegitimate DNA integration, and DNA decatenation. However, SETMAR is an atypical protein lysine methyltransferase since in anthropoid primates, the SET domain is fused to an inactive DNA transposase. The presence of the DNA transposase domain confers to SETMAR a DNA binding activity towards the remnants of its transposable element, which has resulted in the emergence of a gene regulatory function. Both the SET and the DNA transposase domains are involved in the different cellular roles of SETMAR, indicating the presence of novel and specific functions in anthropoid primates. In addition, SETMAR is dysregulated in different types of cancer, indicating a potential pathological role. While some light has been shed on SETMAR functions, more research and new tools are needed to better understand the cellular activities of SETMAR and to investigate the therapeutic potential of SETMAR.

The conventional explanation of delayed-choice experiments seems to violate our causal intuition. This apparent violation is caused by a misinterpretation of the conventional formulation of quantum mechanics. I reanalyze these experiments using advanced and time-symmetric formulations of quantum mechanics. All three formulations give the same experimental predictions, but the advanced and time-symmetric formulations violate our causal intuition that effects only happen after causes. I explore reasons why our causal intuition may be wrong at the quantum level. I also suggest how conventional causation might be recovered in the classical limit, and speculate on cosmological boundary conditions.

Stellar heated gas and dust makes a significant entropic/information energy contribution to the universe. At temperatures ~10⁷ the ~10⁸⁶ bits are equivalent to ~10⁷⁰J, equivalent to the energy equivalence of the universe’s ~10⁵³ kg ordinary baryon matter. A survey of stellar mass density measurements shows this dark energy contribution has a constant energy density that effectively mimics a cosmological constant over the redshift range z<1.35. The measurable difference between this information energy and a true cosmological constant is small, with a maximum difference of <2% in Hubble parameter at z~2. As information energy is significant and co-located with hot baryons it produces gravitational effects that resemble dark matter. Information energy is shown to be consistent with the dark matter effects observed in clusters of colliding galaxies (e.g. Bullet Cluster), with dark matter location specified by baryon location and strongest in regions of highest luminosity / temperature. The dark matter fraction measured in galaxy surveys more closely fits an information energy explanation than the fraction expected in the standard ɅCDM model. Information energy provides a solution to the cosmological coincidence problem and also would allow the cosmological constant to take the preferred zero value.

This work presents a numerical study on atmospheric sound propagation over rough water surfaces. A method to generate pseudorandom sea profiles consistent with sea wave spectra is presented. The proposed method is suited to capture the logarithmic nature of the energy distribution of the waves. Sea profiles representing fully developed seas for sea states 2, 3, 4 and 5 are generated from the Elfouhaily et al. (ECKV) sea wave spectra. Excess attenuation caused by refraction and surface roughness is predicted with a parabolic equation (PE) solver. A novel method to estimate equivalent effective impedance based on PE predictions at different sea states is presented. Parametric expressions using acoustic frequency and significant wave height are developed for effective surface impedances. In this work, sea surface roughness is on a scale comparable to the acoustic wavelength. Under this condition, the acoustic scattering is primarily incoherent. This work shows the limitations of using an equivalent surface impedance in such incoherent scattering cases.

Radiosensitivity, the susceptibility of cells to ionizing radiation, plays a critical role in understanding the effects of radiation therapy and exposure on tissue health and regeneration. Identifying characteristics that predict how a patient may respond to radiotherapy enables clinicians to maximize the therapeutic window. Limited clinical data suggested a difference in male and female radiotherapy outcomes. Radiotherapy for gastrointestinal malignancy is still a challenge due to intestinal sensitivity to radiation toxicity. In this manuscript we demonstrated sex specific differences in intestinal epithelial radiosensitivity. In mice model of abdominal irradiation, we observed significant increase in oxidative stress and injury in male compared to female. Lgr5+ve intestinal stem cells from male mice showed higher sensitivity to radiation induced toxicity. However, sex specific differences in intestinal radiosensitivity are not dependent on sex hormone as we demonstrated similar sex specific radiosensitivity differences in pediatric mice. In ex-vivo study we found that human patient derived intestinal organoid (PID) derived from male showed higher sensitivity to irradiation compared to female as evident from loss of budding crypt, organoid size, and membrane integrity. Transcriptomic analysis of human Lgr5+ intestinal stem cells suggested radiation induced upregulation of mitochondrial oxidative metabolism in male compared to female possible mechanism for radiosensitivity differences.

The use of convolutional neural networks (CNNs) in image classification has become the standard method of approaching computer vision problems. Here we apply pre-trained networks to classify images of non-breaking, plunging and spilling breaking waves. The CNNs are used as basic feature extractors and a classifier is then trained on top of these networks. The dynamic nature of breaking waves is exploited by using image sequences to gain extra information and improve the classification results. We also see improved classification performance in using pre-computed image features such as the optical flow between image pairs. The inclusion of the dynamic information improves the classification between breaking wave classes. We also provide corrections to the methodology from the article from which the data originates to achieve a more accurate assessment of performance.

NMR spectral datasets, especially in systems with limited samples, can be difficult to interpret if they contain multiple chemical components (phases, polymorphs, molecules, crystals, glasses, etc…) and the possibility of overlapping resonances. In this paper, we benchmark several blind source separation techniques for analysis of NMR spectral datasets containing negative intensity. For benchmarking purposes, we generated a large synthetic datasbase of quadrupolar solid-state NMR-like spectra that model spin-lattice T1 relaxation or nutation tip/flip angle experiments. Our benchmarking approach focused exclusively on the ability of blind source separation techniques to reproduce the spectra of the underlying pure components. In general, we find that FastICA (Fast Independent Component Analysis), SIMPLISMA (SIMPLe-to-use-Interactive Self-modeling Mixture Analysis), and NNMF (Non-Negative Matrix Factorization) are top-performing techniques. We demonstrate that dataset normalization approaches prior to blind source separation do not considerably improve outcomes. Within the range of noise levels studied, we did not find drastic changes to the ranking of techniques. The accuracy of FastICA and SIMPLISMA degrades quickly if excess (unreal) pure components are predicted. Our results indicate poor performance of SVD (Singular Value Decomposition) methods, and we propose alternative techniques for matrix initialization. The benchmarked techniques are also applied to real solid state NMR datasets. In general, the recommendations from the synthetic datasets agree with the recommendations and results from the real data analysis. The discussion provides some additional recommendations for spectroscopists applying blind source separation to NMR datasets, and for future benchmark studies. Applications of blind source separation to NMR datasets containing negative intensity may be especially useful for understanding complex and disordered systems with limited samples and mixtures of chemical components.

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. While most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.

Flaring in the SS 433 microquasar is dominated by outbursts from material at distances from the centre of mass of the binary system comparable to the separation of the two components. This note completes a demonstration that ejected plasma leaves the system in the region of the L_2 point, there overflowing the outer Roche lobe and giving rise to a spiral structure as it leaves the system as part of the local environment.

Adeno-associated viral (AAV) vectors can be used for gene delivery. AAV.CAP-Mac was recently developed; it can cross the blood-brain barrier and transduce cells throughout the CNS. However, some brain regions were not transduced in adult rhesus monkeys. Additionally, AAV vectors can only package 5 kb of DNA. Also, AAV vectors may be genotoxic and cytotoxic, especially at high doses. Finally, AAV vectors are very expensive to produce at sufficiently high titers for treatment. Off-the-shelf cell-based delivery systems wherein the cells can infiltrate the target tissue and be hyper-motile would be ideal. Also, mRNA-based gene editing would be a transient treatment, and thus be much safer.

Lipofuscin is indigestible garbage that accumulates in the autophagic vesicles and cytosol of post-mitotic cells with age. Drs. Brunk and Terman postulated that lipofuscin accumulation is the main or at least a major driving factor in aging. They even posited that the evolution of memory is the reason why we get lipofuscin at all, as stable synaptic connections must be maintained over time, meaning that the somas of neurons must also remain in the same locale. In other words, they cannot dilute out their garbage over time through cell division. Mechanistically, their position certainly makes sense given that rendering a large percentage of a post-mitotic cell’s lysosomes useless must almost certainly negatively affect that cell and the surrounding microenvironment. It may be the case that lipofuscin accumulation is the main issue with regard to current age-related disease. Degradation in situ may be an insurmountable task currently. However, a method of systemic lipofuscin removal is discussed herein.

This review covers some of the central relationships between artificial intelligence, psychology, and economics through the lens of information theory, specifically focusing on formal models of decision-theory. In doing so we look at a particular approach that each field has adopted and how information theory has informed the development of the ideas of each field. A key theme is expected utility theory, its connection to information theory, and the Bayesian approach to decision-making and forms of (bounded) rationality. What emerges from this review is a broadly unified formal perspective derived from three very different starting points that reflect the unique principles of each field. Each of the three approaches reviewed can, in principle at least, be implemented in a computational model in such a way that, with sufficient computational power, they could be compared with human abilities in complex tasks. However, a central critique that can be applied to all three approaches was first put forward by Savage in {\it The Foundations of Statistics} and recently brought to the fore by the economist Binmore: Bayesian approaches to decision-making work in what Savage called `small worlds' but cannot work in `large worlds'. This point, in various different guises, is central to some of the current debates about the power of artificial intelligence and its relationship to human-like learning and decision-making. Recent work on artificial intelligence has gone some way to bridging this gap but significant questions still need to be answered in all three fields in order to make progress on these problems.

Here we present a fast and highly scalable community structure preserving network module detection that recursively integrates graph sparsification and clustering. Our algorithm, called SparseClust, participated in the most recent DREAM community challenge on disease module identification, an open competition to comprehensively assess module identification methods across a wide range of biological networks.

Research into the causes of neurotoxicity in Alzheimer’s Dementia (AD) has focused on neurofibrillary tangles and beta amyloid (Aβ) plaques. This paper proposes the heterodox theory that these hallmarks of AD are the visible effects, not direct causes of neuronal necrosis. Rather AD results from a combination of age-induced, disproportional decline in physiological support for aerobic metabolism, and dysregulation of the sleep cycle processes. The hypothesis is that the decimation of neurons in AD results from a combination of neurotoxicity and increased apoptosis caused by: 1. direct damage from toxic waste products of anaerobic glycolysis due to a progressive decline in the capacity of neurons to perform oxidative phosphorylation (OXPHOS) and an increased reliance on anaerobic glycolysis to meet metabolic needs; 2. impaired cellular repair and effluent release due to dysregulation of non-rapid eye movement (NREM) sleep allowing damage to cell membranes and synaptic junctions to accumulate inducing a chronic inflammatory response; 3. indirect damage from products produced by inflammatory reaction to toxic metabolites; 4. neuronal apoptosis from the AβPP-mediated pathway due to the age-induced decline of growth hormone (GH), GH-releasing hormone (GHRH) and insulin-like growth factor (IGF).

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

Through the use of a simplified model of consciousness this paper illustrates the symptoms of schizophrenia linked to neocortical structures and functions. It makes the case that the bewildering and varied presentation of symptoms in schizophrenia can be analyzed and explained using such models. The model is used to illustrate the central thesis of the paper, that schizophrenia is a disorder of neurogenesis which leads to progressive neurochemical, functional and neurophysiological changes that create the characteristic behaviors of the disease.

Several methods of processing wood into strong, durable products for the construction industry provide transformative opportunities to substitute for less sustainable building materials. Carbon storage is a further advantage, with the added possibility of combustion for bioenergy at end of life. Intense research activity in this area is expected to open up new markets for wood fiber during the lifetime of trees now being planted. Here, wood-derived materials are classified according to the particle size, from metres to nanometres, into which the wood is fragmented before reconstitution. Materials made by densifying or chemically modifying solid wood with no fragmentation are already in production for exterior doors, window frames and cladding, with improved uniformity and stability compared with unmodified wood. Pre-commercial developments promise further gains in durability and strength. Emerging developments extend these process technologies to wood that has been chipped or stranded or pulped, retaining the above advantages over raw timber for weather-facing applications and adding processability by moulding or extrusion. Crucially, the raw material does not then need to be sawn timber but can be bioenergy-grade wood biomass. This will facilitate afforestation strategies that combine the aims of carbon sequestration and biodiversity.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

This article challenges the assumption that journals and peer review are essential for developing, evaluating and disseminating scientific and other academic knowledge. It suggests a more flexible ecosystem, and examines some of the possibilities this might facilitate. The market for academic outputs should be opened up by encouraging the separation of the dissemination service from the evaluation service. Publishing research in subject-specific journals encourages compartmentalising research into rigid categories. The dissemination of knowledge would be better served by an open access, web-based repository system encompassing all disciplines. There would then be a role for organisations to assess the items in this repository to help users find relevant, high-quality work. There could be a variety of such organisations which could enable reviews from peers to be supplemented with evaluation by non-peers from a variety of different perspectives: user reviews, statistical reviews, reviews from the perspective of different disciplines, and so on. This should reduce the inevitably conservative influence of relying on two or three peers, and make the evaluation system more critical, multi-dimensional and responsive to the requirements of different audience groups, changing circumstances, and new ideas. Non-peer review might make it easier to challenge dominant paradigms, and expanding the potential audience beyond a narrow group of peers might encourage the criterion of simplicity to be taken more seriously - which is essential if human knowledge is to continue to progress.

This paper discusses recent developments in creep, over a wide range of temperature, that mqy change our understanding of creep. The five-power law creep exponent (3.5 to 7) has never been explained in fundamental terms. The best the scientific community has done is to develop a natural three power-law creep equation that falls short of rationalizing the higher stress exponents that are typically five. This inability has persisted for many decades. Computational work examining the stress-dependence of the climb rate of edge dislocations we may rationalize the phenomenological creep equations. Harper-Dorn creep, “discovered” over 60 years ago has been immersed in controversy. Some investigators have insisted that a stress exponent of one is reasonable. Others believe that the observation of a stress exponent of one is a consequence of dislocation network frustration. Others believe the stress exponent is artificial due to the inclusion of restoration mechanisms such as dynamic recrystallization or grain growth that is not of any consequence in the five power-law regime. Also, the experiments in the Harper-Dorn regime, which accumulate strain very slowly (sometimes over a year) may not have attained a true steady state. New theories suggest that absence or presence of Harper-Dorn may be a consequence of the initial dislocation density. Novel experimental work suggests that power-law breakdown may be a consequence of a supersaturation of vacancies which increase self-diffusion.